Mixed crop-livestock systems: an economic and environmental-friendly way of farming?

PubMed

Ryschawy, J; Choisis, N; Choisis, J P; Joannon, A; Gibon, A

2012-10-01

Intensification and specialisation of agriculture in developed countries enabled productivity to be improved but had detrimental impacts on the environment and threatened the economic viability of a huge number of farms. The combination of livestock and crops, which was very common in the past, is assumed to be a viable alternative to specialised livestock or cropping systems. Mixed crop-livestock systems can improve nutrient cycling while reducing chemical inputs and generate economies of scope at farm level. Most assumptions underlying these views are based on theoretical and experimental evidence. Very few assessments of their environmental and economic advantages have nevertheless been undertaken in real-world farming conditions. In this paper, we present a comparative assessment of the environmental and economic performances of mixed crop-livestock farms v. specialised farms among the farm population of the French 'Coteaux de Gascogne'. In this hilly region, half of the farms currently use a mixed crop-livestock system including beef cattle and cash crops, the remaining farms being specialised in either crops or cattle. Data were collected through an exhaustive survey of farms located in our study area. The economic performances of farming systems were assessed on 48 farms on the basis of (i) overall gross margin, (ii) production costs and (iii) analysis of the sensitivity of gross margins to fluctuations in the price of inputs and outputs. The environmental dimension was analysed through (i) characterisation of farmers' crop management practices, (ii) analysis of farm land use diversity and (iii) nitrogen farm-gate balance. Local mixed crop-livestock farms did not have significantly higher overall gross margins than specialised farms but were less sensitive than dairy and crop farms to fluctuations in the price of inputs and outputs considered. Mixed crop-livestock farms had lower costs than crop farms, while beef farms had the lowest costs as they are grass-based systems. Concerning crop management practices, our results revealed an intensification gradient from low to high input farming systems. Beyond some general trends, a wide range of management practices and levels of intensification were observed among farms with a similar production system. Mixed crop-livestock farms were very heterogeneous with respect to the use of inputs. Nevertheless, our study revealed a lower potential for nitrogen pollution in mixed crop-livestock and beef production systems than in dairy and crop farming systems. Even if a wide variability exists within system, mixed crop-livestock systems appear to be a way for an environmental and economical sustainable agriculture.

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.

Developing trap cropping systems for effective organic management of key insect pests of cucurbit crops (IPM)

USDA-ARS?s Scientific Manuscript database

Trap cropping is a behaviorally-based pest management approach that functions by planting highly attractive plants next to a higher value crop so as to attract the pest to the trap crop plants, thus preventing or making less likely the arrival of the pest to the main crop (= cash crop). In 2012, a s...

A center for commercial development of space: Real-time satellite mapping. Remote sensing-based agricultural information expert system

NASA Technical Reports Server (NTRS)

Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.

1989-01-01

The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.

Effects of crop rotation on properties of a Vietnam clay soil under rice-based cropping systems in small-scale farmers' fields

USDA-ARS?s Scientific Manuscript database

In tropical deltas, intensive monocultures with three rice crops per year have been the standard for decades. In recent years, though, rice-based rotations with one or more upland crops per year are being adopted by several farmers. Their trends of increasing grain yields raise the question whether ...

Prioritizing stream types according to their potential risk to receive crop plant material--A GIS-based procedure to assist in the risk assessment of genetically modified crops and systemic insecticide residues.

PubMed

Bundschuh, Rebecca; Kuhn, Ulrike; Bundschuh, Mirco; Naegele, Caroline; Elsaesser, David; Schlechtriemen, Ulrich; Oehen, Bernadette; Hilbeck, Angelika; Otto, Mathias; Schulz, Ralf; Hofmann, Frieder

2016-03-15

Crop plant residues may enter aquatic ecosystems via wind deposition or surface runoff. In the case of genetically modified crops or crops treated with systemic pesticides, these materials may contain insecticidal Bt toxins or pesticides that potentially affect aquatic life. However, the particular exposure pattern of aquatic ecosystems (i.e., via plant material) is not properly reflected in current risk assessment schemes, which primarily focus on waterborne toxicity and not on plant material as the route of uptake. To assist in risk assessment, the present study proposes a prioritization procedure of stream types based on the freshwater network and crop-specific cultivation data using maize in Germany as a model system. To identify stream types with a high probability of receiving crop materials, we developed a formalized, criteria-based and thus transparent procedure that considers the exposure-related parameters, ecological status--an estimate of the diversity and potential vulnerability of local communities towards anthropogenic stress--and availability of uncontaminated reference sections. By applying the procedure to maize, ten stream types out of 38 are expected to be the most relevant if the ecological effects from plant-incorporated pesticides need to be evaluated. This information is an important first step to identifying habitats within these stream types with a high probability of receiving crop plant material at a more local scale, including accumulation areas. Moreover, the prioritization procedure developed in the present study may support the selection of aquatic species for ecotoxicological testing based on their probability of occurrence in stream types having a higher chance of exposure. Finally, this procedure can be adapted to any geographical region or crop of interest and is, therefore, a valuable tool for a site-specific risk assessment of crop plants carrying systemic pesticides or novel proteins, such as insecticidal Bt toxins, expressed in genetically modified crops. Copyright © 2015 Elsevier B.V. All rights reserved.

The century experiment: the first twenty years of UC Davis' Mediterranean agroecological experiment.

PubMed

Wolf, Kristina M; Torbert, Emma E; Bryant, Dennis; Burger, Martin; Denison, R Ford; Herrera, Israel; Hopmans, Jan; Horwath, Will; Kaffka, Stephen; Kong, Angela Y Y; Norris, R F; Six, Johan; Tomich, Thomas P; Scow, Kate M

2018-02-01

The Century Experiment at the Russell Ranch Sustainable Agriculture Facility at the University of California, Davis provides long-term agroecological data from row crop systems in California's Central Valley starting in 1993. The Century Experiment was initially designed to study the effects of a gradient of water and nitrogen availability on soil properties and crop performance in ten different cropping systems to measure tradeoffs and synergies between agricultural productivity and sustainability. Currently systems include 11 different cropping systems-consisting of four different crops and a cover crop mixture-and one native grass system. This paper describes the long-term core data from the Century Experiment from 1993-2014, including crop yields and biomass, crop elemental contents, aerial-photo-based Normalized Difference Vegetation Index data, soil properties, weather, chemical constituents in irrigation water, winter weed populations, and operational data including fertilizer and pesticide application amounts and dates, planting dates, planting quantity and crop variety, and harvest dates. This data set represents the only known long-term set of data characterizing food production and sustainability in irrigated and rainfed Mediterranean annual cropping systems. There are no copyright restrictions associated with the use of this dataset. © 2018 by the Ecological Society of America.

Spring wheat production and associated pests in conventional and diversified cropping systems in north central Montana

USDA-ARS?s Scientific Manuscript database

Producers in the northern Plains are diversifying and intensifying traditional wheat-based cropping systems by reducing summer fallow and including legume and oilseed crops. This study examined the influence of diversification and intensification on spring wheat yield and quality, and associated ins...

Integrating sheep grazing into cereal-based crop rotations: spring wheat yields and weed communities

USDA-ARS?s Scientific Manuscript database

Crop diversification and integration of livestock into cropping systems may improve the economic and environmental sustainability of agricultural systems. However, few studies have examined the integration of these practices in the semiarid areas of the Northern Great Plains (NGP). A 3-yr experiment...

Direct and indirect impacts of crop-livestock organization on mixed crop-livestock systems sustainability: a model-based study.

PubMed

Sneessens, I; Veysset, P; Benoit, M; Lamadon, A; Brunschwig, G

2016-11-01

Crop-livestock production is claimed more sustainable than specialized production systems. However, the presence of controversial studies suggests that there must be conditions of mixing crop and livestock productions to allow for higher sustainable performances. Whereas previous studies focused on the impact of crop-livestock interactions on performances, we posit here that crop-livestock organization is a key determinant of farming system sustainability. Crop-livestock organization refers to the percentage of the agricultural area that is dedicated to each production. Our objective is to investigate if crop-livestock organization has both a direct and an indirect impact on mixed crop-livestock (MC-L) sustainability. In that objective, we build a whole-farm model parametrized on representative French sheep and crop farming systems in plain areas (Vienne, France). This model permits simulating contrasted MC-L systems and their subsequent sustainability through the following indicators of performance: farm income, production, N balance, greenhouse gas (GHG) emissions (/kg product) and MJ consumption (/kg product). Two MC-L systems were simulated with contrasted crop-livestock organizations (MC20-L80: 20% of crops; MC80-L20: 80% of crops). A first scenario - constraining no crop-livestock interactions in both MC-L systems - permits highlighting that crop-livestock organization has a significant direct impact on performances that implies trade-offs between objectives of sustainability. Indeed, the MC80-L20 system is showing higher performances for farm income (+44%), livestock production (+18%) and crop GHG emissions (-14%) whereas the MC20-L80 system has a better N balance (-53%) and a lower livestock MJ consumption (-9%). A second scenario - allowing for crop-livestock interactions in both MC20-L80 and MC80-L20 systems - stated that crop-livestock organization has a significant indirect impact on performances. Indeed, even if crop-livestock interactions permit improving performances, crop-livestock organization influences the capacity of MC-L systems to benefit from crop-livestock interactions. As a consequence, we observed a decreasing performance trade-off between MC-L systems for farm income (-4%) and crop GHG emissions (-10%) whereas the gap increases for nitrogen balance (+23%), livestock production (+6%) - MJ consumption (+16%) - GHG emissions (+5%) and crop MJ consumption (+5%). However, the indirect impact of crop-livestock organization doesn't reverse the trend of trade-offs between objectives of sustainability determined by the direct impact of crop-livestock organization. As a conclusion, crop-livestock organization is a key factor that has to be taken into account when studying the sustainability of mixed crop-livestock systems.

Farm-scale costs and returns for second generation bioenergy cropping systems in the US Corn Belt

NASA Astrophysics Data System (ADS)

Manatt, Robert K.; Hallam, Arne; Schulte, Lisa A.; Heaton, Emily A.; Gunther, Theo; Hall, Richard B.; Moore, Ken J.

2013-09-01

While grain crops are meeting much of the initial need for biofuels in the US, cellulosic or second generation (2G) materials are mandated to provide a growing portion of biofuel feedstocks. We sought to inform development of a 2G crop portfolio by assessing the profitability of novel cropping systems that potentially mitigate the negative effects of grain-based biofuel crops on food supply and environmental quality. We analyzed farm-gate costs and returns of five systems from an ongoing experiment in central Iowa, USA. The continuous corn cropping system was most profitable under current market conditions, followed by a corn-soybean rotation that incorporated triticale as a 2G cover crop every third year, and a corn-switchgrass system. A novel triticale-hybrid aspen intercropping system had the highest yields over the long term, but could only surpass the profitability of the continuous corn system when biomass prices exceeded foreseeable market values. A triticale/sorghum double cropping system was deemed unviable. We perceive three ways 2G crops could become more cost competitive with grain crops: by (1) boosting yields through substantially greater investment in research and development, (2) increasing demand through substantially greater and sustained investment in new markets, and (3) developing new schemes to compensate farmers for environmental benefits associated with 2G crops.

Effects of dynamic agricultural decision making in an ecohydrological model

NASA Astrophysics Data System (ADS)

Reichenau, T. G.; Krimly, T.; Schneider, K.

2012-04-01

Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop distribution and constant management. Results show that the influence of the modeled dynamic management adaptation on variables like transpiration, carbon uptake, or nitrate leaching from the vadose zone is stronger than the influence of a dynamic choice of crops. Climate change was found to have a stronger impact on this modeled choice of crops than the agro-political framework. These results suggest that scenario studies in areas with a large share of arable land should take into account management adaptations to changing climate.

Perspectives on genetically modified crops and food detection.

PubMed

Lin, Chih-Hui; Pan, Tzu-Ming

2016-01-01

Genetically modified (GM) crops are a major product of the global food industry. From 1996 to 2014, 357 GM crops were approved and the global value of the GM crop market reached 35% of the global commercial seed market in 2014. However, the rapid growth of the GM crop-based industry has also created controversies in many regions, including the European Union, Egypt, and Taiwan. The effective detection and regulation of GM crops/foods are necessary to reduce the impact of these controversies. In this review, the status of GM crops and the technology for their detection are discussed. As the primary gap in GM crop regulation exists in the application of detection technology to field regulation, efforts should be made to develop an integrated, standardized, and high-throughput GM crop detection system. We propose the development of an integrated GM crop detection system, to be used in combination with a standardized international database, a decision support system, high-throughput DNA analysis, and automated sample processing. By integrating these technologies, we hope that the proposed GM crop detection system will provide a method to facilitate comprehensive GM crop regulation. Copyright © 2015. Published by Elsevier B.V.

Economic assessment of conventional and conservation tillage practices in different wheat-based cropping systems of Punjab, Pakistan.

PubMed

Shahzad, Muhammad; Hussain, Mubshar; Farooq, Muhammad; Farooq, Shahid; Jabran, Khawar; Nawaz, Ahmad

2017-11-01

Wheat productivity and profitability is low under conventional tillage systems as they increase the production cost, soil compaction, and the weed infestation. Conservation tillage could be a pragmatic option to sustain the wheat productivity and enhance the profitability on long term basis. This study was aimed to evaluate the economics of different wheat-based cropping systems viz. fallow-wheat, rice-wheat, cotton-wheat, mung bean-wheat, and sorghum-wheat, with zero tillage, conventional tillage, deep tillage, bed sowing (60/30 cm beds and four rows), and bed sowing (90/45 cm beds and six rows). Results indicated that the bed sown wheat had the maximum production cost than other tillage systems. Although both bed sowing treatments incurred the highest production cost, they generated the highest net benefits and benefit: cost ratio (BCR). Rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) had the highest net income (4129.7 US$ ha -1 ), BCR (2.87), and marginal rate of return compared with rest of the cropping systems. In contrast, fallow-wheat cropping system incurred the lowest input cost, but had the least economic return. In crux, rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) was the best option for getting the higher economic returns. Moreover, double cropping systems within a year are more profitable than sole planting of wheat under all tillage practices.

Crop and varietal diversification of rainfed rice based cropping systems for higher productivity and profitability in Eastern India

PubMed Central

Panda, B. B.; Raja, R.; Singh, Teekam; Tripathi, R.; Shahid, M.; Nayak, A. K.

2017-01-01

Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June–September) and land leftovers fallow after rice harvest in the post-rainy season (November–May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November–March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield. PMID:28437487

Crop and varietal diversification of rainfed rice based cropping systems for higher productivity and profitability in Eastern India.

PubMed

Lal, B; Gautam, Priyanka; Panda, B B; Raja, R; Singh, Teekam; Tripathi, R; Shahid, M; Nayak, A K

2017-01-01

Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June-September) and land leftovers fallow after rice harvest in the post-rainy season (November-May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November-March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield.

Climate Change and Dryland Wheat Systems in the US Pacific Northwest

NASA Astrophysics Data System (ADS)

Stockle, C.; Karimi, T.; Huggins, D. R.; Nelson, R.

2015-12-01

A regional assessment of historical and future yields, and components of the water, nitrogen, and carbon soil balance of dryland wheat-based cropping systems in the US Pacific Northwest is being conducted (Regional Approaches to Climate Change project funded by USDA-NIFA). All these elements intertwines and are important to understand the future of these systems in the region. A computer simulation methodology was used based on the CropSyst model and historic and projected daily weather data downscaled to a 4x4 km grid including 14 general circulation models (GCMs) and two representative concentration pathways of future atmospheric CO2 (RCP 4.5 and RCP 8.5). The study region was divided in 3 agro-ecological zones (AEZ) based on precipitation amount: low (<300 mm/year), intermediate (300-460 mm/year) and high (>460 mm/year), with a change from crop-fallow, to transition fallow (crop-crop-fallow) to annual cropping, respectively. Typical wheat-based rotations included winter wheat (WW)-Summer fallow (SF) for the low AEZ, WW-spring wheat (SW)-SF for the intermediate AEZ, and WW-SW-spring peas for the high AEZ, all under conventional and no tillage management. Alternative systems incorporating canola were also evaluated. Results suggest that, in most cases, these dryland systems may fare well in the future (31-year periods centered around 2030, 2050, and 2070), with potential gains in productivity. Also, a trend towards increased fallow in the intermediate AEZ appears possible for higher productivity, and the inclusion of less water demanding crops may help sustain cropping intensity. Uncertainties in these projections arise from large discrepancies among climate models regarding the warming rate, compounded by different possible future CO2 emission scenarios, the degree of change in frequency and severity of extreme events and associated potential damages to crop canopies due to cold weather and grain set reduction due to extreme heat events. Furthermore, there is little understanding of the impact of climate change on pests, diseases and weeds that could affect crop production and management costs. Finally, there is also uncertainty on the speed of technological innovation allowing producers to adapt to changing conditions.

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Forward chaining method on diagnosis of diseases and pests corn crop

NASA Astrophysics Data System (ADS)

Nurlaeli, Subiyanto

2017-03-01

Integrated pest management should be done to control the explosion of plants pest and diseases due to climate change is uncertain. This paper is a present implementation of the forward chaining method in the diagnosis diseases and pests of corn crop to help farmers/agricultural facilitators in getting knowledge about disease and pest corn crop. Forward chaining method as inference engine is used to get a disease/pest that attacks the corn crop based on symptoms. The forward chaining method works based on the fact that there is to get a conclusion. Fact in this system derived from the symptoms of the selected user is matched with the premise on every rule in the knowledge base. A rule that matches the facts to be executed to be the conclusion in the form of diagnosis. This validation using 36 data test, 32 data showed the same diagnostic results between systems with an expert. So, the percentage accuracy of results of diagnosis using data test of 88%. Finally, it can be concluded that the diagnosis system of diseases and pests corn crop can be used to help farmers/agricultural facilitators to diagnose diseases and pests corn crop.

Old Dog New Tricks: Use of Point-based Crop Models in Grid-based Regional Assessment of Crop Management Technologies Impact on Future Food Security

NASA Astrophysics Data System (ADS)

Koo, J.; Wood, S.; Cenacchi, N.; Fisher, M.; Cox, C.

2012-12-01

HarvestChoice (harvestchoice.org) generates knowledge products to guide strategic investments to improve the productivity and profitability of smallholder farming systems in sub-Saharan Africa (SSA). A keynote component of the HarvestChoice analytical framework is a grid-based overlay of SSA - a cropping simulation platform powered by process-based, crop models. Calibrated around the best available representation of cropping production systems in SSA, the simulation platform engages the DSSAT Crop Systems Model with the CENTURY Soil Organic Matter model (DSSAT-CENTURY) and provides a virtual experimentation module with which to explore the impact of a range of technological, managerial and environmental metrics on future crop productivity and profitability, as well as input use. For each of 5 (or 30) arc-minute grid cells in SSA, a stack of model input underlies it: datasets that cover soil properties and fertility, historic and future climate scenarios and farmers' management practices; all compiled from analyses of existing global and regional databases and consultations with other CGIAR centers. Running a simulation model is not always straightforward, especially when certain cropping systems or management practices are not even practiced by resource-poor farmers yet (e.g., precision agriculture) or they were never included in the existing simulation framework (e.g., water harvesting). In such cases, we used DSSAT-CENTURY as a function to iteratively estimate relative responses of cropping systems to technology-driven changes in water and nutrient balances compared to zero-adoption by farmers, while adjusting model input parameters to best mimic farmers' implementation of technologies in the field. We then fed the results of the simulation into to the economic and food trade model framework, IMPACT, to assess the potential implications on future food security. The outputs of the overall simulation analyses are packaged as a web-accessible database and published on the web with an interface that allows users to explore the simulation results in each country with user-defined baseline and what-if scenarios. The results are dynamically presented on maps, charts, and tables. This paper discusses the development of the simulation platform and its underlying data layers, a case study that assessed the role of potential crop management technology development, and the development of a web-based application that visualizes the simulation results.

Conservation tillage issues: cover crop-based organic rotational no-till grain production in the mid-atlantic region

USDA-ARS?s Scientific Manuscript database

Organic producers in the mid-Atlantic region are interested in reducing tillage, labor, and time requirements for grain production. Cover crop-based organic rotational no-till grain production is one approach to accomplishing these goals. Advancements in a system for planting crops into a mat of cov...

Performance of the CELSS Antarctic Analog Project (CAAP) crop production system.

PubMed

Bubenheim, D L; Schlick, G; Wilson, D; Bates, M

2003-01-01

Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515 g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.

Performance of the CELSS Antarctic Analog Project (CAAP) crop production system

NASA Astrophysics Data System (ADS)

Bubenheim, D. L.; Schlick, G.; Wilson, D.; Bates, M.

Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility.

Performance of the CELSS Antarctic Analog Project (CAAP) crop production system

NASA Technical Reports Server (NTRS)

Bubenheim, D. L.; Schlick, G.; Wilson, D.; Bates, M.

2003-01-01

Regenerative life support systems potentially offer a level of self-sufficiency and a decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant-based, regenerative life support requires resources in excess of allocation proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of the likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system. Both single crop, batch production and continuous cultivation of mixed crops production studies have been completed. The crop productivity as well as engineering performance of the chamber are described. For each scenario, energy required and partitioned for lighting, cooling, pumping, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with 27 different crops under cultivation, 17 m2 of crop area provided a mean of 515 g edible biomass per day (85% of the approximate 620 g required for one person). Enhanced engineering and crop production performance achieved with the CAAP chamber, compared with current state-of-the-art, places plant-based life support systems at the threshold of feasibility. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.

Compatibility of switchgrass as an energy crop in farming systems of the southeastern USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bransby, D.I.; Rodriguez-Kabana, R.; Sladden, S.E.

1993-12-31

The objective of this paper is to examine the compatibility of switchgrass as an energy crop in farming systems in the southeastern USA, relative to other regions. In particular, the issues addressed are (1) competition between switchgrass as an energy crop and existing farm enterprises, based primarily on economic returns, (2) complementarity between switchgrass and existing farm enterprises, and (3) environmental benefits. Because projected economic returns for switchgrass as an energy crop are highest in the Southeast, and returns from forestry and beef pastures (the major existing enterprises) are low, there is a very strong economic incentive in this region.more » In contrast, based on current information, economic viability of switchgrass as an energy crop in other regions appears doubtful. In addition, switchgrass in the southeastern USA would complement forage-livestock production, row crop production and wildlife and would provide several additional environmental benefits. It is concluded that the southeastern USA offers the greatest opportunity for developing switchgrass as an economically viable energy crop.« less

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Bioregenerative food system cost based on optimized menus for advanced life support

NASA Technical Reports Server (NTRS)

Waters, Geoffrey C R.; Olabi, Ammar; Hunter, Jean B.; Dixon, Mike A.; Lasseur, Christophe

2002-01-01

Optimized menus for a bioregenerative life support system have been developed based on measures of crop productivity, food item acceptability, menu diversity, and nutritional requirements of crew. Crop-specific biomass requirements were calculated from menu recipe demands while accounting for food processing and preparation losses. Under the assumption of staggered planting, the optimized menu demanded a total crop production area of 453 m2 for six crew. Cost of the bioregenerative food system is estimated at 439 kg per menu cycle or 7.3 kg ESM crew-1 day-1, including agricultural waste processing costs. On average, about 60% (263.6 kg ESM) of the food system cost is tied up in equipment, 26% (114.2 kg ESM) in labor, and 14% (61.5 kg ESM) in power and cooling. This number is high compared to the STS and ISS (nonregenerative) systems but reductions in ESM may be achieved through intensive crop productivity improvements, reductions in equipment masses associated with crop production, and planning of production, processing, and preparation to minimize the requirement for crew labor.

Integrated weed management systems with herbicide-tolerant crops in the European Union: lessons learnt from home and abroad.

PubMed

Lamichhane, Jay Ram; Devos, Yann; Beckie, Hugh J; Owen, Micheal D K; Tillie, Pascal; Messéan, Antoine; Kudsk, Per

2017-06-01

Conventionally bred (CHT) and genetically modified herbicide-tolerant (GMHT) crops have changed weed management practices and made an important contribution to the global production of some commodity crops. However, a concern is that farm management practices associated with the cultivation of herbicide-tolerant (HT) crops further deplete farmland biodiversity and accelerate the evolution of herbicide-resistant (HR) weeds. Diversification in crop systems and weed management practices can enhance farmland biodiversity, and reduce the risk of weeds evolving herbicide resistance. Therefore, HT crops are most effective and sustainable as a component of an integrated weed management (IWM) system. IWM advocates the use of multiple effective strategies or tactics to manage weed populations in a manner that is economically and environmentally sound. In practice, however, the potential benefits of IWM with HT crops are seldom realized because a wide range of technical and socio-economic factors hamper the transition to IWM. Here, we discuss the major factors that limit the integration of HT crops and their associated farm management practices in IWM systems. Based on the experience gained in countries where CHT or GMHT crops are widely grown and the increased familiarity with their management, we propose five actions to facilitate the integration of HT crops in IWM systems within the European Union.

Soil characteristics and associated wind erosion potential altered by oilseeds in wheat-based cropping systems

USDA-ARS?s Scientific Manuscript database

Oilseeds are integral to the production of biofuels and diversifying rainfed cropping systems in the Pacific Northwest. However, there is evidence to suggest greater potential for wind erosion when growing oilseeds in wheat-based rotations when tillage is used during fallow. Little is known concerni...

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Surprising yields with no-till cropping systems

USDA-ARS?s Scientific Manuscript database

Producers using no-till systems have found that crop yields often exceed their expectation based on nutrient and water supply. For example, corn yields 7% higher in a no-till system in central South Dakota than in a tilled system in eastern South Dakota. This is surprising because rainfall is 5 in...

A National Crop Progress Monitoring System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Zhang, B.; Deng, M.; Yang, Z.

2011-12-01

Crop progress is an important piece of information for food security and agricultural commodities. Timely monitoring and reporting are mandated for the operation of agricultural statistical agencies. Traditionally, the weekly reporting issued by the National Agricultural Statistics Service (NASS) of the United States Department of Agriculture (USDA) is based on reports from the knowledgeable state and county agricultural officials and farmers. The results are spatially coarse and subjective. In this project, a remote-sensing-supported crop progress monitoring system is being developed intensively using the data and derived products from NASA Earth Observing satellites. Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 product - MOD09 (Surface Reflectance) is used for deriving daily normalized vegetation index (NDVI), vegetation condition index (VCI), and mean vegetation condition index (MVCI). Ratio change to previous year and multiple year mean can be also produced on demand. The time-series vegetation condition indices are further combined with the NASS' remote-sensing-derived Cropland Data Layer (CDL) to estimate crop condition and progress crop by crop. To facilitate the operational requirement and increase the accessibility of data and products by different users, each component of the system has being developed and implemented following open specifications under the Web Service reference model of Open Geospatial Consortium Inc. Sensor observations and data are accessed through Web Coverage Service (WCS), Web Feature Service (WFS), or Sensor Observation Service (SOS) if available. Products are also served through such open-specification-compliant services. For rendering and presentation, Web Map Service (WMS) is used. A Web-service based system is set up and deployed at dss.csiss.gmu.edu/NDVIDownload. Further development will adopt crop growth models, feed the models with remotely sensed precipitation and soil moisture information, and incorporate the model results with vegetation-index time series for crop progress stage estimation.

Performance of the CELSS Antarctic Analog Project (CAAP) Crop Production System

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Flynn, Michael T.; Bates, Maynard; Schlick, Greg; Kliss, Mark (Technical Monitor)

1998-01-01

Regenerative life support systems potentially offer a level of self-sufficiency and a concomitant decrease in logistics and associated costs in support of space exploration and habitation missions. Current state-of-the-art in plant based, regenerative life support requires resources in excess of resource allocations proposed for candidate mission scenarios. Feasibility thresholds have been identified for candidate exploration missions. The goal of this paper is to review recent advances in performance achieved in the CELSS Antarctic Analog Project (CAAP) in light of likely resource constraints. A prototype CAAP crop production chamber has been constructed and operated at the Ames Research Center. The chamber includes a number of unique hardware and software components focused on attempts to increase production efficiency, increase energy efficiency, and control the flow of energy and mass through the system to achieve enhanced performance efficiency. Both single crop, batch production, and continuous cultivation of mixed crops Product ion scenarios have been completed. The crop productivity as well as engineering performance of the chamber will be described. For each scenario, energy required and partitioned for lighting, cooling, pumps, fans, etc. is quantified. Crop production and the resulting lighting efficiency and energy conversion efficiencies are presented. In the mixed-crop scenario, with up to 25 different crops under cultivation, 17 sq m of crop area provided a mean of 515 g edible biomass per day (83% of the approximately 620 g required for one person). Lighting efficiency (moles on photons kWh-1) approached 4 and the conversion efficiency of light energy to biomass was greatly enhanced compared with conventional growing systems. Engineering and biological performance achieved place plant-based life support systems at the threshold of feasibility.

Diversifying crop rotations with pulses enhances system productivity

PubMed Central

Gan, Yantai; Hamel, Chantal; O’Donovan, John T.; Cutforth, Herb; Zentner, Robert P.; Campbell, Con A.; Niu, Yining; Poppy, Lee

2015-01-01

Agriculture in rainfed dry areas is often challenged by inadequate water and nutrient supplies. Summerfallowing has been used to conserve rainwater and promote the release of nitrogen via the N mineralization of soil organic matter. However, summerfallowing leaves land without any crops planted for one entire growing season, creating lost production opportunity. Additionally, summerfallowing has serious environmental consequences. It is unknown whether alternative systems can be developed to retain the beneficial features of summerfallowing with little or no environmental impact. Here, we show that diversifying cropping systems with pulse crops can enhance soil water conservation, improve soil N availability, and increase system productivity. A 3-yr cropping sequence study, repeated for five cycles in Saskatchewan from 2005 to 2011, shows that both pulse- and summerfallow-based systems enhances soil N availability, but the pulse system employs biological fixation of atmospheric N2, whereas the summerfallow-system relies on ‘mining’ soil N with depleting soil organic matter. In a 3-yr cropping cycle, the pulse system increased total grain production by 35.5%, improved protein yield by 50.9%, and enhanced fertilizer-N use efficiency by 33.0% over the summerfallow system. Diversifying cropping systems with pulses can serve as an effective alternative to summerfallowing in rainfed dry areas. PMID:26424172

The Myth of Coexistence: Why Transgenic Crops Are Not Compatible With Agroecologically Based Systems of Production

ERIC Educational Resources Information Center

Altieri, Miguel

2005-01-01

The coexistence of genetically modified (GM) crops and non-GM crops is a myth because the movement of transgenes beyond their intended destinations is a certainty, and this leads to genetic contamination of organic farms and other systems. It is unlikely that transgenes can be retracted once they have escaped, thus the damage to the purity of…

A process-based agricultural model for the irrigated agriculture sector in Alberta, Canada

NASA Astrophysics Data System (ADS)

Ammar, M. E.; Davies, E. G.

2015-12-01

Connections between land and water, irrigation, agricultural productivity and profitability, policy alternatives, and climate change and variability are complex, poorly understood, and unpredictable. Policy assessment for agriculture presents a large potential for development of broad-based simulation models that can aid assessment and quantification of policy alternatives over longer temporal scales. The Canadian irrigated agriculture sector is concentrated in Alberta, where it represents two thirds of the irrigated land-base in Canada and is the largest consumer of surface water. Despite interest in irrigation expansion, its potential in Alberta is uncertain given a constrained water supply, significant social and economic development and increasing demands for both land and water, and climate change. This paper therefore introduces a system dynamics model as a decision support tool to provide insights into irrigation expansion in Alberta, and into trade-offs and risks associated with that expansion. It is intended to be used by a wide variety of users including researchers, policy analysts and planners, and irrigation managers. A process-based cropping system approach is at the core of the model and uses a water-driven crop growth mechanism described by AquaCrop. The tool goes beyond a representation of crop phenology and cropping systems by permitting assessment and quantification of the broader, long-term consequences of agricultural policies for Alberta's irrigation sector. It also encourages collaboration and provides a degree of transparency that gives confidence in simulation results. The paper focuses on the agricultural component of the systems model, describing the process involved; soil water and nutrients balance, crop growth, and water, temperature, salinity, and nutrients stresses, and how other disciplines can be integrated to account for the effects of interactions and feedbacks in the whole system. In later stages, other components such as livestock production systems and agricultural production economics will be integrated to the agricultural model to make the systems tool. It will capture feedback loops, time delays, and the nonlinearities of the system. Moreover, the model is designed for quick reconfiguration to different regions given parametrized crop data.

Comparison of Uncalibrated Rgbvi with Spectrometer-Based Ndvi Derived from Uav Sensing Systems on Field Scale

NASA Astrophysics Data System (ADS)

Bareth, G.; Bolten, A.; Gnyp, M. L.; Reusch, S.; Jasper, J.

2016-06-01

The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg) is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs) are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg) for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers' field in Western Germany. (i) A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii) NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

E-precision agriculture for small scale cash crops in Tobasa regency

NASA Astrophysics Data System (ADS)

Putra Simanjuntak, Panca; Tiurniari Napitupulu, Pangeran; Pratama Silalahi, Soni; Kisno; Pasaribu, Norlina; Valešová, Libuše

2017-09-01

Cash crop is a promising sector in Tobasa regency; however, the trend showed a negative change of the cash crop production in. This research aims to develop an application which is based on Arduino for watering and fertilizing corn land. The result of using e-precision agriculture based on embedded system is 100% higher than the conventional one and the risk of harvesting failure using the embedded system decreased to 50%. Embedded system in this study acquired critical environment measurements which at last affected the yield raising and risk reduction. As the result, the use of e-precision agriculture provided a framework to be used by different stakeholders to implement e-agriculture platform that supports marketing of agricultural production since the system is proven to save the material and time which finally reduces the risk of harvesting failure and increases the yield. In other words, the system is able to economize the use of water and fertilizer on a small corn land. The system will be developed for more efficiency in material loss and the mobile-based application development to reach sustainable rural development particularly for cash-crop farmers.

Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

PubMed

Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

2017-07-01

Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R 2 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

The Challenges in the Development of a Long Duration Space Mission Food System

NASA Technical Reports Server (NTRS)

Perchonok, Michele H.; Swango, Beverly; Toerne, Mary E.; Russo, Dane M. (Technical Monitor)

2001-01-01

The Advanced Food System at Johnson Space Center/NASA will be responsible for supplying food to the crew for long duration exploratory missions. These missions require development of both a Transit Food System and of a Planetary Food System. The Transit Food System will consist of pre-packaged food of extended shelf life. It will be supplemented with salad crops that will be consumed fresh. The challenge is to develop a food system with a shelf life of 3 - 5 years that will use minimal power and create minimal waste from the food packaging. The Planetary Food System will allow for food processing of crops grown on the planetary surface due to the presence of some gravitational force. Crops will be processed to final products to provide a nutritious and acceptable diet for the crew. The food system must be flexible due to crop variation, availability, and shelf life. Crew meals, based on thesc: crops, must be nutritious, high quality, safe, and contain variety. The Advanced Food System becomes a fulcrum creating the right connection from crops to crew meals while dealing with issues of integration within a closed self-regenerative system (e.g., safety, waste production, volumes, water usage, etc.).

Production versus environmental impact trade-offs for Swiss cropping systems: a model-based approach

NASA Astrophysics Data System (ADS)

Necpalova, Magdalena; Lee, Juhwan; Six, Johan

2017-04-01

There is a growing need to improve sustainability of agricultural systems. The key focus remains on optimizing current production systems in order to deliver food security at low environmental costs. It is therefore essential to identify and evaluate agricultural management practices for their potential to maintain or increase productivity and mitigate climate change and N pollution. Previous research on Swiss cropping systems has been concentrated on increasing crop productivity and soil fertility. Thus, relatively little is known about management effects on net soil greenhouse gas (GHG) emissions and environmental N losses in the long-term. The aim of this study was to extrapolate findings from Swiss long-term field experiments and to evaluate the system-level sustainability of a wide range of cropping systems under conditions beyond field experimentation by comparing their crop productivity and impacts on soil carbon, net soil GHG emissions, NO3 leaching and soil N balance over 30 years. The DayCent model was previously parameterized for common Swiss crops and crop-specific management practices and evaluated for productivity, soil carbon dynamics and N2O emissions from Swiss cropping systems. Based on a prediction uncertainty criterion for crop productivity and soil carbon (rRMSE<0.3), in total 39 cropping systems were selected. Each system was evaluated under soil and climate conditions representative of Therwil, Frick, Reckenholz and Changins sites with four replications. Soil inputs were sampled from normal probability distributions defined by available site-specific data using the Latin hypercube sampling method. Net soil GHG emissions were derived from changes in soil carbon, N2O emissions and CH4 oxidation and the annual net global warming potential (GWP) was calculated using IPCC (2014). For statistical analyses, the systems were grouped into the following categories: (a) farming system: organic (ORG), integrated (IN) and mineral (MIN); (b) tillage: conventional (CT), reduced (RT) and no-till (NT); (c) cover cropping: no cover cropping (NCC), winter cover cropping (CC) and winter green manuring (GM). The productivity of Swiss cropping systems was mainly driven by total N inputs to the systems. The GWP of systems ranged from -450 to 1309 kg CO2 eq ha-1 yr-1. All studied systems, except for ORG-RT-GM systems, acted as a source of net soil GHG emissions with the relative contribution of soil N2O emissions to GWP of more than 60%. The GWP of systems with CT decreased consistently with increasing use of organic manures (MIN>IN>ORG). NT relative to RT management showed to be more effective in reducing GWP from MIN systems due to reduced soil N2O emissions and positive effects on soil C sequestration. GM relative to CC management was shown to be more effective in mitigating NO3 leaching and overall N losses from MIN systems; particularly in combination with NT management. GM management also increased soil N balance of MIN and ORG systems relative to CC management, which caused an additional N removal through CC harvest. Our results suggest that there is a substantial potential for improvement and optimizing the sustainability of Swiss cropping systems across sites especially in the context of climate change mitigation and adaptation.

Nitrogen dynamics in corn and switchgrass production influenced by soils of varying depths in central Missouri

USDA-ARS?s Scientific Manuscript database

Sustainable biomass feedstock production systems involve biomass generation from non-agricultural or marginal lands with minimal external inputs. Switch grass based alley cropping systems have been proposed as biomass feedstock crop systems in marginal lands. In many areas in the Midwest United Stat...

Nitrogen uptake by corn and switchgrass plants in soils of varying depths in Central Missouri

USDA-ARS?s Scientific Manuscript database

Sustainable biomass feedstock production systems involve biomass generation from non-agricultural or marginal lands with minimal external inputs. Switchgrass based alley cropping systems have been proposed as biomass feedstock crop systems in marginal lands. In many areas in the Midwest United State...

Mapping and monitoring potato cropping systems in Maine: geospatial methods and land use assessments

USDA-ARS?s Scientific Manuscript database

Geospatial frameworks and GIS-based approaches were used to assess current cropping practices in potato production systems in Maine. Results from the geospatial integration of remotely-sensed cropland layers (2008-2011) and soil datasets for Maine revealed a four-year potato systems footprint estima...

Integration of lessons from recent research for “Earth to Mars” life support systems

NASA Astrophysics Data System (ADS)

Nelson, M.; Dempster, W. F.; Allen, J. P.

Development of reliable and robust strategies for long-term life support for planetary exploration must be built from real-time experimentation to verify and improve system components. Also critical is incorporating a range of viable options to handle potential short-term life system imbalances. This paper revisits some of the conceptual framework for a Mars base prototype which has been developed by the authors along with others previously advanced ("Mars on Earth ®") in the light of three years of experimentation in the Laboratory Biosphere, further investigation of system alternatives and the advent of other innovative engineering and agri-ecosystem approaches. Several experiments with candidate space agriculture crops have demonstrated the higher productivity possible with elevated light levels and improved environmental controls. For example, crops of sweet potatoes exceeded original Mars base prototype projections by an average of 46% (53% for best crop) ultradwarf (Apogee) wheat by 9% (23% for best crop), pinto bean by 13% (31% for best crop). These production levels, although they may be increased with further optimization of lighting regimes, environmental parameters, crop density etc. offer evidence that a soil-based system can be as productive as the hydroponic systems which have dominated space life support scenarios and research. But soil also offers distinct advantages: the capability to be created on the Moon or Mars using in situ space resources, reduces long-term reliance on consumables and imported resources, and more readily recycling and incorporating crew and crop waste products. In addition, a living soil contains a complex microbial ecosystem which helps prevent the buildup of trace gases or compounds, and thus assist with air and water purification. The atmospheric dynamics of these crops were studied in the Laboratory Biosphere adding to the database necessary for managing the mixed stands of crops essential for supplying a nutritionally adequate diet in space. This paper explores some of the challenges of small bioregenerative life support: air-sealing and facility architecture/design, balance of short-term variations of carbon dioxide and oxygen through staggered plantings, options for additional atmospheric buffers and sinks, lighting/energy efficiency engineering, crop and waste product recycling approaches, and human factor considerations in the design and operation of a Mars base. An "Earth to Mars" project, forging the ability to live sustainably in space (as on Earth) requires continued research and testing of these components and integrated subsystems; and developing a step-by-step learning process.

Wireless sensor network-based greenhouse environment monitoring and automatic control system for dew condensation prevention.

PubMed

Park, Dae-Heon; Park, Jang-Woo

2011-01-01

Dew condensation on the leaf surface of greenhouse crops can promote diseases caused by fungus and bacteria, affecting the growth of the crops. In this paper, we present a WSN (Wireless Sensor Network)-based automatic monitoring system to prevent dew condensation in a greenhouse environment. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for driving devices for adjusting the environment inside greenhouse and an environment server for data storage and processing. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent dew condensation phenomena on the crop's surface acting as an important element for prevention of diseases infections. We also constructed a physical model resembling the typical greenhouse in order to verify the performance of our system with regard to dew condensation control.

Globally Increased Crop Growth and Cropping Intensity from the Long-Term Satellite-Based Observations

NASA Astrophysics Data System (ADS)

Chen, Bin

2018-04-01

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

Detecting crop population growth using chlorophyll fluorescence imaging.

PubMed

Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

2017-12-10

For both field and greenhouse crops, it is challenging to evaluate their growth information on a large area over a long time. In this work, we developed a chlorophyll fluorescence imaging-based system for crop population growth information detection. Modular design was used to make the system provide high-intensity uniform illumination. This system can perform modulated chlorophyll fluorescence induction kinetics measurement and chlorophyll fluorescence parameter imaging over a large area of up to 45  cm×34  cm. The system can provide different lighting intensity by modulating the duty cycle of its control signal. Results of continuous monitoring of cucumbers in nitrogen deficiency show the system can reduce the judge error of crop physiological status and improve monitoring efficiency. Meanwhile, the system is promising in high throughput application scenarios.

The Lower Sevier River Basin Crop Monitor and Forecast Decision Support System: Exploiting Landsat Imagery to Provide Continuous Information to Farmers and Water Managers

NASA Astrophysics Data System (ADS)

Torres-Rua, A. F.; Walker, W. R.; McKee, M.

2013-12-01

The last century has seen a large number of innovations in agriculture such as better policies for water control and management, upgraded water conveyance, irrigation, distribution, and monitoring systems, and better weather forecasting products. In spite of this, irrigation management and irrigation water deliveries by farmers/water managers is still based on factors like water share amounts, tradition, and past experience on irrigation. These factors are not necessarily related to the actual crop water use; they are followed because of the absence of related information provided in a timely manner at an affordable cost. Thus, it is necessary to develop means to deliver continuous and personalized information about crop water requirements to water users/managers at the field and irrigation system levels so managers at these levels can better quantify the required versus available water for irrigation during the irrigation season. This study presents a new decision support system (DSS) platform that addresses the absence of information on actual crop water requirements and crop performance by providing continuous updated farm-based crop water use along with other farm performance indicators such as crop yield and farm management to irrigators and water managers. This DSS exploits the periodicity of the Landsat Satellite Mission (8 to 16 days, depending on the period of interest) to provide remote monitoring at the individual field and irrigation system levels. The Landsat satellite images are converted into information about crop water use, yield performance and field management through application of state-of-the-art semi-physical and statistical algorithms that provide this information at a pixel basis that are ultimately aggregated to field and irrigation system levels. A version of the DSS has been implemented for the agricultural lands in the Lower Sevier River, Utah, and has been operational since the beginning of the 2013 irrigation season. The main goal of this DSS implementation is to provide continuous and personalized information to farmers and water managers regarding crops in fields and the irrigation delivery system throughout the irrigation season so that decisions related to agricultural water use can result in water savings while not diminishing crop yields.

Organic vs. organic - soil arthropods as bioindicators of ecological sustainability in greenhouse system experiment under Mediterranean conditions.

PubMed

Madzaric, Suzana; Ceglie, F G; Depalo, L; Al Bitar, L; Mimiola, G; Tittarelli, F; Burgio, G

2017-11-23

Organic greenhouse (OGH) production is characterized by different systems and agricultural practices with diverse environmental impact. Soil arthropods are widely used as bioindicators of ecological sustainability in open field studies, while there is a lack of research on organic production for protected systems. This study assessed the soil arthropod abundance and diversity over a 2-year crop rotation in three systems of OGH production in the Mediterranean. The systems under assessment differed in soil fertility management: SUBST - a simplified system of organic production, based on an input substitution approach (use of guano and organic liquid fertilizers), AGROCOM - soil fertility mainly based on compost application and agroecological services crops (ASC) cultivation (tailored use of cover crops) as part of crop rotation, and AGROMAN - animal manure and ASC cultivation as part of crop rotation. Monitoring of soil fauna was performed by using pitfall traps and seven taxa were considered: Carabidae, Staphylinidae, Araneae, Opiliones, Isopoda, Myriapoda, and Collembola. Results demonstrated high potential of ASC cultivation as a technique for beneficial soil arthropod conservation in OGH conditions. SUBST system was dominated by Collembola in all crops, while AGROMAN and AGROCOM had more balanced relative abundance of Isopoda, Staphylinidae, and Aranea. Opiliones and Myriapoda were more affected by season, while Carabidae were poorly represented in the whole monitoring period. Despite the fact that all three production systems are in accordance with the European Union regulation on organic farming, findings of this study displayed significant differences among them and confirmed the suitability of soil arthropods as bioindicators in protected systems of organic farming.

Estimating millet production for famine early warning: An application of crop simulation modelling using satellite and ground-based data in Burkina Faso

USGS Publications Warehouse

Thornton, P. K.; Bowen, W. T.; Ravelo, A.C.; Wilkens, P. W.; Farmer, G.; Brock, J.; Brink, J. E.

1997-01-01

Early warning of impending poor crop harvests in highly variable environments can allow policy makers the time they need to take appropriate action to ameliorate the effects of regional food shortages on vulnerable rural and urban populations. Crop production estimates for the current season can be obtained using crop simulation models and remotely sensed estimates of rainfall in real time, embedded in a geographic information system that allows simple analysis of simulation results. A prototype yield estimation system was developed for the thirty provinces of Burkina Faso. It is based on CERES-Millet, a crop simulation model of the growth and development of millet (Pennisetum spp.). The prototype was used to estimate millet production in contrasting seasons and to derive production anomaly estimates for the 1986 season. Provincial yields simulated halfway through the growing season were generally within 15% of their final (end-of-season) values. Although more work is required to produce an operational early warning system of reasonable credibility, the methodology has considerable potential for providing timely estimates of regional production of the major food crops in countries of sub-Saharan Africa.

Conservation Agriculture Practices in Rainfed Uplands of India Improve Maize-Based System Productivity and Profitability

PubMed Central

Pradhan, Aliza; Idol, Travis; Roul, Pravat K.

2016-01-01

Traditional agriculture in rainfed uplands of India has been experiencing low agricultural productivity as the lands suffer from poor soil fertility, susceptibility to water erosion and other external pressures of development and climate change. A shift toward more sustainable cropping systems such as conservation agriculture production systems (CAPSs) may help in maintaining soil quality as well as improving crop production and farmer’s net economic benefit. This research assessed the effects over 3 years (2011–2014) of reduced tillage, intercropping, and cover cropping practices customized for maize-based production systems in upland areas of Odisha, India. The study focused on crop yield, system productivity and profitability through maize equivalent yield and dominance analysis. Results showed that maize grain yield did not differ significantly over time or among CAPS treatments while cowpea yield was considered as an additional yield in intercropping systems. Mustard and horsegram grown in plots after maize cowpea intercropping recorded higher grain yields of 25 and 37%, respectively, as compared to those without intercropping. Overall, the full CAPS implementation, i.e., minimum tillage, maize–cowpea intercropping and mustard residue retention had significantly higher system productivity and net benefits than traditional farmer practices, i.e., conventional tillage, sole maize cropping, and no mustard residue retention. The dominance analysis demonstrated increasing benefits of combining conservation practices that exceeded thresholds for farmer adoption. Given the use of familiar crops and technologies and the magnitude of yield and income improvements, these types of CAPS should be acceptable and attractive for smallholder farmers in the area. This in turn should support a move toward sustainable intensification of crop production to meet future household income and nutritional needs. PMID:27471508

Conservation Agriculture Practices in Rainfed Uplands of India Improve Maize-Based System Productivity and Profitability.

PubMed

Pradhan, Aliza; Idol, Travis; Roul, Pravat K

2016-01-01

Traditional agriculture in rainfed uplands of India has been experiencing low agricultural productivity as the lands suffer from poor soil fertility, susceptibility to water erosion and other external pressures of development and climate change. A shift toward more sustainable cropping systems such as conservation agriculture production systems (CAPSs) may help in maintaining soil quality as well as improving crop production and farmer's net economic benefit. This research assessed the effects over 3 years (2011-2014) of reduced tillage, intercropping, and cover cropping practices customized for maize-based production systems in upland areas of Odisha, India. The study focused on crop yield, system productivity and profitability through maize equivalent yield and dominance analysis. Results showed that maize grain yield did not differ significantly over time or among CAPS treatments while cowpea yield was considered as an additional yield in intercropping systems. Mustard and horsegram grown in plots after maize cowpea intercropping recorded higher grain yields of 25 and 37%, respectively, as compared to those without intercropping. Overall, the full CAPS implementation, i.e., minimum tillage, maize-cowpea intercropping and mustard residue retention had significantly higher system productivity and net benefits than traditional farmer practices, i.e., conventional tillage, sole maize cropping, and no mustard residue retention. The dominance analysis demonstrated increasing benefits of combining conservation practices that exceeded thresholds for farmer adoption. Given the use of familiar crops and technologies and the magnitude of yield and income improvements, these types of CAPS should be acceptable and attractive for smallholder farmers in the area. This in turn should support a move toward sustainable intensification of crop production to meet future household income and nutritional needs.

Winter cover crops on processing tomato yield, quality, pest pressure, nitrogen availability, and profit margins.

PubMed

Belfry, Kimberly D; Trueman, Cheryl; Vyn, Richard J; Loewen, Steven A; Van Eerd, Laura L

2017-01-01

Much of cover crop research to date focuses on key indicators of impact without considering the implications over multiple years, in the absence of a systems-based approach. To evaluate the effect of three years of autumn cover crops on subsequent processing tomato (Solanum lycopersicum L.) production in 2010 and 2011, a field split-split-plot factorial design trial with effects of cover crop type, urea ammonium nitrate fertilizer rate (0 or 140 kg N ha-1 preplant broadcast incorporated) and tomato cultivar (early vs. late) was conducted. The main plot factor, cover crop, included a no cover crop control, oat (Avena sativa L.), winter cereal rye (hereafter referred to as rye) (Secale cereale L.), oilseed radish (OSR) (Raphanus sativus L. var. oleiferus Metzg Stokes), and mix of OSR and rye (OSR + rye) treatments. Cover crop biomass of 0.5 to 2.8 and 1.7 to 3.1 Mg ha-1 was attained in early Oct. and the following early May, respectively. In general, OSR increased soil mineral N during cover crop growth and into the succeeding summer tomato growing season, while the remaining cover crops did not differ from the no cover crop control. The lack of a cover crop by N rate interaction in soil and plant N analyses at harvest suggests that growers may not need to modify N fertilizer rates to tomatoes based on cover crop type. Processing tomato fruit quality at harvest (rots, insect or disease damage, Agtron colour, pH, or natural tomato soluble solids (NTSS)) was not affected by cover crop type. In both years, marketable yield in the no cover crop treatment was lower or not statistically different than all planted cover crops. Partial profit margins over both years were 1320 $ ha-1 higher with OSR and $960 higher with oat compared to the no cover crop control. Thus, results from a systems-based approach suggest that the cover crops tested had no observed negative impact on processing tomato production and have the potential to increase marketable yield and profit margins.

Winter cover crops on processing tomato yield, quality, pest pressure, nitrogen availability, and profit margins

PubMed Central

Belfry, Kimberly D.; Trueman, Cheryl; Vyn, Richard J.; Loewen, Steven A.; Van Eerd, Laura L.

2017-01-01

Much of cover crop research to date focuses on key indicators of impact without considering the implications over multiple years, in the absence of a systems-based approach. To evaluate the effect of three years of autumn cover crops on subsequent processing tomato (Solanum lycopersicum L.) production in 2010 and 2011, a field split-split-plot factorial design trial with effects of cover crop type, urea ammonium nitrate fertilizer rate (0 or 140 kg N ha-1 preplant broadcast incorporated) and tomato cultivar (early vs. late) was conducted. The main plot factor, cover crop, included a no cover crop control, oat (Avena sativa L.), winter cereal rye (hereafter referred to as rye) (Secale cereale L.), oilseed radish (OSR) (Raphanus sativus L. var. oleiferus Metzg Stokes), and mix of OSR and rye (OSR + rye) treatments. Cover crop biomass of 0.5 to 2.8 and 1.7 to 3.1 Mg ha-1 was attained in early Oct. and the following early May, respectively. In general, OSR increased soil mineral N during cover crop growth and into the succeeding summer tomato growing season, while the remaining cover crops did not differ from the no cover crop control. The lack of a cover crop by N rate interaction in soil and plant N analyses at harvest suggests that growers may not need to modify N fertilizer rates to tomatoes based on cover crop type. Processing tomato fruit quality at harvest (rots, insect or disease damage, Agtron colour, pH, or natural tomato soluble solids (NTSS)) was not affected by cover crop type. In both years, marketable yield in the no cover crop treatment was lower or not statistically different than all planted cover crops. Partial profit margins over both years were 1320 $ ha-1 higher with OSR and $960 higher with oat compared to the no cover crop control. Thus, results from a systems-based approach suggest that the cover crops tested had no observed negative impact on processing tomato production and have the potential to increase marketable yield and profit margins. PMID:28683080

Lasting effects of soil health improvements with management changes in cotton-based cropping systems in a sandy soil

USDA-ARS?s Scientific Manuscript database

The soil microbial component is essential for sustainable agricultural systems and soil health. This study evaluated the lasting impacts of 5 years of soil health improvements from alternative cropping systems compared to intensively tilled continuous cotton (Cont. Ctn) in a low organic matter sandy...

WEBGIS based CropWatch online agriculture monitoring system

NASA Astrophysics Data System (ADS)

Zhang, X.; Wu, B.; Zeng, H.; Zhang, M.; Yan, N.

2015-12-01

CropWatch, which was developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), has achieved breakthrough results in the integration of methods, independence of the assessments and support to emergency response by periodically releasing global agricultural information. Taking advantages of the multi-source remote sensing data and the openness of the data sharing policies, CropWatch group reported their monitoring results by publishing four bulletins one year. In order to better analysis and generate the bulletin and provide an alternative way to access agricultural monitoring indicators and results in CropWatch, The CropWatch online system based on the WEBGIS techniques has been developed. Figure 1 shows the CropWatch online system structure and the system UI in Clustering mode. Data visualization is sorted into three different modes: Vector mode, Raster mode and Clustering mode. Vector mode provides the statistic value for all the indicators over each monitoring units which allows users to compare current situation with historical values (average, maximum, etc.). Users can compare the profiles of each indicator over the current growing season with the historical data in a chart by selecting the region of interest (ROI). Raster mode provides pixel based anomaly of CropWatch indicators globally. In this mode, users are able to zoom in to the regions where the notable anomaly was identified from statistic values in vector mode. Data from remote sensing image series at high temporal and low spatial resolution provide key information in agriculture monitoring. Clustering mode provides integrated information on different classes in maps, the corresponding profiles for each class and the percentage of area of each class to the total area of all classes. The time series data is categorized into limited types by the ISODATA algorithm. For each clustering type, pixels on the map, profiles, and percentage legend are all linked together. All the three visualization methods are applied to four scales including 65 monitoring and reporting units (MRUs), 7 major production zones (MPZs), 173 countries and sub-countries for 9 large countries. Agro-Climatic information, Agronomic information and indicators related with crop area, crop yield and crop production are provided.

Monitoring and Modeling Crop Health and Water Use via in-situ, Airborne and Space-based Platforms

NASA Astrophysics Data System (ADS)

McCabe, M. F.

2014-12-01

The accurate retrieval of plant water use, health and function together with soil state and condition, represent key objectives in the management and monitoring of large-scale agricultural production. In regions of water shortage or stress, understanding the sustainable use of available water supplies is critical. Unfortunately, this need is all too often limited by a lack of reliable observations. Techniques that balance the demand for reliable ground-based data with the rapid retrieval of spatially distributed crop characteristics represent a needed line of research. Data from in-situ monitoring coupled with advances in satellite retrievals of key land surface variables, provide the information necessary to characterize many crop health and water use features, including evaporation, leaf-chlorophyll and other common vegetation indices. With developments in UAV and quadcopter solutions, the opportunity to bridge the spatio-temporal gap between satellite and ground based sensing now exists, along with the capacity for customized retrievals of crop information. While there remain challenges in the routine application of autonomous airborne systems, the state of current technology and sensor developments provide the capacity to explore the operational potential. While this presentation will focus on the multi-scale estimation of crop-water use and crop-health characteristics from satellite-based sensors, the retrieval of high resolution spatially distributed information from near-surface airborne and ground-based systems will also be examined.

Management of herbicide resistance in wheat cropping systems: learning from the Australian experience.

PubMed

Walsh, Michael J; Powles, Stephen B

2014-09-01

Herbicide resistance continues to escalate in weed populations infesting global wheat (Triticum aestivum L.) crops, threatening grain production and thereby food supply. Conservation wheat production systems are reliant on the use of efficient herbicides providing low-cost, selective weed control in intensive cropping systems. The resistance-driven loss of herbicide resources combined with limited potential for new herbicide molecules means greater emphasis must be placed on preserving existing herbicides. For more than two decades, since the initial recognition of the dramatic consequences of herbicide resistance, the challenge of introducing additional weed control strategies into herbicide-based weed management programmes has been formidable. Throughout this period, herbicide resistance has expanded unabated across the world's wheat production regions. However, in Australia, where herbicide resources have become desperately depleted, the adoption of harvest weed seed control is evidence, at last, of a successful approach to sustainable weed management in wheat production systems. Growers routinely including strategies to target weed seeds during crop harvest, as part of herbicide-based weed management programmes, are now realising significant weed control and crop production benefits. When combined with an attitude of zero weed tolerance, there is evidence of a sustainable weed control future for wheat production systems. The hard-learned lessons of Australian growers can now be viewed by global wheat producers as an example of how to stop the continual loss of herbicide resources in productive cropping systems. © 2013 Society of Chemical Industry.

Proteomics and plant disease: advances in combating a major threat to the global food supply.

PubMed

Rampitsch, Christof; Bykova, Natalia V

2012-02-01

The study of plant disease and immunity is benefiting tremendously from proteomics. Parallel streams of research from model systems, from pathogens in vitro and from the relevant pathogen-crop interactions themselves have begun to reveal a model of how plants succumb to invading pathogens and how they defend themselves without the benefit of a circulating immune system. In this review, we discuss the contribution of proteomics to these advances, drawing mainly on examples from crop-fungus interactions, from Arabidopsis-bacteria interactions, from elicitor-based model systems and from pathogen studies, to highlight also the important contribution of non-crop systems to advancing crop protection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The crop growth research chamber

NASA Technical Reports Server (NTRS)

Wagenbach, Kimberly

1993-01-01

The Crop Growth Research Chamber (CGRC) has been defined by CELSS principle investigators and science advisory panels as a necessary ground-based tool in the development of a regenerative life support system. The focus of CGRC research will be on the biomass production component of the CELSS system. The ground-based Crop Growth Research Chamber is for the study of plant growth and development under stringently controlled environments isolated from the external environment. The chamber has importance in three areas of CELSS activities: (1) crop research; (2) system control and integration, and (3) flight hardware design and experimentation. The laboratory size of the CGRC will be small enough to allow duplication of the unit, the conducting of controlled experiments, and replication of experiments, but large enough to provide information representative of larger plant communities. Experiments will focus on plant growth in a wide variety of environments and the effects of those environments on plant production of food, water, oxygen, toxins, and microbes. To study these effects in a closed system, tight control of the environment is necessary.

Identifying populations potentially exposed to agricultural pesticides using remote sensing and a Geographic Information System

USGS Publications Warehouse

Ward, M.H.; Nuckols, J.R.; Weigel, S. J.; Cantor, K.P.; Miller, Roger S.

2000-01-01

Pesticides used in agriculture may cause adverse health effects among the population living near agricultural areas. However, identifying the populations most likely to be exposed is difficult. We conducted a feasibility study to determine whether satellite imagery could be used to reconstruct historical crop patterns. We used historical Farm Service Agency records as a source of ground reference data to classify a late summer 1984 satellite image into crop species in a three-county area in south central Nebraska. Residences from a population-based epidemiologic study of non-Hodgkin lymphoma were located on the crop maps using a geographic information system (GIS). Corn, soybeans, sorghum, and alfalfa were the major crops grown in the study area. Eighty-five percent of residences could be located, and of these 22% had one of the four major crops within 500 m of the residence, an intermediate distance for the range of drift effects from pesticides applied in agriculture. We determined the proximity of residences to specific crop species and calculated crop-specific probabilities of pesticide use based on available data. This feasibility study demonstrated that remote sensing data and historical records on crop location can be used to create historical crop maps. The crop pesticides that were likely to have been applied can be estimated when information about crop-specific pesticide use is available. Using a GIS, zones of potential exposure to agricultural pesticides and proximity measures can be determined for residences in a study.

Development of an irrigation scheduling software based on model predicted crop water stress

USDA-ARS?s Scientific Manuscript database

Modern irrigation scheduling methods are generally based on sensor-monitored soil moisture regimes rather than crop water stress which is difficult to measure in real-time, but can be computed using agricultural system models. In this study, an irrigation scheduling software based on RZWQM2 model pr...

Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.

A Portable Farmland Information Collection System with Multiple Sensors.

PubMed

Zhang, Jianfeng; Hu, Jinyang; Huang, Lvwen; Zhang, Zhiyong; Ma, Yimian

2016-10-22

Precision agriculture is the trend of modern agriculture, and it is also one of the important ways to realize the sustainable development of agriculture. In order to meet the production requirements of precision agriculture-efficient use of agricultural resources, and improving the crop yields and quality-some necessary field information in crop growth environment needs to be collected and monitored. In this paper, a farmland information collection system is developed, which includes a portable farmland information collection device based on STM32 (a 32-bit comprehensive range of microcontrollers based on ARM Crotex-M3), a remote server and a mobile phone APP. The device realizes the function of portable and mobile collecting of multiple parameters farmland information, such as chlorophyll content of crop leaves, air temperature, air humidity, and light intensity. UM220-III (Unicore Communication Inc., Beijing, China) is used to realize the positioning based on BDS/GPS (BeiDou Navigation Satellite System, BDS/Global Positioning System, GPS) dual-mode navigation and positioning system, and the CDMA (Code Division Multiple Access, CDMA) wireless communication module is adopted to realize the real-time remote transmission. The portable multi-function farmland information collection system is real-time, accurate, and easy to use to collect farmland information and multiple information parameters of crops.

A Portable Farmland Information Collection System with Multiple Sensors

PubMed Central

Zhang, Jianfeng; Hu, Jinyang; Huang, Lvwen; Zhang, Zhiyong; Ma, Yimian

2016-01-01

Precision agriculture is the trend of modern agriculture, and it is also one of the important ways to realize the sustainable development of agriculture. In order to meet the production requirements of precision agriculture—efficient use of agricultural resources, and improving the crop yields and quality—some necessary field information in crop growth environment needs to be collected and monitored. In this paper, a farmland information collection system is developed, which includes a portable farmland information collection device based on STM32 (a 32-bit comprehensive range of microcontrollers based on ARM Crotex-M3), a remote server and a mobile phone APP. The device realizes the function of portable and mobile collecting of multiple parameters farmland information, such as chlorophyll content of crop leaves, air temperature, air humidity, and light intensity. UM220-III (Unicore Communication Inc., Beijing, China) is used to realize the positioning based on BDS/GPS (BeiDou Navigation Satellite System, BDS/Global Positioning System, GPS) dual-mode navigation and positioning system, and the CDMA (Code Division Multiple Access, CDMA) wireless communication module is adopted to realize the real-time remote transmission. The portable multi-function farmland information collection system is real-time, accurate, and easy to use to collect farmland information and multiple information parameters of crops. PMID:27782076

Push-Pull: Chemical Ecology-Based Integrated Pest Management Technology.

PubMed

Khan, Zeyaur; Midega, Charles A O; Hooper, Antony; Pickett, John

2016-07-01

Lepidopterous stemborers, and parasitic striga weeds belonging to the family Orobanchaceae, attack cereal crops in sub-Saharan Africa causing severe yield losses. The smallholder farmers are resource constrained and unable to afford expensive chemicals for crop protection. The push-pull technology, a chemical ecology- based cropping system, is developed for integrated pest and weed management in cereal-livestock farming systems. Appropriate plants were selected that naturally emit signaling chemicals (semiochemicals). Plants highly attractive for stemborer egg laying were selected and employed as trap crops (pull), to draw pests away from the main crop. Plants that repelled stemborer females were selected as intercrops (push). The stemborers are attracted to the trap plant, and are repelled from the main cereal crop using a repellent intercrop (push). Root exudates of leguminous repellent intercrops also effectively control the parasitic striga weed through an allelopathic mechanism. Their root exudates contain flavonoid compounds some of which stimulate germination of Striga hermonthica seeds, such as Uncinanone B, and others that dramatically inhibit their attachment to host roots, such as Uncinanone C and a number of di-C-glycosylflavones (di-CGFs), resulting in suicidal germination. The intercrop also improves soil fertility through nitrogen fixation, natural mulching, improved biomass, and control of erosion. Both companion plants provide high value animal fodder, facilitating milk production and diversifying farmers' income sources. The technology is appropriate to smallholder mixed cropping systems in Africa. Adopted by about 125,000 farmers to date in eastern Africa, it effectively addresses major production constraints, significantly increases maize yields, and is economical as it is based on locally available plants, not expensive external inputs.

Monitoring corn and soybean crop development by remote sensing techniques

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Elgin, J. H., Jr.; Mcmurtrey, J. E., III

1978-01-01

A system for spectrally monitoring the stages of crop development for corn and soybeans based upon red and photographic infrared spectral radiances is proposed. The red and photographic infrared spectral radiance, highly correlated with the green leaf area index or green leaf biomass, enable nondestructive monitoring of the crop canopy throughout the growing season. Five distinct periods are apparent which are related to crop development for corn and soybeans.

Evaluating an ensemble classification approach for crop diversity verification in Danish greening subsidy control

NASA Astrophysics Data System (ADS)

Chellasamy, Menaka; Ferré, Ty Paul Andrew; Greve, Mogens Humlekrog

2016-07-01

Beginning in 2015, Danish farmers are obliged to meet specific crop diversification rules based on total land area and number of crops cultivated to be eligible for new greening subsidies. Hence, there is a need for the Danish government to extend their subsidy control system to verify farmers' declarations to warrant greening payments under the new crop diversification rules. Remote Sensing (RS) technology has been used since 1992 to control farmers' subsidies in Denmark. However, a proper RS-based approach is yet to be finalised to validate new crop diversity requirements designed for assessing compliance under the recent subsidy scheme (2014-2020); This study uses an ensemble classification approach (proposed by the authors in previous studies) for validating the crop diversity requirements of the new rules. The approach uses a neural network ensemble classification system with bi-temporal (spring and early summer) WorldView-2 imagery (WV2) and includes the following steps: (1) automatic computation of pixel-based prediction probabilities using multiple neural networks; (2) quantification of the classification uncertainty using Endorsement Theory (ET); (3) discrimination of crop pixels and validation of the crop diversification rules at farm level; and (4) identification of farmers who are violating the requirements for greening subsidies. The prediction probabilities are computed by a neural network ensemble supplied with training samples selected automatically using farmers declared parcels (field vectors containing crop information and the field boundary of each crop). Crop discrimination is performed by considering a set of conclusions derived from individual neural networks based on ET. Verification of the diversification rules is performed by incorporating pixel-based classification uncertainty or confidence intervals with the class labels at the farmer level. The proposed approach was tested with WV2 imagery acquired in 2011 for a study area in Vennebjerg, Denmark, containing 132 farmers, 1258 fields, and 18 crops. The classification results obtained show an overall accuracy of 90.2%. The RS-based results suggest that 36 farmers did not follow the crop diversification rules that would qualify for the greening subsidies. When compared to the farmers' reported crop mixes, irrespective of the rule, the RS results indicate that false crop declarations were made by 8 farmers, covering 15 fields. If the farmers' reports had been submitted for the new greening subsidies, 3 farmers would have made a false claim; while remaining 5 farmers obey the rules of required crop proportion even though they have submitted the false crop code due to their small holding size. The RS results would have supported 96 farmers for greening subsidy claims, with no instances of suggesting a greening subsidy for a holding that the farmer did not report as meeting the required conditions. These results suggest that the proposed RS based method shows great promise for validating the new greening subsidies in Denmark.

Field-based estimates of global warming potential in bioenergy systems of Hawaii: Crop choice and deficit irrigation

USDA-ARS?s Scientific Manuscript database

Replacing fossil fuel with biofuel is environmentally viable only if the net greenhouse gas (GHG) footprint of the system is reduced. The effects of replacing annual arable crops with perennial bioenergy feedstocks on net GHG production and soil carbon (C) stock are critical to the system-level bal...

United States benefits of improved worldwide wheat crop information from a LANDSAT system

NASA Technical Reports Server (NTRS)

Heiss, K. P.; Sand, F.; Seidel, A.; Warner, D.; Sheflin, N.; Bhattacharyya, R.; Andrews, J.

1975-01-01

The value of worldwide information improvements on wheat crops, promised by LANDSAT, is measured in the context of world wheat markets. These benefits are based on current LANDSAT technical goals and assume that information is made available to all (United States and other countries) at the same time. A detailed empirical sample demonstration of the effect of improved information is given; the history of wheat commodity prices for 1971-72 is reconstructed and the price changes from improved vs. historical information are compared. The improved crop forecasting from a LANDSAT system assumed include wheat crop estimates of 90 percent accuracy for each major wheat producing region. Accurate, objective worldwide wheat crop information using space systems may have a very stabilizing influence on world commodity markets, in part making possible the establishment of long-term, stable trade relationships.

Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties

USDA-ARS?s Scientific Manuscript database

Tillage is an important procedure for modifying the soil environment in order to enhance crop growth and conserve soil and water resources. Process-based models of crop production are widely used in decision support, but few explicitly simulate tillage. The Cropping Systems Model (CSM) was modified ...

Integrating Satellite and Surface Sensor Networks for Irrigation Management Applications in California

NASA Astrophysics Data System (ADS)

Melton, F. S.; Johnson, L.; Post, K. M.; Guzman, A.; Zaragoza, I.; Spellenberg, R.; Rosevelt, C.; Michaelis, A.; Nemani, R. R.; Cahn, M.; Frame, K.; Temesgen, B.; Eching, S.

2016-12-01

Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water managers with information that can be used to optimize agricultural water use, especially in regions with limited water supplies. The timely delivery of information on agricultural crop water requirements has the potential to make irrigation scheduling more practical, convenient, and accurate. We present a system for irrigation scheduling and management support in California and describe lessons learned from the development and implementation of the system. The Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development, basal crop coefficients (Kcb), and basal crop evapotranspiration (ETcb) at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based irrigation management decision support system and web data services. SIMS also provides an application programming interface (API) that facilitates integration with other irrigation decision support tools, estimation of total crop evapotranspiration (ETc) and calculation of on-farm water use efficiency metrics. Accuracy assessments conducted in commercial fields for more than a dozen crop types to date have shown that SIMS seasonal ETcb estimates are within 10% mean absolute error (MAE) for well-watered crops and within 15% across all crop types studied, and closely track daily ETc and running totals of ETc measured in each field. Use of a soil water balance model to correct for soil evaporation and crop water stress reduces this error to less than 8% MAE across all crop types studied to date relative to field measurements of ETc. Results from irrigation trials conducted by the project for four vegetable crops have also demonstrated the potential for use of ET-based irrigation management strategies to reduce total applied water by 20-40% relative to grower standard practices while maintaining crop yields and quality.

New insights into phosphorus management in agriculture--A crop rotation approach.

PubMed

Łukowiak, Remigiusz; Grzebisz, Witold; Sassenrath, Gretchen F

2016-01-15

This manuscript presents research results examining phosphorus (P) management in a soil–plant system for three variables: i) internal resources of soil available phosphorus, ii) cropping sequence, and iii) external input of phosphorus (manure, fertilizers). The research was conducted in long-term cropping sequences with oilseed rape (10 rotations) and maize (six rotations) over three consecutive growing seasons (2004/2005, 2005/2006, and 2006/2007) in a production farm on soils originated from Albic Luvisols in Poland. The soil available phosphorus pool, measured as calcium chloride extractable P (CCE-P), constituted 28% to 67% of the total phosphorus input (PTI) to the soil–plant system in the spring. Oilseed rape and maize dominant cropping sequences showed a significant potential to utilize the CCE-P pool within the soil profile. Cropping sequences containing oilseed rape significantly affected the CCE-P pool, and in turn contributed to the P(TI). The P(TI) uptake use efficiency was 50% on average. Therefore, the CCE-P pool should be taken into account as an important component of a sound and reliable phosphorus balance. The instability of the yield prediction, based on the P(TI), was mainly due to an imbalanced management of both farmyard manure and phosphorus fertilizer. Oilseed rape plants provide a significant positive impact on the CCE-P pool after harvest, improving the productive stability of the entire cropping sequence. This phenomenon was documented by the P(TI) increase during wheat cultivation following oilseed rape. The Unit Phosphorus Uptake index also showed a higher stability in oilseed rape cropping systems compared to rotations based on maize. Cropping sequences are a primary factor impacting phosphorus management. Judicious implementation of crop rotations can improve soil P resources, efficiency of crop P use, and crop yield and yield stability. Use of cropping sequences can reduce the need for external P sources such as farmyard manure and chemical fertilizers.

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System.

PubMed

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-03-03

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R²) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively.

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System

PubMed Central

Ni, Jun; Yao, Lili; Zhang, Jingchao; Cao, Weixing; Zhu, Yan; Tai, Xiuxiang

2017-01-01

In view of the demand for a low-cost, high-throughput method for the continuous acquisition of crop growth information, this study describes a crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform. The system is capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index (NDVI) of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW). By carrying out three-dimensional numerical simulations based on computational fluid dynamics, spatial distributions were obtained for the UAV down-wash flow fields on the surface of the crop canopy. Based on the flow-field characteristics and geometrical dimensions, a UAV-borne crop-growth sensor was designed. Our field experiments show that the monitoring system has good dynamic stability and measurement accuracy over the range of operating altitudes of the sensor. The linear fitting determination coefficients (R2) for the output RVI value with respect to LNA, LAI, and LDW are 0.63, 0.69, and 0.66, respectively, and the Root-mean-square errors (RMSEs) are 1.42, 1.02 and 3.09, respectively. The equivalent figures for the output NDVI value are 0.60, 0.65, and 0.62 (LNA, LAI, and LDW, respectively) and the RMSEs are 1.44, 1.01 and 3.01, respectively. PMID:28273815

Rice crop growth and outlook monitoring using SAR in Asia

NASA Astrophysics Data System (ADS)

Hamamoto, K.; Sobue, S.; Oyoshi, K.; Ikehata, Y.

2016-12-01

The Asia-RiCE initiative (http://www.asia-rice.org) has been organized to enhance rice production estimates through the use of Earth observation satellites data, and seeks to ensure that Asian rice crops are appropriately represented within GEO Global Agriculture Monitoring (GEO-GLAM) to support FAO Agriculture Market Information System (FAO-AMIS). Asia-RiCE is composed of national teams that are actively contributing to the Crop Monitor for AMIS and developing technical demonstrations of rice crop monitoring activities using both Synthetic Aperture Radar (SAR) data (Radarsat-2 from 2013; Sentinel-1 and ALOS-2 from 2015; TerraSAR-X, Cosmo-SkyMed, RISAT, and others) and optical imagery (such as from MODIS, SPOT-5, Landsat, and Sentinel-2) for 100x100km Technical Demonstration Sites (TDS) as a phase 1 (2013-2015) in Asia. with satellite -based cultivated area and growing stage map. The Asia-RiCE teams are also developing satellite-based agro-met information for rice crop outlook, crop calendars and damage assessment in cooperation with ASEAN food security information system (AFSIS) for selected countries (currently Indonesia, Thailand, Vietnam, Philippine, and Japan; http://www.afsisnc.org/blog), using JAXA's Satellite-based MonItoring Network system as a contribution to the FAO AMIS outlook (JASMIN) with University of Tokyo (http://suzaku.eorc.jaxa.jp/cgi-bin/gcomw/jasm/jasm_top.cgi). Because of continous El Nino in South East Asia, there are less precipitation and rain fall pattern change in South East Asia, crop pattern has been changed and production may be decreased, especially for dry season crop. JAXA provides drought index (KBDI) and accumulated precipitation of Tak province, Thailand where main reservior is located, to AFSIS and national experts to assess rice crop outlook and NDVI time seriese to Ang Tong province where is main rice production area in downstream area of that reservior.From 2016 as a phase 2, Asia-RiCE initiative deploy up-scaling activity from a province (100x100km) to major crop areas or entire country to implement operational use for rice crop production information in low Mekong, Vietnam and top 10 provinces in Indonesia using space based technology. This paper reports this year activity of 2016 accomplishment and way forward.

[Effects of different multiple cropping systems on paddy field weed community under long term paddy-upland rotation].

PubMed

Yang, Bin-Juan; Huang, Guo-Qin; Xu, Ning; Wang, Shu-Bin

2013-09-01

Based on a long term field experiment, this paper studied the effects of different multiple cropping systems on the weed community composition and species diversity under paddy-upland rotation. The multiple cropping rotation systems could significantly decrease weed density and inhibited weed growth. Among the rotation systems, the milk vetch-early rice-late maize --> milk vetchearly maize intercropped with early soybean-late rice (CCSR) had the lowest weed species dominance, which inhibited the dominant weeds and decreased their damage. Under different multiple cropping systems, the main weed community was all composed of Monochoia vaginalis, Echinochloa crusgalli, and Sagittaria pygmae, and the similarity of weed community was higher, with the highest similarity appeared in milk vetch-early rice-late maize intercropped with late soybean --> milk vetch-early maize-late rice (CSCR) and in CCSR. In sum, the multiple cropping rotations in paddy field could inhibit weeds to a certain extent, but attentions should be paid to the damage of some less important weeds.

Projected dryland cropping system shifts in the Pacific Northwest in response to climate change

USDA-ARS?s Scientific Manuscript database

Agriculture in the dryland region of the Inland Pacific Northwest (IPNW, including northern Idaho, eastern Washington and northern Oregon) is typically characterized based on annual rainfall and associated distribution of cropping systems that have evolved in response to biophysical and socio-econom...

Development and implementation of a GEOGLAM Crop Monitor web interface

NASA Astrophysics Data System (ADS)

Oliva, P.; Sanchez, A.; Humber, M. L.; Becker-Reshef, I.; Justice, C. J.; McGaughey, K.; Barker, B.

2016-12-01

Beginning in September 2013, the GEOGLAM Crop Monitor activity has provided earth observation (EO) data to a network of partners and collected crop assessments on a subnational basis through a web interface known as the Crop Assessment Tool. Based on the collection of monthly crop assessments, a monthly crop condition bulletin is published in the Agricultural Market Information System (AMIS) Market Monitor report. This workflow has been successfully applied to food security applications through the Early Warning Crop Monitor activity. However, a lack of timely and accurate information on crop conditions and prospects at the national scale is a critical issue in the majority of southern and eastern African countries and some South American countries. Such information is necessary for informed and prompt decision making in the face of emergencies, food insecurity and planning requirements for agricultural markets. This project addresses these needs through the development of relevant, user-friendly remote sensing monitor systems, collaborative internet technology, and collaboration with national and regional agricultural monitoring networks. By building on current projects and relationships established through the various GEOGLAM Crop Monitor activities, this project aims to ultimately provide EO-informed crop condition maps and charts designed for economics and policy oriented audiences, thereby providing quick and easy to understand products on crop conditions as the season progresses. Integrating these data and assessments vertically throughout the system provides a basis for regional sharing and collaboration in food security applications.

Benchmark study on glyphosate-resistant crop systems in the United States. Part 2: Perspectives.

PubMed

Owen, Micheal D K; Young, Bryan G; Shaw, David R; Wilson, Robert G; Jordan, David L; Dixon, Philip M; Weller, Stephen C

2011-07-01

A six-state, 5 year field project was initiated in 2006 to study weed management methods that foster the sustainability of genetically engineered (GE) glyphosate-resistant (GR) crop systems. The benchmark study field-scale experiments were initiated following a survey, conducted in the winter of 2005-2006, of farmer opinions on weed management practices and their views on GR weeds and management tactics. The main survey findings supported the premise that growers were generally less aware of the significance of evolved herbicide resistance and did not have a high recognition of the strong selection pressure from herbicides on the evolution of herbicide-resistant (HR) weeds. The results of the benchmark study survey indicated that there are educational challenges to implement sustainable GR-based crop systems and helped guide the development of the field-scale benchmark study. Paramount is the need to develop consistent and clearly articulated science-based management recommendations that enable farmers to reduce the potential for HR weeds. This paper provides background perspectives about the use of GR crops, the impact of these crops and an overview of different opinions about the use of GR crops on agriculture and society, as well as defining how the benchmark study will address these issues. Copyright © 2011 Society of Chemical Industry.

Changes in the potential multiple cropping system in response to climate change in China from 1960-2010.

PubMed

Liu, Luo; Xu, Xinliang; Zhuang, Dafang; Chen, Xi; Li, Shuang

2013-01-01

The multiple cropping practice is essential to agriculture because it has been shown to significantly increase the grain yield and promote agricultural economic development. In this study, potential multiple cropping systems in China are calculated based on meteorological observation data by using the Agricultural Ecology Zone (AEZ) model. Following this, the changes in the potential cropping systems in response to climate change between the 1960s and the 2010s were subsequently analyzed. The results indicate that the changes of potential multiple cropping systems show tremendous heterogeneity in respect to the spatial pattern in China. A key finding is that the magnitude of change of the potential cropping systems showed a pattern of increase both from northern China to southern China and from western China to eastern China. Furthermore, the area found to be suitable only for single cropping decreased, while the area suitable for triple cropping increased significantly from the 1960s to the 2000s. During the studied period, the potential multiple cropping index (PMCI) gap between rain-fed and irrigated scenarios increased from 18% to 24%, which indicated noticeable growth of water supply limitations under the rain-fed scenario. The most significant finding of this research was that from the 1960s to the 2000s climate change had led to a significant increase of PMCI by 13% under irrigated scenario and 7% under rain-fed scenario across the whole of China. Furthermore, the growth of the annual mean temperature is identified as the main reason underlying the increase of PMCI. It has also been noticed that across China the changes of potential multiple cropping systems under climate change were different from region to region.

Water uptake depth analyses using stable water isotopes in rice-based cropping systems in Southeastern Asia

NASA Astrophysics Data System (ADS)

Mahindawansha, Amani; Kraft, Philipp; Orlowski, Natalie; Racela, Healthcliff S. U.; Breuer, Lutz

2017-04-01

Rice is one of the most water-consuming crop in the world. Understanding water source utilization of rice-based cropping systems will help to improve water use efficiency (WUE) in paddy management. The objectives of our study were to (1) determine the contributions of various water sources to plant growth in diversified rice-based production systems (wet rice, aerobic rice) (2) investigate water uptake depths at different maturity periods during wet and dry conditions, and (3) calculate WUE of the cropping systems. Our field experiment is based on changes of stable water isotope concentrations in the soil-plant-atmosphere continuum due to transpiration and evaporation. Soil samples were collected together with root sampling from nine different depths under vegetative, reproductive, and matured periods of plant growth together with stem samples. Soil and plant samples were extracted by cryogenic vacuum extraction. Groundwater, surface water, rain, and irrigation water were sampled weekly. All water samples were analyzed for hydrogen and oxygen isotope ratios (δ2H and δ18O) via a laser spectroscope (Los Gatos DLT100). The direct inference approach, which is based on comparing isotopic compositions between plant stem water and soil water, were used to determine water sources taken up by plant. Multiple-source mass balance assessment can provide the estimated range of potential contributions of water from each soil depth to root water uptake of a crop. These estimations were used to determine the proportion of water from upper soil horizons and deep horizons for rice in different maturity periods during wet and dry seasons. Shallow soil water has the higher evaporation than from deeper soil water where the highest evaporation effect is at 5 cm depth (drying front). Water uptake is mostly taking place from surface water in the vegetative and between 5-10 cm in the reproductive period, since roots have grown widely and deeper in the reproductive stage. This will be helpful to understand the WUE and identify the most efficient water management system and the influence of groundwater and surface water during both seasons in rice-based cropping ecosystems by using means of stable water isotope.

Consideration in selecting crops for the human-rated life support system: a Linear Programming model

NASA Technical Reports Server (NTRS)

Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.; Henninger, D. L. (Principal Investigator)

1996-01-01

A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.

Consideration in selecting crops for the human-rated life support system: a linear programming model

NASA Astrophysics Data System (ADS)

Wheeler, E. F.; Kossowski, J.; Goto, E.; Langhans, R. W.; White, G.; Albright, L. D.; Wilcox, D.

A Linear Programming model has been constructed which aids in selecting appropriate crops for CELSS (Controlled Environment Life Support System) food production. A team of Controlled Environment Agriculture (CEA) faculty, staff, graduate students and invited experts representing more than a dozen disciplines, provided a wide range of expertise in developing the model and the crop production program. The model incorporates nutritional content and controlled-environment based production yields of carefully chosen crops into a framework where a crop mix can be constructed to suit the astronauts' needs. The crew's nutritional requirements can be adequately satisfied with only a few crops (assuming vitamin mineral supplements are provided) but this will not be satisfactory from a culinary standpoint. This model is flexible enough that taste and variety driven food choices can be built into the model.

Biofuel as an Integrated Farm Drainage Management crop: A bioeconomic analysis

NASA Astrophysics Data System (ADS)

Levers, L. R.; Schwabe, K. A.

2017-04-01

Irrigated agricultural lands in arid regions often suffer from soil salinization and lack of drainage, which affect environmental quality and productivity. Integrated Farm Drainage Management (IFDM) systems, where drainage water generated from higher-valued crops grown on high quality soils are used to irrigate salt-tolerant crops grown on marginal soils, is one possible strategy for managing salinity and drainage problems. If the IFDM crop were a biofuel crop, both environmental and private benefits may be generated; however, little is known about this possibility. As such, we develop a bioeconomic programming model of irrigated agricultural production to examine the role salt-tolerant biofuel crops might play within an IFDM system. Our results, generated by optimizing profits over land, water, and crop choice decisions subject to resource constraints, suggest that based on the private profits alone, biofuel crops can be a competitive alternative to the common practices of land retirement and nonbiofuel crop production under both low to high drainage water salinity. Yet IFDM biofuel crop production generates 30-35% fewer GHG emissions than the other strategies. The private market competitiveness coupled with the public good benefits may justify policy changes encouraging the growth of IFDM biofuel crops in arid agricultural areas globally.

Environmental health impacts of feeding crops to farmed fish.

PubMed

Fry, Jillian P; Love, David C; MacDonald, Graham K; West, Paul C; Engstrom, Peder M; Nachman, Keeve E; Lawrence, Robert S

2016-05-01

Half of the seafood consumed globally now comes from aquaculture, or farmed seafood. Aquaculture therefore plays an increasingly important role in the global food system, the environment, and human health. Traditionally, aquaculture feed has contained high levels of wild fish, which is unsustainable for ocean ecosystems as demand grows. The aquaculture industry is shifting to crop-based feed ingredients, such as soy, to replace wild fish as a feed source and allow for continued industry growth. This shift fundamentally links seafood production to terrestrial agriculture, and multidisciplinary research is needed to understand the ecological and environmental health implications. We provide basic estimates of the agricultural resource use associated with producing the top five crops used in commercial aquaculture feed. Aquaculture's environmental footprint may now include nutrient and pesticide runoff from industrial crop production, and depending on where and how feed crops are produced, could be indirectly linked to associated negative health outcomes. We summarize key environmental health research on health effects associated with exposure to air, water, and soil contaminated by industrial crop production. Our review also finds that changes in the nutritional content of farmed seafood products due to altered feed composition could impact human nutrition. Based on our literature reviews and estimates of resource use, we present a conceptual framework describing the potential links between increasing use of crop-based ingredients in aquaculture and human health. Additional data and geographic sourcing information for crop-based ingredients are needed to fully assess the environmental health implications of this trend. This is especially critical in the context of a food system that is using both aquatic and terrestrial resources at unsustainable rates. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrating NASA Earth Science Enterprise (ESE) Data Into Global Agricultural Decision Support Systems

NASA Astrophysics Data System (ADS)

Teng, W.; Kempler, S.; Chiu, L.; Doraiswamy, P.; Liu, Z.; Milich, L.; Tetrault, R.

2003-12-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of U.S. agricultural products and for global food security. Two major operational users of satellite remote sensing for global crop monitoring are the USDA Foreign Agricultural Service (FAS) and the U.N. World Food Programme (WFP). The primary goal of FAS is to improve foreign market access for U.S. agricultural products. The WFP uses food to meet emergency needs and to support economic and social development. Both use global agricultural decision support systems that can integrate and synthesize a variety of data sources to provide accurate and timely information on global crop conditions. The Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (GES DAAC) has begun a project to provide operational solutions to FAS and WFP, by fully leveraging results from previous work, as well as from existing capabilities of the users. The GES DAAC has effectively used its recently developed prototype TRMM Online Visualization and Analysis System (TOVAS) to provide ESE data and information to the WFP for its agricultural drought monitoring efforts. This prototype system will be evolved into an Agricultural Information System (AIS), which will operationally provide ESE and other data products (e.g., rainfall, land productivity) and services, to be integrated into and thus enhance the existing GIS-based, decision support systems of FAS and WFP. Agriculture-oriented, ESE data products (e.g., MODIS-based, crop condition assessment product; TRMM derived, drought index product) will be input to a crop growth model in collaboration with the USDA Agricultural Research Service, to generate crop condition and yield prediction maps. The AIS will have the capability for remotely accessing distributed data, by being compliant with community-based interoperability standards, enabling easy access to agriculture-related products from other data producers. The AIS? system approach will provide a generic mechanism for easily incorporating new products and making them accessible to users.

Systems biology-based approaches toward understanding drought tolerance in food crops.

PubMed

Jogaiah, Sudisha; Govind, Sharathchandra Ramsandra; Tran, Lam-Son Phan

2013-03-01

Economically important crops, such as maize, wheat, rice, barley, and other food crops are affected by even small changes in water potential at important growth stages. Developing a comprehensive understanding of host response to drought requires a global view of the complex mechanisms involved. Research on drought tolerance has generally been conducted using discipline-specific approaches. However, plant stress response is complex and interlinked to a point where discipline-specific approaches do not give a complete global analysis of all the interlinked mechanisms. Systems biology perspective is needed to understand genome-scale networks required for building long-lasting drought resistance. Network maps have been constructed by integrating multiple functional genomics data with both model plants, such as Arabidopsis thaliana, Lotus japonicus, and Medicago truncatula, and various food crops, such as rice and soybean. Useful functional genomics data have been obtained from genome-wide comparative transcriptome and proteome analyses of drought responses from different crops. This integrative approach used by many groups has led to identification of commonly regulated signaling pathways and genes following exposure to drought. Combination of functional genomics and systems biology is very useful for comparative analysis of other food crops and has the ability to develop stable food systems worldwide. In addition, studying desiccation tolerance in resurrection plants will unravel how combination of molecular genetic and metabolic processes interacts to produce a resurrection phenotype. Systems biology-based approaches have helped in understanding how these individual factors and mechanisms (biochemical, molecular, and metabolic) "interact" spatially and temporally. Signaling network maps of such interactions are needed that can be used to design better engineering strategies for improving drought tolerance of important crop species.

The use of seasonal forecasts in a crop failure early warning system for West Africa

NASA Astrophysics Data System (ADS)

Nicklin, K. J.; Challinor, A.; Tompkins, A.

2011-12-01

Seasonal rainfall in semi-arid West Africa is highly variable. Farming systems in the region are heavily dependent on the monsoon rains leading to large variability in crop yields and a population that is vulnerable to drought. The existing crop yield forecasting system uses observed weather to calculate a water satisfaction index, which is then related to expected crop yield (Traore et al, 2006). Seasonal climate forecasts may be able to increase the lead-time of yield forecasts and reduce the humanitarian impact of drought. This study assesses the potential for a crop failure early warning system, which uses dynamic seasonal forecasts and a process-based crop model. Two sets of simulations are presented. In the first, the crop model is driven with observed weather as a control run. Observed rainfall is provided by the GPCP 1DD data set, whilst observed temperature and solar radiation data are given by the ERA-Interim reanalysis. The crop model used is the groundnut version of the General Large Area Model for annual crops (GLAM), which has been designed to operate on the grids used by seasonal weather forecasts (Challinor et al, 2004). GLAM is modified for use in West Africa by allowing multiple planting dates each season, replanting failed crops and producing parameter sets for Spanish- and Virginia- type West African groundnut. Crop yields are simulated for three different assumptions concerning the distribution and relative abundance of Spanish- and Virginia- type groundnut. Model performance varies with location, but overall shows positive skill in reproducing observed crop failure. The results for the three assumptions are similar, suggesting that the performance of the system is limited by something other than information on the type of groundnut grown. In the second set of simulations the crop model is driven with observed weather up to the forecast date, followed by ECMWF system 3 seasonal forecasts until harvest. The variation of skill with forecast date is assessed along with the extent to which forecasts can be improved by bias correction of the rainfall data. Two forms of bias correction are applied: a novel method of spatially bias correcting daily data, and statistical bias correction of the frequency and intensity distribution. Results are presented using both observed yields and the control run as the reference for verification. The potential for current dynamic seasonal forecasts to form part of an operational system giving timely and accurate warnings of crop failure is discussed. Traore S.B. et al., 2006. A Review of Agrometeorological Monitoring Tools and Methods Used in the West African Sahel. In: Motha R.P. et al., Strengthening Operational Agrometeorological Services at the National Level. Technical Bulletin WAOB-2006-1 and AGM-9, WMO/TD No. 1277. Pages 209-220. www.wamis.org/agm/pubs/agm9/WMO-TD1277.pdf Challinor A.J. et al., 2004. Design and optimisation of a large-area process based model for annual crops. Agric. For. Meteorol. 124, 99-120.

Eight years of Conservation Agriculture-based cropping systems research in Eastern Africa to conserve soil and water and mitigate effects of climate change

NASA Astrophysics Data System (ADS)

Araya, Tesfay; Nyssen, Jan; Govaerts, Bram; Lanckriet, Sil; Baudron, Frédéric; Deckers, Jozef; Cornelis, Wim

2014-05-01

In Ethiopia, repeated plowing, complete removal of crop residues at harvest, aftermath grazing of crop fields and occurrence of repeated droughts have reduced the biomass return to the soil and aggravated cropland degradation. Conservation Agriculture (CA)-based resource conserving cropping systems may reduce runoff and soil erosion, and improve soil quality, thereby increasing crop productivity. Thus, a long-term tillage experiment has been carried out (2005 to 2012) on a Vertisol to quantify - among others - changes in runoff and soil loss for two local tillage practices, modified to integrate CA principles in semi-arid northern Ethiopia. The experimental layout was a randomized complete block design with three replications on permanent plots of 5 m by 19 m. The tillage treatments were (i) derdero+ (DER+) with a furrow and permanent raised bed planting system, ploughed only once at planting by refreshing the furrow from 2005 to 2012 and 30% standing crop residue retention, (ii) terwah+ (TER+) with furrows made at 1.5 m interval, plowed once at planting, 30% standing crop residue retention and fresh broad beds, and (iii) conventional tillage (CT) with a minimum of three plain tillage operations and complete removal of crop residues. All the plowing and reshaping of the furrows was done using the local ard plough mahresha and wheat, teff, barley and grass pea were grown. Glyphosate was sprayed starting from the third year onwards (2007) at 2 l ha-1 before planting to control pre-emergent weeds in CA plots. Runoff and soil loss were measured daily. Soil water content was monitored every 6 days. Significantly different (p<0.05) runoff coefficients averaged over 8 years were 14, 20 and 27% for DER+, TER+ and CT, respectively. Mean soil losses were 4 t ha-1 y-1 in DER+, 13 in TER+ and 18 in CT. Soil water storage during the growing season was constantly higher in CA-based systems compared with CT. A period of at least three years of cropping was required before improvements in crop yield became significant. Further, modeling of the sediment budgets shows that total soil loss due to sheet and rill erosion in cropland, when CA would be practiced at large scale in a 180 ha catchment, would reduce to 581 t y-1, instead of 1109 t y-1 under the current farmer practice. Using NASA/GISS Model II precipitation projections of IPCC scenario A1FI, CA is estimated to reduce soil loss and runoff and mitigate the effect of increased rainfall due to climate change. For smallholder farmers in semi-arid agro-ecosystems, CA-based systems constitute a field rainwater and soil conservation improvement strategy that enhances crop and economic productivity and reduces siltation of reservoirs, especially under changing climate. The reduction in draught power requirement would enable a reduction in oxen density and crop residue demand for livestock feed, which would encourage smallholder farmers to increase biomass return to the soil. Adoption of CA-based systems in the study area requires further work to improve smallholder farmers' awareness on benefits, to guarantee high standards during implementation and to design appropriate weed management strategies.

A new nitrogen index for assessment of nitrogen management practices of Andean Mountain cropping systems of Ecuador

USDA-ARS?s Scientific Manuscript database

Corn (Zea mays L.) is the most important crop for food security in several regions of Ecuador. Small farmers are using nitrogen (N) fertilizer without technical advice based on soil, crop and climatological data. The scientific literature lacks studies where tools are validated that can be used to q...

How efficiently do corn- and soybean-based cropping systems use water? A systems modeling analysis.

PubMed

Dietzel, Ranae; Liebman, Matt; Ewing, Robert; Helmers, Matt; Horton, Robert; Jarchow, Meghann; Archontoulis, Sotirios

2016-02-01

Agricultural systems are being challenged to decrease water use and increase production while climate becomes more variable and the world's population grows. Low water use efficiency is traditionally characterized by high water use relative to low grain production and usually occurs under dry conditions. However, when a cropping system fails to take advantage of available water during wet conditions, this is also an inefficiency and is often detrimental to the environment. Here, we provide a systems-level definition of water use efficiency (sWUE) that addresses both production and environmental quality goals through incorporating all major system water losses (evapotranspiration, drainage, and runoff). We extensively calibrated and tested the Agricultural Production Systems sIMulator (APSIM) using 6 years of continuous crop and soil measurements in corn- and soybean-based cropping systems in central Iowa, USA. We then used the model to determine water use, loss, and grain production in each system and calculated sWUE in years that experienced drought, flood, or historically average precipitation. Systems water use efficiency was found to be greatest during years with average precipitation. Simulation analysis using 28 years of historical precipitation data, plus the same dataset with ± 15% variation in daily precipitation, showed that in this region, 430 mm of seasonal (planting to harvesting) rainfall resulted in the optimum sWUE for corn, and 317 mm for soybean. Above these precipitation levels, the corn and soybean yields did not increase further, but the water loss from the system via runoff and drainage increased substantially, leading to a high likelihood of soil, nutrient, and pesticide movement from the field to waterways. As the Midwestern United States is predicted to experience more frequent drought and flood, inefficiency of cropping systems water use will also increase. This work provides a framework to concurrently evaluate production and environmental performance of cropping systems. © 2015 John Wiley & Sons Ltd.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Satellite Based Cropland Carbon Monitoring System

NASA Astrophysics Data System (ADS)

Bandaru, V.; Jones, C. D.; Sedano, F.; Sahajpal, R.; Jin, H.; Skakun, S.; Pnvr, K.; Kommareddy, A.; Reddy, A.; Hurtt, G. C.; Izaurralde, R. C.

2017-12-01

Agricultural croplands act as both sources and sinks of atmospheric carbon dioxide (CO2); absorbing CO2 through photosynthesis, releasing CO2 through autotrophic and heterotrophic respiration, and sequestering CO2 in vegetation and soils. Part of the carbon captured in vegetation can be transported and utilized elsewhere through the activities of food, fiber, and energy production. As well, a portion of carbon in soils can be exported somewhere else by wind, water, and tillage erosion. Thus, it is important to quantify how land use and land management practices affect the net carbon balance of croplands. To monitor the impacts of various agricultural activities on carbon balance and to develop management strategies to make croplands to behave as net carbon sinks, it is of paramount importance to develop consistent and high resolution cropland carbon flux estimates. Croplands are typically characterized by fine scale heterogeneity; therefore, for accurate carbon flux estimates, it is necessary to account for the contribution of each crop type and their spatial distribution. As part of NASA CMS funded project, a satellite based Cropland Carbon Monitoring System (CCMS) was developed to estimate spatially resolved crop specific carbon fluxes over large regions. This modeling framework uses remote sensing version of Environmental Policy Integrated Climate Model and satellite derived crop parameters (e.g. leaf area index (LAI)) to determine vertical and lateral carbon fluxes. The crop type LAI product was developed based on the inversion of PRO-SAIL radiative transfer model and downscaled MODIS reflectance. The crop emergence and harvesting dates were estimated based on MODIS NDVI and crop growing degree days. To evaluate the performance of CCMS framework, it was implemented over croplands of Nebraska, and estimated carbon fluxes for major crops (i.e. corn, soybean, winter wheat, grain sorghum, alfalfa) grown in 2015. Key findings of the CCMS framework will be presented and discussed some of which include 1) comparison of remote sensing based crop type LAI and crop phenology estimates with observed field scale data 2) comparison of carbon flux estimates from CCMS framework with measured fluxes at flux tower sites 3) regional scale differences in carbon fluxes among various crops in Nebraska.

Effects of crop species richness on pest-natural enemy systems based on an experimental model system using a microlandscape.

PubMed

Zhao, ZiHua; Shi, PeiJian; Men, XingYuan; Ouyang, Fang; Ge, Feng

2013-08-01

The relationship between crop richness and predator-prey interactions as they relate to pest-natural enemy systems is a very important topic in ecology and greatly affects biological control services. The effects of crop arrangement on predator-prey interactions have received much attention as the basis for pest population management. To explore the internal mechanisms and factors driving the relationship between crop richness and pest population management, we designed an experimental model system of a microlandscape that included 50 plots and five treatments. Each treatment had 10 repetitions in each year from 2007 to 2010. The results showed that the biomass of pests and their natural enemies increased with increasing crop biomass and decreased with decreasing crop biomass; however, the effects of plant biomass on the pest and natural enemy biomass were not significant. The relationship between adjacent trophic levels was significant (such as pests and their natural enemies or crops and pests), whereas non-adjacent trophic levels (crops and natural enemies) did not significantly interact with each other. The ratio of natural enemy/pest biomass was the highest in the areas of four crop species that had the best biological control service. Having either low or high crop species richness did not enhance the pest population management service and lead to loss of biological control. Although the resource concentration hypothesis was not well supported by our results, high crop species richness could suppress the pest population, indicating that crop species richness could enhance biological control services. These results could be applied in habitat management aimed at biological control, provide the theoretical basis for agricultural landscape design, and also suggest new methods for integrated pest management.

A generic model for estimating biomass accumulation and greenhouse gas emissions from perennial crops

NASA Astrophysics Data System (ADS)

Ledo, Alicia; Heathcote, Richard; Hastings, Astley; Smith, Pete; Hillier, Jonathan

2017-04-01

Agriculture is essential to maintain humankind but is, at the same time, a substantial emitter of greenhouse gas (GHG) emissions. With a rising global population, the need for agriculture to provide secure food and energy supply is one of the main human challenges. At the same time, it is the only sector which has significant potential for negative emissions through the sequestration of carbon and offsetting via supply of feedstock for energy production. Perennial crops accumulate carbon during their lifetime and enhance organic soil carbon increase via root senescence and decomposition. However, inconsistency in accounting for this stored biomass undermines efforts to assess the benefits of such cropping systems when applied at scale. A consequence of this exclusion is that efforts to manage this important carbon stock are neglected. Detailed information on carbon balance is crucial to identify the main processes responsible for greenhouse gas emissions in order to develop strategic mitigation programs. Perennial crops systems represent 30% in area of total global crop systems, a considerable amount to be ignored. Furthermore, they have a major standing both in the bioenergy and global food industries. In this study, we first present a generic model to calculate the carbon balance and GHGs emissions from perennial crops, covering both food and bioenergy crops. The model is composed of two simple process-based sub-models, to cover perennial grasses and other perennial woody plants. The first is a generic individual based sub-model (IBM) covering crops in which the yield is the fruit and the plant biomass is an unharvested residue. Trees, shrubs and climbers fall into this category. The second model is a generic area based sub-model (ABM) covering perennial grasses, in which the harvested part includes some of the plant parts in which the carbon storage is accounted. Most second generation perennial bioenergy crops fall into this category. Both generic sub-models presented in this paper can be parametrized for different crops. Quantifying CO2 capture by plants and biomass accumulation and changes in soil carbon, are key in evaluating the impacts of perennial crops in life cycle analysis. We then use this model to illustrate the importance of biomass in the overall GHG estimation from four important perennial crops - sugarcane, Miscanthus, coffee, and apples - which were chosen to cover tropical and temperate regions, trees and grasses, and energy and food supply.

Development and Deployment of a Short Rotation Woody Crops Harvesting System Based on a Case New Holland Forage Harvester and SRC Woody Crop Header

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisenbies, Mark; Volk, Timothy; Abrahamson, Lawrence

Biomass for biofuels, bioproducts and bioenergy can be sourced from forests, agricultural crops, various residue streams, and dedicated woody or herbaceous crops. Short rotation woody crops (SRWC), like willow and hybrid poplar, are perennial cropping systems that produce a number of environmental and economic development benefits in addition to being a renewable source of biomass that can be produced on marginal land. Both hybrid poplar and willow have several characteristics that make them an ideal feedstock for biofuels, bioproducts, and bioenergy; these include high yields that can be obtained in three to four years, ease of cultivar propagation from dormantmore » cuttings, a broad underutilized genetic base, ease of breeding, ability to resprout after multiple harvests, and feedstock composition similar to other sources of woody biomass. Despite the range of benefits associated with SRWC systems, their deployment has been restricted by high costs, low market acceptance associated with inconsistent chip quality (see below for further explanation), and misperceptions about other feedstock characteristics (see below for further explanation). Harvesting of SRWC is the largest single cost factor (~1/3 of the final delivered cost) in the feedstock supply system. Harvesting is also the second largest input of primary fossil energy in the system after commercial N fertilizer, accounting for about one third of the input. Therefore, improving the efficiency of the harvesting system has the potential to reduce both cost and environmental impact. At the start of this project, we projected that improving the overall efficiency of the harvesting system by 25% would reduce the delivered cost of SRWC by approximately $0.50/MMBtu (or about $7.50/dry ton). This goal was exceeded over the duration of this project, as noted below.« less

WheatGenome.info: an integrated database and portal for wheat genome information.

PubMed

Lai, Kaitao; Berkman, Paul J; Lorenc, Michal Tadeusz; Duran, Chris; Smits, Lars; Manoli, Sahana; Stiller, Jiri; Edwards, David

2012-02-01

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement. We provide a variety of web-based systems hosting wheat genome and genomic data to support wheat research and crop improvement. WheatGenome.info is an integrated database resource which includes multiple web-based applications. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second-generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This system includes links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/.

Impact of preceding crop on alfalfa competitiveness with weeds

USDA-ARS?s Scientific Manuscript database

Organic producers would like to include no-till practices in their farming systems. We are seeking to develop a continuous no-till system for organic farming, based on a complex rotation that includes a 3-year sequence of alfalfa. In this study, we evaluated impact of preceding crop on weed infest...

Recycling of Na in advanced life support: strategies based on crop production systems.

PubMed

Guntur, S V; Mackowiak, C; Wheeler, R M

1999-01-01

Sodium is an essential dietary requirement in human nutrition, but seldom holds much importance as a nutritional element for crop plants. In Advanced Life Support (ALS) systems, recycling of gases, nutrients, and water loops is required to improve system closure. If plants are to play a significant role in recycling of human wastes, Na will need to accumulate in edible tissues for return to the crew diet. If crops fail to accumulate the incoming Na into edible tissues, Na could become a threat to the hydroponic food production system by increasing the nutrient solution salinity. Vegetable crops of Chenopodiaceae such as spinach, table beet, and chard may have a high potential to supply Na to the human diet, as Na can substitute for K to a large extent in metabolic processes of these crops. Various strategies are outlined that include both genetic and environmental management aspects to optimize the Na recovery from waste streams and their resupply through the human diet in ALS.

Hydroponic Crop Production using Recycled Nutrients from Inedible Crop Residues

NASA Technical Reports Server (NTRS)

Garland, Jay L.; Mackowiak, Cheryl L.; Sager, John C.

1993-01-01

The coupling of plant growth and waste recycling systems is an important step toward the development of bioregenerative life support systems. This research examined the effectiveness of two alternative methods for recycling nutrients from the inedible fraction (residue) of candidate crops in a bioregenerative system as follows: (1) extraction in water, or leaching, and (2) combustion at 550 C, with subsequent reconstitution of the ash in acid. The effectiveness of the different methods was evaluated by (1) comparing the percent recovery of nutrients, and (2) measuring short- and long-term plant growth in hydroponic solutions, based on recycled nutrients.

[Water-saving mechanisms of intercropping system in improving cropland water use efficiency].

PubMed

Zhang, Feng-Yun; Wu, Pu-Te; Zhao, Xi-Ning; Cheng, Xue-Feng

2012-05-01

Based on the multi-disciplinary researches, and in terms of the transformation efficiency of surface water to soil water, availability of cropland soil water, crop canopy structure, total irrigation volume needed on a given area, and crop yield, this paper discussed the water-saving mechanisms of intercropping system in improving cropland water use efficiency. Intercropping system could promote the full use of cropland water by plant roots, increase the water storage in root zone, reduce the inter-row evaporation and control excessive transpiration, and create a special microclimate advantageous to the plant growth and development. In addition, intercropping system could optimize source-sink relationship, provide a sound foundation for intensively utilizing resources temporally and spatially, and increase the crop yield per unit area greatly without increase of water consumption, so as to promote the crop water use efficiency effectively.

A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. A thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temp...

Potential economic benefits of adapting agricultural production systems to future climate change

USGS Publications Warehouse

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Potential economic benefits of adapting agricultural production systems to future climate change.

PubMed

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

NASA Astrophysics Data System (ADS)

Sawant, S. A.; Chakraborty, M.; Suradhaniwar, S.; Adinarayana, J.; Durbha, S. S.

2016-06-01

Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (http://earthexplorer.usgs.gov/). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system observed relevant weather parameters for crop ET estimation. The results show that time series EO based crop growth stage estimates provide better information about geographically separated citrus orchards. Attempts are being made to estimate regional variations in citrus crop water requirement for effective irrigation planning. In future high resolution Sentinel 2 observations from European Space Agency (ESA) will be used to fill the time gaps and to get better understanding about citrus crop canopy parameters.

A triangular climate-based decision model to forecast crop anomalies in Kenya

NASA Astrophysics Data System (ADS)

Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

2017-12-01

By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

Uncertainties in Integrated Climate Change Impact Assessments by Sub-setting GCMs Based on Annual as well as Crop Growing Period under Rice Based Farming System of Indo-Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Pillai, S. N.; Singh, H.; Panwar, A. S.; Meena, M. S.; Singh, S. V.; Singh, B.; Paudel, G. P.; Baigorria, G. A.; Ruane, A. C.; McDermid, S.; Boote, K. J.; Porter, C.; Valdivia, R. O.

2016-12-01

Integrated assessment of climate change impact on agricultural productivity is a challenge to the scientific community due to uncertainties of input data, particularly the climate, soil, crop calibration and socio-economic dataset. However, the uncertainty due to selection of GCMs is the major source due to complex underlying processes involved in initial as well as the boundary conditions dealt in solving the air-sea interactions. Under Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Indo-Gangetic Plains Regional Research Team investigated the uncertainties caused due to selection of GCMs through sub-setting based on annual as well as crop-growth period of rice-wheat systems in AgMIP Integrated Assessment methodology. The AgMIP Phase II protocols were used to study the linking of climate-crop-economic models for two study sites Meerut and Karnal to analyse the sensitivity of current production systems to climate change. Climate Change Projections were made using 29 CMIP5 GCMs under RCP4.5 and RCP 8.5 during mid-century period (2040-2069). Two crop models (APSIM & DSSAT) were used. TOA-MD economic model was used for integrated assessment. Based on RAPs (Representative Agricultural Pathways), some of the parameters, which are not possible to get through modeling, derived from literature and interactions with stakeholders incorporated into the TOA-MD model for integrated assessment.

Adapting crop rotations to climate change in regional impact modelling assessments.

PubMed

Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

2018-03-01

The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used to develop improved regional impact assessments for situations where multi-crop rotations better represent predominant agricultural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA

NASA Astrophysics Data System (ADS)

Fraisse, C.

2014-12-01

AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.

Forage-based dairying in a water-limited future: use of models to investigate farming system adaptation in southern Australia.

PubMed

Chapman, D F; Dassanayake, K; Hill, J O; Cullen, B R; Lane, N

2012-07-01

The irrigated dairy industry in southern Australia has experienced significant restrictions in irrigation water allocations since 2005, consistent with climate change impact predictions for the region. Simulation models of pasture growth (DairyMod), crop yield (Agricultural Production Systems Simulator, APSIM), and dairy system management and production (UDDER) were used in combination to investigate a range of forage options that may be capable of sustaining dairy business profitability under restricted water-allocation scenarios in northern Victoria, Australia. A total of 23 scenarios were simulated and compared with a base farm system (100% of historical water allocations, grazed perennial ryegrass pasture with supplements; estimated operating surplus $A2,615/ha at a milk price of $A4.14/kg of milk solids). Nine simulations explored the response of the base farm to changes in stocking rate or the implementation of a double cropping rotation on 30% of farm area, or both. Five simulations explored the extreme scenario of dairying without any irrigation water. Two general responses to water restrictions were investigated in a further 9 simulations. Annual ryegrass grazed pasture, complemented by a double cropping rotation (maize grown in summer for silage, followed by either brassica forage crop and annual ryegrass for silage in winter and spring) on 30% of farm area, led to an estimated operating surplus of $A1746/ha at the same stocking rate as the base farm when calving was moved to autumn (instead of late winter, as in the base system). Estimated total irrigation water use was 2.7ML/ha compared with 5.4ML/ha for the base system. Summer-dormant perennial grass plus double cropping (30% of farm area) lifted operating surplus by a further $A100/ha if associated with autumn calving (estimated total irrigation water use 3.1ML/ha). Large shifts in the forage base of dairy farms could sustain profitability in the face of lower, and fluctuating, water allocations. However, changes in other strategic management policies, notably calving date and stocking rate, would be required, and these systems would be more complex to manage. The adaptation scenarios that resulted in the highest estimated operating surplus were those where at least 10 t of pasture or crop DM was grazed directly by cows per hectare per year, resulting in grazed pasture intake of at least 2 t of DM/cow, and at least 60% of all homegrown feed that was consumed was grazed directly. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Weather based risks and insurances for crop production in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Extreme weather events such as late frosts, droughts, heat waves and rain storms can have devastating effects on cropping systems. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The impact of extreme weather events particularly during the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event. The risk of soil moisture deficit increases towards harvesting, such that drought stress occurs in spring and summer. Conversely, waterlogging occurs mostly during early spring and autumn. Risks of temperature stress appear during winter and spring for chilling and during summer for heat. Since crop development is driven by thermal time and photoperiod, the regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. The risk profiles were subsequently confronted with yields, yield losses and insurance claims for different crops. Physically based crop models such as REGCROP assist in understanding the links between different factors causing crop damage as demonstrated for cropping systems in Belgium. Extreme weather events have already precipitated contraction of insurance coverage in some markets (e.g. hail insurance), and the process can be expected to continue if the losses or damages from such events increase in the future. Climate change will stress this further and impacts on crop growth are expected to be twofold, owing to the sensitive stages occurring earlier during the growing season and to the changes in return period of extreme weather events. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Weather based risks and insurances for agricultural production

NASA Astrophysics Data System (ADS)

Gobin, Anne

2015-04-01

Extreme weather events such as frost, drought, heat waves and rain storms can have devastating effects on cropping systems. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The principle of return periods or frequencies of natural hazards is adopted in many countries as the basis of eligibility for the compensation of associated losses. For adequate risk management and eligibility, hazard maps for events with a 20-year return period are often used. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The impact of extreme weather events particularly during the sensitive periods of the farming calendar therefore requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event in the farming calendar. Physically based crop models such as REGCROP (Gobin, 2010) assist in understanding the links between different factors causing crop damage. Subsequent examination of the frequency, magnitude and impacts of frost, drought, heat stress and soil moisture stress in relation to the cropping season and crop sensitive stages allows for risk profiles to be confronted with yields, yield losses and insurance claims. The methodology is demonstrated for arable food crops, bio-energy crops and fruit. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Greenhouse irrigation control system design based on ZigBee and fuzzy PID technology

NASA Astrophysics Data System (ADS)

Zhou, Bing; Yang, Qiliang; Liu, Kenan; Li, Peiqing; Zhang, Jing; Wang, Qijian

In order to achieve the water demand information accurately detect of the greenhouse crop and its precision irrigation automatic control, this article has designed a set of the irrigated control system based on ZigBee and fuzzy PID technology, which composed by the soil water potential sensor, CC2530F256 wireless microprocessor, IAR Embedded Workbench software development platform. And the time of Irrigation as the output .while the amount of soil water potential and crop growth cycle as the input. The article depended on Greenhouse-grown Jatropha to verify the object, the results show that the system can irrigate timely and appropriately according to the soil water potential and water demend of the different stages of Jatropha growth , which basically meet the design requirements. Therefore, the system has broad application prospects in the amount of greenhouse crop of fine control irrigation.

An Intelligent Crop Planning Tool for Controlled Ecological Life Support Systems

NASA Technical Reports Server (NTRS)

Whitaker, Laura O.; Leon, Jorge

1996-01-01

This paper describes a crop planning tool developed for the Controlled Ecological Life Support Systems (CELSS) project which is in the research phases at various NASA facilities. The Crop Planning Tool was developed to assist in the understanding of the long term applications of a CELSS environment. The tool consists of a crop schedule generator as well as a crop schedule simulator. The importance of crop planning tools such as the one developed is discussed. The simulator is outlined in detail while the schedule generator is touched upon briefly. The simulator consists of data inputs, plant and human models, and various other CELSS activity models such as food consumption and waste regeneration. The program inputs such as crew data and crop states are discussed. References are included for all nominal parameters used. Activities including harvesting, planting, plant respiration, and human respiration are discussed using mathematical models. Plans provided to the simulator by the plan generator are evaluated for their 'fitness' to the CELSS environment with an objective function based upon daily reservoir levels. Sample runs of the Crop Planning Tool and future needs for the tool are detailed.

Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

Estimating yield gaps at the cropping system level.

PubMed

Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

2017-05-01

Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

Remediation of Stratified Soil Acidity Through Surface Application of Lime in No-Till Cropping Systems

USDA-ARS?s Scientific Manuscript database

Yield reduction and reduced crop vigor, resulting from soil acidification, are of increasing concern in eastern Washington and northern Idaho. In this region, soil pH has been decreasing at an accelerated rate, primarily due to the long-term use of ammonium based fertilizers. In no-till systems, the...

High Resolution Modelling of Crop Response to Climate Change

NASA Astrophysics Data System (ADS)

Mirmasoudi, S. S.; Byrne, J. M.; MacDonald, R. J.; Lewis, D.

2014-12-01

Crop production is one of the most vulnerable sectors to climatic variability and change. Increasing atmospheric CO2 concentration and other greenhouse gases are causing increases in global temperature. In western North America, water supply is largely derived from mountain snowmelt. Climate change will have a significant impact on mountain snowpack and subsequently, the snow-derived water supply. This will strain water supplies and increase water demand in areas with substantial irrigation agriculture. Increasing temperatures may create heat stress for some crops regardless of soil water supply, and increasing surface O3 and other pollutants may damage crops and ecosystems. CO2 fertilization may or may not be an advantage in future. This work is part of a larger study that will address a series of questions based on a range of future climate scenarios for several watersheds in western North America. The key questions are: (1) how will snowmelt and rainfall runoff vary in future; (2) how will seasonal and inter-annual soil water supply vary, and how might that impacts food supplies; (3) how might heat stress impact (some) crops even with adequate soil water; (4) will CO2 fertilization alter crop yields; and (5) will pollution loads, particularly O3, cause meaningful changes to crop yields? The Generate Earth Systems Science (GENESYS) Spatial Hydrometeorological Model is an innovative, efficient, high-resolution model designed to assess climate driven changes in mountain snowpack derived water supplies. We will link GENESYS to the CROPWAT crop model system to assess climate driven changes in water requirement and associated crop productivity for a range of future climate scenarios. Literature bases studies will be utilised to develop approximate crop response functions for heat stress, CO2 fertilization and for O3 damages. The overall objective is to create modeling systems that allows meaningful assessment of agricultural productivity at a watershed scale under a range of climate scenarios.

Development and Testing of a Decision Making Based Method to Adjust Automatically the Harrowing Intensity

PubMed Central

Rueda-Ayala, Victor; Weis, Martin; Keller, Martina; Andújar, Dionisio; Gerhards, Roland

2013-01-01

Harrowing is often used to reduce weed competition, generally using a constant intensity across a whole field. The efficacy of weed harrowing in wheat and barley can be optimized, if site-specific conditions of soil, weed infestation and crop growth stage are taken into account. This study aimed to develop and test an algorithm to automatically adjust the harrowing intensity by varying the tine angle and number of passes. The field variability of crop leaf cover, weed density and soil density was acquired with geo-referenced sensors to investigate the harrowing selectivity and crop recovery. Crop leaf cover and weed density were assessed using bispectral cameras through differential images analysis. The draught force of the soil opposite to the direction of travel was measured with electronic load cell sensor connected to a rigid tine mounted in front of the harrow. Optimal harrowing intensity levels were derived in previously implemented experiments, based on the weed control efficacy and yield gain. The assessments of crop leaf cover, weed density and soil density were combined via rules with the aforementioned optimal intensities, in a linguistic fuzzy inference system (LFIS). The system was evaluated in two field experiments that compared constant intensities with variable intensities inferred by the system. A higher weed density reduction could be achieved when the harrowing intensity was not kept constant along the cultivated plot. Varying the intensity tended to reduce the crop leaf cover, though slightly improving crop yield. A real-time intensity adjustment with this system is achievable, if the cameras are attached in the front and at the rear or sides of the harrow. PMID:23669712

The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

NASA Technical Reports Server (NTRS)

Cacas, Joseph; Glaser, John; Copenhaver, Kenneth; May, George; Stephens, Karen

2008-01-01

The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

Crop candidates for the bioregenerative life support systems in China

NASA Astrophysics Data System (ADS)

Chunxiao, Xu; Hong, Liu

The use of plants for life support applications in space is appealing because of the multiple life support functions by the plants. Research on crops that were grown in the life support system to provide food and oxygen, remove carbon dioxide was begun from 1960. To select possible crops for research on the bioregenerative life support systems in China, criteria for the selection of potential crops were made, and selection of crops was carried out based on these criteria. The results showed that 14 crops including 4 food crops (wheat, rice, soybean and peanut) and 7 vegetables (Chinese cabbage, lettuce, radish, carrot, tomato, squash and pepper) won higher scores. Wheat ( Triticum aestivum L.), rice ( Oryza sativa L.), soybean ( Glycine max L.) and peanut ( Arachis hypogaea L.) are main food crops in China. Chinese cabbage ( Brassica campestris L. ssp. chinensis var. communis), lettuce ( Lactuca sativa L. var. longifolia Lam.), radish ( Raphanus sativus L.), carrot ( Daucus carota L. var. sativa DC.), tomato ( Lycopersicon escalentum L.), squash ( Cucurbita moschata Duch.) and pepper ( Capsicum frutescens L. var. longum Bailey) are 7 vegetables preferred by Chinese. Furthermore, coriander ( Coriandum sativum L.), welsh onion ( Allium fistulosum L. var. giganteum Makino) and garlic ( Allium sativum L.) were selected as condiments to improve the taste of space crew. To each crop species, several cultivars were selected for further research according to their agronomic characteristics.

Root system-based limits to agricultural productivity and efficiency: the farming systems context

PubMed Central

Thorup-Kristensen, Kristian; Kirkegaard, John

2016-01-01

Background There has been renewed global interest in both genetic and management strategies to improve root system function in order to improve agricultural productivity and minimize environmental damage. Improving root system capture of water and nutrients is an obvious strategy, yet few studies consider the important interactions between the genetic improvements proposed, and crop management at a system scale that will influence likely success. Scope To exemplify these interactions, the contrasting cereal-based farming systems of Denmark and Australia were used, where the improved uptake of water and nitrogen from deeper soil layers has been proposed to improve productivity and environmental outcomes in both systems. The analysis showed that water and nitrogen availability, especially in deeper layers (>1 m), was significantly affected by the preceding crops and management, and likely to interact strongly with deeper rooting as a specific trait of interest. Conclusions In the semi-arid Australian environment, grain yield impacts from storage and uptake of water from depth (>1 m) could be influenced to a stronger degree by preceding crop choice (0·42 t ha–1), pre-crop fallow management (0·65 t ha–1) and sowing date (0·63 t ha–1) than by current genetic differences in rooting depth (0·36 t ha–1). Matching of deep-rooted genotypes to management provided the greatest improvements related to deep water capture. In the wetter environment of Denmark, reduced leaching of N was the focus. Here the amount of N moving below the root zone was also influenced by previous crop choice or cover crop management (effects up to 85 kg N ha–1) and wheat crop sowing date (up to 45 kg ha–1), effects which over-ride the effects of differences in rooting depth among genotypes. These examples highlight the need to understand the farming system context and important G × E × M interactions in studies on proposed genetic improvements to root systems for improved productivity or environmental outcomes. PMID:27411680

Overcoming weed management challenges in cover crop-based organic rotational no-till soybean production in the Eastern US

USDA-ARS?s Scientific Manuscript database

Cover crop-based, organic rotational no-till soybean production has been gaining traction in the Eastern region of the United States because of the ability of this new system to enhance soil conservation, reduce labor requirements, and decrease diesel fuel use compared to traditional organic product...

Dry Matter Production, Nutrient Cycled and Removed, and Soil Fertility Changes in Yam-Based Cropping Systems with Herbaceous Legumes in the Guinea-Sudan Zone of Benin.

PubMed

Maliki, Raphiou; Sinsin, Brice; Floquet, Anne; Cornet, Denis; Malezieux, Eric; Vernier, Philippe

2016-01-01

Traditional yam-based cropping systems (shifting cultivation, slash-and-burn, and short fallow) often result in deforestation and soil nutrient depletion. The objective of this study was to determine the impact of yam-based systems with herbaceous legumes on dry matter (DM) production (tubers, shoots), nutrients removed and recycled, and the soil fertility changes. We compared smallholders' traditional systems (1-year fallow of Andropogon gayanus-yam rotation, maize-yam rotation) with yam-based systems integrated herbaceous legumes (Aeschynomene histrix/maize intercropping-yam rotation, Mucuna pruriens/maize intercropping-yam rotation). The experiment was conducted during the 2002 and 2004 cropping seasons with 32 farmers, eight in each site. For each of them, a randomized complete block design with four treatments and four replicates was carried out using a partial nested model with five factors: Year, Replicate, Farmer, Site, and Treatment. Analysis of variance (ANOVA) using the general linear model (GLM) procedure was applied to the dry matter (DM) production (tubers, shoots), nutrient contribution to the systems, and soil properties at depths 0-10 and 10-20 cm. DM removed and recycled, total N, P, and K recycled or removed, and soil chemical properties (SOM, N, P, K, and pH water) were significantly improved on yam-based systems with legumes in comparison with traditional systems.

Dry Matter Production, Nutrient Cycled and Removed, and Soil Fertility Changes in Yam-Based Cropping Systems with Herbaceous Legumes in the Guinea-Sudan Zone of Benin

PubMed Central

Sinsin, Brice; Floquet, Anne; Cornet, Denis; Malezieux, Eric; Vernier, Philippe

2016-01-01

Traditional yam-based cropping systems (shifting cultivation, slash-and-burn, and short fallow) often result in deforestation and soil nutrient depletion. The objective of this study was to determine the impact of yam-based systems with herbaceous legumes on dry matter (DM) production (tubers, shoots), nutrients removed and recycled, and the soil fertility changes. We compared smallholders' traditional systems (1-year fallow of Andropogon gayanus-yam rotation, maize-yam rotation) with yam-based systems integrated herbaceous legumes (Aeschynomene histrix/maize intercropping-yam rotation, Mucuna pruriens/maize intercropping-yam rotation). The experiment was conducted during the 2002 and 2004 cropping seasons with 32 farmers, eight in each site. For each of them, a randomized complete block design with four treatments and four replicates was carried out using a partial nested model with five factors: Year, Replicate, Farmer, Site, and Treatment. Analysis of variance (ANOVA) using the general linear model (GLM) procedure was applied to the dry matter (DM) production (tubers, shoots), nutrient contribution to the systems, and soil properties at depths 0–10 and 10–20 cm. DM removed and recycled, total N, P, and K recycled or removed, and soil chemical properties (SOM, N, P, K, and pH water) were significantly improved on yam-based systems with legumes in comparison with traditional systems. PMID:27446635

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Envirotyping for deciphering environmental impacts on crop plants.

PubMed

Xu, Yunbi

2016-04-01

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Root zone soil water dynamics and its effects on above ground biomass in cellulosic and grain based bioenergy crops of Midwest USA

NASA Astrophysics Data System (ADS)

Bhardwaj, A. K.; Hamilton, S. K.; van Dam, R. L.; Diker, K.; Basso, B.; Glbrc-Sustainability Thrust-4. 3 Biogeochemistry

2010-12-01

Root-zone soil moisture constitutes an important variable for hydrological and agronomic models. In agriculture, crop yields are directly related to soil moisture, levels that are most important in the root zone area of the soil. One of the most accurate in-situ methods that has established itself as a recognized standard around the world uses Time Domain Reflectometry (TDR) to determine volumetric water content of the soil. We used automated field-to-desk TDR based systems to monitor temporal (1-hr interval) soil moisture variability in 10 different bioenergy cropping systems at the Great Lakes Bioenergy Research Center’s (GLBRC) sustainability research site in south western Michigan, U.S.A. These crops range from high-diversity, low-input grass mixes to low-diversity, high-input crop monocultures. We equipped the 28 x 40 m vegetation plots with 30 cm long TDR probes at seven depths from 10 cm to 1.25 m below surface. The parent material at the site consists of coarse sandy glacial tills in which a soil with an approximately 50cm thick A-Bt horizon has developed. Additional equipment permanently installed for each system includes soil moisture access tubes, multi-depth temperature sensors, and multi-electrode resistivity arrays. The access tubes were monitored using a portable TDR system at bi-weekly intervals. 2D dipole-dipole electrical resistivity tomography (ERT) data are collected in 4-week intervals, while a subset of the electrodes is used for bi-hourly monitoring. The continuous scans (1 hr) provided us the real time changes in water content, replenishment and depletion, providing indications of water uptake by plant roots and potential seasonal water limitation of biomass accumulation. The results show significant seasonal variations between the crops and cropping systems. Significant relationships were observed between soil moisture stress, above-ground biomass and rooting characteristics. The overall goal of the study is to quantify the components of water balance, and identify water quality and water use implications of these cropping systems.Key Words

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gelfand, Ilya; Shcherbak, Iurii; Millar, Neville

Differences in soil nitrous oxide (N 2O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N 2O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn–soybean–wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N 2O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N 2O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30–80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop 9 management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N 2O-N ha -1 yr -1 and were best predicted by IPCC Tier 1 and DEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil NOmore » $$-\\atop{3}$$ pools (r 2 = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N 2O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes.« less

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt.

PubMed

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-11-09

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations.

Beyond the plot: technology extrapolation domains for scaling out agronomic science

NASA Astrophysics Data System (ADS)

Rattalino Edreira, Juan I.; Cassman, Kenneth G.; Hochman, Zvi; van Ittersum, Martin K.; van Bussel, Lenny; Claessens, Lieven; Grassini, Patricio

2018-05-01

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland. Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate ‘technology extrapolation domains’ based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment.

Designing bioenergy crop buffers to mitigate nitrous oxide emissions and water quality impacts from agriculture

NASA Astrophysics Data System (ADS)

Gopalakrishnan, G.; Negri, C. M.

2010-12-01

There is a strong societal need to evaluate and understand the environmental aspects of bioenergy production, especially due to the significant increases in production mandated by many countries, including the United States. Bioenergy is a land-based renewable resource and increases in production are likely to result in large-scale conversion of land from current uses to bioenergy crop production; potentially causing increases in the prices of food, land and agricultural commodities as well as disruption of ecosystems. Current research on the environmental sustainability of bioenergy has largely focused on the potential of bioenergy crops to sequester carbon and mitigate greenhouse gas (GHG) emissions and possible impacts on water quality and quantity. A key assumption in these studies is that bioenergy crops will be grown in a manner similar to current agricultural crops such as corn and hence would affect the environment similarly. This study presents a systems approach where the agricultural, energy and environmental sectors are considered as components of a single system, and bioenergy crops are used to design multi-functional agricultural landscapes that meet society’s requirements for food, energy and environmental protection. We evaluate the production of bioenergy crop buffers on marginal land and using degraded water and discuss the potential for growing cellulosic bioenergy crops such as miscanthus and switchgrass in optimized systems such that (1) marginal land is brought into productive use; (2) impaired water is used to boost yields (3); clean freshwater is left for other uses that require higher water quality; and (4) feedstock diversification is achieved that helps ecological sustainability, biodiversity, and economic opportunities for farmers. The process-based biogeochemical model DNDC was used to simulate crop yield, nitrous oxide production and nitrate concentrations in groundwater when bioenergy crops were grown in buffer strips adjacent to corn fields. The bioenergy crops used in this study were miscanthus, switchgrass and native prairie grasses. Results indicated that growing bioenergy crops in buffer strips mitigated nutrient runoff and reduced nitrate concentrations in groundwater to below EPA’s mandated drinking water limit (10 mg/l). Additionally, nitrous oxide emissions in these systems were reduced by 50-90% when compared to corn fields without the bioenergy buffer strips. While all the bioenergy crop buffers had significant positive environmental benefits, switchgrass performed the best with respect to minimizing nutrient runoff and nitrous oxide emissions. The findings of this research have important implications with respect to land management for agriculture and bioenergy.

Assessment of Cropping System Diversity in the Fergana Valley Through Image Fusion of Landsat 8 and SENTINEL-1

NASA Astrophysics Data System (ADS)

Dimov, D.; Kuhn, J.; Conrad, C.

2016-06-01

In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

Intelligent irrigation performance: evaluation and quantifying its ability for conserving water in arid region

NASA Astrophysics Data System (ADS)

Al-Ghobari, Hussein M.; Mohammad, Fawzi S.

2011-12-01

Intelligent irrigation technologies have been developed in recent years to apply irrigation to turf and landscape plants. These technologies are an evapotranspiration (ET)-based irrigation controller, which calculates ET for local microclimate. Then, the controller creates a program for loading and communicating automatically with drip or sprinkler system controllers. The main objective of this study was to evaluate the effectiveness of the new ET sensors in ability to irrigate agricultural crops and to conserve water use for crop in arid climatic conditions. This paper presents the case for water conservation using intelligent irrigation system (IIS) application technology. The IIS for automating irrigation scheduling was implemented and tested with sprinkle and drip irrigation systems to irrigate wheat and tomato crops. Another irrigation scheduling system was also installed and operated as another treatment, which is based on weather data that retrieved from an automatic weather station. This irrigation control system was running in parallel to the former system (IIS) to be control experiments for comparison purposes. However, this article discusses the implementation of IIS, its installation, testing and calibration of various components. The experiments conducted for one growing season 2009-2010 and the results were represented and discussed herein. Data from all plots were analyzed, which were including soil water status, water consumption, and crop yield. The initial results indicate that up to 25% water saving by intelligent irrigation compared to control method, while maintaining competing yield. Results show that the crop evapotranspiration values for control experiments were higher than that of ET-System in consistent trend during whole growth season. The analysis points out that the values of the two treatments were somewhat close to each other's only in the initial development stages. Generally, the ET-System, with some modification was precise in controlling irrigation water and has been proven to be a good mean to determine the water requirements for crops and to schedule irrigation automatically.

Crop and cattle production responses to tillage and cover crop management in an integrated crop-livestock system in the southeastern USA

USDA-ARS?s Scientific Manuscript database

Integrated crop-livestock systems can help achieve greater environmental quality from disparate crop and livestock systems by recycling nutrients and taking advantage of synergies between systems. We investigated crop and animal production responses in integrated crop-livestock systems with two typ...

2005 AG20/20 Annual Review

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney D.

2005-01-01

Topics covered include: Implementation and Validation of Sensor-Based Site-Specific Crop Management; Enhanced Management of Agricultural Perennial Systems (EMAPS) Using GIS and Remote Sensing; Validation and Application of Geospatial Information for Early Identification of Stress in Wheat; Adapting and Validating Precision Technologies for Cotton Production in the Mid-Southern United States - 2004 Progress Report; Development of a System to Automatically Geo-Rectify Images; Economics of Precision Agriculture Technologies in Cotton Production-AG 2020 Prescription Farming Automation Algorithms; Field Testing a Sensor-Based Applicator for Nitrogen and Phosphorus Application; Early Detection of Citrus Diseases Using Machine Vision and DGPS; Remote Sensing of Citrus Tree Stress Levels and Factors; Spectral-based Nitrogen Sensing for Citrus; Characterization of Tree Canopies; In-field Sensing of Shallow Water Tables and Hydromorphic Soils with an Electromagnetic Induction Profiler; Maintaining the Competitiveness of Tree Fruit Production Through Precision Agriculture; Modeling and Visualizing Terrain and Remote Sensing Data for Research and Education in Precision Agriculture; Thematic Soil Mapping and Crop-Based Strategies for Site-Specific Management; and Crop-Based Strategies for Site-Specific Management.

Perennial crop phase effects on soil fertility

USDA-ARS?s Scientific Manuscript database

There is a need to develop agricultural management systems that enhance soil fertility and reduce reliance on external inputs. Perennial phases in crop rotations are effective at restoring soil fertility, though little information exists in the northern Great Plains regarding soil-based outcomes re...

Pigeon Pea and Cowpea-Based Cropping Systems Improve Vesicular Arbuscular Mycorrhizal Fungal Colonisation of Subsequent Maize on the Alfisols in Central Malawi

PubMed Central

Semu, Ernest; Mrema, Jerome P.; Nalivata, Patson C.

2017-01-01

Mycorrhizal associations contribute to the sustainability of crop production systems through their roles in nutrient cycling and other benefits in the soil-plant ecosystems. A two-year study was conducted on the Alfisols of Lilongwe and Dowa districts, Central Malawi, to assess the vesicular-arbuscular mycorrhizal (VAM) fungal colonisation levels in pigeon pea, cowpea, and maize grown in sole cropping, legume-cereal, and legume-legume intercropping systems and in the maize grown in short rotation (year 2) as influenced by the previous cropping systems and N fertilizer application. The gridline intersect method was used to assess the VAM fungal colonisation levels. Results showed that all treatments that included legumes whether grown as sole crop, in legume-cereal or in legume-legume cropping systems in the previous year, had significantly higher (P < 0.05) VAM fungal colonisation of the rotational maize crop roots by a range 39% to 50% and 19% to 47% than those in maize supplied and not supplied with N fertilizer, respectively, in a maize-maize short rotation, at the Lilongwe site. A similar trend was reported for the Dowa site. Furthermore, there were positive correlations between VAM fungal colonisation and the plant P content, dry matter yield, and nodule numbers. Further studies may help to assess the diversity of VAM fungal species in Malawi soils and identify more adaptive ones for inoculation studies. PMID:28584528

Pigeon Pea and Cowpea-Based Cropping Systems Improve Vesicular Arbuscular Mycorrhizal Fungal Colonisation of Subsequent Maize on the Alfisols in Central Malawi.

PubMed

Njira, Keston O W; Semu, Ernest; Mrema, Jerome P; Nalivata, Patson C

2017-01-01

Mycorrhizal associations contribute to the sustainability of crop production systems through their roles in nutrient cycling and other benefits in the soil-plant ecosystems. A two-year study was conducted on the Alfisols of Lilongwe and Dowa districts, Central Malawi, to assess the vesicular-arbuscular mycorrhizal (VAM) fungal colonisation levels in pigeon pea, cowpea, and maize grown in sole cropping, legume-cereal, and legume-legume intercropping systems and in the maize grown in short rotation (year 2) as influenced by the previous cropping systems and N fertilizer application. The gridline intersect method was used to assess the VAM fungal colonisation levels. Results showed that all treatments that included legumes whether grown as sole crop, in legume-cereal or in legume-legume cropping systems in the previous year, had significantly higher ( P < 0.05) VAM fungal colonisation of the rotational maize crop roots by a range 39% to 50% and 19% to 47% than those in maize supplied and not supplied with N fertilizer, respectively, in a maize-maize short rotation, at the Lilongwe site. A similar trend was reported for the Dowa site. Furthermore, there were positive correlations between VAM fungal colonisation and the plant P content, dry matter yield, and nodule numbers. Further studies may help to assess the diversity of VAM fungal species in Malawi soils and identify more adaptive ones for inoculation studies.

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera.

PubMed

Nguyen, Thuy Tuong; Slaughter, David C; Hanson, Bradley D; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

2015-07-28

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

PubMed Central

Nguyen, Thuy Tuong; Slaughter, David C.; Hanson, Bradley D.; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

2015-01-01

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images. PMID:26225982

Machine-assisted analysis of Landsat data in the study of crop-soils relationships

USGS Publications Warehouse

Draeger, William C.

1976-01-01

To date, relatively few studies have dealt with crop-soil interactions as they affect the appearance of agricultural areas on Landsat imagery, and hence crop and soil classification or the analysis of agricultural land use.The Image 100, a computer-based data analysis system which allows an interpreter to interact directly and rapidly with Landsat computer compatible tape data, provided a tool to assist in the evaluation of the extent and significance of these interactions. Used with timely and accurate ground data, the system made possible a determination of the variability in crop spectral appearance, from soil type to soil type, as recorded on Landsat data. Information was provided in the form of spectral distribution histrograms for each crop-soil class on each Landsat band. Several crop categories in a test area in  rookings County, South Dakota, were classified using training fields that were selected to be representative of each major crop-soil class. Accuracies in each case, on a total acreage basis, were greater than 90 percent.

Developing a Satellite Based Automatic System for Crop Monitoring: Kenya's Great Rift Valley, A Case Study

NASA Astrophysics Data System (ADS)

Lucciani, Roberto; Laneve, Giovanni; Jahjah, Munzer; Mito, Collins

2016-08-01

The crop growth stage represents essential information for agricultural areas management. In this study we investigate the feasibility of a tool based on remotely sensed satellite (Landsat 8) imagery, capable of automatically classify crop fields and how much resolution enhancement based on pan-sharpening techniques and phenological information extraction, useful to create decision rules that allow to identify semantic class to assign to an object, can effectively support the classification process. Moreover we investigate the opportunity to extract vegetation health status information from remotely sensed assessment of the equivalent water thickness (EWT). Our case study is the Kenya's Great Rift valley, in this area a ground truth campaign was conducted during August 2015 in order to collect crop fields GPS measurements, leaf area index (LAI) and chlorophyll samples.

Implementation of a global-scale operational data assimilation system for satellite-based soil moisture retrievals

NASA Astrophysics Data System (ADS)

Bolten, J.; Crow, W.; Zhan, X.; Reynolds, C.

2008-08-01

Timely and accurate monitoring of global weather anomalies and drought conditions is essential for assessing global crop conditions. Soil moisture observations are particularly important for crop yield fluctuations provided by the US Department of Agriculture (USDA) Production Estimation and Crop Assessment Division (PECAD). The current system utilized by PECAD estimates soil moisture from a 2-layer water balance model based on precipitation and temperature data from World Meteorological Organization (WMO) and US Air Force Weather Agency (AFWA). The accuracy of this system is highly dependent on the data sources used; particularly the accuracy, consistency, and spatial and temporal coverage of the land and climatic data input into the models. However, many regions of the globe lack observations at the temporal and spatial resolutions required by PECAD. This study incorporates NASA's soil moisture remote sensing product provided by the EOS Advanced Microwave Scanning Radiometer (AMSR-E) into the U.S. Department of Agriculture Crop Assessment and Data Retrieval (CADRE) decision support system. A quasi-global-scale operational data assimilation system has been designed and implemented to provide CADRE a daily product of integrated AMSR-E soil moisture observations with the PECAD two-layer soil moisture model forecasts. A methodology of the system design and a brief evaluation of the system performance over the Conterminous United States (CONUS) is presented.

Diversified cropping systems support greater microbial cycling and retention of carbon and nitrogen

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, Alison E.; Hofmockel, Kirsten S.

2017-03-01

Diversifying biologically simple cropping systems often entails altering other management practices, such as tillage regime or nitrogen (N) source. We hypothesized that the interaction of crop rotation, N source, and tillage in diversified cropping systems would promote microbially-mediated soil C and N cycling while attenuating inorganic N pools. We studied a cropping systems trial in its 10th year in Iowa, USA, which tested a 2-yr cropping system of corn (Zea mays L.)/soybean [Glycine max (L.) Merr.] managed with conventional fertilizer N inputs and conservation tillage, a 3-yr cropping system of corn/soybean/small grain + red clover (Trifolium pratense L.), and amore » 4-yr cropping system of corn/soybean/small grain + alfalfa (Medicago sativa L.)/alfalfa. Three year and 4-yr cropping systems were managed with composted manure, reduced N fertilizer inputs, and periodic moldboard ploughing. We assayed soil microbial biomass carbon (MBC) and N (MBN), soil extractable NH4 and NO3, gross proteolytic activity of native soil, and potential activity of six hydrolytic enzymes eight times during the growing season. At the 0-20cm depth, native protease activity in the 4-yr cropping system was greater than in the 2-yr cropping system by a factor of 7.9, whereas dissolved inorganic N pools did not differ between cropping systems (P = 0.292). At the 0-20cm depth, MBC and MBN the 4-yr cropping system exceeded those in the 2-yr cropping system by factors of 1.51 and 1.57. Our findings suggest that diversified crop cropping systems, even when periodically moldboard ploughed, support higher levels of microbial biomass, greater production of bioavailable N from SOM, and a deeper microbially active layer than less diverse cropping systems.« less

Organic farming and cover crops as an alternative to mineral fertilizers to improve soil physical properties

NASA Astrophysics Data System (ADS)

Sánchez de Cima, Diego; Luik, Anne; Reintam, Endla

2015-10-01

For testing how cover crops and different fertilization managements affect the soil physical properties in a plough based tillage system, a five-year crop rotation experiment (field pea, white potato, common barley undersown with red clover, red clover, and winter wheat) was set. The rotation was managed under four different farming systems: two conventional: with and without mineral fertilizers and two organic, both with winter cover crops (later ploughed and used as green manure) and one where cattle manure was added yearly. The measurements conducted were penetration resistance, soil water content, porosity, water permeability, and organic carbon. Yearly variations were linked to the number of tillage operations, and a cumulative effect of soil organic carbon in the soil as a result of the different fertilization amendments, organic or mineral. All the systems showed similar tendencies along the three years of study and differences were only found between the control and the other systems. Mineral fertilizers enhanced the overall physical soil conditions due to the higher yield in the system. In the organic systems, cover crops and cattle manure did not have a significant effect on soil physical properties in comparison with the conventional ones, which were kept bare during the winter period. The extra organic matter boosted the positive effect of crop rotation, but the higher number of tillage operations in both organic systems counteracted this effect to a greater or lesser extent.

Separability of agricultural crops with airborne scatterometry

NASA Technical Reports Server (NTRS)

Mehta, N. C.

1983-01-01

Backscattering measurements were acquired with airborne scatterometers over a site in Cass County, North Dakota on four days in the 1981 crop growing season. Data were acquired at three frequencies (L-, C- and Ku-bands), two polarizations (like and cross) and ten incidence angles (5 degrees to 50 degrees in 5 degree steps). Crop separability is studied in an hierarchical fashion. A two-class separability measure is defined, which compares within-class to between-class variability, to determine crop separability. The scatterometer channels with the best potential for crop separability are determined, based on this separability measure. Higher frequencies are more useful for discriminating small grains, while lower frequencies tend to separate non-small grains better. Some crops are more separable when row direction is taken into account. The effect of pixel purity is to increase the separability between all crops while not changing the order of useful scatterometer channels. Crude estimates of separability errors are calculated based on these analyses. These results are useful in selecting the parameters of active microwave systems in agricultural remote sensing.

[New method and instrument to diagnose crop growth status in greenhouse based on spectroscopy].

PubMed

Zhang, Xi-Jie; Li, Min-Zan; Cui, Di; Zhao, Peng; Sun, Jian-Ying; Tang, Ning

2006-05-01

Spectral reflectance of cucumber leaves in greenhouse was measured using an ASD FieldSpec Pro VNIR spectrometer with natural illumination. Two sensitive wavelengths, 527 nm and 762 nm, were selected to evaluate the nitrogen content of the cucumber leaves. A model was established and validated using normal difference color index(NDCI) with the correlation coefficient of 0.881. Based on the above efforts, a handheld spectral instrument was developed to diagnose the growth status of the crop in greenhouse using fiber optics. The instrument was mainly composed of four parts: reflected light acquisition system, light intensity measurement unit, signal conditioning unit, and data acquisition system. The sunlight reflected by the crop was transmitted by the fiber, and passed through the light filter to obtain light at the sensitive wavelengths. Finally it was transformed into electronic signal by the photoelectric transistor, and was used to diagnose the growth status of the crop according to the evaluation model. The result showed that the developed instrument was practical.

[Main interspecific competition and land productivity of fruit-crop intercropping in Loess Region of West Shauxi].

PubMed

Yun, Lei; Bi, Hua-Xing; Tian, Xiao-Ling; Cui, Zhe-Wei; Zhou, Hui-Zi; Gao, Lu-Bo; Liu, Li-Xia

2011-05-01

Taking the four typical fruit-crop intercropping models, i.e., walnut-peanut, walnut-soybean, apple-peanut, and apple-soybean, in the Loess Region of western Shanxi Province as the objects, this paper analyzed the crop (peanut and soybean) photosynthetic active radiation (PAR), net photosynthetic rate (P(n)), yield, and soil moisture content. Comparing with crop monoculture, fruit-crop intercropping decreased the crop PAR and P(n). The smaller the distance from tree rows, the smaller the crop PAR and P(n). There was a significantly positive correlation between the P(n) and crop yield, suggesting that illumination was one of the key factors affecting crop yield. From the whole trend, the 0-100 cm soil moisture content had no significant differences between walnut-crop intercropping systems and corresponding monoculture cropping systems, but had significant differences between apple-crop intercropping systems and corresponding monoculture cropping systems, indicating that the competition for soil moisture was more intense in apple-crop intercropping systems than in walnut-crop intercropping systems. Comparing with monoculture, fruit-crop intercropping increased the land use efficiency and economic benefit averagely by 70% and 14%, respectively, and walnut-crop intercropping was much better than apple-crop intercropping. To increase the crop yield in fruit-crop intercropping systems, the following strategies should be taken: strengthening the management of irrigation and fertilization, increasing the distances or setting root barriers between crop and tree rows, regularly and properly pruning, and planting shade-tolerant crops in intercropping.

UAV-Based Hyperspectral Remote Sensing for Precision Agriculture: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Angel, Y.; Parkes, S. D.; Turner, D.; Houborg, R.; Lucieer, A.; McCabe, M.

2017-12-01

Modern agricultural production relies on monitoring crop status by observing and measuring variables such as soil condition, plant health, fertilizer and pesticide effect, irrigation and crop yield. Managing all of these factors is a considerable challenge for crop producers. As such, providing integrated technological solutions that enable improved diagnostics of field condition to maximize profits, while minimizing environmental impacts, would be of much interest. Such challenges can be addressed by implementing remote sensing systems such as hyperspectral imaging to produce precise biophysical indicator maps across the various cycles of crop development. Recent progress in unmanned aerial vehicles (UAVs) have advanced traditional satellite-based capabilities, providing a capacity for high-spatial, spectral and temporal response. However, while some hyperspectral sensors have been developed for use onboard UAVs, significant investment is required to develop a system and data processing workflow that retrieves accurately georeferenced mosaics. Here we explore the use of a pushbroom hyperspectral camera that is integrated on-board a multi-rotor UAV system to measure the surface reflectance in 272 distinct spectral bands across a wavelengths range spanning 400-1000 nm, and outline the requirement for sensor calibration, integration onto a stable UAV platform enabling accurate positional data, flight planning, and development of data post-processing workflows for georeferenced mosaics. The provision of high-quality and geo-corrected imagery facilitates the development of metrics of vegetation health that can be used to identify potential problems such as production inefficiencies, diseases and nutrient deficiencies and other data-streams to enable improved crop management. Immense opportunities remain to be exploited in the implementation of UAV-based hyperspectral sensing (and its combination with other imaging systems) to provide a transferable and scalable integrated framework for crop growth monitoring and yield prediction. Here we explore some of the challenges and issues in translating the available technological capacity into a useful and useable image collection and processing flow-path that enables these potential applications to be better realized.

Irrigation Trials for ET Estimation and Water Management in California Specialty Crops

NASA Astrophysics Data System (ADS)

Johnson, L.; Cahn, M.; Martin, F.; Lund, C.; Melton, F. S.

2012-12-01

Accurate estimation of crop evapotranspiration (ETc) can support efficient irrigation water management, which in turn brings benefits including surface water conservation, mitigation of groundwater depletion/degradation, energy savings, and crop quality assurance. Past research in California has revealed strong relationships between canopy fractional cover (Fc) and ETc of certain specialty crops, while additional research has shown the potential of monitoring Fc by satellite remote sensing. California's Central Coast is the leading region of cool season vegetable production in the U.S. Monterey County alone produces more than 80,000 ha of lettuce and broccoli (about half of U.S. production), valued at $1.5 billion in 2009. Under this study, we are conducting ongoing irrigation trials on these crops at the USDA Agricultural Research Station (Salinas) to compare irrigation scheduling via plant-based ETc approaches, by way of Fc, with current industry standard-practice. The following two monitoring approaches are being evaluated - 1) a remote sensing model employed by NASA's prototype Satellite Irrigation Management System, and 2) an online irrigation scheduling tool, CropManage, recently developed by U.C. Cooperative Extension. Both approaches utilize daily grass-reference ETo data as provided by the California Irrigation Management Irrigation System (CIMIS). A sensor network is deployed to monitor applied irrigation, volumetric soil water content, soil water potential, deep drainage, and standard meteorologic variables in order to derive ETc by a water balance approach. Evaluations of crop yield and crop quality are performed by the research team and by commercial growers. Initial results to-date indicate that applied water reductions based on Fc measurements are possible with little-to-no impact on yield of crisphead lettuce (Lactuca sativa). Additional results for both lettuce and broccoli trials, conducted during summer-fall 2012, are presented with respect to nutrient management and crop viability.

Model development for prediction of soil water dynamics in plant production.

PubMed

Hu, Zhengfeng; Jin, Huixia; Zhang, Kefeng

2015-09-01

Optimizing water use in agriculture and medicinal plants is crucially important worldwide. Soil sensor-controlled irrigation systems are increasingly becoming available. However it is questionable whether irrigation scheduling based on soil measurements in the top soil could make best use of water for deep-rooted crops. In this study a mechanistic model was employed to investigate water extraction by a deep-rooted cabbage crop from the soil profile throughout crop growth. The model accounts all key processes governing water dynamics in the soil-plant-atmosphere system. Results show that the subsoil provides a significant proportion of the seasonal transpiration, about a third of water transpired over the whole growing season. This suggests that soil water in the entire root zone should be taken into consideration in irrigation scheduling, and for sensor-controlled irrigation systems sensors in the subsoil are essential for detecting soil water status for deep-rooted crops.

Cover crops support ecological intensification of arable cropping systems

NASA Astrophysics Data System (ADS)

Wittwer, Raphaël A.; Dorn, Brigitte; Jossi, Werner; van der Heijden, Marcel G. A.

2017-02-01

A major challenge for agriculture is to enhance productivity with minimum impact on the environment. Several studies indicate that cover crops could replace anthropogenic inputs and enhance crop productivity. However, so far, it is unclear if cover crop effects vary between different cropping systems, and direct comparisons among major arable production systems are rare. Here we compared the short-term effects of various cover crops on crop yield, nitrogen uptake, and weed infestation in four arable production systems (conventional cropping with intensive tillage and no-tillage; organic cropping with intensive tillage and reduced tillage). We hypothesized that cover cropping effects increase with decreasing management intensity. Our study demonstrated that cover crop effects on crop yield were highest in the organic system with reduced tillage (+24%), intermediate in the organic system with tillage (+13%) and in the conventional system with no tillage (+8%) and lowest in the conventional system with tillage (+2%). Our results indicate that cover crops are essential to maintaining a certain yield level when soil tillage intensity is reduced (e.g. under conservation agriculture), or when production is converted to organic agriculture. Thus, the inclusion of cover crops provides additional opportunities to increase the yield of lower intensity production systems and contribute to ecological intensification.

A second-generation expression system for tyrosine-sulfated proteins and its application in crop protection.

PubMed

Schwessinger, Benjamin; Li, Xiang; Ellinghaus, Thomas L; Chan, Leanne Jade G; Wei, Tong; Joe, Anna; Thomas, Nicholas; Pruitt, Rory; Adams, Paul D; Chern, Maw Sheng; Petzold, Christopher J; Liu, Chang C; Ronald, Pamela C

2016-04-18

Posttranslational modification (PTM) of proteins and peptides is important for diverse biological processes in plants and animals. The paucity of heterologous expression systems for PTMs and the technical challenges associated with chemical synthesis of these modified proteins has limited detailed molecular characterization and therapeutic applications. Here we describe an optimized system for expression of tyrosine-sulfated proteins in Escherichia coli and its application in a bio-based crop protection strategy in rice.

A second-generation expression system for tyrosine-sulfated proteins and its application in crop protection

DOE PAGES

Schwessinger, Benjamin; Li, Xiang; Ellinghaus, Thomas L.; ...

2015-11-27

Posttranslational modification (PTM) of proteins and peptides is important for diverse biological processes in plants and animals. The paucity of heterologous expression systems for PTMs and the technical challenges associated with chemical synthesis of these modified proteins has limited detailed molecular characterization and therapeutic applications. Here we describe an optimized system for expression of tyrosine-sulfated proteins in Escherichia coli and its application in a bio-based crop protection strategy in rice.

Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases

PubMed Central

Aubertot, Jean-Noël; Robin, Marie-Hélène

2013-01-01

The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop. PMID:24019908

Injury Profile SIMulator, a qualitative aggregative modelling framework to predict crop injury profile as a function of cropping practices, and the abiotic and biotic environment. I. Conceptual bases.

PubMed

Aubertot, Jean-Noël; Robin, Marie-Hélène

2013-01-01

The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop.

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.

The status of parametric studies in radar agriculture

NASA Technical Reports Server (NTRS)

Morain, S. A.

1972-01-01

Outlined is an information system based on the use of remote sensor data and the design, testing, and implementation of interpretation keys for agriculture. The task of crop identification from radar imagery emphasizes dichotomous keys and the effects of frequency, angular and other microwave dependencies of crops for use in discrimination. A mosaic is formulated from imagery and used to study acres in wheat for spread of circular irrigation, spread of crops, and other phenomena.

Advances in regional crop yield estimation over the United States using satellite remote sensing data

NASA Astrophysics Data System (ADS)

Johnson, D. M.; Dorn, M. F.; Crawford, C.

2015-12-01

Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a variety of data mining and modeling options and results strongly lean toward solutions of ensemble decision trees like Cubist and Random Forest. Those comparisons of what are seen as best will be also be shown. And finally, important model refinements accounting for temporal and spatial trends have also been considered and results will be presented.

Bioregenerative Life Support Systems Test Complex (Bio-Plex) Food Processing System: A Dual System

NASA Technical Reports Server (NTRS)

Perchonok, Michele; Vittadini, Elena; Peterson, Laurie J.; Swango, Beverly E.; Toerne, Mary E.; Russo, Dane M. (Technical Monitor)

2001-01-01

A Bioregenerative Life Support Test Complex, BIO-Plex, is currently being constructed at the Johnson Space Center (JSC) in Houston, TX. This facility will attempt to answer the questions involved in developing a lunar or planetary base. The Food Processing System (FPS) of the BIO-Plex is responsible for supplying food to the crew in coordination with the chosen mission scenario. Long duration space missions require development of both a Transit Food System and of a Lunar or Planetary Food System. These two systems are intrinsically different since the first one will be utilized in the transit vehicle in microgravity conditions with mostly resupplied foods, while the second will be used in conditions of partial gravity (hypogravity) to process foods from crops grown in the facility. The Transit Food System will consist of prepackaged food of extended shelf life. It will be supplemented with salad crops that will be consumed fresh. Microgravity imposes significant limitation on the ability to handle food and allows only for minimal processing. The challenge is to develop food systems similar to the International Space Station or Shuttle Food Systems but with a shelf life of 3 - 5 years. The Lunar or Planetary Food System will allow for food processing of crops due to the presence of some gravitational force (1/6 to 1/3 that of Earth). Crops such as wheat, soybean, rice, potato, peanut, and salad crops, will be processed to final products to provide a nutritious and acceptable diet for the crew. Not only are constraints imposed on the FPS from the crops (e.g., crop variation, availability, storage and shelf-life) but also significant requirements are present for the crew meals (e.g., RDA, high quality, safety, variety). The FPS becomes a fulcrum creating the right connection from crops to crew meals while dealing with issues of integration within a closed self-regenerative system (e.g., safe processing, waste production, volumes, air contaminations, water usage, etc.). Options for the first test, for duration of 120 days, currently scheduled for late 2003 are outlined.

Improving irrigation management in L'Horta Nord (Valencia, Spain)

NASA Astrophysics Data System (ADS)

Pascual-Seva, Nuria; San Bautista, Alberto; López-Galarza, Salvador; Maroto, Jose Vicente; Pascual, Bernardo

2014-05-01

L'Horta Nord is an important irrigation district in Valencia (Spain), especially for vegetable crops. The traditional cropping pattern in the region consists of a rotation of chufa with crops such as potato, onion, lettuce, escarole and red cabbage, being all these crops furrow irrigated. Currently, the quality of the water used is acceptable, water is not expensive and there are no limitations on supply. Consequently, growers are not aware of the volumes of water used, application efficiencies, nor water productivity for any of the crops cited. The European Framework Directive 2000/60, based on the precautionary principle, considers preventive action for measures to be taken; moreover, drought periods are becoming more frequent and extended, and water is being diverted to other uses. Thus, water use is an issue to improve. In this sense, the current situation of the irrigation in the area is analysed using chufa (Cyperus esculentus L. var. sativus Boeck.) as representative of the crops, since most of the crops in the area have shallow root systems, as chufa, which are irrigated in similar patterns. In order to analyse the irrigation performance of the traditional chufa crop as well as to achieve more sustainable results, different studies have been carried out, during the last decade. Efforts have been directed to increase water productivity, increasing yield and minimising the volumes of water applied. Different planting configurations and different irrigation thresholds, not only in furrow irrigation but also in drip irrigation, are examples of how the irrigation performance could be improved. Herein is presented a two-year study, comparing, in both furrow and drip irrigation, two irrigation schedules based on the volumetric soil water content, which was continuously monitored using capacitance sensors. Yield was significantly affected by the growing season, the irrigation system and by the irrigation schedule, and by the second order interactions of the irrigation system with the other studied variables. Greater yields (p≤0.01) were obtained in the first growing season, drip irrigation and maintaining a higher soil moisture level. When considering the irrigation water use efficiency, the irrigation system showed significant differences (p≤0.01) with greater efficiencies for drip irrigation. Considering the homogeneity of the plots in the area and the similarities of the irrigation managements of chufa with the other crops, the results could be extended to most of the plots and crops in the area.

Characterizing Chickpeas for End Use Characteristics

USDA-ARS?s Scientific Manuscript database

In the United States, cool-season grain legumes, including chickpeas, are integral components of cereal-based cropping systems in the Pacific Northwest and the Upper Midwest. The addition of a pulse crop helps break disease and weed cycles and adds nitrogen and organic matter to the soil. In this ...

Greenhouse gas flux and crop productivity after 10 years of reduced and no tillage in a wheat-maize cropping system.

PubMed

Tian, Shenzhong; Wang, Yu; Ning, Tangyuan; Zhao, Hongxiang; Wang, Bingwen; Li, Na; Li, Zengjia; Chi, Shuyun

2013-01-01

Appropriate tillage plays an important role in mitigating the emissions of greenhouse gases (GHG) in regions with higher crop yields, but the emission situations of some reduced tillage systems such as subsoiling, harrow tillage and rotary tillage are not comprehensively studied. The objective of this study was to evaluate the emission characteristics of GHG (CH4 and N2O) under four reduced tillage systems from October 2007 to August 2009 based on a 10-yr tillage experiment in the North China Plain, which included no-tillage (NT) and three reduced tillage systems of subsoil tillage (ST), harrow tillage (HT) and rotary tillage (RT), with the conventional tillage (CT) as the control. The soil under the five tillage systems was an absorption sink for CH4 and an emission source for N2O. The soil temperature positive impacted on the CH4 absorption by the soils of different tillage systems, while a significant negative correlation was observed between the absorption and soil moisture. The main driving factor for increased N2O emission was not the soil temperature but the soil moisture and the content of nitrate. In the two rotation cycle of wheat-maize system (10/2007-10/2008 and 10/2008-10/2009), averaged cumulative uptake fluxes of CH4 under CT, ST, HT, RT and NT systems were approximately 1.67, 1.72, 1.63, 1.77 and 1.17 t ha(-1) year(-1), respectively, and meanwhile, approximately 4.43, 4.38, 4.47, 4.30 and 4.61 t ha(-1) year(-1) of N2O were emitted from soil of these systems, respectively. Moreover, they also gained 33.73, 34.63, 32.62, 34.56 and 27.54 t ha(-1) yields during two crop-rotation periods, respectively. Based on these comparisons, the rotary tillage and subsoiling mitigated the emissions of CH4 and N2O as well as improving crop productivity of a wheat-maize cropping system.

Greenhouse Gas Flux and Crop Productivity after 10 Years of Reduced and No Tillage in a Wheat-Maize Cropping System

PubMed Central

Tian, Shenzhong; Wang, Yu; Ning, Tangyuan; Zhao, Hongxiang; Wang, Bingwen; Li, Na; Li, Zengjia; Chi, Shuyun

2013-01-01

Appropriate tillage plays an important role in mitigating the emissions of greenhouse gases (GHG) in regions with higher crop yields, but the emission situations of some reduced tillage systems such as subsoiling, harrow tillage and rotary tillage are not comprehensively studied. The objective of this study was to evaluate the emission characteristics of GHG (CH4 and N2O) under four reduced tillage systems from October 2007 to August 2009 based on a 10-yr tillage experiment in the North China Plain, which included no-tillage (NT) and three reduced tillage systems of subsoil tillage (ST), harrow tillage (HT) and rotary tillage (RT), with the conventional tillage (CT) as the control. The soil under the five tillage systems was an absorption sink for CH4 and an emission source for N2O. The soil temperature positive impacted on the CH4 absorption by the soils of different tillage systems, while a significant negative correlation was observed between the absorption and soil moisture. The main driving factor for increased N2O emission was not the soil temperature but the soil moisture and the content of nitrate. In the two rotation cycle of wheat-maize system (10/2007–10/2008 and 10/2008–10/2009), averaged cumulative uptake fluxes of CH4 under CT, ST, HT, RT and NT systems were approximately 1.67, 1.72, 1.63, 1.77 and 1.17 t ha−1 year−1, respectively, and meanwhile, approximately 4.43, 4.38, 4.47, 4.30 and 4.61 t ha−1 year−1 of N2O were emitted from soil of these systems, respectively. Moreover, they also gained 33.73, 34.63, 32.62, 34.56 and 27.54 t ha−1 yields during two crop-rotation periods, respectively. Based on these comparisons, the rotary tillage and subsoiling mitigated the emissions of CH4 and N2O as well as improving crop productivity of a wheat-maize cropping system. PMID:24019923

Rice crop risk map in Babahoyo canton (Ecuador)

NASA Astrophysics Data System (ADS)

Valverde Arias, Omar; Tarquis, Ana; Garrido, Alberto

2016-04-01

It is widely known that extreme climatic phenomena occur with more intensity and frequency. This fact has put more pressure over farming, making agricultural and livestock production riskier. In order to reduce hazards and economic loses that could jeopardize farmer's incomes and even its business continuity, it is very important to implement agriculture risk management plans by governments and institutions. One of the main strategies is transfer risk by agriculture insurance. Agriculture insurance based in indexes has a significant growth in the last decade. And consist in a comparison between measured index values with a defined threshold that triggers damage losses. However, based index insurance could not be based on an isolated measurement. It is necessary to be integrated in a complete monitoring system that uses many sources of information and tools. For example, index influence areas, crop production risk maps, crop yields, claim statistics, and so on. Crop production risk is related with yield variation of crops and livestock, due to weather, pests, diseases, and other factors that affect both the quantity and quality of commodities produced. This is the risk which farmers invest more time managing, and it is completely under their control. The aim of this study is generate a crop risk map of rice that can provide risk manager important information about the status of crop facing production risks. Then, based on this information, it will be possible to make best decisions to deal with production risk. The rice crop risk map was generated qualifying a 1:25000 scale soil and climatic map of Babahoyo canton, which is located in coast region of Ecuador, where rice is one of the main crops. The methodology to obtain crop risk map starts by establishing rice crop requirements and indentifying the risks associated with this crop. A second step is to evaluate soil and climatic conditions of the study area related to optimal crop requirements. Based on it, we can determinate which level of rice crop requirement is met. Finally we have established rice crop zones classified as: suitable, moderate suitable, marginal suitable and unsuitable. Several methods have been used to estimate the degree with which crop requirements are satisfied, pondering weights of limiting factors to adequate crop conditions. Better conditions for cropping in a specific area imply less risk in production. In this case, crop will be less affected by pests and disease, although this closely depends on crop management. Farmers have to invest less money to produce and could increase their benefit. Results are showed and discussed with the aim to study the efficiency and potential of this risk map.

Maximizing root/rhizosphere efficiency to improve crop productivity and nutrient use efficiency in intensive agriculture of China.

PubMed

Shen, Jianbo; Li, Chunjian; Mi, Guohua; Li, Long; Yuan, Lixing; Jiang, Rongfeng; Zhang, Fusuo

2013-03-01

Root and rhizosphere research has been conducted for many decades, but the underlying strategy of root/rhizosphere processes and management in intensive cropping systems remain largely to be determined. Improved grain production to meet the food demand of an increasing population has been highly dependent on chemical fertilizer input based on the traditionally assumed notion of 'high input, high output', which results in overuse of fertilizers but ignores the biological potential of roots or rhizosphere for efficient mobilization and acquisition of soil nutrients. Root exploration in soil nutrient resources and root-induced rhizosphere processes plays an important role in controlling nutrient transformation, efficient nutrient acquisition and use, and thus crop productivity. The efficiency of root/rhizosphere in terms of improved nutrient mobilization, acquisition, and use can be fully exploited by: (1) manipulating root growth (i.e. root development and size, root system architecture, and distribution); (2) regulating rhizosphere processes (i.e. rhizosphere acidification, organic anion and acid phosphatase exudation, localized application of nutrients, rhizosphere interactions, and use of efficient crop genotypes); and (3) optimizing root zone management to synchronize root growth and soil nutrient supply with demand of nutrients in cropping systems. Experiments have shown that root/rhizosphere management is an effective approach to increase both nutrient use efficiency and crop productivity for sustainable crop production. The objectives of this paper are to summarize the principles of root/rhizosphere management and provide an overview of some successful case studies on how to exploit the biological potential of root system and rhizosphere processes to improve crop productivity and nutrient use efficiency.

Strategic system development toward biofuel, desertification, and crop production monitoring in continental scales using satellite-based photosynthesis models

NASA Astrophysics Data System (ADS)

Kaneko, Daijiro

2013-10-01

The author regards fundamental root functions as underpinning photosynthesis activities by vegetation and as affecting environmental issues, grain production, and desertification. This paper describes the present development of monitoring and near real-time forecasting of environmental projects and crop production by approaching established operational monitoring step-by-step. The author has been developing a thematic monitoring structure (named RSEM system) which stands on satellite-based photosynthesis models over several continents for operational supports in environmental fields mentioned above. Validation methods stand not on FLUXNET but on carbon partitioning validation (CPV). The models demand continuing parameterization. The entire frame system has been built using Reanalysis meteorological data, but model accuracy remains insufficient except for that of paddy rice. The author shall accomplish the system that incorporates global environmental forces. Regarding crop production applications, industrialization in developing countries achieved through direct investment by economically developed nations raises their income, resulting in increased food demand. Last year, China began to import rice as it had in the past with grains of maize, wheat, and soybeans. Important agro-potential countries make efforts to cultivate new crop lands in South America, Africa, and Eastern Europe. Trends toward less food sustainability and stability are continuing, with exacerbation by rapid social and climate changes. Operational monitoring of carbon sequestration by herbaceous and bore plants converges with efforts at bio-energy, crop production monitoring, and socio-environmental projects such as CDM A/R, combating desertification, and bio-diversity.

Effects of Cover Crops on Pratylenchus penetrans and the Nematode Community in Carrot Production

PubMed Central

Grabau, Zane J.; Zar Maung, Zin Thu; Noyes, D. Corey; Baas, Dean G.; Werling, Benjamin P.; Brainard, Daniel C.; Melakeberhan, Haddish

2017-01-01

Cover cropping is a common practice in U.S. Midwest carrot production for soil conservation, and may affect soil ecology and plant-parasitic nematodes—to which carrots are very susceptible. This study assessed the impact of cover crops—oats (Avena sativa), radish (Raphanus sativus) cv. Defender, rape (Brassica napus) cv. Dwarf Essex, and a mixture of oats and radish—on plant-parasitic nematodes and soil ecology based on the nematode community in Michigan carrot production systems. Research was conducted at two field sites where cover crops were grown in Fall 2014 preceding Summer 2015 carrot production. At Site 1, root-lesion (Pratylenchus penetrans) and stunt (Tylenchorhynchus sp.) nematodes were present at low population densities (less than 25 nematodes/100 cm3 soil), but were not significantly affected (P > 0.05) by cover crops. At Site 2, P. penetrans population densities were increased (P ≤ 0.05) by ‘Defender’ radish compared to other cover crops or fallow control during cover crop growth and midseason carrot production. At both sites, there were few short-term impacts of cover cropping on soil ecology based on the nematode community. At Site 1, only at carrot harvest, radish-oats mixture and ‘Dwarf Essex’ rape alone enriched the soil food web based on the enrichment index (P ≤ 0.05) while rape and radish increased structure index values. At Site 2, bacterivore abundance was increased by oats or radish cover crops compared to control, but only during carrot production. In general, cover crops did not affect the nematode community until nearly a year after cover crop growth suggesting that changes in the soil community following cover cropping may be gradual. PMID:28512383

Base-Case 1% Yield Increase (BC1), All Energy Crops scenario of the 2016 Billion Ton Report

DOE Data Explorer

Davis, Maggie R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000181319328); Hellwinkel, Chad [University of Tennessee] (ORCID:0000000173085058); Eaton, Laurence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000312709626); Langholtz, Matthew H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000281537154); Turhollow, Anthony [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000228159350); Brandt, Craig [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000214707379); Myers, Aaron (ORCID:0000000320373827)

2016-07-13

Scientific reason for data generation: to serve as the base-case scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 1% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply to crops already planted, but new plantings do take advantage of the gains in expected yield growth. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling

NASA Astrophysics Data System (ADS)

Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.

2017-12-01

For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce uncertainties in agro-ecosystem modeling. Through the combination of the multi annual land use fractions, the resulting datasets additionally inform about land use changes and trends within the coarser grid cells. We see this as a major advantage, because we are able to maintain much more precise land use information when a coarser cell size is used.

Early forecasting of crop condition using an integrative remote sensing method for corn and soybeans in Iowa and Illinois, USA

NASA Astrophysics Data System (ADS)

Seo, Bumsuk; Lee, Jihye; Kang, Sinkyu

2017-04-01

The weather-related risks in crop production is not only crucial for farmers but also for market participants and policy makers since securing food supply is an important issue for society. While crop growth condition and phenology are essential information about such risks, the extensive observations on those are often non-existent in many parts of the world. In this study, we have developed a novel integrative approach to remotely sense crop growth condition and phenology at a large scale. For corn and soybeans in Iowa and Illinois of USA (2003-2014), we assessed crop growth condition and crop phenology by EO data and validated it against the United States Department of Agriculture (USDA) National Agriculture Statistics System (NASS) crop statistics. For growth condition, we used two distinguished approaches to acquire crop condition indicators: a process-based crop growth modelling and a satellite NDVI based method. Based on their pixel-wise historic distributions, we determined relative growth conditions and scaled-down to the state-level. For crop phenology, we calculated three crop phenology metrics [i.e., start of season (SOS), end of season (EOS), and peak of season (POS)] at the pixel level from MODIS 8-day Normalized Difference Vegetation Index (NDVI). The estimates were compared with the Crop Progress and Condition (CPC) data of NASS. For the condition, the state-level 10-day estimates showed a moderate agreement (RMSE < 15.0%) and the average accuracy of the normal/bad year classification was well (> 70%). Notably, the condition estimates corresponded to the severe soybeans disease in 2003 and the drought in 2012 for both crops. For the phenology, the average RMSE of the estimates was 8.6 day for the all three metrics. The average |ME| was smaller than 1.0 day after bias correction. The proposed method enables us to evaluate crop growth at any given period and place. Global climate changes are increasing the risk in agricultural production such as long-term drought. We hope that the presented remote sensing method for crop condition and crop phenology contributes to reducing the growing risk of crop production in the Earth.

Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt

PubMed Central

Jayaraman, Prem Prakash; Yavari, Ali; Georgakopoulos, Dimitrios; Morshed, Ahsan; Zaslavsky, Arkady

2016-01-01

Improving farm productivity is essential for increasing farm profitability and meeting the rapidly growing demand for food that is fuelled by rapid population growth across the world. Farm productivity can be increased by understanding and forecasting crop performance in a variety of environmental conditions. Crop recommendation is currently based on data collected in field-based agricultural studies that capture crop performance under a variety of conditions (e.g., soil quality and environmental conditions). However, crop performance data collection is currently slow, as such crop studies are often undertaken in remote and distributed locations, and such data are typically collected manually. Furthermore, the quality of manually collected crop performance data is very low, because it does not take into account earlier conditions that have not been observed by the human operators but is essential to filter out collected data that will lead to invalid conclusions (e.g., solar radiation readings in the afternoon after even a short rain or overcast in the morning are invalid, and should not be used in assessing crop performance). Emerging Internet of Things (IoT) technologies, such as IoT devices (e.g., wireless sensor networks, network-connected weather stations, cameras, and smart phones) can be used to collate vast amount of environmental and crop performance data, ranging from time series data from sensors, to spatial data from cameras, to human observations collected and recorded via mobile smart phone applications. Such data can then be analysed to filter out invalid data and compute personalised crop recommendations for any specific farm. In this paper, we present the design of SmartFarmNet, an IoT-based platform that can automate the collection of environmental, soil, fertilisation, and irrigation data; automatically correlate such data and filter-out invalid data from the perspective of assessing crop performance; and compute crop forecasts and personalised crop recommendations for any particular farm. SmartFarmNet can integrate virtually any IoT device, including commercially available sensors, cameras, weather stations, etc., and store their data in the cloud for performance analysis and recommendations. An evaluation of the SmartFarmNet platform and our experiences and lessons learnt in developing this system concludes the paper. SmartFarmNet is the first and currently largest system in the world (in terms of the number of sensors attached, crops assessed, and users it supports) that provides crop performance analysis and recommendations. PMID:27834862

United States benefits of improved worldwide wheat crop information from a LANDSAT system overview

NASA Technical Reports Server (NTRS)

1976-01-01

The value of improvements in worldwide information on wheat crops provided by LANDSAT was measured in the context of world wheat markets. These benefits were based on exiting LANDSAT technical goals and assumed that information would be made available to the United States and other countries at the same time. The benefits to the United States of such public LANDSAT information on wheat crops were found to be 174 million dollars a year on the average. The benefits from improved wheat crop information compare favorably with the annual system's cost of about $62 million. A detailed empirical sample demonstration of the effect of improved information was developed. The history of wheat commodity prices for 1971-72 was reconstructed and the price changes from improved vs. historical information were compared.

Long-term nitrous oxide fluxes in annual and perennial agricultural and unmanaged ecosystems in the upper Midwest USA

DOE PAGES

Gelfand, Ilya; Shcherbak, Iurii; Millar, Neville; ...

2016-08-11

Differences in soil nitrous oxide (N 2O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N 2O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn–soybean–wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N 2O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N 2O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30–80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop 9 management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N 2O-N ha -1 yr -1 and were best predicted by IPCC Tier 1 and DEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil NOmore » $$-\\atop{3}$$ pools (r 2 = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N 2O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes.« less

Long-term nitrous oxide fluxes in annual and perennial agricultural and unmanaged ecosystems in the upper Midwest USA.

PubMed

Gelfand, Ilya; Shcherbak, Iurii; Millar, Neville; Kravchenko, Alexandra N; Robertson, G Philip

2016-11-01

Differences in soil nitrous oxide (N 2 O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N 2 O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn-soybean-wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N 2 O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N 2 O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30-80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop × management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N 2 O-N ha -1  yr -1 and were best predicted by IPCC Tier 1 and ΔEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil NO3- pools (r 2  = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N 2 O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Meteorological risks and impacts on crop production systems in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2013-04-01

Extreme weather events such as droughts, heat stress, rain storms and floods can have devastating effects on cropping systems. The perspective of rising risk-exposure is exacerbated further by projected increases of extreme events with climate change. More limits to aid received for agricultural damage and an overall reduction of direct income support to farmers further impacts farmers' resilience. Based on insurance claims, potatoes and rapeseed are the most vulnerable crops, followed by cereals and sugar beets. Damages due to adverse meteorological events are strongly dependent on crop type, crop stage and soil type. Current knowledge gaps exist in the response of arable crops to the occurrence of extreme events. The degree of temporal overlap between extreme weather events and the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop and its environment. The regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency and magnitude of drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages of six arable crops: winter wheat, winter barley, winter rapeseed, potato, sugar beet and maize. Since crop development is driven by thermal time, crops matured earlier during the warmer 1988-2008 period than during the 1947-1987 period. Drought and heat stress, in particular during the sensitive crop stages, occur at different times in the cropping season and significantly differ between two climatic periods, 1947-1987 and 1988-2008. Soil moisture deficit increases towards harvesting, such that earlier maturing winter crops may avoid drought stress that occurs in late spring and summer. This is reflected in a decrease both in magnitude and frequency of soil moisture deficit around the sensitive stages during the 1988-2008 period when atmospheric drought may be compensated for with soil moisture. The risk of drought spells during the sensitive stages of summer crops increases and may be further aggravated by atmospheric moisture deficits and heat stress. Summer crops may therefore benefit from earlier planting dates and beneficial moisture conditions during early canopy development, but will suffer from increased drought and heat stress during crop maturity. During the harvesting stages, the number of waterlogged days increases in particular for tuber crops. Physically based crop models assist in understanding the links between different factors causing crop damage. The approach allows for assessing the meteorological impacts on crop growth due to the sensitive stages occurring earlier during the growing season and due to extreme weather events. Though average yields have risen continuously between 1947 and 2008 mainly due to technological advances, there is no evidence that relative tolerance to adverse weather conditions such as atmospheric moisture deficit and temperature extremes has changed.

Net global warming potential and greenhouse gas intensity of conventional and conservation agriculture system in rainfed semi arid tropics of India

NASA Astrophysics Data System (ADS)

Pratibha, G.; Srinivas, I.; Rao, K. V.; Shanker, Arun K.; Raju, B. M. K.; Choudhary, Deepak K.; Srinivas Rao, K.; Srinivasarao, Ch.; Maheswari, M.

2016-11-01

Agriculture has been considered as one of the contributors to greenhouse gas (GHG) emissions and it continues to increase with increase in crop production. Hence development of sustainable agro techniques with maximum crop production, and low global warming potential is need of the hour. Quantifying net global warming potential (NGWP) and greenhouse gas intensity (GHGI) of an agricultural activity is a method to assess the mitigation potential of the activity. But there is dearth of information on NGWP of conservation agriculture under rainfed conditions. Hence in this study two methods such as crop based (NGWPcrop) and soil based (NGWPsoil) were estimated from the data of the experiment initiated in 2009 in rainfed semiarid regions of Hyderabad, India with different tillage practices like conventional tillage (CT), reduced tillage (RT), zero tillage (ZT) and residue retention levels by harvesting at different heights which includes 0, 10 and 30 cm anchored residue in pigeonpea-castor systems. The results of the study revealed that under rainfed conditions CT recorded 24% higher yields over ZT, but CT and RT were on par with each other. However, the yield gap between the tillage treatments is narrowing down over 5 years of study. ZT and RT recorded 26 and 11% lower indirect GHG emissions (emissions from farm operations and input use) over CT, respectively. The percent contribution of CO2 eq. N2O emission is higher to total GHG emissions in both the crops. Both NGWPcrop, NGWPsoil, GHGIcrop, and GHGIsoil based were influenced by tillage and residue treatments. Further, castor grown on pigeonpea residue recorded 20% higher GHG emissions over pigeonpea grown on castor residues. The fuel consumption in ZT was reduced by 58% and 81% as compared to CT in pigeonpea and castor, respectively. Lower NGWP and GHGI based on crop and soil was observed with increase in crop residues and decrease in tillage intensity in both the crops. The results of the study indicate that, there is scope to reduce the NGWP emissions by reducing one tillage operation as in RT and increase in crop residue by harvesting at 10 and 30 cm height with minimal impact on the crop yields. However, the trade-off between higher yield and soil health versus GHG emissions should be considered while promoting conservation agriculture. The NGWPcrop estimation method indicated considerable benefits of residues to the soil and higher potential of GHG mitigation than by the NGWPsoil method and may overestimate the potential of GHG mitigation in agriculture system.

Tillage and Composting Strategies to Maximize Potentially Mineralizable Nitrogen in Maize-based Cropping Systems

USDA-ARS?s Scientific Manuscript database

Cereal crop yields vary drastically between developed and developing nations. In developing nations, a lack of synthetic nitrogen (N) fertilizer often limits yields. Low-cost soil management strategies that increase biologically available soil organic matter can reduce farmer reliance on synthetic N...

Surprising yields with no-till cropping systems

USDA-ARS?s Scientific Manuscript database

Producers using no-till practices have observed that crop yields can greatly exceed expectations based on nutrient and water supply. For example, Ralph Holzwarth, who farms near Gettysburg, SD, has averaged 150 bu/ac of corn on his farm for the past 6 years. We were surprised with this yield, as c...

Simulating soil organic carbon changes across toposequences under dryland agriculture using CQESTR

USDA-ARS?s Scientific Manuscript database

Soil organic carbon (SOC) and its management under dryland cropping systems are very critical for both crop productivity and environment health. The objective of this study was to evaluate the performance of CQESTR, a process-based C model, in simulating SOC changes across toposequences of selected ...

The Joint Experiment for Crop Assessment and Monitoring (JECAM): Update on Multisite Inter-comparison Experiments

NASA Astrophysics Data System (ADS)

Jarvis, I.; Gilliams, S. J. B.; Defourny, P.

2016-12-01

Globally there is significant convergence on agricultural monitoring research questions. The focus of interest usually revolves around crop type, crop area estimation and near real time crop condition and yield forecasting. Notwithstanding this convergence, agricultural systems differ significantly throughout the world, reflecting the diversity of ecosystems they are located in. Consequently, a global system of systems for operational monitoring must be based on multiple approaches. Research is required to compare and assess these approaches to identify which are most appropriate for any given location. To this end the Joint Experiments for Crop Assessment and Monitoring (JECAM) was established in 2009 to as a research platform to allow the global agricultural monitoring community to work towards a set of best practices and recommendations for using earth observation data to map, monitor and report on agricultural productivity globally. The JECAM initiative brings together researchers from a large number of globally distributed, well monitored agricultural test sites that cover a range of crop types, cropping systems and climate regimes. The results of JECAM optical inter-comparison research taking place in the Stimulating Innovation for Global Monitoring of Agriculture (SIGMA) project and the Sentinel-2 for Agriculture project will be discussed. The presentation will also highlight upcoming work on a Synthetic Aperture Radar (SAR) inter-comparison study. The outcome of these projects will result in a set of best practices that cover the range of remote sensing monitoring and reporting needs, including satellite data acquisition, pre-processing techniques, information retrieval and ground data validation. These outcomes provide the R&D foundation for GEOGLAM and will help to inform the development of the GEOGLAM system of systems for global agricultural monitoring.

Fusarium and mycotoxin spectra in Swiss barley are affected by various cropping techniques.

PubMed

Schöneberg, Torsten; Martin, Charlotte; Wettstein, Felix E; Bucheli, Thomas D; Mascher, Fabio; Bertossa, Mario; Musa, Tomke; Keller, Beat; Vogelgsang, Susanne

2016-10-01

Fusarium head blight is one of the most important cereal diseases worldwide. Cereals differ in terms of the main occurring Fusarium species and the infection is influenced by various factors, such as weather and cropping measures. Little is known about Fusarium species in barley in Switzerland, hence harvest samples from growers were collected in 2013 and 2014, along with information on respective cropping factors. The incidence of different Fusarium species was obtained by using a seed health test and mycotoxins were quantified by LC-MS/MS. With these techniques, the most dominant species, F. graminearum, and the most prominent mycotoxin, deoxynivalenol (DON), were identified. Between the three main Swiss cropping systems, Organic, Extenso and Proof of ecological performance, we observed differences with the lowest incidence and toxin accumulation in organically cultivated barley. Hence, we hypothesise that this finding was based on an array of growing techniques within a given cropping system. We observed that barley samples from fields with maize as previous crop had a substantially higher F. graminearum incidence and elevated DON accumulation compared with other previous crops. Furthermore, the use of reduced tillage led to a higher disease incidence and toxin content compared with samples from ploughed fields. Further factors increasing Fusarium infection were high nitrogen fertilisation as well as the application of fungicides and growth regulators. Results from the current study can be used to develop optimised cropping systems that reduce the risks of mycotoxin contamination.

Fusarium and mycotoxin spectra in Swiss barley are affected by various cropping techniques

PubMed Central

Schöneberg, Torsten; Martin, Charlotte; Wettstein, Felix E.; Bucheli, Thomas D.; Mascher, Fabio; Bertossa, Mario; Musa, Tomke; Keller, Beat; Vogelgsang, Susanne

2016-01-01

ABSTRACT Fusarium head blight is one of the most important cereal diseases worldwide. Cereals differ in terms of the main occurring Fusarium species and the infection is influenced by various factors, such as weather and cropping measures. Little is known about Fusarium species in barley in Switzerland, hence harvest samples from growers were collected in 2013 and 2014, along with information on respective cropping factors. The incidence of different Fusarium species was obtained by using a seed health test and mycotoxins were quantified by LC-MS/MS. With these techniques, the most dominant species, F. graminearum, and the most prominent mycotoxin, deoxynivalenol (DON), were identified. Between the three main Swiss cropping systems, Organic, Extenso and Proof of ecological performance, we observed differences with the lowest incidence and toxin accumulation in organically cultivated barley. Hence, we hypothesise that this finding was based on an array of growing techniques within a given cropping system. We observed that barley samples from fields with maize as previous crop had a substantially higher F. graminearum incidence and elevated DON accumulation compared with other previous crops. Furthermore, the use of reduced tillage led to a higher disease incidence and toxin content compared with samples from ploughed fields. Further factors increasing Fusarium infection were high nitrogen fertilisation as well as the application of fungicides and growth regulators. Results from the current study can be used to develop optimised cropping systems that reduce the risks of mycotoxin contamination. PMID:27491813

Analytical steady-state solutions for water-limited cropping systems using saline irrigation water

NASA Astrophysics Data System (ADS)

Skaggs, T. H.; Anderson, R. G.; Corwin, D. L.; Suarez, D. L.

2014-12-01

Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady-state irrigated systems modeling framework that accounts for reduced plant water uptake due to root zone salinity. Two explicit, closed-form analytical solutions for the root zone solute concentration profile are obtained, corresponding to two alternative functional forms of the uptake reduction function. The solutions express a general relationship between irrigation water salinity, irrigation rate, crop salt tolerance, crop transpiration, and (using standard approximations) crop yield. Example applications are illustrated, including the calculation of irrigation requirements for obtaining targeted submaximal yields, and the generation of crop-water production functions for varying irrigation waters, irrigation rates, and crops. Model predictions are shown to be mostly consistent with existing models and available experimental data. Yet the new solutions possess advantages over available alternatives, including: (i) the solutions were derived from a complete physical-mathematical description of the system, rather than based on an ad hoc formulation; (ii) the analytical solutions are explicit and can be evaluated without iterative techniques; (iii) the solutions permit consideration of two common functional forms of salinity induced reductions in crop water uptake, rather than being tied to one particular representation; and (iv) the utilized modeling framework is compatible with leading transient-state numerical models.

Sensitivity analysis of the STICS-MACRO model to identify cropping practices reducing pesticides losses.

PubMed

Lammoglia, Sabine-Karen; Makowski, David; Moeys, Julien; Justes, Eric; Barriuso, Enrique; Mamy, Laure

2017-02-15

STICS-MACRO is a process-based model simulating the fate of pesticides in the soil-plant system as a function of agricultural practices and pedoclimatic conditions. The objective of this work was to evaluate the influence of crop management practices on water and pesticide flows in contrasted environmental conditions. We used the Morris screening sensitivity analysis method to identify the most influential cropping practices. Crop residues management and tillage practices were shown to have strong effects on water percolation and pesticide leaching. In particular, the amount of organic residues added to soil was found to be the most influential input. The presence of a mulch could increase soil water content so water percolation and pesticide leaching. Conventional tillage was also found to decrease pesticide leaching, compared to no-till, which is consistent with many field observations. The effects of the soil, crop and climate conditions tested in this work were less important than those of cropping practices. STICS-MACRO allows an ex ante evaluation of cropping systems and agricultural practices, and of the related pesticides environmental impacts. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and application of SINE multilocus and quantitative genetic markers to study oilseed rape (Brassica napus L.) crops.

PubMed

Allnutt, T R; Roper, K; Henry, C

2008-01-23

A genetic marker system based on the S1 Short Interspersed Elements (SINEs) in the important commercial crop, oilseed rape ( Brassica napus L.) has been developed. SINEs provided a successful multilocus, dominant marker system that was capable of clearly delineating winter- and spring-type crop varieties. Sixteen of 20 varieties tested showed unique profiles from the 17 polymorphic SINE markers generated. The 3' or 5' flank region of nine SINE markers were cloned, and DNA was sequenced. In addition, one putative pre-transposition SINE allele was cloned and sequenced. Two SINE flanking sequences were used to design real-time PCR assays. These quantitative SINE assays were applied to study the genetic structure of eight fields of oilseed rape crops. Studied fields were more genetically diverse than expected for the chosen loci (mean H T = 0.23). The spatial distribution of SINE marker frequencies was highly structured in some fields, suggesting locations of volunteer impurities within the crop. In one case, the assay identified a mislabeling of the crop variety. SINE markers were a useful tool for crop genetics, phylogenetics, variety identification, and purity analysis. The use and further application of quantitative, real-time PCR markers are discussed.

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

PubMed Central

Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

2015-01-01

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983–1999 and 2000–2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6–11.0% and 19.5–92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming. PMID:26336098

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China.

PubMed

Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

2015-01-01

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983-1999 and 2000-2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6-11.0% and 19.5-92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming.

Humans as Sensors: Assessing the Information Value of Qualitative Farmer's Crop Condition Surveys for Crop Yield Monitoring and Forecasting

NASA Astrophysics Data System (ADS)

Beguería, S.

2017-12-01

While large efforts are devoted to developing crop status monitoring and yield forecasting systems trough the use of Earth observation data (mostly remotely sensed satellite imagery) and observational and modeled weather data, here we focus on the information value of qualitative data on crop status from direct observations made by humans. This kind of data has a high value as it reflects the expert opinion of individuals directly involved in the development of the crop. However, they have issues that prevent their direct use in crop monitoring and yield forecasting systems, such as their non-spatially explicit nature, or most importantly their qualitative nature. Indeed, while the human brain is good at categorizing the status of physical systems in terms of qualitative scales (`very good', `good', `fair', etcetera), it has difficulties in quantifying it in physical units. This has prevented the incorporation of this kind of data into systems that make extensive use of numerical information. Here we show an example of using qualitative crop condition data to estimate yields of the most important crops in the US early in the season. We use USDA weekly crop condition reports, which are based on a sample of thousands of reporters including mostly farmers and people in direct contact with them. These reporters provide subjective evaluations of crop conditions, in a scale including five levels ranging from `very poor' to `excellent'. The USDA report indicates, for each state, the proportion of reporters fort each condition level. We show how is it possible to model the underlying non-observed quantitative variable that reflects the crop status on each state, and how this model is consistent across states and years. Furthermore, we show how this information can be used to monitor the status of the crops and to produce yield forecasts early in the season. Finally, we discuss approaches for blending this information source with other, more classical earth data sources such as remote sensing or weather data, in the context of hierarchical regression models.

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

PubMed Central

Calera, Alfonso; Campos, Isidro; Osann, Anna; D’Urso, Guido; Menenti, Massimo

2017-01-01

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. PMID:28492515

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users.

PubMed

Calera, Alfonso; Campos, Isidro; Osann, Anna; D'Urso, Guido; Menenti, Massimo

2017-05-11

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Smart LED lighting for major reductions in power and energy use for plant lighting in space

NASA Astrophysics Data System (ADS)

Poulet, Lucie

Launching or resupplying food, oxygen, and water into space for long-duration, crewed missions to distant destinations, such as Mars, is currently impossible. Bioregenerative life-support systems under development worldwide involving photoautotrophic organisms offer a solution to the food dilemma. However, using traditional Earth-based lighting methods, growth of food crops consumes copious energy, and since sunlight will not always be available at different space destinations, efficient electric lighting solutions are badly needed to reduce the Equivalent System Mass (ESM) of life-support infrastructure to be launched and transported to future space destinations with sustainable human habitats. The scope of the present study was to demonstrate that using LEDs coupled to plant detection, and optimizing spectral and irradiance parameters of LED light, the model crop lettuce (Lactuca sativa L. cv. Waldmann's Green) can be grown with significantly lower electrical energy for plant lighting than using traditional lighting sources. Initial experiments aimed at adapting and troubleshooting a first-generation "smart" plant-detection system coupled to LED arrays resulted in optimizing the detection process for plant position and size to the limits of its current design. Lettuce crops were grown hydroponically in a growth chamber, where temperature, relative humidity, and CO2 level are controlled. Optimal irradiance and red/blue ratio of LED lighting were determined for plant growth during both lag and exponential phases of crop growth. Under optimizing conditions, the efficiency of the automatic detection system was integrated with LED switching and compared to a system in which all LEDs were energized throughout a crop-production cycle. At the end of each cropping cycle, plant fresh and dry weights and leaf area were measured and correlated with the amount of electrical energy (kWh) consumed. Preliminary results indicated that lettuce plants grown under optimizing conditions with red and blue LED lighting required 12 times less energy than with a traditional high-intensity discharge lighting system. This study paves the way for refinement of the smart lighting system and further, major reductions in ESM for space life-support systems and for ground-based controlled-environment agriculture. Project supported by NASA grant number NNX09AL99G.

Intercropping Competition between Apple Trees and Crops in Agroforestry Systems on the Loess Plateau of China

PubMed Central

Gao, Lubo; Xu, Huasen; Bi, Huaxing; Xi, Weimin; Bao, Biao; Wang, Xiaoyan; Bi, Chao; Chang, Yifang

2013-01-01

Agroforestry has been widely practiced in the Loess Plateau region of China because of its prominent effects in reducing soil and water losses, improving land-use efficiency and increasing economic returns. However, the agroforestry practices may lead to competition between crops and trees for underground soil moisture and nutrients, and the trees on the canopy layer may also lead to shortage of light for crops. In order to minimize interspecific competition and maximize the benefits of tree-based intercropping systems, we studied photosynthesis, growth and yield of soybean (Glycine max L. Merr.) and peanut (Arachis hypogaea L.) by measuring photosynthetically active radiation, net photosynthetic rate, soil moisture and soil nutrients in a plantation of apple (Malus pumila M.) at a spacing of 4 m × 5 m on the Loess Plateau of China. The results showed that for both intercropping systems in the study region, soil moisture was the primary factor affecting the crop yields followed by light. Deficiency of the soil nutrients also had a significant impact on crop yields. Compared with soybean, peanut was more suitable for intercropping with apple trees to obtain economic benefits in the region. We concluded that apple-soybean and apple-peanut intercropping systems can be practical and beneficial in the region. However, the distance between crops and tree rows should be adjusted to minimize interspecies competition. Agronomic measures such as regular canopy pruning, root barriers, additional irrigation and fertilization also should be applied in the intercropping systems. PMID:23936246

Intercropping competition between apple trees and crops in agroforestry systems on the Loess Plateau of China.

PubMed

Gao, Lubo; Xu, Huasen; Bi, Huaxing; Xi, Weimin; Bao, Biao; Wang, Xiaoyan; Bi, Chao; Chang, Yifang

2013-01-01

Agroforestry has been widely practiced in the Loess Plateau region of China because of its prominent effects in reducing soil and water losses, improving land-use efficiency and increasing economic returns. However, the agroforestry practices may lead to competition between crops and trees for underground soil moisture and nutrients, and the trees on the canopy layer may also lead to shortage of light for crops. In order to minimize interspecific competition and maximize the benefits of tree-based intercropping systems, we studied photosynthesis, growth and yield of soybean (Glycine max L. Merr.) and peanut (Arachis hypogaea L.) by measuring photosynthetically active radiation, net photosynthetic rate, soil moisture and soil nutrients in a plantation of apple (Malus pumila M.) at a spacing of 4 m × 5 m on the Loess Plateau of China. The results showed that for both intercropping systems in the study region, soil moisture was the primary factor affecting the crop yields followed by light. Deficiency of the soil nutrients also had a significant impact on crop yields. Compared with soybean, peanut was more suitable for intercropping with apple trees to obtain economic benefits in the region. We concluded that apple-soybean and apple-peanut intercropping systems can be practical and beneficial in the region. However, the distance between crops and tree rows should be adjusted to minimize interspecies competition. Agronomic measures such as regular canopy pruning, root barriers, additional irrigation and fertilization also should be applied in the intercropping systems.

Crop Row Detection in Maize Fields Inspired on the Human Visual Perception

PubMed Central

Romeo, J.; Pajares, G.; Montalvo, M.; Guerrero, J. M.; Guijarro, M.; Ribeiro, A.

2012-01-01

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection. PMID:22623899

Dynamic optimization of CELSS crop photosynthetic rate by computer-assisted feedback control

NASA Astrophysics Data System (ADS)

Chun, C.; Mitchell, C. A.

1997-01-01

A procedure for dynamic optimization of net photosynthetic rate (Pn) for crop production in Controlled Ecological Life-Support Systems (CELSS) was developed using leaf lettuce as a model crop. Canopy Pn was measured in real time and fed back for environmental control. Setpoints of photosynthetic photon flux (PPF) and CO_2 concentration for each hour of the crop-growth cycle were decided by computer to reach a targeted Pn each day. Decision making was based on empirical mathematical models combined with rule sets developed from recent experimental data. Comparisons showed that dynamic control resulted in better yield per unit energy input to the growth system than did static control. With comparable productivity parameters and potential for significant energy savings, dynamic control strategies will contribute greatly to the sustainability of space-deployed CELSS.

An Integrated Biogeochemical and Biophysical Analysis of Bioenergy Crops

NASA Astrophysics Data System (ADS)

Liang, M.; Song, Y.; Barman, R.; Jain, A. K.

2010-12-01

Bioenergy crops are becoming increasingly important with growing concerns about the energy demand and climate change and the need to replace fossil fuels with carbon-neutral renewable sources of energy. The transition to a biofuel-based energy supply raises many questions such as: how and where to grow energy crops, what will be the impacts of growing large scale biofuel crops on climate system, the hydrological cycle and soil biogeochemistry. We are developing and applying an integrated system modeling framework to investigate the biophysical, physiological, and biogeochemical systems governing important processes that regulate crop growth such as water, energy and nutrient cycles. The framework has a two-big-leaf canopy scheme for photosynthesis, stomatal conductance, leaf temperature and energy fluxes. The soil/snow hydrology consists of 10 layers for soil and up to 5 layers for snow. The biogeochemistry component explicitly accounts for coupled carbon and nitrogen dynamics. The feedstocks currently considered include corn stover, Miscanthus and switchgrass. The parameters used for simulation of each crop have been calibrated using field experimental data from the US. The use of this modeling capability will be demonstrated through its applications to study the environmental effects (through changes in albedo and evapotranspiration) of biofuel production as well as the effective management practice in the United States.

Suggestions for crops grown in controlled ecological life-support systems, based on attractive vegetarian diets.

PubMed

Salisbury, F B; Clark, M A

1996-01-01

Assuming that crops grown in controlled ecological life-support systems (CELSS) should provide a basis for meals that are both nutritious and attractive (to taste and vision), and that CELSS diets on the moon or Mars or in space-craft during long voyages will have to be mostly vegetarian, a workshop was convened at the Johnson Space Center, Houston, Texas, U.S.A. on 19 to 21 January, 1994. Participants consisted of trained nutritionists and others; many of the approximately 18 presenters who discussed possible diets were practicing vegetarians, some for more than two decades. Considering all the presentations, seven conclusions (or points for discussion) could be formulated: nutritious vegetarian diets are relatively easily to formulate, vegetarian diets are healthy, variety is essential in vegetarian diets, some experiences (e.g., Bios-3 and Biosphere 2) are relevant to planning of CELSS diets, physical constraints will limit the choice of crops, a preliminary list of recommended crops can be formulated, and this line of research has some potential practical spinoffs. The list of crops and the reasons for including specific crops might be of interest to professionals in the field of health and nutrition as well as to those who are designing closed ecological systems.

Suggestions for crops grown in controlled ecological life-support systems, based on attractive vegetarian diets

NASA Technical Reports Server (NTRS)

Salisbury, F. B.; Clark, M. A.

1996-01-01

Assuming that crops grown in controlled ecological life-support systems (CELSS) should provide a basis for meals that are both nutritious and attractive (to taste and vision), and that CELSS diets on the moon or Mars or in space-craft during long voyages will have to be mostly vegetarian, a workshop was convened at the Johnson Space Center, Houston, Texas, U.S.A. on 19 to 21 January, 1994. Participants consisted of trained nutritionists and others; many of the approximately 18 presenters who discussed possible diets were practicing vegetarians, some for more than two decades. Considering all the presentations, seven conclusions (or points for discussion) could be formulated: nutritious vegetarian diets are relatively easily to formulate, vegetarian diets are healthy, variety is essential in vegetarian diets, some experiences (e.g., Bios-3 and Biosphere 2) are relevant to planning of CELSS diets, physical constraints will limit the choice of crops, a preliminary list of recommended crops can be formulated, and this line of research has some potential practical spinoffs. The list of crops and the reasons for including specific crops might be of interest to professionals in the field of health and nutrition as well as to those who are designing closed ecological systems.

Suggestions for crops grown in controlled ecological life-support systems, based on attractive vegetarian diets

NASA Astrophysics Data System (ADS)

Salisbury, F. B.; Clark, M. A. Z.

Assuming that crops grown in controlled ecological life-support systems (CELSS) should provide a basis for meals that are both nutritious and attractive (to taste and vision), and that CELSS diets on the moon or Mars or in space-craft during long voyages will have to be mostly vegetarian, a workshop was convened at the Johnson Space Center, Houston, Texas, U.S.A. on 19 to 21 January, 1994. Participants consisted of trained nutritionists and others; many of the approximately 18 presenters who discussed possible diets were practicing vegetarians, some for more than two decades. Considering all the presentations, seven conclusions (or points for discussion) could be formulated: nutritious vegetarian diets are relatively easily to formulate, vegetarian diets are healthy, variety is essential in vegetarian diets, some experiences (e.g., Bios-3 and Biosphere 2) are relevant to planning of CELSS diets, physical constraints will limit the choice of crops, a preliminary list of recommended crops can be formulated, and this line of research has some potential practical spinoffs. The list of crops and the reasons for including specific crops might be of interest to professionals in the field of health and nutrition as well as to those who are designing closed ecological systems.

Integrating remote sensing, geographic information system and modeling for estimating crop yield

NASA Astrophysics Data System (ADS)

Salazar, Luis Alonso

This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

Spatial variability of soil carbon and nitrogen in two hybrid poplar-hay crop systems in southern Quebec, Canada

NASA Astrophysics Data System (ADS)

Winans, K. S.

2013-12-01

Canadian agricultural operations contribute approximately 8% of national GHG emissions each year, mainly from fertilizers, enteric fermentation, and manure management (Environment Canada, 2010). With improved management of cropland and forests, it is possible to mitigate GHG emissions through carbon (C) sequestration while enhancing soil and crop productivity. Tree-based intercropped (TBI) systems, consisting of a fast-growing woody species such as poplar (Populus spp.) planted in widely-spaced rows with crops cultivated between tree rows, were one of the technologies prioritized for investigation by the Agreement for the Agricultural Greenhouse Gases Program (AAGGP), because fast growing trees can be a sink for atmospheric carbon-dioxide (CO2) as well as a long-term source of farm income (Montagnini and Nair, 2004). However, there are relatively few estimates of the C sequestration in the trees or due to tree inputs (e.g., fine root turnover, litterfall that gets incorporated into SOC), and hybrid poplars grow exponentially in the first 8-10 years after planting. With the current study, our objectives were (1) to evaluate spatial variation in soil C and nitrogen (N) storage, CO2 and nitrogen oxide (N20), and tree and crop productivity for two hybrid poplar-hay intercrop systems at year 9, comparing TBI vs. non-TBI systems, and (2) to evaluate TBI systems in the current context of C trading markets, which value C sequestration in trees, unharvested crop components, and soils of TBI systems. The study results will provide meaningful measures that indicate changes due to TBI systems in the short-term and in the long-term, in terms of GHG mitigation, enhanced soil and crop productivity, as well as the expected economic returns in TBI systems.

Nitrous oxide emissions in cover crop-based corn production systems

NASA Astrophysics Data System (ADS)

Davis, Brian Wesley

Nitrous oxide (N2O) is a potent greenhouse gas; the majority of N2O emissions are the result of agricultural management, particularly the application of N fertilizers to soils. The relationship of N2O emissions to varying sources of N (manures, mineral fertilizers, and cover crops) has not been well-evaluated. Here we discussed a novel methodology for estimating precipitation-induced pulses of N2O using flux measurements; results indicated that short-term intensive time-series sampling methods can adequately describe the magnitude of these pulses. We also evaluated the annual N2O emissions from corn-cover crop (Zea mays; cereal rye [Secale cereale], hairy vetch [Vicia villosa ], or biculture) production systems when fertilized with multiple rates of subsurface banded poultry litter, as compared with tillage incorporation or mineral fertilizer. N2O emissions increased exponentially with total N rate; tillage decreased emissions following cover crops with legume components, while the effect of mineral fertilizer was mixed across cover crops.

Assessing environmental impacts of constructed wetland effluents for vegetable crop irrigation.

PubMed

Castorina, A; Consoli, S; Barbagallo, S; Branca, F; Farag, A; Licciardello, F; Cirelli, G L

2016-01-01

The objective of this study was to monitor and assess environmental impacts of reclaimed wastewater (RW), used for irrigation of vegetable crops, on soil, crop quality and irrigation equipment. During 2013, effluents of a horizontal sub-surface flow constructed treatment wetland (TW) system, used for tertiary treatment of sanitary wastewater from a small rural municipality located in Eastern Sicily (Italy), were reused by micro-irrigation techniques to irrigate vegetable crops. Monitoring programs, based on in situ and laboratory analyses were performed for assessing possible adverse effects on water-soil-plant systems caused by reclaimed wastewater reuse. In particular, experimental results evidenced that Escherichia coli content found in RW would not present a risk for rotavirus infection following WHO (2006) standards. Irrigated soil was characterized by a certain persistence of microbial contamination and among the studied vegetable crops, lettuce responds better, than zucchini and eggplants, to the irrigation with low quality water, evidencing a bettering of nutraceutical properties and production parameters.

Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China.

PubMed

Xiong, Zhengqin; Liu, Yinglie; Wu, Zhen; Zhang, Xiaolin; Liu, Pingli; Huang, Taiqing

2015-12-02

Double rice (DR) and upland crop-single rice (UR) systems are the major rice-based cropping systems in China, yet differences in net global warming potential (NGWP) and greenhouse gas intensity (GHGI) between the two systems are poorly documented. Accordingly, a 3-year field experiment was conducted to simultaneously measure methane (CH4) and nitrous oxide (N2O) emissions and changes in soil organic carbon (SOC) in oil rape-rice-rice and wheat-rice (representing DR and UR, respectively) systems with straw incorporation (0, 3 and 6 t/ha) during the rice-growing seasons. Compared with the UR system, the annual CH4, N2O, grain yield and NGWP were significantly increased in the DR system, though little effect on SOC sequestration or GHGI was observed without straw incorporation. Straw incorporation increased CH4 emission and SOC sequestration but had no significant effect on N2O emission in both systems. Averaged over the three study years, straw incorporation had no significant effect on NGWP and GHGI in the UR system, whereas these parameters were greatly increased in the DR system, i.e., by 108% (3 t/ha) and 180% (6 t/ha) for NGWP and 103% (3 t/ha) and 168% (6 t/ha) for GHGI.

Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China

PubMed Central

Xiong, Zhengqin; Liu, Yinglie; Wu, Zhen; Zhang, Xiaolin; Liu, Pingli; Huang, Taiqing

2015-01-01

Double rice (DR) and upland crop-single rice (UR) systems are the major rice-based cropping systems in China, yet differences in net global warming potential (NGWP) and greenhouse gas intensity (GHGI) between the two systems are poorly documented. Accordingly, a 3-year field experiment was conducted to simultaneously measure methane (CH4) and nitrous oxide (N2O) emissions and changes in soil organic carbon (SOC) in oil rape-rice-rice and wheat-rice (representing DR and UR, respectively) systems with straw incorporation (0, 3 and 6 t/ha) during the rice-growing seasons. Compared with the UR system, the annual CH4, N2O, grain yield and NGWP were significantly increased in the DR system, though little effect on SOC sequestration or GHGI was observed without straw incorporation. Straw incorporation increased CH4 emission and SOC sequestration but had no significant effect on N2O emission in both systems. Averaged over the three study years, straw incorporation had no significant effect on NGWP and GHGI in the UR system, whereas these parameters were greatly increased in the DR system, i.e., by 108% (3 t/ha) and 180% (6 t/ha) for NGWP and 103% (3 t/ha) and 168% (6 t/ha) for GHGI. PMID:26626733

Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China

NASA Astrophysics Data System (ADS)

Xiong, Zhengqin; Liu, Yinglie; Wu, Zhen; Zhang, Xiaolin; Liu, Pingli; Huang, Taiqing

2015-12-01

Double rice (DR) and upland crop-single rice (UR) systems are the major rice-based cropping systems in China, yet differences in net global warming potential (NGWP) and greenhouse gas intensity (GHGI) between the two systems are poorly documented. Accordingly, a 3-year field experiment was conducted to simultaneously measure methane (CH4) and nitrous oxide (N2O) emissions and changes in soil organic carbon (SOC) in oil rape-rice-rice and wheat-rice (representing DR and UR, respectively) systems with straw incorporation (0, 3 and 6 t/ha) during the rice-growing seasons. Compared with the UR system, the annual CH4, N2O, grain yield and NGWP were significantly increased in the DR system, though little effect on SOC sequestration or GHGI was observed without straw incorporation. Straw incorporation increased CH4 emission and SOC sequestration but had no significant effect on N2O emission in both systems. Averaged over the three study years, straw incorporation had no significant effect on NGWP and GHGI in the UR system, whereas these parameters were greatly increased in the DR system, i.e., by 108% (3 t/ha) and 180% (6 t/ha) for NGWP and 103% (3 t/ha) and 168% (6 t/ha) for GHGI.

AgRISTARS. Semiannual program review presentation to level 1, interagency Coordination Committee

NASA Technical Reports Server (NTRS)

1982-01-01

Results are presented for (1) spring small grains; (2) summer crops/corn and soybeans; and (3) crop signature characterization. The development of an early season approach, profile and segment based change estimation, and future satellite and sensor system requirements are discussed. Documentation for the inventory technology development project is included.

Effects of seeding rate and poultry litter on weed suppression from a rolled cereal rye cover crop

USDA-ARS?s Scientific Manuscript database

Growing enough cover crop biomass to adequately suppress weeds is one of the primary challenges in reduced-tillage systems that rely on mulch-based weed suppression. We investigated two approaches to increasing cereal rye biomass for improved weed suppression: (1) increasing soil fertility and (2) i...

Northwest Ohio crop yield benefits of water capture and subirrigation based on future climate change projections

USDA-ARS?s Scientific Manuscript database

Climate change projections for the Midwest U.S. indicate increased growing season crop water deficits in the future that will adversely impact the sustainability of agricultural production. Systems that capture water on site for later subirrigation use have potential as a climate adaptation strateg...

Manipulation of soil microbes using higher biomass cropping systems to sustain soil health in cotton-based agroecosystems

USDA-ARS?s Scientific Manuscript database

The semiarid Texas High Plains produces ~30% of U.S. cotton (Gossypium hirsutum L.). Agricultural production, however, is experiencing a transition from irrigated to dryland crop production due to reductions in water availability from the Ogallala aquifer. Additional challenges are imposed by extrem...

Implications of observed and simulated soil carbon sequestration for management options in corn-based rotations

USDA-ARS?s Scientific Manuscript database

Managing cropping systems to sequester soil organic carbon (SOC) improves soil health and a system’s resiliency to impacts of changing climate. Our objectives were to 1) monitor SOC from a bio-energy cropping study in central Pennsylvania that included a corn-soybean-alfalfa rotation, switchgrass, a...

Implications of observed and simulated soil carbon sequestration for management options in corn-based rotations

USDA-ARS?s Scientific Manuscript database

Managing cropping systems to sequester soil organic carbon (SOC) improves soil health and a system’s resiliency to impacts of changing climate. Our objectives were to 1) monitor SOC from a bio-energy cropping study in central Pennsylvania that included a corn-soybean-alfalfa rotation, switchgrass, ...

Simulating crop growth with Expert-N-GECROS under different site conditions in Southwest Germany

NASA Astrophysics Data System (ADS)

Poyda, Arne; Ingwersen, Joachim; Demyan, Scott; Gayler, Sebastian; Streck, Thilo

2016-04-01

When feedbacks between the land surface and the atmosphere are investigated by Atmosphere-Land surface-Crop-Models (ALCM) it is fundamental to accurately simulate crop growth dynamics as plants directly influence the energy partitioning at the plant-atmosphere interface. To study both the response and the effect of intensive agricultural crop production systems on regional climate change in Southwest Germany, the crop growth model GECROS (YIN & VAN LAAR, 2005) was calibrated based on multi-year field data from typical crop rotations in the Kraichgau and Swabian Alb regions. Additionally, the SOC (soil organic carbon) model DAISY (MÜLLER et al., 1998) was implemented in the Expert-N model tool (ENGEL & PRIESACK, 1993) and combined with GECROS. The model was calibrated based on a set of plant (BBCH, LAI, plant height, aboveground biomass, N content of biomass) and weather data for the years 2010 - 2013 and validated with the data of 2014. As GECROS adjusts the root-shoot partitioning in response to external conditions (water, nitrogen, CO2), it is suitable to simulate crop growth dynamics under changing climate conditions and potentially more frequent stress situations. As C and N pools and turnover rates in soil as well as preceding crop effects were expected to considerably influence crop growth, the model was run in a multi-year, dynamic way. Crop residues and soil mineral N (nitrate, ammonium) available for the subsequent crop were accounted for. The model simulates growth dynamics of winter wheat, winter rape, silage maize and summer barley at the Kraichgau and Swabian Alb sites well. The Expert-N-GECROS model is currently parameterized for crops with potentially increasing shares in future crop rotations. First results will be shown.

Investment risk in bioenergy crops

DOE PAGES

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia; ...

2015-11-18

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Investment risk in bioenergy crops

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Utilization of GIS/GPS-Based Information Technology in Commercial Crop Decision Making in California, Washington, Oregon, Idaho, and Arizona

PubMed Central

Thomas, C. S.; Skinner, P. W.; Fox, A. D.; Greer, C. A.; Gubler, W. D.

2002-01-01

Ground-based weather, plant-stage measurements, and remote imagery were geo-referenced in geographic information system (GIS) software using an integrated approach to determine insect and disease risk and crop cultural requirements. Weather forecasts and disease weather forecasts for agricultural areas were constructed with elevation, weather, and satellite data. Models for 6 insect pests and 12 diseases of various crops were calculated and presented daily in georeferenced maps for agricultural areas in northern California and Washington. Grape harvest dates and yields also were predicted with high accuracy. The data generated from the GIS global positioning system (GPS) analyses were used to make management decisions over a large number of acres in California, Washington, Oregon, Idaho, and Arizona. Information was distributed daily over the Internet as regional weather, insect, and disease risk maps as industry-sponsored or subscription-based products. Use of GIS/GPS technology for semi-automated data analysis is discussed. PMID:19265934

Wireless Sensor Network-Based Greenhouse Environment Monitoring and Automatic Control System for Dew Condensation Prevention

PubMed Central

Park, Dae-Heon; Park, Jang-Woo

2011-01-01

Dew condensation on the leaf surface of greenhouse crops can promote diseases caused by fungus and bacteria, affecting the growth of the crops. In this paper, we present a WSN (Wireless Sensor Network)-based automatic monitoring system to prevent dew condensation in a greenhouse environment. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for driving devices for adjusting the environment inside greenhouse and an environment server for data storage and processing. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent dew condensation phenomena on the crop’s surface acting as an important element for prevention of diseases infections. We also constructed a physical model resembling the typical greenhouse in order to verify the performance of our system with regard to dew condensation control. PMID:22163813

Life-cycle phosphorus management of the crop production-consumption system in China, 1980-2012.

PubMed

Wu, Huijun; Yuan, Zengwei; Gao, Liangmin; Zhang, Ling; Zhang, Yongliang

2015-01-01

Phosphorus (P) is an essential resource for agriculture and also a pollutant capable of causing eutrophication. The possibility of a future P scarcity and the requirement to improve the environment quality necessitate P management to increase the efficiency of P use. This study applied a substance flow analysis (SFA) to implement a P management procedure in a crop production-consumption (PMCPC) system model. This model determined the life-cycle P use efficiency (PUE) of the crop production-consumption system in China during 1980-2012. The system includes six subsystems: fertilizer manufacturing, crop cultivation, crop processing, livestock breeding, rural consumption, and urban consumption. Based on this model, the P flows and PUEs of the subsystems were identified and quantified using data from official statistical databases, published literature, questionnaires, and interviews. The results showed that the total PUE of the crop production-consumption system in China was low, notably from 1980 to 2005, and increased from 7.23% in 1980 to 20.13% in 2012. Except for fertilizer manufacturing, the PUEs of the six subsystems were also low. The PUEs in the urban consumption subsystem and the crop cultivation subsystem were less than 40%. The PUEs of other subsystems, such as the rural consumption subsystem and the livestock breeding subsystem, were also low and even decreased during these years. Measures aimed to improve P management practices in China have been proposed such as balancing fertilization, disposing livestock excrement, adjusting livestock feed, changing the diet of residents, and raising the waste disposal level, etc. This study also discussed several limitations related with the model and data. Conducting additional related studies on other regions and combining the analysis of risks with opportunities may be necessary to develop effective management strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

A generic model to simulate air-borne diseases as a function of crop architecture.

PubMed

Casadebaig, Pierre; Quesnel, Gauthier; Langlais, Michel; Faivre, Robert

2012-01-01

In a context of pesticide use reduction, alternatives to chemical-based crop protection strategies are needed to control diseases. Crop and plant architectures can be viewed as levers to control disease outbreaks by affecting microclimate within the canopy or pathogen transmission between plants. Modeling and simulation is a key approach to help analyze the behaviour of such systems where direct observations are difficult and tedious. Modeling permits the joining of concepts from ecophysiology and epidemiology to define structures and functions generic enough to describe a wide range of epidemiological dynamics. Additionally, this conception should minimize computing time by both limiting the complexity and setting an efficient software implementation. In this paper, our aim was to present a model that suited these constraints so it could first be used as a research and teaching tool to promote discussions about epidemic management in cropping systems. The system was modelled as a combination of individual hosts (population of plants or organs) and infectious agents (pathogens) whose contacts are restricted through a network of connections. The system dynamics were described at an individual scale. Additional attention was given to the identification of generic properties of host-pathogen systems to widen the model's applicability domain. Two specific pathosystems with contrasted crop architectures were considered: ascochyta blight on pea (homogeneously layered canopy) and potato late blight (lattice of individualized plants). The model behavior was assessed by simulation and sensitivity analysis and these results were discussed against the model ability to discriminate between the defined types of epidemics. Crop traits related to disease avoidance resulting in a low exposure, a slow dispersal or a de-synchronization of plant and pathogen cycles were shown to strongly impact the disease severity at the crop scale.

Effect of diversified crop rotations on groundwater levels and crop water productivity in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Xiaolin; Chen, Yuanquan; Pacenka, Steven; Gao, Wangsheng; Ma, Li; Wang, Guangya; Yan, Peng; Sui, Peng; Steenhuis, Tammo S.

2015-03-01

Water shortage is the major bottleneck that limits sustainable yield of agriculture in the North China Plain. Due to the over-exploitation of groundwater for irrigating the winter wheat-summer maize double cropping systems, a groundwater crisis is becoming increasingly serious. To help identify more efficient and sustainable utilization of the limited water resources, the water consumption and water use efficiency of five irrigated cropping systems were calculated and the effect of cropping systems on groundwater table changes was estimated based on a long term field experiment from 2003 to 2013 in the North China Plain interpreted using a soil-water-balance model. The five cropping systems included sweet potato → cotton → sweet potato → winter wheat-summer maize (SpCSpWS, 4-year cycle), ryegrass-cotton → peanuts → winter wheat-summer maize (RCPWS, 3-year cycle), peanuts → winter wheat-summer maize (PWS, 2-year cycle), winter wheat-summer maize (WS, 1-year cycle), and continuous cotton (Cont C). The five cropping systems had a wide range of annual average actual evapotranspiration (ETa): Cont C (533 mm/year) < SpCSpWS (556 mm/year) < PWS (615 mm/year) < RCPWS (650 mm/year) < WS rotation (734 mm/year). The sequence of the simulated annual average groundwater decline due to the five cropping systems was WS (1.1 m/year) > RCPWS (0.7 m/year) > PWS (0.6 m/year) > SPCSPWS and Cont C (0.4 m/year). The annual average economic output water use efficiency (WUEe) increased in the order SpCSpWS (11.6 yuan ¥ m-3) > RCPWS (9.0 ¥ m-3) > PWS (7.3 ¥ m-3) > WS (6.8 ¥ m-3) > Cont C (5.6 ¥ m-3) from 2003 to 2013. Results strongly suggest that diversifying crop rotations could play a critically important role in mitigating the over-exploitation of the groundwater, while ensuring the food security or boosting the income of farmers in the North China Plain.

The biogeochemistry of bioenergy landscapes: carbon, nitrogen, and water considerations.

PubMed

Robertson, G Philip; Hamilton, Stephen K; Del Grosso, Stephen J; Parton, William J

2011-06-01

The biogeochemical liabilities of grain-based crop production for bioenergy are no different from those of grain-based food production: excessive nitrate leakage, soil carbon and phosphorus loss, nitrous oxide production, and attenuated methane uptake. Contingent problems are well known, increasingly well documented, and recalcitrant: freshwater and coastal marine eutrophication, groundwater pollution, soil organic matter loss, and a warming atmosphere. The conversion of marginal lands not now farmed to annual grain production, including the repatriation of Conservation Reserve Program (CRP) and other conservation set-aside lands, will further exacerbate the biogeochemical imbalance of these landscapes, as could pressure to further simplify crop rotations. The expected emergence of biorefinery and combustion facilities that accept cellulosic materials offers an alternative outcome: agricultural landscapes that accumulate soil carbon, that conserve nitrogen and phosphorus, and that emit relatively small amounts of nitrous oxide to the atmosphere. Fields in these landscapes are planted to perennial crops that require less fertilizer, that retain sediments and nutrients that could otherwise be transported to groundwater and streams, and that accumulate carbon in both soil organic matter and roots. If mixed-species assemblages, they additionally provide biodiversity services. Biogeochemical responses of these systems fall chiefly into two areas: carbon neutrality and water and nutrient conservation. Fluxes must be measured and understood in proposed cropping systems sufficient to inform models that will predict biogeochemical behavior at field, landscape, and regional scales. Because tradeoffs are inherent to these systems, a systems approach is imperative, and because potential biofuel cropping systems and their environmental contexts are complex and cannot be exhaustively tested, modeling will be instructive. Modeling alternative biofuel cropping systems converted from different starting points, for example, suggests that converting CRP to corn ethanol production under conventional tillage results in substantially increased net greenhouse gas (GHG) emissions that can be only partly mitigated with no-till management. Alternatively, conversion of existing cropland or prairie to switchgrass production results in a net GHG sink. Outcomes and policy must be informed by science that adequately quantifies the true biogeochemical costs and advantages of alternative systems.

Vertical farming increases lettuce yield per unit area compared to conventional horizontal hydroponics.

PubMed

Touliatos, Dionysios; Dodd, Ian C; McAinsh, Martin

2016-08-01

Vertical farming systems (VFS) have been proposed as an engineering solution to increase productivity per unit area of cultivated land by extending crop production into the vertical dimension. To test whether this approach presents a viable alternative to horizontal crop production systems, a VFS (where plants were grown in upright cylindrical columns) was compared against a conventional horizontal hydroponic system (HHS) using lettuce ( Lactuca sativa L . cv. "Little Gem") as a model crop. Both systems had similar root zone volume and planting density. Half-strength Hoagland's solution was applied to plants grown in perlite in an indoor controlled environment room, with metal halide lamps providing artificial lighting. Light distribution (photosynthetic photon flux density, PPFD) and yield (shoot fresh weight) within each system were assessed. Although PPFD and shoot fresh weight decreased significantly in the VFS from top to base, the VFS produced more crop per unit of growing floor area when compared with the HHS. Our results clearly demonstrate that VFS presents an attractive alternative to horizontal hydroponic growth systems and suggest that further increases in yield could be achieved by incorporating artificial lighting in the VFS.

Folksong based appraisal of bioecocultural heritage of sorghum (Sorghum bicolor (L.) Moench): A new approach in ethnobiology

PubMed Central

Mekbib, Firew

2009-01-01

Background Sorghum is one of the main staple crops for the world's poorest and most food insecure people. As Ethiopia is the centre of origin and diversity for sorghum, the crop has been cultivated for thousands of years and hence the heritage of the crop is expected to be rich. Folksong based appraisal of bioecocultural heritage has not been done before. Methods In order to assess the bioecocultural heritage of sorghum by folksongs various research methods were employed. These included focus group discussions with 360 farmers, direct on-farm participatory monitoring and observation with 120 farmers, and key informant interviews with 60 farmers and development agents. Relevant secondary data was also collected from the museum curators and historians. Results The crop is intimately associated with the life of the farmers. The association of sorghum with the farmers from seed selection to utilization is presented using folksongs. These include both tune and textual (ballad stories or poems) types. Folksongs described how farmers maintain a number of varieties on-farm for many biological, socio-economic, ecological, ethnological and cultural reasons. Farmers describe sorghum as follows: Leaf number is less than twenty; Panicle hold a thousand seeds; a clever farmer takes hold of it. In addition, they described the various farmers' varieties ethnobotanically by songs. The relative importance of sorghum vis-à-vis others crops is similarly explained in folksong terms. Conclusion The qualitative description of farmers' characterisation of the crop systems based on folksongs is a new system of appraising farmers' bioecocultural heritage. Hence, researchers, in addition to formal and quantitative descriptions, should use the folksong system for enhanced characterisation and utilization of bioecocultural heritages. In general, the salient characteristics of the folksongs used in describing the bioecocultural heritages are their oral traditions, varied function, communal or individual recreation and message transmissions. PMID:19575802

Embodied crop calories in animal products

NASA Astrophysics Data System (ADS)

Pradhan, Prajal; Lüdeke, Matthias K. B.; Reusser, Dominik E.; Kropp, Jürgen P.

2013-12-01

Increases in animal products consumption and the associated environmental consequences have been a matter of scientific debate for decades. Consequences of such increases include rises in greenhouse gas emissions, growth of consumptive water use, and perturbation of global nutrients cycles. These consequences vary spatially depending on livestock types, their densities and their production system. In this letter, we investigate the spatial distribution of embodied crop calories in animal products. On a global scale, about 40% of the global crop calories are used as livestock feed (we refer to this ratio as crop balance for livestock) and about 4 kcal of crop products are used to generate 1 kcal of animal products (embodied crop calories of around 4). However, these values vary greatly around the world. In some regions, more than 100% of the crops produced is required to feed livestock requiring national or international trade to meet the deficit in livestock feed. Embodied crop calories vary between less than 1 for 20% of the livestock raising areas worldwide and greater than 10 for another 20% of the regions. Low values of embodied crop calories are related to production systems for ruminants based on fodder and forage, while large values are usually associated with production systems for non-ruminants fed on crop products. Additionally, we project the future feed demand considering three scenarios: (a) population growth, (b) population growth and changes in human dietary patterns and (c) changes in population, dietary patterns and feed conversion efficiency. When considering dietary changes, we project the global feed demand to be almost doubled (1.8-2.3 times) by 2050 compared to 2000, which would force us to produce almost equal or even more crops to raise our livestock than to directly nourish ourselves in the future. Feed demand is expected to increase over proportionally in Africa, South-Eastern Asia and Southern Asia, putting additional stress on these regions.

Estimation of crop water requirements using remote sensing for operational water resources management

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Spiliotopoulos, Marios; Tzabiras, John; Loukas, Athanasios; Mylopoulos, Nikitas

2015-06-01

An integrated modeling system, developed in the framework of "Hydromentor" research project, is applied to evaluate crop water requirements for operational water resources management at Lake Karla watershed, Greece. The framework includes coupled components for operation of hydrotechnical projects (reservoir operation and irrigation works) and estimation of agricultural water demands at several spatial scales using remote sensing. The study area was sub-divided into irrigation zones based on land use maps derived from Landsat 5 TM images for the year 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used to derive actual evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat TM imagery. Agricultural water needs were estimated using the FAO method for each zone and each control node of the system for a number of water resources management strategies. Two operational strategies of hydro-technical project development (present situation without operation of the reservoir and future situation with the operation of the reservoir) are coupled with three water demand strategies. In total, eight (8) water management strategies are evaluated and compared. The results show that, under the existing operational water resources management strategies, the crop water requirements are quite large. However, the operation of the proposed hydro-technical projects in Lake Karla watershed coupled with water demand management measures, like improvement of existing water distribution systems, change of irrigation methods, and changes of crop cultivation could alleviate the problem and lead to sustainable and ecological use of water resources in the study area.

Exploring U.S Cropland - A Web Service based Cropland Data Layer Visualization, Dissemination and Querying System (Invited)

NASA Astrophysics Data System (ADS)

Yang, Z.; Han, W.; di, L.

2010-12-01

The National Agricultural Statistics Service (NASS) of the USDA produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, U.S. crop specific land cover classification. These digital data layers are widely used for a variety of applications by universities, research institutions, government agencies, and private industry in climate change studies, environmental ecosystem studies, bioenergy production & transportation planning, environmental health research and agricultural production decision making. The CDL is also used internally by NASS for crop acreage and yield estimation. Like most geospatial data products, the CDL product is only available by CD/DVD delivery or online bulk file downloading via the National Research Conservation Research (NRCS) Geospatial Data Gateway (external users) or in a printed paper map format. There is no online geospatial information access and dissemination, no crop visualization & browsing, no geospatial query capability, nor online analytics. To facilitate the application of this data layer and to help disseminating the data, a web-service based CDL interactive map visualization, dissemination, querying system is proposed. It uses Web service based service oriented architecture, adopts open standard geospatial information science technology and OGC specifications and standards, and re-uses functions/algorithms from GeoBrain Technology (George Mason University developed). This system provides capabilities of on-line geospatial crop information access, query and on-line analytics via interactive maps. It disseminates all data to the decision makers and users via real time retrieval, processing and publishing over the web through standards-based geospatial web services. A CDL region of interest can also be exported directly to Google Earth for mashup or downloaded for use with other desktop application. This web service based system greatly improves equal-accessibility, interoperability, usability, and data visualization, facilitates crop geospatial information usage, and enables US cropland online exploring capability without any client-side software installation. It also greatly reduces the need for paper map and analysis report printing and media usages, and thus enhances low-carbon Agro-geoinformation dissemination for decision support.

Emergy Analysis and Sustainability Efficiency Analysis of Different Crop-Based Biodiesel in Life Cycle Perspective

PubMed Central

Ren, Jingzheng; Manzardo, Alessandro; Mazzi, Anna; Fedele, Andrea; Scipioni, Antonio

2013-01-01

Biodiesel as a promising alternative energy resource has been a hot spot in chemical engineering nowadays, but there is also an argument about the sustainability of biodiesel. In order to analyze the sustainability of biodiesel production systems and select the most sustainable scenario, various kinds of crop-based biodiesel including soybean-, rapeseed-, sunflower-, jatropha- and palm-based biodiesel production options are studied by emergy analysis; soybean-based scenario is recognized as the most sustainable scenario that should be chosen for further study in China. DEA method is used to evaluate the sustainability efficiencies of these options, and the biodiesel production systems based on soybean, sunflower, and palm are considered as DEA efficient, whereas rapeseed-based and jatropha-based scenarios are needed to be improved, and the improved methods have also been specified. PMID:23766723

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Teng, William; Chiu, Long; Doraiswamy, Paul; Kempler, Steven; Liu, Zhong; Pham, Long; Rui, Hualan

2005-01-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

The perspective crops for the bioregenerative human life support systems

NASA Astrophysics Data System (ADS)

Polonskiy, Vadim; Polonskaya, Janna

The perspective crops for the bioregenerative human life support systems V.I. Polonskiy, J.E. Polonskaya aKrasnoyarsk State Agrarian University, 660049, Krasnoyarsk, Russia In the nearest future the space missions will be too long. In this case it is necessary to provide the crew by vitamins, antioxidants, and water-soluble dietary fibers. These compounds will be produced by higher plants. There was not enough attention at present to increasing content of micronutrients in edible parts of crops candidates for CELSS. We suggested to add the new crops to this list. 1. Barley -is the best crop for including to food crops (wheat, rice, soybean). Many of the health effects of barley are connected to dietary fibers beta-glucan of barley grains. Bar-ley is the only seed from cereals including wheat with content of all eight tocopherols (vitamin E, important antioxidant). Barley grains contain much greater amounts of phenolic compounds (potential antioxidant activities) than other cereal grains. Considerable focus is on supplement-ing wheat-based breads with barley to introduce the inherent nutritional advantages of barley flour, currently only 20We have selected and tested during 5 generations two high productive barley lines -1-K-O and 25-K-O. Our investigations (special breeding program for improving grain quality of barley) are in progress. 2. Volatile crops. Young leaves and shoots of these crops are edible and have a piquant taste. A lot of organic volatile compounds, oils, vitamins, antioxidants are in their biomass. These micronutrients are useful for good appetite and health of the crew. We have investigated 11 species: basil (Ocimum basilicum), hyssop (Hyssopus officinalis), marjoram (Origanum majorana), sweet-Mary (Melissa officinalis), common thyme (Thymus vulgaris), creeping thyme (Thymus serpyllum), summer savory (Satureja hortensis), catnip (Nepeta cataria), rue (Ruta graveolens), coriander (Coriandrum Ativum), sulfurwort (Levisticum officinale). These plants were grown under artificial light conditions from 5 to 7 months. All crops were cut periodically in every month. On the base of our investigations it is possible to recommend for using in CELSS the next crops: marjoram, sweet-Mary and common thyme. The micronutrients containing in barley and above mentioned volatile crops will be useful for good appetite and health of the crew.

Classification and Mapping of Agricultural Land for National Water-Quality Assessment

USGS Publications Warehouse

Gilliom, Robert J.; Thelin, Gail P.

1997-01-01

Agricultural land use is one of the most important influences on water quality at national and regional scales. Although there is great diversity in the character of agricultural land, variations follow regional patterns that are influenced by environmental setting and economics. These regional patterns can be characterized by the distribution of crops. A new approach to classifying and mapping agricultural land use for national water-quality assessment was developed by combining information on general land-use distribution with information on crop patterns from agricultural census data. Separate classification systems were developed for row crops and for orchards, vineyards, and nurseries. These two general categories of agricultural land are distinguished from each other in the land-use classification system used in the U.S. Geological Survey national Land Use and Land Cover database. Classification of cropland was based on the areal extent of crops harvested. The acreage of each crop in each county was divided by total row-crop area or total orchard, vineyard, and nursery area, as appropriate, thus normalizing the crop data and making the classification independent of total cropland area. The classification system was developed using simple percentage criteria to define combinations of 1 to 3 crops that account for 50 percent or more or harvested acreage in a county. The classification system consists of 21 level I categories and 46 level II subcategories for row crops, and 26 level I categories and 19 level II subcategories for orchards, vineyards, and nurseries. All counties in the United States with reported harvested acreage are classified in these categories. The distribution of agricultural land within each county, however, must be evaluated on the basis of general land-use data. This can be done at the national scale using 'Major Land Uses of the United States,' at the regional scale using data from the national Land Use and Land Cover database, or at smaller scales using locally available data.

Nitrous oxide emissions during establishment of eight alternative cellulosic bioenergy cropping systems in the North Central United States

DOE PAGES

Oates, Lawrence G.; Duncan, David S.; Gelfand, Ilya; ...

2015-05-14

Greenhouse gas (GHG) emissions from soils are a key sustainability metric of cropping systems. During crop establishment, disruptive land-use change is known to be a critical, but under reported period, for determining GHG emissions. We measured soil N 2O emissions and potential environmental drivers of these fluxes from a three-year establishment-phase bioenergy cropping systems experiment replicated in southcentral Wisconsin (ARL) and southwestern Michigan (KBS). Cropping systems treatments were annual monocultures (continuous corn, corn–soybean–canola rotation), perennial monocultures (switchgrass, miscanthus, and poplar), and perennial polycultures (native grass mixture, early successional community, and restored prairie) all grown using best management practices specific tomore » the system. Cumulative three-year N 2O emissions from annuals were 142% higher than from perennials, with fertilized perennials 190% higher than unfertilized perennials. Emissions ranged from 3.1 to 19.1 kg N 2O-N ha -1 yr -1 for the annuals with continuous corn > corn–soybean–canola rotation and 1.1 to 6.3 kg N 2O-N ha -1 yr -1 for perennials. Nitrous oxide peak fluxes typically were associated with precipitation events that closely followed fertilization. Bayesian modeling of N 2O fluxes based on measured environmental factors explained 33% of variability across all systems. Models trained on single systems performed well in most monocultures (e.g., R 2 = 0.52 for poplar) but notably worse in polycultures (e.g., R 2 = 0.17 for early successional, R 2 = 0.06 for restored prairie), indicating that simulation models that include N 2O emissions should be parameterized specific to particular plant communities. These results indicate that perennial bioenergy crops in their establishment phase emit less N 2O than annual crops, especially when not fertilized. These findings should be considered further alongside yield and other metrics contributing to important ecosystem services.« less

Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the "i-ROP" System and Image Features Associated With Expert Diagnosis.

PubMed

Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Campbell, J Peter; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir; Jonas, Karyn; Chan, R V Paul; Ostmo, Susan; Chiang, Michael F

2015-11-01

We developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis. A dataset of 77 wide-angle retinal images from infants screened for ROP was collected. A reference standard diagnosis was determined for each image by combining image grading from 3 experts with the clinical diagnosis from ophthalmoscopic examination. Manually segmented images were cropped into a range of shapes and sizes, and a computer algorithm was developed to extract tortuosity and dilation features from arteries and veins. Each feature was fed into our system to identify the set of characteristics that yielded the highest-performing system compared to the reference standard, which we refer to as the "i-ROP" system. Among the tested crop shapes, sizes, and measured features, point-based measurements of arterial and venous tortuosity (combined), and a large circular cropped image (with radius 6 times the disc diameter), provided the highest diagnostic accuracy. The i-ROP system achieved 95% accuracy for classifying preplus and plus disease compared to the reference standard. This was comparable to the performance of the 3 individual experts (96%, 94%, 92%), and significantly higher than the mean performance of 31 nonexperts (81%). This comprehensive analysis of computer-based plus disease suggests that it may be feasible to develop a fully-automated system based on wide-angle retinal images that performs comparably to expert graders at three-level plus disease discrimination. Computer-based image analysis, using objective and quantitative retinal vascular features, has potential to complement clinical ROP diagnosis by ophthalmologists.

Integrated pest management and weed management in the United States and Canada.

PubMed

Owen, Micheal D K; Beckie, Hugh J; Leeson, Julia Y; Norsworthy, Jason K; Steckel, Larry E

2015-03-01

There is interest in more diverse weed management tactics because of evolved herbicide resistance in important weeds in many US and Canadian crop systems. While herbicide resistance in weeds is not new, the issue has become critical because of the adoption of simple, convenient and inexpensive crop systems based on genetically engineered glyphosate-tolerant crop cultivars. Importantly, genetic engineering has not been a factor in rice and wheat, two globally important food crops. There are many tactics that help to mitigate herbicide resistance in weeds and should be widely adopted. Evolved herbicide resistance in key weeds has influenced a limited number of growers to include a more diverse suite of tactics to supplement existing herbicidal tactics. Most growers still emphasize herbicides, often to the exclusion of alternative tactics. Application of integrated pest management for weeds is better characterized as integrated weed management, and more typically integrated herbicide management. However, adoption of diverse weed management tactics is limited. Modifying herbicide use will not solve herbicide resistance in weeds, and the relief provided by different herbicide use practices is generally short-lived at best. More diversity of tactics for weed management must be incorporated in crop systems. © 2014 Society of Chemical Industry.

Incorporating Medium-Range Weather Forecasts in Seasonal Crop Scenarios over the Greater Horn of Africa to Support National/Regional/Local Decision Makers

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Funk, C. C.; Verdin, J. P.

2015-12-01

The USAID's Famine Early Warning Systems Network (FEWS NET) provides seasonal assessments of crop conditions over the Greater Horn of Africa (GHA) and other food insecure regions. These assessments and current livelihood, nutrition, market conditions and conflicts are used to generate food security scenarios that help national, regional and local decision makers target their resources and mitigate socio-economic losses. Among the various tools that FEWS NET uses is the FAO's Water Requirement Satisfaction Index (WRSI). The WRSI is a simple yet powerful crop assessment model that incorporates current moisture conditions (at the time of the issuance of forecast), precipitation scenarios, potential evapotranspiration and crop parameters to categorize crop conditions into different classes ranging from "failure" to "very good". The WRSI tool has been shown to have a good agreement with local crop yields in the GHA region. At present, the precipitation scenarios used to drive the WRSI are based on either a climatological forecast (that assigns equal chances of occurrence to all possible scenarios and has no skill over the forecast period) or a sea-surface temperature anomaly based scenario (which at best have skill at the seasonal scale). In both cases, the scenarios fail to capture the skill that can be attained by initial atmospheric conditions (i.e., medium-range weather forecasts). During the middle of a cropping season, when a week or two of poor rains can have a devastating effect, two weeks worth of skillful precipitation forecasts could improve the skill of the crop scenarios. With this working hypothesis, we examine the value of incorporating medium-range weather forecasts in improving the skill of crop scenarios in the GHA region. We use the NCEP's Global Ensemble Forecast system (GEFS) weather forecasts and examine the skill of crop scenarios generated using the GEFS weather forecasts with respect to the scenarios based solely on the climatological forecast. The period of analysis is from 1985-2010 (over which the reforecasts of GEFS is available) and the focus season is October-November-December. We examine the improvement (if any) in long-term skill, and present results for several recent drought events in the region.

The southern Brazilian grassland biome: soil carbon stocks, fluxes of greenhouse gases and some options for mitigation.

PubMed

Pillar, V D; Tornquist, C G; Bayer, C

2012-08-01

The southern Brazilian grassland biome contains highly diverse natural ecosystems that have been used for centuries for grazing livestock and that also provide other important environmental services. Here we outline the main factors controlling ecosystem processes, review and discuss the available data on soil carbon stocks and greenhouse gases emissions from soils, and suggest opportunities for mitigation of climatic change. The research on carbon and greenhouse gases emissions in these ecosystems is recent and the results are still fragmented. The available data indicate that the southern Brazilian natural grassland ecosystems under adequate management contain important stocks of organic carbon in the soil, and therefore their conservation is relevant for the mitigation of climate change. Furthermore, these ecosystems show a great and rapid loss of soil organic carbon when converted to crops based on conventional tillage practices. However, in the already converted areas there is potential to mitigate greenhouse gas emissions by using cropping systems based on no soil tillage and cover-crops, and the effect is mainly related to the potential of these crop systems to accumulate soil organic carbon in the soil at rates that surpass the increased soil nitrous oxide emissions. Further modelling with these results associated with geographic information systems could generate regional estimates of carbon balance.

a Weather Monitoring System for Application to Apple and Corn Production

NASA Astrophysics Data System (ADS)

Stirm, Walter Leroy

Many crop management decisions are based on weather -crop development relationships. Daily weather data is currently used in most crop development research and applied models. Present weather and computer technology now makes possible monitoring of crop development on a realtime basis. This research tests a method of computing crop sensitive temperatures for corn and apple using standard hourly meteorological data. The method also makes use of detailed plant physiological stage measurements to determine timing of vital cultural operations tied to the observed weather conditions. The sensitive temperature method incorporates very short term weather variability accounting for changes in the cloud cover, radiation rates, evaporative cooling and other factors involved in the plant's energy balance. The relationship of plant and weather measurements are also used to determine corn emergence, corn grain drydown rate and fruit harvest duration. The monitoring system also incorporates a crop growth unit forecast technique employing short and medium range temperature forecasts of the National Weather Service. The projections of growth units are made for five and ten days into the future. Predicted growth unit accumulations are compared to historical growth unit accumulations to determine the forecast stage. The sensitive temperature crop monitoring system removes some of the error involved in evaluation of growth units by average daily temperature. Carry over maximum and minimums, extended duration of warm or cool periods within the day and disruption of diurnal temperature curve by passage of fronts are eliminated.

Dynamic cropping systems: Holistic approach for dryland agricultural systems in the northern Great Plains of North America

USDA-ARS?s Scientific Manuscript database

Cropping systems over the past century have developed greater crop specialization, more effectively conserve our soil and water resources, and are more resilient. The purpose of this chapter is to discuss the evolution of cropping systems in the Northern Great Plains and provide an approach to crop...

Model-based coefficient method for calculation of N leaching from agricultural fields applied to small catchments and the effects of leaching reducing measures

NASA Astrophysics Data System (ADS)

Kyllmar, K.; Mårtensson, K.; Johnsson, H.

2005-03-01

A method to calculate N leaching from arable fields using model-calculated N leaching coefficients (NLCs) was developed. Using the process-based modelling system SOILNDB, leaching of N was simulated for four leaching regions in southern Sweden with 20-year climate series and a large number of randomised crop sequences based on regional agricultural statistics. To obtain N leaching coefficients, mean values of annual N leaching were calculated for each combination of main crop, following crop and fertilisation regime for each leaching region and soil type. The field-NLC method developed could be useful for following up water quality goals in e.g. small monitoring catchments, since it allows normal leaching from actual crop rotations and fertilisation to be determined regardless of the weather. The method was tested using field data from nine small intensively monitored agricultural catchments. The agreement between calculated field N leaching and measured N transport in catchment stream outlets, 19-47 and 8-38 kg ha -1 yr -1, respectively, was satisfactory in most catchments when contributions from land uses other than arable land and uncertainties in groundwater flows were considered. The possibility of calculating effects of crop combinations (crop and following crop) is of considerable value since changes in crop rotation constitute a large potential for reducing N leaching. When the effect of a number of potential measures to reduce N leaching (i.e. applying manure in spring instead of autumn; postponing ploughing-in of ley and green fallow in autumn; undersowing a catch crop in cereals and oilseeds; and increasing the area of catch crops by substituting winter cereals and winter oilseeds with corresponding spring crops) was calculated for the arable fields in the catchments using field-NLCs, N leaching was reduced by between 34 and 54% for the separate catchments when the best possible effect on the entire potential area was assumed.

Application of water footprint combined with a unified virtual crop pattern to evaluate crop water productivity in grain production in China.

PubMed

Wang, Y B; Wu, P T; Engel, B A; Sun, S K

2014-11-01

Water shortages are detrimental to China's grain production while food production consumes a great deal of water causing water crises and ecological impacts. Increasing crop water productivity (CWP) is critical, so China is devoting significant resources to develop water-saving agricultural systems based on crop planning and agricultural water conservation planning. A comprehensive CWP index is necessary for such planning. Existing indices such as water use efficiency (WUE) and irrigation efficiency (IE) have limitations and are not suitable for the comprehensive evaluation of CWP. The water footprint (WF) index, calculated using effective precipitation and local water use, has advantages for CWP evaluation. Due to regional differences in crop patterns making the CWP difficult to compare directly across different regions, a unified virtual crop pattern is needed to calculate the WF. This project calculated and compared the WF of each grain crop and the integrated WFs of grain products with actual and virtual crop patterns in different regions of China for 2010. The results showed that there were significant differences for the WF among different crops in the same area or among different areas for the same crop. Rice had the highest WF at 1.39 m(3)/kg, while corn had the lowest at 0.91 m(3)/kg among the main grain crops. The WF of grain products was 1.25 m(3)/kg in China. Crop patterns had an important impact on WF of grain products because significant differences in WF were found between actual and virtual crop patterns in each region. The CWP level can be determined based on the WF of a virtual crop pattern, thereby helping optimize spatial distribution of crops and develop agricultural water savings to increase CWP. Copyright © 2014 Elsevier B.V. All rights reserved.

The Potential Role of Neglected and Underutilised Crop Species as Future Crops under Water Scarce Conditions in Sub-Saharan Africa

PubMed Central

Chivenge, Pauline; Mabhaudhi, Tafadzwanashe; Modi, Albert T.; Mafongoya, Paramu

2015-01-01

Modern agricultural systems that promote cultivation of a very limited number of crop species have relegated indigenous crops to the status of neglected and underutilised crop species (NUCS). The complex interactions of water scarcity associated with climate change and variability in sub-Saharan Africa (SSA), and population pressure require innovative strategies to address food insecurity and undernourishment. Current research efforts have identified NUCS as having potential to reduce food and nutrition insecurity, particularly for resource poor households in SSA. This is because of their adaptability to low input agricultural systems and nutritional composition. However, what is required to promote NUCS is scientific research including agronomy, breeding, post-harvest handling and value addition, and linking farmers to markets. Among the essential knowledge base is reliable information about water utilisation by NUCS with potential for commercialisation. This commentary identifies and characterises NUCS with agronomic potential in SSA, especially in the semi-arid areas taking into consideration inter alia: (i) what can grow under water-scarce conditions, (ii) water requirements, and (iii) water productivity. Several representative leafy vegetables, tuber crops, cereal crops and grain legumes were identified as fitting the NUCS category. Agro-biodiversity remains essential for sustainable agriculture. PMID:26016431

A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops.

PubMed

Bengochea-Guevara, José M; Andújar, Dionisio; Sanchez-Sardana, Francisco L; Cantuña, Karla; Ribeiro, Angela

2017-12-24

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, "on ground crop inspection" potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. "On ground monitoring" is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows.

Land Husbandry: Biochar application to reduce land degradation and erosion on cassava production

NASA Astrophysics Data System (ADS)

Yuniwati, E. D.

2017-12-01

This field experiment was carried out to examine the effect of increasing crop yield on land degradation and erosion in cassava-based cropping systems. The experiment was also aimed at showing that with proper crop management, the planting of cassava does not result in land degradation, and therefore, a sustainable production system can be obtained. The experiment was done in a farmer's fields in Batu, about 15 km south east of Malang, East Java, Indonesia. The soils are Alfisols with a surface slope of about 8%. There were 8 experimental treatments with two replications. The experiment results show that biochar applications reduce of soil erosion rate of the cassava field were not necessarily higher than those of maize in terms of crop yield and crop management. At low-to-medium yield, also observed the nutrient uptake of cassava was lower than that of maize. At high yield, only the K uptake of cassava was higher than that of maize, whereas the N and P uptake was more or less similar. Soil erosion on the cassava field was significantly higher than that on the maize field; however, this only occurred when there was no suitable crop management. Simple crop managements, such as ridging, biochar application, or manure application could significantly reduce soil erosion. The results also revealed that proper management could prevent land degradation and increase crop yield. In turn, the increase in crop yield could decrease soil erosion and plant nutrient depletion.

A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops

PubMed Central

Andújar, Dionisio; Sanchez-Sardana, Francisco L.; Cantuña, Karla

2017-01-01

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows. PMID:29295536

Development of a Global Agricultural Hotspot Detection and Early Warning System

NASA Astrophysics Data System (ADS)

Lemoine, G.; Rembold, F.; Urbano, F.; Csak, G.

2015-12-01

The number of web based platforms for crop monitoring has grown rapidly over the last years and anomaly maps and time profiles of remote sensing derived indicators can be accessed online thanks to a number of web based portals. However, while these systems make available a large amount of crop monitoring data to the agriculture and food security analysts, there is no global platform which provides agricultural production hotspot warning in a highly automatic and timely manner. Therefore a web based system providing timely warning evidence as maps and short narratives is currently under development by the Joint Research Centre. The system (called "HotSpot Detection System of Agriculture Production Anomalies", HSDS) will focus on water limited agricultural systems worldwide. The automatic analysis of relevant meteorological and vegetation indicators at selected administrative units (Gaul 1 level) will trigger warning messages for the areas where anomalous conditions are observed. The level of warning (ranging from "watch" to "alert") will depend on the nature and number of indicators for which an anomaly is detected. Information regarding the extent of the agricultural areas concerned by the anomaly and the progress of the agricultural season will complement the warning label. In addition, we are testing supplementary detailed information from other sources for the areas triggering a warning. These regard the automatic web-based and food security-tailored analysis of media (using the JRC Media Monitor semantic search engine) and the automatic detection of active crop area using Sentinel 1, upcoming Sentinel-2 and Landsat 8 imagery processed in Google Earth Engine. The basic processing will be fully automated and updated every 10 days exploiting low resolution rainfall estimates and satellite vegetation indices. Maps, trend graphs and statistics accompanied by short narratives edited by a team of crop monitoring experts, will be made available on the website on a monthly basis.

Simulating soil organic carbon responses to cropping intensity, tillage, and climate change in Pacific Northwest dryland

USDA-ARS?s Scientific Manuscript database

Managing dryland cropping systems to increase soil organic C (SOC) under changing climate is challenging after decades of winter wheat (Triticum aestivum L.)-fallow and moldboard plow tillage (W-F/MP). The objective was to use CQESTR, a process-based C model, and SOC data collected in 2004, 2008, an...

Forcasting Shortleaf Pine Seed Crops in the Ouachita Mountains

Treesearch

Michael G. Shelton; Robert F. Wittwer

2004-01-01

We field tested a cone-rating system to forecast seed crops from 1993 to 1996 in 28 shortleaf pine (Pinus echinata Mill.) stands, which represented a wide range of stand conditions. Sample trees were visually assigned to one of three cone-density classes based on cone spacing, occurrence of cones in clusters, and distribution of cones within the...

Bamboo vs. crops: An integrated emergy and economic evaluation of using bamboo to replace crops in south Sichuan Province, China

EPA Science Inventory

Based on long-term monitoring conducted in Chang-ning county, a pilot site of the ‘Grain for Green Program’ (GFGP), an integrated emergy and economic method was applied to evaluate the dynamic ecological-economic performance of 3 kinds of bamboo systems planted on slo...

Comparing second year growth of American sycamore, black willow, and eastern cottonwood with and without fertilization

Treesearch

Jamie L. Schuler

2012-01-01

Interest in developing domestically produced bio-based fuel systems has been responsible for a large increase in short rotation woody crop (SRWC) research. Much of this work has been used in developing regional production estimates for woody crops like cottonwood (Populus deltoides Bartr. ex Marsh.) and eucalyptus (Eucalyptus spp...

Assessing methods for developing crop forecasting in the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Ines, A. V. M.; Capa Morocho, M. I.; Baethgen, W.; Rodriguez-Fonseca, B.; Han, E.; Ruiz Ramos, M.

2015-12-01

Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004). The limited predictability that exhibits the atmosphere in mid-latitudes, and therefore de Iberian Peninsula (PI), can be managed by a probabilistic approach based in terciles. This study presents an application for the IP of two methods for linking tercile-based seasonal climate forecasts with crop models to improve crop predictability. Two methods were evaluated and applied for disaggregating seasonal rainfall forecasts into daily weather realizations: 1) a stochastic weather generator and 2) a forecast tercile resampler. Both methods were evaluated in a case study where the impacts of two seasonal rainfall forecasts (wet and dry forecast for 1998 and 2015 respectively) on rainfed wheat yield and irrigation requirements of maize in IP were analyzed. Simulated wheat yield and irrigation requirements of maize were computed with the crop models CERES-wheat and CERES-maize which are included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at several locations in Spain where the crop model was calibrated and validated with independent field data. These methodologies would allow quantifying the benefits and risks of a seasonal climate forecast to potential users as farmers, agroindustry and insurance companies in the IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse ones. ReferencesPalmer, T. et al., 2004. Development of a European multimodel ensemble system for seasonal-to-interannual prediction (DEMETER). Bulletin of the American Meteorological Society, 85(6): 853-872.

Pollinators, pests, and predators: Recognizing ecological trade-offs in agroecosystems.

PubMed

Saunders, Manu E; Peisley, Rebecca K; Rader, Romina; Luck, Gary W

2016-02-01

Ecological interactions between crops and wild animals frequently result in increases or declines in crop yield. Yet, positive and negative interactions have mostly been treated independently, owing partly to disciplinary silos in ecological and agricultural sciences. We advocate a new integrated research paradigm that explicitly recognizes cost-benefit trade-offs among animal activities and acknowledges that these activities occur within social-ecological contexts. Support for this paradigm is presented in an evidence-based conceptual model structured around five evidence statements highlighting emerging trends applicable to sustainable agriculture. The full range of benefits and costs associated with animal activities in agroecosystems cannot be quantified by focusing on single species groups, crops, or systems. Management of productive agroecosystems should sustain cycles of ecological interactions between crops and wild animals, not isolate these cycles from the system. Advancing this paradigm will therefore require integrated studies that determine net returns of animal activity in agroecosystems.

Assessment of potential biomass energy production in China towards 2030 and 2050

NASA Astrophysics Data System (ADS)

Zhao, Guangling

2018-01-01

The objective of this paper is to provide a more detailed picture of potential biomass energy production in the Chinese energy system towards 2030 and 2050. Biomass for bioenergy feedstocks comes from five sources, which are agricultural crop residues, forest residues and industrial wood waste, energy crops and woody crops, animal manure, and municipal solid waste. The potential biomass production is predicted based on the resource availability. In the process of identifying biomass resources production, assumptions are made regarding arable land, marginal land, crops yields, forest growth rate, and meat consumption and waste production. Four scenarios were designed to describe the potential biomass energy production to elaborate the role of biomass energy in the Chinese energy system in 2030. The assessment shows that under certain restrictions on land availability, the maximum potential biomass energy productions are estimated to be 18,833 and 24,901 PJ in 2030 and 2050.

Improvements of the Profil Cultural Method for a better Low-tech Field Assessment of Soil Structure under no-till

NASA Astrophysics Data System (ADS)

Roger-Estrade, Jean; Boizard, Hubert; Peigné, Josephine; Sasal, Maria Carolina; Guimaraes, Rachel; Piron, Denis; Tomis, Vincent; Vian, Jean-François; Cadoux, Stephane; Ralisch, Ricardo; Filho, Tavares; Heddadj, Djilali; de Battista, Juan; Duparque, Annie

2016-04-01

In France, agronomists have studied the effects of cropping systems on soil structure, using a field method based on a visual description of soil structure. The "profil cultural" method (Manichon and Gautronneau, 1987) has been designed to perform a field diagnostic of the effects of tillage and compaction on soil structure dynamics. This method is of great use to agronomists improving crop management for a better preservation of soil structure. However, this method was developed and mainly used in conventional tillage systems, with ploughing. As several forms of reduced, minimum and no tillage systems are expanding in many parts of the world, it is necessary to re-evaluate the ability of this method to describe and interpret soil macrostructure in unploughed situations. In unploughed fields, soil structure dynamics of untilled layers is mainly driven by compaction and regeneration by natural agents (climatic conditions, root growth and macrofauna) and it is of major importance to evaluate the importance of these natural processes on soil structure regeneration. These concerns have led us to adapt the standard method and to propose amendments based on a series of field observations and experimental work in different situations of cropping systems, soil types and climatic conditions. We improved the description of crack type and we introduced an index of biological activity, based on the visual examination of clods. To test the improved method, a comparison with the reference method was carried out and the ability of the "profil cultural" method to make a diagnosis was tested on five experiments in France, Brazil and Argentina. Using the improved method, the impact of cropping systems on soil functioning was better assessed when natural processes were integrated into the description.

Comparison of Satellite-based Basal and Adjusted Evapotranspiration for Several California Crops

NASA Astrophysics Data System (ADS)

Johnson, L.; Lund, C.; Melton, F. S.

2013-12-01

There is a continuing need to develop new sources of information on agricultural crop water consumption in the arid Western U.S. Pursuant to the California Water Conservation Act of 2009, for instance, the stakeholder community has developed a set of quantitative indicators involving measurement of evapotranspiration (ET) or crop consumptive use (Calif. Dept. Water Resources, 2012). Fraction of reference ET (or, crop coefficients) can be estimated from a biophysical description of the crop canopy involving green fractional cover (Fc) and height as per the FAO-56 practice standard of Allen et al. (1998). The current study involved 19 fields in California's San Joaquin Valley and Central Coast during 2011-12, growing a variety of specialty and commodity crops: lettuce, raisin, tomato, almond, melon, winegrape, garlic, peach, orange, cotton, corn and wheat. Most crops were on surface or subsurface drip, though micro-jet, sprinkler and flood were represented as well. Fc was retrospectively estimated every 8-16 days by optical satellite data and interpolated to a daily timestep. Crop height was derived as a capped linear function of Fc using published guideline maxima. These variables were used to generate daily basal crop coefficients (Kcb) per field through most or all of each respective growth cycle by the density coefficient approach of Allen & Pereira (2009). A soil water balance model for both topsoil and root zone, based on FAO-56 and using on-site measurements of applied irrigation and precipitation, was used to develop daily soil evaporation and crop water stress coefficients (Ke, Ks). Key meteorological variables (wind speed, relative humidity) were extracted from the California Irrigation Management Information System (CIMIS) for climate correction. Basal crop ET (ETcb) was then derived from Kcb using CIMIS reference ET. Adjusted crop ET (ETc_adj) was estimated by the dual coefficient approach involving Kcb, Ke, and incorporating Ks. Cumulative ETc_adj throughout each monitoring period was lower than cumulative ETb for most crops, indicating that effect of water stress tended to exceed that of soil evaporation relative to basal conditions. We present results from the analysis and discuss implications for operational use of satellite-based Kcb and ETcb estimates for agricultural water resource management.

Using a Decision Support System to Optimize Production of Agricultural Crop Residue Biofeedstock

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reed L. Hoskinson; Ronald C. Rope; Raymond K. Fink

2007-04-01

For several years the Idaho National Laboratory (INL) has been developing a Decision Support System for Agriculture (DSS4Ag) which determines the economically optimum recipe of various fertilizers to apply at each site in a field to produce a crop, based on the existing soil fertility at each site, as well as historic production information and current prices of fertilizers and the forecast market price of the crop at harvest, for growing a crop such as wheat, potatoes, corn, or cotton. In support of the growing interest in agricultural crop residues as a bioenergy feedstock, we have extended the capability ofmore » the DSS4Ag to develop a variable-rate fertilizer recipe for the simultaneous economically optimum production of both grain and straw, and have been conducting field research to test this new DSS4Ag. In this paper we report the results of two years of field research testing and enhancing the DSS4Ag’s ability to economically optimize the fertilization for the simultaneous production of both grain and its straw, where the straw is an agricultural crop residue that can be used as a biofeedstock.« less

New Approaches to Capture High Frequency Agricultural Dynamics in Africa through Mobile Phones

NASA Astrophysics Data System (ADS)

Evans, T. P.; Attari, S.; Plale, B. A.; Caylor, K. K.; Estes, L. D.; Sheffield, J.

2015-12-01

Crop failure early warning systems relying on remote sensing constitute a new critical resource to assess areas where food shortages may arise, but there is a disconnect between the patterns of crop production on the ground and the environmental and decision-making dynamics that led to a particular crop production outcome. In Africa many governments use mid-growing season household surveys to get an on-the-ground assessment of current agricultural conditions. But these efforts are cost prohibitive over large scales and only offer a one-time snapshot at a particular time point. They also rely on farmers to recall past decisions and farmer recall may be imperfect when answering retrospectively on a decision made several months back (e.g. quantity of seed planted). We introduce a novel mobile-phone based approach to acquire information from farmers over large spatial extents, at high frequency at relatively low-cost compared to household survey approaches. This system makes compromises in number of questions which can feasibly be asked of a respondent (compared to household interviews), but the benefit of capturing weekly data from farmers is very exciting. We present data gathered from farmers in Kenya and Zambia to understand key dimensions of agricultural decision making such as choice of seed variety/planting date, frequency and timing of weeding/fertilizing and coping strategies such as pursuing off-farm labor. A particularly novel aspect of this work is reporting from farmers of what their expectation of end-season harvest will be on a week-by-week basis. Farmer's themselves can serve as sentinels of crop failure in this system. And farmers responses to drought are as much driven by their expectations of looming crop failure that may be different from that gleaned from remote sensing based assessment. This work is one piece of a larger design to link farmers to high-density meteorological data in Africa as an additional tool to improve crop failure early warning systems and understand adaptation to climate variability.

Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

2014-12-01

The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are associated to derive food production estimates. Based on trends analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. CropWatch bulletin can be downloaded from the CropWatch website at http://www.cropwatch.com.cn.

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in combination with advanced analytic and extraction techniques provides a vital remote sensing tool for decision makers and scientists with a high-degree of flexibility to adapt to different uses.

A bioenergy feedstock/vegetable double-cropping system

USDA-ARS?s Scientific Manuscript database

Certain warm-season vegetable crops may lend themselves to bioenergy double-cropping systems, which involve growing a winter annual bioenergy feedstock crop followed by a summer annual crop. The objective of the study was to compare crop productivity and weed communities in different pumpkin product...

A regional scale modeling framework combining biogeochemical model with life cycle and economic analysis for integrated assessment of cropping systems.

PubMed

Tabatabaie, Seyed Mohammad Hossein; Bolte, John P; Murthy, Ganti S

2018-06-01

The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO 2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO 2 -eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point. Copyright © 2017 Elsevier B.V. All rights reserved.

First typology of cacao (Theobroma cacao L.) systems in Colombian Amazonia, based on tree species richness, canopy structure and light availability.

PubMed

Suárez Salazar, Juan Carlos; Ngo Bieng, Marie Ange; Melgarejo, Luz Marina; Di Rienzo, Julio A; Casanoves, Fernando

2018-01-01

We present a typology of cacao agroforest systems in Colombian Amazonia. These systems had yet to be described in the literature, especially their potential in terms of biodiversity conservation. The systems studied are located in a post-conflict area, and a deforestation front in Colombian Amazonia. Cacao cropping systems are of key importance in Colombia: cacao plays a prime role in post conflict resolution, as cacao is a legal crop to replace illegal crops; cacao agroforests are expected to be a sustainable practice, promoting forest-friendly land use. We worked in 50 x 2000 m2 agroforest plots, in Colombian Amazonia. A cluster analysis was used to build a typology based on 28 variables characterised in each plot, and related to diversity, composition, spatial structure and light availability for the cacao trees. We included variables related to light availability to evaluate the amount of transmitted radiation to the cacao trees in each type, and its suitability for cacao ecophysiological development. We identified 4 types of cacao agroforests based on differences concerning tree species diversity and the impact of canopy spatial structure on light availability for the cacao trees in the understorey. We found 127 tree species in the dataset, with some exclusive species in each type. We also found that 3 out of the 4 types identified displayed an erosion of tree species diversity. This reduction in shade tree species may have been linked to the desire to reduce shade, but we also found that all the types described were compatible with good ecophysiological development of the cacao trees. Cacao agroforest systems may actually be achieving biodiversity conservation goals in Colombian Amazonia. One challenging prospect will be to monitor and encourage the conservation of tree species diversity in cacao agroforest systems during the development of these cropping systems, as a form of forest-friendly management enhancing sustainable peace building in Colombia.

Economics, energy, and environmental assessment of diversified crop rotations in sub-Himalayas of India.

PubMed

Singh, Raman Jeet; Meena, Roshan Lal; Sharma, N K; Kumar, Suresh; Kumar, Kuldeep; Kumar, Dileep

2016-02-01

Reducing the carbon footprint and increasing energy use efficiency of crop rotations are the two most important sustainability issues of the modern agriculture. Present study was undertaken to assess economics, energy, and environmental parameters of common diversified crop rotations (maize-tomato, and maize-toria-wheat) vis-a-vis traditional crop rotations like maize-wheat, maize + ginger and rice-wheat of the north-western Himalayan region of India. Results revealed that maize-tomato and maize + ginger crop rotations being on par with each other produced significantly higher system productivity in terms of maize equivalent yield (30.2-36.2 t/ha) than other crop rotations (5.04-7.68 t/ha). But interestingly in terms of energy efficiencies, traditional maize-wheat system (energy efficiency 7.9, human energy profitability of 177.8 and energy profitability of 6.9 MJ/ha) was significantly superior over other systems. Maize + ginger rotation showed greater competitive advantage over other rotations because of less consumption of non-renewable energy resources. Similarly, maize-tomato rotation had ability of the production process to exploit natural resources due to 14-38% less use of commercial or purchased energy sources over other crop rotations. Vegetable-based crop rotations (maize + ginger and maize-tomato) maintained significantly the least carbon footprint (0.008 and 0.019 kg CO2 eq./kg grain, respectively) and the highest profitability (154,322 and 274,161 Rs./ha net return, respectively) over other crop rotations. As the greatest inputs of energy and carbon across the five crop rotations were nitrogen fertilizer (15-29% and 17-28%, respectively), diesel (14-24% and 8-19%, respectively) and irrigation (10-27% and 11-44%, respectively), therefore, alternative sources like organic farming, conservation agriculture practices, soil and water conservation measures, rain water harvesting etc. should be encouraged to reduce dependency of direct energy and external carbon inputs particularly in sub-Himalayas of India.

The Crop Growth Research Chamber - A ground-based facility for CELSS research

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Luna, Phil M.; Wagenbach, Kimberly M.; Haslerud, Mark; Straight, Christian L.

1989-01-01

Crop Growth Research Chambers (CGRCs) are being developed as CELSS research facilities for the NASA/Ames Research Center. The history of the CGRC project is reviewed, noting the applications of CGRC research for the development of the Space Station. The CGRCs are designed for CELSS research and development, system control and integration, and flight hardware design and experimentation. The atmospheric and hydroponic environments of the CGRC system are described and the science requirements for CGRC environmental control are listed.

A Comparative Nitrogen Balance and Productivity Analysis of Legume and Non-legume Supported Cropping Systems: The Potential Role of Biological Nitrogen Fixation

PubMed Central

Iannetta, Pietro P. M.; Young, Mark; Bachinger, Johann; Bergkvist, Göran; Doltra, Jordi; Lopez-Bellido, Rafael J.; Monti, Michele; Pappa, Valentini A.; Reckling, Moritz; Topp, Cairistiona F. E.; Walker, Robin L.; Rees, Robert M.; Watson, Christine A.; James, Euan K.; Squire, Geoffrey R.; Begg, Graham S.

2016-01-01

The potential of biological nitrogen fixation (BNF) to provide sufficient N for production has encouraged re-appraisal of cropping systems that deploy legumes. It has been argued that legume-derived N can maintain productivity as an alternative to the application of mineral fertilizer, although few studies have systematically evaluated the effect of optimizing the balance between legumes and non N-fixing crops to optimize production. In addition, the shortage, or even absence in some regions, of measurements of BNF in crops and forages severely limits the ability to design and evaluate new legume–based agroecosystems. To provide an indication of the magnitude of BNF in European agriculture, a soil-surface N-balance approach was applied to historical data from 8 experimental cropping systems that compared legume and non-legume crop types (e.g., grains, forages and intercrops) across pedoclimatic regions of Europe. Mean BNF for different legume types ranged from 32 to 115 kg ha−1 annually. Output in terms of total biomass (grain, forage, etc.) was 30% greater in non-legumes, which used N to produce dry matter more efficiently than legumes, whereas output of N was greater from legumes. When examined over the crop sequence, the contribution of BNF to the N-balance increased to reach a maximum when the legume fraction was around 0.5 (legume crops were present in half the years). BNF was lower when the legume fraction increased to 0.6–0.8, not because of any feature of the legume, but because the cropping systems in this range were dominated by mixtures of legume and non-legume forages to which inorganic N as fertilizer was normally applied. Forage (e.g., grass and clover), as opposed to grain crops in this range maintained high outputs of biomass and N. In conclusion, BNF through grain and forage legumes has the potential to generate major benefit in terms of reducing or dispensing with the need for mineral N without loss of total output. PMID:27917178

A Comparative Nitrogen Balance and Productivity Analysis of Legume and Non-legume Supported Cropping Systems: The Potential Role of Biological Nitrogen Fixation.

PubMed

Iannetta, Pietro P M; Young, Mark; Bachinger, Johann; Bergkvist, Göran; Doltra, Jordi; Lopez-Bellido, Rafael J; Monti, Michele; Pappa, Valentini A; Reckling, Moritz; Topp, Cairistiona F E; Walker, Robin L; Rees, Robert M; Watson, Christine A; James, Euan K; Squire, Geoffrey R; Begg, Graham S

2016-01-01

The potential of biological nitrogen fixation (BNF) to provide sufficient N for production has encouraged re-appraisal of cropping systems that deploy legumes. It has been argued that legume-derived N can maintain productivity as an alternative to the application of mineral fertilizer, although few studies have systematically evaluated the effect of optimizing the balance between legumes and non N-fixing crops to optimize production. In addition, the shortage, or even absence in some regions, of measurements of BNF in crops and forages severely limits the ability to design and evaluate new legume-based agroecosystems. To provide an indication of the magnitude of BNF in European agriculture, a soil-surface N-balance approach was applied to historical data from 8 experimental cropping systems that compared legume and non-legume crop types (e.g., grains, forages and intercrops) across pedoclimatic regions of Europe. Mean BNF for different legume types ranged from 32 to 115 kg ha -1 annually. Output in terms of total biomass (grain, forage, etc.) was 30% greater in non-legumes, which used N to produce dry matter more efficiently than legumes, whereas output of N was greater from legumes. When examined over the crop sequence, the contribution of BNF to the N-balance increased to reach a maximum when the legume fraction was around 0.5 (legume crops were present in half the years). BNF was lower when the legume fraction increased to 0.6-0.8, not because of any feature of the legume, but because the cropping systems in this range were dominated by mixtures of legume and non-legume forages to which inorganic N as fertilizer was normally applied. Forage (e.g., grass and clover), as opposed to grain crops in this range maintained high outputs of biomass and N. In conclusion, BNF through grain and forage legumes has the potential to generate major benefit in terms of reducing or dispensing with the need for mineral N without loss of total output.

CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture.

PubMed

Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

2017-02-01

CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; www.cropwatch.com.cn , Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture

NASA Astrophysics Data System (ADS)

Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

2017-02-01

CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; http://www.cropwatch.com.cn, Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

A Biophysical Modeling Framework for Assessing the Environmental Impact of Biofuel Production

NASA Astrophysics Data System (ADS)

Zhang, X.; Izaurradle, C.; Manowitz, D.; West, T. O.; Post, W. M.; Thomson, A. M.; Nichols, J.; Bandaru, V.; Williams, J. R.

2009-12-01

Long-term sustainability of a biofuel economy necessitates environmentally friendly biofuel production systems. We describe a biophysical modeling framework developed to understand and quantify the environmental value and impact (e.g. water balance, nutrients balance, carbon balance, and soil quality) of different biomass cropping systems. This modeling framework consists of three major components: 1) a Geographic Information System (GIS) based data processing system, 2) a spatially-explicit biophysical modeling approach, and 3) a user friendly information distribution system. First, we developed a GIS to manage the large amount of geospatial data (e.g. climate, land use, soil, and hydrograhy) and extract input information for the biophysical model. Second, the Environmental Policy Integrated Climate (EPIC) biophysical model is used to predict the impact of various cropping systems and management intensities on productivity, water balance, and biogeochemical variables. Finally, a geo-database is developed to distribute the results of ecosystem service variables (e.g. net primary productivity, soil carbon balance, soil erosion, nitrogen and phosphorus losses, and N2O fluxes) simulated by EPIC for each spatial modeling unit online using PostgreSQL. We applied this framework in a Regional Intensive Management Area (RIMA) of 9 counties in Michigan. A total of 4,833 spatial units with relatively homogeneous biophysical properties were derived using SSURGO, Crop Data Layer, County, and 10-digit watershed boundaries. For each unit, EPIC was executed from 1980 to 2003 under 54 cropping scenarios (eg. corn, switchgrass, and hybrid poplar). The simulation results were compared with historical crop yields from USDA NASS. Spatial mapping of the results show high variability among different cropping scenarios in terms of the simulated ecosystem services variables. Overall, the framework developed in this study enables the incorporation of environmental factors into economic and life-cycle analysis in order to optimize biomass cropping production scenarios.

Meteorological risks are drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen

2017-04-01

Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risk types were quantified in terms of probability and distribution, and further distinguished according to production type. Examples of strategies and options were provided at field, farm and policy level using different modelling methods.

An AgMIP framework for improved agricultural representation in integrated assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.« less

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

Crop water productivity under increasing irrigation capacities in Romania. A spatially-explicit assessment of winter wheat and maize cropping systems in the southern lowlands of the country

NASA Astrophysics Data System (ADS)

Dogaru, Diana

2016-04-01

Improved water use efficiency in agriculture is a key issue in terms of sustainable management and consumption of water resources in the context of peoples' increasing food demands and preferences, economic growth and agricultural adaptation options to climate variability and change. Crop Water Productivity (CWP), defined as the ratio of yield (or value of harvested crop) to actual evapotranspiration or as the ratio of yield (or value of harvested crop) to volume of supplied irrigation water (Molden et al., 1998), is a useful indicator in the evaluation of water use efficiency and ultimately of cropland management, particularly in the case of regions affected by or prone to drought and where irrigation application is essential for achieving expected productions. The present study investigates the productivity of water in winter wheat and maize cropping systems in the Romanian Plain (49 594 sq. km), an important agricultural region in the southern part of the country which is increasingly affected by drought and dry spells (Sandu and Mateescu, 2014). The scope of the analysis is to assess the gains and losses in CWP for the two crops, by considering increased irrigated cropland and improved fertilization, these being the most common measures potentially and already implemented by the farmers. In order to capture the effects of such measures on agricultural water use, the GIS-based EPIC crop-growth model (GEPIC) (Williams et al., 1989; Liu, 2009) was employed to simulate yields, seasonal evapotranspiration from crops and volume of irrigation water in the Romanian Plain for the 2002 - 2013 interval with focus on 2007 and 2010, two representative years for dry and wet periods, respectively. The GEPIC model operates on a daily time step, while the geospatial input datasets for this analysis (e.g. climate data, soil classes and soil parameters, land use) were harmonized at 1km resolution grid cell. The sources of the spatial data are mainly the national profile agencies/institutes, providing the data at fine resolutions. The increased irrigated area was accounted according to the reported increased percentages of the irrigated area out of the total area equipped for irrigation, as an expected outcome of public irrigation systems rehabilitation schemes (MADR, 2011), while the optimum Nitrogen fertilizer rates for wheat and maize were established according to several field experiments made on irrigated and rain-fed wheat and maize plots in south Romania (Hera and Borlan, 1980). The effects of such farming measures on yields were compared to a baseline condition given by actual irrigated area and fertilization rates. The preliminary results show that potential gains in CWP could be obtained through improved fertilizer management and water allocation in winter wheat cropping systems, particularly in the dry periods, while in maize cropping systems CWP is more sensitive to water than to optimum fertilization rates. Irrigation water supply increases the stability of yields in both cropping systems, although regional differences can be observed across the study area, thus augmenting the relevance and the need for investigations on sustainable use of irrigation water in Romania. As such, this study could represent an information base for further analyses on yield potential under current and future climatic conditions, on impacts of land use patterns and farming practices on crop production in Romania, etc. Keywords: agricultural water use, crop water productivity, irrigation water, GEPIC, Romania References: Molden, D.J., Sakthivadivel, R., Perry, C.J., de Fraiture, C., Kloezen, W.H. (1998). Indicators for comparing performance of irrigated agricultural systems, Research Report 20, IWMI: Colombo, Sri Lanka. Sandu, I., Mateescu E. (2014). Current and prospective climate changes in Romania (in Romanian), in vol. Climate change: a major challenge for research in agriculture (ed. Saulescu, N.), Romanian Academy Publishing House, 17-36. Williams, J.R., Jones, C.A., Kiniry, J.R., Spanel, D.A. (1989). The EPIC crop growth model. Trans. ASAE 32 (2), 497-511. Liu, J. (2009). A GIS-based tool for modelling large-scale crop-water relations, Environmental Modelling & Software, 24, 411-422. MADR (Ministry of Agriculture and Rural Development), (2011). Rehabilitation and reform in the irrigation sector. Strategy of investment in the irrigation sector (in Romanian), Fidman Merk at., Bucharest, http://old.madr.ro/pages/strategie/strategie-investitii-irigatii.pdf. Hera, C., Borlan, Z. (1980). Guide for fertilization planning (in Romanian), 2nd edition, CERES Publishing House, Bucharest, Romania, 341p.

Regional modelling of nitrate leaching from Swiss organic and conventional cropping systems under climate change

NASA Astrophysics Data System (ADS)

Calitri, Francesca; Necpalova, Magdalena; Lee, Juhwan; Zaccone, Claudio; Spiess, Ernst; Herrera, Juan; Six, Johan

2016-04-01

Organic cropping systems have been promoted as a sustainable alternative to minimize the environmental impacts of conventional practices. Relatively little is known about the potential to reduce NO3-N leaching through the large-scale adoption of organic practices. Moreover, the potential to mitigate NO3-N leaching and thus the N pollution under future climate change through organic farming remain unknown and highly uncertain. Here, we compared regional NO3-N leaching from organic and conventional cropping systems in Switzerland using a terrestrial biogeochemical process-based model DayCent. The objectives of this study are 1) to calibrate and evaluate the model for NO3-N leaching measured under various management practices from three experiments at two sites in Switzerland; 2) to estimate regional NO3-N leaching patterns and their spatial uncertainty in conventional and organic cropping systems (with and without cover crops) for future climate change scenario A1B; 3) to explore the sensitivity of NO3-N leaching to changes in soil and climate variables; and 4) to assess the nitrogen use efficiency for conventional and organic cropping systems with and without cover crops under climate change. The data for model calibration/evaluation were derived from field experiments conducted in Liebefeld (canton Bern) and Eschikon (canton Zürich). These experiments evaluated effects of various cover crops and N fertilizer inputs on NO3-N leaching. The preliminary results suggest that the model was able to explain 50 to 83% of the inter-annual variability in the measured soil drainage (RMSE from 12.32 to 16.89 cm y-1). The annual NO3-N leaching was also simulated satisfactory (RMSE = 3.94 to 6.38 g N m-2 y-1), although the model had difficulty to reproduce the inter-annual variability in the NO3-N leaching losses correctly (R2 = 0.11 to 0.35). Future climate datasets (2010-2099) from the 10 regional climate models (RCM) were used in the simulations. Regional NO3-N leaching predictions for conventional cropping system with a three years rotation (silage maize, potatoes and winter wheat) in Zurich and Bern cantons varied from 6.30 to 16.89 g N m-2 y-1 over a 30-years period. Further simulations and analyses will follow to provide insights into understanding of driving variables and patterns of N losses by leaching in response to changes from conventional to organic cropping systems, and climate change.

Data base design for a worldwide multicrop information system

NASA Technical Reports Server (NTRS)

Driggers, W. G.; Downs, J. M.; Hickman, J. R.; Packard, R. L. (Principal Investigator)

1979-01-01

A description of the USDA Application Test System data base design approach and resources is presented. The data is described in detail by category, with emphasis on those characteristics which influenced the design most. It was concluded that the use of a generalized data base in support of crop assessment is a sound concept. The IDMS11 minicomputer base system is recommended for this purpose.

Comparing crop rotations between organic and conventional farming.

PubMed

Barbieri, Pietro; Pellerin, Sylvain; Nesme, Thomas

2017-10-23

Cropland use activities are major drivers of global environmental changes and of farming system resilience. Rotating crops is a critical land-use driver, and a farmers' key strategy to control environmental stresses and crop performances. Evidence has accumulated that crop rotations have been dramatically simplified over the last 50 years. In contrast, organic farming stands as an alternative production way that promotes crop diversification. However, our understanding of crop rotations is surprisingly limited. In order to understand if organic farming would result in more diversified and multifunctional landscapes, we provide here a novel, systematic comparison of organic-to-conventional crop rotations at the global scale based on a meta-analysis of the scientific literature, paired with an independent analysis of organic-to-conventional land-use. We show that organic farming leads to differences in land-use compared to conventional: overall, crop rotations are 15% longer and result in higher diversity and evener crop species distribution. These changes are driven by a higher abundance of temporary fodders, catch and cover-crops, mostly to the detriment of cereals. We also highlighted differences in organic rotations between Europe and North-America, two leading regions for organic production. This increased complexity of organic crop rotations is likely to enhance ecosystem service provisioning to agroecosystems.

When should irrigators invest in more water-efficient technologies as an adaptation to climate change?

NASA Astrophysics Data System (ADS)

Malek, K.; Adam, J. C.; Stockle, C.; Brady, M.; Yoder, J.

2015-12-01

The western US is expected to experience more frequent droughts with higher magnitudes and persistence due to the climate change, with potentially large impacts on agricultural productivity and the economy. Irrigated farmers have many options for minimizing drought impacts including changing crops, engaging in water markets, and switching irrigation technologies. Switching to more efficient irrigation technologies, which increase water availability in the crop root zone through reduction of irrigation losses, receives significant attention because of the promise of maintaining current production with less. However, more efficient irrigation systems are almost always more capital-intensive adaptation strategy particularly compared to changing crops or trading water. A farmer's decision to switch will depend on how much money they project to save from reducing drought damages. The objective of this study is to explore when (and under what climate change scenarios) it makes sense economically for farmers to invest in a new irrigation system. This study was performed over the Yakima River Basin (YRB) in Washington State, although the tools and information gained from this study are transferable to other watersheds in the western US. We used VIC-CropSyst, a large-scale grid-based modeling framework that simulates hydrological processes while mechanistically capturing crop water use, growth and development. The water flows simulated by VIC-CropSyst were used to run the RiverWare river system and water management model (YAK-RW), which simulates river processes and calculates regional water availability for agricultural use each day (i.e., the prorationing ratio). An automated computational platform has been developed and programed to perform the economic analysis for each grid cell, crop types and future climate projections separately, which allows us to explore whether or not implementing a new irrigation system is economically viable. Results of this study indicate that climate change could justify the investment in new irrigation systems during this century, but the timing of a farmer's response is likely to depend on a variety of factors, including changes in the frequency and magnitude of drought events, current irrigation systems, climatological characteristics within the basin, and crop type.

Copula-based models of systemic risk in U.S

Treesearch

Barry K. Goodwin; Ashley Hungerford Hungerford

2015-01-01

The federal crop insurance program has been a major fixture of U.S. agricultural policy since the 1930s, and continues to grow in size and importance. Indeed, it now represents the most prominent farm policy instrument, accounting for more government spending than any other farm commodity program. The 2014 Farm Bill further expanded the crop insurance program and...

Agricultural Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Tam, A.; Jain, M.

2016-12-01

This research includes two projects pertaining to agricultural systems' adaption to climate change. The first research project focuses on the wheat yielding regions of India. Wheat is a major staple crop and many rural households and smallholder farmers rely on crop yields for survival. We examine the impacts of weather variability and groundwater depletion on agricultural systems, using geospatial analysis and satellite-based analysis and household-based and census data sets. We use these methods to estimate the crop yields and identify what factors are associated with low versus high yielding regions. This can help identify strategies that should be further promoted to increase crop yields. The second research project is a literature review. We conduct a meta-analysis and synthetic review on literature about agricultural adaptation to climate change. We sort through numerous articles to identify and examine articles that associate socio-economic, biophysical, and perceptional factors to farmers' adaption to climate change. Our preliminary results show that researchers tend to associate few factors to a farmers' vulnerability and adaptive capacity, and most of the research conducted is concentrated in North America, whereas tropical regions that are highly vulnerable to weather variability are underrepresented by literature. There are no conclusive results in both research projects as of so far.

Variation of Bacterial Community Diversity in Rhizosphere Soil of Sole-Cropped versus Intercropped Wheat Field after Harvest.

PubMed

Yang, Zhenping; Yang, Wenping; Li, Shengcai; Hao, Jiaomin; Su, Zhifeng; Sun, Min; Gao, Zhiqiang; Zhang, Chunlai

2016-01-01

As the major crops in north China, spring crops are usually planted from April through May every spring and harvested in fall. Wheat is also a very common crop traditionally planted in fall or spring and harvested in summer year by year. This continuous cropping system exhibited the disadvantages of reducing the fertility of soil through decreasing microbial diversity. Thus, management of microbial diversity in the rhizosphere plays a vital role in sustainable crop production. In this study, ten common spring crops in north China were chosen sole-cropped and four were chosen intercropped with peanut in wheat fields after harvest. Denaturing gradient gel electrophoresis (DGGE) and DNA sequencing of one 16S rDNA fragment were used to analyze the bacterial diversity and species identification. DGGE profiles showed the bacterial community diversity in rhizosphere soil samples varied among various crops under different cropping systems, more diverse under intercropping system than under sole-cropping. Some intercropping-specific bands in DGGE profiles suggested that several bacterial species were stimulated by intercropping systems specifically. Furthermore, the identification of these dominant and functional bacteria by DNA sequencing indicated that intercropping systems are more beneficial to improve soil fertility. Compared to intercropping systems, we also observed changes in microbial community of rhizosphere soil under sole-crops. The rhizosphere bacterial community structure in spring crops showed a strong crop species-specific pattern. More importantly, Empedobacter brevis, a typical plant pathogen, was only found in the carrot rhizosphere, suggesting carrot should be sown prudently. In conclusion, our study demonstrated that crop species and cropping systems had significant effects on bacterial community diversity in the rhizosphere soils. We strongly suggest sorghum, glutinous millet and buckwheat could be taken into account as intercropping crops with peanut; while hulled oat, mung bean or foxtail millet could be considered for sowing in wheat fields after harvest in North China.

Numerical modeling of the agricultural-hydrologic system in Punjab, India

NASA Astrophysics Data System (ADS)

Nyblade, M.; Russo, T. A.; Zikatanov, L.; Zipp, K.

2017-12-01

The goal of food security for India's growing population is threatened by the decline in freshwater resources due to unsustainable water use for irrigation. The issue is acute in parts of Punjab, India, where small landholders produce a major quantity of India's food with declining groundwater resources. To further complicate this problem, other regions of the state are experiencing groundwater logging and salinization, and are reliant on canal systems for fresh water delivery. Due to the lack of water use records, groundwater consumption for this study is estimated with available data on crop yields, climate, and total canal water delivery. The hydrologic and agricultural systems are modeled using appropriate numerical methods and software. This is a state-wide hydrologic numerical model of Punjab that accounts for multiple aquifer layers, agricultural water demands, and interactions between the surface canal system and groundwater. To more accurately represent the drivers of agricultural production and therefore water use, we couple an economic crop optimization model with the hydrologic model. These tools will be used to assess and optimize crop choice scenarios based on farmer income, food production, and hydrologic system constraints. The results of these combined models can be used to further understand the hydrologic system response to government crop procurement policies and climate change, and to assess the effectiveness of possible water conservation solutions.

Socio-climatic Exposure of an Afghan Poppy Farmer

NASA Astrophysics Data System (ADS)

Mankin, J. S.; Diffenbaugh, N. S.

2011-12-01

Many posit that climate impacts from anthropogenic greenhouse gas emissions will have consequences for the natural and agricultural systems on which humans rely for food, energy, and livelihoods, and therefore, on stability and human security. However, many of the potential mechanisms of action in climate impacts and human systems response, as well as the differential vulnerabilities of such systems, remain underexplored and unquantified. Here I present two initial steps necessary to characterize and quantify the consequences of climate change for farmer livelihood in Afghanistan, given both climate impacts and farmer vulnerabilities. The first is a conceptual model mapping the potential relationships between Afghanistan's climate, the winter agricultural season, and the country's political economy of violence and instability. The second is a utility-based decision model for assessing farmer response sensitivity to various climate impacts based on crop sensitivities. A farmer's winter planting decision can be modeled roughly as a tradeoff between cultivating the two crops that dominate the winter growing season-opium poppy (a climate tolerant cash crop) and wheat (a climatically vulnerable crop grown for household consumption). Early sensitivity analysis results suggest that wheat yield dominates farmer decision making variability; however, such initial results may dependent on the relative parameter ranges of wheat and poppy yields. Importantly though, the variance in Afghanistan's winter harvest yields of poppy and wheat is tightly linked to household livelihood and thus, is indirectly connected to the wider instability and insecurity within the country. This initial analysis motivates my focused research on the sensitivity of these crops to climate variability in order to project farmer well-being and decision sensitivity in a warmer world.

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems

PubMed Central

Reckling, Moritz; Bergkvist, Göran; Watson, Christine A.; Stoddard, Frederick L.; Zander, Peter M.; Walker, Robin L.; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann

2016-01-01

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers. PMID:27242870

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems.

PubMed

Reckling, Moritz; Bergkvist, Göran; Watson, Christine A; Stoddard, Frederick L; Zander, Peter M; Walker, Robin L; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann

2016-01-01

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers.

Agricultural biotechnology and smallholder farmers in developing countries.

PubMed

Anthony, Vivienne M; Ferroni, Marco

2012-04-01

Agricultural biotechnology holds much potential to contribute towards crop productivity gains and crop improvement for smallholder farmers in developing countries. Over 14 million smallholder farmers are already benefiting from biotech crops such as cotton and maize in China, India and other Asian, African and Central/South American countries. Molecular breeding can accelerate crop improvement timescales and enable greater use of diversity of gene sources. Little impact has been realized to date with fruits and vegetables because of development timescales for molecular breeding and development and regulatory costs and political considerations facing biotech crops in many countries. Constraints to the development and adoption of technology-based solutions to reduce yield gaps need to be overcome. Full integration with broader commercial considerations such as farmer access to seed distribution systems that facilitate dissemination of improved varieties and functioning markets for produce are critical for the benefits of agricultural biotechnology to be fully realized by smallholders. Public-private partnerships offer opportunities to catalyze new approaches and investment while accelerating integrated research and development and commercial supply chain-based solutions. Copyright © 2011. Published by Elsevier Ltd.

Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe.

PubMed

Elsgaard, L; Børgesen, C D; Olesen, J E; Siebert, S; Ewert, F; Peltonen-Sainio, P; Rötter, R P; Skjelvåg, A O

2012-01-01

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.

A decision support system (GesCoN) for managing fertigation in open field vegetable crops. Part I-methodological approach and description of the software.

PubMed

Elia, Antonio; Conversa, Giulia

2015-01-01

Reduced water availability and environmental pollution caused by nitrogen (N) losses have increased the need for rational management of irrigation and N fertilization in horticultural systems. Decision support systems (DSS) could be powerful tools to assist farmers to improve irrigation and N fertilization efficiency. Currently, fertilization by drip irrigation system (fertigation) is used for many vegetable crops around the world. The paper illustrates the theoretical basis, the methodological approach and the structure of a DSS called GesCoN for fertigation management in open field vegetable crops. The DSS is based on daily water and N balance, considering the water lost by evapotranspiration (ET) and the N content in the aerial part of the crop (N uptake) as subtraction and the availability of water and N in the wet soil volume most effected by roots as the positive part. For the water balance, reference ET can be estimated using the Penman-Monteith (PM) or the Priestley-Taylor and Hargreaves models, specifically calibrated under local conditions. Both single or dual Kc approach can be used to calculate crop ET. Rain runoff and deep percolation are considered to calculate the effective rainfall. The soil volume most affected by the roots, the wet soil under emitters and their interactions are modeled. Crop growth is modeled by a non-linear logistic function on the basis of thermal time, but the model takes into account thermal and water stresses and allows an in-season calibration through a dynamic adaptation of the growth rate to the specific genetic and environmental conditions. N crop demand is related to DM accumulation by the N critical curve. N mineralization from soil organic matter is daily estimated. The DSS helps users to evaluate the daily amount of water and N fertilizer that has to be applied in order to fulfill the water and N-crop requirements to achieve the maximum potential yield, while reducing the risk of nitrate outflows.

Enhancing the USDA Global Crop Assessment Decision Support System Using SMAP Soil Moisture Data

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mladenova, I. E.; Crow, W. T.; Reynolds, C. A.

2016-12-01

The Foreign Agricultural Services (FAS) is a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected crop supply and demand estimates. Knowledge of the amount of water in the root zone is an essential source of information for the crop analysts as it governs the crop development and crop growth, which in turn determine the end-of-season yields. USDA FAS currently relies on root zone soil moisture (RZSM) estimates generated using the modified two-layer Palmer Model (PM). PM is a simple water-balance hydrologic model that is driven by daily precipitation observations and minimum and maximum temperature data. These forcing data are based on ground meteorological station measurements from the World Meteorological Organization (WMO), and gridded weather data from the former U.S. Air Force Weather Agency (AFWA), currently called U.S. Air Force 557th Weather Wing. The PM was extended by adding a data assimilation (DA) unit that provides the opportunity to routinely ingest satellite-based soil moisture observations. This allows us to adjust for precipitation-related inaccuracies and enhance the quality of the PM soil moisture estimates. The current operational DA system is based on a 1-D Ensample Kalman Filter approach and relies on observations obtained from the Soil Moisture Ocean Salinity Mission (SMOS). Our talk will demonstrate the value of assimilating two satellite products (i.e. a passive and active) and discuss work that is done in preparation for ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission.

Soybean Physiology Calibration in the Community Land Model

NASA Astrophysics Data System (ADS)

Drewniak, B. A.; Bilionis, I.; Constantinescu, E. M.

2014-12-01

With the large influence of agricultural land use on biophysical and biogeochemical cycles, integrating cultivation into Earth System Models (ESMs) is increasingly important. The Community Land Model (CLM) was augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. However, the strong nonlinearity of ESMs makes parameter fitting a difficult task. In this study, our goal is to calibrate ten of the CLM-Crop parameters for one crop type, soybean, in order to improve model projection of plant development and carbon fluxes. We used measurements of gross primary productivity, net ecosystem exchange, and plant biomass from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). Our scheme can perform model calibration using very few evaluations and, by exploiting parallelism, at a fraction of the time required by plain vanilla Markov Chain Monte Carlo (MCMC). We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from an AmeriFlux tower site in the Midwestern United States, for the soybean crop type. The improved model will help researchers understand how climate affects crop production and resulting carbon fluxes, and additionally, how cultivation impacts climate.

Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller

NASA Astrophysics Data System (ADS)

Gines, G. A.; Bea, J. G.; Palaoag, T. D.

2018-03-01

Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.

Risk, regulation and biotechnology: the case of GM crops.

PubMed

Smyth, Stuart J; Phillips, Peter W B

2014-07-03

The global regulation of products of biotechnology is increasingly divided. Regulatory decisions for genetically modified (GM) crops in North America are predictable and efficient, with numerous countries in Latin and South America, Australia and Asia following this lead. While it might have been possible to argue that Europe's regulations were at one time based on real concerns about minimizing risks and ensuring health and safety, it is increasingly apparent that the entire European Union (EU) regulatory system for GM crops and foods is now driven by political agendas. Countries within the EU are at odds with each other as some have commercial production of GM crops, while others refuse to even develop regulations that could provide for the commercial release of GM crops. This divide in regulatory decision-making is affecting international grain trade, creating challenges for feeding an increasing global population.

Synthetically engineered Medea gene drive system in the worldwide crop pest Drosophila suzukii

PubMed Central

Buchman, Anna; Marshall, John M.; Ostrovski, Dennis; Yang, Ting; Akbari, Omar S.

2018-01-01

Synthetic gene drive systems possess enormous potential to replace, alter, or suppress wild populations of significant disease vectors and crop pests; however, their utility in diverse populations remains to be demonstrated. Here, we report the creation of a synthetic Medea gene drive system in a major worldwide crop pest, Drosophila suzukii. We demonstrate that this drive system, based on an engineered maternal “toxin” coupled with a linked embryonic “antidote,” is capable of biasing Mendelian inheritance rates with up to 100% efficiency. However, we find that drive resistance, resulting from naturally occurring genetic variation and associated fitness costs, can be selected for and hinder the spread of such a drive. Despite this, our results suggest that this gene drive could maintain itself at high frequencies in a wild population and spread to fixation if either its fitness costs or toxin resistance were reduced, providing a clear path forward for developing future such systems in this pest. PMID:29666236

Rice production in relation to soil quality under different rice-based cropping systems

NASA Astrophysics Data System (ADS)

Tran Ba, Linh; Sleutel, Steven; Nguyen Van, Qui; Thi, Guong Vo; Le Van, Khoa; Cornelis, Wim

2016-04-01

Soil quality of shallow paddy soils may be improved by introducing upland crops and thus a more diverse crop cultivation pattern. Yet, the causal relationship between crop performance and enhanced soil traits in rice-upland crop rotations remains elusive. The objectives of this study were to (i) find correlations among soil properties under different rice-upland crop systems and link selected soil properties to rice growth and yield, (ii) present appropriate values of soil parameters for sustainable rice productivity in heavy clay soil, (iii) evaluate the effect of rotating rice with upland crops on rice yield and economic benefit in a long-term experiment. A rice-upland crop rotational field experiment in the Vietnamese Mekong delta was conducted for 10 years using a randomized complete block design with four treatments and four replications. Treatments were: (i) rice-rice-rice (control - conventional system as farmers' practice), (ii) rice-maize-rice, (iii) rice-mung bean-rice, and (iv) rice-mung bean-maize. Soil and plant sampling were performed after harvest of the rice crop at the end of the final winter-spring cropping season (i.e. year 10). Results show differences in rice growth and yield, and economic benefit as an effect of the crop rotation system. These differences were linked with changes in bulk density, soil porosity, soil aggregate stability index, soil penetration resistance, soil macro-porosity, soil organic carbon, acid hydrolysable soil C and soil nutrient elements, especially at soil depth of 20-30 cm. This is evidenced by the strong correlation (P < 0.01) between rice plant parameters, rice yield and soil properties such as bulk density, porosity, penetration resistance, soil organic carbon and Chydrolysable. It turned out that good rice root growth and rice yield corresponded to bulk density values lower than 1.3 Mg m-3, soil porosity higher than 50%, penetration resistance below 1.0 MPa, and soil organic carbon above 25 g kg-1. The optimal soil depth without restriction for rice root elongation was at least 25 cm from the soil surface. We suggest these values as indicative for optimal physical soil quality when growing rice in fine-textured alluvial soils and their definition as a first step towards presenting real threshold values.

Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China

DOE PAGES

Ye, Qing; Yang, Xiaoguang; Dai, Shuwei; ...

2015-06-05

Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.

PCPPI: a comprehensive database for the prediction of Penicillium-crop protein-protein interactions.

PubMed

Yue, Junyang; Zhang, Danfeng; Ban, Rongjun; Ma, Xiaojing; Chen, Danyang; Li, Guangwei; Liu, Jia; Wisniewski, Michael; Droby, Samir; Liu, Yongsheng

2017-01-01

Penicillium expansum , the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium -crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein-protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium -Crop Protein-Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen-plant systems and available domain-domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community. : http://bdg.hfut.edu.cn/pcppi/index.html. © The Author(s) 2017. Published by Oxford University Press.

Agricultural practices to improve nitrogen use efficiency through the use of arbuscular mycorrhizae: Basic and agronomic aspects.

PubMed

Verzeaux, Julien; Hirel, Bertrand; Dubois, Frédéric; Lea, Peter J; Tétu, Thierry

2017-11-01

Nitrogen cycling in agroecosystems is heavily dependent upon arbuscular mycorrhizal fungi (AMF) present in the soil microbiome. These fungi develop obligate symbioses with various host plant species, thus increasing their ability to acquire nutrients. However, AMF are particularly sensitive to physical, chemical and biological disturbances caused by human actions that limit their establishment. For a more sustainable agriculture, it will be necessary to further investigate which agricultural practices could be favorable to maximize the benefits of AMF to improve crop nitrogen use efficiency (NUE), thus reducing nitrogen (N) fertilizer usage. Direct seeding, mulch-based cropping systems prevent soil mycelium disruption and increase AMF propagule abundance. Such cropping systems lead to more efficient root colonization by AMF and thus a better establishment of the plant/fungal symbiosis. In addition, the use of continuous cover cropping systems can also enhance the formation of more efficient interconnected hyphal networks between mycorrhizae colonized plants. Taking into account both fundamental and agronomic aspects of mineral nutrition by plant/AMF symbioses, we have critically described, how improving fungal colonization through the reduction of soil perturbation and maintenance of an ecological balance could be helpful for increasing crop NUE. Copyright © 2017 Elsevier B.V. All rights reserved.

An integrated approach to monitoring ecosystem services and agriculture: implications for sustainable agricultural intensification in Rwanda.

PubMed

Rosa, Melissa F; Bonham, Curan A; Dempewolf, Jan; Arakwiye, Bernadette

2017-01-01

Maintaining the long-term sustainability of human and natural systems across agricultural landscapes requires an integrated, systematic monitoring system that can track crop productivity and the impacts of agricultural intensification on natural resources. This study presents the design and practical implementation of a monitoring framework that combines satellite observations with ground-based biophysical measurements and household surveys to provide metrics on ecosystem services and agricultural production at multiple spatial scales, reaching from individual households and plots owned by smallholder farmers to 100-km 2 landscapes. We developed a set of protocols for monitoring and analyzing ecological and agricultural household parameters within two 10 × 10-km landscapes in Rwanda, including soil fertility, crop yield, water availability, and fuelwood sustainability. Initial results suggest providing households that rely on rainfall for crop irrigation with timely climate information and improved technical inputs pre-harvest could help increase crop productivity in the short term. The value of the monitoring system is discussed as an effective tool for establishing a baseline of ecosystem services and agriculture before further change in land use and climate, identifying limitations in crop production and soil fertility, and evaluating food security, economic development, and environmental sustainability goals set forth by the Rwandan government.

The Potential of Transcription Factor-Based Genetic Engineering in Improving Crop Tolerance to Drought

PubMed Central

Tripathi, Prateek

2014-01-01

Abstract Drought is one of the major constraints in crop production and has an effect on a global scale. In order to improve crop production, it is necessary to understand how plants respond to stress. A good understanding of regulatory mechanisms involved in plant responses during drought will enable researchers to explore and manipulate key regulatory points in order to enhance stress tolerance in crops. Transcription factors (TFs) have played an important role in crop improvement from the dawn of agriculture. TFs are therefore good candidates for genetic engineering to improve crop tolerance to drought because of their role as master regulators of clusters of genes. Many families of TFs, such as CCAAT, homeodomain, bHLH, NAC, AP2/ERF, bZIP, and WRKY have members that may have the potential to be tools for improving crop tolerance to drought. In this review, the roles of TFs as tools to improve drought tolerance in crops are discussed. The review also focuses on current strategies in the use of TFs, with emphasis on several major TF families in improving drought tolerance of major crops. Finally, many promising transgenic lines that may have improved drought responses have been poorly characterized and consequently their usefulness in the field is uncertain. New advances in high-throughput phenotyping, both greenhouse and field based, should facilitate improved phenomics of transgenic lines. Systems biology approaches should then define the underlying changes that result in higher yields under water stress conditions. These new technologies should help show whether manipulating TFs can have effects on yield under field conditions. PMID:25118806

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

NASA Technical Reports Server (NTRS)

Shukla, Sonali P.; Ruane, Alexander Clark

2014-01-01

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).

Agronomic responses to late-seeded cover crops in a semiarid region

USDA-ARS?s Scientific Manuscript database

Intensification of cropping systems in the Great Plains beyond annual cropping practices may be limited by inadequate precipitation, short growing seasons, and highly variable climatic conditions. Inclusion of cover crops in dryland cropping systems may serve as an effective intensification strateg...

The release of genetically modified crops into the environment. Part I. Overview of current status and regulations.

PubMed

Nap, Jan-Peter; Metz, Peter L J; Escaler, Marga; Conner, Anthony J

2003-01-01

In the past 6 years, the global area of commercially grown, genetically modified (GM) crops has increased more than 30-fold to over 52 million hectares. The number of countries involved has more than doubled. Especially in developing countries, the GM crop area is anticipated to increase rapidly in the coming years. Despite this high adoption rate and future promises, there is a multitude of concerns about the impact of GM crops on the environment. Regulatory approaches in Europe and North America are essentially different. In the EU, it is based on the process of making GM crops; in the US, on the characteristics of the GM product. Many other countries are in the process of establishing regulation based on either system or a mixture. Despite these differences, the information required for risk assessment tends to be similar. Each risk assessment considers the possibility, probability and consequence of harm on a case-by-case basis. For GM crops, the impact of non-use should be added to this evaluation. It is important that the regulation of risk should not turn into the risk of regulation. The best and most appropriate baseline for comparison when performing risk assessment on GM crops is the impact of plants developed by traditional breeding. The latter is an integral and accepted part of agriculture.

Soil microbiome characteristics and soilborne disease development associated with long-term potato cropping system practices

USDA-ARS?s Scientific Manuscript database

Potato cropping system practices substantially affect soil microbial communities and the development of soilborne diseases. Cropping systems incorporating soil health management practices, such as longer rotations, disease-suppressive crops, reduced tillage, and/or organic amendments can potentially...

Soil organic carbon and land use in Veneto and Friuli Venezia Giulia (Northern Italy)

NASA Astrophysics Data System (ADS)

Francaviglia, Rosa; Renzi, Gianluca; Benedetti, Anna

2014-05-01

The Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF) has set up a statistical survey aimed to provide the national forecast of yields and areas related to the main Italian agricultural crops (AGRIT). The methodology is based on field surveys and remote-sensed data, covers yearly the whole national territory, and is based on 100,000 observations which are statistically selected from a predefined grid made up of about 1,200,000 georeferenced points. In 2011-2012 we determined the soil organic carbon content (SOC) of 1,160 sampling points situated in Northern Italy in the plains and hills of Veneto (VEN) and Friuli Venezia Giulia (FVG), for which the land use in the period 2008-2010 was known. Samples have been subdivided in three main classes: arable crops, orchards and fodder crops. SOC was higher in FVG samples (2.48%, n=266) than in VEN samples (1.90%, n=894). The average value (2.03%) is clearly affected by the higher number of VEN samples. FVG data have been aggregated in continuous crops (maize, soybean, wheat), 2-yr rotations (maize-wheat, soybean wheat, maize-soybean), 3-yr rotations, vineyards (totally, partially and no-grassed), alfalfa, and permanent fodder crops. No significant differences were detected among the land uses due to the low number of samples in some classes, but some important findings do exist from the agronomic point of view. Fodder crops (5.65%), alfalfa (3.41%) and vineyards (2.72%) showed the higher SOC content. SOC was 2.94% and 1.39 % in the grassed and no-grassed vineyards respectively. In the arable crops the average SOC was 2.18%, ranging from 2.32% (soybean-wheat rotation) to 2.03% (continuous soybean). SOC was 2.19% in the continuous maize, with 2.23% in corn and 1.87% in silage maize. The lower values were in the maize-wheat rotation (1.53%) and the continuous wheat (1.47%). VEN data have been aggregated in continuous crops (maize, soybean and wheat), 2-yr rotations (maize-wheat, soybean-wheat, maize-soybean, soybean-alfalfa, wheat-alfalfa, maize-alfalfa), 3-yr rotations, orchards (mulched, totally, partially and no-grassed), alfalfa, permanent fodder crops, and land use change (from arable to fodder crops and vice versa). The mean value was 1.57% in arable crops, 2.46% in orchards (including vineyards, olive groves, and fruit crops), 3.13% in fodder crops. SOC in orchards was 1.82% (no grassed), 2.46% (grassed), 2.69% (mulched); 2.10 and 2.08% in the 2-yr rotations soybean-wheat and soybean-alfalfa respectively. SOC in the other arable crops was between 1.79% (land use change) and 1.37% (continuous soybean). A higher SOC was shown in VEN samples also when comparing continuous corn (1.69%) and continuous silage maize (1.43%). Data, even limited to two Regions, have clearly shown the positive contribution to SOC storage of orchards (mainly in grassed and mulched systems) and fodder crops, which are more conservative systems due to the lower soil disturbance from tillage operations; and to a lower extent of cropping systems with alfalfa or other legume crops.

Forecasting wheat and barley crop production in arid and semi-arid regions using remotely sensed primary productivity and crop phenology: A case study in Iraq.

PubMed

Qader, Sarchil Hama; Dash, Jadunandan; Atkinson, Peter M

2018-02-01

Crop production and yield estimation using remotely sensed data have been studied widely, but such information is generally scarce in arid and semi-arid regions. In these regions, inter-annual variation in climatic factors (such as rainfall) combined with anthropogenic factors (such as civil war) pose major risks to food security. Thus, an operational crop production estimation and forecasting system is required to help decision-makers to make early estimates of potential food availability. Data from NASA's MODIS with official crop statistics were combined to develop an empirical regression-based model to forecast winter wheat and barley production in Iraq. The study explores remotely sensed indices representing crop productivity over the crop growing season to find the optimal correlation with crop production. The potential of three different remotely sensed indices, and information related to the phenology of crops, for forecasting crop production at the governorate level was tested and their results were validated using the leave-one-year-out approach. Despite testing several methodological approaches, and extensive spatio-temporal analysis, this paper depicts the difficulty in estimating crop yield on an annual base using current satellite low-resolution data. However, more precise estimates of crop production were possible. The result of the current research implies that the date of the maximum vegetation index (VI) offered the most accurate forecast of crop production with an average R 2 =0.70 compared to the date of MODIS EVI (Avg R 2 =0.68) and a NPP (Avg R 2 =0.66). When winter wheat and barley production were forecasted using NDVI, EVI and NPP and compared to official statistics, the relative error ranged from -20 to 20%, -45 to 28% and -48 to 22%, respectively. The research indicated that remotely sensed indices could characterize and forecast crop production more accurately than simple cropping area, which was treated as a null model against which to evaluate the proposed approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate change vulnerability in the food, energy, and water nexus: concerns for agricultural production in Arizona and its urban export supply

NASA Astrophysics Data System (ADS)

Berardy, Andrew; Chester, Mikhail V.

2017-03-01

Interdependent systems providing water and energy services are necessary for agriculture. Climate change and increased resource demands are expected to cause frequent and severe strains on these systems. Arizona is especially vulnerable to such strains due to its hot and arid climate. However, its climate enables year-round agricultural production, allowing Arizona to supply most of the country’s winter lettuce and vegetables. In addition to Phoenix and Tucson, cities including El Paso, Las Vegas, Los Angeles, and San Diego rely on Arizona for several types of agricultural products such as animal feed and livestock, meaning that disruptions to Arizona’s agriculture also disrupt food supply chains to at least six major cities. Arizona’s predominately irrigated agriculture relies on water imported through an energy intensive process from water-stressed regions. Most irrigation in Arizona is electricity powered, so failures in energy or water systems can cascade to the food system, creating a food-energy-water (FEW) nexus of vulnerability. We construct a dynamic simulation model of the FEW nexus in Arizona to assess the potential impacts of increasing temperatures and disruptions to energy and water supplies on crop irrigation requirements, on-farm energy use, and yield. We use this model to identify critical points of intersection between energy, water, and agricultural systems and quantify expected increases in resource use and yield loss. Our model is based on threshold temperatures of crops, USDA and US Geological Survey data, Arizona crop budgets, and region-specific literature. We predict that temperature increase above the baseline could decrease yields by up to 12.2% per 1 °C for major Arizona crops and require increased irrigation of about 2.6% per 1 °C. Response to drought varies widely based on crop and phenophase, so we estimate irrigation interruption effects through scenario analysis. We provide an overview of potential adaptation measures farmers can take, and barriers to implementation.

JPRS Report Science & Technology USSR: Science & Technology Policy.

DTIC Science & Technology

1989-01-17

ing the genetic apparatus of various organisms and creates necessary conditions for breeding high-yielding agricultural crops and races. However...labor. For the present every flower of creativity, not only scientific, but also inventing and artistic, in our country should penetrate the...ensured. The necessary set of local selection varieties for individual crops does not exist. A modern industrially-based seed- growing system is

Global Monitoring RSEM System for Crop Production by Incorporating Satellite-based Photosynthesis Rates and Anomaly Data of Sea Surface Temperature

NASA Astrophysics Data System (ADS)

Kaneko, D.; Sakuma, H.

2014-12-01

The first author has been developing RSEM crop-monitoring system using satellite-based assessment of photosynthesis, incorporating meteorological conditions. Crop production comprises of several stages and plural mechanisms based on leaf photosynthesis, surface energy balance, and the maturing of grains after fixation of CO2, along with water exchange through soil vegetation-atmosphere transfer. Grain production in prime countries appears to be randomly perturbed regionally and globally. Weather for crop plants reflects turbulent phenomena of convective and advection flows in atmosphere and surface boundary layer. It has been difficult for scientists to simulate and forecast weather correctly for sufficiently long terms to crop harvesting. However, severely poor harvests related to continental events must originate from a consistent mechanism of abnormal energetic flow in the atmosphere through both land and oceans. It should be remembered that oceans have more than 100 times of energy storage compared to atmosphere and ocean currents represent gigantic energy flows, strongly affecting climate. Anomalies of Sea Surface Temperature (SST), globally known as El Niño, Indian Ocean dipole, and Atlantic Niño etc., affect the seasonal climate on a continental scale. The authors aim to combine monitoring and seasonal forecasting, considering such mechanisms through land-ocean biosphere transfer. The present system produces assessments for all continents, specifically monitoring agricultural fields of main crops. Historical regions of poor and good harvests are compared with distributions of SST anomalies, which are provided by NASA GSFC. Those comparisons fairly suggest that the Worst harvest in 1993 and the Best in 1994 relate to the offshore distribution of low temperature anomalies and high gaps in ocean surface temperatures. However, high-temperature anomalies supported good harvests because of sufficient solar radiation for photosynthesis, and poor harvests because of insufficient precipitation. Integrated rates of photosynthesis on prime grains with planted areas were compared with the SST anomalies in poor and good harvests years. Other factors for poor harvest such as rainfall, solar radiation in addition to the intensity of winds as a measure of pressure perturbations need to be studied.

Grassland-Cropping Rotations: An Avenue for Agricultural Diversification to Reconcile High Production with Environmental Quality

NASA Astrophysics Data System (ADS)

Lemaire, Gilles; Gastal, François; Franzluebbers, Alan; Chabbi, Abad

2015-11-01

A need to increase agricultural production across the world to ensure continued food security appears to be at odds with the urgency to reduce the negative environmental impacts of intensive agriculture. Around the world, intensification has been associated with massive simplification and uniformity at all levels of organization, i.e., field, farm, landscape, and region. Therefore, we postulate that negative environmental impacts of modern agriculture are due more to production simplification than to inherent characteristics of agricultural productivity. Thus by enhancing diversity within agricultural systems, it should be possible to reconcile high quantity and quality of food production with environmental quality. Intensification of livestock and cropping systems separately within different specialized regions inevitably leads to unacceptable environmental impacts because of the overly uniform land use system in intensive cereal areas and excessive N-P loads in intensive animal areas. The capacity of grassland ecosystems to couple C and N cycles through microbial-soil-plant interactions as a way for mitigating the environmental impacts of intensive arable cropping system was analyzed in different management options: grazing, cutting, and ley duration, in order to minimize trade-offs between production and the environment. We suggest that integrated crop-livestock systems are an appropriate strategy to enhance diversity. Sod-based rotations can temporally and spatially capture the benefits of leys for minimizing environmental impacts, while still maintaining periods and areas of intensive cropping. Long-term experimental results illustrate the potential of such systems to sequester C in soil and to reduce and control N emissions to the atmosphere and hydrosphere.

Grassland-Cropping Rotations: An Avenue for Agricultural Diversification to Reconcile High Production with Environmental Quality.

PubMed

Lemaire, Gilles; Gastal, François; Franzluebbers, Alan; Chabbi, Abad

2015-11-01

A need to increase agricultural production across the world to ensure continued food security appears to be at odds with the urgency to reduce the negative environmental impacts of intensive agriculture. Around the world, intensification has been associated with massive simplification and uniformity at all levels of organization, i.e., field, farm, landscape, and region. Therefore, we postulate that negative environmental impacts of modern agriculture are due more to production simplification than to inherent characteristics of agricultural productivity. Thus by enhancing diversity within agricultural systems, it should be possible to reconcile high quantity and quality of food production with environmental quality. Intensification of livestock and cropping systems separately within different specialized regions inevitably leads to unacceptable environmental impacts because of the overly uniform land use system in intensive cereal areas and excessive N-P loads in intensive animal areas. The capacity of grassland ecosystems to couple C and N cycles through microbial-soil-plant interactions as a way for mitigating the environmental impacts of intensive arable cropping system was analyzed in different management options: grazing, cutting, and ley duration, in order to minimize trade-offs between production and the environment. We suggest that integrated crop-livestock systems are an appropriate strategy to enhance diversity. Sod-based rotations can temporally and spatially capture the benefits of leys for minimizing environmental impacts, while still maintaining periods and areas of intensive cropping. Long-term experimental results illustrate the potential of such systems to sequester C in soil and to reduce and control N emissions to the atmosphere and hydrosphere.

Impacts of climate change on cropping patterns in a tropical, sub-humid watershed

PubMed Central

Zwart, Sander J.; Hein, Lars

2018-01-01

In recent decades, there have been substantial increases in crop production in sub-Saharan Africa (SSA) as a result of higher yields, increased cropping intensity, expansion of irrigated cropping systems, and rainfed cropland expansion. Yet, to date much of the research focus of the impact of climate change on crop production in the coming decades has been on crop yield responses. In this study, we analyse the impact of climate change on the potential for increasing rainfed cropping intensity through sequential cropping and irrigation expansion in central Benin. Our approach combines hydrological modelling and scenario analysis involving two Representative Concentration Pathways (RCPs), two water-use scenarios for the watershed based on the Shared Socioeconomic Pathways (SSPs), and environmental water requirements leading to sustained streamflow. Our analyses show that in Benin, warmer temperatures will severely limit crop production increases achieved through the expansion of sequential cropping. Depending on the climate change scenario, between 50% and 95% of cultivated areas that can currently support sequential cropping or will need to revert to single cropping. The results also show that the irrigation potential of the watershed will be at least halved by mid-century in all scenario combinations. Given the urgent need to increase crop production to meet the demands of a growing population in SSA, our study outlines challenges and the need for planned development that need to be overcome to improve food security in the coming decades. PMID:29513753

Predictive spatial modeling of narcotic crop growth patterns

USGS Publications Warehouse

Waltz, Frederick A.; Moore, D.G.

1986-01-01

Spatial models for predicting the geographic distribution of marijuana crops have been developed and are being evaluated for use in law enforcement programs. The models are based on growing condition preferences and on psychological inferences regarding grower behavior. Experiences of local law officials were used to derive the initial model, which was updated and improved as data from crop finds were archived and statistically analyzed. The predictive models are changed as crop locations are moved in response to the pressures of law enforcement. The models use spatial data in a raster geographic information system. The spatial data are derived from the U.S. Geological Survey's US GeoData, standard 7.5-minute topographic quadrangle maps, interpretations of aerial photographs, and thematic maps. Updating of cultural patterns, canopy closure, and other dynamic features is conducted through interpretation of aerial photographs registered to the 7.5-minute quadrangle base. The model is used to numerically weight various data layers that have been processed using spread functions, edge definition, and categorization. The building of the spatial data base, model development, model application, product generation, and use are collectively referred to as the Area Reduction Program (ARP). The goal of ARP is to provide law enforcement officials with tactical maps that show the most likely locations for narcotic crops.

Crop diversity effects on productivity and economic returns under dryland agriculture

USDA-ARS?s Scientific Manuscript database

Increasing crop diversity has been identified as a method to improve agronomic performance of cropping systems and increase provision of ecosystem services. However, there is a need to understand the economic performance of more diverse cropping systems. Crop productivity and economic net returns we...

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Statistical modeling of yield and variance instability in conventional and organic cropping systems

USDA-ARS?s Scientific Manuscript database

Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...

Tolerance of interseeded annual ryegrass and red clover cover crops to residual herbicides in Mid-Atlantic corn cropping systems

USDA-ARS?s Scientific Manuscript database

In the Mid-Atlantic region, there is increasing interest in the use of relay-cropping strategies to establish cover crops in corn cropping systems. Recent studies have demonstrated the potential to establish annual ryegrass and red clover cover crops at the V5 corn growth stage using a high-clearan...

Radar response to vegetation. [soil moisture mapping via microwave backscattering

NASA Technical Reports Server (NTRS)

Ulaby, F. T.

1975-01-01

Active microwave measurements of vegetation backscatter were conducted to determine the utility of radar in mapping soil moisture through vegetation and mapping crop types. Using a truck-mounted boom, spectral response data were obtained for four crop types (corn, milo, soybeans, and alfalfa) over the 4-8 GHz frequency band, at incidence angles of 0 to 70 degrees in 10-degree steps, and for all four linear polarization combinations. Based on a total of 125 data sets covering a wide range of soil moisture, content, system design criteria are proposed for each of the aforementioned objectives. Quantitative soil moisture determination was best achieved at the lower frequency end of the 4-8 GHz band using HH polarized waves in the 5- to 15-degree incidence angle range. A combination of low and high frequency measurements are suggested for classifying crop types. For crop discrimination, a dual-frequency dual-polarization (VV and cross) system operating at incidence angles above 40 degrees is suggested.

Losses Assessment of Crops due to Typhoon Disaster in China Coastal Areas —— A Case Study of Zhanjiang City, Guangdong Province

NASA Astrophysics Data System (ADS)

Mo, W.; Fang, W.

2015-12-01

Vulnerability which quantifies the loss ratio under different hazard intensity is an important feature of the natural disaster system and has important significance to natural disaster risk assessment. Agriculture is an outdoor industry with high risk of meteorological disasters. The strong winds, heavy rain and storm surge are main typhoon hazard factors to crops. To provide a quantitative research method for the loss evaluation of crops due to typhoon disaster we first revised two vulnerability curves for crops under comprehensive intensity of typhoon based on the simulated hazard data and loss data related to historical typhoon events landing on China from 1949 to 2014；and then established a storm surge vulnerability matrix of crops regarding Zhanjiang City of Guangdong Province as the study area ; finally, we put forward three storm surge fragility curves for crops representing different states of loss. The results can effectively describe the typhoon vulnerability for crops in China coastal areas so as to provide the input to post-disaster loss assessments and catastrophe modeling applications.

Introducing non-flooded crops in rice-dominated landscapes: Impact on carbon, nitrogen and water budgets

NASA Astrophysics Data System (ADS)

Jauker, Frank; Wassmann, Reiner; Amelung, Wulf; Breuer, Lutz; Butterbach-Bahl, Klaus; Conrad, Ralf; Ekschmitt, Klemens; Goldbach, Heiner; He, Yao; John, Katharina; Kiese, Ralf; Kraus, David; Reinhold-Hurek, Barbara; Siemens, Jan; Weller, Sebastian; Wolters, Volkmar

2013-04-01

Rice production consumes about 30% of all freshwater used worldwide and 45% in Asia. Turning away from permanently flooded rice cropping systems for mitigating future water scarcity and reducing methane emissions, however, will alter a variety of ecosystem services with potential adverse effects to both the environment and agricultural production. Moreover, implementing systems that alternate between flooded and non-flooded crops increases the risk of disruptive effects. The multi-disciplinary DFG research unit ICON aims at exploring and quantifying the ecological consequences of altered water regimes (flooded vs. non-flooded), crop diversification (irrigated rice vs. aerobic rice vs. maize), and different fertilization strategies (conventional, site-specific, and zero N fertilization). ICON particularly focuses on the biogeochemical cycling of carbon and nitrogen, green-house gas (GHG) emissions, water balance, soil biotic processes and other important ecosystem services. The overarching goal is to provide the basic process understanding that is necessary for balancing the revenues and environmental impacts of high-yield rice cropping systems while maintaining their vital ecosystem services. To this aim, a large-scale field experiment has been established at the experimental farm of the International Rice Research Institute (IRRI, Philippines). Ultimately, the experimental results are analyzed in the context of management scenarios by an integrated modeling of crop development (ORYZA), carbon and nitrogen cycling (MoBiLE-DNDC), and water fluxes (CMF), providing the basis for developing pathways to a conversion of rice-based systems towards higher yield potentials under minimized environmental impacts. In our presentation, we demonstrate the set-up of the controlled large-scale field experiment for simultaneous assessment of carbon and nitrogen fluxes and water budgets. We show and discuss first results for: - Quantification and assessment of the net-fluxes of CH4, N2O and CO2 from rice-rice and rice-maize rotations. The conversion of flooded to non-flooded cropping systems resulted in pollution swapping of greenhouse gas emissions, shifting from CH4 under wet conditions to N2O under dry conditions. - Quantification and assessment of water budgets and nutrient loss in rice-rice and rice-maize rotations. Switching from rice-rice dominated growing systems to upland rice or maize-rice cropping systems resulted in reduced water use efficiency and increased nitrogen loss. - Quantification and assessment of soil functions affected by soil fauna community structure in flooded and non-flooded cropping rotations. In contrast to temperate soils, earthworms reduced the peaks of microbial C and N decomposition depending on soil water content.

Integrated crop-livestock systems and cover crop grazing in the Northern Great Plains

USDA-ARS?s Scientific Manuscript database

Integrating crops and livestock has been identified as an approach to sustainably intensify agricultural systems, increasing production while reducing the need for external inputs, building soil health, and increasing economic returns. Cover crops and grazing these cover crops are a natural fit with...

Long-term cropping systems study

USDA-ARS?s Scientific Manuscript database

This long-term study has been conducted on the Agronomy Farm at ARDC since the early 1970’s. In the beginning, the objectives were mainly related to crop production as affected by different cropping systems. The cropping systems included in the study are Continuous Corn, Soybean, and Sorghum; 2-year...

Online irrigation service for fruit und vegetable crops at farmers site

NASA Astrophysics Data System (ADS)

Janssen, W.

2009-09-01

Online irrigation service for fruit und vegetable crops at farmers site by W. Janssen, German Weather Service, 63067 Offenbach Agrowetter irrigation advice is a product which calculates the present soil moisture as well as the soil moisture to be expected over the next 5 days for over 30 different crops. It's based on a water balance model and provides targeted recommendations for irrigation. Irrigation inputs according to the soil in order to avoid infiltration and, as a consequence thereof, the undesired movement of nitrate and plant protectants into the groundwater. This interactive 'online system' takes into account the user's individual circumstances such as crop and soil characteristics and the precipitation and irrigation amounts at the user's site. Each user may calculate up to 16 different enquiries simultaneously (different crops or different emergence dates). The user can calculate the individual soil moistures for his fields with a maximum effort of 5 minutes per week only. The sources of water are precipitation and irrigation whereas water losses occur due to evapotranspiration and infiltration of water into the ground. The evapotranspiration is calculated by multiplying a reference evapotranspiration (maximum evapotranspiration over grass) with the so-called crop coefficients (kc values) that have been developed by the Geisenheim Research Centre, Vegetable Crops Branch. Kc values depending on the crop and the individual plant development stage. The reference evapotranspiration is calculated from a base weather station user has chosen (out of around 500 weather stations) using Penman method based on daily values. After chosen a crop and soil type the user must manually enter the precipitation data measured at the site, the irrigation water inputs and the dates for a few phenological stages. Economical aspects can be considered by changing the values of soil moisture from which recommendations for irrigation start from optimal to necessary plant supply. Previous comparative measurements carried out by the Agricultural Administration of Baden-Württemberg relating to potatoes, onions, vine stocks, and strawberries agreed very well with the calculations.

Developing an automatic classification system of vegetation anomalies for early warning with the ASAP (Anomaly hot Spots of Agricultural Production) system

NASA Astrophysics Data System (ADS)

Meroni, M.; Rembold, F.; Urbano, F.; Lemoine, G.

2016-12-01

Anomaly maps and time profiles of remote sensing derived indicators relevant to monitor crop and vegetation stress can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for SDG 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide monthly warning of production deficits in water-limited agriculture worldwide. The first step is fully automated and aims at classifying each administrative unit (1st sub-national level) into a number of possible warning levels, ranging from "none" to "watch" and up to "extended alarm". The second step involves the verification of the automatic warnings and integration into a short national level analysis by agricultural analysts. In this paper we describe the methodological development of the automatic vegetation anomaly classification system. Warnings are triggered only during the crop growing season, defined by a remote sensing based phenology. The classification takes into consideration the fraction of the agricultural and rangelands area for each administrative unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index (SPI), computed at 1 and 3-month scale) and one biophysical indicator (the cumulative NDVI from the start of the growing season). The severity of the warning thus depends on the timing, the nature and the number of indicators for which an anomaly is detected. The prototype system is using global NDVI images of the METOP sensor, while a second version is being developed based on 1km Modis NDVI with temporal smoothing and near real time filtering. Also a specific water balance model is under development to include agriculture water stress information in addition to the SPI. The monthly warning classification and crop condition assessment will be made available on a website and will strengthen the JRC support to information products based on consensus assessment such as the GEOGLAM Crop Monitor for Early Warning.

Phosphorus (P) balances and P availability in a field trial comparing organic and conventional farming systems since 35 years

NASA Astrophysics Data System (ADS)

Jarosch, Klaus; Oberson, Astrid; Emmanuel, Frossard; Gunst, Lucie; Dubois, David; Mäder, Paul; Mayer, Jochen

2017-04-01

Background: The adequate supply with phosphorus (P) is crucial to maintain constant yields in all cropping systems. It remains yet unclear whether P in organic farming systems may become a limiting factor for plant nutrition in the long term. Material and Methods: The DOK long-term field trial was established in 1978 to compare different farming systems. The trial consists of two organic (biodynamic (DYN), bioorganic (ORG)) and two conventional treatments (using farmyard manure plus mineral fertilizer (KON) and mineral fertilizer only (MIN, established in 1985)). In a control treatment (NON) no fertilizer is applied. The fertilization for the organic treatments DYN and ORG is defined on manure production of 1.4 livestock units (since 1992), while before that 1.2 livestock units were used as reference. Fertilization on the conventional treatments KON and MIN is defined by Swiss fertilization guidelines. Treatments DYN, ORG and KON are maintained at full fertilization level (2) as well as halved fertilization level (1) while treatment MIN is only maintained at fertilization level 2. All treatments are maintained with the same crop rotation with a period of 7 years. An annual P-balance was calculated, based on the input factors 1) fertilization, 2) seeds and 3) deposition and the output factors 4) removal with crop yields and 5) leaching. The factors fertilization and removal with crop yields were based on documentation since trial establishment. Factor seeds was estimated based on documented quantity of used seeds per treatment and factors deposition and leaching were estimated by values available in literature. Additionally, P availability was determined via isotopic exchange kinetics (IEK) experiments after each crop rotation period (7 years). The IEK experiments allow to estimate the rate of P exchange from soil into soil solution and thus to estimate plant P availability over a cropping period. Results and Conclusions: Main influencing parameters of the P-balance were the factors fertilization and the removal with cropping products. Other inputs (deposition, seeds) and outputs (leaching) were of minor importance for the outcome of the balance for all treatments. For the treatments KON2 and M we observed a slightly positive P-balance of 3 and 6 kg ha-1 year-1, respectively. All other treatments showed a negative P-balance, even in the systems with high fertilization levels (DYN2 and ORG2). The deficit in the P-balance was even more pronounced in the farming systems with reduced fertilizer application rates DYN1, ORG1 and KON1 (-11 to -13 kg ha-1 year-1). The unfertilized control (NON) showed the highest deficit with -19 kg ha-1 year-1. The calculated P-balance suggests that the full fertilization level in treatments DYN2 and ORG2 is not sufficient to mitigate the entire P removal. This deficit is even more pronounced on treatments with less fertilization. In the long term, this fertilization practice may lead to P limitation, especially in the organic treatments. Phosphorus availability determined by IEK in the top soil (0-20 cm) declined with time in all treatments. This decline may currently already limit crop yield in some farming systems, yet, a redistribution of P from deeper soil layers seems to mitigate this limitation. Additionally, the relatively high P-status in the soil prior to initiation of the DOK trial may currently still buffer against P-limitation for plants. The results of this study will be discussed in regard to sustainable P use in different farming systems.

Regulation of Population Densities of Heterodera cajani and Other Plant-Parasitic Nematodes by Crop Rotations on Vertisols, in Semi-Arid Tropical Production Systems in India

PubMed Central

Sharma, S. B.; Rego, T. J.; Mohiuddin, M.; Rao, V. N.

1996-01-01

The significance of double crop (intercrop and sequential crop), single crop (rainy season crop fallow from June to September), and rotations on densities of Heterodera cajani, Helicotylenchus retusus, and Rotylenchulus reniformis was studied on Vertisol (Typic Pellusterts) between 1987 and 1993. Cowpea (Vigna sinensis), mungbean (Phaseolus aureus), and pigeonpea (Cajanus cajan) greatly increased the population densities of H. cajani and suppressed the population densities of other plant-parasitic nematodes. Mean population densities of H. cajani were about 8 times lower in single crop systems than in double crop systems, with pigeonpea as a component intercrop. Plots planted to sorghum, safflower, and chickpea in the preceding year contained fewer H. cajani eggs and juveniles than did plots previously planted to pigeonpea, cowpea, or mungbean. Continuous cropping of sorghum in the rainy season and safflower in the post-rainy season markedly reduced the population density of H. cajani. Sorghum, safflower, and chickpea favored increased population densities of H. retusus. Adding cowpea to the system resulted in a significant increase in the densities of R. reniformis. Mean densities of total plant-parasitic nematodes were three times greater in double crop systems, with pigeonpea as a component intercrop than in single crop systems with rainy season fallow component. Cropping systems had a regulatory effect on the nematode populations and could be an effective nematode management tactic. Intercropping of sorghum with H. cajani tolerant pigeonpea could be effective in increasing the productivity of traditional production systems in H. cajani infested regions. PMID:19277141

Risk, regulation and biotechnology: The case of GM crops

PubMed Central

Smyth, Stuart J; Phillips, Peter WB

2014-01-01

The global regulation of products of biotechnology is increasingly divided. Regulatory decisions for genetically modified (GM) crops in North America are predictable and efficient, with numerous countries in Latin and South America, Australia and Asia following this lead. While it might have been possible to argue that Europe's regulations were at one time based on real concerns about minimizing risks and ensuring health and safety, it is increasingly apparent that the entire European Union (EU) regulatory system for GM crops and foods is now driven by political agendas. Countries within the EU are at odds with each other as some have commercial production of GM crops, while others refuse to even develop regulations that could provide for the commercial release of GM crops. This divide in regulatory decision-making is affecting international grain trade, creating challenges for feeding an increasing global population. PMID:25437235

An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

NASA Astrophysics Data System (ADS)

Ding, Deng

Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form of perennial grasses or corn stover as a more risky enterprise than their current crop production systems, likely because of market and production risks and lock in effects. As a result farmers do not follow a simple farm-profit maximization rule. In the third study, the consequent water quantity and quality change of the potential land use transitions given alternative biofuel crop market scenarios is explored in a case study in the Clear Creek watershed. A computer program is developed to implement the loose-coupling strategy to couple an agent-based land use model with SWAT. The simulation results show that watershed-scale water quantity (water yield and runoff) and quality variables (sediment and nutrient loads) decrease in values as switchgrass price increases. However, negligence of farmers risk aversions towards biofuel crop adoption would cause overestimation of the impacts of switchgrass price on water quantity and quality.

A UAS-based remote sensing platform for crop water stress detection

NASA Astrophysics Data System (ADS)

Zhang, H.; Wang, D.; Ayars, J. E.

2014-12-01

The remote detection of water stress in a biofuel crop field was investigated using canopy temperature measurements. An experimental trial was set up in the central valley of Maui, Hawaii, comprising different sugarcane varieties and irrigation regimes. An unmanned aerial system (UAS) was equipped with a FLIR A615 thermal camera to acquire canopy temperature imagery. Images were mosaicked and processed to show spatial temperature difference of entire field. A weather station was installed in a full irrigation plot to collect meteorological parameters. The sensitivity of canopy to air temperature difference and crop water stress index were investigated on detecting cop water stress levels. The results showed that low irrigation level treatment plots resulted in higher canopy temperatures compared to the high irrigation level treatment plots. Canopy temperatures also showed differences in water stress in different sugarcane varieties. The study demonstrated the feasibility of UAS-based thermal method to quantify plant water status of sugar canes used for biofuel crops.

Advances in shrub-willow crops for bioenergy, renewable products, and environmental benefits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volk, Timothy A.; Heavey, Justin P.; Eisenbies, Mark H.

Short-rotation coppice systems like shrub willow are projected to be an important source of biomass in the United States for the production of bioenergy, biofuels, and renewable bio-based products, with the potential for auxiliary environmental benefits and multifunctional systems. Almost three decades of research has focused on the development of shrub willow crops for biomass and ecosystem services. The current expansion of willow in New York State (about 500 ha) for the production of renewable power and heat has been possible because of incentive programs offered by the federal government, commitments by end users, the development of reliable harvesting systems,more » and extension services offered to growers. Improvements in the economics of the system are expected as willow production expands further, which should help lower establishment costs, enhance crop management options and increase efficiencies in harvesting and logistics. As a result, deploying willow in multifunctional value-added systems provides opportunities for both potential producers and end users to learn about the system and the quality of the biomass feedstock, which in turn will help overcome barriers to expansion.« less

Advances in shrub-willow crops for bioenergy, renewable products, and environmental benefits

DOE PAGES

Volk, Timothy A.; Heavey, Justin P.; Eisenbies, Mark H.

2016-05-02

Short-rotation coppice systems like shrub willow are projected to be an important source of biomass in the United States for the production of bioenergy, biofuels, and renewable bio-based products, with the potential for auxiliary environmental benefits and multifunctional systems. Almost three decades of research has focused on the development of shrub willow crops for biomass and ecosystem services. The current expansion of willow in New York State (about 500 ha) for the production of renewable power and heat has been possible because of incentive programs offered by the federal government, commitments by end users, the development of reliable harvesting systems,more » and extension services offered to growers. Improvements in the economics of the system are expected as willow production expands further, which should help lower establishment costs, enhance crop management options and increase efficiencies in harvesting and logistics. As a result, deploying willow in multifunctional value-added systems provides opportunities for both potential producers and end users to learn about the system and the quality of the biomass feedstock, which in turn will help overcome barriers to expansion.« less

Environmental Systems Test Stand

NASA Astrophysics Data System (ADS)

Barta, D.; Young, J.; Ewert, M.; Lee, S.; Wells, P.; Fortson, R.; Castillo, J.

A test stand has been developed for the evaluation of prototype lighting, environmental control and crop cultivation technologies for plant production within an advanced life support system. Design of the test stand was based on preliminary designs of the center growth bay of the Biomass Production Chamber, one of several modules of the Bioregenerative Planetary Life Support Systems Test Complex (BIO- Plex). It consists of two controlled-environment shelves, each with 4.7 m2 of area for crop growth (150 cm width, 315 cm length). There are two chilled water loops, one for operation at conventional temperatures (5-10C) for air temperature and humidity control and one for operation at higher temperatures (15-50C) for waste heat acquisition and heating. Modular light boxes, utilizing either air-cooled or water- jacketed HPS lamps, have been developed. This modular design will allow for easy replacement of new lighting technologies within the light banks. An advanced data acquisition and control system has been developed utilizing localized, networked- based data acquisition modules and programmed with object-based control software.

Simulating changes in cropping practices in conventional and glyphosate-resistant maize. II. Weed impacts on crop production and biodiversity.

PubMed

Colbach, Nathalie; Darmency, Henri; Fernier, Alice; Granger, Sylvie; Le Corre, Valérie; Messéan, Antoine

2017-05-01

Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FLORSYS; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.

A Data-driven Approach to Integrate Crop Rotation Agronomic Practices in a Global Gridded Land-use Forcing Dataset

NASA Astrophysics Data System (ADS)

Sahajpal, R.; Hurtt, G. C.; Chini, L. P.; Frolking, S. E.; Izaurralde, R. C.

2016-12-01

Agro-ecosystems are the dominant land-use type on Earth, covering more than a third of ice-free land surface. Agricultural practices have influenced the Earth's climate system by significantly altering the biogeophysical and biogeochemical properties from hyper-local to global scales. While past work has focused largely on characterizing the effects of net land cover changes, the magnitude and nature of gross transitions and agricultural management practices on climate remains highly uncertain. To address this issue, a new set of global gridded land-use forcing datasets (LUH2) have been developed in a standard format required by climate models for CMIP6. For the first time, this dataset includes information on key agricultural management practices including crop rotations. Crop rotations describe the practice of growing crops on the same land in sequential seasons and are essential to agronomic management as they influence key ecosystem services such as crop yields, water quality, carbon and nutrient cycling, pest and disease control. Here, we present a data-driven approach to infer crop rotations based on crop specific land cover data, derived from moderate resolution satellite imagery and created at an annual time-step for the continental United States. Our approach compresses the more than 100,000 unique crop rotations prevalent in the United States from 2013 - 2015 to about 200 representative crop rotations that account for nearly 80% of the spatio-temporal variability. Further simplification is achieved by mapping individual crops to crop functional types, which identify crops based on their photosynthetic pathways (C3/C4), life strategy (annual/perennial) and whether they are N-fixing or not. The resulting matrix of annual transitions between crop functional types averages 41,000 km2/yr for rotations between C3 and C4 annual crops, and 140,000 km2/yr between C3 N-fixing and C4 annual crops. The crop rotation matrix is combined with information on other land-use states to compute annual changes between these states, thereby producing a detailed land-use transition information that can help close regional and global carbon budgets. We also validate the quality of the crop rotations identified in our product in countries with agronomic practices different from the United States.

Sen2-Agri country level demonstration for Ukraine

NASA Astrophysics Data System (ADS)

Kussul, N.; Kolotii, A.; Shelestov, A.; Lavreniuk, M. S.

2016-12-01

Due to launch of Sentinel-2 mission European Space Agency (ESA) started Sentinel-2 for Agriculture (Sen2-Agri) project coordinated by Universite catholique de Louvain (UCL). Ukraine is selected as one of 3 country level demonstration sites for benchmarking Sentinel-2 data due to wide range of main crops (both winter and summer), big fields and high enough climate variability over the territory [1-2]. Within this county level demonstration main objectives are following: i) Sentinel's products quality assessment and their suitability estimation for the territory of Ukraine [2]; ii) demonstration in order to convince decision makers and state authorities; iii) assessment of the personnel and facilities required to run the Sen2-Agri system and creation of Sen-2 Agri products (crop type maps and such essential climatic variable as Leaf Area Index - LAI [3]). During this project ground data were collected for crop land mapping and crop type classification along the roads within main agro-climatic zones of Ukraine. For LAI estimation we used indirect non-destructive method which is based on DHP-images and VALERI protocol. Products created with use of Sen2-Agri system deployed during project execution and results of neural-network approach utilization will be compared. References Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508. Kussul, N., Skakun, S., Shelestov, A., Lavreniuk, M., Yailymov, B., & Kussul, O. (2015). Regional scale crop mapping using multi-temporal satellite imagery. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 45-52. Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation

PubMed Central

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation. PMID:27625660

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation.

PubMed

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation.

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.

PubMed

Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias

2017-11-03

Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

Agricultural production and water use scenarios in Cyprus under global change

NASA Astrophysics Data System (ADS)

Bruggeman, Adriana; Zoumides, Christos; Camera, Corrado; Pashiardis, Stelios; Zomeni, Zomenia

2014-05-01

In many countries of the world, food demand exceeds the total agricultural production. In semi-arid countries, agricultural water demand often also exceeds the sustainable supply of water resources. These water-stressed countries are expected to become even drier, as a result of global climate change. This will have a significant impact on the future of the agricultural sector and on food security. The aim of the AGWATER project consortium is to provide recommendations for climate change adaptation for the agricultural sector in Cyprus and the wider Mediterranean region. Gridded climate data sets, with 1-km horizontal resolution were prepared for Cyprus for 1980-2010. Regional Climate Model results were statistically downscaled, with the help of spatial weather generators. A new soil map was prepared using a predictive modelling and mapping technique and a large spatial database with soil and environmental parameters. Stakeholder meetings with agriculture and water stakeholders were held to develop future water prices, based on energy scenarios and to identify climate resilient production systems. Green houses, including also hydroponic systems, grapes, potatoes, cactus pears and carob trees were the more frequently identified production systems. The green-blue-water model, based on the FAO-56 dual crop coefficient approach, has been set up to compute agricultural water demand and yields for all crop fields in Cyprus under selected future scenarios. A set of agricultural production and water use performance indicators are computed by the model, including green and blue water use, crop yield, crop water productivity, net value of crop production and economic water productivity. This work is part of the AGWATER project - AEIFORIA/GEOGRO/0311(BIE)/06 - co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation.

GIS based evaluation of crop suitability for agricultural sustainability around Kolaghat thermal power plant, India.

PubMed

Adak, Subhas; Adhikari, Kalyan; Brahmachari, Koushik

2016-09-01

Fly ash exhaust from Kolaghat thermal power plant, West Bengal, India,?? affects the areas within the radius of 3 - 4 km. Land information system indicated that surface texture within 4 km was silty loam and clay content increased with increase of distance. Soil pH was alkaline (7.58-8.01) in affected circles, whereas soil was acidic (5.95-6.41) in rest of block. Organic carbon (OC) is roving from 0.36 to 0.64% in the nearer circles which is lesser from others. The present Crop suitability analysis revealed that 96.98 % area was suitable (S1) for maize, sesame, jute, whereas these were cultivated in less than 1% of land. Flowers are the best suitable (S1) in 88.9 % but it was grown in 6.02 % area.? The present rice area within 4 km of KTPP is showing moderately suitable (S2) and S1 for the rest. Wheat is moderately suitable (S2) in the almost all the circles.? Cultivation of vegetable crops is limited in the affected circles while the highly suitable (S1) comprises 67.49 % for the remaining areas though it covered only 6.01 % of the block.? This evaluation precisely improves more than 300% from the earlier cropping intensity of 177.95 %. Suitability based land use allocation serves as stepping stone to promote agricultural sustainability. Geographic information system (GIS) model has been developed to assess site specific crop suitability for sustainable agricultural planning.

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth

PubMed Central

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production. PMID:28848565

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth.

PubMed

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production.

[Soil quality assessment under different cropping system and straw management in farmland of arid oasis region].

PubMed

Zhang, Peng Peng; Pu, Xiao Zhen; Zhang, Wang Feng

2018-03-01

To reveal the regulatory mechanism of agricultural management practices on soil quality, an experiment was carried out to study the different cropping system and straw management on soil organic carbon and fractions and soil enzyme activity in farmland of arid oasis region, which would provide a scientific basic for enhancing agricultural resources utilization and sustainable development. In crop planting planning area, we took the mainly crop (cotton, wheat, maize) as research objects and designed long-term continues cropping and crop rotation experiments. The results showed that the soil organic carbon (SOC), soil microbial biomass C, labile C, water-soluble organic C, and hot-water-soluble organic C content were increased by 3.6%-9.9%, 41.8%-98.9%, 3.3%-17.0%, 11.1%-32.4%, 4.6%-27.5% by crop rotation compared to continues cropping, and 12%-35.9%, 22.4%-49.7%, 30.7%-51.0%, 10.6%-31.9%, 41.0%-96.4% by straw incorporated compared to straw removed, respectively. The soil catalase, dehydrogenase, β-glucosidase, invertase glucose, cellulase glucose activity were increased by 6.4%-10.9%, 6.6%-18.8%, 5.9%-15.3%, 10.0%-27.4%, 28.1%-37.5% by crop rotation compared to continues cropping, and 31.4%-47.5%, 19.9%-46.6%, 13.8%-20.7%, 19.8%-55.6%, 54.1%-70.9% by straw incorporated compared to straw removed, respectively. There were significant positive linear correlations among SOC, labile SOC fractions and soil enzyme. Therefore, we concluded that labile SOC fractions and soil enzyme were effective index for evaluating the change of SOC and soil quality. Based on factor analysis, in arid region, developing agricultural production using cropland management measures, such as straw-incorporated and combined short-term continues cotton and crop rotation, could enhance SOC and labile SOC fractions contents and soil enzyme activity, which could improve soil quality and be conducive to agricultural sustainable development.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Plants for space plantations. [crops for closed life support systems

NASA Technical Reports Server (NTRS)

Nikishanova, T. I.

1978-01-01

Criteria for selection of candidate crops for closed life support systems are presented and discussed, and desired characteristics of candidate higher plant crops are given. Carbohydrate crops, which are most suitable, grown worldwide are listed and discussed. The sweet potato, ipomoea batatas Poir., is shown to meet the criteria to the greatest degree, and the criteria are recommended as suitable for initial evaluation of candidate higher plant crops for such systems.

Linking pesticides and human health: a geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure.

PubMed

VoPham, Trang; Wilson, John P; Ruddell, Darren; Rashed, Tarek; Brooks, Maria M; Yuan, Jian-Min; Talbott, Evelyn O; Chang, Chung-Chou H; Weissfeld, Joel L

2015-08-01

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.

Benchmark study on glyphosate-resistant crop systems in the United States. Economics of herbicide resistance management practices in a 5 year field-scale study.

PubMed

Edwards, C Blake; Jordan, David L; Owen, Michael Dk; Dixon, Philip M; Young, Bryan G; Wilson, Robert G; Weller, Steven C; Shaw, David R

2014-12-01

Since the introduction of glyphosate-resistant (GR) crops, growers have often relied on glyphosate-only weed control programs. As a result, multiple weeds have evolved resistance to glyphosate. A 5 year study including 156 growers from Illinois, Iowa, Indiana, Nebraska, North Carolina and Mississippi in the United States was conducted to compare crop yields and net returns between grower standard weed management programs (SPs) and programs containing best management practices (BMPs) recommended by university weed scientists. The BMPs were designed to prevent or mitigate/manage evolved herbicide resistance. Weed management costs were greater for the BMP approach in most situations, but crop yields often increased sufficiently for net returns similar to those of the less expensive SPs. This response was similar across all years, geographical regions, states, crops and tillage systems. Herbicide use strategies that include a diversity of herbicide mechanisms of action will increase the long-term sustainability of glyphosate-based weed management strategies. Growers can adopt herbicide resistance BMPs with confidence that net returns will not be negatively affected in the short term and contribute to resistance management in the long term. © 2014 Society of Chemical Industry.

Crop Species Diversity Changes in the United States: 1978–2012

PubMed Central

Aguilar, Jonathan; Gramig, Greta G.; Hendrickson, John R.; Archer, David W.; Forcella, Frank; Liebig, Mark A.

2015-01-01

Anecdotal accounts regarding reduced US cropping system diversity have raised concerns about negative impacts of increasingly homogeneous cropping systems. However, formal analyses to document such changes are lacking. Using US Agriculture Census data, which are collected every five years, we quantified crop species diversity from 1978 to 2012, for the contiguous US on a county level basis. We used Shannon diversity indices expressed as effective number of crop species (ENCS) to quantify crop diversity. We then evaluated changes in county-level crop diversity both nationally and for each of the eight Farm Resource Regions developed by the National Agriculture Statistics Service. During the 34 years we considered in our analyses, both national and regional ENCS changed. Nationally, crop diversity was lower in 2012 than in 1978. However, our analyses also revealed interesting trends between and within different Resource Regions. Overall, the Heartland Resource Region had the lowest crop diversity whereas the Fruitful Rim and Northern Crescent had the highest. In contrast to the other Resource Regions, the Mississippi Portal had significantly higher crop diversity in 2012 than in 1978. Also, within regions there were differences between counties in crop diversity. Spatial autocorrelation revealed clustering of low and high ENCS and this trend became stronger over time. These results show that, nationally counties have been clustering into areas of either low diversity or high diversity. Moreover, a significant trend of more counties shifting to lower rather than to higher crop diversity was detected. The clustering and shifting demonstrates a trend toward crop diversity loss and attendant homogenization of agricultural production systems, which could have far-reaching consequences for provision of ecosystem system services associated with agricultural systems as well as food system sustainability. PMID:26308552

Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2016-01-01

Growing cellulosic feedstock crops (e.g., switchgrass) for biofuel is more environmentally sustainable than corn-based ethanol. Specifically, this practice can reduce soil erosion and water quality impairment from pesticides and fertilizer, improve ecosystem services and sustainability (e.g., serve as carbon sinks), and minimize impacts on global food supplies. The main goal of this study was to identify high-risk marginal croplands that are potentially suitable for growing cellulosic feedstock crops (e.g., switchgrass) in the US Great Plains (GP). Satellite-derived growing season Normalized Difference Vegetation Index, a switchgrass biomass productivity map obtained from a previous study, US Geological Survey (USGS) irrigation and crop masks, and US Department of Agriculture (USDA) crop indemnity maps for the GP were used in this study. Our hypothesis was that croplands with relatively low crop yield but high productivity potential for switchgrass may be suitable for converting to switchgrass. Areas with relatively low crop indemnity (crop indemnity <$2 157 068) were excluded from the suitable areas based on low probability of crop failures. Results show that approximately 650 000 ha of marginal croplands in the GP are potentially suitable for switchgrass development. The total estimated switchgrass biomass productivity gain from these suitable areas is about 5.9 million metric tons. Switchgrass can be cultivated in either lowland or upland regions in the GP depending on the local soil and environmental conditions. This study improves our understanding of ecosystem services and the sustainability of cropland systems in the GP. Results from this study provide useful information to land managers for making informed decisions regarding switchgrass development in the GP.

Effects of crop rotation and management system on water-extractable organic matter concentration, structure, and bioavailability in a chernozemic agricultural soil.

PubMed

Xu, Na; Wilson, Henry F; Saiers, James E; Entz, Martin

2013-01-01

Water-extractable organic matter (WEOM) in soil affects contaminant mobility and toxicity, heterotrophic production, and nutrient cycling in terrestrial and aquatic ecosystems. This study focuses on the influences of land use history and agricultural management practices on the water extractability of organic matter and nutrients from soils. Water-extractable organic matter was extracted from soils under different crop rotations (an annual rotation of wheat-pea/bean-wheat-flax or a perennial-based rotation of wheat-alfalfa-alfalfa-flax) and management systems (organic or conventional) and examined for its concentration, composition, and biodegradability. The results show that crop rotations including perennial legumes increased the concentration of water-extractable organic carbon (WEOC) and water-extractable organic nitrogen (WEON) and the biodegradability of WEOC in soil but depleted the quantity of water-extractable organic phosphorus (WEOP) and water-extractable reactive phosphorus. The 30-d incubation experiments showed that bioavailable WEOC varied from 12.5% in annual systems to 22% for perennial systems. The value of bioavailable WEOC was found to positively correlate with WEON concentrations and to negatively correlate with C:N ratio and the specific ultraviolet absorbance of WEOM. No significant treatment effect was present with the conventional and organic management practices, which suggested that WEOM, as the relatively labile pool in soil organic matter, is more responsive to the change in crop rotation than to mineral fertilizer application. Our results indicated that agricultural landscapes with contrasting crop rotations are likely to differentially affect rates of microbial cycling of organic matter leached to soil waters. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

First typology of cacao (Theobroma cacao L.) systems in Colombian Amazonia, based on tree species richness, canopy structure and light availability

PubMed Central

Suárez Salazar, Juan Carlos; Melgarejo, Luz Marina; Di Rienzo, Julio A.; Casanoves, Fernando

2018-01-01

Aim and background We present a typology of cacao agroforest systems in Colombian Amazonia. These systems had yet to be described in the literature, especially their potential in terms of biodiversity conservation. The systems studied are located in a post-conflict area, and a deforestation front in Colombian Amazonia. Cacao cropping systems are of key importance in Colombia: cacao plays a prime role in post conflict resolution, as cacao is a legal crop to replace illegal crops; cacao agroforests are expected to be a sustainable practice, promoting forest-friendly land use. Material and methods We worked in 50 x 2000 m2 agroforest plots, in Colombian Amazonia. A cluster analysis was used to build a typology based on 28 variables characterised in each plot, and related to diversity, composition, spatial structure and light availability for the cacao trees. We included variables related to light availability to evaluate the amount of transmitted radiation to the cacao trees in each type, and its suitability for cacao ecophysiological development. Main results We identified 4 types of cacao agroforests based on differences concerning tree species diversity and the impact of canopy spatial structure on light availability for the cacao trees in the understorey. We found 127 tree species in the dataset, with some exclusive species in each type. We also found that 3 out of the 4 types identified displayed an erosion of tree species diversity. This reduction in shade tree species may have been linked to the desire to reduce shade, but we also found that all the types described were compatible with good ecophysiological development of the cacao trees. Main conclusions and prospects Cacao agroforest systems may actually be achieving biodiversity conservation goals in Colombian Amazonia. One challenging prospect will be to monitor and encourage the conservation of tree species diversity in cacao agroforest systems during the development of these cropping systems, as a form of forest-friendly management enhancing sustainable peace building in Colombia. PMID:29401499

Population dynamics of caterpillars on three cover crops before sowing cotton in Mato Grosso (Brazil).

PubMed

Silvie, P J; Menzel, C A; Mello, A; Coelho, A G

2010-01-01

Direct seeding mulch-based cropping systems under a preliminary cover crop such as millet are common in some areas of Brazil. Lepidopteran pests that damage cotton, soybean and maize crops can proliferate on cover crops, so preventive chemical treatments are necessary. Very little data is available on these pests on cover crops. This paper presents the dynamics of Spodoptera frugiperda, S. eridania, Mocis latipes and Diatraea saccharalis caterpillars monitored at Primavera do Leste, Mato Grosso state (Brazil) during the of 2005/2006 and 2006/2007 cropping seasons on four cover crops, i.e. finger millet (Eleusine coracana), pearl millet (Pennisetum glaucum), sorghum (Sorghum bicolor) and ruzigrass (Brachiaria ruziziensis). The pests were visually counted on plants within a 1 m2 transect (wooden frame). Caterpillars were reared to facilitate identification of collected species and parasitoids. Many S. frugiperda caterpillars were observed on millet in 2005, with a maximum of 37 caterpillars/m2. On sorghum, we found 30 caterpillars/m2, or 0.83 caterpillars/plant. The Diatraea borer attacked sorghum later than the other pests. M. latipes was also observed on millet. The millet cover crop had to be dried for at least 1 month before direct drilling the main cotton crop in order to impede S. frugiperda infestations on cotton plantlets, thus avoiding the need for substantial resowing. The comparative methodological aspects are discussed.

Assessing HYDRUS-2D model to estimate soil water contents and olive tree transpiration fluxes under different water distribution systems

NASA Astrophysics Data System (ADS)

Autovino, Dario; Negm, Amro; Rallo, Giovanni; Provenzano, Giuseppe

2016-04-01

In Mediterranean countries characterized by limited water resources for agricultural and societal sectors, irrigation management plays a major role to improve water use efficiency at farm scale, mainly where irrigation systems are correctly designed to guarantee a suitable application efficiency and the uniform water distribution throughout the field. In the last two decades, physically-based agro-hydrological models have been developed to simulate mass and energy exchange processes in the soil-plant-atmosphere (SPA) system. Mechanistic models like HYDRUS 2D/3D (Šimunek et al., 2011) have been proposed to simulate all the components of water balance, including actual crop transpiration fluxes estimated according to a soil potential-dependent sink term. Even though the suitability of these models to simulate the temporal dynamics of soil and crop water status has been reported in the literature for different horticultural crops, a few researches have been considering arboreal crops where the higher gradients of root water uptake are the combination between the localized irrigation supply and the three dimensional root system distribution. The main objective of the paper was to assess the performance of HYDRUS-2D model to evaluate soil water contents and transpiration fluxes of an olive orchard irrigated with two different water distribution systems. Experiments were carried out in Castelvetrano (Sicily) during irrigation seasons 2011 and 2012, in a commercial farm specialized in the production of table olives (Olea europaea L., var. Nocellara del Belice), representing the typical variety of the surrounding area. During the first season, irrigation water was provided by a single lateral placed along the plant row with four emitters per plant (ordinary irrigation), whereas during the second season a grid of emitters laid on the soil was installed in order to irrigate the whole soil surface around the selected trees. The model performance was assessed based on the comparison between measured and simulated soil water content and actual transpiration fluxes, under the hypothesis to neglect the contribute of the tree capacitance. Moreover, two different crop water stress functions and in particular the linear model proposed by Feddes et al. (1978) and the S-shape model suggested by van Genuchten et al. (1987), were considered. The result of the study evidenced that for the investigated crop and under the examined conditions, HYDRUS-2D model reproduces fairly well the dynamic of soil water contents at different distances from the emitters (RMSE<0.09 cm3 cm-3) and actual crop transpiration fluxes (RMSE<0.11 mm d-1), whose estimations can be slightly improved by assuming a S-shape crop water stress function. Key-words: Olive tree, HYDRUS-2D, Soil water content, Actual transpiration fluxes

Effects of meteorological droughts on agricultural water resources in southern China

NASA Astrophysics Data System (ADS)

Lu, Houquan; Wu, Yihua; Li, Yijun; Liu, Yongqiang

2017-05-01

With the global warming, frequencies of drought are rising in the humid area of southern China. In this study, the effects of meteorological drought on the agricultural water resource based on the agricultural water resource carrying capacity (AWRCC) in southern China were investigated. The entire study area was divided into three regions based on the distributions of climate and agriculture. The concept of the maximum available water resources for crops was used to calculate AWRCC. Meanwhile, an agricultural drought intensity index (ADI), which was suitable for rice planting areas, was proposed based on the difference between crop water requirements and precipitation. The actual drought area and crop yield in drought years from 1961 to 2010 were analyzed. The results showed that ADI and AWRCC were significantly correlated with the actual drought occurrence area and food yield in the study area, which indicated ADI and AWRCC could be used in drought-related studies. The effects of seasonal droughts on AWRCC strongly depended on both the crop growth season and planting structure. The influence of meteorological drought on agricultural water resources was pronounced in regions with abundant water resources, especially in Southwest China, which was the most vulnerable to droughts. In Southwest China, which has dry and wet seasons, reducing the planting area of dry season crops and rice could improve AWRCC during drought years. Likewise, reducing the planting area of double-season rice could improve AWRCC during drought years in regions with a double-season rice cropping system. Our findings highlight the importance of adjusting the proportions of crop planting to improve the utilization efficiency of agricultural water resources and alleviate drought hazards in some humid areas.

Three-Dimension Visualization for Primary Wheat Diseases Based on Simulation Model

NASA Astrophysics Data System (ADS)

Shijuan, Li; Yeping, Zhu

Crop simulation model has been becoming the core of agricultural production management and resource optimization management. Displaying crop growth process makes user observe the crop growth and development intuitionisticly. On the basis of understanding and grasping the occurrence condition, popularity season, key impact factors for main wheat diseases of stripe rust, leaf rust, stem rust, head blight and powdery mildew from research material and literature, we designed 3D visualization model for wheat growth and diseases occurrence. The model system will help farmer, technician and decision-maker to use crop growth simulation model better and provide decision-making support. Now 3D visualization model for wheat growth on the basis of simulation model has been developed, and the visualization model for primary wheat diseases is in the process of development.

Gis-Based Crop Support System For Common Oatand Naked Oat in China

NASA Astrophysics Data System (ADS)

Wan, Fan; Wang, Zhen; Li, Fengmin; Cao, Huhua; Sun, Guojun

The identification of the suitable areas for common oat (Avena sativa L.) and naked oat (Avena nuda L.) in China using Multi-Criteria Evaluation (MCE) approach based on GIS is presented in the current article. Climate, topography, soil, land use and oat variety databases were created. Relevant criteria,suitability levels and their weights for each factor were defined. Then the criteria maps were obtained and turned into the MCE process, and suitability maps for common oat and naked oat were created. The land use and the suitability maps were crossed to identify the suitable areas for each crop. The results identified 397,720 km2 of suitable areas for common oats of forage purpose distributed in 744 counties in 17 provinces, and 556,232 km2 of suitable areas for naked oats of grain purpose distributed in 779 counties in 19 provinces. This result is in accordance with the distribution of farmingpastoral ecozones located in semi-arid regions of northern China. The mapped areas can help define the working limits and serve as indicative zones for oat in China. The created databases, mapped results, interface of expert system and relevant hardware facilities could construct a complete crop support system for oats.

Population dynamics of plant nematodes in cultivated soil: length of rotation in newly cleared and old agricultural land.

PubMed

Good, J M; Murphy, W S; Brodie, B B

1973-04-01

During a 6-year study of 1-, 2-, and 3-year crop rotations, population densities of Pratylenchus brachyurus, Trichodorus christiei, and Meloidogyne incognita were significantly affected by the choice of crops but not by length of crop rotation. The density of P. brachyurus and T. christiei increased rapidly on milo (Sorghum vulgate). In addition, populations of P. brachyurus increased significantly in cropping systems that involved crotalaria (C. rnucronata), millet (Setaria italica), and sudangrass (Sorghum sudanense). Lowest numbers of P. brachyurus occurred where okra (Hibiscus esculentus) was grown or where land was fallow. The largest increase in populations of T. christiei occurred in cropping systems that involved millet, sudangrass, and okra whereas the smallest increase occurred in cropping systems that involved crotalaria or fallow. A winter cover of rye (Secale cereale) had no distinguishable effect on population densities of P. brachyurus or T. christiei. Meloidogyne incognita was detected during the fourth year in both newly cleared and old agricultural land when okra was included in the cropping system. Detectable populations of M. incognita did not develop in any of the other cropping systems. Yields of tomato transplants were higher on the newly cleared land than on the old land. Highest yields were obtained when crotalaria was included in the cropping system. Lowest yields were obtained when milo, or fallow were included in the cropping system. Length of rotation had no distinguishable effect on yields of tomato transplants.

Broomrape Weeds. Underground Mechanisms of Parasitism and Associated Strategies for their Control: A Review

PubMed Central

Fernández-Aparicio, Mónica; Reboud, Xavier; Gibot-Leclerc, Stephanie

2016-01-01

Broomrapes are plant-parasitic weeds which constitute one of the most difficult-to-control of all biotic constraints that affect crops in Mediterranean, central and eastern Europe, and Asia. Due to their physical and metabolic overlap with the crop, their underground parasitism, their achlorophyllous nature, and hardly destructible seed bank, broomrape weeds are usually not controlled by management strategies designed for non-parasitic weeds. Instead, broomrapes are in current state of intensification and spread due to lack of broomrape-specific control programs, unconscious introduction to new areas and may be decline of herbicide use and global warming to a lesser degree. We reviewed relevant facts about the biology and physiology of broomrape weeds and the major feasible control strategies. The points of vulnerability of some underground events, key for their parasitism such as crop-induced germination or haustorial development are reviewed as inhibition targets of the broomrape-crop association. Among the reviewed strategies are those aimed (1) to reduce broomrape seed bank viability, such as fumigation, herbigation, solarization and use of broomrape-specific pathogens; (2) diversion strategies to reduce the broomrape ability to timely detect the host such as those based on promotion of suicidal germination, on introduction of allelochemical interference, or on down-regulating host exudation of germination-inducing factors; (3) strategies to inhibit the capacity of the broomrape seedling to penetrate the crop and connect with the vascular system, such as biotic or abiotic inhibition of broomrape radicle growth and crop resistance to broomrape penetration either natural, genetically engineered or elicited by biotic- or abiotic-resistance-inducing agents; and (4) strategies acting once broomrape seedling has bridged its vascular system with that of the host, aimed to impede or to endure the parasitic sink such as those based on the delivery of herbicides via haustoria, use of resistant or tolerant varieties and implementation of cultural practices improving crop competitiveness. PMID:26925071

The Global Positioning System--Direction for the Future [and] GPS Technology and Agriculture.

ERIC Educational Resources Information Center

Edmondson, Paul R.; Ginsburg, Alan

1996-01-01

Edmondson introduces a satellite-based radio navigation, positioning, and timing system that can be integrated into a variety of curriculum areas. Ginsburg describes how the global positioning system brings far-reaching benefits for crop growers and the environment. (Author)

Development and characterization of transgenic dominant male sterile rice toward an outcross-based breeding system.

PubMed

Abe, Kiyomi; Oshima, Masao; Akasaka, Maiko; Konagaya, Ken-Ichi; Nanasato, Yoshihiko; Okuzaki, Ayako; Taniguchi, Yojiro; Tanaka, Junichi; Tabei, Yutaka

2018-03-01

Genomic selection is attracting attention in the field of crop breeding. To apply genomic selection effectively for autogamous (self-pollinating) crops, an efficient outcross system is desired. Since dominant male sterility is a powerful tool for easy and successive outcross of autogamous crops, we developed transgenic dominant male sterile rice ( Oryza sativa L.) using the barnase gene that is expressed by the tapetum-specific promoter BoA9 . Barnase -induced male sterile rice No. 10 (BMS10) was selected for its stable male sterility and normal growth characteristics. The BMS10 flowering habits, including heading date, flowering date, and daily flowering time of BMS10 tended to be delayed compared to wild type. When BMS10 and wild type were placed side-by-side and crossed under an open-pollinating condition, the seed-setting rate was <1.5%. When the clipping method was used to avoid the influence of late flowering habits, the seed-setting rate of BMS10 increased to a maximum of 86.4%. Although flowering synchronicity should be improved to increase the seed-setting rate, our results showed that this system can produce stable transgenic male sterility with normal female fertility in rice. The transgenic male sterile rice would promote a genomic selection-based breeding system in rice.

Effects of alternative cropping systems on globe artichoke qualitative traits.

PubMed

Spanu, Emanuela; Deligios, Paola A; Azara, Emanuela; Delogu, Giovanna; Ledda, Luigi

2018-02-01

Traditionally, globe artichoke cultivation in the Mediterranean basin is based on monoculture and on use of high amounts of nitrogen fertiliser. This raises issues regarding its compatibility with sustainable agriculture. We studied the effect of one typical conventional (CONV) and two alternative cropping systems [globe artichoke in sequence with French bean (NCV1), or in biannual rotation (NCV2) with cauliflower and with a leguminous cover crop in inter-row spaces] on yield, polyphenol and mineral content of globe artichoke heads over two consecutive growing seasons. NCV2 showed statistical differences in terms of fresh product yield with respect to the monoculture systems. In addition, the dihydroxycinnamic acids and dicaffeoylquinic acids of non-conventional samples were one-fold significantly higher than the conventional one. All the samples reported good mineral content, although NCV2 achieved a higher Fe content than conventional throughout the two seasons. After two and three dates of sampling, the CONV samples showed the highest levels of K content. In our study, an acceptable commercial yield and quality of 'Spinoso sardo' were achieved by shifting the common conventional agronomic management to more sustainable ones, by means of an accurate choice of cover crop species and rotations introduced in the systems. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

HERBICIDE SENSITIVITY OF ECHINOCHLOA CRUS-GALLI POPULATIONS: A COMPARISON BETWEEN CROPPING SYSTEMS.

PubMed

Claerhout, S; De Cauwer, B; Reheul, D

2014-01-01

Echinochloa crus-galli populations exhibit high morphological variability and their response to herbicides varies from field to field. Differential response to herbicides could reflect differences in selection pressure, caused by years of cropping system related herbicide usage. This study investigates the relation between herbicide sensitivity of Echinochloa crus-galli populations and the cropping system to which they were subjected. The herbicide sensitivity of Echinochloa crus-galli was evaluated for populations collected on 18 fields, representing three cropping systems, namely (1) a long-term organic cropping system, (2) a conventional cropping system with corn in crop rotation or (3) a conventional cropping system with long-term monoculture of corn. Each cropping system was represented by 6 E. crus-galli populations. All fields were located on sandy soils. Dose-response pot experiments were conducted in the greenhouse to assess the effectiveness of three foliar-applied corn herbicides: nicosulfuron (ALS-inhibitor), cycloxydim (ACCase-inhibitor) and topramezone (HPPD-inhibitor), and two soil-applied corn herbicides: S-metolachlor and dimethenamid-P (both VLCFA-inhibitors). Foliar-applied herbicides were tested at a quarter, half and full recommended doses. Soil-applied herbicides were tested within a dose range of 0-22.5 g a.i. ha(-1) for S-metolachlor and 0-45 g a.i. ha(-1) for dimethenamid-P. Foliar-applied herbicides were applied at the three true leaves stage. Soil-applied herbicides were treated immediately after sowing the radicle-emerged seeds. All experiments were performed twice. The foliage dry weight per pot was determined four weeks after treatment. Plant responses to herbicides were expressed as biomass reduction (%, relative to the untreated control). Sensitivity to foliar-applied herbicides varied among cropping systems. Compared to populations from monoculture corn fields, populations originating from organic fields were significantly more sensitive to cycloxydim, topramezone and nicosulfuron (resp. 5.3%, 5.9% and 12.3%). Populations from the conventional crop rotation system showed intermediate sensitivity levels. Contrary to foliar-applied herbicides, the effectiveness of soil-applied herbicides was not affected by cropping system. Integrated weed management may be necessary to preserve herbicide efficacy on the long term.

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

PubMed Central

Skovsen, Søren

2017-01-01

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kgNha. The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations. PMID:29168783

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

PubMed

Christiansen, Martin Peter; Laursen, Morten Stigaard; Jørgensen, Rasmus Nyholm; Skovsen, Søren; Gislum, René

2017-11-23

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35-0.58 m are correlated to the applied nitrogen treatments of 0-300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

Application of SAR remote sensing and crop modeling for operational rice crop monitoring in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.; Holecz, F.; Khan, N. I.; Barbieri, M.; Maunahan, A. A.; Gatti, L.; Quicho, E. D.; Pazhanivelan, S.; Campos-Taberner, M.; Collivignarelli, F.; Haro, J. G.; Intrman, A.; Phuong, D.; Boschetti, M.; Prasadini, P.; Busetto, L.; Minh, V. Q.; Tuan, V. Q.

2017-12-01

This study uses multi-temporal SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations in South and South Asian countries and assimilate the information into ORYZA Crop Growth Simulation Model (CGSM) to monitor rice yield. The study demonstrates examples of operational application of this rice monitoring system in: (1) detecting drought impact on rice planting in Central Thailand and Tamil Nadu, India, (2) mapping heat stress impact on rice yield in Andhra Pradesh, India, and (3) generating historical rice yield data for districts in Red River Delta, Vietnam.

Drivers of land use change and household determinants of sustainability in smallholder farming systems of Eastern Uganda.

PubMed

Ebanyat, Peter; de Ridder, Nico; de Jager, Andre; Delve, Robert J; Bekunda, Mateete A; Giller, Ken E

2010-07-01

Smallholder farming systems in sub-Saharan Africa have undergone changes in land use, productivity and sustainability. Understanding of the drivers that have led to changes in land use in these systems and factors that influence the systems' sustainability is useful to guide appropriate targeting of intervention strategies for improvement. We studied low input Teso farming systems in eastern Uganda from 1960 to 2001 in a place-based analysis combined with a comparative analysis of similar low input systems in southern Mali. This study showed that policy-institutional factors next to population growth have driven land use changes in the Teso systems, and that nutrient balances of farm households are useful indicators to identify their sustainability. During the period of analysis, the fraction of land under cultivation increased from 46 to 78%, and communal grazing lands nearly completely disappeared. Cropping diversified over time; cassava overtook cotton and millet in importance, and rice emerged as an alternative cash crop. Impacts of political instability, such as the collapse of cotton marketing and land management institutions, of communal labour arrangements and aggravation of cattle rustling were linked to the changes. Crop productivity in the farming systems is poor and nutrient balances differed between farm types. Balances of N, P and K were all positive for larger farms (LF) that had more cattle and derived a larger proportion of their income from off-farm activities, whereas on the medium farms (MF), small farms with cattle (SF1) and without cattle (SF2) balances were mostly negative. Sustainability of the farming system is driven by livestock, crop production, labour and access to off-farm income. Building private public partnerships around market-oriented crops can be an entry point for encouraging investment in use of external nutrient inputs to boost productivity in such African farming systems. However, intervention strategies should recognise the diversity and heterogeneity between farms to ensure efficient use of these external inputs.

Comparison of crop yield sensitivity to ozone between open-top chamber and free-air experiments.

PubMed

Feng, Zhaozhong; Uddling, Johan; Tang, Haoye; Zhu, Jianguo; Kobayashi, Kazuhiko

2018-02-02

Assessments of the impacts of ozone (O 3 ) on regional and global food production are currently based on results from experiments using open-top chambers (OTCs). However, there are concerns that these impact estimates might be biased due to the environmental artifacts imposed by this enclosure system. In this study, we collated O 3 exposure and yield data for three major crop species-wheat, rice, and soybean-for which O 3 experiments have been conducted with OTCs as well as the ecologically more realistic free-air O 3 elevation (O 3 -FACE) exposure system; both within the same cultivation region and country. For all three crops, we found that the sensitivity of crop yield to the O 3 metric AOT40 (accumulated hourly O 3 exposure above a cut-off threshold concentration of 40 ppb) significantly differed between OTC and O 3 -FACE experiments. In wheat and rice, O 3 sensitivity was higher in O 3 -FACE than OTC experiments, while the opposite was the case for soybean. In all three crops, these differences could be linked to factors influencing stomatal conductance (manipulation of water inputs, passive chamber warming, and cultivar differences in gas exchange). Our study thus highlights the importance of accounting for factors that control stomatal O 3 flux when applying experimental data to assess O 3 impacts on crops at large spatial scales. © 2018 John Wiley & Sons Ltd.

Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization

DOE PAGES

Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.; ...

2016-10-03

The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less

Bioenergy cropping systems that incorporate native grasses stimulate growth of plant-associated soil microbes in the absence of nitrogen fertilization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oates, Lawrence G.; Duncan, David S.; Sanford, Gregg R.

The choice of crops and their management can strongly influence soil microbial communities and their processes. Here, we used lipid biomarker profiling to characterize how soil microbial composition of five potential bioenergy cropping systems diverged from a common baseline five years after they were established. The cropping systems we studied included an annual system (continuous no-till corn) and four perennial crops (switchgrass, miscanthus, hybrid poplar, and restored prairie). Partial- and no-stover removal were compared for the corn system, while N-additions were compared to unfertilized plots for the perennial cropping systems. Arbuscular mycorrhizal fungi (AMF) and Gram-negative biomass was higher inmore » unfertilized perennial grass systems, especially in switchgrass and prairie. Gram-positive bacterial biomass decreased in all systems relative to baseline values in surface soils (0–10 cm), but not subsurface soils (10–25 cm). Overall microbial composition was similar between the two soil depths. Our findings demonstrate the capacity of unfertilized perennial cropping systems to recreate microbial composition found in undisturbed soil environments and indicate how strongly agroecosystem management decisions such as N addition and plant community composition can influence soil microbial assemblages.« less

Productivity and nutrient cycling in bioenergy cropping systems

NASA Astrophysics Data System (ADS)

Heggenstaller, Andrew Howard

One of the greatest obstacles confronting large-scale biomass production for energy applications is the development of cropping systems that balance the need for increased productive capacity with the maintenance of other critical ecosystem functions including nutrient cycling and retention. To address questions of productivity and nutrient dynamics in bioenergy cropping systems, we conducted two sets of field experiments during 2005-2007, investigating annual and perennial cropping systems designed to generate biomass energy feedstocks. In the first experiment we evaluated productivity and crop and soil nutrient dynamics in three prototypical bioenergy double-crop systems, and in a conventionally managed sole-crop corn system. Double-cropping systems included fall-seeded forage triticale (x Triticosecale Wittmack), succeeded by one of three summer-adapted crops: corn (Zea mays L.), sorghum-sudangrass [Sorghum bicolor (L.) Moench], or sunn hemp (Crotalaria juncea L.). Total dry matter production was greater for triticale/corn and triticale/sorghum-sudangrass compared to sole-crop corn. Functional growth analysis revealed that photosynthetic duration was more important than photosynthetic efficiency in determining biomass productivity of sole-crop corn and double-crop triticale/corn, and that greater yield in the tiritcale/corn system was the outcome of photosynthesis occurring over an extended duration. Increased growth duration in double-crop systems was also associated with reductions in potentially leachable soil nitrogen relative to sole-crop corn. However, nutrient removal in harvested biomass was also greater in the double-crop systems, indicating that over the long-term, double-cropping would mandate increased fertilizer inputs. In a second experiment we assessed the effects of N fertilization on biomass and nutrient partitioning between aboveground and belowground crop components, and on carbon storage by four perennial, warm-season grasses: big bluestem (Andropogon geradii Vitman), switchgrass (Panicum virgatum L.), indiangrass [ Sorghastrum nutans (L.) Nash], and eastern gamagrass (Tripsacum dactyloides L.). Generally, the optimum rate of fertilization for biomass yield by the grasses was 140 kg N ha-1. Nitrogen inputs also had pronounced but grass-specific effects on biomass and nutrient partitioning, and on carbon storage. For big bluestem and switchgrass, 140 kg N ha -1. maximized root biomass, favored allocation of nutrients to roots over shoots, and led to net increases in carbon storage over the study duration. In contrast, for indiangrass and eastern gamagrass, root biomass and root nutrient allocation were generally adversely affected by N fertilization and carbon storage increased only with 0 or 65 kg N ha-1. For all grasses, 220 kg N ha -1 tended to shift allocation of nutrients to shoots over roots and resulted in no net increase in carbon storage. Optimal nitrogen management strategies for perennial, warm-season grass energy crops should take into consideration the effects of N on biomass yield as well as factors such as nutrient and carbon balance that will also impact economic feasibility and environmental sustainability.

The Crop Risk Zones Monitoring System for resilience to drought in the Sahel

NASA Astrophysics Data System (ADS)

Vignaroli, Patrizio; Rocchi, Leandro; De Filippis, Tiziana; Tarchiani, Vieri; Bacci, Maurizio; Toscano, Piero; Pasqui, Massimiliano; Rapisardi, Elena

2016-04-01

Food security is still one of the major concerns that Sahelian populations have to face. In the Sahel, agriculture is primarily based on rainfed crops and it is often structurally inadequate to manage the climatic variability. The predominantly rainfed cropping system of Sahel region is dependent on season quality on a year-to-year basis, and susceptible to weather extremes of droughts and extreme temperatures. Low water-storage capacity and high dependence on rainfed agriculture leave the agriculture sector even more vulnerable to climate risks. Crop yields may suffer significantly with either a late onset or early cessation of the rainy season, as well as with a high frequency of damaging dry spells. Early rains at the beginning of the season are frequently followed by dry spells which may last a week or longer. As the amount of water stored in the soil at this time of the year is negligible, early planted crops can suffer water shortage stresses during a prolonged dry spell. Therefore, the choice of the sowing date is of fundamental importance for farmers. The ability to estimate effectively the onset of the season and potentially dangerous dry spells becomes therefore vital for planning rainfed agriculture practices aiming to minimize risks and maximize yields. In this context, advices to farmers are key drivers for prevention allowing a better adaptation of traditional crop calendar to climatic variability. In the Sahel, particularly in CILSS (Permanent Interstates Committee for Drought Control in the Sahel) countries, national Early Warning System (EWS) for food security are underpinned by Multidisciplinary Working Groups (MWGs) lead by National Meteorological Services (NMS). The EWSs are mainly based on tools and models utilizing numeric forecasts and satellite data to outlook and monitor the growing season. This approach is focused on the early identification of risks and on the production of information within the prescribed time period for decision-making. Since the '90s, analysis tools and models based on meteorological satellites data have been developed within different regional and national initiatives to allow near-real-time monitoring of the cropping season. The software was in general stand-alone applications, transferred to MWGs without continuous user support and updates. Currently MWGs in the Sahel do not have any working operational tool for drought risk identification and forecast, because such tools are by now obsolete from the IT perspective. The challenge and the objective of this work is to provide to MWGs and local end-users an open access/source Crop Risk Zones Monitoring System (CRZ-MS) supporting decision making for drought risk reduction and resilience improvement. A first prototype has been developed for Niger and Mali NMSs, based on a coherent Open Source web-based infrastructure to treat all input and output data in a interoperable, platform-independent and uniform way. The System architecture and functions are based on a agro-meteorological model, running in two different modes: 1) diagnostic mode for the drought monitoring during the agro-pastoral campaign allowing MWGs to identify agricultural drought risk areas in order to support decision making at local and national level in agricultural drought management. This early warning information also represents an input for estimating the nutritional food insecurity, for the identification of potentially vulnerable populations and assessing food crises risks by National EWSs put in place by CILSS with EU, FAO and WFP. 2) predictive mode for "advisory-support" activities to the farmers by the Agricultural Extension Services, in order to implement the most appropriate strategies for minimizing drought risk on crops (i.e. identification of the optimal period of sowing, choice of varieties based on the expected length of the growing season, adoption of suitable cultural practices for soil water management) and to build farmers resilience. To increase the accessibility of appropriate and targeted drought risk information, it is essential to move from generic information to specific advises for end-users at different decision-making levels, bridging the gap between available technology and local users' needs. Thus, advices to farmers are a fundamental component of prevention allowing a better country's preparedness to cope with weather variability.

Does grazing of cover crops impact biologically active soil C and N fractions under inversion and no tillage management

USDA-ARS?s Scientific Manuscript database

Cover crops are a key component of conservation cropping systems. They can also be a key component of integrated crop-livestock systems by offering high-quality forage during short periods between cash crops. The impact of cattle grazing on biologically active soil C and N fractions has not receiv...

CropEx Web-Based Agricultural Monitoring and Decision Support

NASA Technical Reports Server (NTRS)

Harvey. Craig; Lawhead, Joel

2011-01-01

CropEx is a Web-based agricultural Decision Support System (DSS) that monitors changes in crop health over time. It is designed to be used by a wide range of both public and private organizations, including individual producers and regional government offices with a vested interest in tracking vegetation health. The database and data management system automatically retrieve and ingest data for the area of interest. Another stores results of the processing and supports the DSS. The processing engine will allow server-side analysis of imagery with support for image sub-setting and a set of core raster operations for image classification, creation of vegetation indices, and change detection. The system includes the Web-based (CropEx) interface, data ingestion system, server-side processing engine, and a database processing engine. It contains a Web-based interface that has multi-tiered security profiles for multiple users. The interface provides the ability to identify areas of interest to specific users, user profiles, and methods of processing and data types for selected or created areas of interest. A compilation of programs is used to ingest available data into the system, classify that data, profile that data for quality, and make data available for the processing engine immediately upon the data s availability to the system (near real time). The processing engine consists of methods and algorithms used to process the data in a real-time fashion without copying, storing, or moving the raw data. The engine makes results available to the database processing engine for storage and further manipulation. The database processing engine ingests data from the image processing engine, distills those results into numerical indices, and stores each index for an area of interest. This process happens each time new data is ingested and processed for the area of interest, and upon subsequent database entries, the database processing engine qualifies each value for each area of interest and conducts a logical processing of results indicating when and where thresholds are exceeded. Reports are provided at regular, operator-determined intervals that include variances from thresholds and links to view raw data for verification, if necessary. The technology and method of development allow the code base to easily be modified for varied use in the real-time and near-real-time processing environments. In addition, the final product will be demonstrated as a means for rapid draft assessment of imagery.

Anticipating on amplifying water stress: Optimal crop production supported by anticipatory water management

NASA Astrophysics Data System (ADS)

Bartholomeus, Ruud; van den Eertwegh, Gé; Simons, Gijs

2015-04-01

Agricultural crop yields depend largely on the soil moisture conditions in the root zone. Drought but especially an excess of water in the root zone and herewith limited availability of soil oxygen reduces crop yield. With ongoing climate change, more prolonged dry periods alternate with more intensive rainfall events, which changes soil moisture dynamics. With unaltered water management practices, reduced crop yield due to both drought stress and waterlogging will increase. Therefore, both farmers and water management authorities need to be provided with opportunities to reduce risks of decreasing crop yields. In The Netherlands, agricultural production of crops represents a market exceeding 2 billion euros annually. Given the increased variability in meteorological conditions and the resulting larger variations in soil moisture contents, it is of large economic importance to provide farmers and water management authorities with tools to mitigate risks of reduced crop yield by anticipatory water management, both at field and at regional scale. We provide the development and the field application of a decision support system (DSS), which allows to optimize crop yield by timely anticipation on drought and waterlogging situations. By using this DSS, we will minimize plant water stress through automated drainage and irrigation management. In order to optimize soil moisture conditions for crop growth, the interacting processes in the soil-plant-atmosphere system need to be considered explicitly. Our study comprises both the set-up and application of the DSS on a pilot plot in The Netherlands, in order to evaluate its implementation into daily agricultural practice. The DSS focusses on anticipatory water management at the field scale, i.e. the unit scale of interest to a farmer. We combine parallel field measurements ('observe'), process-based model simulations ('predict'), and the novel Climate Adaptive Drainage (CAD) system ('adjust') to optimize soil moisture conditions. CAD is used both for controlled drainage practices and for sub-irrigation. The DSS has a core of the plot-scale SWAP model (soil-water-atmosphere-plant), extended with a process-based module for the simulation of oxygen stress for plant roots. This module involves macro-scale and micro-scale gas diffusion, as well as the plant physiological demand of oxygen, to simulate transpiration reduction due to limited oxygen availability. Continuous measurements of soil moisture content, groundwater level, and drainage level are used to calibrate the SWAP model each day. This leads to an optimal reproduction of the actual soil moisture conditions by data assimilation in the first step in the DSS process. During the next step, near-future (+10 days) soil moisture conditions and drought and oxygen stress are predicted using weather forecasts. Finally, optimal drainage levels to minimize stress are simulated, which can be established by CAD. Linkage to a grid-based hydrological simulation model (SPHY) facilitates studying the spatial dynamics of soil moisture and associated implications for management at the regional scale. Thus, by using local-scale measurements, process-based models and weather forecasts to anticipate on near-future conditions, not only field-scale water management but also regional surface water management can be optimized both in space and time.

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

Airborne and ground-based remote sensing for the estimation of evapotranspiration and yield of bean, potato, and sugar beet crops

NASA Astrophysics Data System (ADS)

Jayanthi, Harikishan

The focus of this research was two-fold: (1) extend the reflectance-based crop coefficient approach to non-grain (potato and sugar beet), and vegetable crops (bean), and (2) develop vegetation index (VI)-yield statistical models for potato and sugar beet crops using high-resolution aerial multispectral imagery. Extensive crop biophysical sampling (leaf area index and aboveground dry biomass sampling) and canopy reflectance measurements formed the backbone of developing of canopy reflectance-based crop coefficients for bean, potato, and sugar beet crops in this study. Reflectance-based crop coefficient equations were developed for the study crops cultivated in Kimberly, Idaho, and subsequently used in water availability simulations in the plant root zone during 1998 and 1999 seasons. The simulated soil water profiles were compared with independent measurements of actual soil water profiles in the crop root zone in selected fields. It is concluded that the canopy reflectance-based crop coefficient technique can be successfully extended to non-grain crops as well. While the traditional basal crop coefficients generally expect uniform growth in a region the reflectance-based crop coefficients represent the actual crop growth pattern (in less than ideal water availability conditions) in individual fields. Literature on crop canopy interactions with sunlight states that there is a definite correspondence between leaf area index progression in the season and the final yield. In case of crops like potato and sugar beet, the yield is influenced not only on how early and how quickly the crop establishes its canopy but also on how long the plant stands on the ground in a healthy state. The integrated area under the crop growth curve has shown excellent correlations with hand-dug samples of potato and sugar beet crops in this research. Soil adjusted vegetation index-yield models were developed, and validated using multispectral aerial imagery. Estimated yield images were compared with the actual yields extracted from the ground. The remote sensing-derived yields compared well with the actual yields sampled on the ground. This research has highlighted the importance of the date of spectral emergence, the need to know the duration for which the crops stand on the ground, and the need to identify critical periods of time when multispectral coverages are essential for reliable tuber yield estimation.

A management information system to study space diets

NASA Technical Reports Server (NTRS)

Kang, Sukwon; Both, A. J.; Janes, H. W. (Principal Investigator)

2002-01-01

A management information system (MIS), including a database management system (DBMS) and a decision support system (DSS), was developed to dynamically analyze the variable nutritional content of foods grown and prepared in an Advanced Life Support System (ALSS) such as required for long-duration space missions. The DBMS was designed around the known nutritional content of a list of candidate crops and their prepared foods. The DSS was designed to determine the composition of the daily crew diet based on crop and nutritional information stored in the DBMS. Each of the selected food items was assumed to be harvested from a yet-to-be designed ALSS biomass production subsystem and further prepared in accompanying food preparation subsystems. The developed DBMS allows for the analysis of the nutrient composition of a sample 20-day diet for future Advanced Life Support missions and is able to determine the required quantities of food needed to satisfy the crew's daily consumption. In addition, based on published crop growth rates, the DBMS was able to calculate the required size of the biomass production area needed to satisfy the daily food requirements for the crew. Results from this study can be used to help design future ALSS for which the integration of various subsystems (e.g., biomass production, food preparation and consumption, and waste processing) is paramount for the success of the mission.

A management information system to study space diets.

PubMed

Kang, Sukwon; Both, A J

2002-01-01

A management information system (MIS), including a database management system (DBMS) and a decision support system (DSS), was developed to dynamically analyze the variable nutritional content of foods grown and prepared in an Advanced Life Support System (ALSS) such as required for long-duration space missions. The DBMS was designed around the known nutritional content of a list of candidate crops and their prepared foods. The DSS was designed to determine the composition of the daily crew diet based on crop and nutritional information stored in the DBMS. Each of the selected food items was assumed to be harvested from a yet-to-be designed ALSS biomass production subsystem and further prepared in accompanying food preparation subsystems. The developed DBMS allows for the analysis of the nutrient composition of a sample 20-day diet for future Advanced Life Support missions and is able to determine the required quantities of food needed to satisfy the crew's daily consumption. In addition, based on published crop growth rates, the DBMS was able to calculate the required size of the biomass production area needed to satisfy the daily food requirements for the crew. Results from this study can be used to help design future ALSS for which the integration of various subsystems (e.g., biomass production, food preparation and consumption, and waste processing) is paramount for the success of the mission.

SPECTRAL data-based estimation of soil heat flux

USGS Publications Warehouse

Singh, Ramesh K.; Irmak, A.; Walter-Shea, Elizabeth; Verma, S.B.; Suyker, A.E.

2011-01-01

Numerous existing spectral-based soil heat flux (G) models have shown wide variation in performance for maize and soybean cropping systems in Nebraska, indicating the need for localized calibration and model development. The objectives of this article are to develop a semi-empirical model to estimate G from a normalized difference vegetation index (NDVI) and net radiation (Rn) for maize (Zea mays L.) and soybean (Glycine max L.) fields in the Great Plains, and present the suitability of the developed model to estimate G under similar and different soil and management conditions. Soil heat fluxes measured in both irrigated and rainfed fields in eastern and south-central Nebraska were used for model development and validation. An exponential model that uses NDVI and Rn was found to be the best to estimate G based on r2 values. The effect of geographic location, crop, and water management practices were used to develop semi-empirical models under four case studies. Each case study has the same exponential model structure but a different set of coefficients and exponents to represent the crop, soil, and management practices. Results showed that the semi-empirical models can be used effectively for G estimation for nearby fields with similar soil properties for independent years, regardless of differences in crop type, crop rotation, and irrigation practices, provided that the crop residue from the previous year is more than 4000 kg ha-1. The coefficients calibrated from particular fields can be used at nearby fields in order to capture temporal variation in G. However, there is a need for further investigation of the models to account for the interaction effects of crop rotation and irrigation. Validation at an independent site having different soil and crop management practices showed the limitation of the semi-empirical model in estimating G under different soil and environment conditions.

Whole genome sequences in pulse crops: a global community resource to expedite translational genomics and knowledge-based crop improvement.

PubMed

Bohra, Abhishek; Singh, Narendra P

2015-08-01

Unprecedented developments in legume genomics over the last decade have resulted in the acquisition of a wide range of modern genomic resources to underpin genetic improvement of grain legumes. The genome enabled insights direct investigators in various ways that primarily include unearthing novel structural variations, retrieving the lost genetic diversity, introducing novel/exotic alleles from wider gene pools, finely resolving the complex quantitative traits and so forth. To this end, ready availability of cost-efficient and high-density genotyping assays allows genome wide prediction to be increasingly recognized as the key selection criterion in crop breeding. Further, the high-dimensional measurements of agronomically significant phenotypes obtained by using new-generation screening techniques will empower reference based resequencing as well as allele mining and trait mapping methods to comprehensively associate genome diversity with the phenome scale variation. Besides stimulating the forward genetic systems, accessibility to precisely delineated genomic segments reveals novel candidates for reverse genetic techniques like targeted genome editing. The shifting paradigm in plant genomics in turn necessitates optimization of crop breeding strategies to enable the most efficient integration of advanced omics knowledge and tools. We anticipate that the crop improvement schemes will be bolstered remarkably with rational deployment of these genome-guided approaches, ultimately resulting in expanded plant breeding capacities and improved crop performance.

Sequential use of the STICS crop model and of the MACRO pesticide fate model to simulate pesticides leaching in cropping systems.

PubMed

Lammoglia, Sabine-Karen; Moeys, Julien; Barriuso, Enrique; Larsbo, Mats; Marín-Benito, Jesús-María; Justes, Eric; Alletto, Lionel; Ubertosi, Marjorie; Nicolardot, Bernard; Munier-Jolain, Nicolas; Mamy, Laure

2017-03-01

The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

Drivers of land use change and household determinants of sustainability in smallholder farming systems of Eastern Uganda

PubMed Central

de Ridder, Nico; de Jager, Andre; Delve, Robert J.; Bekunda, Mateete A.; Giller, Ken E.

2010-01-01

Smallholder farming systems in sub-Saharan Africa have undergone changes in land use, productivity and sustainability. Understanding of the drivers that have led to changes in land use in these systems and factors that influence the systems’ sustainability is useful to guide appropriate targeting of intervention strategies for improvement. We studied low input Teso farming systems in eastern Uganda from 1960 to 2001 in a place-based analysis combined with a comparative analysis of similar low input systems in southern Mali. This study showed that policy-institutional factors next to population growth have driven land use changes in the Teso systems, and that nutrient balances of farm households are useful indicators to identify their sustainability. During the period of analysis, the fraction of land under cultivation increased from 46 to 78%, and communal grazing lands nearly completely disappeared. Cropping diversified over time; cassava overtook cotton and millet in importance, and rice emerged as an alternative cash crop. Impacts of political instability, such as the collapse of cotton marketing and land management institutions, of communal labour arrangements and aggravation of cattle rustling were linked to the changes. Crop productivity in the farming systems is poor and nutrient balances differed between farm types. Balances of N, P and K were all positive for larger farms (LF) that had more cattle and derived a larger proportion of their income from off-farm activities, whereas on the medium farms (MF), small farms with cattle (SF1) and without cattle (SF2) balances were mostly negative. Sustainability of the farming system is driven by livestock, crop production, labour and access to off-farm income. Building private public partnerships around market-oriented crops can be an entry point for encouraging investment in use of external nutrient inputs to boost productivity in such African farming systems. However, intervention strategies should recognise the diversity and heterogeneity between farms to ensure efficient use of these external inputs. PMID:20628448

Crop physiology calibration in the CLM

DOE PAGES

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

2015-04-15

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Crop physiology calibration in the CLM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Estimating landscape-scale impacts of agricultural management on soil carbon using measurements and models

NASA Astrophysics Data System (ADS)

Schipanski, M.; Rosenzweig, S. T.; Robertson, A. D.; Sherrod, L. A.; Ghimire, R.; McMaster, G. S.

2017-12-01

Agriculture covers 40% of Earth's ice-free land area and has broad impacts on global biogeochemical cycles. While some agricultural management changes are small in scale or impact, others have the potential to shift biogeochemical cycles at landscape and larger scales if widely adopted. Understanding which management practices have the potential to contribute to climate change adaptation and mitigation while maintaining productivity requires scaling up estimates spatially and temporally. We used on-farm, long-term, and landscape scale datasets to estimate how crop rotations impact soil organic carbon (SOC) accumulation rates under current and future climate scenarios across the semi-arid Central and Southern Great Plains. We used a stratified, landscape-scale soil sampling approach across 96 farm fields to evaluate crop rotation intensity effects on SOC pools and pesticide inputs. Replacing traditional wheat-fallow rotations with more diverse, continuously cropped rotations increased SOC by 17% and 12% in 0-10 cm and 0-20 cm depths, respectively, and reduced herbicide use by 50%. Using USDA Cropland Data Layer, we estimated soil C accumulation and pesticide reduction potentials of shifting to more intensive rotations. We also used a 30-year cropping systems experiment to calibrate and validate the Daycent model to evaluate rotation intensify effects under future climate change scenarios. The model estimated greater SOC accumulation rates under continuously cropped rotations, but SOC stocks peaked and then declined for all cropping systems beyond 2050 under future climate scenarios. Perennial grasslands were the only system estimated to maintain SOC levels in the future. In the Southern High Plains, soil C declined despite increasing input intensity under current weather while modest gains were simulated under future climate for sorghum-based cropping systems. Our findings highlight the potential vulnerability of semi-arid regions to climate change, which will be compounded by declining groundwater levels along the western edge of the High Plains Aquifer that increase reliance on dryland farming systems. Understanding these challenges provides opportunities to develop future transition and adaptation strategies in partnership with producers, policy makers, and rural communities.

Control of cucurbit viruses.

PubMed

Lecoq, Hervé; Katis, Nikolaos

2014-01-01

More than 70 well-characterized virus species transmitted by a diversity of vectors may infect cucurbit crops worldwide. Twenty of those cause severe epidemics in major production areas, occasionally leading to complete crop failures. Cucurbit viruses' control is based on three major axes: (i) planting healthy seeds or seedlings in a clean environment, (ii) interfering with vectors activity, and (iii) using resistant cultivars. Seed disinfection and seed or seedling quality controls guarantee growers on the sanitary status of their planting material. Removal of virus or vector sources in the crop environment can significantly delay the onset of viral epidemics. Insecticide or oil application may reduce virus spread in some situations. Diverse cultural practices interfere with or prevent vector reaching the crop. Resistance can be obtained by grafting for soil-borne viruses, by cross-protection, or generally by conventional breeding or genetic engineering. The diversity of the actions that may be taken to limit virus spread in cucurbit crops and their limits will be discussed. The ultimate goal is to provide farmers with technical packages that combine these methods within an integrated disease management program and are adapted to different countries and cropping systems.

Estimating cropland NPP using national crop inventory and MODIS derived crop specific parameters

NASA Astrophysics Data System (ADS)

Bandaru, V.; West, T. O.; Ricciuto, D. M.

2011-12-01

Estimates of cropland net primary production (NPP) are needed as input for estimates of carbon flux and carbon stock changes. Cropland NPP is currently estimated using terrestrial ecosystem models, satellite remote sensing, or inventory data. All three of these methods have benefits and problems. Terrestrial ecosystem models are often better suited for prognostic estimates rather than diagnostic estimates. Satellite-based NPP estimates often underestimate productivity on intensely managed croplands and are also limited to a few broad crop categories. Inventory-based estimates are consistent with nationally collected data on crop yields, but they lack sub-county spatial resolution. Integrating these methods will allow for spatial resolution consistent with current land cover and land use, while also maintaining total biomass quantities recorded in national inventory data. The main objective of this study was to improve cropland NPP estimates by using a modification of the CASA NPP model with individual crop biophysical parameters partly derived from inventory data and MODIS 8day 250m EVI product. The study was conducted for corn and soybean crops in Iowa and Illinois for years 2006 and 2007. We used EVI as a linear function for fPAR, and used crop land cover data (56m spatial resolution) to extract individual crop EVI pixels. First, we separated mixed pixels of both corn and soybean that occur when MODIS 250m pixel contains more than one crop. Second, we substituted mixed EVI pixels with nearest pure pixel values of the same crop within 1km radius. To get more accurate photosynthetic active radiation (PAR), we applied the Mountain Climate Simulator (MTCLIM) algorithm with the use of temperature and precipitation data from the North American Land Data Assimilation System (NLDAS-2) to generate shortwave radiation data. Finally, county specific light use efficiency (LUE) values of each crop for years 2006 to 2007 were determined by application of mean county inventory NPP and EVI-derived APAR into the Monteith equation. Results indicate spatial variability in LUE values across Iowa and Illinois. Northern regions of both Iowa and Illinois have higher LUE values than southern regions. This trend is reflected in NPP estimates. Results also show that corn has higher LUE values than soybean, resulting in higher NPP for corn than for soybean. Current NPP estimates were compared with NPP estimates from MOD17A3 product and with county inventory-based NPP estimates. Results indicate that current NPP estimates closely agree with inventory-based estimates, and that current NPP estimates are higher than those of the MOD17A3 product. It was also found that when mixed pixels were substituted with nearest pure pixels, revised NPP estimates were improved showing better agreement with inventory-based estimates.

Changing Pattern of Crop Fraction in Late Blight Induced Potato Crops in Potato Bowl of West Bengal by using Multi-temporal Time Series AWiFs Data

NASA Astrophysics Data System (ADS)

Chakrabarty, Abhisek

2016-07-01

Crop fraction is the ratio of crop occupying a unit area in ground pixel, is very important for monitoring crop growth. One of the most important variables in crop growth monitoring is the fraction of available solar radiation intercepted by foliage. Late blight of potato (Solanum tuberosum), caused by the oomycete pathogen Phytophthora infestans, is considered to be the most destructive crop diseases of potato worldwide. Under favourable climatic conditions, and without intervention (i.e. fungicide sprays), the disease can destroy potato crop within few weeks. Therefore it is important to evaluate the crop fraction for monitoring the healthy and late blight affected potato crops. This study was conducted in potato bowl of West Bengal, which consists of districts of Hooghly, Howrah, Burdwan, Bankuara, and Paschim Medinipur. In this study different crop fraction estimation method like linear spectral un-mixing, Normalized difference vegetation index (NDVI) based DPM model (Zhang et al. 2013), Ratio vegetation index based DPM model, improved Pixel Dichotomy Model (Li et al. 2014) ware evaluated using multi-temporal IRS AWiFs data in two successive potato growing season of 2012-13 and 2013-14 over the study area and compared with measured crop fraction. The comparative study based on measured healthy and late blight affected potato crop fraction showed that improved Pixel Dichotomy Model maintain the high coefficient of determination (R2= 0.835) with low root mean square error (RMSE=0.21) whereas the correlation values of NDVI based DPM model and RVI based DPM model is 0.763 and 0.694 respectively. The changing pattern of crop fraction profile of late blight affected potato crop was studied in respect of healthy potato crop fraction which was extracted from the 269 GPS points of potato field. It showed that the healthy potato crop fraction profile maintained the normal phenological trend whereas the late blight affected potato crop fraction profile suddenly fallen after late blight disease affected in potato crops. Therefore, it can be concluded that based on the result of this study the improved Pixel Dichotomy Model is the most convenient method for crop fraction estimation for this region with satisfactory accuracy.

Mobile Phenotyping System Using an Aeromotively Stabilized Cable-Driven Robot

NASA Astrophysics Data System (ADS)

Newman, M. B.; Zygielbaum, A. I.

2017-12-01

Agricultural researchers are constantly attempting to generate superior agricultural crops. Whether this means creating crops with greater yield, crops that are more resilient to disease, or crops that can tolerate harsh environments with fewer failures, test plots of these experimental crops must be studied in real-world environments with minimal invasion to determine how they will perform in full-scale agricultural settings. To monitor these crops without interfering with their natural growth, a noninvasive sensor system has been implemented. This system, instituted by the College of Agricultural Sciences and Natural Resources at the University of Nebraska - Lincoln (UNL), uses a system of poles, cables, and winches to support and maneuver a sensor platform above the crops at an outdoor phenotyping site. In this work, we improve upon the UNL outdoor phenotyping system presenting the concept design for a mobile, cable-driven phenotyping system as opposed to a permanent phenotyping facility. One major challenge in large-scale, cable-driven robots is stability of the end-effector. As a result, this mobile system seeks to use a novel method of end-effector stabilization using an onboard rotor drive system, herein referred to as the Instrument Platform Aeromotive Stabilization System (IPASS). A prototype system is developed and analyzed to determine the viability of IPASS.

Modeling the cadmium balance in Australian agricultural systems in view of potential impacts on food and water quality.

PubMed

de Vries, W; McLaughlin, M J

2013-09-01

The historical build up and future cadmium (Cd) concentrations in top soils and in crops of four Australian agricultural systems are predicted with a mass balance model, focusing on the period 1900-2100. The systems include a rotation of dryland cereals, a rotation of sugarcane and peanuts/soybean, intensive dairy production and intensive horticulture. The input of Cd to soil is calculated from fertilizer application and atmospheric deposition and also examines options including biosolid and animal manure application in the sugarcane rotation and dryland cereal production systems. Cadmium output from the soil is calculated from leaching to deeper horizons and removal with the harvested crop or with livestock products. Parameter values for all Cd fluxes were based on a number of measurements on Australian soil-plant systems. In the period 1900-2000, soil Cd concentrations were predicted to increase on average between 0.21 mg kg(-1) in dryland cereals, 0.42 mg kg(-1) in intensive agriculture and 0.68 mg kg(-1) in dairy production, which are within the range of measured increases in soils in these systems. Predicted soil concentrations exceed critical soil Cd concentrations, based on food quality criteria for Cd in crops during the simulation period in clay-rich soils under dairy production and intensive horticulture. Predicted dissolved Cd concentrations in soil pore water exceed a ground water quality criterion of 2 μg l(-1) in light textured soils, except for the sugarcane rotation due to large water leaching fluxes. Results suggest that the present fertilizer Cd inputs in Australia are in excess of the long-term critical loads in heavy-textured soils for dryland cereals and that all other systems are at low risk. Calculated critical Cd/P ratios in P fertilizers vary from <50 to >1000 mg Cd kg P(-1) for the different soil, crop and environmental conditions applied. Copyright © 2013 Elsevier B.V. All rights reserved.

Relation between Ocean SST Dipoles and Downwind Continental Croplands Assessed for Early Management Using Satellite-based Photosynthesis Models

NASA Astrophysics Data System (ADS)

Kaneko, Daijiro

2015-04-01

Crop-monitoring systems with the unit of carbon-dioxide sequestration for environmental issues related to climate adaptation to global warming have been improved using satellite-based photosynthesis and meteorological conditions. Early management of crop status is desirable for grain production, stockbreeding, and bio-energy providing that the seasonal climate forecasting is sufficiently accurate. Incorrect seasonal forecasting of crop production can damage global social activities if the recognized conditions are unsatisfied. One cause of poor forecasting related to the atmospheric dynamics at the Earth surface, which reflect the energy budget through land surface, especially the oceans and atmosphere. Recognition of the relation between SST anomalies (e.g. ENSO, Atlantic Niño, Indian dipoles, and Ningaloo Niño) and crop production, as expressed precisely by photosynthesis or the sequestrated-carbon rate, is necessary to elucidate the mechanisms related to poor production. Solar radiation, surface air temperature, and water stress all directly affect grain vegetation photosynthesis. All affect stomata opening, which is related to the water balance or definition by the ratio of the Penman potential evaporation and actual transpiration. Regarding stomata, present data and reanalysis data give overestimated values of stomata opening because they are extended from wet models in forests rather than semi-arid regions commonly associated with wheat, maize, and soybean. This study applies a complementary model based on energy conservation for semi-arid zones instead of the conventional Penman-Monteith method. Partitioning of the integrated Net PSN enables precise estimation of crop yields by modifying the semi-closed stomata opening. Partitioning predicts production more accurately using the cropland distribution already classified using satellite data. Seasonal crop forecasting should include near-real-time monitoring using satellite-based process crop models to avoid social difficulties that can derive from uncertain seasonal predictions produced from long-term forecasting. Acknowledgement The author appreciates scientific discussions held with the application team of seasonal prediction at the Japan Agency for Marine-Earth Science and Technology. Key words: crop production, monitoring, forecasting, SST anomaly, remote sensing

The simulation of cropping pattern to improve the performance of irrigation network in Cau irrigation area

NASA Astrophysics Data System (ADS)

Wahyuningsih, Retno; Rintis Hadiani, RR; Sobriyah

2017-01-01

Cau irrigation area located in Madiun district, East Java Province, irrigates 1.232 Ha of land which covers Cau primary channel irrigation network, Wungu Secondary channel irrigation network, and Grape secondary channel irrigation network. The problems in Cau irrigation area are limited availability of water especially during the dry season (planting season II and III) and non-compliance to cropping patterns. The evaluation of irrigation system performance of Cau irrigation area needs to be done in order to know how far the irrigation system performance is, especially based on planting productivity aspect. The improvement of irrigation network performance through cropping pattern optimization is based on the increase of water necessity fulfillment (k factor), the realization of planting area and rice productivity. The research method of irrigation system performance is by analyzing the secondary data based on the Regulation of Ministry of Public Work and State Minister for Public Housing Number: 12/PRT/M/2015. The analysis of water necessity fulfillment (k factor) uses Public Work Plan Criteria Method. The performance level of planting productivity aspect in existing condition is 87.10%, alternative 1 is 93.90% dan alternative 2 is 96.90%. It means that the performance of the irrigation network from productivity aspect increases 6.80% for alternative 1 and 9.80% for alternative 2.

Implementation of Sentinel-2 Data in the M4Land System for the Generation of Continuous Information Products in Agriculture

NASA Astrophysics Data System (ADS)

Klug, P.; Schlenz, F.; Hank, T.; Migdall, S.; Weiß, I.; Danner, M.; Bach, H.; Mauser, W.

2016-08-01

The analysis system developed in the frame of the M4Land project (Model based, Multi-temporal, Multi scale and Multi sensorial retrieval of continuous land management information) has proven its capabilities of classifying crop type and creating products on the intensity of agricultural production using optical remote sensing data from Landsat and RapidEye. In this study, Sentinel-2 data is used for the first time together with Landsat 7 ETM+ and 8 OLI data within the M4Land analysis system to derive continuously crop type and the agricultural intensity of fields in an area north of Munich, Germany and the year 2015.

Co-existence of GM, conventional and organic crops in developing countries: Main debates and concerns.

PubMed

Azadi, Hossein; Taube, Friedhelm; Taheri, Fatemeh

2017-06-05

The co-existence approach of GM crops with conventional agriculture and organic farming as a feasible agricultural farming system has recently been placed in the center of hot debates at the EU-level and become a source of anxiety in developing countries. The main promises of this approach is to ensure "food security" and "food safety" on the one hand, and to avoid the adventitious presence of GM crops in conventional and organic farming on the other, as well as to present concerns in many debates on implementing the approach in developing countries. Here, we discuss the main debates on ("what," "why," "who," "where," "which," and "how") applying this approach in developing countries and review the main considerations and tradeoffs in this regard. The paper concludes that a peaceful co-existence between GM, conventional, and organic farming is not easy but is still possible. The goal should be to implement rules that are well-established proportionately, efficiently and cost-effectively, using crop-case, farming system-based and should be biodiversity-focused ending up with "codes of good agricultural practice" for co-existence.

Intensifying a semi-arid dryland crop rotation by replacing fallow with pea

USDA-ARS?s Scientific Manuscript database

Increasing dryland cropping system intensity in the semi-arid central Great Plains by reducing frequency of fallow can add diversity to cropping systems and decrease erosion potential. However elimination of the periodic fallow phase has been shown to reduce yields of subsequent crops in this region...

Diverse rotations and poultry litter improves soybean yield

USDA-ARS?s Scientific Manuscript database

Continuous cropping systems without rotations or cover crops are perceived as unsustainable for long-term yield and soil health. Continuous systems, defined as continually producing a crop on the same parcel of land for more than three years, is thought to reduce yields. Given that crop rotations a...

Large scale maps of cropping intensity in Asia from MODIS

NASA Astrophysics Data System (ADS)

Gray, J. M.; Friedl, M. A.; Frolking, S. E.; Ramankutty, N.; Nelson, A.

2013-12-01

Agricultural systems are geographically extensive, have profound significance to society, and also affect regional energy, carbon, and water cycles. Since most suitable lands worldwide have been cultivated, there is growing pressure to increase yields on existing agricultural lands. In tropical and sub-tropical regions, multi-cropping is widely used to increase food production, but regional-to-global information related to multi-cropping practices is poor. Such information is of critical importance to ensure sustainable food production while mitigating against negative environmental impacts associated with agriculture such as contamination and depletion of freshwater resources. Unfortunately, currently available large-area inventory statistics are inadequate because they do not capture important spatial patterns in multi-cropping, and are generally not available in a timeframe that can be used to help manage cropping systems. High temporal resolution sensors such as MODIS provide an excellent source of information for addressing this need. However, relative to studies that document agricultural extensification, systematic assessment of agricultural intensification via multi-cropping has received relatively little attention. The goal of this work is to help close this methodological and information gap by developing methods that use multi-temporal remote sensing to map multi-cropping systems in Asia. Image time series analysis is especially challenging in Asia because atmospheric conditions including clouds and aerosols lead to high frequencies of missing or low quality remote sensing observations, especially during the Asian Monsoon. The methodology that we use for this work builds upon the algorithm used to produce the MODIS Land Cover Dynamics product (MCD12Q2), but employs refined methods to segment, smooth, and gap-fill 8-day EVI time series calculated from MODIS BRDF corrected surface reflectances. Crop cycle segments are identified based on changes in slope for linear regressions estimated for local windows, and constrained by the EVI amplitude and length of crop cycles that are identified. The procedure can be used to map seasonal or long-term average cropping strategies, and to characterize changes in cropping intensity over longer time periods. The datasets produced using this method therefore provide information related to global cropping systems, and more broadly, provide important information that is required to ensure sustainable management of Earth's resources and ensure food security. To test our algorithm, we applied it to time series of MODIS EVI images over Asia from 2000-2012. Our results demonstrate the utility of multi-temporal remote sensing for characterizing multi-cropping practices in some of the most important and intensely agricultural regions in the world. To evaluate our approach, we compared results from MODIS to field-scale survey data at the pixel scale, and agricultural inventory statistics at sub-national scales. We then mapped changes in multi-cropped area in Asia from the early MODIS period (2001-2004) to present (2009-2012), and characterizes the magnitude and location of changes in cropping intensity over the last 12 years. We conclude with a discussion of the challenges, future improvements, and broader impacts of this work.

Impacts of projected mid-century temperatures on thermal regimes for select specialty and fieldcrops common to the southwestern U.S.

NASA Astrophysics Data System (ADS)

Elias, E.; Lopez-Brody, N.; Dialesandro, J.; Steele, C. M.; Rango, A.

2015-12-01

The impacts of projected temperature increases in agricultural ecosystems are complex, varyingby region, cropping system, crop growth stage and humidity. We analyze the impacts of mid-century temperature increases on crops grown in five southwestern states: Arizona, California,New Mexico, Nevada and Utah. Here we present a spatial impact assessment of commonsouthwestern specialty (grapes, almonds and tomatoes) and field (alfalfa, cotton and corn)crops. This analysis includes three main components: development of empirical temperaturethresholds for each crop, classification of predicted future climate conditions according to thesethresholds, and mapping the probable impacts of these climatic changes on each crop. We use30m spatial resolution 2012 crop distribution and seasonal minimum and maximumtemperature normals (1970 to 2000) to define the current thermal envelopes for each crop.These represent the temperature range for each season where 95% of each crop is presentlygrown. Seasonal period change analysis of mid-century temperatures changes downscaled from20 CMIP5 models (RCP8.5) estimate future temperatures. Change detection maps representareas predicted to become more or less suitable, or remain unchanged. Based upon mid-centurytemperature changes, total regional suitable area declined for all crops except cotton, whichincreased by 20%. For each crop there are locations which change to and from optimal thermalenvelope conditions. More than 80% of the acres currently growing tomatoes and almonds willshift outside the present 95% thermal range. Fewer acres currently growing alfalfa (14%) andcotton (20%) will shift outside the present 95% thermal range by midcentury. Crops outsidepresent thermal envelopes by midcentury may adapt, possibly aided by adaptation technologiessuch as misters or shade structures, to the new temperature regime or growers may elect togrow alternate crops better suited to future thermal envelopes.

The Controlled Ecological Life Support System Antarctic Analog Project: Prototype Crop Production and Water Treatment System Performance

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Flynn, Michael T.; Bates, Maynard; Schlick, Greg; Kliss, Mark (Technical Monitor)

1997-01-01

The Controlled Ecological Life Support System (CELSS) Antarctic Analog Project (CAAP), is a joint endeavor between the National Science Foundation, Office of Polar Programs (NSF-OPP) and the NASA. The fundamental objective is to develop, deploy, and operate a testbed of advanced life support technologies at the Amundsen-Scott South Pole Station that enable the objectives of both the NSF and NASA. The functions of food production, water purification, and waste treatment, recycle and reduction provided by CAAP will improve the quality of life for the South Pole inhabitants, reduce logistics dependence, enhance safety and minimize environmental impacts associated with human presence on the polar plateau. Because of the analogous technical, scientific, and mission features with Planetary missions such as a mission to Mars, CAAP provides NASA with a method for validating technologies and overall approaches to supporting humans. Prototype systems for sewage treatment, water recycle and crop production are being evaluated at Ames Research Center. The product water from sewage treatment using a Wiped-Film Rotating Disk is suitable for input to the crop production system. The crop production system has provided an enhanced level of performance compared with projected performance for plant-based life support: an approximate 50% increase in productivity per unit area, more than a 65% decrease in power for plant lighting, and more than a 75% decrease in the total power requirement to produce an equivalent mass of edible biomass.

Biomass power for rural development. Technical progress report, May 1, 1996--December 31, 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neuhauser, E.

Developing commercial energy crops for power generation by the year 2000 is the focus of the DOE/USDA sponsored Biomass Power for Rural Development project. The New York based Salix Consortium project is a multi-partner endeavor, implemented in three stages. Phase-I, Final Design and Project Development, will conclude with the preparation of construction and/or operating permits, feedstock production plans, and contracts ready for signature. Field trials of willow (Salix) have been initiated at several locations in New York (Tully, Lockport, King Ferry, La Facette, Massena, and Himrod) and co-firing tests are underway at Greenidge Station (NYSEG). Phase-II of the project willmore » focus on scale-up of willow crop acreage, construction of co-firing facilities at Dunkirk Station (NMPC), and final modifications for Greenidge Station. There will be testing of the energy crop as part of the gasification trials expected to occur at BED`s McNeill power station and potentially at one of GPU`s facilities. Phase-III will represent full-scale commercialization of the energy crop and power generation on a sustainable basis. Willow has been selected as the energy crop of choice for many reasons. Willow is well suited to the climate of the Northeastern United States, and initial field trials have demonstrated that the yields required for the success of the project are obtainable. Like other energy crops, willow has rural development benefits and could serve to diversify local crop production, provide new sources of income for participating growers, and create new jobs. Willow could be used to put a large base of idle acreage back into crop production. Additionally, the willow coppicing system integrates well with current farm operations and utilizes agricultural practices that are already familiar to farmers.« less

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops.

PubMed

Qian, Lunwen; Hickey, Lee T; Stahl, Andreas; Werner, Christian R; Hayes, Ben; Snowdon, Rod J; Voss-Fels, Kai P

2017-01-01

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Integrating sheep grazing into wheat-fallow systems: Crop yield and soil properties

USDA-ARS?s Scientific Manuscript database

The two predominant systems for weed management in summer fallow are tillage with a field cultivator or multiple applications of broad spectrum herbicides with zero tillage. Both systems are based on substantial use of off farm resources. Strategic grazing of sheep may allow grain growers to more ...

Applications of UAVs in row-crop agriculture: advantages and limitations

NASA Astrophysics Data System (ADS)

Basso, B.; Putnam, G.; Price, R.; Zhang, J.

2016-12-01

The application of Unmanned Aerial Vehicles (UAV) to monitor agricultural fields has increased over the last few years due to advances in the technology, sensors, post-processing software for image analysis, along with more favorable regulations that allowed UAVs to be flown for commercial use. UAV have several capabilities depending on the type of sensors that are mounted onboard. The most widely used application remains crop scouting to identify areas within fields where the crops underperform for various reasons (nutritional status and water stress, presence of weeds, poor stands etc). In this talk, we present the preliminary results of UAVs field based research to better understand spatial and temporal variability of crop yield. Their advantage in providing timely information is critical, but adaptive management requires a system approach to account for the interactions occurring between genetics, environment and management.

Ecological Intensification Through Pesticide Reduction: Weed Control, Weed Biodiversity and Sustainability in Arable Farming.

PubMed

Petit, Sandrine; Munier-Jolain, Nicolas; Bretagnolle, Vincent; Bockstaller, Christian; Gaba, Sabrina; Cordeau, Stéphane; Lechenet, Martin; Mézière, Delphine; Colbach, Nathalie

2015-11-01

Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.

Ecological Intensification Through Pesticide Reduction: Weed Control, Weed Biodiversity and Sustainability in Arable Farming

NASA Astrophysics Data System (ADS)

Petit, Sandrine; Munier-Jolain, Nicolas; Bretagnolle, Vincent; Bockstaller, Christian; Gaba, Sabrina; Cordeau, Stéphane; Lechenet, Martin; Mézière, Delphine; Colbach, Nathalie

2015-11-01

Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

PubMed Central

Khan, M. A.; Gemenet, Dorcus C.; Villordon, Arthur

2016-01-01

The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture (RSA), made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops (RTCs) such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive ‘green revolution.’ In the current review, we discuss RSA with special reference to RTCs, and how knowledge on genetics of RSA can be manipulated to improve their tolerance to abiotic stresses. PMID:27847508

Soil Functional Zone Management: A Vehicle for Enhancing Production and Soil Ecosystem Services in Row-Crop Agroecosystems.

PubMed

Williams, Alwyn; Kane, Daniel A; Ewing, Patrick M; Atwood, Lesley W; Jilling, Andrea; Li, Meng; Lou, Yi; Davis, Adam S; Grandy, A Stuart; Huerd, Sheri C; Hunter, Mitchell C; Koide, Roger T; Mortensen, David A; Smith, Richard G; Snapp, Sieglinde S; Spokas, Kurt A; Yannarell, Anthony C; Jordan, Nicholas R

2016-01-01

There is increasing global demand for food, bioenergy feedstocks and a wide variety of bio-based products. In response, agriculture has advanced production, but is increasingly depleting soil regulating and supporting ecosystem services. New production systems have emerged, such as no-tillage, that can enhance soil services but may limit yields. Moving forward, agricultural systems must reduce trade-offs between production and soil services. Soil functional zone management (SFZM) is a novel strategy for developing sustainable production systems that attempts to integrate the benefits of conventional, intensive agriculture, and no-tillage. SFZM creates distinct functional zones within crop row and inter-row spaces. By incorporating decimeter-scale spatial and temporal heterogeneity, SFZM attempts to foster greater soil biodiversity and integrate complementary soil processes at the sub-field level. Such integration maximizes soil services by creating zones of 'active turnover', optimized for crop growth and yield (provisioning services); and adjacent zones of 'soil building', that promote soil structure development, carbon storage, and moisture regulation (regulating and supporting services). These zones allow SFZM to secure existing agricultural productivity while avoiding or minimizing trade-offs with soil ecosystem services. Moreover, the specific properties of SFZM may enable sustainable increases in provisioning services via temporal intensification (expanding the portion of the year during which harvestable crops are grown). We present a conceptual model of 'virtuous cycles', illustrating how increases in crop yields within SFZM systems could create self-reinforcing feedback processes with desirable effects, including mitigation of trade-offs between yield maximization and soil ecosystem services. Through the creation of functionally distinct but interacting zones, SFZM may provide a vehicle for optimizing the delivery of multiple goods and services in agricultural systems, allowing sustainable temporal intensification while protecting and enhancing soil functioning.

Soil Functional Zone Management: A Vehicle for Enhancing Production and Soil Ecosystem Services in Row-Crop Agroecosystems

PubMed Central

Williams, Alwyn; Kane, Daniel A.; Ewing, Patrick M.; Atwood, Lesley W.; Jilling, Andrea; Li, Meng; Lou, Yi; Davis, Adam S.; Grandy, A. Stuart; Huerd, Sheri C.; Hunter, Mitchell C.; Koide, Roger T.; Mortensen, David A.; Smith, Richard G.; Snapp, Sieglinde S.; Spokas, Kurt A.; Yannarell, Anthony C.; Jordan, Nicholas R.

2016-01-01

There is increasing global demand for food, bioenergy feedstocks and a wide variety of bio-based products. In response, agriculture has advanced production, but is increasingly depleting soil regulating and supporting ecosystem services. New production systems have emerged, such as no-tillage, that can enhance soil services but may limit yields. Moving forward, agricultural systems must reduce trade-offs between production and soil services. Soil functional zone management (SFZM) is a novel strategy for developing sustainable production systems that attempts to integrate the benefits of conventional, intensive agriculture, and no-tillage. SFZM creates distinct functional zones within crop row and inter-row spaces. By incorporating decimeter-scale spatial and temporal heterogeneity, SFZM attempts to foster greater soil biodiversity and integrate complementary soil processes at the sub-field level. Such integration maximizes soil services by creating zones of ‘active turnover’, optimized for crop growth and yield (provisioning services); and adjacent zones of ‘soil building’, that promote soil structure development, carbon storage, and moisture regulation (regulating and supporting services). These zones allow SFZM to secure existing agricultural productivity while avoiding or minimizing trade-offs with soil ecosystem services. Moreover, the specific properties of SFZM may enable sustainable increases in provisioning services via temporal intensification (expanding the portion of the year during which harvestable crops are grown). We present a conceptual model of ‘virtuous cycles’, illustrating how increases in crop yields within SFZM systems could create self-reinforcing feedback processes with desirable effects, including mitigation of trade-offs between yield maximization and soil ecosystem services. Through the creation of functionally distinct but interacting zones, SFZM may provide a vehicle for optimizing the delivery of multiple goods and services in agricultural systems, allowing sustainable temporal intensification while protecting and enhancing soil functioning. PMID:26904043

Assessing agro-environmental performance of dairy farms in northwest Italy based on aggregated results from indicators.

PubMed

Gaudino, Stefano; Goia, Irene; Grignani, Carlo; Monaco, Stefano; Sacco, Dario

2014-07-01

Dairy farms control an important share of the agricultural area of Northern Italy. Zero grazing, large maize-cropped areas, high stocking densities, and high milk production make them intensive and prone to impact the environment. Currently, few published studies have proposed indicator sets able to describe the entire dairy farm system and their internal components. This work had four aims: i) to propose a list of agro-environmental indicators to assess dairy farms; ii) to understand which indicators classify farms best; iii) to evaluate the dairy farms based on the proposed indicator list; iv) to link farmer decisions to the consequent environmental pressures. Forty agro-environmental indicators selected for this study are described. Northern Italy dairy systems were analysed considering both farmer decision indicators (farm management) and the resulting pressure indicators that demonstrate environmental stress on the entire farming system, and its components: cropping system, livestock system, and milk production. The correlations among single indicators identified redundant indicators. Principal Components Analysis distinguished which indicators provided meaningful information about each pressure indicator group. Analysis of the communalities and the correlations among indicators identified those that best represented farm variability: Farm Gate N Balance, Greenhouse Gas Emission, and Net Energy of the farm system; Net Energy and Gross P Balance of the cropping system component; Energy Use Efficiency and Purchased Feed N Input of the livestock system component; N Eco-Efficiency of the milk production component. Farm evaluation, based on the complete list of selected indicators demonstrated organic farming resulted in uniformly high values, while farms with low milk-producing herds resulted in uniformly low values. Yet on other farms, the environmental quality varied greatly when different groups of pressure indicators were considered, which highlighted the importance of expanding environmental analysis to effects within the farm. Statistical analysis demonstrated positive correlations between all farmer decision and pressure group indicators. Consumption of mineral fertiliser and pesticide negatively influenced the cropping system. Furthermore, stocking rate was found to correlate positively with the milk production component and negatively with the farm system. This study provides baseline references for ex ante policy evaluation, and monitoring tools for analysis both in itinere and ex post environment policy implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support

NASA Technical Reports Server (NTRS)

Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.

1996-01-01

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

Earth benefits of interdisciplinary celss-related research by the NSCORT in Bioregenerative Life Support

NASA Astrophysics Data System (ADS)

Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO_2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainability of a CELSS that will enable management of diverse complex systems on Earth.

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support.

PubMed

Mitchell, C; Sherman, L; Nielsen, S; Nelson, P; Trumbo, P; Hodges, T; Hasegawa, P; Bressan, R; Ladisch, M; Auslander, D

1996-01-01

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

Remote-sensing-based rapid assessment of flood crop loss to support USDA flooding decision-making

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Yang, Z.; Hipple, J.; Shrestha, R.

2016-12-01

Floods often cause significant crop loss in the United States. Timely and objective assessment of flood-related crop loss is very important for crop monitoring and risk management in agricultural and disaster-related decision-making in USDA. Among all flood-related information, crop yield loss is particularly important. Decision on proper mitigation, relief, and monetary compensation relies on it. Currently USDA mostly relies on field surveys to obtain crop loss information and compensate farmers' loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. Recent studies have demonstrated that Earth observation (EO) data are useful in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. There are three stages of flood damage assessment, including rapid assessment, early recovery assessment, and in-depth assessment. EO-based flood assessment methods currently rely on the time-series of vegetation index to assess the yield loss. Such methods are suitable for in-depth assessment but are less suitable for rapid assessment since the after-flood vegetation index time series is not available. This presentation presents a new EO-based method for the rapid assessment of crop yield loss immediately after a flood event to support the USDA flood decision making. The method is based on the historic records of flood severity, flood duration, flood date, crop type, EO-based both before- and immediate-after-flood crop conditions, and corresponding crop yield loss. It hypotheses that a flood of same severity occurring at the same pheonological stage of a crop will cause the similar damage to the crop yield regardless the flood years. With this hypothesis, a regression-based rapid assessment algorithm can be developed by learning from historic records of flood events and corresponding crop yield loss. In this study, historic records of MODIS-based flood and vegetation products and USDA/NASS crop type and crop yield data are used to train the regression-based rapid assessment algorithm. Validation of the rapid assessment algorithm indicates it can predict the yield loss at 90% accuracy, which is accurate enough to support USDA on flood-related quick response and mitigation.

Challenges Facing Crop Production And (Some) Potential Solutions

NASA Astrophysics Data System (ADS)

Schnable, P. S.

2017-12-01

To overcome some of the myriad challenges facing sustainable crop production we are seeking to develop statistical models that will predict crop performance in diverse agronomic environments. Crop phenotypes such as yield and drought tolerance are controlled by genotype, environment (considered broadly) and their interaction (GxE). As a consequence of the next generation sequencing revolution genotyping data are now available for a wide diversity of accessions in each of the major crops. The necessary volumes of phenotypic data, however, remain limiting and our understanding of molecular basis of GxE is minimal. To address this limitation, we are collaborating with engineers to construct new sensors and robots to automatically collect large volumes of phenotypic data. Two types of high-throughput, high-resolution, field-based phenotyping systems and new sensors will be described. Some of these technologies will be introduced within the context of the Genomes to Fields Initiative. Progress towards developing predictive models will be briefly summarized. An administrative structure that fosters transdisciplinary collaborations will be briefly described.

Using dual-purpose crops in sheep-grazing systems.

PubMed

Dove, Hugh; Kirkegaard, John

2014-05-01

The utilisation of dual-purpose crops, especially wheat and canola grown for forage and grain production in sheep-grazing systems, is reviewed. When sown early and grazed in winter before stem elongation, later-maturing wheat and canola crops can be grazed with little impact on grain yield. Recent research has sought to develop crop- and grazing-management strategies for dual-purpose crops. Aspects examined have been grazing effects on crop growth, recovery and yield development along with an understanding of the grazing value of the crop fodder, its implications for animal nutrition and grazing management to maximise live-weight gain. By alleviating the winter 'feed gap', the increase in winter stocking rate afforded by grazing crops allows crop and livestock production to be increased simultaneously on the same farm. Integration of dual-purpose wheat with canola on mixed farms provides further systems advantages related to widened operational windows, weed and disease control and risk management. Dual-purpose crops are an innovation that has potential to assist in addressing the global food-security challenge. © 2013 Society of Chemical Industry.

Application of Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

NASA Astrophysics Data System (ADS)

Jayasinghe, S.; Dutta, R.; Basnayake, S. B.; Granger, S. L.; Andreadis, K. M.; Das, N.; Markert, K. N.; Cutter, P. G.; Towashiraporn, P.; Anderson, E.

2017-12-01

The Lower Mekong Region has been experiencing frequent and prolonged droughts resulting in severe damage to agricultural production leading to food insecurity and impacts on livelihoods of the farming communities. Climate variability further complicates the situation by making drought harder to forecast. The Regional Drought and Crop Yield Information System (RDCYIS), developed by SERVIR-Mekong, helps decision makers to take effective measures through monitoring, analyzing and forecasting of drought conditions and providing early warnings to farmers to make adjustments to cropping calendars. The RDCYIS is built on regionally calibrated Regional Hydrologic Extreme Assessment System (RHEAS) framework that integrates the Variable Infiltration Capacity (VIC) and Decision Support System for Agro-technology Transfer (DSSAT) models, allowing both nowcast and forecast of drought. The RHEAS allows ingestion of numerus freely available earth observation and ground observation data to generate and customize drought related indices, variables and crop yield information for better decision making. The Lower Mekong region has experienced severe drought in 2016 encompassing the region's worst drought in 90 years. This paper presents the simulation of the 2016 drought event using RDCYIS based on its hindcast and forecast capabilities. The regionally calibrated RDCYIS can help capture salient features of drought through a variety of drought indices, soil variables, energy balance variables and water balance variables. The RDCYIS is capable of assimilating soil moisture data from different satellite products and perform ensemble runs to further reduce the uncertainty of it outputs. The calibrated results have correlation coefficient around 0.73 and NSE between 0.4-0.5. Based on the acceptable results of the retrospective runs, the system has the potential to generate reliable drought monitoring and forecasting information to improve decision-makings at operational, technological and institutional level of mandated institutes of lower Mekong countries. This is turn would help countries to prepare for and respond to drought situations by taking short and long-term risk mitigation measures such as adjusting cropping calendars, rainwater harvesting, and so on.

Cytoplasmic male sterility (CMS) in hybrid breeding in field crops.

PubMed

Bohra, Abhishek; Jha, Uday C; Adhimoolam, Premkumar; Bisht, Deepak; Singh, Narendra P

2016-05-01

A comprehensive understanding of CMS/Rf system enabled by modern omics tools and technologies considerably improves our ability to harness hybrid technology for enhancing the productivity of field crops. Harnessing hybrid vigor or heterosis is a promising approach to tackle the current challenge of sustaining enhanced yield gains of field crops. In the context, cytoplasmic male sterility (CMS) owing to its heritable nature to manifest non-functional male gametophyte remains a cost-effective system to promote efficient hybrid seed production. The phenomenon of CMS stems from a complex interplay between maternally-inherited (mitochondrion) and bi-parental (nucleus) genomic elements. In recent years, attempts aimed to comprehend the sterility-inducing factors (orfs) and corresponding fertility determinants (Rf) in plants have greatly increased our access to candidate genomic segments and the cloned genes. To this end, novel insights obtained by applying state-of-the-art omics platforms have substantially enriched our understanding of cytoplasmic-nuclear communication. Concomitantly, molecular tools including DNA markers have been implicated in crop hybrid breeding in order to greatly expedite the progress. Here, we review the status of diverse sterility-inducing cytoplasms and associated Rf factors reported across different field crops along with exploring opportunities for integrating modern omics tools with CMS-based hybrid breeding.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Limited irrigation of corn-based no-till crop rotations in West Central Great Plains

USDA-ARS?s Scientific Manuscript database

Due to numerous alternatives in crop sequence and changes in crop yield and price, finding the most profitable crop rotation for an area is a continuous research challenge. The objective of this study was to evaluate 1-, 2-, 3-, and 4-yr limited irrigation corn (Zea mays L.)-based crop rotations for...

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Greenhouse gas emissions from traditional and biofuels cropping systems

USDA-ARS?s Scientific Manuscript database

Cropping systems can have a tremendous effect on the greenhouse gas emissions from soils. The objectives of this study were to compare greenhouse gas emissions from traditional (continuous corn or corn/soybean rotation) and biomass (miscanthus, sorghum, switchgrass) cropping systems. Biomass croppin...

Candidate Species Selection: Cultural and Photosynthetic Aspects

NASA Technical Reports Server (NTRS)

Mitchell, C. A.

1982-01-01

Cultural information is provided for a data base that will be used to select candidate crop species for a controlled ecological life support system (CELSS). Lists of food crops which will satisfy most nutritional requirements of humans and also fit within the scope of cultural restrictions that logically would apply to a closed, regenerating system were generated. Cultural and environmental conditions that will allow the most rapid production of edible biomass from candidate species in the shortest possible time are identified. Cultivars which are most productive in terms of edible biomass production by (CE) conditions, and which respond to the ever-closed approach to optimization realized by each shortened production cycle are selected. The experimental approach with lettuce was to grow the crop hydroponically in a growth chamber and to manipulate such variables as light level and duration, day/night temperature, and nutrient form and level in the solution culture.

[Methodology for an assessment of derived radiation levels for agrocenoses].

PubMed

Udalova, A A; Ul'ianenko, L N; Aleksakhin, R M; Geras'kin, S A; Filipas, A S

2010-01-01

Radiation protection of agrarian ecosystems should be considered as an integral part of a system for radiation protection of environment, with a special concern to agroecosystems' features. A methodology is proposed for an assessment of maximum permissible doses of radiation impact for agrocenoses based on an unified analysis of available data about effects of radiation in cultivated plants. It is considered as a component of radiation protection system for agricultural ecosystems. Critical doses and dose rates are estimated for crops under different exposure situations. It is shown that doses that could result in decreasing indexes of productivity and survival for main crops below 50% are unlikely up to 170-200 Gy and 15-17 Gy at an acute exposure of dormant seeds and vegetative plants, correspondingly. At chronic exposure, above 10% loss of productivity in crops is not expected at dose rates below 3-10 mGy/h.

A Systematic Review of Perennial Staple Crops Literature Using Topic Modeling and Bibliometric Analysis

PubMed Central

2016-01-01

Research on perennial staple crops has increased in the past ten years due to their potential to improve ecosystem services in agricultural systems. However, multiple past breeding efforts as well as research on traditional ratoon systems mean there is already a broad body of literature on perennial crops. In this review, we compare the development of research on perennial staple crops, including wheat, rice, rye, sorghum, and pigeon pea. We utilized the advanced search capabilities of Web of Science, Scopus, ScienceDirect, and Agricola to gather a library of 914 articles published from 1930 to the present. We analyzed the metadata in the entire library and in collections of literature on each crop to understand trends in research and publishing. In addition, we applied topic modeling to the article abstracts, a type of text analysis that identifies frequently co-occurring terms and latent topics. We found: 1.) Research on perennials is increasing overall, but individual crops have each seen periods of heightened interest and research activity; 2.) Specialist journals play an important role in supporting early research efforts. Research often begins within communities of specialists or breeders for the individual crop before transitioning to a more general scientific audience; 3.) Existing perennial agricultural systems and their domesticated crop material, such as ratoon rice systems, can provide a useful foundation for breeding efforts, accelerating the development of truly perennial crops and farming systems; 4.) Primary research is lacking for crops that are produced on a smaller scale globally, such as pigeon pea and sorghum, and on the ecosystem service benefits of perennial agricultural systems. PMID:27213283

Cover Crop Species and Management Influence Predatory Arthropods and Predation in an Organically Managed, Reduced-Tillage Cropping System.

PubMed

Rivers, Ariel N; Mullen, Christina A; Barbercheck, Mary E

2018-04-05

Agricultural practices affect arthropod communities and, therefore, have the potential to influence the activities of arthropods. We evaluated the effect of cover crop species and termination timing on the activity of ground-dwelling predatory arthropods in a corn-soybean-wheat rotation in transition to organic production in Pennsylvania, United States. We compared two cover crop treatments: 1) hairy vetch (Vicia villosa Roth) planted together with triticale (×Triticosecale Wittmack) after wheat harvest, and 2) cereal rye (Secale cereale Linnaeus) planted after corn harvest. We terminated the cover crops in the spring with a roller-crimper on three dates (early, middle, and late) based on cover crop phenology and standard practices for cash crop planting in our area. We characterized the ground-dwelling arthropod community using pitfall traps and assessed relative predation using sentinel assays with live greater waxworm larvae (Galleria mellonella Fabricius). The activity density of predatory arthropods was significantly higher in the hairy vetch and triticale treatments than in cereal rye treatments. Hairy vetch and triticale favored the predator groups Araneae, Opiliones, Staphylinidae, and Carabidae. Specific taxa were associated with cover crop condition (e.g., live or dead) and termination dates. Certain variables were positively or negatively associated with the relative predation on sentinel prey, depending on cover crop treatment and stage, including the presence of predatory arthropods and various habitat measurements. Our results suggest that management of a cover crop by roller-crimper at specific times in the growing season affects predator activity density and community composition. Terminating cover crops with a roller-crimper can conserve generalist predators.

Using remote sensing to calculate plant available nitrogen needed by crops on swine factory farm sprayfields in North Carolina

NASA Astrophysics Data System (ADS)

Christenson, Elizabeth; Serre, Marc

2015-10-01

North Carolina (NC) is the second largest producer of hogs in the United States with Duplin county, NC having the densest population of hogs in the world. In NC, liquid swine manure is generally stored in open-air lagoons and sprayed onto sprayfields with sprinkler systems to be used as fertilizer for crops. Swine factory farms, termed concentrated animal feeding operations (CAFOs), are regulated by the Department of Environment and Natural Resources (DENR) based on nutrient management plans (NMPs) having balanced plant available nitrogen (PAN). The estimated PAN in liquid manure being sprayed must be less than the estimated PAN needed crops during irrigation. Estimates for PAN needed by crops are dependent on crop and soil types. Objectives of this research were to develop a new, time-efficient method to identify PAN needed by crops on Duplin county sprayfields for years 2010-2014. Using remote sensing data instead of NMP data to identify PAN needed by crops allowed calendar year identification of which crops were grown on sprayfields instead of a five-year range of values. Although permitted data have more detailed crop information than remotely sensed data, identification of PAN needed by crops using remotely sensed data is more time efficient, internally consistent, easily publically accessible, and has the ability to identify annual changes in PAN on sprayfields. Once PAN needed by crops is known, remote sensing can be used to quantify PAN at other spatial scales, such as sub-watershed levels, and can be used to inform targeted water quality monitoring of swine CAFOs.

Using Nonmetric Multidimensional Scaling to Analyze Bee Visitation in East Tennessee Crops as an Indicator of Pollination Services Provided by Honey Bees (Apis mellifera L.) and Native Bees.

PubMed

Wilson, Michael E; Skinner, John A; Wszelaki, Annette L; Drummond, Frank

2016-04-01

This study investigated bee visitation on 10 agricultural crops grown on diverse small farms in Tennessee to determine the abundance of native bees and honey bees and the partitioning of visitation among crops. Summaries for each crop are used to generate mean proportions of bee visitation by categories of bees. This shows that native bee visits often occur as frequently, or in greater proportions than non-native honey bee visits. Visitation across multiple crops is then analyzed together with nonmetric multidimensional scaling to show how communities of bees that provide crop pollination change depending on the crop. Within squash and pumpkin plantings, continuous and discrete factors, such as "time of day" and "organic practices," further explain shifts in the community composition of flower visitors. Results from this study show that native bees frequently visit flowers on various crops, indicating that they are likely contributing to pollination services in addition to honey bees. Furthermore, the community of bees visiting flowers changes based on crop type, phenology, and spatial-temporal factors. Results suggest that developing pollinator conservation for farms that grow a wide variety of crops will likely require multiple conservation strategies. Farms that concentrate on a single crop may be able to tailor conservation practices toward the most important bees in their system and geographic locale. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effect of chemical and mechanical weed control on cassava yield, soil quality and erosion under cassava cropping system

NASA Astrophysics Data System (ADS)

Islami, Titiek; Wisnubroto, Erwin; Utomo, Wani

2016-04-01

Three years field experiments were conducted to study the effect of chemical and mechanical weed control on soil quality and erosion under cassava cropping system. The experiment were conducted at University Brawijaya field experimental station, Jatikerto, Malang, Indonesia. The experiments were carried out from 2011 - 2014. The treatments consist of three cropping system (cassava mono culture; cassava + maize intercropping and cassava + peanut intercropping), and two weed control method (chemical and mechanical methods). The experimental result showed that the yield of cassava first year and second year did not influenced by weed control method and cropping system. However, the third year yield of cassava was influence by weed control method and cropping system. The cassava yield planted in cassava + maize intercropping system with chemical weed control methods was only 24 t/ha, which lower compared to other treatments, even with that of the same cropping system used mechanical weed control. The highest cassava yield in third year was obtained by cassava + peanuts cropping system with mechanical weed control method. After three years experiment, the soil of cassava monoculture system with chemical weed control method possessed the lowest soil organic matter, and soil aggregate stability. During three years of cropping soil erosion in chemical weed control method, especially on cassava monoculture, was higher compared to mechanical weed control method. The soil loss from chemical control method were 40 t/ha, 44 t/ha and 54 t/ha for the first, second and third year crop. The soil loss from mechanical weed control method for the same years was: 36 t/ha, 36 t/ha and 38 t/ha. Key words: herbicide, intercropping, soil organic matter, aggregate stability.

Conservation Agriculture Improves Soil Quality, Crop Yield, and Incomes of Smallholder Farmers in North Western Ghana

PubMed Central

Naab, Jesse B.; Mahama, George Y.; Yahaya, Iddrisu; Prasad, P. V. V.

2017-01-01

Conservation agriculture (CA) practices are being widely promoted in many areas in sub-Saharan Africa to recuperate degraded soils and improve ecosystem services. This study examined the effects of three tillage practices [conventional moldboard plowing (CT), hand hoeing (MT) and no-tillage (NT)], and three cropping systems (continuous maize, soybean–maize annual rotation, and soybean/maize intercropping) on soil quality, crop productivity, and profitability in researcher and farmer managed on-farm trials from 2010 to 2013 in northwestern Ghana. In the researcher managed mother trial, the CA practices of NT, residue retention and crop rotation/intercropping maintained higher soil organic carbon, and total soil N compared to conventional tillage practices after 4 years. Soil bulk density was higher under NT than under CT soils in the researcher managed mother trails or farmers managed baby trials after 4 years. In the researcher managed mother trial, there was no significant difference between tillage systems or cropping systems in maize or soybean yields in the first three seasons. In the fourth season, crop rotation had the greatest impact on maize yields with CT maize following soybean increasing yields by 41 and 49% compared to MT and NT maize, respectively. In the farmers’ managed trials, maize yield ranged from 520 to 2700 kg ha-1 and 300 to 2000 kg ha-1 for CT and NT, respectively, reflecting differences in experience of farmers with NT. Averaged across farmers, CT cropping systems increased maize and soybean yield ranging from 23 to 39% compared with NT cropping systems. Partial budget analysis showed that the cost of producing maize or soybean is 20–29% cheaper with NT systems and gives higher returns to labor compared to CT practice. Benefit-to-cost ratios also show that NT cropping systems are more profitable than CT systems. We conclude that with time, implementation of CA practices involving NT, crop rotation, intercropping of maize and soybean along with crop residue retention presents a win–win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. The biggest challenge, however, remains with producing enough biomass and retaining same on the field. PMID:28680427

Reconciling pesticide reduction with economic and environmental sustainability in arable farming.

PubMed

Lechenet, Martin; Bretagnolle, Vincent; Bockstaller, Christian; Boissinot, François; Petit, Marie-Sophie; Petit, Sandrine; Munier-Jolain, Nicolas M

2014-01-01

Reducing pesticide use is one of the high-priority targets in the quest for a sustainable agriculture. Until now, most studies dealing with pesticide use reduction have compared a limited number of experimental prototypes. Here we assessed the sustainability of 48 arable cropping systems from two major agricultural regions of France, including conventional, integrated and organic systems, with a wide range of pesticide use intensities and management (crop rotation, soil tillage, cultivars, fertilization, etc.). We assessed cropping system sustainability using a set of economic, environmental and social indicators. We failed to detect any positive correlation between pesticide use intensity and both productivity (when organic farms were excluded) and profitability. In addition, there was no relationship between pesticide use and workload. We found that crop rotation diversity was higher in cropping systems with low pesticide use, which would support the important role of crop rotation diversity in integrated and organic strategies. In comparison to conventional systems, integrated strategies showed a decrease in the use of both pesticides and nitrogen fertilizers, they consumed less energy and were frequently more energy efficient. Integrated systems therefore appeared as the best compromise in sustainability trade-offs. Our results could be used to re-design current cropping systems, by promoting diversified crop rotations and the combination of a wide range of available techniques contributing to pest management.

Reconciling Pesticide Reduction with Economic and Environmental Sustainability in Arable Farming

PubMed Central

Lechenet, Martin; Bretagnolle, Vincent; Bockstaller, Christian; Boissinot, François; Petit, Marie-Sophie; Petit, Sandrine; Munier-Jolain, Nicolas M.

2014-01-01

Reducing pesticide use is one of the high-priority targets in the quest for a sustainable agriculture. Until now, most studies dealing with pesticide use reduction have compared a limited number of experimental prototypes. Here we assessed the sustainability of 48 arable cropping systems from two major agricultural regions of France, including conventional, integrated and organic systems, with a wide range of pesticide use intensities and management (crop rotation, soil tillage, cultivars, fertilization, etc.). We assessed cropping system sustainability using a set of economic, environmental and social indicators. We failed to detect any positive correlation between pesticide use intensity and both productivity (when organic farms were excluded) and profitability. In addition, there was no relationship between pesticide use and workload. We found that crop rotation diversity was higher in cropping systems with low pesticide use, which would support the important role of crop rotation diversity in integrated and organic strategies. In comparison to conventional systems, integrated strategies showed a decrease in the use of both pesticides and nitrogen fertilizers, they consumed less energy and were frequently more energy efficient. Integrated systems therefore appeared as the best compromise in sustainability trade-offs. Our results could be used to re-design current cropping systems, by promoting diversified crop rotations and the combination of a wide range of available techniques contributing to pest management. PMID:24887494

Crop and livestock enterprise integration: Effects of annual crops used for fall forage production on livestock productivity

USDA-ARS?s Scientific Manuscript database

Diversification of farm enterprises is important to maintain sustainable production systems. Systems that integrate crops and livestock may prove beneficial to each enterprise. Our objectives were to determine the effects of annual crops grazed in the fall and early-winter period on cow and calf gro...

Long-term impacts of cropping systems and landscape positions on grain crop production on claypan soils

USDA-ARS?s Scientific Manuscript database

Sustainable grain crop production on vulnerable claypan soils requires improved knowledge of long-term impacts of conservation cropping systems (CS) with reduced inputs. Therefore, effects of CS and landscape positions (LP) on corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum...

Advances in Agrobacterium tumefaciens-mediated genetic transformation of graminaceous crops.

PubMed

Singh, Roshan Kumar; Prasad, Manoj

2016-05-01

Steady increase in global population poses several challenges to plant science research, including demand for increased crop productivity, grain yield, nutritional quality and improved tolerance to different environmental factors. Transgene-based approaches are promising to address these challenges by transferring potential candidate genes to host organisms through different strategies. Agrobacterium-mediated gene transfer is one such strategy which is well known for enabling efficient gene transfer in both monocot and dicots. Due to its versatility, this technique underwent several advancements including development of improved in vitro plant regeneration system, co-cultivation and selection methods, and use of hyper-virulent strains of Agrobacterium tumefaciens harbouring super-binary vectors. The efficiency of this method has also been enhanced by the use of acetosyringone to induce the activity of vir genes, silver nitrate to reduce the Agrobacterium-induced necrosis and cysteine to avoid callus browning during co-cultivation. In the last two decades, extensive efforts have been invested towards achieving efficient Agrobacterium-mediated transformation in cereals. Though high-efficiency transformation systems have been developed for rice and maize, comparatively lesser progress has been reported in other graminaceous crops. In this context, the present review discusses the progress made in Agrobacterium-mediated transformation system in rice, maize, wheat, barley, sorghum, sugarcane, Brachypodium, millets, bioenergy and forage and turf grasses. In addition, it also provides an overview of the genes that have been recently transferred to these graminaceous crops using Agrobacterium, bottlenecks in this technique and future possibilities for crop improvement.

Estimation of Remote Microclimates from Weather Station Data with Applications to Landscape Architecture.

NASA Astrophysics Data System (ADS)

Brown, Robert Douglas

Several components of a system for quantitative application of climatic statistics to landscape planning and design (CLIMACS) have been developed. One component model (MICROSIM) estimated the microclimate at the top of a remote crop using physically-based models and inputs of weather station data. Temperatures at the top of unstressed, uniform crops on flat terrain within 1600 m of a recording weather station were estimated within 1.0 C 96% of the time for a corn crop and 92% of the time for a soybean crop. Crop top winds were estimated within 0.4 m/s 92% of the time for corn and 100% of the time for soybean. This is of sufficient accuracy for application in landscape planning and design models. A physically-based model (COMFA) was developed for the determination of outdoor human thermal comfort from microclimate inputs. Estimated versus measured comfort levels in a wide range of environments agreed with a correlation coefficient of r = 0.91. Using these components, the CLIMACS concept has been applied to a typical planning example. Microclimate data were generated from weather station information using MICROSIM, then input to COMFA and to a house energy consumption model called HOTCAN to derive quantitative climatic justification for design decisions.

Characteristics of nitrogen balance in open-air and greenhouse vegetable cropping systems of China.

PubMed

Ti, Chaopu; Luo, Yongxia; Yan, Xiaoyuan

2015-12-01

Nitrogen (N) loss from vegetable cropping systems has become a significant environmental issue in China. In this study, estimation of N balances in both open-air and greenhouse vegetable cropping systems in China was established. Results showed that the total N input in open-air and greenhouse vegetable cropping systems in 2010 was 5.44 and 2.60 Tg, respectively. Chemical fertilizer N input in the two cropping systems was 201 kg N ha(-1) per season (open-air) and 478 kg N ha(-1) per season (greenhouse). The N use efficiency (NUE) was 25.9 ± 13.3 and 19.7 ± 9.4% for open-air and greenhouse vegetable cropping systems, respectively, significantly lower than that of maize, wheat, and rice. Approximately 30.6% of total N input was accumulated in soils and 0.8% was lost by ammonia volatilization in greenhouse vegetable system, while N accumulation and ammonia volatilization accounted for 19.1 and 11.1%, respectively, of total N input in open-air vegetable systems.

Efficient crop type mapping based on remote sensing in the Central Valley, California

NASA Astrophysics Data System (ADS)

Zhong, Liheng

Most agricultural systems in California's Central Valley are purposely flexible and intentionally designed to meet the demands of dynamic markets. Agricultural land use is also impacted by climate change and urban development. As a result, crops change annually and semiannually, which makes estimating agricultural water use difficult, especially given the existing method by which agricultural land use is identified and mapped. A minor portion of agricultural land is surveyed annually for land-use type, and every 5 to 8 years the entire valley is completely evaluated. So far no effort has been made to effectively and efficiently identify specific crop types on an annual basis in this area. The potential of satellite imagery to map agricultural land cover and estimate water usage in the Central Valley is explored. Efforts are made to minimize the cost and reduce the time of production during the mapping process. The land use change analysis shows that a remote sensing based mapping method is the only means to map the frequent change of major crop types. The traditional maximum likelihood classification approach is first utilized to map crop types to test the classification capacity of existing algorithms. High accuracy is achieved with sufficient ground truth data for training, and crop maps of moderate quality can be timely produced to facilitate a near-real-time water use estimate. However, the large set of ground truth data required by this method results in high costs in data collection. It is difficult to reduce the cost because a trained classification algorithm is not transferable between different years or different regions. A phenology based classification (PBC) approach is developed which extracts phenological metrics from annual vegetation index profiles and identifies crop types based on these metrics using decision trees. According to the comparison with traditional maximum likelihood classification, this phenology-based approach shows great advantages when the size of the training set is limited by ground truth availability. Once developed, the classifier is able to be applied to different years and a vast area with only a few adjustments according to local agricultural and annual weather conditions. 250 m MODIS imagery is utilized as the main input to the PBC algorithm and displays promising capacity in crop identification in several counties in the Central Valley. A time series of Landsat TM/ETM+ images at a 30 m resolution is necessary in the crop mapping of counties with smaller land parcels, although the processing time is longer. Spectral characteristics are also employed to identify crops in PBC. Spectral signatures are associated with phenological stages instead of imaging dates, which highly increases the stability of the classifier performance and overcomes the problem of over-fitting. Moderate accuracies are achieved by PBC, with confusions mostly within the same crop categories. Based on a quantitative analysis, misclassification in PBC has very trivial impacts on the accuracy of agricultural water use estimate. The cost of the entire PBC procedure is controlled to a very low level, which will enable its usage in routine annual crop mapping in the Central Valley.

The Role of Crop Systems Simulation in Agriculture and Environment

USDA-ARS?s Scientific Manuscript database

Over the past 30 to 40 years, simulation of crop systems has advanced from a neophyte science with inadequate computing power into a robust and increasingly accepted science supported by improved software, languages, development tools, and computer capabilities. Crop system simulators contain mathe...

Identification of agricultural crops by computer processing of ERTS MSS data

NASA Technical Reports Server (NTRS)

Bauer, M. E.; Cipra, J. E.

1973-01-01

Quantitative evaluation of computer-processed ERTS MSS data classifications has shown that major crop species (corn and soybeans) can be accurately identified. The classifications of satellite data over a 2000 square mile area not only covered more than 100 times the area previously covered using aircraft, but also yielded improved results through the use of temporal and spatial data in addition to the spectral information. Furthermore, training sets could be extended over far larger areas than was ever possible with aircraft scanner data. And, preliminary comparisons of acreage estimates from ERTS data and ground-based systems agreed well. The results demonstrate the potential utility of this technology for obtaining crop production information.

Decision Support system- DSS- for irrigation management in greenhouses: a case study in Campania Region

NASA Astrophysics Data System (ADS)

Monaco, Eugenia; De Mascellis, Roberto; Riccardi, Maria; Basile, Angelo; D'Urso, Guido; Magliulo, Vincenzo; Tedeschi, Anna

2016-04-01

In Mediterranean Countries the proper management of water resources is important for the preservation of actual production systems. The possibility to manage water resources is possible especially in the greenhouses systems. The challenge to manage the soil in greenhouse farm can be a strategy to maintain both current production systems both soil conservation. In Campania region protected crops (greenhouses and tunnels) have a considerable economic importance both for their extension in terms of surface harvested and also for their production in terms of yields. Agricultural production in greenhouse is closely related to the micro-climatic condition but also to the physical and agronomic characteristics of the soil-crop system. The protected crops have an high level of technology compare to the other production systems, but the irrigation management is still carried out according to empirical criteria. The rational management of the production process requires an appropriate control of climatic parameters (temperature, humidity, wind) and agronomical inputs (irrigation, fertilization,). All these factors need to be monitored as well is possible, in order to identify the optimal irrigation schedule. The aim of this work is to implement a Decision Support system -DSS- for irrigation management in greenhouses focused on a smart irrigation control based on observation of the agro-climatic parameters monitored with an advanced wireless sensors network. The study is conducted in a greenhouse farm of 6 ha located in the district of Salerno were seven plots were cropped with rocket. Preliminary a study of soils proprieties was conducted in order to identify spatial variability of the soil in the farm. So undisturbed soil samples were collected to define chemical and physical proprieties; moreover soil hydraulic properties were determined for two soils profiles deemed representation of the farm. Then the wireless sensors, installed at different depth in the soils, determined volumetric water content (VWC) by measuring the dielectric constant of the soil using frequency domain technology (FDR). The data acquired real time were used to determine water balance with a physically based model Hydrus 1D. The results show how the model is able to identify the optimal irrigation schedule as function of soil proprieties and crop needs. Keywords: irrigation, DSS, rocket, water content

Relay cropping of wheat (Triticum aestivum L.) in cotton (Gossypium hirsutum L.) improves the profitability of cotton-wheat cropping system in Punjab, Pakistan.

PubMed

Sajjad, Aamer; Anjum, Shakeel Ahmad; Ahmad, Riaz; Waraich, Ejaz Ahmad

2018-01-01

Delayed sowing of wheat (Triticum aestivum L.) in cotton-based system reduces the productivity and profitability of the cotton-wheat cropping system. In this scenario, relay cropping of wheat in standing cotton might be a viable option to ensure the timely wheat sowing with simultaneous improvement in wheat yields and system profitability. This 2-year study (2012-2013 and 2013-2014) aimed to evaluate the influence of sowing dates and relay cropping combined with different management techniques of cotton sticks on the wheat yield, soil physical properties, and the profitability of the cotton-wheat system. The experiment consisted of five treatments viz. (S1) sowing of wheat at the 7th of November by conventional tillage (two disc harrows + one rotavator + two plankings) after the removal of cotton sticks, (S2) sowing of wheat at the 7th of November by conventional tillage (two disc harrows + two plankings) after the incorporation of cotton sticks in the field with a rotavator, (S3) sowing of wheat at the 7th of November as relay crop in standing cotton with broadcast method, (S4) sowing of wheat at the 15th of December by conventional tillage (two disc harrows + one rotavator + two plankings) after the removal of cotton sticks, and (S5) sowing of wheat at the 15th of December by conventional tillage (two disc harrows + two plankings) after the incorporation of cotton sticks in the field with a rotavator. The highest seed cotton yield was observed in the S5 treatment which was statistically similar with the S3 and S4 treatments; seed cotton yield in the S1 and S2 treatments has been the lowest in both years of experimentation. However, the S2 treatment produced substantially higher root length, biological yield, and grain yield of wheat than the other treatments. The lower soil bulk density at 0-10-cm depth was recorded in the S2 treatment which was statistically similar with the S5 treatment during both years of experimentation. The volumetric water contents, net benefit, and benefit-cost ratio were the highest in the S3 treatment during both years of experimentation. Thus, relay cropping of wheat in standing cotton might be a viable option to improve the soil physical environment and profitability of the cotton-wheat cropping system.

Synthetic aperture radar for a crop information system: A multipolarization and multitemporal approach

NASA Astrophysics Data System (ADS)

Ban, Yifang

Acquisition of timely information is a critical requirement for successful management of an agricultural monitoring system. Crop identification and crop-area estimation can be done fairly successfully using satellite sensors operating in the visible and near-infrared (VIR) regions of the spectrum. However, data collection can be unreliable due to problems of cloud cover at critical stages of the growing season. The all-weather capability of synthetic aperture radar (SAR) imagery acquired from satellites provides data over large areas whenever crop information is required. At the same time, SAR is sensitive to surface roughness and should be able to provide surface information such as tillage-system characteristics. With the launch of ERS-1, the first long-duration SAR system became available. The analysis of airborne multipolarization SAR data, multitemporal ERS-1 SAR data, and their combinations with VIR data, is necessary for the development of image-analysis methodologies that can be applied to RADARSAT data for extracting agricultural crop information. The overall objective of this research is to evaluate multipolarization airborne SAR data, multitemporal ERS-1 SAR data, and combinations of ERS-1 SAR and satellite VIR data for crop classification using non-conventional algorithms. The study area is situated in Norwich Township, an agricultural area in Oxford County, southern Ontario, Canada. It has been selected as one of the few representative agricultural 'supersites' across Canada at which the relationships between radar data and agriculture are being studied. The major field crops are corn, soybeans, winter wheat, oats, barley, alfalfa, hay, and pasture. Using airborne C-HH and C-HV SAR data, it was found that approaches using contextual information, texture information and per-field classification for improving agricultural crop classification proved to be effective, especially the per-field classification method. Results show that three of the four best per-field classification accuracies (\\ K=0.91) are achieved using combinations of C-HH and C-VV SAR data. This confirms the strong potential of multipolarization data for crop classification. The synergistic effects of multitemporal ERS-1 SAR and Landsat TM data are evaluated for crop classification using an artificial neural network (ANN) approach. The results show that the per-field approach using a feed-forward ANN significantly improves the overall classification accuracy of both single-date and multitemporal SAR data. Using the combination of TM3,4,5 and Aug. 5 SAR data, the best per-field ANN classification of 96.8% was achieved. It represents an 8.5% improvement over a single TM3,4,5 classification alone. Using multitemporal ERS-1 SAR data acquired during the 1992 and 1993 growing seasons, the radar backscatter characteristics of crops and their underlying soils are analyzed. The SAR temporal backscatter profiles were generated for each crop type and the earliest times of the year for differentiation of individual crop types were determined. Orbital (incidence-angle) effects were also observed on all crops. The average difference between the two orbits was about 3 dB. Thus attention should be given to the local incidence-angle effects when using ERS-1 SAR data, especially when comparing fields from different scenes or different areas within the same scene. Finally, early- and mid-season multitemporal SAR data for crop classification using sequential-masking techniques are evaluated, based on the temporal backscatter profiles. It was found that all crops studied could be identified by July 21.

The Challenge of Improving Soil Fertility in Yam Cropping Systems of West Africa

PubMed Central

Frossard, Emmanuel; Aighewi, Beatrice A.; Aké, Sévérin; Barjolle, Dominique; Baumann, Philipp; Bernet, Thomas; Dao, Daouda; Diby, Lucien N.; Floquet, Anne; Hgaza, Valérie K.; Ilboudo, Léa J.; Kiba, Delwende I.; Mongbo, Roch L.; Nacro, Hassan B.; Nicolay, Gian L.; Oka, Esther; Ouattara, Yabile F.; Pouya, Nestor; Senanayake, Ravinda L.; Six, Johan; Traoré, Orokya I.

2017-01-01

Yam (Dioscorea spp.) is a tuber crop grown for food security, income generation, and traditional medicine. This crop has a high cultural value for some of the groups growing it. Most of the production comes from West Africa where the increased demand has been covered by enlarging cultivated surfaces while the mean yield remained around 10 t tuber ha−1. In West Africa, yam is traditionally cultivated without input as the first crop after a long-term fallow as it is considered to require a high soil fertility. African soils, however, are being more and more degraded. The aims of this review were to show the importance of soil fertility for yam, discuss barriers that might limit the adoption of integrated soil fertility management (ISFM) in yam-based systems in West Africa, present the concept of innovation platforms (IPs) as a tool to foster collaboration between actors for designing innovations in yam-based systems and provide recommendations for future research. This review shows that the development of sustainable, feasible, and acceptable soil management innovations for yam requires research to be conducted in interdisciplinary teams including natural and social sciences and in a transdisciplinary manner involving relevant actors from the problem definition, to the co-design of soil management innovations, the evaluation of research results, their communication and their implementation. Finally, this research should be conducted in diverse biophysical and socio-economic settings to develop generic rules on soil/plant relationships in yam as affected by soil management and on how to adjust the innovation supply to specific contexts. PMID:29209341

Toward an automated low-cost three-dimensional crop surface monitoring system using oblique stereo imagery from consumer-grade smart cameras

NASA Astrophysics Data System (ADS)

Brocks, Sebastian; Bendig, Juliane; Bareth, Georg

2016-10-01

Crop surface models (CSMs) representing plant height above ground level are a useful tool for monitoring in-field crop growth variability and enabling precision agriculture applications. A semiautomated system for generating CSMs was implemented. It combines an Android application running on a set of smart cameras for image acquisition and transmission and a set of Python scripts automating the structure-from-motion (SfM) software package Agisoft Photoscan and ArcGIS. Only ground-control-point (GCP) marking was performed manually. This system was set up on a barley field experiment with nine different barley cultivars in the growing period of 2014. Images were acquired three times a day for a period of two months. CSMs were successfully generated for 95 out of 98 acquisitions between May 2 and June 30. The best linear regressions of the CSM-derived plot-wise averaged plant-heights compared to manual plant height measurements taken at four dates resulted in a coefficient of determination R2 of 0.87 and a root-mean-square error (RMSE) of 0.08 m, with Willmott's refined index of model performance dr equaling 0.78. In total, 103 mean plot heights were used in the regression based on the noon acquisition time. The presented system succeeded in semiautomatedly monitoring crop height on a plot scale to field scale.

My Morning Coffee: The Effect of Climate Change on the Economies of Coffee-Producing Countries

NASA Astrophysics Data System (ADS)

Shilling, K.; Brauman, K. A.

2012-12-01

Through its effect on export crops, climate change will have important effects on economic systems and government capacity in sub-Saharan Africa. We show that climate change effects on three important export crops - coffee, cocoa and cotton - will undermine large portions of the economy, not just the rural farmers who grow these crops. Our analysis is based high-resolution data on crop location, temperature, and water requirements in conjunction with new projections for temperature increases and precipitation changes in sub-Saharan Africa. Our focus on export crops is distinct from most work on the effects of climate change on agriculture, which often focuses on subsistence and food crops. We posit that substantial and important effects on the economy and political systems will come from negative impacts on cash crops, which underpin many economies in sub-Saharan Africa. For instance, 3% of cropland in Uganda (and 2% in Ethiopia) is used for coffee production and over 3.5 million households are involved in the sector; by contrast, 7% of cropland in Uganda (and 11% in Ethiopia) is used for maize, which contributes much less to the formal economy. The relationship between the value of coffee exported and government revenue illustrates the importance of coffee to political and economic stability. A drop in the export value of coffee by 10% in Uganda will drive government revenue down by 20%, and while there is uncertainty around the exact impact of climate change, it is likely that production will take a turn for the worse. We use these factors to assess reliance of select country's economy on these crops, from the farmer to the exporter; the sensitivity of the crops to variation in the climate; and the subsequent impact on government capacity. Our research illustrates how strongly the impacts of climate change are linked to economic and political structures.

Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950

PubMed Central

Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P

2015-01-01

Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Key Points Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands PMID:26709335

Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950.

PubMed

Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P

2015-06-01

Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands.

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

NASA Astrophysics Data System (ADS)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is well suited for the use of Sentinel-2's continuous and manifold data stream.

VegScape: U.S. Crop Condition Monitoring Service

NASA Astrophysics Data System (ADS)

mueller, R.; Yang, Z.; Di, L.

2013-12-01

Since 1995, the US Department of Agriculture (USDA)/National Agricultural Statistics Service (NASS) has provided qualitative biweekly vegetation condition indices to USDA policymakers and the public on a weekly basis during the growing season. Vegetation indices have proven useful for assessing crop condition and identifying the areal extent of floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. With growing emphasis on more extreme weather events and food security issues rising to the forefront of national interest, a new vegetation condition monitoring system was developed. The new vegetation condition portal named VegScape was initiated at the start of the 2013 growing season. VegScape delivers web mapping service based interactive vegetation indices. Users can use an interactive map to explore, query and disseminate current crop conditions. Vegetation indices like Normal Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and mean, median, and ratio comparisons to prior years can be constructed for analytical purposes and on-demand crop statistics. The NASA MODIS satellite with 250 meter (15 acres) resolution and thirteen years of data history provides improved spatial and temporal resolutions and delivers improved detailed timely (i.e., daily) crop specific condition and dynamics. VegScape thus provides supplemental information to support NASS' weekly crop reports. VegScape delivers an agricultural cultivated crop mask and the most recent Cropland Data Layer (CDL) product to exploit the agricultural domain and visualize prior years' planted crops. Additionally, the data can be directly exported to Google Earth for web mashups or delivered via web mapping services for uses in other applications. VegScape supports the ethos of data democracy by providing free and open access to digital geospatial data layers using open geospatial standards, thereby supporting transparent and collaborative government initiatives. NASS developed VegScape in cooperation with the Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA. VegScape Ratio to Median NDVI

Adverse weather impacts on arable cropping systems

NASA Astrophysics Data System (ADS)

Gobin, Anne

2016-04-01

Damages due to extreme or adverse weather strongly depend on crop type, crop stage, soil conditions and management. The impact is largest during the sensitive periods of the farming calendar, and requires a modelling approach to capture the interactions between the crop, its environment and the occurrence of the meteorological event. The hypothesis is that extreme and adverse weather events can be quantified and subsequently incorporated in current crop models. Since crop development is driven by thermal time and photoperiod, a regional crop model was used to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. Risk profiles and associated return levels were obtained by fitting generalized extreme value distributions to block maxima for air humidity, water balance and temperature variables. The risk profiles were subsequently confronted with yields and yield losses for the major arable crops in Belgium, notably winter wheat, winter barley, winter oilseed rape, sugar beet, potato and maize at the field (farm records) to regional scale (statistics). The average daily vapour pressure deficit (VPD) and reference evapotranspiration (ET0) during the growing season is significantly lower (p < 0.001) and has a higher variability before 1988 than after 1988. Distribution patterns of VPD and ET0 have relevant impacts on crop yields. The response to rising temperatures depends on the crop's capability to condition its microenvironment. Crops short of water close their stomata, lose their evaporative cooling potential and ultimately become susceptible to heat stress. Effects of heat stress therefore have to be combined with moisture availability such as the precipitation deficit or the soil water balance. Risks of combined heat and moisture deficit stress appear during the summer. These risks are subsequently related to crop damage. The methodology of defining meteorological risks and subsequently relating the risk to the cropping calendar will be demonstrated for major arable crops in Belgium. Physically based crop models assist in understanding the links between adverse weather events, sensitive crop stages and crop damage. Financial support was obtained from Belspo under research contract SD/RI/03A.

Water-food-energy nexus index: analysis of water-energy-food nexus of crop's production system applying the indicators approach

NASA Astrophysics Data System (ADS)

El-Gafy, Inas

2017-10-01

Analysis the water-food-energy nexus is the first step to assess the decision maker in developing and evaluating national strategies that take into account the nexus. The main objective of the current research is providing a method for the decision makers to analysis the water-food-energy nexus of the crop production system at the national level and carrying out a quantitative assessment of it. Through the proposed method, indicators considering the water and energy consumption, mass productivity, and economic productivity were suggested. Based on these indicators a water-food-energy nexus index (WFENI) was performed. The study showed that the calculated WFENI of the Egyptian summer crops have scores that range from 0.21 to 0.79. Comparing to onion (the highest scoring WFENI,i.e., the best score), rice has the lowest WFENI among the summer food crops. Analysis of the water-food-energy nexus of forty-two Egyptian crops in year 2010 was caried out (energy consumed for irrigation represent 7.4% of the total energy footprint). WFENI can be applied to developed strategies for the optimal cropping pattern that minimizing the water and energy consumption and maximizing their productivity. It can be applied as a holistic tool to evaluate the progress in the water and agricultural national strategies. Moreover, WFENI could be applied yearly to evaluate the performance of the water-food-energy nexus managmant.

Hydroponics Database and Handbook for the Advanced Life Support Test Bed

NASA Technical Reports Server (NTRS)

Nash, Allen J.

1999-01-01

During the summer 1998, I did student assistance to Dr. Daniel J. Barta, chief plant growth expert at Johnson Space Center - NASA. We established the preliminary stages of a hydroponic crop growth database for the Advanced Life Support Systems Integration Test Bed, otherwise referred to as BIO-Plex (Biological Planetary Life Support Systems Test Complex). The database summarizes information from published technical papers by plant growth experts, and it includes bibliographical, environmental and harvest information based on plant growth under varying environmental conditions. I collected 84 lettuce entries, 14 soybean, 49 sweet potato, 16 wheat, 237 white potato, and 26 mix crop entries. The list will grow with the publication of new research. This database will be integrated with a search and systems analysis computer program that will cross-reference multiple parameters to determine optimum edible yield under varying parameters. Also, we have made preliminary effort to put together a crop handbook for BIO-Plex plant growth management. It will be a collection of information obtained from experts who provided recommendations on a particular crop's growing conditions. It includes bibliographic, environmental, nutrient solution, potential yield, harvest nutritional, and propagation procedure information. This handbook will stand as the baseline growth conditions for the first set of experiments in the BIO-Plex facility.

A Method of High Throughput Monitoring Crop Physiology Using Chlorophyll Fluorescence and Multispectral Imaging.

PubMed

Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

2018-01-01

We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

Using cover crops and cropping systems for nitrogen management

USDA-ARS?s Scientific Manuscript database

The reasons for using cover crops and optimized cropping sequences to manage nitrogen (N) are to maximize economic returns, improve soil quality and productivity, and minimize losses of N that might adversely impact environmental quality. Cover crops and cropping systems’ effects on N management are...

Evaluation of Learning Group Approaches for Fostering Integrated Cropping Systems Management

ERIC Educational Resources Information Center

Blissett, Hana; Simmons, Steve; Jordan, Nicholas; Nelson, Kristen

2004-01-01

Cropping systems management requires integration of multiple forms of knowledge, practice, and learning by farmers, extension educators, and researchers. We evaluated the outcomes of participation in collaborative learning groups organized to address cropping systems and, specifically, challenges of integrated weed management. Groups were…

Cover crops effect on farm benefits and nitrate leaching: linking economic and environmental analysis

NASA Astrophysics Data System (ADS)

Gabriel, José Luis; Vanclooster, Marnik; Garrido, Alberto; Quemada, Miguel

2013-04-01

Introducing cover crops interspersed with intensively fertilized crops in rotation has the potential to reduce nitrate leaching. However, despite the evident environmental services provided and the range of agronomic benefits documented in the literature, farmers' adoption of the technique is still limited because growing CC could lead to extra costs for the farm in three different forms: direct, indirect, and opportunity costs. Environmental studies are complex, and evaluating the indicators that are representative of the environmental impact of an agricultural system is a complicated task that is conducted by specialized groups and methodologies. Multidisciplinary studies may help to develop reliable approaches that would contribute to choosing the best agricultural strategies based on linking economic and environmental benefits. This study evaluates barley (Hordeum vulgare L., cv. Vanessa), vetch (Vicia villosa L., cv. Vereda) and rapeseed (Brassica napus L., cv. Licapo) as cover crops between maize, leaving the residue in the ground or selling it for animal feeding, and compares the economic and environmental results with respect to a typical maize-fallow rotation. Nitrate leaching for different weather conditions was calculated using the mechanistic-deterministic WAVE model, using the Richards equation parameterised with a conceptual model for the soil hydraulic properties for describing the water flow in the vadose zone, combined with field observed data. The economic impact was evaluated through stochastic (Monte-Carlo) simulation models of farms' profits using probability distribution functions of maize yield and cover crop biomass developed fitted with data collected from various field trials (during more than 5 years) and probability distribution functions of maize and different cover crop forage prices fitted from statistical sources. Stochastic dominance relationships are obtained to rank the most profitable strategies from a farm financial perspective. A two-criterion comparison scheme is proposed to rank alternative strategies based on farm profit and nitrate leaching levels, taking the baseline scenario as the maize-fallow rotation. The results show that cover crops reduced nitrate leaching respect to fallow almost every year and, when cover crop biomass is sold as forage instead of keeping it in the soil, greater profit were achieved than in the baseline scenario. While the fertilizer could be lower if cover crop is sold than if it is kept in the soil, the revenue obtained from the sale of the cover crops can compensate improvement of the soil properties. The results show that cover crops would perhaps provide a double dividend of greater profit and reduced nitrate leaching in intensive irrigated cropping systems in Mediterranean regions. But, if agro-environmental services provided by leaving the barley residue in the field were to be promoted, farmer subsidies would be required to promote cover cropping. Acknowledgements: Financial support by Spain CICYT (ref. AGL 2011-24732), Comunidad de Madrid (project AGRISOST, S2009/AGR-1630), Belgium FSR 2012 (ref. SPER/DST/340-1120525) and Marie Curie actions.

Sum Insured Determination for Cereal, Citrus and Vineyards in the Spanish Agricultural Insurance System

NASA Astrophysics Data System (ADS)

Lozano, C.; Tarquis, A. M.; Gómez-Barona, J. A.

2012-04-01

In general, insurance is a form of risk management used to hedge against a contingent loss. The conventional definition is the equitable transfer of a risk of loss from one entity to another in exchange for a premium or a guaranteed and quantifiable small loss to prevent a large and possibly devastating loss being agricultural insurance a special line of property insurance. Agriculture insurance, as actually are designed in the Spanish scenario, were established in 1978. At the macroeconomic insurance studies scale, it is necessary to know a basic element for the insurance actuarial components: sum insured. When a new risk assessment has to be evaluated in the insurance framework, it is essential to determinate venture capital in the total Spanish agriculture. In this study, three different crops (cereal, citrus and vineyards) cases are showed to determinate sum insured as they are representative of the cases found in the Spanish agriculture. Crop sum insured is calculated by the product of crop surface, unit surface production and crop price insured. In the cereal case, winter as spring cereal sowing, represents the highest Spanish crop surface, above to 6 millions of hectares (ha). Meanwhile, the four citrus species (oranges, mandarins, lemons and grapefruits) occupied an extension just over 275.000 ha. On the other hand, vineyard target to wine process shows almost one million of ha in Spain. A new method has been applied to estimate crop sum insured in these three cases. Under the maximum economic impact assumption, the maximum market price has been used to insurance each species. Depending on crop and reliability of the data base available, the insured area or insured production has been used in this estimation. When for a certain crop varieties or type of varieties show different insurance prices a geometric average was used as average insurance price for that particular crop. One extreme difficult case was vineyards, where differentiate prices based on Denomination of Origin (DO), varieties and autonomous communities made this estimation more complex. The macroeconomic results obtained based on MARM (Ministerio de Agricultura, Alimentación y Medio Ambiente) prices and crop data in 2009 are showed and discussed. Acknowledgements Funding provided by CEIGRAM (Research Centre for the Management of Agricultural and Environmental Risks) is greatly appreciated.

Effect of Mixed Systems on Crop Productivity

NASA Astrophysics Data System (ADS)

Senturklu, Songul; Landblom, Douglas; Cihacek, Larry; Brevik, Eric

2017-04-01

The goals of this non-irrigated research has been to determine the effect of mixed systems integration on crop, soil, and beef cattle production in the northern Great Plains region of the United States. Over a 5-year period, growing spring wheat (HRSW-C) continuously year after year was compared to a 5-year crop rotation that included spring wheat (HRSW-R), cover crop (dual crop consisting of winter triticale/hairy vetch seeded in the fall and harvested for hay followed by a 7-species cover crop that was seeded in June after hay harvest), forage corn, field pea/barley, and sunflower. Control 5-year HRSW yield was 2690 kg/ha compared to 2757 kg/ha for HRSW grown in rotation. Available soil nitrogen (N) is often the most important limitation for crop production. Expensive fertilizer inputs were reduced in this study due to the mixed system's complementarity in which the rotation system that included beef cattle grazing sustained N availability and increased nutrient cycling, which had a positive effect on all crops grown in the rotation. Growing HRSW continuously requires less intensive management and in this research was 14.5% less profitable. Whereas, when crop management increased and complementing crops were grown in rotation to produce crops and provide feed for grazing livestock, soil nutrient cycling improved. Increased nutrient cycling increased crop rotation yields and yearling beef cattle steers that grazing annual forages in the rotation gain more body weight than similar steers grazing NGP native range. Results of this long-term research will be presented in a PICO format for participant discussion.

Comparison of Fungal Community in Black Pepper-Vanilla and Vanilla Monoculture Systems Associated with Vanilla Fusarium Wilt Disease.

PubMed

Xiong, Wu; Zhao, Qingyun; Xue, Chao; Xun, Weibing; Zhao, Jun; Wu, Huasong; Li, Rong; Shen, Qirong

2016-01-01

Long-term vanilla monocropping often results in the occurrence of vanilla Fusarium wilt disease, seriously affecting its production all over the world. In the present study, vanilla exhibited significantly less Fusarium wilt disease in the soil of a long-term continuously cropped black pepper orchard. The entire fungal communities of bulk and rhizosphere soils between the black pepper-vanilla system (i.e., vanilla cropped in the soil of a continuously cropped black pepper orchard) and vanilla monoculture system were compared through the deep pyrosequencing. The results showed that the black pepper-vanilla system revealed a significantly higher fungal diversity than the vanilla monoculture system in both bulk and rhizosphere soils. The UniFrac-weighted PCoA analysis revealed significant differences in bulk soil fungal community structures between the two cropping systems, and fungal community structures were seriously affected by the vanilla root system. In summary, the black pepper-vanilla system harbored a lower abundance of Fusarium oxysporum in the vanilla rhizosphere soil and increased the putatively plant-beneficial fungal groups such as Trichoderma and Penicillium genus, which could explain the healthy growth of vanilla in the soil of the long-term continuously cropped black pepper field. Thus, cropping vanilla in the soil of continuously cropped black pepper fields for maintaining the vanilla industry is executable and meaningful as an agro-ecological system.

Comparison of Fungal Community in Black Pepper-Vanilla and Vanilla Monoculture Systems Associated with Vanilla Fusarium Wilt Disease

PubMed Central

Xiong, Wu; Zhao, Qingyun; Xue, Chao; Xun, Weibing; Zhao, Jun; Wu, Huasong; Li, Rong; Shen, Qirong

2016-01-01

Long-term vanilla monocropping often results in the occurrence of vanilla Fusarium wilt disease, seriously affecting its production all over the world. In the present study, vanilla exhibited significantly less Fusarium wilt disease in the soil of a long-term continuously cropped black pepper orchard. The entire fungal communities of bulk and rhizosphere soils between the black pepper-vanilla system (i.e., vanilla cropped in the soil of a continuously cropped black pepper orchard) and vanilla monoculture system were compared through the deep pyrosequencing. The results showed that the black pepper-vanilla system revealed a significantly higher fungal diversity than the vanilla monoculture system in both bulk and rhizosphere soils. The UniFrac-weighted PCoA analysis revealed significant differences in bulk soil fungal community structures between the two cropping systems, and fungal community structures were seriously affected by the vanilla root system. In summary, the black pepper-vanilla system harbored a lower abundance of Fusarium oxysporum in the vanilla rhizosphere soil and increased the putatively plant-beneficial fungal groups such as Trichoderma and Penicillium genus, which could explain the healthy growth of vanilla in the soil of the long-term continuously cropped black pepper field. Thus, cropping vanilla in the soil of continuously cropped black pepper fields for maintaining the vanilla industry is executable and meaningful as an agro-ecological system. PMID:26903995

Potential for Woody Bioenergy Crops Grown on Marginal Lands in the US Midwest to Reduce Carbon Emissions

NASA Astrophysics Data System (ADS)

Sahajpal, R.; Hurtt, G. C.; Fisk, J. P.; Izaurralde, R. C.; Zhang, X.

2012-12-01

While cellulosic biofuels are widely considered to be a low carbon energy source for the future, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting US energy and food needs without exacerbating environmental harm. To assess the carbon emission reduction potential of cellulosic biofuels, we need to identify lands that are initially not storing large quantities of carbon in soil and vegetation but are capable of producing abundant biomass with limited management inputs, and accurately model forest production rates and associated input requirements. Here we present modeled results for carbon emission reduction potential and cellulosic ethanol production of woody bioenergy crops replacing existing native prairie vegetation grown on marginal lands in the US Midwest. Marginal lands are selected based on soil properties describing use limitation, and are extracted from the SSURGO (Soil Survey Geographic) database. Yield estimates for existing native prairie vegetation on marginal lands modeled using the process-based field-scale model EPIC (Environmental Policy Integrated Climate) amount to ~ 6.7±2.0 Mg ha-1. To model woody bioenergy crops, the individual-based terrestrial ecosystem model ED (Ecosystem Demography) is initialized with the soil organic carbon stocks estimated at the end of the EPIC simulation. Four woody bioenergy crops: willow, southern pine, eucalyptus and poplar are parameterized in ED. Sensitivity analysis of model parameters and drivers is conducted to explore the range of carbon emission reduction possible with variation in woody bioenergy crop types, spatial and temporal resolution. We hypothesize that growing cellulosic crops on these marginal lands can provide significant water quality, biodiversity and GHG emissions mitigation benefits, without accruing additional carbon costs from the displacement of food and feed production.

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production

PubMed Central

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-01-01

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm−2), leaf area index (RMSE = 0.67 m2·m−2), canopy chlorophyll (RMSE = 0.24 g·m−2) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm−2, 0.85 m2·m−2, 0.28 g·m−2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CIg provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system. PMID:28629159

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production.

PubMed

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-06-18

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm -2 ), leaf area index (RMSE = 0.67 m²·m -2 ), canopy chlorophyll (RMSE = 0.24 g·m -2 ) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm -2 , 0.85 m²·m -2 , 0.28 g·m -2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CI g provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system.

Cover crop biomass harvest for bioenergy: implications for crop productivity

USDA-ARS?s Scientific Manuscript database

Winter cover crops, such as rye (Secale cereale), are usually used in conservation agriculture systems in the Southeast. Typically, the cover crop is terminated two to three weeks before planting the summer crop, with the cover biomass left on the soil surface as a mulch. However, these cover crops ...

Can diversity in root architecture explain plant water use efficiency? A modeling study

PubMed Central

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-01-01

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment. PMID:26412932

Can diversity in root architecture explain plant water use efficiency? A modeling study.

PubMed

Tron, Stefania; Bodner, Gernot; Laio, Francesco; Ridolfi, Luca; Leitner, Daniel

2015-09-24

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment.

Big agronomic data validates an oxymoron: Sustainable intensification under climate change

USDA-ARS?s Scientific Manuscript database

Crop science is increasingly embracing big data to reconcile the apparent rift between intensification of food production and sustainability of a steadily stressed production base. A strategy based on long-term agroecosystem research and modeling simulation of crops, crop rotations and cropping sys...

Origins of food crops connect countries worldwide

PubMed Central

Achicanoy, Harold A.; Bjorkman, Anne D.; Navarro-Racines, Carlos; Guarino, Luigi; Flores-Palacios, Ximena; Engels, Johannes M. M.; Wiersema, John H.; Dempewolf, Hannes; Sotelo, Steven; Ramírez-Villegas, Julian; Castañeda-Álvarez, Nora P.; Fowler, Cary; Jarvis, Andy; Rieseberg, Loren H.; Struik, Paul C.

2016-01-01

Research into the origins of food plants has led to the recognition that specific geographical regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not been quantified. Here we determine the origins (‘primary regions of diversity’) of the crops comprising the food supplies and agricultural production of countries worldwide. We estimate the degree to which countries use crops from regions of diversity other than their own (‘foreign crops’), and quantify changes in this usage over the past 50 years. Countries are highly interconnected with regard to primary regions of diversity of the crops they cultivate and/or consume. Foreign crops are extensively used in food supplies (68.7% of national food supplies as a global mean are derived from foreign crops) and production systems (69.3% of crops grown are foreign). Foreign crop usage has increased significantly over the past 50 years, including in countries with high indigenous crop diversity. The results provide a novel perspective on the ongoing globalization of food systems worldwide, and bolster evidence for the importance of international collaboration on genetic resource conservation and exchange.

Soil profile organic carbon as affected by tillage and cropping systems

USDA-ARS?s Scientific Manuscript database

Reports on the long-term effects of tillage and cropping systems on soil organic carbon (SOC) sequestration in the entire rooting profile are limited. A long-term experiment with three cropping systems [continuous corn (CC), continuous soybean (CSB), and soybean-corn (SB-C)] in six primary tillage s...

Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.

PubMed

Li, Jing; Wang, Jing; Li, Jing

2017-12-01

As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .

Agricultural pesticide emissions associated with common crops in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benjey, W.G.

Annual emissions for the year 1987 from the application of agricultural pesticides have been estimated by crop type by county for the United States using a geographic information system. The emissions estimates are based upon computed volatilization rates accounting for the properties of each pesticide, evaporation rates, mode of application (surface or soil incorporation) and percent of interception by leaves. Key pesticide properties include the Henry's Law constant, half-life in soil and the organic carbon partitioning coefficient. The volatilization rates are multiplied by the amount of pesticide applied by crop acreage in each county as determined from agricultural census andmore » pesticide sales data. The geographic distribution of the dominant emissions, such as atrazine and diazinon, etc. are presented by crop type and state. For a given pesticide, the geographic variability is controlled principally by amount applied and water availability as reflected in evaporation rates.« less

Mind the Roots: Phenotyping Below-Ground Crop Diversity and Its Influence on Final Yield

NASA Astrophysics Data System (ADS)

Nieters, C.; Guadagno, C. R.; Lemli, S.; Hosseini, A.; Ewers, B. E.

2017-12-01

Changes in global climate patterns and water regimes are having profound impacts on worldwide crop production. An ever-growing population paired with increasing temperatures and unpredictable periods of severe drought call for accurate modeling of future crop yield. Although novel approaches are being developed in high-throughput, above-ground image phenotyping, the below-ground plant system is still poorly phenotyped. Collection of plant root morphology and hydraulics are needed to inform mathematical models to reliably estimate yields of crops grown in sub-optimal conditions. We used Brassica rapa to inform our model as it is a globally cultivated crop with several functionally diverse cultivars. Specifically, we use 7 different accessions from oilseed (R500 and Yellow Sarson), leafy type (Pac choi and Chinese cabbage), a vegetable turnip, and two Wisconsin Fast Plants (Imb211 and Fast Plant self-compatible), which have shorter life cycles and potentially large differences in allocation to roots. Bi-weekly, we harvested above and below-ground biomass to compare the varieties in terms of carbon allocation throughout their life cycle. Using WinRhizo software, we analyzed root system length and surface area to compare and contrast root morphology among cultivars. Our results confirm that root structural characteristics are crucial to explain plant water use and carbon allocation. The root:shoot ratio reveals a significant (p < 0.01) difference among crop accession. To validate the procedure across different varieties and life stages we also compared surface area results from the image-based technology to dry biomass finding a strong linear relationship (R2= 0.85). To assess the influence of a diverse above-ground morphology on the root system we also measured above-ground anatomical and physiological traits such as gas exchange, chlorophyll content, and chlorophyll a fluorescence. A thorough analysis of the root system will clarify carbon dynamics and hydraulics at the whole-plant level, improving final yield predictions.

New Microwave-Based Missions Applications for Rainfed Crops Characterization

NASA Astrophysics Data System (ADS)

Sánchez, N.; Lopez-Sanchez, J. M.; Arias-Pérez, B.; Valcarce-Diñeiro, R.; Martínez-Fernández, J.; Calvo-Heras, J. M.; Camps, A.; González-Zamora, A.; Vicente-Guijalba, F.

2016-06-01

A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.

Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado

USGS Publications Warehouse

Carrollo, Emily M.; Johnson, Heather E.; Fischer, Justin W.; Hammond, Matthew; Dorsey, Patricia D.; Anderson, Charles; Vercauteren, Kurt C.; Walter, W. David

2017-01-01

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Volatile Organic Compound Emissions by Agricultural Crops

NASA Astrophysics Data System (ADS)

Ormeno, E.; Farres, S.; Gentner, D.; Park, J.; McKay, M.; Karlik, J.; Goldstein, A.

2008-12-01

Biogenic Volatile Organic Compounds (BVOCs) participate in ozone and aerosol formation, and comprise a substantial fraction of reactive VOC emission inventories. In the agriculturally intensive Central Valley of California, emissions from crops may substantially influence regional air quality, but emission potentials have not been extensively studied with advanced instrumentation for many important crops. Because crop emissions may vary according to the species, and California emission inventories are constructed via a bottom-up approach, a better knowledge of the emission rate at the species-specific level is critical for reducing uncertainties in emission inventories and evaluating emission model performance. In the present study we identified and quantified the BVOCs released by dominant agricultural crops in California. A screening study to investigate both volatile and semivolatile BVOC fractions (oxygenated VOCs, isoprene, monoterepenes, sesquiterpenes, etc.) was performed for 25 crop species (at least 3 replicates plants each), including branch enclosures of woody species (e.g. peach, mandarin, grape, pistachio) and whole plant enclosures for herbaceous species (e.g. onion, alfalfa, carrot), through a dynamic cuvette system with detection by PTRMS, in-situ GCMS/FID, and collection on carbon-based adsorbents followed by extraction and GCMS analysis. Emission data obtained in this study will allow inclusion of these crops in BVOC emission inventories and air quality simulations.