Crop Damage by Primates: Quantifying the Key Parameters of Crop-Raiding Events

PubMed Central

Wallace, Graham E.; Hill, Catherine M.

2012-01-01

Human-wildlife conflict often arises from crop-raiding, and insights regarding which aspects of raiding events determine crop loss are essential when developing and evaluating deterrents. However, because accounts of crop-raiding behaviour are frequently indirect, these parameters are rarely quantified or explicitly linked to crop damage. Using systematic observations of the behaviour of non-human primates on farms in western Uganda, this research identifies number of individuals raiding and duration of raid as the primary parameters determining crop loss. Secondary factors include distance travelled onto farm, age composition of the raiding group, and whether raids are in series. Regression models accounted for greater proportions of variation in crop loss when increasingly crop and species specific. Parameter values varied across primate species, probably reflecting differences in raiding tactics or perceptions of risk, and thereby providing indices of how comfortable primates are on-farm. Median raiding-group sizes were markedly smaller than the typical sizes of social groups. The research suggests that key parameters of raiding events can be used to measure the behavioural impacts of deterrents to raiding. Furthermore, farmers will benefit most from methods that discourage raiding by multiple individuals, reduce the size of raiding groups, or decrease the amount of time primates are on-farm. This study demonstrates the importance of directly relating crop loss to the parameters of raiding events, using systematic observations of the behaviour of multiple primate species. PMID:23056378

Vulnerability of field crops to midcentury temperature changes and yield effects in the Southwestern USA

USDA-ARS?s Scientific Manuscript database

Increased temperatures in the Southwestern United States will impact future crop production via multiple pathways. We used four methods to provide an illustrative analysis of midcentury temperature impacts to eight field crops. By midcentury, cropland area thermally suitable for maize cultivation is...

Detecting and correcting logically inconsistent crop rotations and other land-use sequences

USDA-ARS?s Scientific Manuscript database

Multi-year landuse data of adequate duration and quality has the potential to identify crop rotation history on individual fields. In the diverse landscape of western Oregon where many crops are established perennials whose stands can remain in production for multiple years, our interests included m...

Establishment trial of an oak-pine/soybean-corn-wheat alley-cropping system in the upper coastal plain of North Carolina

Treesearch

H.D. Stevenson; D.J. Robison; F.W. Cubbage; J.P. Mueller; M.G. Burton; M.H. Gocke

2013-01-01

Alley cropping may prove useful in the Southeast United States, providing multiple products and income streams, as well as affording sustainable land use alternatives to conventional farming. An alley-cropping system may be a good alternative in agriculture because of the benefits provided by trees to crops and soils, as well as the income generated from wood products...

Increasing crop diversity mitigates weather variations and improves yield stability.

PubMed

Gaudin, Amélie C M; Tolhurst, Tor N; Ker, Alan P; Janovicek, Ken; Tortora, Cristina; Martin, Ralph C; Deen, William

2015-01-01

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments.

Chemistry and microbial functional diversity differences in biofuel crop and grassland soils in multiple geographies

USDA-ARS?s Scientific Manuscript database

As crop and non-crop lands are increasingly becoming converted to biofuel feedstock production, it is of interest to identify potential impacts of annual and perennial feedstocks on soil ecosystem services. Soil samples obtained from 6 regional sets of switchgrass (Panicum virgatum L.) and 3 regiona...

The 4Rs for cover crops and other advances in cover crop management for environmental quality

USDA-ARS?s Scientific Manuscript database

Cover crops (CC) are universal tools that can be used to improve management practices to draw multiple benefits with increased sustainability across different continents (Dabney et al. 2001; Reeves 1994; Woodruff and Siddoway 1965; Frye et al. 1985; Holderbaum et al. 1990; Bilbro 1991; Langdale et a...

Integrating winter camelina into maize and soybean cropping systems

USDA-ARS?s Scientific Manuscript database

Camelina [Camelina sativa (L.) Crantz.] is an industrial oilseed crop in the Brassicaceae family with multiple uses. Currently, camelina is not used as a cover crop, but it has the potential to be used as such in maize (Zea mays L.)-soybean [Glycine max (L.) Merr.] systems. The objectives of this st...

Changes of crop rotation in Iowa determined from the USDA-NASS cropland data layer product

USDA-ARS?s Scientific Manuscript database

Crop rotation is one of the important decisions made independently by numerous farm managers, and is a critical variable in models of crop growth and soil carbon. By combining multiple years (2001-2009) of the USDA National Agricultural Statistics Service (NASS) cropland data layer (CDL), it is pos...

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.

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

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

Modeling the long-term effect of winter cover crops on nitrate transport in artificially drained fields across the Midwest U.S.

USDA-ARS?s Scientific Manuscript database

A fall-planted cover crop is a management practice with multiple benefits including reducing nitrate losses from artificially drained fields. We used the Root Zone Water Quality Model (RZWQM) to simulate the impact of a cereal rye cover crop on reducing nitrate losses from drained fields across five...

Cloning crops in a CELSS via tissue culture: Prospects and problems

NASA Technical Reports Server (NTRS)

Carman, John G.; Hess, J. Richard

1990-01-01

Micropropagation is currently used to clone fruits, nuts, and vegetables and involves controlling the outgrowth in vitro of basal, axillary, or adventitious buds. Following clonal multiplication, shoots are divided and rooted. This process has greatly reduced space and energy requirements in greenhouses and field nurseries and has increased multiplication rates by greater than 20 fold for some vegetatively propagated crops and breeding lines. Cereal and legume crops can also be cloned by tissue culture through somatic embryogenesis. Somatic embryos can be used to produce 'synthetic seed', which can tolerate desiccation and germinate upon rehydration. Synthetic seed of hybrid wheat, rice, soybean and other crops could be produced in a controlled ecological life support system. Thus, yield advantages of hybreds over inbreds (10 to 20 percent) could be exploited without having to provide additional facilities and energy for parental-line and hybrid seed nurseries.

Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability

PubMed Central

Gaudin, Amélie C. M.; Tolhurst, Tor N.; Ker, Alan P.; Janovicek, Ken; Tortora, Cristina; Martin, Ralph C.; Deen, William

2015-01-01

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments. PMID:25658914

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran

2010-01-01

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Perennial grasslands enhance biodiversity and multiple ecosystem services in bioenergy landscapes

PubMed Central

Werling, Ben P.; Dickson, Timothy L.; Isaacs, Rufus; Gaines, Hannah; Gratton, Claudio; Gross, Katherine L.; Liere, Heidi; Malmstrom, Carolyn M.; Meehan, Timothy D.; Ruan, Leilei; Robertson, Bruce A.; Robertson, G. Philip; Schmidt, Thomas M.; Schrotenboer, Abbie C.; Teal, Tracy K.; Wilson, Julianna K.; Landis, Douglas A.

2014-01-01

Agriculture is being challenged to provide food, and increasingly fuel, for an expanding global population. Producing bioenergy crops on marginal lands—farmland suboptimal for food crops—could help meet energy goals while minimizing competition with food production. However, the ecological costs and benefits of growing bioenergy feedstocks—primarily annual grain crops—on marginal lands have been questioned. Here we show that perennial bioenergy crops provide an alternative to annual grains that increases biodiversity of multiple taxa and sustain a variety of ecosystem functions, promoting the creation of multifunctional agricultural landscapes. We found that switchgrass and prairie plantings harbored significantly greater plant, methanotrophic bacteria, arthropod, and bird diversity than maize. Although biomass production was greater in maize, all other ecosystem services, including methane consumption, pest suppression, pollination, and conservation of grassland birds, were higher in perennial grasslands. Moreover, we found that the linkage between biodiversity and ecosystem services is dependent not only on the choice of bioenergy crop but also on its location relative to other habitats, with local landscape context as important as crop choice in determining provision of some services. Our study suggests that bioenergy policy that supports coordinated land use can diversify agricultural landscapes and sustain multiple critical ecosystem services. PMID:24474791

Crop effect to soil moisture retrieval at different microwave frequencies

NASA Astrophysics Data System (ADS)

Zhang, Zhongjun; Luan, Jinzhe

2006-12-01

In soil moisture retrieval by microwave remote sensing technology, vegetation effect is important, due to its emission upward as well as masking the soil surface contribution. Because of good penetration characteristics through crop at low frequencies, L-band is often used, where crop is treated as a uniform layer, and 0 th-order Brightness Temperature model is used. Higher frequencies upper than L-band, the frequencies both on NASA AQUA AMSR-E and FY-3 to be launched next year in CHINA, may be more informative in SM retrieval. The multiple-scattering effects inside crop and that between crop layer and soil surface will be increasing when frequencies go higher from L-band. In this paper, a Matrix-Doubling model that account for multiple-scattering based on ray tracing technique is used to simulate the microwave emission of vegetated-surface at C- and X-band. The orientation and size of crop element such as leaves and cylinders are accounted for in crop layer, and AIEM is used for calculation of ground surface scattering. Simulation results from this model for corn and SGP99 experiment data are in good agreement. Since complicated theoretical model as used in this paper involves too many parameters, to make SM retrieval more directly, corresponding terms from the developed model are matched with 0 th-order,so as to derive effective single scattering albedo and vegetation opacity at C- and X-band.

Relay cropping as a sustainable approach: problems and opportunities for sustainable crop production.

PubMed

Tanveer, Mohsin; Anjum, Shakeel Ahmad; Hussain, Saddam; Cerdà, Artemi; Ashraf, Umair

2017-03-01

Climate change, soil degradation, and depletion of natural resources are becoming the most prominent challenges for crop productivity and environmental sustainability in modern agriculture. In the scenario of conventional farming system, limited chances are available to cope with these issues. Relay cropping is a method of multiple cropping where one crop is seeded into standing second crop well before harvesting of second crop. Relay cropping may solve a number of conflicts such as inefficient use of available resources, controversies in sowing time, fertilizer application, and soil degradation. Relay cropping is a complex suite of different resource-efficient technologies, which possesses the capability to improve soil quality, to increase net return, to increase land equivalent ratio, and to control the weeds and pest infestation. The current review emphasized relay cropping as a tool for crop diversification and environmental sustainability with special focus on soil. Briefly, benefits, constraints, and opportunities of relay cropping keeping the goals of higher crop productivity and sustainability have also been discussed in this review. The research and knowledge gap in relay cropping was also highlighted in order to guide the further studies in future.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series.

PubMed

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-04-19

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series

PubMed Central

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-01-01

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536

Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

NASA Astrophysics Data System (ADS)

Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

2016-12-01

The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas concentration pathways. The results indicate that the projected Yp in the Korean peninsula is significantly changed comparing to the historical period and proper adaptation strategies such as optimized planting dates can considerably alleviate Yp decrease.

Carbon exchange by establishing biofuel crops in Central Illinois

USDA-ARS?s Scientific Manuscript database

Perennial grass biofuels may contribute to long-term carbon sequestration in soils, thereby providing a broad range of environmental benefits at multiple scales. To quantify those benefits, the carbon balance was investigated over three perennial grass biofuel crops miscanthus (Miscanthus giganteus)...

Current situation of pests targeted by Bt crops in Latin America.

PubMed

Blanco, C A; Chiaravalle, W; Dalla-Rizza, M; Farias, J R; García-Degano, M F; Gastaminza, G; Mota-Sánchez, D; Murúa, M G; Omoto, C; Pieralisi, B K; Rodríguez, J; Rodríguez-Maciel, J C; Terán-Santofimio, H; Terán-Vargas, A P; Valencia, S J; Willink, E

2016-06-01

Transgenic crops producing Bacillus thuringiensis- (Bt) insecticidal proteins (Bt crops) have provided useful pest management tools to growers for the past 20 years. Planting Bt crops has reduced the use of synthetic insecticides on cotton, maize and soybean fields in 11 countries throughout Latin America. One of the threats that could jeopardize the sustainability of Bt crops is the development of resistance by targeted pests. Governments of many countries require vigilance in measuring changes in Bt-susceptibility in order to proactively implement corrective measures before Bt-resistance is widespread, thus prolonging the usefulness of Bt crops. A pragmatic approach to obtain information on the effectiveness of Bt-crops is directly asking growers, crop consultants and academics about Bt-resistance problems in agricultural fields, first-hand information that not necessarily relies on susceptibility screens performed in laboratories. This type of information is presented in this report. Problematic pests of cotton and soybeans in five Latin American countries currently are effectively controlled by Bt crops. Growers that plant conventional (non-Bt) cotton or soybeans have to spray synthetic insecticides against multiple pests that otherwise are controlled by these Bt crops. A similar situation has been observed in six Latin American countries where Bt maize is planted. No synthetic insecticide applications are used to control corn pests because they are controlled by Bt maize, with the exception of Spodoptera frugiperda. While this insect in some countries is still effectively controlled by Bt maize, in others resistance has evolved and necessitates supplemental insecticide applications and/or the use of Bt maize cultivars that express multiple Bt proteins. Partial control of S. frugiperda in certain countries is due to its natural tolerance to the Bt bacterium. Of the 31 pests targeted and controlled by Bt crops in Latin America, only S. frugiperda has shown tolerance to certain Bt proteins in growers' fields, the most reliable indication of the status of Bt-susceptibility in most of the American continent. Copyright © 2016 Elsevier Inc. All rights reserved.

A Pretest for Introductory Crops Students.

ERIC Educational Resources Information Center

Elkins, Donald M.

1987-01-01

Discusses the advantages of using a pretest in introductory agronomy courses. Provides a pretest that has been developed for use in an introductory crops course taught at Southern Illinois University. Includes 25 definitions, 17 true-false and multiple choice questions, and 6 short answer questions. (TW)

Incorporating pest management into the design of multiple goal-oriented cropping systems

USDA-ARS?s Scientific Manuscript database

Suggestions are offered to facilitate efforts to incorporate pest management goals into the design of crop production systems. The scope of research programs should be expanded to ensure broad multidisciplinary cooperation. Inclusion of farmers, production specialists and researchers from discipli...

Crop-specific seasonal estimates of irrigation-water demand in South Asia

NASA Astrophysics Data System (ADS)

Biemans, Hester; Siderius, Christian; Mishra, Ashok; Ahmad, Bashir

2016-05-01

Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight into these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation-water demand resulting from the typical practice of multiple cropping in South Asia was accounted for by introducing double cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest state-level statistics of India, Pakistan, Bangladesh and Nepal. The improvements in seasonal land use and cropping periods lead to lower estimates of irrigation-water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation-water demand differs sharply between seasons and regions; in Pakistan, winter (rabi) and monsoon summer (kharif) irrigation demands are almost equal, whereas in Bangladesh the rabi demand is ~ 100 times higher. Moreover, the relative importance of irrigation supply versus rain decreases sharply from west to east. Given the size and importance of South Asia improved regional estimates of food production and its irrigation-water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple cropping and monsoon-dependent planting dates should not be ignored.

Designing a new cropping system for high productivity and sustainable water usage under climate change

NASA Astrophysics Data System (ADS)

Meng, Qingfeng; Wang, Hongfei; Yan, Peng; Pan, Junxiao; Lu, Dianjun; Cui, Zhenling; Zhang, Fusuo; Chen, Xinping

2017-02-01

The food supply is being increasingly challenged by climate change and water scarcity. However, incremental changes in traditional cropping systems have achieved only limited success in meeting these multiple challenges. In this study, we applied a systematic approach, using model simulation and data from two groups of field studies conducted in the North China Plain, to develop a new cropping system that improves yield and uses water in a sustainable manner. Due to significant warming, we identified a double-maize (M-M; Zea mays L.) cropping system that replaced the traditional winter wheat (Triticum aestivum L.) -summer maize system. The M-M system improved yield by 14-31% compared with the conventionally managed wheat-maize system, and achieved similar yield compared with the incrementally adapted wheat-maize system with the optimized cultivars, planting dates, planting density and water management. More importantly, water usage was lower in the M-M system than in the wheat-maize system, and the rate of water usage was sustainable (net groundwater usage was ≤150 mm yr-1). Our study indicated that systematic assessment of adaptation and cropping system scale have great potential to address the multiple food supply challenges under changing climatic conditions.

A black color morph of adult Nezara viridula (L.)

USDA-ARS?s Scientific Manuscript database

The southern green stink bug is a worldwide pest of cotton and other row crops, affecting crop yield and transmitting diseases. Adult coloration is sometimes used to identify southern green stink bugs and to determine their physiological condition. Multiple colors occur in southern green stink bug. ...

Fall cover crops boost soil arbuscular mycorrhizal fungi which can lead to reduced inputs

USDA-ARS?s Scientific Manuscript database

Fall cover crops provide multiple benefits to producers. These benefits include pathogen and pest protection, drought protection, weed control, reduced soil erosion, nutrient acquisition and retention, increased soil organic matter, and conservation of soil water by improvement of soil structure th...

Effect of different crops on soil organic matter and biological activity in Oxisols under three different crops

NASA Astrophysics Data System (ADS)

Toledo, Diana Marcela; Arzuaga, Silvia; Dalurzo, Humberto; Zornoza, Raúl; Vazquez, Sara

2015-04-01

The objective of this work was to evaluate changes in soil organic matter in Oxisols under different crops compared to native rainforest, and to assess if acid phosphatase activity (APA) could be a good indicator for SOC changes and soil quality. The experimental design consisted of four completely randomized blocks with four treatments: subtropical rainforest (F); yerba mate crop (I) (Ilex paraguariensis SH.); citrus crop (C) (Citrus unshiu Marc); and tobacco crop (T) (Nicotiana tabacum L.). Soil samples were taken at 0-10; 10-20 and 20-30 cm depths. The variables measured were soil organic carbon (SOC), APA, clay content, pH, total nitrogen (Nt), available phosphorus (P) and CO2 emissions. All data were analyzed by ANOVA to assess the effects of land-use changes. The treatment means were compared through Duncan's multiple range tests (p<0.05). The relationship between variables was determined with a simple correlation analysis and with a multiple linear regression analysis through the stepwise method. These soils showed an acid reaction and their clay content was over 650 g kg-1 for the three depths. SOC and N contents were higher in native soils, intermediate for the citrus crop, and lower under both tobacco and yerba mate crops. CO2 emissions were higher in the rainforest (47.32 kg ha-1 of CO2) than in cultivated soils, which indicates that biological activity is enhanced in rainforest soils where substrates for soil biota and fauna are more readily available. The variability of 76% in APA was explained by total nitrogen, which is closely related to soil organic matter, and by available P. Conversion of subtropical rainforests into agricultural lands reduced SOC content and acid phosphatase activity, thereby lowering soil quality. In this study, acid phosphatase activity proved to be a sensitive indicator to detect changes from pristine to cropped soils, but it failed to distinguish differences among crop systems.

A multiple chamber, semicontinuous, crop carbon dioxide exchange system: design, calibration, and data interpretation

NASA Technical Reports Server (NTRS)

van Iersel, M. W.; Bugbee, B.

2000-01-01

Long-term, whole crop CO2 exchange measurements can be used to study factors affecting crop growth. These factors include daily carbon gain, cumulative carbon gain, and carbon use efficiency, which cannot be determined from short-term measurements. We describe a system that measures semicontinuously crop CO2 exchange in 10 chambers over a period of weeks or months. Exchange of CO2 in every chamber can be measured at 5 min intervals. The system was designed to be placed inside a growth chamber, with additional environmental control provided by the individual gas exchange chambers. The system was calibrated by generating CO2 from NaHCO3 inside the chambers, which indicated that accuracy of the measurements was good (102% and 98% recovery for two separate photosynthesis systems). Since the systems measure net photosynthesis (P-net, positive) and dark respiration(R-dark, negative), the data can be used to estimate gross photosynthesis, daily carbon gain, cumulative carbon gain, and carbon use efficiency. Continuous whole-crop measurements are a valuable tool that complements leaf photosynthesis measurements. Multiple chambers allow for replication and comparison among several environmental or cultural treatments that may affect crop growth. Example data from a 2 week study with petunia (Petunia x hybrida Hort. Vilm.-Andr.) are presented to illustrate some of the capabilities of this system.

Simultaneous determination of multiple soil enzyme activities for soil health-biogeochemical indexes

USDA-ARS?s Scientific Manuscript database

Enzyme activities (EAs) are soil health indicators of changes in decomposition processes due to management and the crop(s) affecting the quantity and quality of plant residues and nutrients entering the soil. More commonly assessed soil EAs can provide information of reactions where plant available ...

Effect of new auxin herbicide formulations on control of herbicide resistant weeds and on microbial activities in the rhizosphere

USDA-ARS?s Scientific Manuscript database

Widespread distribution of glyphosate-resistant weeds in soybean-growing areas across Mississippi has economically affected soybean planting and follow-up crop management operations. New multiple herbicide-resistant crop (including soybean) technologies with associated formulations will soon be comm...

Multiple microbial activity-based measures reflect effects of cover cropping and tillage on soils

USDA-ARS?s Scientific Manuscript database

Agricultural producers, conservation professionals, and policy makers are eager to learn of soil analytical techniques and data that document improvement in soil health by agricultural practices such as no-till and incorporation of cover crops. However, there is considerable uncertainty within the r...

Optimization based trade-off analysis of biodiesel crop production for managing a German agricultural catchment

USDA-ARS?s Scientific Manuscript database

In agricultural production, the existence of multiple trade-offs among several conflicting objectives, such as food production, water quantity, water quality, biodiversity and ecosystem services, is well known. However, quantification of the trade-offs among objectives in bioenergy crop production i...

Fruit metabolite networks in engineered and non-engineered tomato genotypes reveal fluidity in a hormone and agroecosystem specific manner

USDA-ARS?s Scientific Manuscript database

Multiple strategies have been explored throughout the world to meet food security. These include molecular breeding, transgenic genotype development, reduced-tillage crop production, modification of the soil environment with cover crops or polyethylene mulches and tunnels, and organic farming. Unde...

Soil health, crop productivity, microbial transport, and mine spoil response to biochars

USDA-ARS?s Scientific Manuscript database

Biochar is being evaluated by scientists from the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) for its potential to sequester soil C, to improve soil health, and to increase crop yields. ARS scientists from multiple locations such as Florence, SC, Kimberly, ID,...

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

Chaubey, Indrajeet; Cibin, Raj; Bowling, Laura

The overall goal of this project was to conduct a watershed-scale sustainability assessment of multiple species of energy crops and removal of crop residues within two watersheds (Wildcat Creek, and St. Joseph River) representative of conditions in the Upper Midwest. The sustainability assessment included bioenergy feedstock production impacts on environmental quality, economic costs of production, and ecosystem services.

Native grass ground covers in California vineyards provide multiple ecosystem services

USDA-ARS?s Scientific Manuscript database

The mechanisms responsible for the success or failure of agricultural diversification are often unknown. Most studies in this area have focused on enhancing the effectiveness of natural enemies, but non-crop plants can also improve pest suppression by changing the host quality of crop plants through...

Characterization of some useful traits in sweet sorghum for bioenergy production

USDA-ARS?s Scientific Manuscript database

Multiple yearly harvests can increase crop productivity but the crop may encounter different environmental challenges (such as early-spring cold or late-fall frost) depending on cultivation zones. Sweet sorghum as a feedstock may be planted early to get a double harvest or be rotated with sugarcane ...

Modeling and control for closed environment plant production systems

NASA Technical Reports Server (NTRS)

Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)

2002-01-01

A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Cover crops in the upper midwestern United States: Simulated effect on nitrate leaching with artificial drainage

USDA-ARS?s Scientific Manuscript database

Fall-planted winter cover crops are an agricultural management practice with multiple benefits that includes reducing nitrate losses from artificially drained fields. While the practice is commonly used in the southern and eastern U.S., little is known about its efficacy in Midwestern states where a...

Trace gas emissions from a sun and shade grown ornamental crop

USDA-ARS?s Scientific Manuscript database

Previous work has begun to establish baseline approximations for greenhouse gas (GHG) (CO2, CH4, and N2O) emissions of several horticultural crops, though much work is still needed to expand contingencies for multiple best management practices. In this study, GHG emissions from one shade-grown speci...

An approach to determine multiple enzyme activities in the same soil sample for soil health-biogeochemical indexes

USDA-ARS?s Scientific Manuscript database

Enzyme activities (EAs) are soil health indicators of changes in decomposition processes due to management and the crop(s) affecting the quantity and quality of plant residues and nutrients entering the soil. More commonly assessed soil EAs can provide information of reactions where plant available ...

Using FACE systems to screen wheat cultivars for yield increases at elevated CO2

USDA-ARS?s Scientific Manuscript database

Because of continuing increases in atmospheric CO2, identifying cultivars of crops with larger yield increases at elevated CO2 may provide an avenue to increase crop yield potential in future climates. Free-air CO2 enrichment (FACE) systems have most often been used with multiple replications of ea...

Genome-wide association mapping of resistance to a Brazilian isolate of Sclerotinia sclerotiorum in soybean genotypes mostly from Brazil

USDA-ARS?s Scientific Manuscript database

Sclerotinia Stem Rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is ubiquitous in cooler climates where soybean crops are grown. Breeding for resistance to SSR remains challenging in crops like soybean, where no single gene provides strong resistance, but instead, multiple genes w...

Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources

EPA Science Inventory

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. One component of the biomass burning inventory, crop residue burning, has been poorly characterized in the National Emissions I...

Multiple rolling/crimping effects on termination of two summer cover crops in a conservation system

USDA-ARS?s Scientific Manuscript database

A field experiment was initiated in the 2015 growing season at the USDA-NSDL to determine the effectiveness of a prototype two-stage roller/crimper in mechanical termination of two summer cover crops intended for organic systems. The experiment was a randomized complete block design with four replic...

Fixating picture boundaries does not eliminate boundary extension: Implications for scene representation

PubMed Central

Gagnier, Kristin Michod; Dickinson, Christopher A.; Intraub, Helene

2015-01-01

Observers frequently remember seeing more of a scene than was shown (boundary extension). Does this reflect a lack of eye fixations to the boundary region? Single-object photographs were presented for 14–15 s each. Main objects were either whole or slightly cropped by one boundary, creating a salient marker of boundary placement. All participants expected a memory test, but only half were informed that boundary memory would be tested. Participants in both conditions made multiple fixations to the boundary region and the cropped region during study. Demonstrating the importance of these regions, test-informed participants fixated them sooner, longer, and more frequently. Boundary ratings (Experiment 1) and border adjustment tasks (Experiments 2–4) revealed boundary extension in both conditions. The error was reduced, but not eliminated, in the test-informed condition. Surprisingly, test knowledge and multiple fixations to the salient cropped region, during study and at test, were insufficient to overcome boundary extension on the cropped side. Results are discussed within a traditional visual-centric framework versus a multisource model of scene perception. PMID:23547787

Fixating picture boundaries does not eliminate boundary extension: implications for scene representation.

PubMed

Michod Gagnier, Kristin; Dickinson, Christopher A; Intraub, Helene

2013-01-01

Observers frequently remember seeing more of a scene than was shown (boundary extension). Does this reflect a lack of eye fixations to the boundary region? Single-object photographs were presented for 14-15 s each. Main objects were either whole or slightly cropped by one boundary, creating a salient marker of boundary placement. All participants expected a memory test, but only half were informed that boundary memory would be tested. Participants in both conditions made multiple fixations to the boundary region and the cropped region during study. Demonstrating the importance of these regions, test-informed participants fixated them sooner, longer, and more frequently. Boundary ratings (Experiment 1) and border adjustment tasks (Experiments 2-4) revealed boundary extension in both conditions. The error was reduced, but not eliminated, in the test-informed condition. Surprisingly, test knowledge and multiple fixations to the salient cropped region, during study and at test, were insufficient to overcome boundary extension on the cropped side. Results are discussed within a traditional visual-centric framework versus a multisource model of scene perception.

Designing a new cropping system for high productivity and sustainable water usage under climate change

PubMed Central

Meng, Qingfeng; Wang, Hongfei; Yan, Peng; Pan, Junxiao; Lu, Dianjun; Cui, Zhenling; Zhang, Fusuo; Chen, Xinping

2017-01-01

The food supply is being increasingly challenged by climate change and water scarcity. However, incremental changes in traditional cropping systems have achieved only limited success in meeting these multiple challenges. In this study, we applied a systematic approach, using model simulation and data from two groups of field studies conducted in the North China Plain, to develop a new cropping system that improves yield and uses water in a sustainable manner. Due to significant warming, we identified a double-maize (M-M; Zea mays L.) cropping system that replaced the traditional winter wheat (Triticum aestivum L.) –summer maize system. The M-M system improved yield by 14–31% compared with the conventionally managed wheat-maize system, and achieved similar yield compared with the incrementally adapted wheat-maize system with the optimized cultivars, planting dates, planting density and water management. More importantly, water usage was lower in the M-M system than in the wheat-maize system, and the rate of water usage was sustainable (net groundwater usage was ≤150 mm yr−1). Our study indicated that systematic assessment of adaptation and cropping system scale have great potential to address the multiple food supply challenges under changing climatic conditions. PMID:28155860

Contrasting effects of landscape composition on crop yield mediated by specialist herbivores.

PubMed

Perez-Alvarez, Ricardo; Nault, Brian A; Poveda, Katja

2018-04-01

Landscape composition not only affects a variety of arthropod-mediated ecosystem services, but also disservices, such as herbivory by insect pests that may have negative effects on crop yield. Yet, little is known about how different habitats influence the dynamics of multiple herbivore species, and ultimately their collective impact on crop production. Using cabbage as a model system, we examined how landscape composition influenced the incidence of three specialist cruciferous pests (aphids, flea beetles, and leaf-feeding Lepidoptera), lepidopteran parasitoids, and crop yield across a gradient of landscape composition in New York, USA. We expected that landscapes with a higher proportion of cropland and lower habitat diversity would lead to an increase in pest pressure of the specialist herbivores and a reduction in crop yield. However, results indicated that neither greater cropland area nor lower landscape diversity influenced pest pressure or yield. Rather, pest pressure and yield were best explained by the presence of non-crop habitats (i.e., meadows) in the landscape. Specifically, cabbage was infested with fewer Lepidoptera in landscapes with a higher proportion of meadows likely resulting from increased parasitism. Conversely, cabbage was infested with more flea beetles and aphids as the proportion of meadows in the landscape increased, suggesting that these pests benefit from non-crop habitats. Furthermore, path analysis confirmed that these landscape-mediated effects on pest populations can have either positive or negative cascading effects on crop yield. Our findings illustrate how different pest species within the same cropping system show contrasting responses to landscape composition with respect to both the direction and spatial scale of the relationship. Such tradeoffs resulting from the complex interaction between multiple-pests, natural enemies, and landscape composition must be considered, if we are to manage landscapes for pest suppression benefits. © 2018 by the Ecological Society of America.

Multiple pathways of commodity crop expansion in tropical forest landscapes

NASA Astrophysics Data System (ADS)

Meyfroidt, Patrick; Carlson, Kimberly M.; Fagan, Matthew E.; Gutiérrez-Vélez, Victor H.; Macedo, Marcia N.; Curran, Lisa M.; DeFries, Ruth S.; Dyer, George A.; Gibbs, Holly K.; Lambin, Eric F.; Morton, Douglas C.; Robiglio, Valentina

2014-07-01

Commodity crop expansion, for both global and domestic urban markets, follows multiple land change pathways entailing direct and indirect deforestation, and results in various social and environmental impacts. Here we compare six published case studies of rapid commodity crop expansion within forested tropical regions. Across cases, between 1.7% and 89.5% of new commodity cropland was sourced from forestlands. Four main factors controlled pathways of commodity crop expansion: (i) the availability of suitable forestland, which is determined by forest area, agroecological or accessibility constraints, and land use policies, (ii) economic and technical characteristics of agricultural systems, (iii) differences in constraints and strategies between small-scale and large-scale actors, and (iv) variable costs and benefits of forest clearing. When remaining forests were unsuitable for agriculture and/or policies restricted forest encroachment, a larger share of commodity crop expansion occurred by conversion of existing agricultural lands, and land use displacement was smaller. Expansion strategies of large-scale actors emerge from context-specific balances between the search for suitable lands; transaction costs or conflicts associated with expanding into forests or other state-owned lands versus smallholder lands; net benefits of forest clearing; and greater access to infrastructure in already-cleared lands. We propose five hypotheses to be tested in further studies: (i) land availability mediates expansion pathways and the likelihood that land use is displaced to distant, rather than to local places; (ii) use of already-cleared lands is favored when commodity crops require access to infrastructure; (iii) in proportion to total agricultural expansion, large-scale actors generate more clearing of mature forests than smallholders; (iv) property rights and land tenure security influence the actors participating in commodity crop expansion, the form of land use displacement, and livelihood outcomes; (v) intensive commodity crops may fail to spare land when inducing displacement. We conclude that understanding pathways of commodity crop expansion is essential to improve land use governance.

7 CFR 1437.13 - Multiple benefits.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 10 2012-01-01 2012-01-01 false Multiple benefits. 1437.13 Section 1437.13... General Provisions § 1437.13 Multiple benefits. (a) If a producer is eligible to receive payments under this part and benefits under any other program administered by the Secretary for the same crop loss...

7 CFR 1437.13 - Multiple benefits.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 10 2014-01-01 2014-01-01 false Multiple benefits. 1437.13 Section 1437.13... General Provisions § 1437.13 Multiple benefits. (a) If a producer is eligible to receive payments under this part and benefits under any other program administered by the Secretary for the same crop loss...

7 CFR 1437.13 - Multiple benefits.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 10 2010-01-01 2010-01-01 false Multiple benefits. 1437.13 Section 1437.13... General Provisions § 1437.13 Multiple benefits. (a) If a producer is eligible to receive payments under this part and benefits under any other program administered by the Secretary for the same crop loss...

7 CFR 1437.13 - Multiple benefits.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Multiple benefits. 1437.13 Section 1437.13... General Provisions § 1437.13 Multiple benefits. (a) If a producer is eligible to receive payments under this part and benefits under any other program administered by the Secretary for the same crop loss...

7 CFR 1437.13 - Multiple benefits.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 10 2013-01-01 2013-01-01 false Multiple benefits. 1437.13 Section 1437.13... General Provisions § 1437.13 Multiple benefits. (a) If a producer is eligible to receive payments under this part and benefits under any other program administered by the Secretary for the same crop loss...

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

NASA Technical Reports Server (NTRS)

Sand, F.; Christie, R.

1975-01-01

Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.

Recent Advances in Utilizing Transcription Factors to Improve Plant Abiotic Stress Tolerance by Transgenic Technology

PubMed Central

Wang, Hongyan; Wang, Honglei; Shao, Hongbo; Tang, Xiaoli

2016-01-01

Agricultural production and quality are adversely affected by various abiotic stresses worldwide and this will be exacerbated by the deterioration of global climate. To feed a growing world population, it is very urgent to breed stress-tolerant crops with higher yields and improved qualities against multiple environmental stresses. Since conventional breeding approaches had marginal success due to the complexity of stress tolerance traits, the transgenic approach is now being popularly used to breed stress-tolerant crops. So identifying and characterizing the critical genes involved in plant stress responses is an essential prerequisite for engineering stress-tolerant crops. Far beyond the manipulation of single functional gene, engineering certain regulatory genes has emerged as an effective strategy now for controlling the expression of many stress-responsive genes. Transcription factors (TFs) are good candidates for genetic engineering to breed stress-tolerant crop because of their role as master regulators of many stress-responsive genes. Many TFs belonging to families AP2/EREBP, MYB, WRKY, NAC, bZIP have been found to be involved in various abiotic stresses and some TF genes have also been engineered to improve stress tolerance in model and crop plants. In this review, we take five large families of TFs as examples and review the recent progress of TFs involved in plant abiotic stress responses and their potential utilization to improve multiple stress tolerance of crops in the field conditions. PMID:26904044

Crop growth and production responses to commercial humic products in U.S. Midwestern rainfed conditions

USDA-ARS?s Scientific Manuscript database

Humic products (humic and/or fulvic acids) have been in use for over 100 years, yet published research is scant on crop responses to humics under differing soil and weather conditions. We initiated field research experiments on corn (Zea mays L.) in Iowa in 2009 and have since expanded to multiple U...

Accelerating Silphium domestication: an opportunity to develop new crop ideotypes and breeding strategies informed by multiple disciplines

USDA-ARS?s Scientific Manuscript database

Silphium perfoliatum L. (cup plant, silphie) and S. integrifolium Michx. (rosinweed, silflower) are in the same sub-family and tribe as sunflower (Helianthus annuus L.). S. perfoliatum has been grown in many countries a forage or bioenergy crop with forage quality approaching that of alfalfa and bio...

Evidence of multiple/cross resistance to Bt and Organophosphate insecticides in Puerto Rico population of the fall armyworm, Spodoptera frugiperda

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Fall armyworm (FAW) is a damaging pest of many economic crops. Long-term use of chemical control prompted resistance development to many insecticide classes. Many populations were found to be significantly less susceptible to major Bt toxins expressed in transgenic crops. In this study, ...

Mapping croplands, cropping patterns, and crop types using MODIS time-series data

NASA Astrophysics Data System (ADS)

Chen, Yaoliang; Lu, Dengsheng; Moran, Emilio; Batistella, Mateus; Dutra, Luciano Vieira; Sanches, Ieda Del'Arco; da Silva, Ramon Felipe Bicudo; Huang, Jingfeng; Luiz, Alfredo José Barreto; de Oliveira, Maria Antonia Falcão

2018-07-01

The importance of mapping regional and global cropland distribution in timely ways has been recognized, but separation of crop types and multiple cropping patterns is challenging due to their spectral similarity. This study developed a new approach to identify crop types (including soy, cotton and maize) and cropping patterns (Soy-Maize, Soy-Cotton, Soy-Pasture, Soy-Fallow, Fallow-Cotton and Single crop) in the state of Mato Grosso, Brazil. The Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) time series data for 2015 and 2016 and field survey data were used in this research. The major steps of this proposed approach include: (1) reconstructing NDVI time series data by removing the cloud-contaminated pixels using the temporal interpolation algorithm, (2) identifying the best periods and developing temporal indices and phenological parameters to distinguish croplands from other land cover types, and (3) developing crop temporal indices to extract cropping patterns using NDVI time-series data and group cropping patterns into crop types. Decision tree classifier was used to map cropping patterns based on these temporal indices. Croplands from Landsat imagery in 2016, cropping pattern samples from field survey in 2016, and the planted area of crop types in 2015 were used for accuracy assessment. Overall accuracies of approximately 90%, 73% and 86%, respectively were obtained for croplands, cropping patterns, and crop types. The adjusted coefficients of determination of total crop, soy, maize, and cotton areas with corresponding statistical areas were 0.94, 0.94, 0.88 and 0.88, respectively. This research indicates that the proposed approach is promising for mapping large-scale croplands, their cropping patterns and crop types.

Future crop production threatened by extreme heat

NASA Astrophysics Data System (ADS)

Siebert, Stefan; Ewert, Frank

2014-04-01

Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation.

Putting mechanisms into crop production models.

PubMed

Boote, Kenneth J; Jones, James W; White, Jeffrey W; Asseng, Senthold; Lizaso, Jon I

2013-09-01

Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop growth and development and at season-end, final yield. Their ability to integrate effects of genetics, environment and crop management have led to applications ranging from understanding gene function to predicting potential impacts of climate change. The history of crop models is reviewed briefly, and their level of mechanistic detail for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use efficiency is discussed. Crop models have improved steadily over the past 30-40 years, but much work remains. Improvements are needed for the prediction of transpiration response to elevated CO₂ and high temperature effects on phenology and reproductive fertility, and simulation of root growth and nutrient uptake under stressful edaphic conditions. Mechanistic improvements are needed to better connect crop growth to genetics and to soil fertility, soil waterlogging and pest damage. Because crop models integrate multiple processes and consider impacts of environment and management, they have excellent potential for linking research from genomics and allied disciplines to crop responses at the field scale, thus providing a valuable tool for deciphering genotype by environment by management effects. © 2013 John Wiley & Sons Ltd.

Modeling ecohydrological dynamics of smallholder strategies for food production in dryland agricultural systems

NASA Astrophysics Data System (ADS)

Gower, Drew B.; Dell'Angelo, Jampel; McCord, Paul F.; Caylor, Kelly K.; Evans, Tom P.

2016-11-01

In dryland environments, characterized by low and frequently variable rainfall, smallholder farmers must take crop water sensitivity into account along with other characteristics like seed availability and market price when deciding what to plant. In this paper we use the results of surveys conducted among smallholders located near Mount Kenya to identify clusters of farmers devoting different fractions of their land to subsistence and market crops. Additionally, we explore the tradeoffs between water-insensitive but low-value subsistence crops and a water-sensitive but high-value market crop using a numerical model that simulates soil moisture dynamics and crop production over multiple growing seasons. The cluster analysis shows that most farmers prefer to plant either only subsistence crops or only market crops, with a minority choosing to plant substantial fractions of both. The model output suggests that the value a farmer places on a successful growing season, a measure of risk aversion, plays a large role in whether the farmer chooses a subsistence or market crop strategy. Furthermore, access to irrigation, makes market crops more appealing, even to very risk-averse farmers. We then conclude that the observed clustering may result from different levels of risk aversion and access to irrigation.

Increased occurrence of pesticide residues on crops grown in protected environments compared to crops grown in open field conditions.

PubMed

Allen, Gina; Halsall, Crispin J; Ukpebor, Justina; Paul, Nigel D; Ridall, Gareth; Wargent, Jason J

2015-01-01

Crops grown under plastic-clad structures or in greenhouses may be prone to an increased frequency of pesticide residue detections and higher concentrations of pesticides relative to equivalent crops grown in the open field. To test this we examined pesticide data for crops selected from the quarterly reports (2004-2009) of the UK's Pesticide Residue Committee. Five comparison crop pairs were identified whereby one crop of each pair was assumed to have been grown primarily under some form of physical protection ('protected') and the other grown primarily in open field conditions ('open'). For each pair, the number of detectable pesticide residues and the proportion of crop samples containing pesticides were statistically compared (n=100 s samples for each crop). The mean concentrations of selected photolabile pesticides were also compared. For the crop pairings of cabbage ('open') vs. lettuce ('protected') and 'berries' ('open') vs. strawberries ('protected') there was a significantly higher number of pesticides and proportion of samples with multiple residues for the protected crops. Statistically higher concentrations of pesticides, including cypermethrin, cyprodinil, fenhexamid, boscalid and iprodione were also found in the protected crops compared to the open crops. The evidence here demonstrates that, in general, the protected crops possess a higher number of detectable pesticides compared to analogous crops grown in the open. This may be due to different pesticide-use regimes, but also due to slower rates of pesticide removal in protected systems. The findings of this study raise implications for pesticide management in protected-crop systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gene flow from single and stacked herbicide-resistant rice (Oryza sativa): modeling occurrence of multiple herbicide-resistant weedy rice.

PubMed

Dauer, Joseph; Hulting, Andrew; Carlson, Dale; Mankin, Luke; Harden, John; Mallory-Smith, Carol

2018-02-01

Provisia™ rice (PV), a non-genetically engineered (GE) quizalofop-resistant rice, will provide growers with an additional option for weed management to use in conjunction with Clearfield ® rice (CL) production. Modeling compared the impact of stacking resistance traits versus single traits in rice on introgression of the resistance trait to weedy rice (also called red rice). Common weed management practices were applied to 2-, 3- and 4-year crop rotations, and resistant and multiple-resistant weedy rice seeds, seedlings and mature plants were tracked for 15 years. Two-year crop rotations resulted in resistant weedy rice after 2 years with abundant populations (exceeding 0.4 weedy rice plants m -2 ) occurring after 7 years. When stacked trait rice was rotated with soybeans in a 3-year rotation and with soybeans and CL in a 4-year rotation, multiple-resistance occurred after 2-5 years with abundant populations present in 4-9 years. When CL rice, PV rice, and soybeans were used in 3- and 4-year rotations, the median time of first appearance of multiple-resistance was 7-11 years and reached abundant levels in 10-15 years. Maintaining separate CL and PV rice systems, in rotation with other crops and herbicides, minimized the evolution of multiple herbicide-resistant weedy rice through gene flow compared to stacking herbicide resistance traits. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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.

Spatial estimation from remotely sensed data via empirical Bayes models

NASA Technical Reports Server (NTRS)

Hill, J. R.; Hinkley, D. V.; Kostal, H.; Morris, C. N.

1984-01-01

Multichannel satellite image data, available as LANDSAT imagery, are recorded as a multivariate time series (four channels, multiple passovers) in two spatial dimensions. The application of parametric empirical Bayes theory to classification of, and estimating the probability of, each crop type at each of a large number of pixels is considered. This theory involves both the probability distribution of imagery data, conditional on crop types, and the prior spatial distribution of crop types. For the latter Markov models indexed by estimable parameters are used. A broad outline of the general theory reveals several questions for further research. Some detailed results are given for the special case of two crop types when only a line transect is analyzed. Finally, the estimation of an underlying continuous process on the lattice is discussed which would be applicable to such quantities as crop yield.

Snapshots of biodiversity in Georgia agroecosystems

USDA-ARS?s Scientific Manuscript database

Georgia agricultural landscapes are composed of a diversity of commodities. Here we present biodiversity and biotic interaction data from multiple agricultural systems including: cotton, corn, peanut, blueberry and non-cropping wildflower areas over multiple years. Our goal is to better understand t...

Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier

USGS Publications Warehouse

Friesz, Aaron M.; Wylie, Bruce K.; Howard, Daniel M.

2017-01-01

Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008 to 2013. In this investigation, we sought to contribute to the availability of consistent CONUS crop cover maps by extending temporal coverage of the NASS CDL archive back eight additional years to 2000 by creating annual NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million records to train a classification tree algorithm and develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000–2013 at 250 m spatial resolution. The CCM and the maps for years 2008–2013 were assessed for accuracy relative to resampled NASS CDLs. The CCM performed well against a withheld test data set with a model prediction accuracy of over 90%. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains; however, the model did show a bias towards the ‘Other’ crop cover class, which caused frequent misclassifications of pixels around the periphery of large crop cover patch clusters and of pixels that form small, sparsely dispersed crop cover patches.

Monitoring water use and crop condition in California vineyards at multiple scales using multi-sensor satellite data fusion

USDA-ARS?s Scientific Manuscript database

Recent weather patterns have left California’s agricultural areas in severe drought. Given the reduced water availability in much of California it is critical to be able to measure water use and crop condition over large areas, but also in fine detail at scales of individual fields to support water...

Variation in fumonisin and ochratoxin production associated with differences in biosynthetic gene content in Aspergillus niger and A. welwitschiae isolates from multiple crop and geographic origins

USDA-ARS?s Scientific Manuscript database

The fungi Aspergillus niger and A. welwitschiae are morphologically indistinguishable species used for industrial fermentation and for food and beverage production. The fungi also occur widely on food crops. Concerns about their safety have arisen with the discovery that some isolates of both specie...

Droughts in India from 1981 to 2013 and Implications to Wheat Production

NASA Astrophysics Data System (ADS)

Zhang, Xiang; Obringer, Renee; Wei, Chehan; Chen, Nengcheng; Niyogi, Dev

2017-03-01

Understanding drought from multiple perspectives is critical due to its complex interactions with crop production, especially in India. However, most studies only provide singular view of drought and lack the integration with specific crop phenology. In this study, four time series of monthly meteorological, hydrological, soil moisture, and vegetation droughts from 1981 to 2013 were reconstructed for the first time. The wheat growth season (from October to April) was particularly analyzed. In this study, not only the most severe and widespread droughts were identified, but their spatial-temporal distributions were also analyzed alone and concurrently. The relationship and evolutionary process among these four types of droughts were also quantified. The role that the Green Revolution played in drought evolution was also studied. Additionally, the trends of drought duration, frequency, extent, and severity were obtained. Finally, the relationship between crop yield anomalies and all four kinds of drought during the wheat growing season was established. These results provide the knowledge of the most influential drought type, conjunction, spatial-temporal distributions and variations for wheat production in India. This study demonstrates a novel approach to study drought from multiple views and integrate it with crop growth, thus providing valuable guidance for local drought mitigation.

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

NASA Technical Reports Server (NTRS)

Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

2010-01-01

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Interactive effects of pests increase seed yield.

PubMed

Gagic, Vesna; Riggi, Laura Ga; Ekbom, Barbara; Malsher, Gerard; Rusch, Adrien; Bommarco, Riccardo

2016-04-01

Loss in seed yield and therefore decrease in plant fitness due to simultaneous attacks by multiple herbivores is not necessarily additive, as demonstrated in evolutionary studies on wild plants. However, it is not clear how this transfers to crop plants that grow in very different conditions compared to wild plants. Nevertheless, loss in crop seed yield caused by any single pest is most often studied in isolation although crop plants are attacked by many pests that can cause substantial yield losses. This is especially important for crops able to compensate and even overcompensate for the damage. We investigated the interactive impacts on crop yield of four insect pests attacking different plant parts at different times during the cropping season. In 15 oilseed rape fields in Sweden, we estimated the damage caused by seed and stem weevils, pollen beetles, and pod midges. Pest pressure varied drastically among fields with very low correlation among pests, allowing us to explore interactive impacts on yield from attacks by multiple species. The plant damage caused by each pest species individually had, as expected, either no, or a negative impact on seed yield and the strongest negative effect was caused by pollen beetles. However, seed yield increased when plant damage caused by both seed and stem weevils was high, presumably due to the joint plant compensatory reaction to insect attack leading to overcompensation. Hence, attacks by several pests can change the impact on yield of individual pest species. Economic thresholds based on single species, on which pest management decisions currently rely, may therefore result in economically suboptimal choices being made and unnecessary excessive use of insecticides.

Spatial diversification of agroecosystems to enhance biological control and other regulating services: An agroecological perspective.

PubMed

Hatt, Séverin; Boeraeve, Fanny; Artru, Sidonie; Dufrêne, Marc; Francis, Frédéric

2018-04-15

Spatial diversification of crop and non-crop habitats in farming systems is promising for enhancing natural regulation of insect pests. Nevertheless, results from recent syntheses show variable effects. One explanation is that the abundance and diversity of pests and natural enemies are affected by the composition, design and management of crop and non-crop habitats. Moreover, interactions between both local and landscape elements and practices carried out at different spatial scales may affect the regulation of insect pests. Hence, research is being conducted to understand these interdependencies. However, insects are not the only pests and pests are not the only elements to regulate in agroecosystems. Broadening the scope could allow addressing multiple issues simultaneously, but also solving them together by enhancing synergies. Indeed, spatial diversification of crop and non-crop habitats can allow addressing the issues of weeds and pathogens, along with being beneficial to several other regulating services like pollination, soil conservation and nutrient cycling. Although calls rise to develop multifunctional landscapes that optimize the delivery of multiple ecosystem services, it still represents a scientific challenge today. Enhancing interdisciplinarity in research institutions and building interrelations between scientists and stakeholders may help reach this goal. Despite obstacles, positive results from research based on such innovative approaches are encouraging for engaging science in this path. Hence, the aim of the present paper is to offer an update on these issues by exploring the most recent findings and discussing these results to highlight needs for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

Meeting the challenge of food and energy security.

PubMed

Karp, Angela; Richter, Goetz M

2011-06-01

Growing crops for bioenergy or biofuels is increasingly viewed as conflicting with food production. However, energy use continues to rise and food production requires fuel inputs, which have increased with intensification. Focussing on the question of food or fuel is thus not helpful. The bigger, more pertinent, challenge is how the increasing demands for food and energy can be met in the future, particularly when water and land availability will be limited. Energy crop production systems differ greatly in environmental impact. The use of high-input food crops for liquid transport fuels (first-generation biofuels) needs to be phased out and replaced by the use of crop residues and low-input perennial crops (second/advanced-generation biofuels) with multiple environmental benefits. More research effort is needed to improve yields of biomass crops grown on lower grade land, and maximum value should be extracted through the exploitation of co-products and integrated biorefinery systems. Policy must continually emphasize the changes needed and tie incentives to improved greenhous gas reduction and environmental performance of biofuels.

Rice Crop Monitoring Using Microwave and Optical Remotely Sensed Image Data

NASA Astrophysics Data System (ADS)

Suga, Y.; Konishi, T.; Takeuchi, S.; Kitano, Y.; Ito, S.

Hiroshima Institute of Technology HIT is operating the direct down-links of microwave and optical satellite data in Japan This study focuses on the validation for rice crop monitoring using microwave and optical remotely sensed image data acquired by satellites referring to ground truth data such as height of crop ratio of crop vegetation cover and leaf area index in the test sites of Japan ENVISAT-1 ASAR data has a capability to capture regularly and to monitor during the rice growing cycle by alternating cross polarization mode images However ASAR data is influenced by several parameters such as landcover structure direction and alignment of rice crop fields in the test sites In this study the validation was carried out combined with microwave and optical satellite image data and ground truth data regarding rice crop fields to investigate the above parameters Multi-temporal multi-direction descending and ascending and multi-angle ASAR alternating cross polarization mode images were used to investigate rice crop growing cycle LANDSAT data were used to detect landcover structure direction and alignment of rice crop fields corresponding to the backscatter of ASAR As the result of this study it was indicated that rice crop growth can be precisely monitored using multiple remotely sensed data and ground truth data considering with spatial spectral temporal and radiometric resolutions

Life history traits and phenotypic selection among sunflower crop-wild hybrids and their wild counterpart: implications for crop allele introgression.

PubMed

Kost, Matthew A; Alexander, Helen M; Jason Emry, D; Mercer, Kristin L

2015-06-01

Hybridization produces strong evolutionary forces. In hybrid zones, selection can differentially occur on traits and selection intensities may differ among hybrid generations. Understanding these dynamics in crop-wild hybrid zones can clarify crop-like traits likely to introgress into wild populations and the particular hybrid generations through which introgression proceeds. In a field experiment with four crop-wild hybrid Helianthus annuus (sunflower) cross types, we measured growth and life history traits and performed phenotypic selection analysis on early season traits to ascertain the likelihood, and routes, of crop allele introgression into wild sunflower populations. All cross types overwintered, emerged in the spring, and survived until flowering, indicating no early life history barriers to crop allele introgression. While selection indirectly favored earlier seedling emergence and taller early season seedlings, direct selection only favored greater early season leaf length. Further, there was cross type variation in the intensity of selection operating on leaf length. Thus, introgression of multiple early season crop-like traits, due to direct selection for greater early season leaf length, should not be impeded by any cross type and may proceed at different rates among generations. In sum, alleles underlying early season sunflower crop-like traits are likely to introgress into wild sunflower populations.

The commercial use of satellite data to monitor the potato crop in the Columbia Basin

NASA Technical Reports Server (NTRS)

Waddington, George R., Jr.; Lamb, Frank G.

1990-01-01

The imaging of potato crops with satellites is described and evaluated in terms of the commercial application of the remotely sensed data. The identification and analysis of the crops is accomplished with multiple images acquired from the Landsat MSS and TM systems. The data are processed on a PC with image-procesing software which produces images of the seven 1024 x 1024 pixel windows which are subdivided into 21 512 x 512 pixel windows. Maximization of imaged data throughout the year aids in the identification of crop types by IR reflectance. The classification techniques involve the use of six or seven spectral classes for particular image dates. Comparisons with ground-truth data show good agreement; for example, potato fields are identified correctly 90 percent of the time. Acreage estimates and crop-condition assessments can be made from satellite data and used for corrective agricultural action.

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2011-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2009-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Crop Frequency Mapping for Land Use Intensity Estimation During Three Decades

NASA Astrophysics Data System (ADS)

Schmidt, Michael; Tindall, Dan

2016-08-01

Crop extent and frequency maps are an important input to inform the debate around land value and competitive land uses, food security and sustainability of agricultural practices. Such spatial datasets are likely to support decisions on natural resource management, planning and policy. The complete Landsat Time Series (LTS) archive for 23 Landsat footprints in western Queensland from 1987 to 2015 was used in a multi-temporal mapping approach. Spatial, spectral and temporal information were combined in multiple crop-modelling steps, supported by on ground training data sampled across space and time for the classes Crop and No-Crop. Temporal information within summer and winter growing seasons for each year were summarised, and combined with various vegetation indices and band ratios computed from a mid-season spectral-composite image. All available temporal information was spatially aggregated to the scale of image segments in the mid- season composite for each growing season and used to train a random forest classifier for a Crop and No- Crop classification. Validation revealed that the predictive accuracy varied by growing season and region to be within k = 0.88 to 0.97 and are thus suitable for mapping current and historic cropping activity. Crop frequency maps were produced for all regions at different time intervals. The crop frequency maps were validated separately with a historic crop information time series. Different land use intensities and conversions e.g. from agricultural to pastures are apparent and potential drivers of these conversions are discussed.

[Impacts of climate change on food production in Gansu: A review].

PubMed

Yang, Feng-ke; He, Bao-lin; Gao, Shi-ming

2015-03-01

The climate of Gansu turned to be overall warming-drying and partly warming-wetting since 1986. In contrast to that of 1960, the average annual temperature had raised by 1.1°C with the average annual precipitation decreased by 28 mm correspondingly, which made the arid region expanded southward by 50 km in 2010. Climate warming increased the growth period effective accumulated temperature of main food grain crops and lengthened the crop growth period. It changed crop maturity, crop disposition, cropping system and generally increased the cultivatable area and planting altitude above the sea level of major crops and expanded northward the multiple cropping system, which further resulted in expansion of autumn grain crop sown area, shrink of summer grain crop sown area, and replacement of strong winter early maturing varieties by weak winter middle late maturing varieties. It benefited the crop yield by increasing the use efficiency of photo-thermal resources. Warming-wetting climate increased the climate productivity of oasis crop while warming-drying weather decreased the climate productivity of rainfed crops, which were mostly determined by the precipitation regimes and water conditions. Any advanced technique that can increase precipitation use ratio and water use efficiency as well as improve and promote soil quality and fertility should be regarded as an effective countermeasure to increase food grain production under climate change in Gsansu. So, selecting and breeding new crop varieties with the characteristics of strong resistance, weak winter, middle-late mature and high water use efficiency, establishing new planting structure and cropping system that suitable to the precipitation and temperature features of changed climate, are the development direction of food grain production in Gansu to cope with the climate change.

A national research & development strategy for biomass crop feedstocks

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

Wright, L.L.; Cushman, J.H.

Planning was initiated in 1996 with the objective of reevaluating current biomass feedstock research and development strategies to: (1) assure that by 2005, one or more commercial lignocellulosic to ethanol projects will be able to acquire a dependable supply of biomass crop feedstocks; (2) assure that recently initiated demonstrations of crops to electricity will be successful and; (3) assure that the research base needed to support future biomass industry expansion is being developed. Multiple trends and analyses indicate that biomass energy research and development strategies must take into account the fact that competition for land will define the upper limitsmore » of available biomass energy crop supplies and will largely dictate the price of those supplies. Only crop production and utilization strategies which contribute profit to the farmer or landowner and to energy producers will be used commercially for biomass energy production. Strategies for developing biomass {open_quotes}energy{close_quotes} crop supplies must take into consideration all of the methods by which biomass crops will enter biomass energy markets. The lignocellulosic materials derived from crops can be available as primary residues or crop by-products; secondary residues or processing by-products; co-products (at both the crop production and processing stages); or, as dedicated energy crops. Basic research and development (R&D) leading to yield improvement continues to be recommended as a major long-term focus for dedicated energy crops. Many additional near term topics need attention, some of which are also applicable to by-products and co-products. Switchgrass R&D should be expanded and developed with greater collaboration of USDA and state extension groups. Woody crop research should continue with significant cost-share from industries developing the crops for other commercial products. Co-product options need more investigation.« less

Temporal dynamics of direct N2O fluxes from agro-ecosystems in cold climates: importance of year-round measurements in multiple cropping systems

NASA Astrophysics Data System (ADS)

Wagner-Riddle, C.; Tenuta, M.

2014-12-01

Soil N2O fluxes (direct emissions) are highly variable in time and space due to soil, weather and management drivers. In cold climates, freeze/thaw cycles and short growing seasons can enhance soil N2O production contributing to the temporal variability of fluxes. Year-round measurements of N2O fluxes in multiple cropping systems are needed to decrease the uncertainty of annual emission estimates and to devise mitigation practices for emission reduction in cold climates. We have deployed a micrometeorological flux-gradient approach coupled to a tunable diode laser absorption spectroscopy system at two long-term sites in Canada: Elora, Ontario (2000-2014) and Glenlea, Manitoba (2006-2014). Quasi-simultaneous half-hourly flux measurements on four 4-ha fields within a level and aerodynamically homogeneous landscape were obtained allowing for comparison of crop type and/or management practices within and between years. Annual crops such as corn, soybeans, wheat, and barley received typical inorganic fertilizer and/or manure applications, and best management practices such as timing of application and reduced tillage were studied. Perennial grass-alfalfa hayfields were compared to annual crops during selected time periods. Here we synthesize the long-term datasets from these two sites, and quantify the overall contribution of non-growing season (mainly freeze/thaw cycles) and growing season (mainly nitrogen application) to annual emission totals. Uncertainties of regional estimates for cold-climates will be assessed using these long-term datasets.

Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

NASA Astrophysics Data System (ADS)

Niazmardi, S.; Safari, A.; Homayouni, S.

2017-09-01

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

NASA Astrophysics Data System (ADS)

Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

2017-02-01

Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

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.

Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice.

PubMed

Jones, Susan; Baizan-Edge, Amanda; MacFarlane, Stuart; Torrance, Lesley

2017-01-01

Viruses cause significant yield and quality losses in a wide variety of cultivated crops. Hence, the detection and identification of viruses is a crucial facet of successful crop production and of great significance in terms of world food security. Whilst the adoption of molecular techniques such as RT-PCR has increased the speed and accuracy of viral diagnostics, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses. Therefore, unknown viruses can be missed and testing can be slow and expensive if molecular tests are unavailable. Methods for simultaneous detection of multiple viruses have been developed, and (NGS) is now a principal focus of this area, as it enables unbiased and hypothesis-free testing of plant samples. The development of NGS protocols capable of detecting multiple known and emergent viruses present in infected material is proving to be a major advance for crops, nuclear stocks or imported plants and germplasm, in which disease symptoms are absent, unspecific or only triggered by multiple viruses. Researchers want to answer the question "how many different viruses are present in this crop plant?" without knowing what they are looking for: RNA-sequencing (RNA-seq) of plant material allows this question to be addressed. As well as needing efficient nucleic acid extraction and enrichment protocols, virus detection using RNA-seq requires fast and robust bioinformatics methods to enable host sequence removal and virus classification. In this review recent studies that use RNA-seq for virus detection in a variety of crop plants are discussed with specific emphasis on the computational methods implemented. The main features of a number of specific bioinformatics workflows developed for virus detection from NGS data are also outlined and possible reasons why these have not yet been widely adopted are discussed. The review concludes by discussing the future directions of this field, including the use of bioinformatics tools for virus detection deployed in analytical environments using cloud computing.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes.

PubMed

Lochlainn, Seosamh Ó; Amoah, Stephen; Graham, Neil S; Alamer, Khalid; Rios, Juan J; Kurup, Smita; Stoute, Andrew; Hammond, John P; Østergaard, Lars; King, Graham J; White, Phillip J; Broadley, Martin R

2011-12-08

Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

PubMed Central

2011-01-01

Background Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service. PMID:22152063

Ecosystem-Service Tradeoffs Associated with Switching from Annual to Perennial Energy Crops in Riparian Zones of the US Midwest

PubMed Central

Meehan, Timothy D.; Gratton, Claudio; Diehl, Erica; Hunt, Natalie D.; Mooney, Daniel F.; Ventura, Stephen J.; Barham, Bradford L.; Jackson, Randall D.

2013-01-01

Integration of energy crops into agricultural landscapes could promote sustainability if they are placed in ways that foster multiple ecosystem services and mitigate ecosystem disservices from existing crops. We conducted a modeling study to investigate how replacing annual energy crops with perennial energy crops along Wisconsin waterways could affect a variety of provisioning and regulating ecosystem services. We found that a switch from continuous corn production to perennial-grass production decreased annual income provisioning by 75%, although it increased annual energy provisioning by 33%, decreased annual phosphorous loading to surface water by 29%, increased below-ground carbon sequestration by 30%, decreased annual nitrous oxide emissions by 84%, increased an index of pollinator abundance by an average of 11%, and increased an index of biocontrol potential by an average of 6%. We expressed the tradeoffs between income provisioning and other ecosystem services as benefit-cost ratios. Benefit-cost ratios averaged 12.06 GJ of additional net energy, 0.84 kg of avoided phosphorus pollution, 18.97 Mg of sequestered carbon, and 1.99 kg of avoided nitrous oxide emissions for every $1,000 reduction in income. These ratios varied spatially, from 2- to 70-fold depending on the ecosystem service. Benefit-cost ratios for different ecosystem services were generally correlated within watersheds, suggesting the presence of hotspots – watersheds where increases in multiple ecosystem services would come at lower-than-average opportunity costs. When assessing the monetary value of ecosystem services relative to existing conservation programs and environmental markets, the overall value of enhanced services associated with adoption of perennial energy crops was far lower than the opportunity cost. However, when we monitized services using estimates for the social costs of pollution, the value of enhanced services far exceeded the opportunity cost. This disparity between recoverable costs and social value represents a fundamental challenge to expansion of perennial energy crops and sustainable agricultural landscapes. PMID:24223215

Ecosystem-service tradeoffs associated with switching from annual to perennial energy crops in riparian zones of the US Midwest.

PubMed

Meehan, Timothy D; Gratton, Claudio; Diehl, Erica; Hunt, Natalie D; Mooney, Daniel F; Ventura, Stephen J; Barham, Bradford L; Jackson, Randall D

2013-01-01

Integration of energy crops into agricultural landscapes could promote sustainability if they are placed in ways that foster multiple ecosystem services and mitigate ecosystem disservices from existing crops. We conducted a modeling study to investigate how replacing annual energy crops with perennial energy crops along Wisconsin waterways could affect a variety of provisioning and regulating ecosystem services. We found that a switch from continuous corn production to perennial-grass production decreased annual income provisioning by 75%, although it increased annual energy provisioning by 33%, decreased annual phosphorous loading to surface water by 29%, increased below-ground carbon sequestration by 30%, decreased annual nitrous oxide emissions by 84%, increased an index of pollinator abundance by an average of 11%, and increased an index of biocontrol potential by an average of 6%. We expressed the tradeoffs between income provisioning and other ecosystem services as benefit-cost ratios. Benefit-cost ratios averaged 12.06 GJ of additional net energy, 0.84 kg of avoided phosphorus pollution, 18.97 Mg of sequestered carbon, and 1.99 kg of avoided nitrous oxide emissions for every $1,000 reduction in income. These ratios varied spatially, from 2- to 70-fold depending on the ecosystem service. Benefit-cost ratios for different ecosystem services were generally correlated within watersheds, suggesting the presence of hotspots--watersheds where increases in multiple ecosystem services would come at lower-than-average opportunity costs. When assessing the monetary value of ecosystem services relative to existing conservation programs and environmental markets, the overall value of enhanced services associated with adoption of perennial energy crops was far lower than the opportunity cost. However, when we monitized services using estimates for the social costs of pollution, the value of enhanced services far exceeded the opportunity cost. This disparity between recoverable costs and social value represents a fundamental challenge to expansion of perennial energy crops and sustainable agricultural landscapes.

An Analysis of the Joint Modular Intermodal Distribution System

DTIC Science & Technology

2007-06-01

the differing airframes. “Two methods are available to move a CROP-load of ammunition: 1. Reconfigure the load from the CROP onto multiple 463L...used among the services lack: • Transportability across different modes without re-handling/packaging • Quick reconfiguration for onward movement...numerous linkages among different channels of distribution. In the world of integrated logistics, that means that ground, rail, air, and sea modes of

Droughts in India from 1981 to 2013 and Implications to Wheat Production

PubMed Central

Zhang, Xiang; Obringer, Renee; Wei, Chehan; Chen, Nengcheng; Niyogi, Dev

2017-01-01

Understanding drought from multiple perspectives is critical due to its complex interactions with crop production, especially in India. However, most studies only provide singular view of drought and lack the integration with specific crop phenology. In this study, four time series of monthly meteorological, hydrological, soil moisture, and vegetation droughts from 1981 to 2013 were reconstructed for the first time. The wheat growth season (from October to April) was particularly analyzed. In this study, not only the most severe and widespread droughts were identified, but their spatial-temporal distributions were also analyzed alone and concurrently. The relationship and evolutionary process among these four types of droughts were also quantified. The role that the Green Revolution played in drought evolution was also studied. Additionally, the trends of drought duration, frequency, extent, and severity were obtained. Finally, the relationship between crop yield anomalies and all four kinds of drought during the wheat growing season was established. These results provide the knowledge of the most influential drought type, conjunction, spatial-temporal distributions and variations for wheat production in India. This study demonstrates a novel approach to study drought from multiple views and integrate it with crop growth, thus providing valuable guidance for local drought mitigation. PMID:28294189

Parsing multiple processes of high temperature impacts on corn/soybean yield using a newly developed CLM-APSIM modeling framework

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.

2016-12-01

Future agricultural production faces a grand challenge of higher temperature under climate change. There are multiple physiological or metabolic processes of how high temperature affects crop yield. Specifically, we consider the following major processes: (1) direct temperature effects on photosynthesis and respiration; (2) speed-up growth rate and the shortening of growing season; (3) heat stress during reproductive stage (flowering and grain-filling); (4) high-temperature induced increase of atmospheric water demands. In this work, we use a newly developed modeling framework (CLM-APSIM) to simulate the corn and soybean growth and explicitly parse the above four processes. By combining the strength of CLM in modeling surface biophysical (e.g., hydrology and energy balance) and biogeochemical (e.g., photosynthesis and carbon-nitrogen interactions), as well as that of APSIM in modeling crop phenology and reproductive stress, the newly developed CLM-APSIM modeling framework enables us to diagnose the impacts of high temperature stress through different processes at various crop phenology stages. Ground measurements from the advanced SoyFACE facility at University of Illinois is used here to calibrate, validate, and improve the CLM-APSIM modeling framework at the site level. We finally use the CLM-APSIM modeling framework to project crop yield for the whole US Corn Belt under different climate scenarios.

Response of Pennsylvania native plant species, corn and soybean to tank mixes of dicamba and glyphosate

EPA Science Inventory

Crops such as soybean are being genetically modified to be tolerant to multiple herbicides, such as dicamba and glyphosate, in order to allow treatment with several herbicides to control the development of herbicide resistance in weeds. However, with increased use of multiple-he...

A maize caffeoyl-CoA O-methyltransferase gene confers quantitative resistance to multiple pathogens

USDA-ARS?s Scientific Manuscript database

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement though molecular mechanisms underlying their functions remain largely unknown. A QTL, qMdr9.02, associated with resistance to three important foliar maize diseases, southern leaf blight (SLB), gray leaf spot (GLS)...

The benefits of herbicide-resistant crops.

PubMed

Green, Jerry M

2012-10-01

Since 1996, genetically modified herbicide-resistant crops, primarily glyphosate-resistant soybean, corn, cotton and canola, have helped to revolutionize weed management and have become an important tool in crop production practices. Glyphosate-resistant crops have enabled the implementation of weed management practices that have improved yield and profitability while better protecting the environment. Growers have recognized their benefits and have made glyphosate-resistant crops the most rapidly adopted technology in the history of agriculture. Weed management systems with glyphosate-resistant crops have often relied on glyphosate alone, have been easy to use and have been effective, economical and more environmentally friendly than the systems they have replaced. Glyphosate has worked extremely well in controlling weeds in glyphosate-resistant crops for more than a decade, but some key weeds have evolved resistance, and using glyphosate alone has proved unsustainable. Now, growers need to renew their weed management practices and use glyphosate with other cultural, mechanical and herbicide options in integrated systems. New multiple-herbicide-resistant crops with resistance to glyphosate and other herbicides will expand the utility of existing herbicide technologies and will be an important component of future weed management systems that help to sustain the current benefits of high-efficiency and high-production agriculture. Copyright © 2012 Society of Chemical Industry.

Increased food production and reduced water use through optimized crop distribution

NASA Astrophysics Data System (ADS)

Davis, Kyle Frankel; Rulli, Maria Cristina; Seveso, Antonio; D'Odorico, Paolo

2017-12-01

Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology — such as irrigation or fertilizers — and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods.

Summer Flowering Cover Crops Support Wild Bees in Vineyards.

PubMed

Wilson, Houston; Wong, Jessica S; Thorp, Robbin W; Miles, Albie F; Daane, Kent M; Altieri, Miguel A

2018-02-08

Agricultural expansion and intensification negatively affect pollinator populations and has led to reductions in pollination services across multiple cropping systems. As a result, growers and researchers have utilized the restoration of local and landscape habitat diversity to support pollinators, and wild bees in particular. Although a majority of studies to date have focussed on effects in pollinator-dependent crops such as almond, tomato, sunflower, and watermelon, supporting wild bees in self-pollinated crops, such as grapes, can contribute to broader conservation goals as well as provide other indirect benefits to growers. This study evaluates the influence of summer flowering cover crops and landscape diversity on the abundance and diversity of vineyard bee populations. We showed that diversity and abundance of wild bees were increased on the flowering cover crop, but were unaffected by changes in landscape diversity. These findings indicate that summer flowering cover crops can be used to support wild bees and this could be a useful strategy for grape growers interested in pollinator conservation as part of a broader farmscape sustainability agenda. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

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.

Precision Farming and Precision Pest Management: The Power of New Crop Production Technologies

PubMed Central

Strickland, R. Mack; Ess, Daniel R.; Parsons, Samuel D.

1998-01-01

The use of new technologies including Geographic Information Systems (GIS), the Global Positioning System (GPS), Variable Rate Technology (VRT), and Remote Sensing (RS) is gaining acceptance in the present high-technology, precision agricultural industry. GIS provides the ability to link multiple data values for the same geo-referenced location, and provides the user with a graphical visualization of such data. When GIS is coupled with GPS and RS, management decisions can be applied in a more precise "micro-managed" manner by using VRT techniques. Such technology holds the potential to reduce agricultural crop production costs as well as crop and environmental damage. PMID:19274236

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.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.

PubMed

Tao, Fulu; Rötter, Reimund P; Palosuo, Taru; Gregorio Hernández Díaz-Ambrona, Carlos; Mínguez, M Inés; Semenov, Mikhail A; Kersebaum, Kurt Christian; Nendel, Claas; Specka, Xenia; Hoffmann, Holger; Ewert, Frank; Dambreville, Anaelle; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G; Salo, Tapio; Ferrise, Roberto; Bindi, Marco; Cammarano, Davide; Schulman, Alan H

2018-03-01

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. © 2017 John Wiley & Sons Ltd.

GM as a route for delivery of sustainable crop protection.

PubMed

Bruce, Toby J A

2012-01-01

Modern agriculture, with its vast monocultures of lush fertilized crops, provides an ideal environment for adapted pests, weeds, and diseases. This vulnerability has implications for food security: when new pesticide-resistant pest biotypes evolve they can devastate crops. Even with existing crop protection measures, approximately one-third yield losses occur globally. Given the projected increase in demand for food (70% by 2050 according to the UN), sustainable ways of preventing these losses are needed. Development of resistant crop cultivars can make an important contribution. However, traditional crop breeding programmes are limited by the time taken to move resistance traits into elite crop genetic backgrounds and the limited gene pools in which to search for novel resistance. Furthermore, resistance based on single genes does not protect against the full spectrum of pests, weeds, and diseases, and is more likely to break down as pests evolve counter-resistance. Although not necessarily a panacea, GM (genetic modification) techniques greatly facilitate transfer of genes and thus provide a route to overcome these constraints. Effective resistance traits can be precisely and conveniently moved into mainstream crop cultivars. Resistance genes can be stacked to make it harder for pests to evolve counter-resistance and to provide multiple resistances to different attackers. GM-based crop protection could substantially reduce the need for farmers to apply pesticides to their crops and would make agricultural production more efficient in terms of resources used (land, energy, water). These benefits merit consideration by environmentalists willing to keep an open mind on the GM debate.

Stream Health Sensitivity to Landscape Changes due to Bioenergy Crops Expansion

NASA Astrophysics Data System (ADS)

Nejadhashemi, A.; Einheuser, M. D.; Woznicki, S. A.

2012-12-01

Global demand for bioenergy has increased due to uncertainty in oil markets, environmental concerns, and expected increases in energy consumption worldwide. To develop a sustainable biofuel production strategy, the adverse environmental impacts of bioenergy crops expansion should be understood. To study the impact of bioenergy crops expansion on stream health, the adaptive neural-fuzzy inference system (ANFIS) was used to predict macroinvertebrate and fish stream health measures. The Hilsenhoff Biotic Index (HBI), Family Index of Biological Integrity (Family IBI), and Number of Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT taxa) were used as macroinvertebrate measures, while the Index of Biological Integrity (IBI) was used for fish. A high-resolution biophysical model built using the Soil and Water Assessment Tool was used to obtain water quantity and quality variables for input into the ANFIS stream health predictive models. Twenty unique crop rotations were developed to examine impacts of bioenergy crops expansion on stream health in the Saginaw Bay basin. Traditional intensive row crops generated more pollution than current landuse conditions, while second-generation biofuel crops associated with less intensive agricultural activities resulted in water quality improvement. All three macroinvertebrate measures were negatively impacted during intensive row crop productions but improvement was predicted when producing perennial crops. However, the expansion of native grass, switchgrass, and miscanthus production resulted in reduced IBI relative to first generation row crops. This study demonstrates that ecosystem complexity requires examination of multiple stream health measures to avoid potential adverse impacts of landuse change on stream health.

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.

Introducing perennial biomass crops into agricultural landscapes to address water quality challenges and provide other environmental services: Integrating perennial bioenergy crops into agricultural landscapes

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

Cacho, J. F.; Negri, M. C.; Zumpf, C. R.

The world is faced with a difficult multiple challenge of meeting nutritional, energy, and other basic needs, under a limited land and water budget, of between 9 and 10 billion people in the next three decades, mitigating impacts of climate change, and making agricultural production resilient. More productivity is expected from agricultural lands, but intensification of production could further impact the integrity of our finite surface water and groundwater resources. Integrating perennial bioenergy crops in agricultural lands could provide biomass for biofuel and potential improvements on the sustainability of commodity crop production. This article provides an overview of ways inmore » which research has shown that perennial bioenergy grasses and short rotation woody crops can be incorporated into agricultural production systems with reduced indirect land use change, while increasing water quality benefits. Current challenges and opportunities as well as future directions are also highlighted.« less

Cover crops do not increase C sequestration in production crops: evidence from 12 years of continuous measurements

NASA Astrophysics Data System (ADS)

Buysse, Pauline; Bodson, Bernard; Debacq, Alain; De Ligne, Anne; Heinesch, Bernard; Manise, Tanguy; Moureaux, Christine; Aubinet, Marc

2017-04-01

The numerous reports on carbon (C) loss from cropland soils have recently raised awareness on the climate change mitigation potential of these ecosystems, and on the necessity to improve C sequestration in these soils. Among the multiple solutions that are proposed, several field measurement and modelling studies reported that growing cover crops over fall and winter time could appear as an efficient solution. However, while the large majority of these studies are based on SOC stock inventories and very few information exists from the CO2 flux dynamics perspective. In the present work, we use the results from long-term (12 years) eddy-covariance measurements performed at the Lonzée Terrestrial Observatory (LTO, candidate ICOS site, Belgium) and focus on six intercrop periods managed with (3) and without (3) cover crops after winter wheat main crops, in order to compare their response to environmental factors and to investigate the impact of cover crops on Net Ecosystem Exchange (NEE). Our results showed that cumulated NEE was not significantly affected by the presence of cover crops. Indeed, while larger CO2 assimilation occurred during cover crop growth, this carbon gain was later lost by larger respiration rates due to larger crop residue amounts brought to the soil. As modelled by a Q10-like relationship, significantly larger R10 values were indeed observed during the three intercrop periods cultivated with cover crops. These CO2 flux-based results therefore tend to moderate the generally acknowledged positive impact of cover crops on net C sequestration by croplands. Our results indicate that the effect of growing cover crops on C sequestration could be less important than announced, at least at certain sites.

Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

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

Lobell, D; Field, C; Cahill, K

2006-01-10

Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiplemore » climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.« less

Variation in Fumonisin and Ochratoxin Production Associated with Differences in Biosynthetic Gene Content in Aspergillus niger and A. welwitschiae Isolates from Multiple Crop and Geographic Origins

PubMed Central

Susca, Antonia; Proctor, Robert H.; Morelli, Massimiliano; Haidukowski, Miriam; Gallo, Antonia; Logrieco, Antonio F.; Moretti, Antonio

2016-01-01

The fungi Aspergillus niger and A. welwitschiae are morphologically indistinguishable species used for industrial fermentation and for food and beverage production. The fungi also occur widely on food crops. Concerns about their safety have arisen with the discovery that some isolates of both species produce fumonisin (FB) and ochratoxin A (OTA) mycotoxins. Here, we examined FB and OTA production as well as the presence of genes responsible for synthesis of the mycotoxins in a collection of 92 A. niger/A. welwitschiae isolates from multiple crop and geographic origins. The results indicate that (i) isolates of both species differed in ability to produce the mycotoxins; (ii) FB-nonproducing isolates of A. niger had an intact fumonisin biosynthetic gene (fum) cluster; (iii) FB-nonproducing isolates of A. welwitschiae exhibited multiple patterns of fum gene deletion; and (iv) OTA-nonproducing isolates of both species lacked the ochratoxin A biosynthetic gene (ota) cluster. Analysis of genome sequence data revealed a single pattern of ota gene deletion in the two species. Phylogenetic analysis suggest that the simplest explanation for this is that ota cluster deletion occurred in a common ancestor of A. niger and A. welwitschiae, and subsequently both the intact and deleted cluster were retained as alternate alleles during divergence of the ancestor into descendent species. Finally, comparison of results from this and previous studies indicate that a majority of A. niger isolates and a minority of A. welwitschiae isolates can produce FBs, whereas, a minority of isolates of both species produce OTA. The comparison also suggested that the relative abundance of each species and frequency of FB/OTA-producing isolates can vary with crop and/or geographic origin. PMID:27667988

Variation in Fumonisin and Ochratoxin Production Associated with Differences in Biosynthetic Gene Content in Aspergillus niger and A. welwitschiae Isolates from Multiple Crop and Geographic Origins.

PubMed

Susca, Antonia; Proctor, Robert H; Morelli, Massimiliano; Haidukowski, Miriam; Gallo, Antonia; Logrieco, Antonio F; Moretti, Antonio

2016-01-01

The fungi Aspergillus niger and A. welwitschiae are morphologically indistinguishable species used for industrial fermentation and for food and beverage production. The fungi also occur widely on food crops. Concerns about their safety have arisen with the discovery that some isolates of both species produce fumonisin (FB) and ochratoxin A (OTA) mycotoxins. Here, we examined FB and OTA production as well as the presence of genes responsible for synthesis of the mycotoxins in a collection of 92 A. niger/A. welwitschiae isolates from multiple crop and geographic origins. The results indicate that (i) isolates of both species differed in ability to produce the mycotoxins; (ii) FB-nonproducing isolates of A. niger had an intact fumonisin biosynthetic gene (fum) cluster; (iii) FB-nonproducing isolates of A. welwitschiae exhibited multiple patterns of fum gene deletion; and (iv) OTA-nonproducing isolates of both species lacked the ochratoxin A biosynthetic gene (ota) cluster. Analysis of genome sequence data revealed a single pattern of ota gene deletion in the two species. Phylogenetic analysis suggest that the simplest explanation for this is that ota cluster deletion occurred in a common ancestor of A. niger and A. welwitschiae, and subsequently both the intact and deleted cluster were retained as alternate alleles during divergence of the ancestor into descendent species. Finally, comparison of results from this and previous studies indicate that a majority of A. niger isolates and a minority of A. welwitschiae isolates can produce FBs, whereas, a minority of isolates of both species produce OTA. The comparison also suggested that the relative abundance of each species and frequency of FB/OTA-producing isolates can vary with crop and/or geographic origin.

Liming impacts on soils, crops and biodiversity in the UK: A review.

PubMed

Holland, J E; Bennett, A E; Newton, A C; White, P J; McKenzie, B M; George, T S; Pakeman, R J; Bailey, J S; Fornara, D A; Hayes, R C

2018-01-01

Fertile soil is fundamental to our ability to achieve food security, but problems with soil degradation (such as acidification) are exacerbated by poor management. Consequently, there is a need to better understand management approaches that deliver multiple ecosystem services from agricultural land. There is global interest in sustainable soil management including the re-evaluation of existing management practices. Liming is a long established practice to ameliorate acidic soils and many liming-induced changes are well understood. For instance, short-term liming impacts are detected on soil biota and in soil biological processes (such as in N cycling where liming can increase N availability for plant uptake). The impacts of liming on soil carbon storage are variable and strongly relate to soil type, land use, climate and multiple management factors. Liming influences all elements in soils and as such there are numerous simultaneous changes to soil processes which in turn affect the plant nutrient uptake; two examples of positive impact for crops are increased P availability and decreased uptake of toxic heavy metals. Soil physical conditions are at least maintained or improved by liming, but the time taken to detect change varies significantly. Arable crops differ in their sensitivity to soil pH and for most crops there is a positive yield response. Liming also introduces implications for the development of different crop diseases and liming management is adjusted according to crop type within a given rotation. Repeated lime applications tend to improve grassland biomass production, although grassland response is variable and indirect as it relates to changes in nutrient availability. Other indicators of liming response in grassland are detected in mineral content and herbage quality which have implications for livestock-based production systems. Ecological studies have shown positive impacts of liming on biodiversity; such as increased earthworm abundance that provides habitat for wading birds in upland grasslands. Finally, understanding of liming impacts on soil and crop processes are explored together with functional aspects (in terms of ecosystems services) in a new qualitative framework that includes consideration of how liming impacts change with time. This holistic approach provides insights into the far-reaching impacts that liming has on ecosystems and the potential for liming to enhance the multiple benefits from agriculturally managed land. Recommendations are given for future research on the impact of liming and the implications for ecosystem services. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Modeling global yield growth of major crops under multiple socioeconomic pathways

NASA Astrophysics Data System (ADS)

Iizumi, T.; Kim, W.; Zhihong, S.; Nishimori, M.

2016-12-01

Global gridded crop models (GGCMs) are a key tool in deriving global food security scenarios under climate change. However, it is difficult for GGCMs to reproduce the reported yield growth patterns—rapid growth, yield stagnation and yield collapse. Here, we propose a set of parameterizations for GGCMs to capture the contributions to yield from technological improvements at the national and multi-decadal scales. These include country annual per capita gross domestic product (GDP)-based parameterizations for the nitrogen application rate and crop tolerance to stresses associated with high temperature, low temperature, water deficit and water excess. Using a GGCM combined with the parameterizations, we present global 140-year (1961-2100) yield growth simulations for maize, soybean, rice and wheat under multiple shared socioeconomic pathways (SSPs) and no climate change. The model reproduces the major characteristics of reported global and country yield growth patterns over the 1961-2013 period. Under the most rapid developmental pathway SSP5, the simulated global yields for 2091-2100, relative to 2001-2010, are the highest (1.21-1.82 times as high, with variations across the crops), followed by SSP1 (1.14-1.56 times as high), SSP2 (1.12-1.49 times as high), SSP4 (1.08-1.38 times as high) and SSP3 (1.08-1.36 times as high). Future country yield growth varies substantially by income level as well as by crop and by SSP. These yield pathways offer a new baseline for addressing the interdisciplinary questions related to global agricultural development, food security and climate change.

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.

Pathogenesis-related proteins and peptides as promising tools for engineering plants with multiple stress tolerance.

PubMed

Ali, Sajad; Ganai, Bashir Ahmad; Kamili, Azra N; Bhat, Ajaz Ali; Mir, Zahoor Ahmad; Bhat, Javaid Akhter; Tyagi, Anshika; Islam, Sheikh Tajamul; Mushtaq, Muntazir; Yadav, Prashant; Rawat, Sandhya; Grover, Anita

Pathogenesis-related (PR) proteins and antimicrobial peptides (AMPs) are a group of diverse molecules that are induced by phytopathogens as well as defense related signaling molecules. They are the key components of plant innate immune system especially systemic acquired resistance (SAR), and are widely used as diagnostic molecular markers of defense signaling pathways. Although, PR proteins and peptides have been isolated much before but their biological function remains largely enigmatic despite the availability of new scientific tools. The earlier studies have demonstrated that PR genes provide enhanced resistance against both biotic and abiotic stresses, which make them one of the most promising candidates for developing multiple stress tolerant crop varieties. In this regard, plant genetic engineering technology is widely accepted as one of the most fascinating approach to develop the disease resistant transgenic crops using different antimicrobial genes like PR genes. Overexpression of PR genes (chitinase, glucanase, thaumatin, defensin and thionin) individually or in combination have greatly uplifted the level of defense response in plants against a wide range of pathogens. However, the detailed knowledge of signaling pathways that regulates the expression of these versatile proteins is critical for improving crop plants to multiple stresses, which is the future theme of plant stress biology. Hence, this review provides an overall overview on the PR proteins like their classification, role in multiple stresses (biotic and abiotic) as well as in various plant defense signaling cascades. We also highlight the success and snags of transgenic plants expressing PR proteins and peptides. Copyright © 2018 Elsevier GmbH. All rights reserved.

Interactions between Bt crops and aquatic ecosystems: A review.

PubMed

Venter, Hermoine J; Bøhn, Thomas

2016-12-01

The term Bt crops collectively refers to crops that have been genetically modified to include a gene (or genes) sourced from Bacillus thuringiensis (Bt) bacteria. These genes confer the ability to produce proteins toxic to certain insect pests. The interaction between Bt crops and adjacent aquatic ecosystems has received limited attention in research and risk assessment, despite the fact that some Bt crops have been in commercial use for 20 yr. Reports of effects on aquatic organisms such as Daphnia magna, Elliptio complanata, and Chironomus dilutus suggest that some aquatic species may be negatively affected, whereas other reports suggest that the decreased use of insecticides precipitated by Bt crops may benefit aquatic communities. The present study reviews the literature regarding entry routes and exposure pathways by which aquatic organisms may be exposed to Bt crop material, as well as feeding trials and field surveys that have investigated the effects of Bt-expressing plant material on such organisms. The present review also discusses how Bt crop development has moved past single-gene events, toward multigene stacked varieties that often contain herbicide resistance genes in addition to multiple Bt genes, and how their use (in conjunction with co-technology such as glyphosate/Roundup) may impact and interact with aquatic ecosystems. Lastly, suggestions for further research in this field are provided. Environ Toxicol Chem 2016;35:2891-2902. © 2016 SETAC. © 2016 SETAC.

Developmental Pathways Are Blueprints for Designing Successful Crops

PubMed Central

Trevaskis, Ben

2018-01-01

Genes controlling plant development have been studied in multiple plant systems. This has provided deep insights into conserved genetic pathways controlling core developmental processes including meristem identity, phase transitions, determinacy, stem elongation, and branching. These pathways control plant growth patterns and are fundamentally important to crop biology and agriculture. This review describes the conserved pathways that control plant development, using Arabidopsis as a model. Historical examples of how plant development has been altered through selection to improve crop performance are then presented. These examples, drawn from diverse crops, show how the genetic pathways controlling development have been modified to increase yield or tailor growth patterns to suit local growing environments or specialized crop management practices. Strategies to apply current progress in genomics and developmental biology to future crop improvement are then discussed within the broader context of emerging trends in plant breeding. The ways that knowledge of developmental processes and understanding of gene function can contribute to crop improvement, beyond what can be achieved by selection alone, are emphasized. These include using genome re-sequencing, mutagenesis, and gene editing to identify or generate novel variation in developmental genes. The expanding scope for comparative genomics, the possibility to engineer new developmental traits and new approaches to resolve gene–gene or gene–environment interactions are also discussed. Finally, opportunities to integrate fundamental research and crop breeding are highlighted. PMID:29922318

Overview of glyphosate-resistant weeds worldwide.

PubMed

Heap, Ian; Duke, Stephen O

2018-05-01

Glyphosate is the most widely used and successful herbicide discovered to date, but its utility is now threatened by the occurrence of several glyphosate-resistant weed species. Glyphosate resistance first appeared in Lolium rigidum in an apple orchard in Australia in 1996, ironically the year that the first glyphosate-resistant crop (soybean) was introduced in the USA. Thirty-eight weed species have now evolved resistance to glyphosate, distributed across 37 countries and in 34 different crops and six non-crop situations. Although glyphosate-resistant weeds have been identified in orchards, vineyards, plantations, cereals, fallow and non-crop situations, it is the glyphosate-resistant weeds in glyphosate-resistant crop systems that dominate the area infested and growing economic impact. Glyphosate-resistant weeds present the greatest threat to sustained weed control in major agronomic crops because this herbicide is used to control weeds with resistance to herbicides with other sites of action, and no new herbicide sites of action have been introduced for over 30 years. Industry has responded by developing herbicide resistance traits in major crops that allow existing herbicides to be used in a new way. However, over reliance on these traits will result in multiple-resistance in weeds. Weed control in major crops is at a precarious point, where we must maintain the utility of the herbicides we have until we can transition to new weed management technologies. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Developmental Pathways Are Blueprints for Designing Successful Crops.

PubMed

Trevaskis, Ben

2018-01-01

Genes controlling plant development have been studied in multiple plant systems. This has provided deep insights into conserved genetic pathways controlling core developmental processes including meristem identity, phase transitions, determinacy, stem elongation, and branching. These pathways control plant growth patterns and are fundamentally important to crop biology and agriculture. This review describes the conserved pathways that control plant development, using Arabidopsis as a model. Historical examples of how plant development has been altered through selection to improve crop performance are then presented. These examples, drawn from diverse crops, show how the genetic pathways controlling development have been modified to increase yield or tailor growth patterns to suit local growing environments or specialized crop management practices. Strategies to apply current progress in genomics and developmental biology to future crop improvement are then discussed within the broader context of emerging trends in plant breeding. The ways that knowledge of developmental processes and understanding of gene function can contribute to crop improvement, beyond what can be achieved by selection alone, are emphasized. These include using genome re-sequencing, mutagenesis, and gene editing to identify or generate novel variation in developmental genes. The expanding scope for comparative genomics, the possibility to engineer new developmental traits and new approaches to resolve gene-gene or gene-environment interactions are also discussed. Finally, opportunities to integrate fundamental research and crop breeding are highlighted.

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

Monitoring cover crops using radar remote sensing in southern Ontario, Canada

NASA Astrophysics Data System (ADS)

Shang, J.; Huang, X.; Liu, J.; Wang, J.

2016-12-01

Information on agricultural land surface conditions is important for developing best land management practices to maintain the overall health of the fields. The climate condition supports one harvest per year for the majority of the field crops in Canada, with a relative short growing season between May and September. During the non-growing-season months (October to the following April), many fields are traditionally left bare. In more recent year, there has been an increased interest in planting cover crops. Benefits of cover crops include boosting soil organic matters, preventing soil from erosion, retaining soil moisture, and reducing surface runoff hence protecting water quality. Optical remote sensing technology has been exploited for monitoring cover crops. However limitations inherent to optical sensors such as cloud interference and signal saturation (when leaf area index is above 2.5) impeded its operational application. Radar remote sensing on the other hand is not hindered by unfavorable weather conditions, and the signal continues to be sensitive to crop growth beyond the saturation point of optical sensors. It offers a viable means for capturing timely information on field surface conditions (with or without crop cover) or crop development status. This research investigated the potential of using multi-temporal RADARSAT-2 C-band synthetic aperture radar (SAR) data collected in 2015 over multiple fields of winter wheat, corn and soybean crops in southern Ontario, Canada, to retrieve information on the presence of cover crops and their growth status. Encouraging results have been obtained. This presentation will report the methodology developed and the results obtained.

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

Performance and cross-crop resistance of Cry1F-maize selected Spodoptera frugiperda on transgenic Bt cotton: implications for resistance management

PubMed Central

Yang, Fei; Kerns, David L.; Brown, Sebe; Kurtz, Ryan; Dennehy, Tim; Braxton, Bo; Head, Graham; Huang, Fangneng

2016-01-01

Transgenic crops producing Bacillus thuringiensis (Bt) proteins have become a primary tool in pest management. Due to the intensive use of Bt crops, resistance of the fall armyworm, Spodoptera frugiperda, to Cry1F maize has occurred in Puerto Rico, Brazil, and some areas of the southeastern U.S. The sustainability of Bt crops faces a great challenge because the Cry1F-maize resistant S. frugiperda may also infest other Bt crops in multiple cropping ecosystems. Here we examined the survival and plant injury of a S. frugiperda population selected with Cry1F maize on three single-gene and five pyramided Bt cotton products. Larvae of Cry1F-susceptible (SS), -heterozygous (RS), and -resistant (RR) genotypes of S. frugiperda were all susceptible to the pyramided cotton containing Cry1Ac/Cry2Ab, Cry1Ac/Cry1F/Vip3A, Cry1Ab/Cry2Ae, or Cry1Ab/Cry2Ae/Vip3A, and the single-gene Cry2Ae cotton. Pyramided cotton containing Cry1Ac/Cry1F was effective against SS and RS, but not for RR. These findings show that the Cry1F-maize selected S. frugiperda can cause cross-crop resistance to other Bt crops expressing similar insecticidal proteins. Resistance management and pest management programs that utilize diversify mortality factors must be implemented to ensure the sustainability of Bt crops. This is especially important in areas where resistance to single-gene Bt crops is already widespread. PMID:27301612

Performance and cross-crop resistance of Cry1F-maize selected Spodoptera frugiperda on transgenic Bt cotton: implications for resistance management.

PubMed

Yang, Fei; Kerns, David L; Brown, Sebe; Kurtz, Ryan; Dennehy, Tim; Braxton, Bo; Head, Graham; Huang, Fangneng

2016-06-15

Transgenic crops producing Bacillus thuringiensis (Bt) proteins have become a primary tool in pest management. Due to the intensive use of Bt crops, resistance of the fall armyworm, Spodoptera frugiperda, to Cry1F maize has occurred in Puerto Rico, Brazil, and some areas of the southeastern U.S. The sustainability of Bt crops faces a great challenge because the Cry1F-maize resistant S. frugiperda may also infest other Bt crops in multiple cropping ecosystems. Here we examined the survival and plant injury of a S. frugiperda population selected with Cry1F maize on three single-gene and five pyramided Bt cotton products. Larvae of Cry1F-susceptible (SS), -heterozygous (RS), and -resistant (RR) genotypes of S. frugiperda were all susceptible to the pyramided cotton containing Cry1Ac/Cry2Ab, Cry1Ac/Cry1F/Vip3A, Cry1Ab/Cry2Ae, or Cry1Ab/Cry2Ae/Vip3A, and the single-gene Cry2Ae cotton. Pyramided cotton containing Cry1Ac/Cry1F was effective against SS and RS, but not for RR. These findings show that the Cry1F-maize selected S. frugiperda can cause cross-crop resistance to other Bt crops expressing similar insecticidal proteins. Resistance management and pest management programs that utilize diversify mortality factors must be implemented to ensure the sustainability of Bt crops. This is especially important in areas where resistance to single-gene Bt crops is already widespread.

A survey of crop-derived transgenes in activated and digester sludges in wastewater treatment plants in the United States.

PubMed

Gardner, Courtney M; Gwin, Carley A; Gunsch, Claudia K

2018-04-01

The use of transgenic crops has become increasingly common in the United States over the last several decades. Increasing evidence suggests that DNA may be protected from enzymatic digestion and acid hydrolysis in the digestive tract, suggesting that crop-derived transgenes may enter into wastewater treatment plants (WWTPs) intact. Given the historical use of antibiotic resistance genes as selection markers in transgenic crop development, it is important to consider the fate of these transgenes. Herein we detected and quantified crop-derived transgenes in WWTPs. All viable US WWTP samples were found to contain multiple gene targets (p35, nos, bla and nptII) at significantly higher levels than control samples. Control wastewater samples obtained from France, where transgenic crops are not cultivated, contained significantly fewer copies of the nptII gene than US activated and digester sludges. No significant differences were measured for the bla antibiotic resistance gene (ARG). In addition, a nested PCR (polymerase chain reaction) assay was developed that targeted the bla ARG located in regions flanked by the p35 promoter and nos terminator. Overall this work suggests that transgenic crops may have provided an environmental source of nptII; however, follow-up studies are needed to ascertain the viability of these genes as they exit WWTPs.

Optimizing Irrigation Water Allocation under Multiple Sources of Uncertainty in an Arid River Basin

NASA Astrophysics Data System (ADS)

Wei, Y.; Tang, D.; Gao, H.; Ding, Y.

2015-12-01

Population growth and climate change add additional pressures affecting water resources management strategies for meeting demands from different economic sectors. It is especially challenging in arid regions where fresh water is limited. For instance, in the Tailanhe River Basin (Xinjiang, China), a compromise must be made between water suppliers and users during drought years. This study presents a multi-objective irrigation water allocation model to cope with water scarcity in arid river basins. To deal with the uncertainties from multiple sources in the water allocation system (e.g., variations of available water amount, crop yield, crop prices, and water price), the model employs a interval linear programming approach. The multi-objective optimization model developed from this study is characterized by integrating eco-system service theory into water-saving measures. For evaluation purposes, the model is used to construct an optimal allocation system for irrigation areas fed by the Tailan River (Xinjiang Province, China). The objective functions to be optimized are formulated based on these irrigation areas' economic, social, and ecological benefits. The optimal irrigation water allocation plans are made under different hydroclimate conditions (wet year, normal year, and dry year), with multiple sources of uncertainty represented. The modeling tool and results are valuable for advising decision making by the local water authority—and the agricultural community—especially on measures for coping with water scarcity (by incorporating uncertain factors associated with crop production planning).

7 CFR 718.6 - Controlled substance.

Code of Federal Regulations, 2010 CFR

2010-01-01

... MARKETING QUOTAS, ACREAGE ALLOTMENTS, AND PRODUCTION ADJUSTMENT PROVISIONS APPLICABLE TO MULTIPLE PROGRAMS... four succeeding crop years, for any of the following USDA benefits: (i) Any payments or benefits under...

Automated phenotyping of permanent crops

NASA Astrophysics Data System (ADS)

McPeek, K. Thomas; Steddom, Karl; Zamudio, Joseph; Pant, Paras; Mullenbach, Tyler

2017-05-01

AGERpoint is defining a new technology space for the growers' industry by introducing novel applications for sensor technology and data analysis to growers of permanent crops. Serving data to a state-of-the-art analytics engine from a cutting edge sensor platform, a new paradigm in precision agriculture is being developed that allows growers to understand the unique needs of each tree, bush or vine in their operation. Autonomous aerial and terrestrial vehicles equipped with multiple varieties of remote sensing technologies give AGERpoint the ability to measure key morphological and spectral features of permanent crops. This work demonstrates how such phenotypic measurements combined with machine learning algorithms can be used to determine the variety of crops (e.g., almond and pecan trees). This phenotypic and varietal information represents the first step in enabling growers with the ability to tailor their management practices to individual plants and maximize their economic productivity.

Forest amount affects soybean productivity in Brazilian agricultural frontier

NASA Astrophysics Data System (ADS)

Rattis, L.; Brando, P. M.; Marques, E. Q.; Queiroz, N.; Silverio, D. V.; Macedo, M.; Coe, M. T.

2017-12-01

Over the past three decades, large tracts of tropical forests have been converted to crop and pasturelands across southern Amazonia, largely to meet the increasing worldwide demand for protein. As the world's population continue to grow and consume more protein per capita, forest conversion to grow more crops could be a potential solution to meet such demand. However, widespread deforestation is expected to negatively affect crop productivity via multiple pathways (e.g., thermal regulation, rainfall, local moisture, pest control, among others). To quantify how deforestation affects crop productivity, we modeled the relationship between forest amount and enhanced vegetation index (EVI—a proxy for crop productivity) during the soybean planting season across southern Amazonia. Our hypothesis that forest amount causes increased crop productivity received strong support. We found that the maximum MODIS-based EVI in soybean fields increased as a function of forest amount across three spatial-scales, 0.5 km, 1 km, 2 km, 5 km, 10 km, 15 km and 20 km. However, the strength of this relationship varied across years and with precipitation, but only at the local scale (e.g., 500 meters and 1 km radius). Our results highlight the importance of considering forests to design sustainable landscapes.

Complementarity among natural enemies enhances pest suppression.

PubMed

Dainese, Matteo; Schneider, Gudrun; Krauss, Jochen; Steffan-Dewenter, Ingolf

2017-08-15

Natural enemies have been shown to be effective agents for controlling insect pests in crops. However, it remains unclear how different natural enemy guilds contribute to the regulation of pests and how this might be modulated by landscape context. In a field exclusion experiment in oilseed rape (OSR), we found that parasitoids and ground-dwelling predators acted in a complementary way to suppress pollen beetles, suggesting that pest control by multiple enemies attacking a pest during different periods of its occurrence in the field improves biological control efficacy. The density of pollen beetle significantly decreased with an increased proportion of non-crop habitats in the landscape. Parasitism had a strong effect on pollen beetle numbers in landscapes with a low or intermediate proportion of non-crop habitats, but not in complex landscapes. Our results underline the importance of different natural enemy guilds to pest regulation in crops, and demonstrate how biological control can be strengthened by complementarity among natural enemies. The optimization of natural pest control by adoption of specific management practices at local and landscape scales, such as establishing non-crop areas, low-impact tillage, and temporal crop rotation, could significantly reduce dependence on pesticides and foster yield stability through ecological intensification in agriculture.

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

NASA Astrophysics Data System (ADS)

Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

2013-11-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991-2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha-1, but it decreased to 4.6-10.1 kg ha-1 with winter cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha-1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implement of winter cover crop programs, in part by helping to target critical pollution source areas for winter cover crop implementation.

Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice

PubMed Central

Jones, Susan; Baizan-Edge, Amanda; MacFarlane, Stuart; Torrance, Lesley

2017-01-01

Viruses cause significant yield and quality losses in a wide variety of cultivated crops. Hence, the detection and identification of viruses is a crucial facet of successful crop production and of great significance in terms of world food security. Whilst the adoption of molecular techniques such as RT-PCR has increased the speed and accuracy of viral diagnostics, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses. Therefore, unknown viruses can be missed and testing can be slow and expensive if molecular tests are unavailable. Methods for simultaneous detection of multiple viruses have been developed, and (NGS) is now a principal focus of this area, as it enables unbiased and hypothesis-free testing of plant samples. The development of NGS protocols capable of detecting multiple known and emergent viruses present in infected material is proving to be a major advance for crops, nuclear stocks or imported plants and germplasm, in which disease symptoms are absent, unspecific or only triggered by multiple viruses. Researchers want to answer the question “how many different viruses are present in this crop plant?” without knowing what they are looking for: RNA-sequencing (RNA-seq) of plant material allows this question to be addressed. As well as needing efficient nucleic acid extraction and enrichment protocols, virus detection using RNA-seq requires fast and robust bioinformatics methods to enable host sequence removal and virus classification. In this review recent studies that use RNA-seq for virus detection in a variety of crop plants are discussed with specific emphasis on the computational methods implemented. The main features of a number of specific bioinformatics workflows developed for virus detection from NGS data are also outlined and possible reasons why these have not yet been widely adopted are discussed. The review concludes by discussing the future directions of this field, including the use of bioinformatics tools for virus detection deployed in analytical environments using cloud computing. PMID:29123534

Influences of climate on aflatoxin producing fungi and aflatoxin contamination.

PubMed

Cotty, Peter J; Jaime-Garcia, Ramon

2007-10-20

Aflatoxins are potent mycotoxins that cause developmental and immune system suppression, cancer, and death. As a result of regulations intended to reduce human exposure, crop contamination with aflatoxins causes significant economic loss for producers, marketers, and processors of diverse susceptible crops. Aflatoxin contamination occurs when specific fungi in the genus Aspergillus infect crops. Many industries frequently affected by aflatoxin contamination know from experience and anecdote that fluctuations in climate impact the extent of contamination. Climate influences contamination, in part, by direct effects on the causative fungi. As climate shifts, so do the complex communities of aflatoxin-producing fungi. This includes changes in the quantity of aflatoxin-producers in the environment and alterations to fungal community structure. Fluctuations in climate also influence predisposition of hosts to contamination by altering crop development and by affecting insects that create wounds on which aflatoxin-producers proliferate. Aflatoxin contamination is prevalent both in warm humid climates and in irrigated hot deserts. In temperate regions, contamination may be severe during drought. The contamination process is frequently broken down into two phases with the first phase occurring on the developing crop and the second phase affecting the crop after maturation. Rain and temperature influence the phases differently with dry, hot conditions favoring the first and warm, wet conditions favoring the second. Contamination varies with climate both temporally and spatially. Geostatistics and multiple regression analyses have shed light on influences of weather on contamination. Geostatistical analyses have been used to identify recurrent contamination patterns and to match these with environmental variables. In the process environmental conditions with the greatest impact on contamination are identified. Likewise, multiple regression analyses allow ranking of environmental variables based on relative influence on contamination. Understanding the impact of climate may allow development of improved management procedures, better allocation of monitoring efforts, and adjustment of agronomic practices in anticipation of global climate change.

Assessment of crop growth and soil water modules in SWAT2000 using extensive field experiment data in an irrigation district of the Yellow River Basin

USGS Publications Warehouse

Luo, Y.; He, C.; Sophocleous, M.; Yin, Z.; Hongrui, R.; Ouyang, Z.

2008-01-01

SWAT, a physically-based, hydrological model simulates crop growth, soil water and groundwater movement, and transport of sediment and nutrients at both the process and watershed scales. While the different versions of SWAT have been widely used throughout the world for agricultural and water resources applications, little has been done to test the performance, variability, and transferability of the parameters in the crop growth, soil water, and groundwater modules in an integrated way with multiple sets of field experimental data at the process scale. Using an multiple years of field experimental data of winter wheat (Triticum aestivum L.) in the irrigation district of the Yellow River Basin, this paper assesses the performance of the plant-soil-groundwater modules and the variability and transferability of SWAT2000. Comparison of the simulated results by SWAT to the observations showed that SWAT performed quite unsatisfactorily in LAI predictions during the senescence stage, in yield predictions, and in soil-water estimation under dry soil-profile conditions. The unsatisfactory performance in LAI prediction might be attributed to over-simplified senescence modeling; in yield prediction to the improper computation of the harvest index; and in soil water under dry conditions to the exclusion of groundwater evaporation from the soil water balance in SWAT. In this paper, improvements in crop growth, soil water, and groundwater modules in SWAT were implemented. The saturated soil profile was coupled to the oscillating groundwater table. A variable evaporation coefficient taking into account soil water deficit index, groundwater depth, and crop root depth was used to replace the fixed coefficient in computing groundwater evaporation. The soil water balance included the groundwater evaporation. The modifications improved simulations of crop evapotranspiration and biomass as well as soil water dynamics under dry soil-profile conditions. The evaluation shows that the crop growth and soil water components of SWAT could be further refined to better simulate the hydrology of agricultural watersheds. ?? 2008 Elsevier B.V. All rights reserved.

Recent advances in development of marker-free transgenic plants: regulation and biosafety concern.

PubMed

Tuteja, Narendra; Verma, Shiv; Sahoo, Ranjan Kumar; Raveendar, Sebastian; Reddy, I N Bheema Lingeshwara

2012-03-01

During the efficient genetic transformation of plants with the gene of interest, some selectable marker genes are also used in order to identify the transgenic plant cells or tissues. Usually, antibiotic- or herbicide-selective agents and their corresponding resistance genes are used to introduce economically valuable genes into crop plants. From the biosafety authority and consumer viewpoints, the presence of selectable marker genes in released transgenic crops may be transferred to weeds or pathogenic microorganisms in the gastrointestinal tract or soil, making them resistant to treatment with herbicides or antibiotics, respectively. Sexual crossing also raises the problem of transgene expression because redundancy of transgenes in the genome may trigger homology-dependent gene silencing. The future potential of transgenic technologies for crop improvement depends greatly on our abilities to engineer stable expression of multiple transgenic traits in a predictable fashion and to prevent the transfer of undesirable transgenic material to non-transgenic crops and related species. Therefore, it is now essential to develop an efficient marker-free transgenic system. These considerations underline the development of various approaches designed to facilitate timely elimination of transgenes when their function is no longer needed. Due to the limiting number of available selectable marker genes, in future the stacking of transgenes will be increasingly desirable. The production of marker-free transgenic plants is now a critical requisite for their commercial deployment and also for engineering multiple and complex trait. Here we describe the current technologies to eliminate the selectable marker genes (SMG) in order to develop marker-free transgenic plants and also discuss the regulation and biosafety concern of genetically modified (GM) crops.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Bringing a transgenic crop to market: where compositional analysis fits.

PubMed

Privalle, Laura S; Gillikin, Nancy; Wandelt, Christine

2013-09-04

In the process of developing a biotechnology product, thousands of genes and transformation events are evaluated to select the event that will be commercialized. The ideal event is identified on the basis of multiple characteristics including trait efficacy, the molecular characteristics of the insert, and agronomic performance. Once selected, the commercial event is subjected to a rigorous safety evaluation taking a multipronged approach including examination of the safety of the gene and gene product - the protein, plant performance, impact of cultivating the crop on the environment, agronomic performance, and equivalence of the crop/food to conventional crops/food - by compositional analysis. The compositional analysis is composed of a comparison of the nutrient and antinutrient composition of the crop containing the event, its parental line (variety), and other conventional lines (varieties). Different geographies have different requirements for the compositional analysis studies. Parameters that vary include the number of years (seasons) and locations (environments) to be evaluated, the appropriate comparator(s), analytes to be evaluated, and statistical analysis. Specific examples of compositional analysis results will be presented.

Assessing cover crop management under actual and climate change conditions.

PubMed

Alonso-Ayuso, María; Quemada, Miguel; Vanclooster, Marnik; Ruiz-Ramos, Margarita; Rodriguez, Alfredo; Gabriel, José Luis

2018-04-15

The termination date is recognized as a key management factor to enhance cover crops for multiple benefits and to avoid competition with the following cash crop. However, the optimum date depends on annual meteorological conditions, and climate variability induces uncertainty in a decision that needs to be taken every year. One of the most important cover crop benefits is reducing nitrate leaching, a major concern for irrigated agricultural systems and highly affected by the termination date. This study aimed to determine the effects of cover crops and their termination date on the water and N balances of an irrigated Mediterranean agroecosystem under present and future climate conditions. For that purpose, two field experiments were used for inverse calibration and validation of the WAVE model (Water and Agrochemicals in the soil and Vadose Environment), based on continuous soil water content data, soil nitrogen content and crop measurements. The calibrated and validated model was subsequently used in advanced scenario analysis under present and climate change conditions. Under present conditions, a late termination date increased cover crop biomass and subsequently soil water and N depletion. Hence, preemptive competition risk with the main crop was enhanced, but a reduction of nitrate leaching also occurred. The hypothetical planting date of the following cash crop was also an important tool to reduce preemptive competition. Under climate change conditions, the simulations showed that the termination date will be even more important to reduce preemptive competition and nitrate leaching. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Impact of seasonal forecast use on agricultural income in a system with varying crop costs and returns: an empirically-grounded simulation

NASA Astrophysics Data System (ADS)

Gunda, T.; Bazuin, J. T.; Nay, J.; Yeung, K. L.

2017-03-01

Access to seasonal climate forecasts can benefit farmers by allowing them to make more informed decisions about their farming practices. However, it is unclear whether farmers realize these benefits when crop choices available to farmers have different and variable costs and returns; multiple countries have programs that incentivize production of certain crops while other crops are subject to market fluctuations. We hypothesize that the benefits of forecasts on farmer livelihoods will be moderated by the combined impact of differing crop economics and changing climate. Drawing upon methods and insights from both physical and social sciences, we develop a model of farmer decision-making to evaluate this hypothesis. The model dynamics are explored using empirical data from Sri Lanka; primary sources include survey and interview information as well as game-based experiments conducted with farmers in the field. Our simulations show that a farmer using seasonal forecasts has more diversified crop selections, which drive increases in average agricultural income. Increases in income are particularly notable under a drier climate scenario, when a farmer using seasonal forecasts is more likely to plant onions, a crop with higher possible returns. Our results indicate that, when water resources are scarce (i.e. drier climate scenario), farmer incomes could become stratified, potentially compounding existing disparities in farmers’ financial and technical abilities to use forecasts to inform their crop selections. This analysis highlights that while programs that promote production of certain crops may ensure food security in the short-term, the long-term implications of these dynamics need careful evaluation.

Current perspectives on genetically modified crops and detection methods.

PubMed

Kamle, Madhu; Kumar, Pradeep; Patra, Jayanta Kumar; Bajpai, Vivek K

2017-07-01

Genetically modified (GM) crops are the fastest adopted commodities in the agribiotech industry. This market penetration should provide a sustainable basis for ensuring food supply for growing global populations. The successful completion of two decades of commercial GM crop production (1996-2015) is underscored by the increasing rate of adoption of genetic engineering technology by farmers worldwide. With the advent of introduction of multiple traits stacked together in GM crops for combined herbicide tolerance, insect resistance, drought tolerance or disease resistance, the requirement of reliable and sensitive detection methods for tracing and labeling genetically modified organisms in the food/feed chain has become increasingly important. In addition, several countries have established threshold levels for GM content which trigger legally binding labeling schemes. The labeling of GM crops is mandatory in many countries (such as China, EU, Russia, Australia, New Zealand, Brazil, Israel, Saudi Arabia, Korea, Chile, Philippines, Indonesia, Thailand), whereas in Canada, Hong Kong, USA, South Africa, and Argentina voluntary labeling schemes operate. The rapid adoption of GM crops has increased controversies, and mitigating these issues pertaining to the implementation of effective regulatory measures for the detection of GM crops is essential. DNA-based detection methods have been successfully employed, while the whole genome sequencing using next-generation sequencing (NGS) technologies provides an advanced means for detecting genetically modified organisms and foods/feeds in GM crops. This review article describes the current status of GM crop commercialization and discusses the benefits and shortcomings of common and advanced detection systems for GMs in foods and animal feeds.

Genome-wide analysis of allele frequency change in sunflower crop-wild hybrid populations evolving under natural conditions.

PubMed

Corbi, Jonathan; Baack, Eric J; Dechaine, Jennifer M; Seiler, Gerald; Burke, John M

2018-01-01

Crop-wild hybridization occurs in numerous plant species and could alter the genetic structure and evolutionary dynamics of wild populations. Studying crop-derived alleles in wild populations is also relevant to assessing/mitigating the risks associated with transgene escape. To date, crop-wild hybridization has generally been examined via short-term studies, typically within a single generation, focusing on few traits or genetic markers. Little is known about patterns of selection on crop-derived alleles over multiple generations, particularly at a genome-wide scale. Here, we documented patterns of natural selection in an experimental crop × wild sunflower population that was allowed to evolve under natural conditions for two generations at two locations. Allele frequencies at a genome-wide collection of SNPs were tracked across generations, and a common garden experiment was conducted to compare trait means between generations. These data allowed us to identify instances of selection on crop-derived alleles/traits and, in concert with QTL mapping results, test for congruence between our genotypic and phenotypic results. We found that natural selection overwhelmingly favours wild alleles and phenotypes. However, crop alleles in certain genomic regions can be favoured, and these changes often occurred in parallel across locations. We did not, however, consistently observe close agreement between our genotypic and phenotypic results. For example, when a trait evolved towards the wild phenotype, wild QTL alleles associated with that trait did not consistently increase in frequency. We discuss these results in the context of crop allele introgression into wild populations and implications for the management of GM crops. © 2017 John Wiley & Sons Ltd.

Genetically modified crops: detection strategies and biosafety issues.

PubMed

Kamle, Suchitra; Ali, Sher

2013-06-15

Genetically modified (GM) crops are increasingly gaining acceptance but concurrently consumers' concerns are also increasing. The introduction of Bacillus thuringiensis (Bt) genes into the plants has raised issues related to its risk assessment and biosafety. The International Regulations and the Codex guidelines regulate the biosafety requirements of the GM crops. In addition, these bodies synergize and harmonize the ethical issues related to the release and use of GM products. The labeling of GM crops and their products are mandatory if the genetically modified organism (GMO) content exceeds the levels of a recommended threshold. The new and upcoming GM crops carrying multiple stacked traits likely to be commercialized soon warrant sensitive detection methods both at the DNA and protein levels. Therefore, traceability of the transgene and its protein expression in GM crops is an important issue that needs to be addressed on a priority basis. The advancement in the area of molecular biology has made available several bioanalytical options for the detection of GM crops based on DNA and protein markers. Since the insertion of a gene into the host genome may even cause copy number variation, this may be uncovered using real time PCR. Besides, assessing the exact number of mRNA transcripts of a gene, correlation between the template activity and expressed protein may be established. Here, we present an overview on the production of GM crops, their acceptabilities, detection strategies, biosafety issues and potential impact on society. Further, overall future prospects are also highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1975-01-01

A model was developed for predicting the day 50 percent of the wheat crop is planted in North Dakota. This model incorporates location as an independent variable. The Julian date when 50 percent of the crop was planted for the nine divisions of North Dakota for seven years was regressed on the 49 variables through the step-down multiple regression procedure. This procedure begins with all of the independent variables and sequentially removes variables that are below a predetermined level of significance after each step. The prediction equation was tested on daily data. The accuracy of the model is considered satisfactory for finding the historic dates on which to initiate yield prediction model. Growth prediction models were also developed for spring wheat.

Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Franch, Belen; Vermote, Eric; Roger, Jean-Claude; Becker-Reshef, Inbal; Justice, Christopher; Kussul, Nataliia

2017-01-01

Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species

PubMed Central

Modise, David M.; Gemeildien, Junaid; Ndimba, Bongani K.; Christoffels, Alan

2018-01-01

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. Conclusions We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species. PMID:29590108

Prairie strips improve biodiversity and the delivery of multiple ecosystem services from corn–soybean croplands

PubMed Central

Helmers, Matthew J.; Liebman, Matt; James, David E.; Kolka, Randall K.; O’Neal, Matthew E.; Tomer, Mark D.; Tyndall, John C.; Asbjornsen, Heidi; Drobney, Pauline; Neal, Jeri; Van Ryswyk, Gary; Witte, Chris

2017-01-01

Loss of biodiversity and degradation of ecosystem services from agricultural lands remain important challenges in the United States despite decades of spending on natural resource management. To date, conservation investment has emphasized engineering practices or vegetative strategies centered on monocultural plantings of nonnative plants, largely excluding native species from cropland. In a catchment-scale experiment, we quantified the multiple effects of integrating strips of native prairie species amid corn and soybean crops, with prairie strips arranged to arrest run-off on slopes. Replacing 10% of cropland with prairie strips increased biodiversity and ecosystem services with minimal impacts on crop production. Compared with catchments containing only crops, integrating prairie strips into cropland led to greater catchment-level insect taxa richness (2.6-fold), pollinator abundance (3.5-fold), native bird species richness (2.1-fold), and abundance of bird species of greatest conservation need (2.1-fold). Use of prairie strips also reduced total water runoff from catchments by 37%, resulting in retention of 20 times more soil and 4.3 times more phosphorus. Corn and soybean yields for catchments with prairie strips decreased only by the amount of the area taken out of crop production. Social survey results indicated demand among both farming and nonfarming populations for the environmental outcomes produced by prairie strips. If federal and state policies were aligned to promote prairie strips, the practice would be applicable to 3.9 million ha of cropland in Iowa alone. PMID:28973922

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

NASA Technical Reports Server (NTRS)

Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

2015-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

Evaluating the sensitivity of agricultural model performance to different climate inputs

PubMed Central

Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

2017-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

7 CFR 760.802 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... minimum 20 percent air pore space and pH adjustment for the type of plant produced designed to prevent... during the calendar year such as grass harvested for seed, hay, and grazing. Multiple cropping means the...

7 CFR 760.802 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... minimum 20 percent air pore space and pH adjustment for the type of plant produced designed to prevent... during the calendar year such as grass harvested for seed, hay, and grazing. Multiple cropping means the...

A multiple soil ecosystem services approach to evaluate the sustainability of reduced tillage systems

NASA Astrophysics Data System (ADS)

Pérès, Guénola; Menasseri, Safya; Hallaire, Vincent; Cluzeau, Daniel; Heddadj, Djilali; Cotinet, Patrice; Manceau, Olivier; Pulleman, Mirjam

2017-04-01

In the current context of soil degradation, reduced tillage systems (including reduced soil disturbance, use of cover crops and crop rotation, and improved organic matter management) are expected to be good alternatives to conventional system which have led to a decrease of soil multi-functionality. Many studies worldwide have analysed the impact of tillage systems on different soil functions, but overran integrated view of the impact of these systems is still lacking. The SUSTAIN project (European SNOWMAN programme), performed in France and the Netherlands, proposes an interdisciplinary collaboration. The goals of SUSTAIN are to assess the multi-functionality of soil and to study how reduced-tillage systems impact on multiple ecosystem services such as soil biodiversity regulation (earthworms, nematodes, microorganisms), soil structure maintenance (aggregate stability, compaction, soil erosion), water regulation (run-off, transfer of pesticides) and food production. Moreover, a socio-economic study on farmer networks has been carried out to identify the drivers of adoption of reduced-tillage systems. Data have been collected in long-term experimental fields (5 - 13 years), representing conventional and organic farming strategies, and were complemented with data from farmer networks. The impact of different reduced tillage systems (direct seeding, minimum tillage, non-inverse tillage, superficial ploughing) were analysed and compared to conventional ploughing. Measurements (biological, chemical, physical, agronomical, water and element transfer) have been done at several dates which allow an overview of the evolution of the soil properties according to climate variation and crop rotation. A sociological approach was performed on several farms covering different production types, different courses (engagement in reduced tillage systems) and different geographical locations. Focusing on French trials, this multiple ecosystem services approach clearly showed that reduced tillage systems improved soil ecosystem services such as soil biodiversity, water regulation (quantity, quality), carbon storage and soil stability; however, the effects on crop production were more variable (-10% to +7 % range), strongly depending on crop type and agricultural practices (fertilisation, rotation, cover crop). Sociological approach showed that saving labour time and fuel costs were the main motivations for change. Agronomic and environmental benefits are not the trigger but are increasingly recognized and contribute to the maintenance of the practice. Farmers also expressed a need for stronger networking and technical advice, which plays a crucial role. Scientists and experts raise awareness, support collective learning and provide instrumental. Recommendations were provided for sustainable soil management aiming at ecological intensification of agricultural land.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Life history traits and phenotypic selection among sunflower crop–wild hybrids and their wild counterpart: implications for crop allele introgression

PubMed Central

Kost, Matthew A; Alexander, Helen M; Jason Emry, D; Mercer, Kristin L

2015-01-01

Hybridization produces strong evolutionary forces. In hybrid zones, selection can differentially occur on traits and selection intensities may differ among hybrid generations. Understanding these dynamics in crop–wild hybrid zones can clarify crop-like traits likely to introgress into wild populations and the particular hybrid generations through which introgression proceeds. In a field experiment with four crop–wild hybrid Helianthus annuus (sunflower) cross types, we measured growth and life history traits and performed phenotypic selection analysis on early season traits to ascertain the likelihood, and routes, of crop allele introgression into wild sunflower populations. All cross types overwintered, emerged in the spring, and survived until flowering, indicating no early life history barriers to crop allele introgression. While selection indirectly favored earlier seedling emergence and taller early season seedlings, direct selection only favored greater early season leaf length. Further, there was cross type variation in the intensity of selection operating on leaf length. Thus, introgression of multiple early season crop-like traits, due to direct selection for greater early season leaf length, should not be impeded by any cross type and may proceed at different rates among generations. In sum, alleles underlying early season sunflower crop-like traits are likely to introgress into wild sunflower populations. PMID:26029263

Concentrated Animal Feeding Operations, Row Crops and their Relationship to Nitrate in Eastern Iowa Rivers

PubMed Central

Weldon, Mark B.; Hornbuckle, Keri C.

2009-01-01

Concentrated animal feeding operations (CAFO) and fertilizer application to row crops may contribute to poor water quality in surface waters. To test this hypothesis, we evaluated nutrient concentrations and fluxes in four Eastern Iowa watersheds sampled between 1996-2004. We found that these watersheds contribute nearly 10% of annual nitrate flux entering the Gulf of Mexico, while representing only 1.5% of the contributing drainage basin. Mass budget analysis shows stream flow to be a major loss of nitrogen (18% of total N output), second only to crop harvest (63%). The major watershed inputs of nitrogen include applied fertilizer for corn (54% of total N input) and nitrogen fixation by soybeans (26%). Despite the relatively small input from animal manure (~5%), the results of spatial analysis indicate that row crop and CAFO densities are significantly and independently correlated to higher nitrate concentration in streams. Pearson correlation coefficients of 0.59 and 0.89 were found between nitrate concentration and row crop and CAFO density, respectively. Multiple linear regression analysis produced a correlation for nitrate concentration with an R2 value of 85%. High spatial density of row crops and CAFOs are linked to the highest river nitrate concentrations (up to 15 mg/l normalized over five years). PMID:16749677

What Happened to Nezara viridula (L.) in the Americas? Possible Reasons to Explain Populations Decline.

PubMed

Panizzi, A R; Lucini, T

2016-12-01

Once abundant in the Americas, the southern green stink bug Nezara viridula (L.) has gradually declined in numbers. Until the 1990s, it was considered the main pest of major crops such as soybean, Glycine max (L.) Merrill, particularly in southern Brazil and southern USA, as well as Argentina, Uruguay, and other countries. In the past 15+ years, a dramatic population decrease was observed to the point of now being considered a secondary pest in these referred countries. In this article, we list and discuss possible reasons which explain the decline in N. viridula population in the Americas. These factors include the following: (1) the steady increase of herbicides used in no-tillage/multiple cropping systems affecting potential hosts such as weeds in crop fields and nearby natural vegetation; (2) the change in cultivation systems, mostly in the Neotropics, favoring other species more adapted to exploit crops in modern day agriculture; (3) competition among several species of stink bugs that colonize major crops; (4) the growing impact of several species of egg parasitoids, some of them laboratory reared and released in crop fields, and other natural enemies (parasitoids and predators); and (5) the impact of global climate change affecting its distribution and biology.

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

USGS Publications Warehouse

Yeo, In-Young; Lee, Sangchui; Sadeghi, Ali M.; Beeson, Peter C.; Hively, W. Dean; McCarty, Greg W.; Lang, Megan W.

2013-01-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991–2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha−1, but it decreased to 4.6–10.1 kg ha−1 with winter cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implement of winter cover crop programs, in part by helping to target critical pollution source areas for winter cover crop implementation.

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.

Future possible crop yield scenarios under multiple SSP and RCP scenarios.

NASA Astrophysics Data System (ADS)

Sakurai, G.; Yokozawa, M.; Nishimori, M.; Okada, M.

2016-12-01

Understanding the effect of future climate change on global crop yields is one of the most important tasks for global food security. Future crop yields would be influenced by climatic factors such as the changes of temperature, precipitation and atmospheric carbon dioxide concentration. On the other hand, the effect of the changes of agricultural technologies such as crop varieties, pesticide and fertilizer input on crop yields have large uncertainty. However, not much is available on the contribution ratio of each factor under the future climate change scenario. We estimated the future global yields of four major crops (maize, soybean, rice and wheat) under three Shared Socio Economic Pathways (SSPs) and four Representative Concentration Pathways (RCPs). For this purpose, firstly, we estimated a parameter of a process based model (PRYSBI2) using a Bayesian method for each 1.125 degree spatial grid. The model parameter is relevant to the agricultural technology (we call "technological parameter" here after). Then, we analyzed the relationship between the values of technological parameter and GDP values. We found that the estimated values of the technological parameter were positively correlated with the GDP. Using the estimated relationship, we predicted future crop yield during 2020 and 2100 under SSP1, SSP2 and SSP3 scenarios and RCP 2.6, 4.5, 6.0 and 8.5. The estimated crop yields were different among SSP scenarios. However, we found that the yield difference attributable to SSPs were smaller than those attributable to CO2 fertilization effects and climate change. Particularly, the estimated effect of the change of atmospheric carbon dioxide concentration on global yields was more than four times larger than that of GDP for C3 crops.

Genetically modified (GM) crops: milestones and new advances in crop improvement.

PubMed

Kamthan, Ayushi; Chaudhuri, Abira; Kamthan, Mohan; Datta, Asis

2016-09-01

New advances in crop genetic engineering can significantly pace up the development of genetically improved varieties with enhanced yield, nutrition and tolerance to biotic and abiotic stresses. Genetically modified (GM) crops can act as powerful complement to the crops produced by laborious and time consuming conventional breeding methods to meet the worldwide demand for quality foods. GM crops can help fight malnutrition due to enhanced yield, nutritional quality and increased resistance to various biotic and abiotic stresses. However, several biosafety issues and public concerns are associated with cultivation of GM crops developed by transgenesis, i.e., introduction of genes from distantly related organism. To meet these concerns, researchers have developed alternative concepts of cisgenesis and intragenesis which involve transformation of plants with genetic material derived from the species itself or from closely related species capable of sexual hybridization, respectively. Recombinase technology aimed at site-specific integration of transgene can help to overcome limitations of traditional genetic engineering methods based on random integration of multiple copy of transgene into plant genome leading to gene silencing and unpredictable expression pattern. Besides, recently developed technology of genome editing using engineered nucleases, permit the modification or mutation of genes of interest without involving foreign DNA, and as a result, plants developed with this technology might be considered as non-transgenic genetically altered plants. This would open the doors for the development and commercialization of transgenic plants with superior phenotypes even in countries where GM crops are poorly accepted. This review is an attempt to summarize various past achievements of GM technology in crop improvement, recent progress and new advances in the field to develop improved varieties aimed for better consumer acceptance.

The role of underutilized fruits in nutritional and economic security of tribals: a review.

PubMed

Nandal, Urvashi; Bhardwaj, Raju Lal

2014-01-01

The tribal people of Rajasthan are severely malnourished along with multiple nutrient-deficiency disorders due to ignorance about importance of fruits and vegetables in their diets. The tribal areas are full of biodiversity having natural vegetation which is not harnessed fully. Due to which a wide gap is formed between health and optimal use of natural sources of nutrients, i.e., underutilized crops. The crops, which are neither grown commercially on large scale nor traded widely, may be termed as underutilized horticultural crops. These crops are cultivated, traded, and consumed locally. These crops have many advantages like easier to grow and hardy in nature, producing a crop even under adverse soil and climatic conditions. So, exploitation of underutilized horticultural crops can become a solution to the social problem of health and nutrition insecurity, poverty, and unemployment. The consumption of underutilized fruit crops can provide nutrition to the poor and needy tribals by meeting the nutrient requirements of vulnerable groups. As underutilized fruits, nuts, and vegetables are a rich of source of carbohydrates, fats, proteins, energy, vitamins-A, B1, B2, B3, B6, B9, B12, C, folic acid, and minerals-Ca, P, Fe, and dietary fiber. Thus, they have the nutritional capacity to prevent and cure various diseases like kwashiorkor, marasmus, night blindness, anemia, diabetes, cancer, hypertension, and hidden hunger. It is also established fact that seasonal, locally available, and cheap fruits and vegetables can also keep the population healthy and nutritionally secure rather than costly off-season ones. Also, the underutilized crops have the potential to give economic security to tribals by giving employment and by fetching good returns from their sale in raw form as well as value-added products.

Reproductive traits and evolutionary divergence between Mediterranean crops and their wild relatives.

PubMed

Iriondo, J M; Milla, R; Volis, S; Rubio de Casas, R

2018-01-01

Changes in reproductive traits associated with domestication critically determine the evolutionary divergence between crops and their wild relatives, as well as the potential of crop plants to become feral. In this review, we examine the genetic mechanisms of plant domestication and the different types of selection involved, and describe the particularities of domestication of Mediterranean field crops with regard to their reproductive traits, showing illustrative examples. We also explore gene flow patterns between Mediterranean field crops and their wild relatives, along with their ecological, evolutionary and economic implications. Domestication entails multiple selective processes, including direct selection, environmental adaptation and developmental constraints. In contrast to clonal propagation in perennials, sexual reproduction and seed propagation in annuals and biennials have led to a distinct pathway of evolution of reproductive traits. Thus, the initial domestication and further breeding of Mediterranean field crops has brought about changes in reproductive traits, such as higher mean values and variance of seed and fruit sizes, reduced fruit and seed toxicity, non-shattering seeds and loss of seed dormancy. Evolution under domestication is not a linear process, and bi-directional gene flow between wild and crop taxa is a frequent phenomenon. Thus, hybridisation and introgression have played a very important role in determining the genetics of current cultivars. In turn, gene flow from crops to wild relatives can lead to introgression of crop genes into wild populations and potentially alter the characteristics of natural communities. In conclusion, plant evolution under domestication has not only changed the reproductive biology of cultivated taxa, its effects are multifaceted and have implications beyond agriculture. © 2017 German Society for Plant Sciences and The Royal Botanical Society of the Netherlands.

Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids.

PubMed

Baack, Eric J; Sapir, Yuval; Chapman, Mark A; Burke, John M; Rieseberg, Loren H

2008-01-01

The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop-wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop-wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11-12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.

Content-aware automatic cropping for consumer photos

NASA Astrophysics Data System (ADS)

Tang, Hao; Tretter, Daniel; Lin, Qian

2013-03-01

Consumer photos are typically authored once, but need to be retargeted for reuse in various situations. These include printing a photo on different size paper, changing the size and aspect ratio of an embedded photo to accommodate the dynamic content layout of web pages or documents, adapting a large photo for browsing on small displays such as mobile phone screens, and improving the aesthetic quality of a photo that was badly composed at the capture time. In this paper, we propose a novel, effective, and comprehensive content-aware automatic cropping (hereafter referred to as "autocrop") method for consumer photos to achieve the above purposes. Our autocrop method combines the state-of-the-art context-aware saliency detection algorithm, which aims to infer the likely intent of the photographer, and the "branch-and-bound" efficient subwindow search optimization technique, which seeks to locate the globally optimal cropping rectangle in a fast manner. Unlike most current autocrop methods, which can only crop a photo into an arbitrary rectangle, our autocrop method can automatically crop a photo into either a rectangle of arbitrary dimensions or a rectangle of the desired aspect ratio specified by the user. The aggressiveness of the cropping operation may be either automatically determined by the method or manually indicated by the user with ease. In addition, our autocrop method is extended to support the cropping of a photo into non-rectangular shapes such as polygons of any number of sides. It may also be potentially extended to return multiple cropping suggestions, which will enable the creation of new photos to enrich the original photo collections. Our experimental results show that the proposed autocrop method in this paper can generate high-quality crops for consumer photos of various types.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

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/.

An improved UHPLC-UV method for separation and quantification of carotenoids in vegetable crops.

PubMed

Maurer, Megan M; Mein, Jonathan R; Chaudhuri, Swapan K; Constant, Howard L

2014-12-15

Carotenoid identification and quantitation is critical for the development of improved nutrition plant varieties. Industrial analysis of carotenoids is typically carried out on multiple crops with potentially thousands of samples per crop, placing critical needs on speed and broad utility of the analytical methods. Current chromatographic methods for carotenoid analysis have had limited industrial application due to their low throughput, requiring up to 60 min for complete separation of all compounds. We have developed an improved UHPLC-UV method that resolves all major carotenoids found in broccoli (Brassica oleracea L. var. italica), carrot (Daucus carota), corn (Zea mays), and tomato (Solanum lycopersicum). The chromatographic method is completed in 13.5 min allowing for the resolution of the 11 carotenoids of interest, including the structural isomers lutein/zeaxanthin and α-/β-carotene. Additional minor carotenoids have also been separated and identified with this method, demonstrating the utility of this method across major commercial food crops. Copyright © 2014 Elsevier Ltd. All rights reserved.

Possible pathways and tensions in the food and water nexus

NASA Astrophysics Data System (ADS)

Grafton, R. Quentin; Williams, John; Jiang, Qiang

2017-05-01

"Bottom-up" field-based, crop-hydrological models are used to estimate food production and irrigation water extractions under multiple scenarios of water and nitrogen use and crop yield increases from 2010 to 2050 for 19 countries. The results show: (1) a food deficit before 2050 under a worst case climate change scenario in terms of annual crop yield improvement; (2) substantial water deficits, as a result of irrigation, for major food-producing countries that will prevent these nations from meeting their domestic food requirements in the absence of investments in water infrastructure or food imports; and (3) a plateau in terms of crop food production associated with increased water extractions given no further increase in the current area of irrigated agriculture. Possible pathways to respond to the tensions in the food-water nexus are evaluated and include: (1) higher water productivity; (2) food trade; (3) improvements in both crop yield and "sustainable" total factor productivity; (4) greater investment in water infrastructure; and (5) integrative policies and decision processes. Without a combination of some, or all, of these possible pathways, appropriately adapted to bio-physical and socio-economic circumstances, the world faces grave risks in food and water security out to 2050.

Biotechnological applications in in vitro plant regeneration studies of broccoli (Brassica oleracea L. var. italica), an important vegetable crop.

PubMed

Kumar, Pankaj; Srivastava, Dinesh Kumar

2016-04-01

Biotechnology holds promise for genetic improvement of important vegetable crops. Broccoli (Brassica oleracea L. var. italica) is an important vegetable crop of the family Brassicaceae. However, various biotic and abiotic stresses cause enormous crop yield losses during commercial cultivation of broccoli. Establishment of a reliable, reproducible and efficient in vitro plant regeneration system with cell and tissue culture is a vital prerequisite for biotechnological application of crop improvement programme. An in vitro plant regeneration technique refers to culturing, cell division, cell multiplication, de-differentiation and differentiation of cells, protoplasts, tissues and organs on defined liquid/solid medium under aseptic and controlled environment. Recent progress in the field of plant tissue culture has made this area one of the most dynamic and promising in experimental biology. There are many published reports on in vitro plant regeneration studies in broccoli including direct organogenesis, indirect organogenesis and somatic embryogenesis. This review summarizes those plant regeneration studies in broccoli that could be helpful in drawing the attention of the researchers and scientists to work on it to produce healthy, biotic and abiotic stress resistant plant material and to carry out genetic transformation studies for the production of transgenic plants.

Increased yield stability of field-grown winter barley (Hordeum vulgare L.) varietal mixtures through ecological processes

PubMed Central

Creissen, Henry E.; Jorgensen, Tove H.; Brown, James K.M.

2016-01-01

Crop variety mixtures have the potential to increase yield stability in highly variable and unpredictable environments, yet knowledge of the specific mechanisms underlying enhanced yield stability has been limited. Ecological processes in genetically diverse crops were investigated by conducting field trials with winter barley varieties (Hordeum vulgare), grown as monocultures or as three-way mixtures in fungicide treated and untreated plots at three sites. Mixtures achieved yields comparable to the best performing monocultures whilst enhancing yield stability despite being subject to multiple predicted and unpredicted abiotic and biotic stresses including brown rust (Puccinia hordei) and lodging. There was compensation through competitive release because the most competitive variety overyielded in mixtures thereby compensating for less competitive varieties. Facilitation was also identified as an important ecological process within mixtures by reducing lodging. This study indicates that crop varietal mixtures have the capacity to stabilise productivity even when environmental conditions and stresses are not predicted in advance. Varietal mixtures provide a means of increasing crop genetic diversity without the need for extensive breeding efforts. They may confer enhanced resilience to environmental stresses and thus be a desirable component of future cropping systems for sustainable arable farming. PMID:27375312

Multiple Models for Rosaceae Genomics[OA

PubMed Central

Shulaev, Vladimir; Korban, Schuyler S.; Sosinski, Bryon; Abbott, Albert G.; Aldwinckle, Herb S.; Folta, Kevin M.; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M.; Lewers, Kim; Brown, Susan K.; Davis, Thomas M.; Gardiner, Susan E.; Potter, Daniel; Veilleux, Richard E.

2008-01-01

The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement. PMID:18487361

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.

Domestication of Plants in the Americas: Insights from Mendelian and Molecular Genetics

PubMed Central

Pickersgill, Barbara

2007-01-01

Background Plant domestication occurred independently in four different regions of the Americas. In general, different species were domesticated in each area, though a few species were domesticated independently in more than one area. The changes resulting from human selection conform to the familiar domestication syndrome, though different traits making up this syndrome, for example loss of dispersal, are achieved by different routes in crops belonging to different families. Genetic and Molecular Analyses of Domestication Understanding of the genetic control of elements of the domestication syndrome is improving as a result of the development of saturated linkage maps for major crops, identification and mapping of quantitative trait loci, cloning and sequencing of genes or parts of genes, and discoveries of widespread orthologies in genes and linkage groups within and between families. As the modes of action of the genes involved in domestication and the metabolic pathways leading to particular phenotypes become better understood, it should be possible to determine whether similar phenotypes have similar underlying genetic controls, or whether human selection in genetically related but independently domesticated taxa has fixed different mutants with similar phenotypic effects. Conclusions Such studies will permit more critical analysis of possible examples of multiple domestications and of the origin(s) and spread of distinctive variants within crops. They also offer the possibility of improving existing crops, not only major food staples but also minor crops that are potential export crops for developing countries or alternative crops for marginal areas. PMID:17766847

Transgenes sustain epigeal insect biodiversity in diversified vegetable farm systems.

PubMed

Leslie, T W; Hoheisel, G A; Biddinger, D J; Rohr, J R; Fleischer, S J

2007-02-01

Many ecological studies have focused on the effects of transgenes in field crops, but few have considered multiple transgenes in diversified vegetable systems. We compared the epigeal, or soil surface-dwelling, communities of Coleoptera and Formicidae between transgenic and isoline vegetable systems consisting of sweet corn, potato, and acorn squash, with transgenic cultivars expressing Cry1(A)b, Cry3, or viral coat proteins. Vegetables were grown in replicated split plots over 2 yr with integrated pest management (IPM) standards defining insecticide use patterns. More than 77.6% of 11,925 insects from 1,512 pitfall traps were identified to species, and activity density was used to compare dominance distribution, species richness, and community composition. Measures of epigeal biodiversity were always equal in transgenic vegetables, which required fewer insecticide applications than their near isolines. There were no differences in species richness between transgenic and isoline treatments at the farm system and individual crop level. Dominance distributions were also similar between transgenic and isoline farming systems. Crop type, and not genotype, had a significant influence on Carabidae and Staphylinidae community composition in the first year, but there were no treatment effects in the second year, possibly because of homogenizing effects of crop rotations. Communities were more influenced by crop type, and possibly crop rotation, than by genotype. The heterogeneity of crops and rotations in diversified vegetable farms seems to aid in preserving epigeal biodiversity, which may be supplemented by reductions in insecticide use associated with transgenic cultivars.

Integrated Systems Mitigate Land Degradation and Improve Agricultural System Sustainability

NASA Astrophysics Data System (ADS)

Landblom, Douglas; Senturklu, Songul; Cihacek, Larry; Brevik, Eric

2017-04-01

Rain-fed agricultural production supported by exogenous inputs is not sustainable because a continuous influx of expensive inputs (fertilizer, chemicals, fossil fuel, labor, tillage, and other) is required. Alternatives to traditional management allow natural occurring dynamic soil processes to provide the necessary microbial activity that supports nutrient cycling in balance with nature. Research designed to investigate the potential for integrated systems to replace expensive inputs has shown that healthy soils rich in soil organic matter (SOM) are the foundation upon which microbial nutrient cycling can reduce and eventually replace expensive fertilizer. No-till seed placement technology effectively replaces multiple-pass cultivation conserving stored soil water in semi-arid farming systems. In multi-crop rotations, cool- and warm-season crops are grown in sequence to meet goals of the integrated farming and ranching system, and each crop in the rotation complements the subsequent crop by supplying a continuous flow of essential SOM for soil nutrient cycling. Grazing animals serve an essential role in the system's sustainability as non-mechanized animal harvesters that reduce fossil fuel consumption and labor, and animal waste contributes soil nutrients to the system. Integrated systems' complementarity has contributed to greater soil nutrient cycling and crop yields, fertilizer reduction or elimination, greater yearling steer grazing net return, reduced cow wintering costs grazing crop residues, increased wildlife sightings, and reduced environmental footprint. Therefore, integrating crop and animal systems can reverse soil quality decline and adopting non-traditional procedures has resulted in a wider array of opportunities for sustainable agriculture and profitability.

77 FR 12731 - Thiamethoxam; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-02

...This regulation establishes tolerances for residues of thiamethoxam in or on multiple commodities which are identified and discussed later in this document. Syngenta Crop Protection, Inc. requested these tolerances under the Federal Food, Drug, and Cosmetic Act (FFDCA).

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

NASA Astrophysics Data System (ADS)

Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

2014-12-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (~ 50 km2) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990-2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellite-based measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha-1, but decreased to 4.6-10.1 kg ha-1 with cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of cover crops (~ 30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~ 2 kg ha-1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implementation of cover crop programs, in part by helping to target critical pollution source areas for cover crop implementation.

Method for Estimating Annual Atrazine Use for Counties in the Conterminous United States, 1992-2007

USGS Publications Warehouse

Thelin, Gail P.; Stone, Wesley W.

2010-01-01

A method was developed to estimate annual atrazine use during 1992 to 2007 on sixteen crops and four agricultural land uses. For each year, atrazine use was estimated for all counties in the conterminous United States (except California) by combining (1) proprietary data from the Doane Marketing Research-Kynetec (DMRK) AgroTrak database on the mass of atrazine applied to agricultural crops, (2) county harvested crop acreage, by county, from the 1992, 1997, 2002, and 2007 Censuses of Agriculture, and (3) annual harvested crop acreage from National Agriculture Statistics Service (NASS) for non-Census years. DMRK estimates of pesticide use on individual crops were derived from surveys of major field crops and selected specialty crops in multicounty areas referred to as Crop Reporting Districts (CRD). The CRD-level atrazine-use estimates were disaggregated to obtain county-level application rates by dividing the mass (pounds) of pesticides applied to a crop by the acreage of that crop in the CRD to yield a rate per harvested acre. When atrazine-use estimates were not available for a CRD, crop, or year, an estimated rate was developed following a hierarchy of decision rules that checked first for the availability of a crop application rate from surveyed atrazine application rate(s) for adjacent CRDs for a specific year, and second, the rates from surveyed CRDs within for U.S. Department of Agriculture Farm Production Regions for a specific year or multiple years. The estimation method applied linear interpolation to estimate crop acreage for years when harvested acres for a crop and county were not reported in either the Census of Agriculture or the NASS database, but were reported by these data sources for other years for that crop and county. Data for atrazine use for the counties in California was obtained from farmers' reports of pesticide use collected and published by the California Department of Pesticide Regulation-Pesticide Use Reporting (DPR-PUR) because these data are more complete than DMRK survey data. National and state annual atrazine-use totals derived by this method were compared with other published pesticide-use estimates and were highly correlated. The method developed is designed to be applicable to other pesticides for which there are similar data; however, for some pesticides that are applied to specialty crops, fewer surveys are usually available to estimate application rates and there are a greater number of years with unreported crop acreage, potentially resulting in greater uncertainty in use

Integrated Modeling to Assess the Impacts of Changes in Climate and Socio Economics on Agriculture in the Columbia River Basin

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Malek, K.; Nelson, R.; Stockle, C.; Brady, M.; Dinesh, S.; Barber, M. E.; Yorgey, G.; Kruger, C.

2012-12-01

The objective of this work is to assess the impacts of climate change and socio economics on agriculture in the Columbia River basin (CRB) in the Pacific Northwest region of the U.S. and a portion of Southwestern Canada. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of CRB water with 14,000 square kilometers of irrigated area. Agriculture is an important component of the region's economy, with an annual value over 5 billion in Washington State alone. Therefore, the region is relevant for applying a modeling framework that can aid agriculture decision making in the context of a changing climate. To do this, we created an integrated biophysical and socio-economic regional modeling framework that includes human and natural systems. The modeling framework captures the interactions between climate, hydrology, crop growth dynamics, water management and socio economics. The biophysical framework includes a coupled macro-scale physically-based hydrology model (the Variable Infiltration Capacity, VIC model), and crop growth model (CropSyst), as well as a reservoir operations simulation model. Water rights data and instream flow target requirements are also incorporated in the model to simulate the process of curtailment during water shortage. The economics model informs the biophysical model of the short term agricultural producer response to water shortage as well as the long term agricultural producer response to domestic growth and international trade in terms of an altered cropping pattern. The modeling framework was applied over the CRB for the historical period 1976-2006 and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Sensitivity associated with estimates of water availability, irrigation demand, crop yields, unmet demand and available instream flows due to climate inputs, hydrology and crop model parameterization, water management assumptions, model integration assumptions, as well as multiple socio economic alternatives are also presented. Compared to historical conditions, for the 2030s time period, our results show an average additional irrigation water demand requirement of 370 million cubic meters in the CRB, an increased frequency of curtailment and a revenue impact between 70 and $150 million resulting from adverse crop yield impacts due to curtailment in the state of Washington. The impacts vary spatially and some of the CRB tributary watersheds are impacted more than others, e.g., unmet demand in the Yakima River basin is expected to increase by 50%. Increased irrigation demand, coupled with decreased seasonal supply poses difficult water resources management questions in the region.

Assessing Climate Risk on Agricultural Production: Insights Using Retrospective Analysis of Crop Insurance and Climatic Trends

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Elias, E.; Eischens, A.; Shilts, M.; Rango, A.; Steele, R.

2017-12-01

The collaborative synthesis of existing datasets, such as long-term climate observations and farmers' crop insurance payments, can increase their overall collective value and societal application. The U.S. Department of Agriculture (USDA) Climate Hubs were created to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this mission, Hubs work across USDA and other climate service agencies to synthesize existing information. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program which currently insures over $100 billion in crops annually. RMA hosts data describing the cause for loss (e.g. drought, wind, irrigation failure) and indemnity amount (i.e. total cost of loss) at multiple spatio-temporal scales (i.e. state, county, year, month). The objective of this paper is to link climate information with indemnities, and their associated cause of loss, to assess climate risk on agricultural production and provide regionally-relevant information to stakeholders to promote resilient working landscapes. We performed a retrospective trend analysis at the state-level for the American Southwest (SW). First, we assessed indemnity-only trends by cause of loss and crop type at varying temporal scales. Historical monthly weather data (i.e. precipitation and temperature) and long-term drought indices (e.g. Palmer Drought Severity Index) were then linked with indemnities and grouped by different causes of loss. Climatological ranks were used to integrate historical comparative intensity of acute and long-term climatic events. Heat and drought as causes of loss were most correlated with temperature and drought indicators, respectively. Across all SW states increasing indemnities were correlated with warmer conditions. Multiple statistical trend analyses suggest a framework is necessary to appropriately measure the biophysical signals in crop insurance trends taking into account spatio-temporal characteristics. Based on stakeholder feedback, we also developed a web-based information browser to visualize and assess indemnity trends providing useful and usable knowledge to support informed land management decisions and ecosystem resilience.

A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley, California

NASA Astrophysics Data System (ADS)

Ransom, Katherine M.; Bell, Andrew M.; Barber, Quinn E.; Kourakos, George; Harter, Thomas

2018-05-01

This study is focused on nitrogen loading from a wide variety of crop and land-use types in the Central Valley, California, USA, an intensively farmed region with high agricultural crop diversity. Nitrogen loading rates for several crop types have been measured based on field-scale experiments, and recent research has calculated nitrogen loading rates for crops throughout the Central Valley based on a mass balance approach. However, research is lacking to infer nitrogen loading rates for the broad diversity of crop and land-use types directly from groundwater nitrate measurements. Relating groundwater nitrate measurements to specific crops must account for the uncertainty about and multiplicity in contributing crops (and other land uses) to individual well measurements, and for the variability of nitrogen loading within farms and from farm to farm for the same crop type. In this study, we developed a Bayesian regression model that allowed us to estimate land-use-specific groundwater nitrogen loading rate probability distributions for 15 crop and land-use groups based on a database of recent nitrate measurements from 2149 private wells in the Central Valley. The water and natural, rice, and alfalfa and pasture groups had the lowest median estimated nitrogen loading rates, each with a median estimate below 5 kg N ha-1 yr-1. Confined animal feeding operations (dairies) and citrus and subtropical crops had the greatest median estimated nitrogen loading rates at approximately 269 and 65 kg N ha-1 yr-1, respectively. In general, our probability-based estimates compare favorably with previous direct measurements and with mass-balance-based estimates of nitrogen loading. Nitrogen mass-balance-based estimates are larger than our groundwater nitrate derived estimates for manured and nonmanured forage, nuts, cotton, tree fruit, and rice crops. These discrepancies are thought to be due to groundwater age mixing, dilution from infiltrating river water, or denitrification between the time when nitrogen leaves the root zone (point of reference for mass-balance-derived loading) and the time and location of groundwater measurement.

Locus-specific view of flax domestication history

PubMed Central

Fu, Yong-Bi; Diederichsen, Axel; Allaby, Robin G

2012-01-01

Crop domestication has been inferred genetically from neutral markers and increasingly from specific domestication-associated loci. However, some crops are utilized for multiple purposes that may or may not be reflected in a single domestication-associated locus. One such example is cultivated flax (Linum usitatissimum L.), the earliest oil and fiber crop, for which domestication history remains poorly understood. Oil composition of cultivated flax and pale flax (L. bienne Mill.) indicates that the sad2 locus is a candidate domestication locus associated with increased unsaturated fatty acid production in cultivated flax. A phylogenetic analysis of the sad2 locus in 43 pale and 70 cultivated flax accessions established a complex domestication history for flax that has not been observed previously. The analysis supports an early, independent domestication of a primitive flax lineage, in which the loss of seed dispersal through capsular indehiscence was not established, but increased oil content was likely occurred. A subsequent flax domestication process occurred that probably involved multiple domestications and includes lineages that contain oil, fiber, and winter varieties. In agreement with previous studies, oil rather than fiber varieties occupy basal phylogenetic positions. The data support multiple paths of flax domestication for oil-associated traits before selection of the other domestication-associated traits of seed dispersal loss and fiber production. The sad2 locus is less revealing about the origin of winter tolerance. In this case, a single domestication-associated locus is informative about the history of domesticated forms with the associated trait while partially informative on forms less associated with the trait. PMID:22408732

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Assessing variable rate nitrogen fertilizer strategies within an extensively instrument field site using the MicroBasin model

NASA Astrophysics Data System (ADS)

Ward, N. K.; Maureira, F.; Yourek, M. A.; Brooks, E. S.; Stockle, C. O.

2014-12-01

The current use of synthetic nitrogen fertilizers in agriculture has many negative environmental and economic costs, necessitating improved nitrogen management. In the highly heterogeneous landscape of the Palouse region in eastern Washington and northern Idaho, crop nitrogen needs vary widely within a field. Site-specific nitrogen management is a promising strategy to reduce excess nitrogen lost to the environment while maintaining current yields by matching crop needs with inputs. This study used in-situ hydrologic, nutrient, and crop yield data from a heavily instrumented field site in the high precipitation zone of the wheat-producing Palouse region to assess the performance of the MicroBasin model. MicroBasin is a high-resolution watershed-scale ecohydrologic model with nutrient cycling and cropping algorithms based on the CropSyst model. Detailed soil mapping conducted at the site was used to parameterize the model and the model outputs were evaluated with observed measurements. The calibrated MicroBasin model was then used to evaluate the impact of various nitrogen management strategies on crop yield and nitrate losses. The strategies include uniform application as well as delineating the field into multiple zones of varying nitrogen fertilizer rates to optimize nitrogen use efficiency. We present how coupled modeling and in-situ data sets can inform agricultural management and policy to encourage improved nitrogen management.

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

Forward selection for multiple resistance across the non-selective glyphosate, glufosinate and oxyfluorfen herbicides in Lolium weed species.

PubMed

Fernández, Pablo; Alcántara, Ricardo; Osuna, María D; Vila-Aiub, Martin M; Prado, Rafael De

2017-05-01

In the Mediterranean area, Lolium species have evolved resistance to glyphosate after decades of continual use without other alternative chemicals in perennial crops (olive, citrus and vineyards). In recent years, oxyfluorfen alone or mixed with glyphosate and glufosinate has been introduced as a chemical option to control dicot and grass weeds. Dose-response studies confirmed that three glyphosate-resistant Lolium weed species (L. rigidum, L. perenne, L. multiflorum) collected from perennial crops in the Iberian Peninsula have also evolved resistance to glufosinate and oxyfluorfen herbicides, despite their recent introduction. Based on the LD 50 resistance parameter, the resistance factor was similar among Lolium species and ranged from 14- to 21-fold and from ten- to 12-fold for oxyfluorfen and glufosinate respectively. Similarly, about 14-fold resistance to both oxyfluorfen and glufosinate was estimated on average for the three Lolium species when growth reduction (GR 50 ) was assessed. This study identified oxyfluorfen resistance in a grass species for the first time. A major threat to sustainability of perennial crops in the Iberian Peninsula is evident, as multiple resistance to non-selective glyphosate, glufosinate and oxyfluorfen herbicides has evolved in L. rigidum, L. perenne and L. multiflorum weeds. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Geoelectrical Soil Properties of Farmlands Located on Ancient River Floodplains in EL Paso County Texas

NASA Astrophysics Data System (ADS)

Pegues, J. G.; Kaip, G.; Doser, D. I.

2013-12-01

Farming in Rio Grande flood plain deposit soils has presented challenges concerning soil salinity, soil drainage and soil collapse. Typical soil forms include Saneli silted clay loam, Harkey loam, Harkey silky loam clay and Tigua silty clay. In the lower valley farmlands of Socorro, TX, cotton and alfalfa are the principal crops, but grain sorghum, corn and vegetable crops also are suitable. Pecan trees, as well as fruit trees suited to the climate, can be grown. Agrarians are faced with varying results of crop yields over relatively small stretches of land; for example, a 22 acre area can contain multiple soil inclusions. This study was conducted on a 22 acre tract of farmland which has recently undergone multiple geophysical testing analyses that include: magnetics, DC resistivity, gravity, and ground penetrating radar. Results will compare flood plain sedimentation qualities to agricultural soil classes through the identification of soil salinity and grain size. This investigation will focus on the testing of geo-electrical soil properties through resistivity assessment. Examination of the sight using a capacity coupled resistivity meter to measure the soil properties over various time periods will be conducted. The results will be compared with the other geophysical data to look for correlations that highlight soil properties.

Multiple hybrid de novo genome assembly of finger millet, an orphan allotetraploid crop

PubMed Central

Hatakeyama, Masaomi; Aluri, Sirisha; Balachadran, Mathi Thumilan; Sivarajan, Sajeevan Radha; Patrignani, Andrea; Grüter, Simon; Poveda, Lucy; Shimizu-Inatsugi, Rie; Baeten, John; Francoijs, Kees-Jan; Nataraja, Karaba N; Reddy, Yellodu A Nanja; Phadnis, Shamprasad; Ravikumar, Ramapura L; Schlapbach, Ralph; Sreeman, Sheshshayee M; Shimizu, Kentaro K

2018-01-01

Abstract Finger millet (Eleusine coracana (L.) Gaertn) is an important crop for food security because of its tolerance to drought, which is expected to be exacerbated by global climate changes. Nevertheless, it is often classified as an orphan/underutilized crop because of the paucity of scientific attention. Among several small millets, finger millet is considered as an excellent source of essential nutrient elements, such as iron and zinc; hence, it has potential as an alternate coarse cereal. However, high-quality genome sequence data of finger millet are currently not available. One of the major problems encountered in the genome assembly of this species was its polyploidy, which hampers genome assembly compared with a diploid genome. To overcome this problem, we sequenced its genome using diverse technologies with sufficient coverage and assembled it via a novel multiple hybrid assembly workflow that combines next-generation with single-molecule sequencing, followed by whole-genome optical mapping using the Bionano Irys® system. The total number of scaffolds was 1,897 with an N50 length >2.6 Mb and detection of 96% of the universal single-copy orthologs. The majority of the homeologs were assembled separately. This indicates that the proposed workflow is applicable to the assembly of other allotetraploid genomes. PMID:28985356

Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

PubMed

Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

2015-05-12

As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

Multiplex PCR for four Sclerotinia species

USDA-ARS?s Scientific Manuscript database

Sclerotinia homeocarpa, S. minor, S. sclerotiorum, and S. trifoliorum are common species within the genus Sclerotinia, where the morphological identification is challenging, especially when one crop hosts multiple species. The objective of this study was to design species specific primers compatibl...

Shifting Patterns of Agricultural Diversity

USDA-ARS?s Scientific Manuscript database

Although monocultural cropping systems can provide the greatest yield efficiency in the short term, more diverse agricultural landscapes may contribute multiple ecosystem benefits. The USDA's Cropland Data Layer provides a yearly map of the agricultural lands of the continental United States broken ...

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

Transgenic salt-tolerant tomato plants accumulate salt in foliage but not in fruit.

PubMed

Zhang, H X; Blumwald, E

2001-08-01

Transgenic tomato plants overexpressing a vacuolar Na+/H+ antiport were able to grow, flower, and produce fruit in the presence of 200 mM sodium chloride. Although the leaves accumulated high sodium concentrations, the tomato fruit displayed very low sodium content. Contrary to the notion that multiple traits introduced by breeding into crop plants are needed to obtain salt-tolerant plants, the modification of a single trait significantly improved the salinity tolerance of this crop plant. These results demonstrate that with a combination of breeding and transgenic plants it could be possible to produce salt-tolerant crops with far fewer target traits than had been anticipated. The accumulation of sodium in the leaves and not in the fruit demonstrates the utility of such a modification in preserving the quality of the fruit.

Strategies for Enhanced Crop Resistance to Insect Pests.

PubMed

Douglas, Angela E

2018-04-29

Insect pests are responsible for substantial crop losses worldwide through direct damage and transmission of plant diseases, and novel approaches that complement or replace broad-spectrum chemical insecticides will facilitate the sustainable intensification of food production in the coming decades. Multiple strategies for improved crop resistance to insect pests, especially strategies relating to plant secondary metabolism and immunity and microbiome science, are becoming available. Recent advances in metabolic engineering of plant secondary chemistry offer the promise of specific toxicity or deterrence to insect pests; improved understanding of plant immunity against insects provides routes to optimize plant defenses against insects; and the microbiomes of insect pests can be exploited, either as a target or as a vehicle for delivery of insecticidal agents. Implementation of these advances will be facilitated by ongoing advances in plant breeding and genetic technologies.

Crop identification for the delineation of irrigated regions under scarce data conditions: a new approach based on chaos theory

NASA Astrophysics Data System (ADS)

Mangiarotti, S.; Muddu, S.; Sharma, A. K.; Corgne, S.; Ruiz, L.; Hubert-Moy, L.

2015-12-01

Groundwater is one of the main water reservoirs used for irrigation in regions of scarce water resources. For this reason, crop irrigation is expected to have a direct influence on this reservoir. To understand the time evolution of the groundwater table and its storage changes, it is important to delineate irrigated crops, whose evaporative demand is relatively higher. Such delineation may be performed based on classical classification approaches using optical remote sensing. However, it remains a difficult problem in regions where plots do not exceed a few hectares and exhibit a very heterogeneous pattern with multiple crops. This difficulty is emphasized in South India where two or three months of cloudy conditions during the monsoon period can hide crop growth during the year. An alternative approach is introduced here that takes advantage of such scarce signal. Ten different crops are considered in the present study. A bank of crop models is first established based on the global modeling technique [1]. These models are then tested using original time series (from which models were obtained) in order to evaluate the information that can be deduced from these models in an inverse approach. The approach is then tested on an independent data set and is finally applied to a large ensemble of 10,000 time series of plot data extracted from the Berambadi catchment (AMBHAS site) part of the Kabini River basin CZO, South India. Results show that despite the important two-month gap in satellite observations in the visible band, interpolated vegetation index remains an interesting indicator for identification of crops in South India. [1] S. Mangiarotti, R. Coudret, L. Drapeau, & L. Jarlan, Polynomial search and global modeling: Two algorithms for modeling chaos, Phys. Rev. E, 86(4), 046205 (2012).

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland.

PubMed

Skelsey, Peter; Cooke, David E L; Lynott, James S; Lees, Alison K

2016-11-01

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop-growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO 2 emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change-driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective. © 2016 John Wiley & Sons Ltd.

Possible changes to arable crop yields by 2050

PubMed Central

Jaggard, Keith W.; Qi, Aiming; Ober, Eric S.

2010-01-01

By 2050, the world population is likely to be 9.1 billion, the CO2 concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2°C. In these conditions, what contribution can increased crop yield make to feeding the world? CO2 enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO2-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations. PMID:20713388

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.

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

Possible changes to arable crop yields by 2050.

PubMed

Jaggard, Keith W; Qi, Aiming; Ober, Eric S

2010-09-27

By 2050, the world population is likely to be 9.1 billion, the CO(2) concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2 degrees C. In these conditions, what contribution can increased crop yield make to feeding the world? CO(2) enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO(2)-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations.

Spatial and temporal variation in evapotranspiration

USDA-ARS?s Scientific Manuscript database

Spatial and temporal variation in evapotranspiration occurs at multiple scales as the result of several different spatial and temporal patterns in precipitation, soil water holding capacity, cloudiness (available energy), types of crops, and residue and tillage management practices. We have often as...

The Joint Experiment for Crop Assessment and Monitoring (JECAM) Initiative: Developing methods and best practices for global agricultural monitoring

NASA Astrophysics Data System (ADS)

Champagne, C.; Jarvis, I.; Defourny, P.; Davidson, A.

2014-12-01

Agricultural systems differ significantly throughout the world, making a 'one size fits all' approach to remote sensing and monitoring of agricultural landscapes problematic. The Joint Experiment for Crop Assessment and Monitoring (JECAM) was established in 2009 to bring together the global scientific 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 across an array of diverse agricultural systems. These methods form the research and development component of the Group on Earth Observation Global Agricultural Monitoring (GEOGLAM) initiative to harmonize global monitoring efforts and increase market transparency. 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. Each test site works independently as well as together across multiple sites to test methods, sensors and field data collection techniques to derive key agricultural parameters, including crop type, crop condition, crop yield and soil moisture. The outcome of this project will be 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 research and development foundation for GEOGLAM and will help to inform the development of the GEOGLAM "system of systems" for global agricultural monitoring. The outcomes of the 2014 JECAM science meeting will be discussed as well as examples of methods being developed by JECAM scientists.

Minimising farm crop protection pressure supported by the multiple functionalities of the DISCUSS indicator set.

PubMed

Wustenberghs, Hilde; Fevery, Davina; Lauwers, Ludwig; Marchand, Fleur; Spanoghe, Pieter

2018-03-15

Sustainable crop protection (SCP) has many facets. Farmers may therefore perceive transition to SCP as very complex. The Dual Indicator Set for Crop Protection Sustainability (DISCUSS) can handle this complexity. To provide targeted support throughout the transition to SCP, complexity capture must be synchronised with the time course of on-farm decision-making. Tool use must be tuned to farmer awareness and appropriate level of data in consecutive stages. This paper thus explores the potential functionalities of DISCUSS in relation to both complexity and time. Results from apple and potato crop protection show three potential functions: DISCUSS can be used as (1) a simulation tool for communication and decision support, (2) an assessment and monitoring tool, and (3) a discussion support tool for farmer groups. Analysis of these functionalities using a framework for guiding on-farm sustainability assessment and strategic decision-making shows how each functionality can support the consecutive steps of transition to SCP, i.e. using the right tool functionality at the right time. Copyright © 2017 Elsevier B.V. All rights reserved.

The genetic and molecular basis of crop height based on a rice model.

PubMed

Liu, Fang; Wang, Pandi; Zhang, Xiaobo; Li, Xiaofei; Yan, Xiaohong; Fu, Donghui; Wu, Gang

2018-01-01

This review presents genetic and molecular basis of crop height using a rice crop model. Height is controlled by multiple genes with potential to be manipulated through breeding strategies to improve productivity. Height is an important factor affecting crop architecture, apical dominance, biomass, resistance to lodging, tolerance to crowding and mechanical harvesting. The impressive increase in wheat and rice yield during the 'green revolution' benefited from a combination of breeding for high-yielding dwarf varieties together with advances in agricultural mechanization, irrigation and agrochemical/fertilizer use. To maximize yield under irrigation and high fertilizer use, semi-dwarfing is optimal, whereas extreme dwarfing leads to decreased yield. Rice plant height is controlled by genes that lie in a complex regulatory network, mainly involved in the biosynthesis or signal transduction of phytohormones such as gibberellins, brassinosteroids and strigolactones. Additional dwarfing genes have been discovered that are involved in other pathways, some of which are uncharacterized. This review discusses our current understanding of the regulation of plant height using rice as a well-characterized model and highlights some of the most promising research that could lead to the development of new, high-yielding varieties. This knowledge underpins future work towards the genetic improvement of plant height in rice and other crops.

Development of Bt Rice and Bt Maize in China and Their Efficacy in Target Pest Control

PubMed Central

Liu, Qingsong; Hallerman, Eric; Peng, Yufa; Li, Yunhe

2016-01-01

Rice and maize are important cereal crops that serve as staple foods, feed, and industrial material in China. Multiple factors constrain the production of both crops, among which insect pests are an important one. Lepidopteran pests cause enormous yield losses for the crops annually. In order to control these pests, China plays an active role in development and application of genetic engineering (GE) to crops, and dozens of GE rice and GE maize lines expressing insecticidal proteins from the soil bacterium Bacillus thuringiensis (Bt) have been developed. Many lines have entered environmental release, field testing, and preproduction testing, and laboratory and field experiments have shown that most of the Bt rice and Bt maize lines developed in China exhibited effective control of major target lepidopteran pests on rice (Chilo suppressalis, Scirpophaga incertulas, and Cnaphalocrocis medinalis) and maize (Ostrinia furnacalis), demonstrating bright prospects for application. However, none of these Bt lines has yet been commercially planted through this writing in 2016. Challenges and perspectives for development and application of Bt rice and maize in China are discussed. This article provides a general context for colleagues to learn about research and development of Bt crops in China, and may shed light on future work in this field. PMID:27763554

Development of Bt Rice and Bt Maize in China and Their Efficacy in Target Pest Control.

PubMed

Liu, Qingsong; Hallerman, Eric; Peng, Yufa; Li, Yunhe

2016-10-18

Rice and maize are important cereal crops that serve as staple foods, feed, and industrial material in China. Multiple factors constrain the production of both crops, among which insect pests are an important one. Lepidopteran pests cause enormous yield losses for the crops annually. In order to control these pests, China plays an active role in development and application of genetic engineering (GE) to crops, and dozens of GE rice and GE maize lines expressing insecticidal proteins from the soil bacterium Bacillus thuringiensis ( Bt ) have been developed. Many lines have entered environmental release, field testing, and preproduction testing, and laboratory and field experiments have shown that most of the Bt rice and Bt maize lines developed in China exhibited effective control of major target lepidopteran pests on rice ( Chilo suppressalis , Scirpophaga incertulas , and Cnaphalocrocis medinalis ) and maize ( Ostrinia furnacalis ), demonstrating bright prospects for application. However, none of these Bt lines has yet been commercially planted through this writing in 2016. Challenges and perspectives for development and application of Bt rice and maize in China are discussed. This article provides a general context for colleagues to learn about research and development of Bt crops in China, and may shed light on future work in this field.

Pre-sowing Seed Treatments in Direct-seeded Early Rice: Consequences for Emergence, Seedling Growth and Associated Metabolic Events under Chilling Stress

NASA Astrophysics Data System (ADS)

Wang, Weiqin; Chen, Qian; Hussain, Saddam; Mei, Junhao; Dong, Huanglin; Peng, Shaobing; Huang, Jianliang; Cui, Kehui; Nie, Lixiao

2016-01-01

Double direct-seeding for double rice cropping is a simplified, labor saving, and efficient cropping system to improve multiple-crop index and total rice production in central China. However, poor crop establishment of direct-seeded early rice due to chilling stress is the main obstacle to wide spread of this system. A series of experiments were conducted to unravel the effects of pre-sowing seed treatments on emergence, seedling growth and associated metabolic events of direct-seeded early rice under chilling stress. Two seed priming treatments and two seed coating treatments were used in all the experiments. A non-treated control treatment was also maintained for comparison. In both the field and growth chamber studies, seed priming with selenium or salicylic acid significantly enhanced the emergence and seedling growth of rice compared with non-treated control. Nevertheless, such positive effects were not apparent for seed coating treatments. Better emergence and vigorous seedling growth of rice after seed priming was associated with enhanced α-amylase activity, higher soluble sugars contents, and greater respiration rate in primed rice seedlings under chilling stress. Taking together, these findings may provide new avenues for understanding and advancing priming-induced chilling tolerance in direct-seeded early rice in double rice cropping system.

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.

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses.

PubMed

Hartman, Yorike; Uwimana, Brigitte; Hooftman, Danny A P; Schranz, Michael E; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2013-06-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop-wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop-wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar-wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability.

Watershed-Scale Cover Crops Reduce Nutrient Export From Agricultural Landscapes.

NASA Astrophysics Data System (ADS)

Tank, J. L.; Hanrahan, B.; Christopher, S. F.; Trentman, M. T.; Royer, T. V.; Prior, K.

2016-12-01

The Midwestern US has undergone extensive land use change as forest, wetlands, and prairies have been converted to agroecosystems. Today, excess fertilizer nutrients from farm fields enter Midwestern agricultural streams, which degrades both local and downstream water quality, resulting in algal blooms and subsequent hypoxic "dead zones" far from the nutrient source. We are quantifying the benefits of watershed-scale conservation practices that may reduce nutrient runoff from adjacent farm fields. Specifically, research is lacking on whether the planting of winter cover crops in watersheds currently dominated by row-crop agriculture can significantly reduce nutrient inputs to adjacent streams. Since 2013, farmers have planted cover crops on 70% of croppable acres in the Shatto Ditch Watershed (IN), and "saturation level" implementation of this conservation practice has been sustained for 3 years. Every 14 days, we have quantified nutrient loss from fields by sampling nutrient fluxes from multiple subsurface tile drains and longitudinally along the stream channel throughout the watershed. Cover crops improved stream water quality by reducing dissolved inorganic nutrients exported downstream; nitrate-N and DRP concentrations and fluxes were significantly lower in tiles draining fields with cover crops compared to those without. Annual watershed nutrient export also decreased, and reductions in N and P loss ( 30-40%) exceeded what we expected based on only a 6-10% reduction in runoff due to increased watershed water holding capacity. We are also exploring the processes responsible for increased nutrient retention, where they are occurring (terrestrial vs. aquatic) and when (baseflow vs. storms). For example, whole-stream metabolism also responded to cover crop planting, showing reduced variation in primary production and respiration in years after watershed-scale planting of cover crops. In summary, widespread land cover change, through cover crop planting, can significantly reduce annual watershed-scale nutrient export. Moreover, successful outcomes highlighted through demonstration projects may facilitate widespread adoption, making them powerful agents of change for advancing conservation success.

Genetic variability in cereal isolates of the Fusarium incarnatum-equiseti species complex

USDA-ARS?s Scientific Manuscript database

The F. incarnatum-equiseti species complex (FIESC) includes fungi associated with diseases of multiple agricultural crops. Although members of FIESC are considered moderately aggressive, they produce diverse mycotoxins, including trichothecenes. Because FIESC exhibits cryptic speciation, DNA-based p...

7 CFR 400.402 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... FCIC or the insurance provider. Retrieval of records. Retrieval of a person's records by that person's... and State, applicable policy numbers, and other information related to multiple peril crop insurance policies as required by FCIC, from which information is retrieved by a personal identifier including, but...

7 CFR 400.402 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... FCIC or the insurance provider. Retrieval of records. Retrieval of a person's records by that person's... and State, applicable policy numbers, and other information related to multiple peril crop insurance policies as required by FCIC, from which information is retrieved by a personal identifier including, but...

7 CFR 400.402 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... FCIC or the insurance provider. Retrieval of records. Retrieval of a person's records by that person's... and State, applicable policy numbers, and other information related to multiple peril crop insurance policies as required by FCIC, from which information is retrieved by a personal identifier including, but...

HiveScience: A Citizen Science Project for Beekeepers

EPA Science Inventory

Honey bee health is affected by multiple factors including parasites, disease, poor nutrition, pesticides and agronomic practices. The value of honey bees goes far beyond providing honey; honey bees pollinate 90 commercial crops and add $11.5 billion in value to agricultural cro...

Cost-Effectiveness of Aflatoxin Control Methods: Economic Incentives

USDA-ARS?s Scientific Manuscript database

Multiple sectors in U.S. crop industries – growers, elevators, handlers/shellers, processors, distributors, and consumers – are affected by aflatoxin contamination of commodities, and have the potential to control it. Aflatoxin control methods at both preharvest and postharvest levels have been dev...

Emerging viruses in Florida and the Caribbean

USDA-ARS?s Scientific Manuscript database

Multiple thrips-, whitefly- and aphid-transmitted viruses have recently emerged or re-emerged in vegetable and ornamental crops in Florida and the Caribbean. Tomato spotted wilt virus (a thrips-transmitted tospovirus) and Tomato yellow leaf curl virus (a whitefly-transmitted begomovirus) have histor...

Root-synthesised cytokinins induce salinity tolerance in tomato (Solanum lycopersicum L.)

USDA-ARS?s Scientific Manuscript database

Soil salinity decreases crop yield via multiple mechanisms, including decreasing concentrations of the growth-promoting, senescence-delaying and insect resistance-enhancing plant hormones cytokinins. Two approaches evaluated whether root-localised ipt (a key enzyme for cytokinin biosynthesis) gene e...

Genetic variation in isolates of the Fusarium incarnatum-equiseti species complex recovered from cereals

USDA-ARS?s Scientific Manuscript database

The Fusarium incarnatum-equiseti species complex (FIESC) includes mycotoxigenic species associated with several diseases of cereals and other crops. These species are considered moderately aggressive and are reported to produce multiple mycotoxins, including beauvericin, zearalenone, equisetin, fusa...

USDA,ARS areawide project-Anaoerobic soil disinfestation

USDA-ARS?s Scientific Manuscript database

Anaerobic soil disinfestation (ASD) is an effective method for control of soilborne pathogens, nematodes, and many weed species. In the absence of pest pressure, ASD provides increased yields of multiple crop species. Utilization of ASD requires the application of organic amendments, such as compos...

Effects of mixtures of dicamba and glyphosate on nontarget plants

EPA Science Inventory

New technologies are being developed using mixtures of herbicides to manage a broader variety of weeds in multiple herbicide resistant crops such as soybean and cotton. As part of its regulation of pesticides, the US Environmental Protection Agency considers environmental risks,...

Assessments of Maize Yield Potential in the Korean Peninsula Using Multiple Crop Models

NASA Astrophysics Data System (ADS)

Kim, S. H.; Myoung, B.; Lim, C. H.; Lee, S. G.; Lee, W. K.; Kafatos, M.

2015-12-01

The Korean Peninsular has unique agricultural environments due to the differences in the political and socio-economical systems between the Republic of Korea (SK, hereafter) and the Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering from the lack of food supplies caused by natural disasters, land degradation and failed political system. The neighboring developed country SK has a better agricultural system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we have utilized multiple process-based crop models capable of regional-scale assessments to evaluate maize Yp over the Korean Peninsula - the GIS version of EPIC model (GEPIC) and APSIM model that can be expanded to regional scales (APSIM regions). First we evaluated model performance and skill for 20 years from 1991 to 2010 using reanalysis data (Local Data Assimilation and Prediction System (LDAPS); 1.5km resolution) and observed data. Each model's performances were compared over different regions within the Korean Peninsula of different regional climate characteristics. To quantify the major influence of individual climate variables, we also conducted a sensitivity test using 20 years of climatology. Lastly, a multi-model ensemble analysis was performed to reduce crop model uncertainties. The results will provide valuable information for estimating the climate change or variability impacts on Yp over the Korean Peninsula.

Seasonal Population Dynamics of Three Potato Pests in Washington State.

PubMed

D'Auria, Elizabeth M; Wohleb, Carrie H; Waters, Timothy D; Crowder, David W

2016-08-01

Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculella Zeller), the beet leafhopper (Circulifer tenellus Baker), and the green peach aphid (Myzus persicae Sulzer). Each of these pests directly damages potato foliage or tubers; C. tenellus and M. persicae also transmit pathogens that can drastically reduce potato yields. We monitored the seasonal population dynamics of these pests by conducting weekly sampling on a network of commercial farms from 2007 to 2014. Using these data, we developed phenology models to characterize the seasonal population dynamics of each pest based on accumulated degree-days (DD). All three pests exhibited consistent population dynamics across seasons that were mediated by temperature. Of the three pests, C. tenellus was generally the first detected in potato crops, with 90% of adults captured by 936 DD. In contrast, populations of P. operculella and M. persicae built up more slowly over the course of the season, with 90% cumulative catch by 1,590 and 2,634 DD, respectively. Understanding these seasonal patterns could help potato producers plan their IPM strategies while allowing them to move away from calendar-based applications of insecticides. More broadly, our results show how long-term monitoring studies that explore dynamics of multiple pest species can aid in developing IPM strategies in crop systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus

PubMed Central

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector’s life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis’ life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector–based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector. PMID:27159134

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

PubMed

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

Functional diversity of home gardens and their agrobiodiversity conservation benefits in Benin, West Africa.

PubMed

Gbedomon, Rodrigue Castro; Salako, Valère Kolawolé; Fandohan, Adandé Belarmain; Idohou, Alix Frank Rodrigue; Glèlè Kakaї, Romain; Assogbadjo, Achille Ephrem

2017-11-25

Understanding the functional diversity of home gardens and their socio-ecological determinants is essential for mainstreaming these agroforestry practices into agrobiodiversity conservation strategies. This paper analyzed functional diversity of home gardens, identified the socio-ecological drivers of functions assigned to them, and assessed the agrobiodiversity benefits of home gardens functions. Using data on occurring species in home garden (HG) and functions assigned to each species by the gardeners, the study combined clustering and discriminant canonical analyses to explore the functional diversity of 360 home gardens in Benin, West Africa. Next, multinomial logistic models and chi-square tests were used to analyze the effect of socio-demographic characteristics of gardeners (age, gender, and education level), agro-ecological zones (humid, sub-humid, and semi-arid), and management regime (single and multiple managers) on the possession of a functional type of home gardens. Generalized linear models were used to assess the effect of the functions of home gardens and the determinant factor on their potential in conserving agrobiodiversity. Seven functional groups of home gardens, four with specific functions (food, medicinal, or both food and medicinal) and three with multiple functions (more than two main functions), were found. Women owned most of home gardens with primarily food plant production purpose while men owned most of home gardens with primarily medicinal plant production purposes. Finding also showed that multifunctional home gardens had higher plant species diversity. Specifically, crops and crop wild relatives occurred mainly in home gardens with food function while wild plant species were mostly found in home gardens with mainly medicinal function. Home gardening is driven by functions beyond food production. These functions are mostly related to direct and extractive values of home gardens. Functions of home gardens were gendered, with women mostly involved in home food gardens, and contribute to maintenance of crops and crop wild relatives while men were mostly home medicinal gardeners and contribute to the maintenance of wild plant species in home gardens. Although multiple functional home gardens were related to higher plant diversity, there was no guarantee for long-term maintenance of plant species in home gardens.

Reduction of antinutritional glucosinolates in Brassica oilseeds by mutation of genes encoding transporters.

PubMed

Nour-Eldin, Hussam Hassan; Madsen, Svend Roesen; Engelen, Steven; Jørgensen, Morten Egevang; Olsen, Carl Erik; Andersen, Jonathan Sonne; Seynnaeve, David; Verhoye, Thalia; Fulawka, Rudy; Denolf, Peter; Halkier, Barbara Ann

2017-04-01

The nutritional value of Brassica seed meals is reduced by the presence of glucosinolates, which are toxic compounds involved in plant defense. Mutation of the genes encoding two glucosinolate transporters (GTRs) eliminated glucosinolates from Arabidopsis thaliana seeds, but translation of loss-of-function phenotypes into Brassica crops is challenging because Brassica is polyploid. We mutated one of seven and four of 12 GTR orthologs and reduced glucosinolate levels in seeds by 60-70% in two different Brassica species (Brassica rapa and Brassica juncea). Reduction in seed glucosinolates was stably inherited over multiple generations and maintained in field trials of two mutant populations at three locations. Successful translation of the gtr loss-of-function phenotype from model plant to two Brassica crops suggests that our transport engineering approach could be broadly applied to reduce seed glucosinolate content in other oilseed crops, such as Camelina sativa or Crambe abyssinica.

Origin and diversification of winged bean (Psophocarpus tetragonolobus (L.) DC.), a multipurpose underutilized legume.

PubMed

Yang, Shuyi; Grall, Aurélie; Chapman, Mark A

2018-05-01

For many crops, research into the origin and partitioning of genetic variation is limited and this can slow or prevent crop improvement programs. Many of these underutilized crops have traits that could be of benefit in a changing climate due to stress tolerance or nutritional properties. Winged bean (Psophocarpus tetragonolobus (L.) DC.) is one such crop. All parts of the plant can be eaten, from the roots to the seeds, and is high in protein as well as other micronutrients. The goal of our study was to identify the wild progenitor and analyze the partitioning of genetic variation in the crop. We used molecular phylogenetic analyses (cpDNA and nuclear ITS sequencing) to resolve relationships between all species in the genus, and population genetics (utilizing microsatellites) to identify genetic clusters of winged bean accessions and compare this to geography. We find that winged bean is genetically distinct from all other members of the genus. We also provide support for four groups of species in the genus, largely, but not completely, corresponding to the results of previous morphological analyses. Within winged bean, population genetic analysis using 10 polymorphic microsatellite markers suggests four genetic groups; however, there is little correspondence between the genetic variation and the geography of the accessions. The true wild progenitor of winged bean remains unknown (or is extinct). There has likely been large-scale cross-breeding, trade, and transport of winged bean and/or multiple origins of the crop. © 2018 Botanical Society of America.

Bulk canopy resistance: Modeling for the estimation of actual evapotranspiration of maize

NASA Astrophysics Data System (ADS)

Gharsallah, O.; Corbari, C.; Mancini, M.; Rana, G.

2009-04-01

Due to the scarcity of water resources, the correct evaluation of water losses by the crops as evapotranspiration (ET) is very important in irrigation management. This work presents a model for estimating actual evapotranspiration on hourly and daily scales of maize crop grown in well water condition in the Lombardia Region (North Italy). The maize is a difficult crop to model from the soil-canopy-atmosphere point of view, due to its very complex architecture and big height. The present ET model is based on the Penman-Monteith equation using Katerji and Perrier approach for modelling the variable canopy resistance value (rc). In fact rc is a primary factor in the evapotranspiration process and needs to be accurately estimated. Furthermore, ET also has an aerodynamic component, hence it depends on multiple factors such as meteorological variables and crop water condition. The proposed approach appears through a linear model in which rc depends on climate variables and aerodynamic resistance [rc/ra = f(r*/ra)] where ra is the aerodynamic resistance, function of wind speed and crop height, and r* is called "critical" or "climatic" resistance. Here, under humid climate, the model has been applied with good results at both hourly and daily scales. In this study, the reached good accuracy shows that the model worked well and are clearly more accurate than those obtained by using the more diffuse and known standard FAO 56 method for well watered and stressed crops.

Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission

USGS Publications Warehouse

Mariotto, Isabella; Thenkabail, Prasad S.; Huete, Alfredo; Slonecker, E. Terrence; Platonov, Alexander

2013-01-01

Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of λ1 (400–2500 nm) versus λ2 (400–2500 nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742 nm and 1175 nm (HVI742-1175), (ii) 1296 nm and 1054 nm (HVI1296-1054), (iii) 1225 nm and 697 nm (HVI1225-697), and (iv) 702 nm and 1104 nm (HVI702-1104). Among the most frequently occurring HNBs in various crop biophysical models, 74% were located in the 1051–2331 nm spectral range, followed by 10% in the moisture sensitive 970 nm, 6% in the red and red-edge (630–752 nm), and the remaining 10% distributed between blue (400–500 nm), green (501–600 nm), and NIR (760–900 nm).Discriminant models, used for discriminating 3 or 4 or 5 crop types, showed significantly higher accuracies when using HNBs (> 90%) over MBBs data (varied between 45 and 84%).Finally, the study highlighted 29 HNBs of Hyperion that are optimal in the study of agricultural crops and potentially significant to the upcoming NASA HyspIRI mission. Determining optimal and redundant bands for a given application will help overcoming the Hughes' phenomenon (or curse of high dimensionality of data).

Climate Change Impacts on Crop Production in Nigeria

NASA Astrophysics Data System (ADS)

Mereu, V.; Gallo, A.; Carboni, G.; Spano, D.

2011-12-01

The agricultural sector in Nigeria is particularly important for the country's food security, natural resources, and growth agenda. The cultivable areas comprise more than 70% of the total area; however, the cultivated area is about the 35% of the total area. The most important components in the food basket of the nation are cereals and tubers, which include rice, maize, corn, millet, sorghum, yam, and cassava. These crops represent about 80% of the total agricultural product in Nigeria (from NPAFS). The major crops grown in the country can be divided into food crops (produced for consumption) and export products. Despite the importance of the export crops, the primary policy of agriculture is to make Nigeria self-sufficient in its food and fiber requirements. The projected impacts of future climate change on agriculture and water resources are expected to be adverse and extensive in these area. This implies the need for actions and measures to adapt to climate change impacts, and especially as they affect agriculture, the primary sector for Nigerian economy. In the framework of the Project Climate Risk Analysis in Nigeria (founded by World Bank Contract n.7157826), a study was made to assess the potential impact of climate change on the main crops that characterize Nigerian agriculture. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT are tools that simulate physiological processes of crop growth, development and production by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were calibrated to evaluate climate change impacts on crop production. The climate data used for the analysis are derived by the Regional Circulation Model COSMO-CLM, from 1971 to 2065, at 8 km of spatial resolution. The RCM model output was "perturbed" with 10 Global Climate Models to have a wide variety of possible climate projections for the impact analysis. Multiple combinations of soil and climate conditions and crop management and varieties were considered for each Agro-Ecological Zone (AEZ) of Nigeria. A sensitivity analysis was made to evaluate the model response to changes in precipitation and temperature. The climate impact assessment was made by comparing the yield obtained with the climate data for the present period and the yield obtainable under future climate conditions. The results were analyzed at state, AEZ and country levels. The analysis shows a general reduction in crop yields in particular in the dryer regions of northern Nigeria.

USE OF GREEN MANURE CROPS AND SUGAR BEET VARIETIES TO CONTROL HETERODERA BETAE.

PubMed

Raaijmakers, E

2014-01-01

Although it is less studied than the white beet cyst nematode (Heterodera schachtii), the yellow beet cyst nematode (H. betae) has been found in many countries in Europe. For example in The Netherlands, France and Spain. H. betae causes yield losses on sandy soils. A high infestation can result in loss of complete plants. In The Netherlands, this nematode is especially found in the south eastern and north eastern part, where it occurs on 18% and 5% of the fields, respectively. From a project of the Dutch Sugar beet Research Institute IRS (SUSY) on factors explaining differences in sugar yield, this nematode was one of the most important factors reducing sugar yields on sandy soils. Until 2008, the only way to control H. betae was by reducing the number of host crops in the crop rotation. Host crops are crops belonging to the families of Cruciferae, Chenopodiaceae, Polygonaceae, Caryophyllaceae and Leguminosea. In order to find more control measures, research was done to investigate the host status of different green manure crops and the resistance and tolerance of different sugar beet varieties to H. betae. White mustard (Sinapis alba) and oil seed radish (Raphanus sativus spp. oleiferus) varieties resistant to H. schachtii were investigated for their resistance against H. betae. A climate room trial and a field trial with white mustard and oil seed radish were conducted in 2007 and 2008, respectively. Results show that H. betae could multiply on susceptible white mustard and susceptible oil seed radish, but not on the H. schachtii resistant varieties. In climate room trials in 2009, 2010 and 2011 and field trials in 2010, 2011 and 2012, the effect of different sugar beet varieties on the multiplication of H. betae and the effect of H. betae on yield at different infestation levels was investigated. Sugar beet varieties with resistance genes to H. schachtii (from Beta procumbens or B. maritima) were selected. Varieties with resistance genes from these sources were not totally resistant to H. betae, but limited the multiplication of this nematode in comparison with susceptible varieties considerably. Only the varieties with resistance genes from B. maritima gave higher yields in comparison with susceptible varieties. Growing these varieties was already profitable from very light infestation levels (75 eggs and larvae/100 ml soil) of H. betae. Therefore, resistant cruciferous green manure crops and resistant and tolerant sugar beet varieties are good tools for growers to control H. betae.

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).

Sugarcane Genotype Performance in Three Environments (Based on Crop Cycle) at Mardan, Pakistan

USDA-ARS?s Scientific Manuscript database

Sugarcane breeders often face significant genotype x environment interactions in their trials grown under multiple environments. Hence, genotypes need to be tested for their stability across different environments keeping in view the significant interactions. An experiment comprising 28 sugarcane ge...

7 CFR 400.402 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... insurance provider. Retrieval of records—Retrieval of a person's records by that person's SSN or EIN, or..., applicable policy numbers, and other information related to multiple peril crop insurance policies as required by FCIC, from which information is retrieved by a personal identifier including, but not limited...

7 CFR 400.402 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... insurance provider. Retrieval of records—Retrieval of a person's records by that person's SSN or EIN, or..., applicable policy numbers, and other information related to multiple peril crop insurance policies as required by FCIC, from which information is retrieved by a personal identifier including, but not limited...

The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies

USDA-ARS?s Scientific Manuscript database

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the...

GiNA, an efficient and high-throughput software for horticultural phenotyping

USDA-ARS?s Scientific Manuscript database

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed,...

DIFFERENTIATING TOXICITIES OF CONAZOLE FUNGICIDES THROUGH METABONOMIC ANALYSES OF MULTIPLE TISSUES

EPA Science Inventory

The conazole fungicides represent a large group of compounds widely used agriculturally for the protection of crop plants (Hutson 1998) and pharmaceutically in the treatment of topical and systemic infections (Sheehan 1999). In 1999, the latest period for which agricultural usage...

DIFFERENTIATING TOXICITIES OF CONAZOLE FUNGICIDES THROUGH METABONOMIC ANALYSES OF MULTIPLE TISSUES

EPA Science Inventory

The conazole fungicides represent a large group of compounds widely used agriculturally for the protection of crop plants (Hutson 1998) and pharmaceutically in the treatment of topical and systemic infections(Sheehan 1999). In 1999, the latest period for which agricultural usage...

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

12 CFR 618.8040 - Authorized insurance services.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 618.8040 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM GENERAL PROVISIONS Member Insurance § 618.8040 Authorized insurance services. (a) Farm Credit System banks (excluding banks for... member's or borrower's farm or aquatic unit is permitted, but limited to hail and multiple-peril crop...

Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data

USGS Publications Warehouse

Thenkabail, P.S.; Mariotto, I.; Gumma, M.K.; Middleton, E.M.; Landis, D.R.; Huemmrich, K.F.

2013-01-01

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy ~70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using ~20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was ~ 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or “the curse of high dimensionality”) in hyperspectral data for a particular application (e.g., biophysi- al characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI.

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

NASA Technical Reports Server (NTRS)

Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

2013-01-01

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e.g., biophysical characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI. Index Terms-Hyperion, field reflectance, imaging spectroscopy, HyspIRI, biophysical parameters, hyperspectral vegetation indices, hyperspectral narrowbands, broadbands.

Multiple hybrid de novo genome assembly of finger millet, an orphan allotetraploid crop.

PubMed

Hatakeyama, Masaomi; Aluri, Sirisha; Balachadran, Mathi Thumilan; Sivarajan, Sajeevan Radha; Patrignani, Andrea; Grüter, Simon; Poveda, Lucy; Shimizu-Inatsugi, Rie; Baeten, John; Francoijs, Kees-Jan; Nataraja, Karaba N; Reddy, Yellodu A Nanja; Phadnis, Shamprasad; Ravikumar, Ramapura L; Schlapbach, Ralph; Sreeman, Sheshshayee M; Shimizu, Kentaro K

2017-09-05

Finger millet (Eleusine coracana (L.) Gaertn) is an important crop for food security because of its tolerance to drought, which is expected to be exacerbated by global climate changes. Nevertheless, it is often classified as an orphan/underutilized crop because of the paucity of scientific attention. Among several small millets, finger millet is considered as an excellent source of essential nutrient elements, such as iron and zinc; hence, it has potential as an alternate coarse cereal. However, high-quality genome sequence data of finger millet are currently not available. One of the major problems encountered in the genome assembly of this species was its polyploidy, which hampers genome assembly compared with a diploid genome. To overcome this problem, we sequenced its genome using diverse technologies with sufficient coverage and assembled it via a novel multiple hybrid assembly workflow that combines next-generation with single-molecule sequencing, followed by whole-genome optical mapping using the Bionano Irys® system. The total number of scaffolds was 1,897 with an N50 length >2.6 Mb and detection of 96% of the universal single-copy orthologs. The majority of the homeologs were assembled separately. This indicates that the proposed workflow is applicable to the assembly of other allotetraploid genomes. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Host Selection Behavior and the Fecundity of Plutella xylostella (Lepidoptera: Plutellidae) on Multiple Host Plants

PubMed Central

Huang, Bin; Shi, Zhanghong; Hou, Youming

2014-01-01

Abstract Insect herbivores often have higher densities on host plants grown in monocultures than those in diverse environments. The underlying mechanisms are thought to be that polyphagous insects have difficulty in selecting food or oviposition sites when multiple host plants exist. However, this hypothesis needs to be extensively investigated. Our field experiments revealed that the population of the diamondback moths, Plutella xylostella (L.) (Lepidoptera: Plutellidae), significantly decreased in a mixed cropping field compared with a monoculture. To determine the reasons for the reduction in population in the mixed cropping field, the takeoff behavior and fecundity of females in no-choice and free-choice laboratory environments were compared by video recordings of host selection by P. xylostella . Adults displayed a significantly higher takeoff frequency in free-choice environments than those in no-choice treatments and preferred landing on Brassica campestris (L.) or Brassica juncea (Coss) plants in contrast with Brassica oleracea (L.). Female adults in the free-choice environment also laid fewer eggs compared with the monoculture. Olfaction experiments demonstrated orientation by P. xylostella to host volatiles when presented with a choice between plant odors and clean air, but females showed no preference when odors from three Brassicaceae species were presented simultaneously. We conclude that mixed cropping alters the host-finding behavior of P. xylostella resulting in reduced oviposition. PMID:25527573

Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions

NASA Astrophysics Data System (ADS)

Russo, T. A.; Sahoo, S.; Elliott, J. W.; Foster, I.

2016-12-01

Improving groundwater management practices under future drought conditions in agricultural regions requires three steps: 1) estimating the impacts of climate and drought on crop water demand, 2) projecting groundwater availability given climate and demand forcing, and 3) using this information to develop climate-smart policy and water use practices. We present an innovative combination of models to address the first two steps, and inform the third. Crop water demand was simulated using biophysical crop models forced by multiple climate models and climate scenarios, with one case simulating climate adaptation (e.g. modify planting or harvest time) and another without adaptation. These scenarios were intended to represent a range of drought projections and farm management responses. Nexty, we used projected climate conditions and simulated water demand across the United States as inputs to a novel machine learning-based groundwater model. The model was applied to major agricultural regions relying on the High Plains and Mississippi Alluvial aquifer systems in the US. The groundwater model integrates input data preprocessed using single spectrum analysis, mutual information, and a genetic algorithm, with an artificial neural network model. Model calibration and test results indicate low errors over the 33 year model run, and strong correlations to groundwater levels in hundreds of wells across each aquifer. Model results include a range of projected groundwater level changes from the present to 2050, and in some regions, identification and timeframe of aquifer depletion. These results quantify aquifer longevity under climate and crop scenarios, and provide decision makers with the data needed to compare scenarios of crop water demand, crop yield, and groundwater response, as they aim to balance water sustainability with food security.

Impact of Crop Conversions on Runoff and Sediment Output in the Lower Mississippi River Basin

NASA Astrophysics Data System (ADS)

Momm, H.; Bingner, R. L.; Elkadiri, R.; Yaraser, L.; Porter, W.

2017-12-01

Farming management practices influence sediment and agrochemical loads exiting fields and entering downstream water bodies. These practices impact multiple physical processes responsible for sediment and nutrient detachment, transport, and deposition. Recent changes in farming practices in the Southern United States coincide with increased grain production, replacing traditional crops such as cotton with corn and soybeans. To grow these crops in the South, adapted crop management practices are needed (irrigation, fertilizer, etc.). In this study, the impact of grain crop adoption on hydrologic processes and non-point source pollutant production is quantified. A watershed located in the Big Sunflower River drainage basin (14,179 km2) - a part of the greater Lower Mississippi River basin - was selected due to its economic relevance, historical agricultural output, and depiction of recent farming management trends. Estimates of runoff and sediment loads were produced using the U.S. Department of Agriculture supported Annualized Agriculture Non-Point Source Pollution (AnnAGNPS) watershed pollution and management model. Existing physical conditions during a 16-year period (2000-2015) were characterized using 3,992 sub-catchments and 1,602 concentrated flow paths. Algorithms were developed to integrate continuous land use/land cover information, variable spatio-temporal irrigation practices, and crop output yield in order to generate a total of 2,922 unique management practices and corresponding soil-disturbing operations. A simulation representing existing conditions was contrasted with simulations depicting alternatives of management, irrigation practices, and temporal variations in crop yield. Quantification of anthropogenic impacts to water quality and water availability at a watershed scale supports the development of targeted pollution mitigation and custom conservation strategies.

Upper midwest climate variations: farmer responses to excess water risks.

PubMed

Morton, Lois Wright; Hobbs, Jonathan; Arbuckle, J Gordon; Loy, Adam

2015-05-01

Persistent above average precipitation and runoff and associated increased sediment transfers from cultivated ecosystems to rivers and oceans are due to changes in climate and human action. The US Upper Midwest has experienced a 37% increase in precipitation (1958-2012), leading to increased crop damage from excess water and off-farm loss of soil and nutrients. Farmer adaptive management responses to changing weather patterns have potential to reduce crop losses and address degrading soil and water resources. This research used farmer survey ( = 4778) and climate data (1971-2011) to model influences of geophysical context, past weather, on-farm flood and saturated soils experiences, and risk and vulnerability perceptions on management practices. Seasonal precipitation varied across six Upper Midwest subregions and was significantly associated with variations in management. Increased warm-season precipitation (2007-2011) relative to the past 40 yr was positively associated with no-till, drainage, and increased planting on highly erodible land (HEL). Experience with saturated soils was significantly associated with increased use of drainage and less use of no-till, cover crops, and planting on HEL. Farmers in counties with a higher percentage of soils considered marginal for row crops were more likely to use no-till, cover crops, and plant on HEL. Respondents who sell corn through multiple markets were more likely to have planted cover crops and planted on HEL in 2011.This suggests that regional climate conditions may not well represent individual farmers' actual and perceived experiences with changing climate conditions. Accurate climate information downscaled to localized conditions has potential to influence specific adaptation strategies. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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 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.

Bayesian Inference of Baseline Fertility and Treatment Effects via a Crop Yield-Fertility Model

PubMed Central

Chen, Hungyen; Yamagishi, Junko; Kishino, Hirohisa

2014-01-01

To effectively manage soil fertility, knowledge is needed of how a crop uses nutrients from fertilizer applied to the soil. Soil quality is a combination of biological, chemical and physical properties and is hard to assess directly because of collective and multiple functional effects. In this paper, we focus on the application of these concepts to agriculture. We define the baseline fertility of soil as the level of fertility that a crop can acquire for growth from the soil. With this strict definition, we propose a new crop yield-fertility model that enables quantification of the process of improving baseline fertility and the effects of treatments solely from the time series of crop yields. The model was modified from Michaelis-Menten kinetics and measured the additional effects of the treatments given the baseline fertility. Using more than 30 years of experimental data, we used the Bayesian framework to estimate the improvements in baseline fertility and the effects of fertilizer and farmyard manure (FYM) on maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max) yields. Fertilizer contributed the most to the barley yield and FYM contributed the most to the soybean yield among the three crops. The baseline fertility of the subsurface soil was very low for maize and barley prior to fertilization. In contrast, the baseline fertility in this soil approximated half-saturated fertility for the soybean crop. The long-term soil fertility was increased by adding FYM, but the effect of FYM addition was reduced by the addition of fertilizer. Our results provide evidence that long-term soil fertility under continuous farming was maintained, or increased, by the application of natural nutrients compared with the application of synthetic fertilizer. PMID:25405353

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California

NASA Astrophysics Data System (ADS)

Fulton, A.; Snyder, R.; Hillyer, C.; English, M.; Sanden, B.; Munk, D.

2012-04-01

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California Allan Fulton, Richard Snyder, Charles Hillyer, Marshall English, Blake Sanden, and Dan Munk Adoption of scientific methods to decide when to irrigate and how much water to apply to a crop has increased over the last three decades in California. In 1988, less than 4.3 percent of US farmers employed some type of science-based technique to assist in making irrigation scheduling decisions (USDA, 1995). An ongoing survey in California, representing an industry irrigating nearly 0.4 million planted almond hectares, indicates adoption rates ranging from 38 to 55 percent of either crop evapotranspiration (ETc), soil moisture monitoring, plant water status, or some combination of these irrigation scheduling techniques to assist with making irrigation management decisions (California Almond Board, 2011). High capital investment to establish fruit and nut crops, sensitivity to over and under-irrigation on crop performance and longevity, and increasing costs and competition for water have all contributed to increased adoption of scientific irrigation scheduling methods. These trends in adoption are encouraging and more opportunities exist to develop improved irrigation scheduling tools, especially computer decision-making models. In 2009 and 2010, an "On-line Irrigation Scheduling Advisory Service" (OISO, 2012), also referred to as Online Irrigation Management (IMO), was used and evaluated in commercial walnut, almond, and French prune orchards in the northern Sacramento Valley of California. This specific model has many features described as the "Next Generation of Irrigation Schedulers" (Hillyer, 2010). While conventional irrigation management involves simply irrigating as needed to avoid crop stress, this IMO is designed to control crop stress, which requires: (i) precise control of crop water availability (rather than controlling applied water); (ii) quantifying crop stress in order to manage it in heterogeneous fields; and (iii) predicting crop responses to water stress. The capacities of this IMO include: 1. Modeling of the disposition of applied water in spatially variable fields; 2. Conjunctive scheduling for multiple fields, rather than scheduling each field independently; 3. Long range forecasting of crop water requirements to better utilize limited water or limited delivery system capacity: and 4. Explicit modeling of the uncertainties of water use and crop yield. This was one of the first efforts to employ a "Next Generation" type computer irrigation scheduling advisory model or IMO in orchard crops. This paper discusses experiences with introducing this model to fruit and nut growers of various size and scale in the northern Sacramento Valley of California and the accuracy of its forecasts of irrigation needs in fruit and nut crops. Strengths and opportunities to forge ahead in the development of a "Next Generation" irrigation scheduler were identified from this on-farm evaluation.

Monitoring the agricultural landscape for insect resistance

NASA Astrophysics Data System (ADS)

Casas, Joseph; Glaser, J. A.; Copenhaver, Ken

Farmers in 25 countries on six continents are using plant biotechnology to solve difficult crop production challenges and conserve the environment. In fact, 13.3 million farmers, which include 90 percent of the farming in developing countries, choose to plant biotech crops. Over the past decade, farmers increased area planted in genetically modified (GM) crops by more than 10 percent each year, thus increasing their farm income by more than 44 billion US dollars (1996-2007), and achieved economic, environmental and social benefits in crops such as soybeans, canola, corn and cotton. To date, total acres of biotech crops harvested exceed more than 2 billion with a proven 13-year history of safe use. Over the next decade, expanded adoption combined with current research on 57 crops in 63 countries will broaden the advantages of genetically modified foods for growers, consumers and the environment. Genetically modified (GM) crops with the ability to produce toxins lethal to specific insect pests are covering a larger percentage of the agricultural landscape every year. The United States department of Agriculture (USDA) estimated that 63 percent of corn and 65 percent of cotton contained these specific genetic traits in 2009. The toxins could protect billions of dollars of loss from insect damage for crops valued at greater than 165 billion US dollars in 2008. The stable and efficient production of these crops has taken on even more importance in recent years with their use, not only as a food source, but now also a source of fuel. It is in the best interest of the United States Environmental Protection Agency (USEPA) to ensure the continued efficacy of toxin producing GM crops as their use reduces pesticides harmful to humans and animals. However, population genetics models have indicated the risk of insect pests developing resistance to these toxins if a high percentage of acreage is grown in these crops. The USEPA is developing methods to monitor the agricultural landscape to ensure resistance is not developing. USEPA is teaming with NASA to perform this monitoring using models and NASA earth observation imagery from airborne and satellite platforms. Using multiple spatial, temporal and spectral resolutions, the project is monitoring the entire Midwestern "Corn Belt". By applying these methods, the project has successfully delineated insect infestations in genetically modified corn fields. Insect resistance development is expected to present itself as infestations thus indicating potential identification of resistance if it develops in genetically modified crops. The USEPA and NASA are currently considering the development of plans to potentially extend this aircraft research to other crops and develop a micro-satellite application.

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.

Standardization of soil apparent electrical conductivity using multi-temporal surveys across multiple production fields

USDA-ARS?s Scientific Manuscript database

Apparent soil electrical conductivity (ECa) is an efficient technique for understanding within-field variability of physical and chemical soil characteristics. Commercial devices are readily available for collecting ECa on whole fields and used broadly for crop management in precision agriculture; h...

Assessment of multiple management systems in the Upper Midwest

USDA-ARS?s Scientific Manuscript database

Reduced tillage, multi-crop rotations and use of organic fertilizers are characteristically expected to improve soil quality. As measures of soil quality, microbial and soluble C and N were evaluated in an nine-year assessment of management practices alternative to a conventionally managed two-year ...

Improving Mineral Nutrition of Micropropagated Red Raspberry

USDA-ARS?s Scientific Manuscript database

In vitro propagation is important for fast multiplication of a wide range of nursery crops, including red raspberry. The variation in genetic background of the many red raspberry cultivars makes it difficult to successfully use one growth medium for all. Although most cultivars will grow on Murashig...

Identification of milling and baking quality QTL in multiple soft wheat mapping populations

USDA-ARS?s Scientific Manuscript database

Wheat derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wh...

EFFECT OF LAND DISPOSAL APPLICATIONS OF MUNICIPAL ENVIRONMENTAL WASTES ON CROP YIELDS AND HEAVY METAL UPTAKE

EPA Science Inventory

This report provides the cumulative data acquired from 1969 through 1975 from field and greenhouse investigations pertaining to the effects on selected soils and plants from municipal compost and sewage sludge applications. Multiple applications of composted municipal refuse resu...

Impact of switchgrass harvest time on biomass yield and conversion

USDA-ARS?s Scientific Manuscript database

Switchgrass (Panicum virgatum L.) is a perennial grass native to much of North America being developed as a dedicated energy crop for conversion to biofuels. Breeding efforts are focused on producing high-yielding cultivars that can maintain high yield across multiple environments, including poor so...

Windrow burning eliminates Italian Ryegrass (Lolium perenne ssp. multiflorum) seed viability

USDA-ARS?s Scientific Manuscript database

Burning of crop residues that have been concentrated behind the harvest combine (windrowed) is one of several harvest weed seed control strategies that have been developed and evaluated in Australia to address the widespread evolution of multiple herbicide resistance in annual weeds. Herbicide-resis...

Coupled Effects of Climatic and Socio-economic Factors on Winter Cropping in India

NASA Astrophysics Data System (ADS)

Jain, M.; Mondal, P.; Galford, G. L.; DeFries, R. S.

2015-12-01

India is predicted to be one of the most vulnerable regions in terms of agricultural sensitivity to future climate changes. Approximately 69% of India's population is rural, and over 55% of the working population relies on agriculture for sustenance and livelihoods. Indian smallholder farmers who own less than 2 ha of farmland represent 78% of the total Indian farmers and produce 41% of the country's food crops. These smallholder farmers are among some of the most vulnerable communities to climatic and economic changes due to limited access to technology, infrastructure, markets, and institutional or financial support in the case of adverse climatic events. Baseline information on agricultural sensitivity to climate variability will provide useful information for regional-level, and eventually state- and national-level, strategies and policies that promote adaption to climate variability. We use a decade of remote sensing analysis of cropping patterns and climatic factors along with census data for irrigation and demographic factors to understand winter cropping trajectories across agro-ecological zones in India. Findings from multiple agro-ecological zones indicate that there are three primary trajectories in winter cropping in India - increasing, fluctuating, and decreasing. In the Central Indian Highlands, for example, the most dominant trend is that of fluctuating cropped area, ranging between ~37,300 km2 in 2010 and ~21,100 km2 in 2013, which is associated with village-level access to irrigation and local labor dynamics. Clay soil type and increasing irrigation coverage were associated with intensification. Yet, suitable soil type and access to irrigation do not reduce vulnerability to high daytime temperatures that is negatively associated with winter crop cover. With pronounced winter warming projected in the coming decades, effective adaptation by smallholder farmers would require additional strategies, such as access to fine-scale temperature forecasts ahead of the planting season and heat-tolerant winter crop varieties.

Risks and consequences of gene flow from herbicide-resistant crops: canola (Brassica napus L) as a case study.

PubMed

Légère, Anne

2005-03-01

Data from the literature and recent experiments with herbicide-resistant (HR) canola (Brassica napus L) repeatedly confirm that genes and transgenes will flow and hybrids will form if certain conditions are met. These include sympatry with a compatible relative (weedy, wild or crop), synchrony of flowering, successful fertilization and viable offspring. The chance of these events occurring is real; however, it is generally low and varies with species and circumstances. Plants of the same species (non-transgenic or with a different HR transgene) in neighbouring fields may inherit the new HR gene, potentially generating plants with single and multiple HR. For canola, seed losses at harvest and secondary dormancy ensures the persistence over time of the HR trait(s) in the seed bank, and the potential presence of crop volunteers in subsequent crops. Although canola has many wild/weedy relatives, the risk of gene flow is quite low for most of these species, except with Brassica rapa L. Introgression of genes and transgenes in B rapa populations occurs with apparently little or no fitness costs. Consequences of HR canola gene flow for the agro-ecosystem include contamination of seed lots, potentially more complex and costly control strategy, and limitations in cropping system design. Consequences for non-agricultural habitats may be minor but appear largely undocumented. Minister of Public Works and Government Services Canada 2005

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

PubMed Central

Dwivedi, Sangam L.; Scheben, Armin; Edwards, David; Spillane, Charles; Ortiz, Rodomiro

2017-01-01

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses. PMID:28900432

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes.

PubMed

Dwivedi, Sangam L; Scheben, Armin; Edwards, David; Spillane, Charles; Ortiz, Rodomiro

2017-01-01

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

NASA Astrophysics Data System (ADS)

Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

2017-12-01

Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

Partitioning evapotranspiration via continuous sampling of water vapor isotopes over common row crops and candidate biofuel crops.

NASA Astrophysics Data System (ADS)

Miller, J. N.; Black, C. K.; Bernacchi, C.

2014-12-01

Global demand for renewable energy is accelerating land conversion from common row crops such as maize and soybean to cellulosic biofuel crops such as miscanthus and switchgrass. This land conversion is expected to alter ecohydrology via changes in evapotranspiration (ET). However, the direction in which evapotranspiration will shift, either partitioning more moisture through soil evaporation (E) or through plant transpiration (T) is uncertain. To investigate how land conversion from maize to miscanthus affects ET partitioning we measured the isotopic composition of water vapor via continuous air sampling. We obtained continuous diurnal measurements of δ2H and δ18O for miscanthus and maize on multiple days over the course of the growing season. Water vapor isotopes drawn from two heights were measured at 2 Hz using a cavity ringdown spectrometer and partitioned into components of E and T using a simple mixing equation. A second approach to partitioning was accomplished by subtracting transpiration measurements, obtained through sap flow sensors, from total ET, measured via eddy covariance. Preliminary results reveal that both methods compare favorably and that transpiration dominates variations in ET in miscanthus fields more so than in fields of maize.

Modeling Emissions and Vertical Plume Transport of Crop Residue Burning Experiments in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Pouliot, G.; Elleman, R. A.; ONeill, S. M.; Urbanski, S. P.; Wong, D. C.

2017-12-01

Crop residue burning has long been a common practice in agriculture with the smoke emissions from the burning linked to negative health impacts. A field study in eastern Washington and northern Idaho in August 2013 consisted of multiple burns of well characterized fuels with nearby surface and aerial measurements including trace species concentrations, plume rise height and boundary layer structure. The chemical transport model CMAQ (Community Multiscale Air Quality Model) was used to assess the fire emissions and subsequent vertical plume transport. The study first compared assumptions made by the 2014 National Emission Inventory approach for crop residue burning with the fuel and emissions information obtained from the field study and then investigated the sensitivity of modeled carbon monoxide (CO) and PM2.5 concentrations to these different emission estimates and plume rise treatment with CMAQ. The study suggests that improvements to the current parameterizations are needed in order for CMAQ to reliably reproduce smoke plumes from burning. In addition, there is enough variability in the smoke emissions, stemming from variable field-specific information such as field size, that attempts to model crop residue burning should use field-specific information whenever possible.

Linking country level food supply to global land and water use and biodiversity impacts: The case of Finland.

PubMed

Sandström, Vilma; Kauppi, Pekka E; Scherer, Laura; Kastner, Thomas

2017-01-01

The agricultural products consumed in Finland are increasingly grown on foreign farms. We analyze the Finnish imports of food and feed crops from 1986 to 2011 by products and by their geographic origin drawing a link to environmental impacts. The share of foreign crops consumed in Finland nearly doubled in the study period. The imports increased especially with commodities that could also be produced domestically. While the production of food increasingly shifted abroad, also the exports from Finland increased. >90% of the blue water of the Finnish crop supply came from foreign water resources. We map the results of land and water use together with their impacts on global biodiversity, and show that most of the land and water use related biodiversity impacts (>93%) associated with the Finnish food consumption are related to the imports and therefore taken place outside the Finnish borders. The use of multiple environmental indicators can help identifying products and spatial hotspots associated with the most severe environmental impacts of the Finnish crop imports contributing to a more holistic decision-making and the promoting of sustainable food consumption both domestically and globally. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimal crop selection and water allocation under limited water supply in irrigation

NASA Astrophysics Data System (ADS)

Stange, Peter; Grießbach, Ulrike; Schütze, Niels

2015-04-01

Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.

Changes in reflectance anisotropy of wheat crop during different phenophases

NASA Astrophysics Data System (ADS)

Lunagaria, Manoj M.; Patel, Haridas R.

2017-04-01

The canopy structure of wheat changes significantly with growth stages and leads to changes in reflectance anisotropy. Bidirectional reflectance distribution function characterises the reflectance anisotropy of the targets, which can be approximated. Spectrodirectional reflectance measurements on wheat crop were acquired using a field goniometer system. The bidirectional reflectance spectra were acquired at 54 view angles to cover the hemispheric span up to 60° view zenith. The observations were made during early growth stages till maturity of the crop. The anisotropy was not constant for all wavelengths and anisotropic factors clearly revealed spectral dependence, which was more pronounced in near principal plane. In near infrared, wheat canopy expressed less reflectance anisotropy because of higher multiple scattering. The broad hotspot signature was noticeable in reflectance of canopy whenever view and solar angles were close. Distinct changes in bidirectional reflectance distribution function were observed during booting to flowering stages as the canopy achieves more uniformity, height and head emergence. The function clearly reveals bowl shape during heading to early milking growth stages of the crop. Late growth stages show less prominent gap and shadow effects. Anisotropy index revealed that wheat exhibits changes in reflectance anisotropy with phenological development and with spectral bands.

Multimodel ensembles of wheat growth: many models are better than one.

PubMed

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W; Rötter, Reimund P; Boote, Kenneth J; Ruane, Alex C; Thorburn, Peter J; Cammarano, Davide; Hatfield, Jerry L; Rosenzweig, Cynthia; Aggarwal, Pramod K; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richie; Grant, Robert F; Heng, Lee; Hooker, Josh; Hunt, Leslie A; Ingwersen, Joachim; Izaurralde, Roberto C; Kersebaum, Kurt Christian; Müller, Christoph; Kumar, Soora Naresh; Nendel, Claas; O'leary, Garry; Olesen, Jørgen E; Osborne, Tom M; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Semenov, Mikhail A; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; White, Jeffrey W; Wolf, Joost

2015-02-01

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. © 2014 John Wiley & Sons Ltd.

Green biotechnology, nanotechnology and bio-fortification: perspectives on novel environment-friendly crop improvement strategies.

PubMed

Yashveer, Shikha; Singh, Vikram; Kaswan, Vineet; Kaushik, Amit; Tokas, Jayanti

2014-10-01

Food insecurity and malnutrition are prominent issues for this century. As the world's population continues to increase, ensuring that the earth has enough food that is nutritious too will be a difficult task. Today one billion people of the world are undernourished and more than a third are malnourished. Moreover, the looming threat of climate change is exasperating the situation even further. At the same time, the total acreage of arable land that could support agricultural use is already near its limits, and may even decrease over the next few years due to salination and desertification patterns resulting from climate change. Clearly, changing the way we think about crop production must take place on multiple levels. New varieties of crops must be developed which can produce higher crop yields with less water and fewer agricultural inputs. Besides this, the crops themselves must have improved nutritional qualities or become biofortified in order to reduce the chances of 'hidden hunger' resulting from malnourishment. It is difficult to envision the optimum way to increase crop production using a single uniform strategy. Instead, a variety of approaches must be employed and tailored for any particular agricultural setting. New high-impact technologies such as green biotechnology, biofortification, and nanotechnology offer opportunities for boosting agricultural productivity and enhancing food quality and nutritional value with eco-friendly manner. These agricultural technologies currently under development will renovate our world to one that can comfortably address the new directions, our planet will take as a result of climate change.

Multimodel Ensembles of Wheat Growth: More Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide;

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Progress and Preliminary Results

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2011-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.

Multimodel Ensembles of Wheat Growth: Many Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alexander C.; Thorburn, Peter J.; Cammarano, Davide;

Biology and management of two important Conyza weeds: a global review.

PubMed

Bajwa, Ali Ahsan; Sadia, Sehrish; Ali, Hafiz Haider; Jabran, Khawar; Peerzada, Arslan Masood; Chauhan, Bhagirath Singh

2016-12-01

Weed management is one of the prime concerns for sustainable crop production. Conyza bonariensis and Conyza canadensis are two of the most problematic, noxious, invasive and widespread weeds in modern-day agriculture. The biology, ecology and interference of C. bonariensis and C. canadensis have been reviewed here to highlight pragmatic management options. Both these species share a unique set of biological features, which enables them to invade and adapt a wide range of environmental conditions. Distinct reproductive biology and an efficient seed dispersal mechanism help these species to spread rapidly. Ability to interfere strongly and to host crop pests makes these two species worst weeds of cropping systems. These weed species cause 28-68 % yield loss in important field crops such as soybean and cotton every year. These weeds are more prevalent in no-till systems and, thus, becoming a major issue in conservation agriculture. Cultural practices such as crop rotations, seed rate manipulation, mulching, inter-row tillage and narrow row spacing may provide an effective control of these species. However, such methods are not feasible and applicable under all types of conditions. Different herbicides also provide a varying degree of control depending on crop, agronomic practices, herbicide dose, application time and season. However, both these species have evolved resistance against multiple herbicides, including glyphosate and paraquat. The use of alternative herbicides and integrated management strategies may provide better control of herbicide-resistant C. bonariensis and C. canadensis. Management plans based on the eco-biological interactions of these species may prove sustainable in the future.

Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

USDA-ARS?s Scientific Manuscript database

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable...

Nitrogen and harvest impact on biomass yield of established switchgrass (Panicum virgatum L.)

USDA-ARS?s Scientific Manuscript database

Switchgrass (Panicum virgatum L.) has been identified as the model herbaceous biomass energy crop by the United States Department of Energy as it is capable of being a viable bioenergy feedstock while providing multiple environmental benefits when grown on marginal soil landscapes. Nitrogen (N) fert...

Impact of agroforestry plantings for bioenergy production on soil organic carbon

USDA-ARS?s Scientific Manuscript database

Tree windbreaks are an attractive multiple-benefit land use through their ability to mitigate climate change by modifying the local microclimate to improve crop growth and by sequestering carbon in the soil and tree biomass. Recently, such agroforestry practices are also being considered for their b...

Mortality and Population Dynamics of Bemisia tabaci within a Multi-Crop System

USDA-ARS?s Scientific Manuscript database

The population dynamics of mobile polyphagous pests is governed by a complex set of interacting factors that involve multiple host-plants, seasonality, movement and demography. Bemisia tabaci is a multivoltine insect with no diapause that maintains population continuity by moving from one host to a...

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Of birds, carbon and water: integrating multiple ecosystem service impacts to identify locations for agricultural conservation practice adoption

EPA Science Inventory

Human use of the landscape for crop production can degrade ecosystem services. A number of agricultural conservation practices are touted as mitigating these impacts. Many of these practices are encouraged by incentive programs such as the Conservation Reserve Program administere...

Integrated description of agricultural field experiments and production: the ICASA version 2.0 data standards

USDA-ARS?s Scientific Manuscript database

Agricultural research increasingly seeks to quantify complex interactions of processes for a wide range of environmental conditions and crop management scenarios, leading to investigation where multiple sets of experimental data are examined using tools such as simulation and regression. The use of ...

The pathogen biology, identification and management of Rhizoctonia species with emphasis on isolates infecting turfgrasses

USDA-ARS?s Scientific Manuscript database

R. solani is an economically important soilborne basidiomycetous pathogen of worldwide distribution and it is known to attack at least 188 species of higher plants, including crops, vegetables, ornamentals, forest trees and turfgrasses. The pathogenic isolates may belong to multiple genera and speci...

High-Throughput resequencing of maize landraces at genomic regions associated with flowering time

USDA-ARS?s Scientific Manuscript database

Despite the reduction in the price of sequencing, it remains expensive to sequence and assemble whole, complex genomes of multiple samples for population studies, particularly for large genomes like those of many crop species. Enrichment of target genome regions coupled with next generation sequenci...

Nutrient transport in runoff as affected by diet, tillage and manure application rate

USDA-ARS?s Scientific Manuscript database

Including distillers grains in feedlot finishing diets may increase feedlot profitability. However the nutrient content of by-products are concentrated about three during the distillation process. Manure can be applied to meet single or multiple year crop nutrient requirements. The water quality eff...

Runoff and sediment reduction from integration of native prairie filter strips into row-crop agriculture

USDA-ARS?s Scientific Manuscript database

Agroecosystems provide multiple benefits including food, fiber, fuel, clean water and air, habitat, carbon sequestration, recreation, and aesthetics. But most agricultural landscapes are managed for only a few of these benefits. This project aimed to evaluate how the integration of diverse perennial...

Incidence and spatial distribution of Rhizoctonia and Pythium species determined with real-time PCR

USDA-ARS?s Scientific Manuscript database

Populations of Rhizoctonia and Pythium are diverse in eastern Washington, with multiple species/anastomosis groups present throughout the region and within individual fields. Recent evidence suggests that species composition may be influenced by crop rotation. The Cook Agronomy Farm near Pullman, WA...

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 ...

A polyphasic approach for characterization of a collection of cereal isolates of the Fusarium incarnatum-equiseti species complex

USDA-ARS?s Scientific Manuscript database

DNA-based phylogenetic analyses have resolved the fungal genus Fusarium into multiple species complexes. The F. incarnatum-equiseti species complex (FIESC) includes fusaria associated with several diseases of agriculturally important crops, including cereals. Although members of FIESC are considered...

Influence of low light intensity and soil flooding on cacao physiology

USDA-ARS?s Scientific Manuscript database

Growth and development of plants frequently are limited by multiple abiotic stresses that occur simultaneously in the environment. Cabruca’ an agroforestry system is a main cropping system invariably adapted for cultivation of cacao in southern Bahia, Brazil. In this system of management cacao is gr...

Modeling Emissions and Vertical Plume Transport of Crop Residue Burning Experiments in the Pacific Northwest

EPA Science Inventory

A study in eastern Washington (Walla Walla) and north Idaho (Nez Perce) in August 2013 consisted of multiple burns of well characterized fuels with nearby surface and aerial measurements including trace species concentrations, plume rise height and boundary layer structure. Detai...

Spatial variability in slug emergence patterns - third year results

USDA-ARS?s Scientific Manuscript database

Gray field slugs damage new plantings of crops such as perennial ryegrass grown for seed, and growers routinely make multiple applications of metaldehyde and iron posphate based slug baits. Two major challenges for growers are: (1) choosing the best timing for the first heavy application of slug bai...

Integrating High Resolution Water Footprint and GIS for Promoting Water Efficiency in the Agricultural Sector: A Case Study of Plantation Crops in the Jordan Valley

PubMed Central

Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit

2016-01-01

Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000–2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts. PMID:28018408

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.

Integrating High Resolution Water Footprint and GIS for Promoting Water Efficiency in the Agricultural Sector: A Case Study of Plantation Crops in the Jordan Valley.

PubMed

Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit

2016-01-01

Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000-2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts.

Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources.

PubMed

Pouliot, George; Rao, Venkatesh; McCarty, Jessica L; Soja, Amber

2017-05-01

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. One component of the biomass burning inventory, crop residue burning, has been poorly characterized in the National Emissions Inventory (NEI). In the 2011 NEI, wildland fires, prescribed fires, and crop residue burning collectively were the largest source of PM 2.5 . This paper summarizes our 2014 NEI method to estimate crop residue burning emissions and grass/pasture burning emissions using remote sensing data and field information and literature-based, crop-specific emission factors. We focus on both the postharvest and pre-harvest burning that takes place with bluegrass, corn, cotton, rice, soybeans, sugarcane and wheat. Estimates for 2014 indicate that over the continental United States (CONUS), crop residue burning excluding all areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay occurred over approximately 1.5 million acres of land and produced 19,600 short tons of PM 2.5 . For areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay, biomass burning emissions occurred over approximately 1.6 million acres of land and produced 30,000 short tons of PM 2.5 . This estimate compares with the 2011 NEI and 2008 NEI as follows: 2008: 49,650 short tons and 2011: 141,180 short tons. Note that in the previous two NEIs rangeland burning was not well defined and so the comparison is not exact. The remote sensing data also provided verification of our existing diurnal profile for crop residue burning emissions used in chemical transport modeling. In addition, the entire database used to estimate this sector of emissions is available on EPA's Clearinghouse for Inventories and Emission Factors (CHIEF, http://www3.epa.gov/ttn/chief/index.html ). Estimates of crop residue burning and rangeland burning emissions can be improved by using satellite detections. Local information is helpful in distinguishing crop residue and rangeland burning from all other types of fires.

Regional simulation of soil nitrogen dynamics and balance in Swiss cropping systems

NASA Astrophysics Data System (ADS)

Lee, Juhwan; Necpalova, Magdalena; Six, Johan

2017-04-01

We evaluated the regional-scale potential of various crop and soil management practices to reduce the dependency of crop N demand on external N inputs and N losses to the environment. The estimates of soil N balance were simulated and compared under alternative and conventional crop production across all Swiss cropland. Alternative practices were all combinations of organic fertilization, reduced tillage and winter cover cropping. Using the DayCent model, we simulated changes in crop N yields as well as the contribution of inputs and outputs to soil N balance by alternative practices, which was complemented with corresponding measurements from available long-term field experiments and site-level simulations. In addition, the effects of reducing (between 0% and 80% of recommended application rates) or increasing chemical fertilizer input rates (between 120% and 300% of recommended application rates) on system-level N dynamics were also simulated. Modeled yields at recommended N rates were only 37-87% of the maximum yield potential across common Swiss crops, and crop productivity were sensitive to the level of external N inputs, except for grass-clover mixture, soybean and peas. Overall, differences in soil N input and output decreased or increased proportionally with changing the amount of N input only from the recommended rate. As a result, there was no additional difference in soil N balance in response to N application rates. Nitrate leaching accounted for 40-81% of total N output differences, while up to 47% of total N output occurred through harvest and straw removal. Regardless of crops, yield potential became insensitive to high N rates. Differences in N2O and N2 emissions slightly increased with increasing N inputs, in which each gas was only responsible for about 1% of changes in total N output. Overall, there was a positive soil N balance under alternative practices. Particularly, considerable improvement in soil N balance was expected when slowly decomposed organic fertilizer was used in combination with cover cropping and/or reduced tillage. However, the increase in soil N balance was due to the decreases in harvested yield and nitrate leaching under these organic cropping based practices. Instead, the use of fast decomposed organic matter with cover cropping could be considered to avoid any yield penalty while decreasing nitrate leaching, hence reducing total N output. In order to effectively reduce N losses from soils, approaches to utilize multiple alternative options should be taken into account at the regional scale.

Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

2013-12-01

Agriculture in Sub-Saharan Africa (SSA) drives the economy of many African countries and it is mainly rain-fed agriculture used for subsistence. Increasing temperatures, changed precipitation patterns and more frequent droughts may lead to a substantial decrease of crop yields. The projected impacts of future climate change on agriculture are expected to be significant and extensive in the SSA due to the shortening of the growing seasons and the increasing of water-stress risk. Differences in Agro-Ecological Zones and geographical characteristics of SSA influence the diverse impacts of climate change, which can greatly differ across the continent and within countries. The vulnerability of African Countries to climate change is aggravated by the low adaptive capacity of the continent, due to the increasing of its population, the widespread poverty, and other social factors. In this contest, the assessment of climate change impact on agricultural sector has a particular interest to stakeholder and policy makers, in order to identify specific agricultural sectors and Agro-Ecological Zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in SSA was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management analysis. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT-CSM are tools that allow to simulate physiological process of crop growth, development and production, by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were used, after a parameterization phase, to evaluate climate change impacts on crop phenology and production. Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.

Temporal variation (seasonal and interannual) of vegetation indices of maize and soybeans across multiple years in central Iowa

NASA Astrophysics Data System (ADS)

Prueger, J. H.; Hatfield, J. L.

2015-09-01

Remotely sensed reflectance parameters from corn and soybean surfaces can be correlated to crop production. Surface reflectance of a typical Upper Midwest corn /soybean region in central Iowa across multiple years reveal subtle dynamics in vegetative surface response to a continually varying climate. From 2006 through 2014 remotely sensed data have been acquired over production fields of corn and soybeans in central IA, U.S.A. with the fields alternating between corn and soybeans. The data have been acquired using ground-based radiometers with 16 wavebands covering the visible, near infrared, shortwave infrared wavebands and combined into a series of vegetative indices. These data were collected on clear days with the goal of collecting data at a minimum of once per week from prior to planting until after fall tillage operations. Within each field, five sites were established and sampled during the year to reduce spatial variation and allow for an assessment of changes in the vegetative indices throughout the growing season. Ancillary data collected for each crop included the phenological stage at each sampling date along with biomass sampled at the onset of the reproductive stage and at physiological maturity. Evaluation of the vegetative indices for the different years revealed that patterns were related to weather effects on corn and soybean growth. Remote sensing provides a method to evaluate changes within and among growing seasons to assess crop growth and development as affected by differences in weather variability.

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.

Enhancements Needed in GE Crop and Food Regulation in the U.S.

PubMed Central

Benbrook, Charles

2016-01-01

Genetically engineered (GE) crops, multi-ingredient foods derived from one or more GE ingredients, and GE agricultural inputs are regulated in the United States under a “Coordinated Framework” that was literally cobbled together in the early 1990s. Via this Framework, responsibility is spread across three federal agencies for the assessment and management of potential risks arising from the planting of GE crops, the raising of GE animals, or uses of GE inputs. The Framework was incomplete and conceptually flawed from the beginning. Despite multiple, piecemeal efforts to update aspects of GE risk assessment and regulatory policy, the Coordinated Framework survives to this day largely unchanged. Its shortcomings are recognized in both the scientific and legal communities, but meaningful reforms thus far remain out of reach, blocked by the intense controversy now surrounding all things biotech. Five generic reforms and another five specific initiatives are described to create a more robust, science-driven GE regulatory infrastructure in the U.S. PMID:27066473

Non-cultivated plants present a season-long route of pesticide exposure for honey bees

PubMed Central

Long, Elizabeth Y.; Krupke, Christian H.

2016-01-01

Recent efforts to evaluate the contribution of neonicotinoid insecticides to worldwide pollinator declines have focused on honey bees and the chronic levels of exposure experienced when foraging on crops grown from neonicotinoid-treated seeds. However, few studies address non-crop plants as a potential route of pollinator exposure to neonicotinoid and other insecticides. Here we show that pollen collected by honey bee foragers in maize- and soybean-dominated landscapes is contaminated throughout the growing season with multiple agricultural pesticides, including the neonicotinoids used as seed treatments. Notably, however, the highest levels of contamination in pollen are pyrethroid insecticides targeting mosquitoes and other nuisance pests. Furthermore, pollen from crop plants represents only a tiny fraction of the total diversity of pollen resources used by honey bees in these landscapes, with the principle sources of pollen originating from non-cultivated plants. These findings provide fundamental information about the foraging habits of honey bees in these landscapes. PMID:27240870

Nitrate stable isotopes: Tools for determining nitrate sources among different land uses in the Mississippi River Basin

USGS Publications Warehouse

Chang, Cecily C.Y.; Kendall, C.; Silva, S.R.; Battaglin, W.A.; Campbell, D.H.

2002-01-01

A study was conducted to determine whether NO3- stable isotopes (??15N and ??18O), at natural abundance levels, could discriminate among NO3- sources from sites with different land uses at the basin scale. Water samples were collected from 24 sites in the Mississippi River Basin from five land-use categories: (1) large river basins (>34 590 km2) draining multiple land uses and smaller basins in which the predominant land use was (2) urban (3) undeveloped, (4) crops, or (5) crops and livestock. Our data suggest that riverine nitrates from different land uses have overlapping but moderately distinct isotopic signatures. ??18O data were critical in showing abrupt changes in NO3- source with discharge. The isotopic values of large rivers resembled crop sites, sites with livestock tended to have ??15N values characteristic of manure, and urban sites tended to have high ??18O values characteristic of atmospheric nitrate.

Transgenesis affects endogenous soybean allergen levels less than traditional breeding.

PubMed

Hill, Ryan C; Fast, Brandon J; Herman, Rod A

2017-10-01

The regulatory body that oversees the safety assessment of genetically modified (GM) crops in the European Union, the European Food Safety Authority (EFSA), uniquely requires that endogenous allergen levels be quantified as part of the compositional characterization of GM versions of crops, such as soybean, that are considered to be major allergenic foods. The value of this requirement for assessing food safety has been challenged for multiple reasons including negligible risk of altering allergen levels compared with traditional non-GM breeding. Scatter plots comparing the mean endogenous allergen levels in non-GM soybean isoline grain with the respective levels in GM grain or concurrently grown non-GM commercial reference varieties clearly show that transgenesis causes less change compared with traditional breeding. This visual assessment is confirmed by the quantitative fit of the line of identity (y = x) to the datasets. The current science on allergy does not support the requirement for quantifying allergen levels in GM crops to support safety assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

NASA Technical Reports Server (NTRS)

Leduc, S. (Principal Investigator)

1982-01-01

Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

Impact of the Invasive Brown Marmorated Stink Bug in North America and Europe: History, Biology, Ecology, and Management.

PubMed

Leskey, Tracy C; Nielsen, Anne L

2018-01-07

The brown marmorated stink bug (BMSB), Halyomorpha halys (Stål), is an invasive pentatomid introduced from Asia into the United States, Canada, multiple European countries, and Chile. In 2010, BMSB populations in the mid-Atlantic United States reached outbreak levels and subsequent feeding severely damaged tree fruit as well as other crops. Significant nuisance issues from adults overwintering inside homes were common. BMSB is a highly polyphagous species with a strong dispersal capacity and high reproductive output, potentially enabling its spread and success in invaded regions. A greater understanding of BMSB biology and ecology and its natural enemies, the identification of the male-produced aggregation pheromone, and the recognition that BMSB disperses into crops from adjacent wooded habitats have led to the development of behavior-based integrated pest management (IPM) tactics. Much is still unknown about BMSB, and continued long-term collaborative studies are necessary to refine crop-specific IPM programs and enhance biological control across invaded landscapes.

Revisiting the Role of Plant Transcription Factors in the Battle against Abiotic Stress.

PubMed

Khan, Sardar-Ali; Li, Meng-Zhan; Wang, Suo-Min; Yin, Hong-Ju

2018-05-31

Owing to diverse abiotic stresses and global climate deterioration, the agricultural production worldwide is suffering serious losses. Breeding stress-resilient crops with higher quality and yield against multiple environmental stresses via application of transgenic technologies is currently the most promising approach. Deciphering molecular principles and mining stress-associate genes that govern plant responses against abiotic stresses is one of the prerequisites to develop stress-resistant crop varieties. As molecular switches in controlling stress-responsive genes expression, transcription factors (TFs) play crucial roles in regulating various abiotic stress responses. Hence, functional analysis of TFs and their interaction partners during abiotic stresses is crucial to perceive their role in diverse signaling cascades that many researchers have continued to undertake. Here, we review current developments in understanding TFs, with particular emphasis on their functions in orchestrating plant abiotic stress responses. Further, we discuss novel molecular mechanisms of their action under abiotic stress conditions. This will provide valuable information for understanding regulatory mechanisms to engineer stress-tolerant crops.

Protocols for In Vitro Propagation, Conservation, Synthetic Seed Production, Embryo Rescue, Microrhizome Production, Molecular Profiling, and Genetic Transformation in Ginger (Zingiber officinale Roscoe.).

PubMed

Nirmal Babu, K; Samsudeen, K; Divakaran, Minoo; Pillai, Geetha S; Sumathi, V; Praveen, K; Ravindran, P N; Peter, K V

2016-01-01

Ginger is a rhizomatous plant that belongs to the family Zingiberaceae. It is a herbaceous perennial but cultivated as annual, with crop duration of 7-10 months. Ginger is native to India and Tropical South Asia. The tuberous rhizomes or underground stems of ginger are used as condiment, an aromatic stimulant, and food preservative as well as in traditional medicine. Ginger is propagated vegetatively with rhizome bits as seed material. Cultivation of ginger is plagued by rhizome rot diseases, most of which are mainly spread through infected seed rhizomes. Micropropagation will help in production of disease-free planting material. Sexual reproduction is absent in ginger, making recombinant breeding very impossible. In vitro technology can thus become the preferred choice as it can be utilized for multiplication, conservation of genetic resources, generating variability, gene transfer, molecular tagging, and their utility in crop improvement of these crops.

Daily monitoring of 30 m crop condition over complex agricultural landscapes

NASA Astrophysics Data System (ADS)

Sun, L.; Gao, F.; Xie, D.; Anderson, M. C.; Yang, Y.

2017-12-01

Crop progress provides information necessary for efficient irrigation, scheduling fertilization and harvesting operations at optimal times for achieving higher yields. In the United States, crop progress reports are released online weekly by US Department of Agriculture (USDA) - National Agricultural Statistics Service (NASS). However, the ground data collection is time consuming and subjective, and these reports are provided at either district (multiple counties) or state level. Remote sensing technologies have been widely used to map crop conditions, to extract crop phenology, and to predict crop yield. However, for current satellite-based sensors, it is difficult to acquire both high spatial resolution and frequent coverage. For example, Landsat satellites are capable to capture 30 m resolution images, while the long revisit cycles, cloud contamination further limited their use in detecting rapid surface changes. On the other hand, MODIS can provide daily observations, but with coarse spatial resolutions range from 250 to 1000 m. In recent years, multi-satellite data fusion technology such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used to combine the spatial resolution of Landsat with the temporal frequency of MODIS. It has been found that this synthetic dataset could provide more valuable information compared to the images acquired from only one single sensor. However, accuracy of STARFM depends on heterogeneity of landscape and available clear image pairs of MODIS and Landsat. In this study, a new fusion method was developed using the crop vegetation index (VI) timeseries extracted from "pure" MODIS pixels and Landsat overpass images to generate daily 30 m VI for crops. The fusion accuracy was validated by comparing to the original Landsat images. Results show that the relative error in non-rapid growing period is around 3-5% and in rapid growing period is around 6-8% . The accuracy is much better than that of STARFM which is 4-9% in non-rapid growing period and 10-16% in rapid growing period based on 13 image pairs. The predicted VI from this approach looks consistent and smooth in the SLC-off gap stripes of Landsat 7 ETM+ image. The new fusion results will be used to map crop phenology and to predict crop yield at field scale in the complex agricultural landscapes.

Nutrient cycling potential of camelina (Camelina sativa L. Crantz.) as a cover crop in the US Northern Great Plains

NASA Astrophysics Data System (ADS)

Berti, Marisol; Samarappuli, Dulan

2017-04-01

Camelina [Camelina sativa (L.) Crantz.] is an industrial oilseed crop in the Brassicaceae family with multiple uses. Currently, camelina is not used as a cover crop, but it has the potential to be used as such in maize-soybean-wheat cropping systems. The objectives of this study were to determine the agronomic performance and nutrient scavenging potential of winter camelina in comparison with other common cover crops. Experiments were conducted in Fargo, ND in 2015 and 2016, and in Prosper, ND in 2015. The experimental design was a randomized complete block design with a split-plot arrangement with three replicates. The main plot was the sowing date and the subplot were camelina cultivars as well as other common cover crops in the area. Sowing dates were targeted to 15 August and September 1, although the final dates varied slightly each year. Biomass yield, N content of the biomass N uptake and P uptake was evaluated. Winter camelina N and P uptake ranged between 21 and 30.5 kg N ha-1 and 3.4 to 5.3 kg P ha-1. The nutrient scavenging potential of winter camelina was similar to other cover crops although slightly lower than turnip (Brassica rapa L.), radish (Raphanus sativus L.), and rape (Brassica napus L.) cultivars which had significantly higher P uptake than winter camelina and the other cover crops in the study. An evaluation of spring regrowth and cover indicated that only rye, winter camelina, and pennycress (Thlaspi arvense L.) survived the winter, although a few plants of triticale (x Trticosecale Witt.) and rape were found on a few plots. Because of the high variability on the plots there were no significant differences among the surviving cover crops on soil coverage. The soil coverage for rye cultivars was 25 and 35% and for camelina cv. Bison was 27%.In 2016, biomass yield was not significant for sowing date, cultivars, or their interaction. Winter camelina cultivars biomass yield fluctuated between 1.15 and 2.33 Mg dry matter ha-1 on the first sowing date while pennycress biomass yield was 1.40 Mg ha-1. In the second sowing date all crops had about half the biomass yield than the first sowing date. In conclusion, even though winter camelina may not provide much soil cover in the fall, the ability to survive the winter and scavenge nutrients in the autummn and spring gives this crop an excellent potential to be integrated as a cover crop in maize-soybean-wheat cropping systems in the US Midwest.

Circular buffer strips in center pivot irrigation for multiple benefits in the Southern Great Plains

USDA-ARS?s Scientific Manuscript database

The Ogallala Aquifer has converted the Southern Great Plains from a dust bowl to a highly productive agricultural region in the US. However, over exploitation of the aquifer is threatening sustainability of irrigated agriculture in the region. Partial pivots, where high water using conventional crop...

Volatile organic compounds from Paenibacillus polymyxa KM2501-1 control Meloidogyne incognita by multiple strategies

USDA-ARS?s Scientific Manuscript database

Plant-parasitic nematodes (PPNs) cause serious crop losses worldwide. Treatment of the PPN Meloidogyne incognita with the biological control agent Paenibacillus polymyxa KM2501-1 resulted in a mortality of 88% in vitro and reduced symptoms on tomato by up to 83% under greenhouse conditions. In this ...

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landrace and cultivars

USDA-ARS?s Scientific Manuscript database

Domesticated crops have experienced strong human-driven selection aimed at the development of improved varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated DNA m...

Modeling the effects of mineral nutrition for improving growth and development of micropropagated red raspberries

USDA-ARS?s Scientific Manuscript database

In vitro propagation is important for rapid multiplication of a wide range of nursery crops, including red raspberries. The genetic variation of the many red raspberry cultivars makes it difficult to use one growth medium for all. Although some cultivars grow well on Murashige and Skoog (1962) mediu...

Soil and water conservation in the Pacific Northwest through no-tillage and intensified crop rotations

USDA-ARS?s Scientific Manuscript database

The winter wheat (Triticum aestivum L.) summer fallow rotation typically practiced in the intermediate precipitation zone [300-450 mm (12-18 in)] of the inland Pacific Northwest has proven to be economically stable for producers in this region. However multiple tillage operations are used to control...

Closed reference metatranscriptomics enables in planta profiling of putative virulence activities in the grapevine trunk-disease complex

USDA-ARS?s Scientific Manuscript database

Grapevines, like other perennial crops, are affected by so-called ‘trunk diseases’, which damage the trunk and other woody tissues. Mature grapevines typically contract more than one trunk disease and often multiple grapevine trunk pathogens (GTPs) are recovered from infected tissues. The co-existen...

Innovations in Agriculture in Oregon: Farmers Irrigation District Improves Water Quality, Maximizes Water Conservation, and Generates Clean, Renewable Energy

EPA Pesticide Factsheets

The Hood River Farmers Irrigation District used $36.2 million in CWSRF loans for a multiple-year endeavor to convert the open canal system to a piped, pressurized irrigation system to maximize water conservation and restore reliable water delivery to crops

Comparison of aerial imagery from manned and unmanned aircraft platforms for monitoring cotton growth

USDA-ARS?s Scientific Manuscript database

Unmanned aircraft systems (UAS) have emerged as a low-cost and versatile remote sensing platform in recent years, but little work has been done on comparing imagery from manned and unmanned platforms for crop assessment. The objective of this study was to compare imagery taken from multiple cameras ...

Development of partial ontogenic resistance to powdery mildew in Hop cones and its management implications

USDA-ARS?s Scientific Manuscript database

Knowledge of processes leading to crop damage is central to devising rational approaches to disease management. Multiple experiments established that infection of hop cones by Podosphaera macularis was most severe if inoculation occurred within 15 to 21 days after bloom. This period of infection was...

20 Years of Archival Ambition

ERIC Educational Resources Information Center

Byrne, Richard

2007-01-01

In this article, the author presents an interview with Thomas F. Staley, director of the Harry Ransom Humanities Research Center at the University of Texas. This interview touches on many issues that have cropped up in his long stay at the helm of the center, where Dr. Staley juggles the demands of multiple constituencies that include scholars,…

A transgene design for enhancing oil content in Arabidopsis and Camelina seeds

USDA-ARS?s Scientific Manuscript database

Increasing the oil yield is a major objective for oilseed crop improvement. Oil biosynthesis and accumulation are influenced by multiple genes involved in embryo and seed development. The LEAFY COTYLEDON1 (LEC1) is a master regulator of embryo development that also enhances the expression of genes i...

Modeling uncertainty of evapotranspiration measurements from multiple eddy covariance towers over a crop canopy

USDA-ARS?s Scientific Manuscript database

All measurements have random error associated with them. With fluxes in an eddy covariance system, measurement error can been modelled in several ways, often involving a statistical description of turbulence at its core. Using a field experiment with four towers, we generated four replicates of meas...

Biodiversity and Ecosystem Functioning: Exploring Principles of Ecology with Agricultural Plants

ERIC Educational Resources Information Center

Ruesink, Jennifer; O'Connor, Eileen; Sparks, Grace

2006-01-01

To date, little of the ecological research on biological diversity and ecosystem functioning has been carried out in agricultural systems, despite the fact that agriculture is a major contributor to loss of native habitats and species. However, agricultural research has demonstrated that polycultures of multiple crop species can have higher total…

Co-overexpression of OsSIZ1 and AVP1 in cotton substantially improves cotton growth and development under multiple-stress conditions

USDA-ARS?s Scientific Manuscript database

Environmental stresses such as salt, drought, and heat cause significant losses in crop production. Our laboratories employ genetic engineering to modify gene expression of selected genes to improve plant performance under environmental stress conditions. Previous studies by our group have shown tha...

Evaluation of Management Practices to Mitigate Pesticide Transport and Ecological Risk of Runoff from Agricultural and Turf Systems

USDA-ARS?s Scientific Manuscript database

Highly managed biotic systems such as agricultural crops and golf courses often require multiple applications of pesticides that may be transported with runoff to surrounding surface waters. Pesticides have been detected in surface waters of rural and urban watersheds invoking concern of their sour...

Multiple applications of ion chromatography oligosaccharide fingerprint profiles to solve a variety of sugar and sugar-biofuel industry problems

USDA-ARS?s Scientific Manuscript database

Sugar crops contain a broad variety of carbohydrates used for human consumption and the production of biofuels and bioproducts. Ion chromatography with integrated pulsed amperometric detection (IC-IPAD), also known as high performance anion exchange chromatography (HPAEC), can be used to simultaneo...

Soil microbial community response to corn stover harvesting under rain-fed, no-till conditions at multiple U.S. locations

USDA-ARS?s Scientific Manuscript database

Harvesting of corn stover for cellulosic ethanol production must be balanced with the requirement for returning plant residues to agricultural fields to maintain soil structure, fertility, crop protection, and other ecosystem services. High rates of corn stover removal can be associated with decrea...

Evaluating an Arachis hypogaea x Arachis diogoi interspecific hybrid derived population for multiple disease resistance

USDA-ARS?s Scientific Manuscript database

The peanut (Arachis hypogaea L.) crop in North Carolina is subject to yield and quality loss from a number of diseases including Cylindrocladium black rot (CBR) caused by Cylindrocladium parasiticum, early leaf spot (ELS) caused by Cercospora arachidicola, late leaf spot (LLS) caused by Cercosporidi...

Iron deficiency-induced changes in growth reveal differences in nutrient partitioning between two ecotypes of Medicago truncatula

USDA-ARS?s Scientific Manuscript database

Enhancing the nutritional quality of crops is of international importance, and multiple methods have been utilized to increase the nutrient content of legume seeds. Because nutrients mobilized from source leaves to growing reproductive sink tissues greatly contribute to the final composition of the ...

Developing host-plant resistance for hemipteran soybean pests: lessons from soybean aphid and stink bugs

USDA-ARS?s Scientific Manuscript database

Soybean is one of the world’s leading agricultural crops with multiple uses, including human food, animal feed, edible oil, biofuel, industrial products, cosmetics, etc. In soybean production, United States is the leading country with 33% of world’s total production of 251.5 million Metric tons. How...

Effects of environmental change on agriculture, nutrition and health: A framework with a focus on fruits and vegetables

PubMed Central

Tuomisto, Hanna L.; Scheelbeek, Pauline F.D.; Chalabi, Zaid; Green, Rosemary; Smith, Richard D.; Haines, Andy; Dangour, Alan D.

2017-01-01

Environmental changes are likely to affect agricultural production over the next  decades. The interactions between environmental change, agricultural yields and crop quality, and the critical pathways to future diets and health outcomes are largely undefined. There are currently no quantitative models to test the impact of multiple environmental changes on nutrition and health outcomes. Using an interdisciplinary approach, we developed a framework to link the multiple interactions between environmental change, agricultural productivity and crop quality, population-level food availability, dietary intake and health outcomes, with a specific focus on fruits and vegetables. The main components of the framework consist of: i) socio-economic and societal factors, ii) environmental change stressors, iii) interventions and policies, iv) food system activities, v) food and nutrition security, and vi) health and well-being outcomes. The framework, based on currently available evidence, provides an overview of the multidimensional and complex interactions with feedback between environmental change, production of fruits and vegetables, diets and health, and forms the analytical basis for future modelling and scenario testing. PMID:29511740

Growth, Morphogenesis, and Virulence of Candida albicans after Oral Inoculation in the Germ-Free and Conventional Chick1

PubMed Central

Balish, Edward; Phillips, A. W.

1966-01-01

Balish, Edward (Syracuse University, Syracuse, N.Y.), and A. W. Phillips. Growth, morphogenesis, and virulence of Candida albicans after oral inoculation in the germ-free and conventional chick. J. Bacteriol. 91:1736–1743. 1966.—The effects of intestinal bacteria on the multiplication, morphogenesis, and infectivity of Candida albicans in the alimentary tract were investigated by comparing results obtained in germ-free and conventional chicks after oral inoculation. This challenge resulted in the establishment of large numbers of the pathogen in the alimentary tract of each group of chicks; these numbers were increased in crop contents from challenged bacteria-free chicks wherein hyphae predominated over the yeast form. These animals also had lesions of the crop epithelium containing numerous hyphae and few yeast-like forms. In contrast, challenged conventional chicks receiving an adequate diet displayed no evidence of infection. Their alimentary tract contained the yeast form of C. albicans; no hyphae were seen. Although we found bacterial inhibition of C. albicans multiplication in the alimentary tract, this in itself did not seem to explain the resistance to intestinal candidiasis in our conventional chicks. We argued that this resistance to infection was due chiefly to the prevention of hyphal development in C. albicans by intestinal bacteria. C. albicans in the gut of our conventional chicks resulted in some increase in numbers of enterococci in contents from the crop. Increased pH values in contents from the gut of germ-free chicks were not clearly related to infection after challenge. The Eh of the above crop contents were only slightly decreased in the germ-free crop. Thus the Eh did not appear to be involved in susceptibility to infection. Invasion of the blood stream and kidneys of conventional chicks by the yeast form of C. albicans occurred in challenged animals receiving a purified diet which had been radiation-sterilized and stored for 6 months at room temperature (25 C). Their growth rate decreased and they became moribund; no hyphae were observed in tissues or intestine of these animals. Challenged bacteria-free chicks receiving the same diet were resistant to the above invasion, although they had crop lesions containing hyphae as described. The resistance of these chicks to systemic invasion was attributed to absence of intestinal bacteria competing for low levels of vitamins in the stored diet. Germ-free chicks had decreased levels of serum γ-globulin which increased after challenge, whereas this value was unchanged in conventional birds after challenge. Images PMID:4160824

Monitoring Global Food Security with New Remote Sensing Products and Tools

NASA Astrophysics Data System (ADS)

Budde, M. E.; Rowland, J.; Senay, G. B.; Funk, C. C.; Husak, G. J.; Magadzire, T.; Verdin, J. P.

2012-12-01

Global agriculture monitoring is a crucial aspect of monitoring food security in the developing world. The Famine Early Warning Systems Network (FEWS NET) has a long history of using remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and climate change. In recent years, it has become apparent that FEWS NET requires the ability to apply monitoring and modeling frameworks at a global scale to assess potential impacts of foreign production and markets on food security at regional, national, and local levels. Scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the University of California Santa Barbara (UCSB) Climate Hazards Group have provided new and improved data products as well as visualization and analysis tools in support of the increased mandate for remote monitoring. We present our monitoring products for measuring actual evapotranspiration (ETa), normalized difference vegetation index (NDVI) in a near-real-time mode, and satellite-based rainfall estimates and derivatives. USGS FEWS NET has implemented a Simplified Surface Energy Balance (SSEB) model to produce operational ETa anomalies for Africa and Central Asia. During the growing season, ETa anomalies express surplus or deficit crop water use, which is directly related to crop condition and biomass. We present current operational products and provide supporting validation of the SSEB model. The expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) production system provides FEWS NET with an improved NDVI dataset for crop and rangeland monitoring. eMODIS NDVI provides a reliable data stream with a relatively high spatial resolution (250-m) and short latency period (less than 12 hours) which allows for better operational vegetation monitoring. We provide an overview of these data and cite specific applications for crop monitoring. FEWS NET uses satellite rainfall estimates as inputs for monitoring agricultural food production and driving crop water balance models. We present a series of derived rainfall products and provide an update on efforts to improve satellite-based estimates. We also present advancements in monitoring tools, namely, the Early Warning eXplorer (EWX) and interactive rainfall and NDVI time series viewers. The EWX is a data analysis and visualization tool that allows users to rapidly visualize multiple remote sensing datasets and compare standardized anomaly maps and time series. The interactive time series viewers allow users to analyze rainfall and NDVI time series over multiple spatial domains. New and improved data products and more targeted analysis tools are a necessity as food security monitoring requirements expand and resources become limited.

Comparison of Hybrid Classifiers for Crop Classification Using Normalized Difference Vegetation Index Time Series: A Case Study for Major Crops in North Xinjiang, China

PubMed Central

Hao, Pengyu; Wang, Li; Niu, Zheng

2015-01-01

A range of single classifiers have been proposed to classify crop types using time series vegetation indices, and hybrid classifiers are used to improve discriminatory power. Traditional fusion rules use the product of multi-single classifiers, but that strategy cannot integrate the classification output of machine learning classifiers. In this research, the performance of two hybrid strategies, multiple voting (M-voting) and probabilistic fusion (P-fusion), for crop classification using NDVI time series were tested with different training sample sizes at both pixel and object levels, and two representative counties in north Xinjiang were selected as study area. The single classifiers employed in this research included Random Forest (RF), Support Vector Machine (SVM), and See 5 (C 5.0). The results indicated that classification performance improved (increased the mean overall accuracy by 5%~10%, and reduced standard deviation of overall accuracy by around 1%) substantially with the training sample number, and when the training sample size was small (50 or 100 training samples), hybrid classifiers substantially outperformed single classifiers with higher mean overall accuracy (1%~2%). However, when abundant training samples (4,000) were employed, single classifiers could achieve good classification accuracy, and all classifiers obtained similar performances. Additionally, although object-based classification did not improve accuracy, it resulted in greater visual appeal, especially in study areas with a heterogeneous cropping pattern. PMID:26360597

Origin of year-long bean (Phaseolus dumosus Macfady, Fabaceae) from reticulated hybridization events between multiple Phaseolus species.

PubMed

Mina-Vargas, Angela M; McKeown, Peter C; Flanagan, Nicola S; Debouck, Daniel G; Kilian, Andrzej; Hodkinson, Trevor R; Spillane, Charles

2016-08-06

Improved understanding of the secondary gene pools of crops is essential for advancing genetic gain in breeding programmes. Common bean, Phaseolus vulgaris, is a staple crop with several wild relatives in its secondary gene pool. The year-long bean, P. dumosus, an important crop in Guatemala, is considered particularly closely related to P. vulgaris and a potential source of novel variation. However, the genetic diversity and relationship to other Phaseolus species of P. dumosus remain unclear. We conducted the first comprehensive investigation of P. dumosus genetic diversity using both nuclear and chloroplast genome markers. Our nuclear marker set included over 700 markers present within the Phaseolus DArT (Diversity Arrays Technology) array, which we applied to P. dumosus and other relatives of P. vulgaris (including every secondary gene pool species: P. acutifolius, P. albescens, P. coccineus and P. costaricensis). Phaseolus dumosus arose from hybridization of P. vulgaris and P. coccineus, followed by at least two later hybridizations with sympatric congener populations. Existing P. dumosus collections have low genetic diversity. The under-utilized crop P. dumosus has a complex hybrid origin. Further sampling in the region in which it arose may uncover additional germplasm for introgressing favourable traits into crops within the P. vulgaris gene pool. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Regional-scale yield simulations using crop and climate models: assessing uncertainties, sensitivity to temperature and adaptation options

NASA Astrophysics Data System (ADS)

Challinor, A. J.

2010-12-01

Recent progress in assessing the impacts of climate variability and change on crops using multiple regional-scale simulations of crop and climate (i.e. ensembles) is presented. Simulations for India and China used perturbed responses to elevated carbon dioxide constrained using observations from FACE studies and controlled environments. Simulations with crop parameter sets representing existing and potential future adapted varieties were also carried out. The results for India are compared to sensitivity tests on two other crop models. For China, a parallel approach used socio-economic data to account for autonomous farmer adaptation. Results for the USA analysed cardinal temperatures under a range of local warming scenarios for 2711 varieties of spring wheat. The results are as follows: 1. Quantifying and reducing uncertainty. The relative contribution of uncertainty in crop and climate simulation to the total uncertainty in projected yield changes is examined. The observational constraints from FACE and controlled environment studies are shown to be the likely critical factor in maintaining relatively low crop parameter uncertainty. Without these constraints, crop simulation uncertainty in a doubled CO2 environment would likely be greater than uncertainty in simulating climate. However, consensus across crop models in India varied across different biophysical processes. 2. The response of yield to changes in local mean temperature was examined and compared to that found in the literature. No consistent response to temperature change was found across studies. 3. Implications for adaptation. China. The simulations of spring wheat in China show the relative importance of tolerance to water and heat stress in avoiding future crop failures. The greatest potential for reducing the number of harvests less than one standard deviation below the baseline mean yield value comes from alleviating water stress; the greatest potential for reducing harvests less than two standard deviations below the mean comes from alleviation of heat stress. The socio-economic analysis suggests that adaptation is also possible through measures such as greater investment. India. The simulations of groundnut in India identified regions where heat stress will play an increasing role in limiting crop yields, and other regions where crops with greater thermal time requirement will be needed. The simulations were used, together with an observed dataset and a simple analysis of crop cardinal temperatures and thermal time, to estimate the potential for adaptation using existing cultivars. USA. Analysis of spring wheat in the USA showed that at +2oC of local warming, 87% of the 2711 varieties examined, and all of the five most common varieties, could be used to maintain the crop duration of the current climate (i.e. successful adaptation to mean warming). At +4o this fell to 54% of all varieties, and two of the top five. 4. Future research. The results, and the limitations of the study, suggest directions for research to link climate and crop models, socio-economic analyses and crop variety trial data in order to prioritise adaptation options such as capacity building, plant breeding and biotechnology.

Spectral variations of canopy reflectance in support of precision agriculture

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi; Borisova, Denitsa; Nikolov, Hristo

2014-05-01

Agricultural monitoring is an important and continuously spreading activity in remote sensing and applied Earth observations. It supplies precise, reliable and valuable information on current crop condition and growth processes. In agriculture, the timing of seasonal cycles of crop activity is important for species classification and evaluation of crop development, growing conditions and potential yield. The correct interpretation of remotely sensed data, however, and the increasing demand for data reliability require ground-truth knowledge of the seasonal spectral behavior of different species and their relation to crop vigor. For this reason, we performed ground-based study of the seasonal response of winter wheat reflectance patterns to crop growth patterns. The goal was to quantify crop seasonality by establishing empirical relationships between plant biophysical and spectral properties in main ontogenetic periods. Phenology and agro-specific relationships allow assessing crop condition during different portions of the growth cycle and thus effectively tracking plant development, and finally make yield predictions. The applicability of a number of vegetation indices (VIs) for monitoring crop seasonal dynamics, its health condition, and yield potential was examined. Special emphasis we put on narrow-band indices as the availability of data from hyperspectral imagers is unavoidable future. The temporal behavior of vegetation indices revealed increased sensitivity to crop growth. The derived spectral-biophysical relationships allowed extraction of quantitative information about crop variables and yield at different stages of the phenological development. Relating plant spectral and biophysical variables in a phenology-based manner allows crop monitoring, that is crop diagnosis and predictions to be performed multiple times during plant ontogenesis. During active vegetative periods spectral data was highly indicative of plant growth trends and yield potential. The VIs values contributed to reliable yield prediction and showed very good correspondence with the estimates from biophysical models. For dates before full maturity most of the examined VIs proved to be meaningful statistical predictors of crop state-indicative biophysical variables. High correlations were obtained for canopy cover fraction, LAI, and biomass. Sensitivity to red, near-infrared and green reflectance showed both vigorous and stressed plants. As crops attained advanced growth stages, decreased sensitivity of VIs and weaker correlations with bioparameters were observed, yet still significant in a statistical sense. The results highlight the capability of the presented approach to track the dynamics of crop growth from multitemporal spectral data, and illustrate the prediction accuracy of the spectral models. The results are useful in assessing the efficiency of various spectral band ratios and other vegetation indices often used in remote sensing studies of natural and agricultural vegetation. They suggest that the used algorithm for data processing is particularly suitable for airborne cropland monitoring and could be expanded to sites at farm or municipality scale. The results reported are from pilot study carried out on a plot located in one of the established polygons for experimental crop monitoring. In the mentioned research GIS database is established for supporting the experiments and modelling process. Recommendations on good farming practices for medium sized farms for monitoring stress conditions such as drought and overfertilizing are developed.

Simulation of targeted pollutant-mitigation-strategies to reduce nitrate and sediment hotspots in agricultural watershed.

PubMed

Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T

2017-12-31

About 50% of U.S. water pollution problems are caused by non-point source (NPS) pollution, primarily sediment and nutrients from agricultural areas, despite the widespread implementation of agricultural Best Management Practices (BMPs). However, the effectiveness of implementation strategies and type of BMPs at watershed scale are still not well understood. In this study, the Soil and Water Assessment Tool (SWAT) ecohydrological model was used to assess the effectiveness of pollutant mitigation strategies in the Raccoon River watershed (RRW) in west-central Iowa, USA. We analyzed fourteen management scenarios based on systematic combinations of five strategies: fertilizer/manure management, changing row-crop land to perennial grass, vegetative filter strips, cover crops and shallower tile drainage systems, specifically aimed at reducing nitrate and total suspended sediment yields from hotspot areas in the RRW. Moreover, we assessed implications of climate change on management practices, and the impacts of management practices on water availability, row crop yield, and total agricultural production. Our results indicate that sufficient reduction of nitrate load may require either implementation of multiple management practices (38.5% with current setup) or conversion of extensive areas into perennial grass (up to 49.7%) to meet and maintain the drinking water standard. However, climate change may undermine the effectiveness of management practices, especially late in the 21st century, cutting the reduction by up to 65% for nitrate and more for sediment loads. Further, though our approach is targeted, it resulted in a slight decrease (~5%) in watershed average crop yield and hence an overall reduction in total crop production, mainly due to the conversion of row-crop lands to perennial grass. Such yield reductions could be quite spatially heterogeneously distributed (0 to 40%). Copyright © 2017 Elsevier B.V. All rights reserved.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

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

Investigating the effect of previous treatments on wheat biomass over multiple spatial frequencies

NASA Astrophysics Data System (ADS)

Milne, A. E.; Castellanos, M. T.; Cartagena, M. C.; Tarquis, A. M.; Lark, R. M.

2010-09-01

In this study we use the maximum overlap discrete packet transform (MODWPT) to investigate residual effects on wheat biomass of fertigation treatments applied to a previous crop. The wheat crop covered nine subplots from a previous experiment on melon response to fertigation. Each subplot had previously received a different level of applied nitrogen. Many factors affect wheat biomass, causing it to vary at different spatial frequencies. We hypothesize that these will include residual effects from fertilizer application (at relatively low spatial frequencies) and the local influence of individual plants from the previous melon crop (at high frequency). To test this hypothesis we use the MODWPT to identify the dominant spatial frequencies of wheat biomass variation, and analyse the relationship to both the previous fertilizer application and the location of individual melon plants in the previous crop. The MODWPT is particularly appropriate for this because it allows us first to identify the key spatial frequencies in the wheat biomass objectively and to analyse them, and their relationship to hypothesized driving factors without any assumptions of uniformity (stationarity) of wheat-biomass variation. The results showed that the applied nitrogen dominated the wheat biomass response, and that there was a noticeable component of wheat-biomass variation at the spatial frequency that corresponds to the melon cropping. We expected wheat biomass to be negatively correlated with the position of melons in the previous crop, due to uptake of the applied nitrogen. The MODWPT, which allows us to detect changes in correlation between variables at different frequencies, showed that such a relationship was found across part of the experiment but not uniformly.

Polymorphisms associated with a tropical climate and root crop diet induce susceptibility to metabolic and cardiovascular diseases in Solomon Islands.

PubMed

Furusawa, Takuro; Naka, Izumi; Yamauchi, Taro; Natsuhara, Kazumi; Eddie, Ricky; Kimura, Ryosuke; Nakazawa, Minato; Ishida, Takafumi; Ohtsuka, Ryutaro; Ohashi, Jun

2017-01-01

The people of the Solomon Islands represent an Austronesian (AN)-speaking population's adaptation to a humid tropical environment and subsistence of tuberous crops. Genome-wide association studies (GWASs) of other populations (e.g. the Human Genome Diversity Project [HGDP]) have suggested the existence of genotypes adaptive to ecoregion, diet, and subsistence, and that those genotypes are also associated with metabolic and cardiovascular diseases. Recently, the incidence of non-communicable diseases has been increasing in the Solomon Islands. In the present study, we explored the association of genotypes adaptive to a tropical environment and tuberous crop diet with metabolic and cardiovascular conditions in rural and urban AN-speaking Melanesian and Micronesian populations of the Solomon Islands. A total of 561 participants were genotyped for single nucleotide polymorphisms (SNPs) potentially associated with a tropical environment (rs174570 and rs2237892) and a tuberous crop diet (rs162036, rs185819, and rs2722425). The results showed that the allele frequencies of the Solomon Islands populations adopted patterns similar to those in populations from other hot, tropical areas with a tuberous crop diet in previous studies. Furthermore, rs162036, rs185819, rs2237892, and rs2722425 were all strongly associated with one or more metabolic and cardiovascular conditions. The derived allele of rs2722425 (i.e. rs2722425-G) was significantly associated with an elevated LDL level (P = 0.000264) even after the significance level was adjusted for multiple testing (i.e., α = 0.0005). Our results suggest that the inhabitants of the Solomon Islands exhibit the effects of the tropical environment and tuberous crop diet on their allele frequencies, and that their susceptibility to metabolic and cardiovascular diseases is therefore considered to be associated with their environment and diet.

Impact of switching crop type on water and solute fluxes in deep vadose zone

NASA Astrophysics Data System (ADS)

Turkeltaub, T.; Kurtzman, D.; Russak, E. E.; Dahan, O.

2015-12-01

Switching crop type and consequently changing irrigation and fertilization regimes lead to alterations in deep percolation and solute concentrations of pore water. Herein, observations from the deep vadose zone and model simulations demonstrate the changes in water, chloride, and nitrate fluxes under a commercial greenhouse following the change from tomato to lettuce cropping. The site, located above a phreatic aquifer, was monitored for 5 years. A vadose-zone monitoring system was implemented under the greenhouse and provided continuous data on both temporal variations in water content and chemical composition of the pore water at multiple depths in the deep vadose zone (up to 20 m). Following crop switching, a significant reduction in chloride concentration and dramatic increase in nitrate were observed across the unsaturated zone. The changes in chemical composition of the vadose-zone pore water appeared as sequential breakthroughs across the unsaturated zone, initiating at land surface and propagating down toward the water table. Today, 3 years after switching the crops, penetration of the impact exceeds 10 m depth. Variations in the isotopic composition of nitrate (18O and 15N) in water samples obtained from the entire vadose zone clearly support a fast leaching process and mobilization of solutes across the unsaturated zone following the change in crop type. Water flow and chloride transport models were calibrated to observations acquired during an enhanced infiltration experiment. Forward simulation runs were performed with the calibrated models, constrained to tomato and lettuce cultivation regimes as surface boundary conditions. Predicted chloride and nitrate concentrations were in agreement with the observed concentrations. The simulated water drainage and nitrogen leaching implied that the observed changes are an outcome of recommended agricultural management practices.

Geographic risk modeling of childhood cancer relative to county-level crops, hazardous air pollutants and population density characteristics in Texas.

PubMed

Thompson, James A; Carozza, Susan E; Zhu, Li

2008-09-25

Childhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types. More specific exposure assessments are needed. It would be helpful to optimize future studies to incorporate knowledge of high-risk locations or geographic risk patterns. The objective of this study was to evaluate potential geographic risk patterns in Texas accounting for the possibility that multiple cancers may have similar geographic risks patterns. A spatio-temporal risk modeling approach was used, whereby 19 childhood cancer types were modeled as potentially correlated within county-years. The standard morbidity ratios were modeled as functions of intensive crop production, intensive release of hazardous air pollutants, population density, and rapid population growth. There was supportive evidence for elevated risks for germ cell tumors and "other" gliomas in areas of intense cropping and for hepatic tumors in areas of intense release of hazardous air pollutants. The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population. Elevated spatial risks included four cancer histotypes, "other" leukemias, Central Nervous System (CNS) embryonal tumors, CNS other gliomas and hepatic tumors with greater than 95% likelihood of elevated risks in at least one county. The Bayesian implementation of the Multivariate Conditional Autoregressive model provided a flexible approach to the spatial modeling of multiple childhood cancer histotypes. The current study identified geographic factors supporting more focused studies of germ cell tumors and "other" gliomas in areas of intense cropping, hepatic cancer near Hazardous Air Pollutant (HAP) release facilities and specific locations with increased risks for CNS embryonal tumors and for "other" leukemias. Further study should be performed to evaluate potentially lower risk for Hodgkin lymphoma and malignant bone tumors in counties with rapidly growing population.

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

PubMed Central

Shi, Yeyin; Thomasson, J. Alex; Murray, Seth C.; Pugh, N. Ace; Rooney, William L.; Shafian, Sanaz; Rajan, Nithya; Rouze, Gregory; Morgan, Cristine L. S.; Neely, Haly L.; Rana, Aman; Bagavathiannan, Muthu V.; Henrickson, James; Bowden, Ezekiel; Valasek, John; Olsenholler, Jeff; Bishop, Michael P.; Sheridan, Ryan; Putman, Eric B.; Popescu, Sorin; Burks, Travis; Cope, Dale; Ibrahim, Amir; McCutchen, Billy F.; Baltensperger, David D.; Avant, Robert V.; Vidrine, Misty; Yang, Chenghai

2016-01-01

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs. PMID:27472222

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

Elicitor-Based Biostimulant PSP1 Protects Soybean Against Late Season Diseases in Field Trials

PubMed Central

Chalfoun, Nadia R.; Durman, Sandra B.; González-Montaner, Jorge; Reznikov, Sebastián; De Lisi, Vicente; González, Victoria; Moretti, Enrique R.; Devani, Mario R.; Ploper, L. Daniel; Castagnaro, Atilio P.; Welin, Björn

2018-01-01

Currently, fungicide application in soybean production accounts for an important amount of global pesticide use, and it is therefore most desirable to find new healthier and more environmental friendly alternatives for the phytosanitary management in this crop. In this study, we present convincing evidence for effective induction of disease protection by the agricultural biostimulant PSP1, a formulation based on the plant-defense eliciting activity of the fungal protease AsES (Acremonium strictum elicitor subtilisin), in multiple field trials in Argentina. PSP1 was shown to combine well with commercial spray adjuvants, an insecticide, a herbicide and fungicides used in Argentinian soybean production without losing any defense-inducing activity, indicating an easy and efficient adaptability to conventional soybean production and disease management in the region. Results from multiple soybean field trials conducted with different elite genotypes at several locations during two consecutive growing seasons, showed that PSP1 is able to induce an enhanced pathogen defense which effectively reduced late season disease (LSD) development in field-grown soybean. This defense response seems to be broad-range as disease development was clearly reduced for at least three different fungi causing LSDs in soybean (Septoria glycines, Cercospora kikuchii and Cercospora sojina). It was noteworthy that application of PSP1 in soybean alone gave a similar protection against fungal diseases as compared to the commercial fungicides included in the field trials and that PSP1 applied together with a fungicide at reproductive stages enhanced disease protection and significantly increased grain yields. PSP1 is the first example of an elicitor-based strategy in order to efficiently control multiple fungal diseases under field conditions in the soybean crop. These results show the feasibility of using induced resistance products as complements or even full-good replacements to currently used chemical pesticides, fulfilling a role as important components of a more sustainable crop disease management system. PMID:29946326

Using water vapor isotopes to examine evapotranspiration dynamics in corn and miscanthus reveals challenges to the technique as well as seasonal differences between crops.

NASA Astrophysics Data System (ADS)

Miller, J. N.; Bernacchi, C.

2016-12-01

Second-generation biofuel crops are being planted at an increasing extent around the globe. Changing land use from common field crops to perennial biofuel crops such as miscanthus or switchgrass is expected to alter ecohydrology via changes in evapotranspiration (ET). However, the direction in which evapotranspiration will shift, either partitioning more moisture through soil evaporation (E) or through plant transpiration (T) is uncertain. To investigate how land conversion from maize to miscanthus affects ET partitioning we measured the isotopic composition of water vapor via continuous air sampling. We obtained continuous diurnal measurements of δ2H and δ18O for miscanthus and maize on multiple days over the course of the growing season. Water vapor isotopes drawn from two heights were measured at 2 Hz using a cavity ringdown spectrometer and partitioned into components of E and T using a simple mixing equation. Partitioning was also accomplished with a combination of sap flow sensors and soil lysimeters. Preliminary results reveal that while daily transpiration fraction can be strongly influenced by meteorological events, the whole season transpiration fraction dominates variations in ET in miscanthus fields more so than in fields of maize.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

Agriculturally Relevant Climate Extremes and Their Trends in the World's Major Growing Regions

NASA Astrophysics Data System (ADS)

Zhu, Xiao; Troy, Tara J.

2018-04-01

Climate extremes can negatively impact crop production, and climate change is expected to affect the frequency and severity of extremes. Using a combination of in situ station measurements (Global Historical Climatology Network's Daily data set) and multiple other gridded data products, a derived 1° data set of growing season climate indices and extremes is compiled over the major growing regions for maize, wheat, soybean, and rice for 1951-2006. This data set contains growing season climate indices that are agriculturally relevant, such as the number of hot days, duration of dry spells, and rainfall intensity. Before 1980, temperature-related indices had few trends; after 1980, statistically significant warming trends exist for each crop in the majority of growing regions. In particular, crops have increasingly been exposed to extreme hot temperatures, above which yields have been shown to decline. Rainfall trends are less consistent compared to temperature, with some regions receiving more rainfall and others less. Anomalous temperature and precipitation conditions are shown to often occur concurrently, with dry growing seasons more likely to be hotter, have larger drought indices, and have larger vapor pressure deficits. This leads to the confluence of a variety of climate conditions that negatively impact crop yields. These results show a consistent increase in global agricultural exposure to negative climate conditions since 1980.

Enhancing agricultural productivity and rural incomes through sustainable use of natural resources in the semi arid tropics.

PubMed

Wani, Suhas P; Dixin, Yin; Li, Zhong; Dar, William D; Chander, Girish

2012-03-30

A participatory watershed management approach is one of the tested, sustainable and eco-friendly options to upgrade rain-fed agriculture to meet growing food demand along with additional multiple benefits in terms of improving livelihoods, addressing equity issues and biodiversity concerns. Watershed interventions at study sites in Thailand (Tad Fa and Wang Chai) and India (Kothapally) effectively reduced runoff and the associated soil loss. Such interventions at Xiaoxincun (China) and Wang Chai improved groundwater recharging and availability. Enhanced productive transpiration increased rainwater use efficiency for crop production by 13-29% at Xiaoxincun; 13-160% at Lucheba (China), 32-37% at Tad Fa and 23-46% at Wang Chai and by two to five times at Kothapally. Watershed interventions increased significantly the additional net returns from crop production as compared with the pre-watershed intervention period. Increased water availability opened up options for crop diversification with high-value crops, including increased forage production and boosted livestock-based livelihoods. In dryland tropics, integrated watershed management approach enabled farmers to diversify the systems along with increasing agricultural productivity through increased water availability, while conserving the natural resource base. Household incomes increased substantially, leading to improved living and building the resilience of the community and natural resources. Copyright © 2011 Society of Chemical Industry.

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.

Plant pathogen nanodiagnostic techniques: forthcoming changes?

PubMed Central

Khiyami, Mohammad A.; Almoammar, Hassan; Awad, Yasser M.; Alghuthaymi, Mousa A.; Abd-Elsalam, Kamel A.

2014-01-01

Plant diseases are among the major factors limiting crop productivity. A first step towards managing a plant disease under greenhouse and field conditions is to correctly identify the pathogen. Current technologies, such as quantitative polymerase chain reaction (Q-PCR), require a relatively large amount of target tissue and rely on multiple assays to accurately identify distinct plant pathogens. The common disadvantage of the traditional diagnostic methods is that they are time consuming and lack high sensitivity. Consequently, developing low-cost methods to improve the accuracy and rapidity of plant pathogens diagnosis is needed. Nanotechnology, nano particles and quantum dots (QDs) have emerged as essential tools for fast detection of a particular biological marker with extreme accuracy. Biosensor, QDs, nanostructured platforms, nanoimaging and nanopore DNA sequencing tools have the potential to raise sensitivity, specificity and speed of the pathogen detection, facilitate high-throughput analysis, and to be used for high-quality monitoring and crop protection. Furthermore, nanodiagnostic kit equipment can easily and quickly detect potential serious plant pathogens, allowing experts to help farmers in the prevention of epidemic diseases. The current review deals with the application of nanotechnology for quicker, more cost-effective and precise diagnostic procedures of plant diseases. Such an accurate technology may help to design a proper integrated disease management system which may modify crop environments to adversely affect crop pathogens. PMID:26740775

Characterisation of caecum and crop microbiota of Indian indigenous chicken targeting multiple hypervariable regions within 16S rRNA gene.

PubMed

Saxena, S; Saxena, V K; Tomar, S; Sapcota, D; Gonmei, G

2016-06-01

A comparative analysis of caecum and crop microbiota of chick, grower and adult stages of Indian indigenous chickens was conducted to investigate the role of the microbiota of the gastrointestinal tract, which play an important role in host performance, health and immunity. High-throughput Illumina sequencing was performed for V3, V4 and V4-V6 hypervariable regions of the 16S rRNA gene. M5RNA and M5NR databases under MG-RAST were used for metagenomic datasets annotation. In the crop, Firmicutes (~78%) and Proteobacteria (~16%) were the predominant phyla whereas in the caecum, Firmicutes (~50%), Bacteroidetes (~29%) and Actinobacteria (~10%) were predominant. The Shannon-Wiener diversity index suggested that sample richness and diversity increased as the chicken aged. For the first time, the presence of Lactobacillus species such as L. frumenti, L. antri, L. mucosae in the chicken crop along with Kineococcus radiotolerans, Desulfohalobium retbaense and L. jensenii in the caecum are reported. Many of these bacterial species have been found to be involved in immune response modulation and disease prevention in pigs and humans. The gut microbiome of the indigenous chicken was enriched with microbes having probiotic potential which might be essential for their adaptability.

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.

Evaluating the influence of plant-specific physiological parameterizations on the partitioning of land surface energy fluxes

NASA Astrophysics Data System (ADS)

Sulis, Mauro; Langensiepen, Matthias; Shrestha, Prabhakar; Schickling, Anke; Simmer, Clemens; Kollet, Stefan

2015-04-01

Vegetation has a significant influence on the partitioning of radiative forcing, the spatial and temporal variability of soil water and soil temperature. Therefore plant physiological properties play a key role in mediating and amplifying interactions and feedback mechanisms in the soil-vegetation-atmosphere continuum. Because of the direct impact on latent heat fluxes, these properties may also influence weather generating processes, such as the evolution of the atmospheric boundary layer (ABL). In land surface models, plant physiological properties are usually obtained from literature synthesis by unifying several plant/crop species in predefined vegetation classes. In this work, crop-specific physiological characteristics, retrieved from detailed field measurements, are included in the bio-physical parameterization of the Community Land Model (CLM), which is a component of the Terrestrial Systems Modeling Platform (TerrSysMP). The measured set of parameters for two typical European mid-latitudinal crops (sugar beet and winter wheat) is validated using eddy covariance measurements (sensible heat and latent heat) over multiple years from three measurement sites located in the North Rhine-Westphalia region, Germany. We found clear improvements of CLM simulations, when using the crop-specific physiological characteristics of the plants instead of the generic crop type when compared to the measurements. In particular, the increase of latent heat fluxes in conjunction with decreased sensible heat fluxes as simulated by the two new crop-specific parameter sets leads to an improved quantification of the diurnal energy partitioning. These findings are cross-validated using estimates of gross primary production extracted from net ecosystem exchange measurements. This independent analysis reveals that the better agreement between observed and simulated latent heat using the plant-specific physiological properties largely stems from an improved simulation of the photosynthesis process owing to a better estimation of the Rubisco enzyme kinematics. Finally, to evaluate the effects of the crop-specific parameterizations on the ABL dynamics, we perform a series of semi-idealized land-atmosphere coupled simulations by hypothesizing three cropland configurations. These numerical experiments reveal different heat and moisture budgets of the ABL that clearly impact the evolution of the boundary layer when using the crop-specific physiological properties.

Retrieval of canopy water content of different crop types with two new hyperspectral indices: Water Absorption Area Index and Depth Water Index

NASA Astrophysics Data System (ADS)

Pasqualotto, Nieves; Delegido, Jesús; Van Wittenberghe, Shari; Verrelst, Jochem; Rivera, Juan Pablo; Moreno, José

2018-05-01

Crop canopy water content (CWC) is an essential indicator of the crop's physiological state. While a diverse range of vegetation indices have earlier been developed for the remote estimation of CWC, most of them are defined for specific crop types and areas, making them less universally applicable. We propose two new water content indices applicable to a wide variety of crop types, allowing to derive CWC maps at a large spatial scale. These indices were developed based on PROSAIL simulations and then optimized with an experimental dataset (SPARC03; Barrax, Spain). This dataset consists of water content and other biophysical variables for five common crop types (lucerne, corn, potato, sugar beet and onion) and corresponding top-of-canopy (TOC) reflectance spectra acquired by the hyperspectral HyMap airborne sensor. First, commonly used water content index formulations were analysed and validated for the variety of crops, overall resulting in a R2 lower than 0.6. In an attempt to move towards more generically applicable indices, the two new CWC indices exploit the principal water absorption features in the near-infrared by using multiple bands sensitive to water content. We propose the Water Absorption Area Index (WAAI) as the difference between the area under the null water content of TOC reflectance (reference line) simulated with PROSAIL and the area under measured TOC reflectance between 911 and 1271 nm. We also propose the Depth Water Index (DWI), a simplified four-band index based on the spectral depths produced by the water absorption at 970 and 1200 nm and two reference bands. Both the WAAI and DWI outperform established indices in predicting CWC when applied to heterogeneous croplands, with a R2 of 0.8 and 0.7, respectively, using an exponential fit. However, these indices did not perform well for species with a low fractional vegetation cover (<30%). HyMap CWC maps calculated with both indices are shown for the Barrax region. The results confirmed the potential of using generically applicable indices for calculating CWC over a great variety of crops.

Integrated Adaptive Scenarios for Ariculture: Synergies and Tradeoffs.

NASA Astrophysics Data System (ADS)

Malek, K.; Rajagopalan, K.; Adam, J. C.; Brady, M.; Stockle, C.; Liu, M.; Kruger, C. E.

2017-12-01

A wide variety of factors can drive adaptation of the agricultural production sector in response to climate change. Warming and increased growing season length can lead to adoption of newer plant varieties as well as increases in double cropping systems. Changes in expectations of drought frequency or economic factors could lead to adoption of new technology (such as irrigation technology or water trading systems) or crop choices with a view of reducing farm-level risk, and these choices can result in unintended system wide effects. These are all examples of producer adaptation decisions made with a long-term (multiple decades) view. In addition, producers respond to short-term (current year) shocks - such as drought events - through management strategies that include deficit irrigation, fallowing, nutrient management, and engaging in water trading. The effects of these short- and long-term decisions are not independent, and can drive or be driven by the other. For example, investment in new irrigation systems (long-term) can be driven by expectations of short-term crop productivity losses in drought years. Similarly, the capacity to manage for short-term shocks will depend on crop type and variety as well as adopted irrigation technologies. Our overarching objective is to understand the synergies and tradeoffs that exist when combining three potential long-term adaptation strategies and two short-term adaptation strategies, with a view of understanding the synergies and tradeoffs. We apply the integrated crop-hydrology modeling framework VIC-CropSyst, along with the water management module Yakima RiverWare to address these questions over our test area, the Yakima River basin. We consider adoption of a) more efficient irrigation technologies, slower growing crop varieties, and increased prevalence of double cropping systems as long-term adaptation strategies; and b) fallowing and deficit irrigation as short-term responses to droughts. We evaluate the individual and combined effect of these strategies on agricultural production. Preliminary results indicate that long-term adaptation strategies impact short-run adaptive capacities to drought shocks. The strategies are complementary under certain situations and results in tradeoffs in other situations, and we characterize these differences.

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

PubMed

Thorburn, Peter J; Biggs, Jody S; Palmer, Jeda; Meier, Elizabeth A; Verburg, Kirsten; Skocaj, Danielle M

2017-01-01

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ∼0.3 Mg cane (kg N) -1 , where yields were low (i.e., <50 Mg ha -1 ) and N inputs were high, to >5 Mg cane (kg N) -1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting, decisions support systems and enhanced efficiency fertilizers have potential for making N fertilizer management more site specific, an action that should facilitate increased NUE.

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops

PubMed Central

Thorburn, Peter J.; Biggs, Jody S.; Palmer, Jeda; Meier, Elizabeth A.; Verburg, Kirsten; Skocaj, Danielle M.

2017-01-01

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ∼0.3 Mg cane (kg N)-1, where yields were low (i.e., <50 Mg ha-1) and N inputs were high, to >5 Mg cane (kg N)-1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting, decisions support systems and enhanced efficiency fertilizers have potential for making N fertilizer management more site specific, an action that should facilitate increased NUE. PMID:28928756

Impacts of multiple global environmental changes on African crop yield and water use efficiency: Implications to food and water security

NASA Astrophysics Data System (ADS)

Pan, S.; Yang, J.; Zhang, J.; Xu, R.; Dangal, S. R. S.; Zhang, B.; Tian, H.

2016-12-01

Africa is one of the most vulnerable regions in the world to climate change and climate variability. Much concern has been raised about the impacts of climate and other environmental factors on water resource and food security through the climate-water-food nexus. Understanding the responses of crop yield and water use efficiency to environmental changes is particularly important because Africa is well known for widespread poverty, slow economic growth and agricultural systems particularly sensitive to frequent and persistent droughts. However, the lack of integrated understanding has limited our ability to quantify and predict the potential of Africa's agricultural sustainability and freshwater supply, and to better manage the system for meeting an increasing food demand in a way that is socially and environmentally or ecologically sustainable. By using the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed the spatial and temporal patterns of crop yield, evapotranspiration (ET) and water use efficiency across entire Africa in the past 35 years (1980-2015) and the rest of the 21st century (2016-2099). Our preliminary results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion (about 50%), elevated atmospheric CO2 concentration, and nitrogen deposition. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Climate extremes especially droughts and heat wave have largely reduced crop yield in the most vulnerable regions. Our results indicate that N fertilizer could be a major driver to improve food security in Africa. Future climate warming could reduce crop yield and shift cropland distribution. Our study further suggests that improving water use efficiency through land management practices including the increased uses of fertilizers and irrigation will be the key for reducing the loss of crop yield in a warming climate and extreme weather.

The cultivation of energy crops for biogas production and the application of digestates are characterized by high variability of CO2 exchange and soil organic C stock changes

NASA Astrophysics Data System (ADS)

Augustin, Juergen; Fiedler, Sebastian; Heintze, Gawan; Rohwer, Marcus; Prescher, Anne-Katrin; Pohl, Madlen; Jurisch, Nicole; Hagemann, Ulrike

2017-04-01

In Germany, agricultural production accounts for approx. 15% of total anthropogenic greenhouse gas emissions. The cultivation of energy crops is thus considered an important option to reduce the climate impact and maintain or increase soil organic carbon (SOC) stocks. In particular, this applies to the continuously expanding cultivation of energy crops for biogas production and the associated use of residues from anaerobic digestion (digestates) as organic fertilizer. To date, there is only limited and contradicting evidence on the impacts of this management practice on the CO2 exchange as well as the change of SOC stocks. We will present results from a 4-year field study at 5 sites in Germany using identical methods to investigate the interacting effects of i) 3 N-fertilizer treatments including calcium ammonium nitrate and digestates and ii) a crop rotation of 7 energy crops like maize, sorghum, triticale, and wheat on net ecosystem CO2 exchange (NEE) and the change of SOC stocks. We used the manual chamber approach for measuring NEE as the difference between gross primary production and ecosystem respiration. The determination of SOC stock changes was based on a C budget approach, which includes the cumulated annual NEE, the C export by harvest, and the C import by application of anaerobic digestates. The CO2 exchange and the change of SOC stocks were influenced by multiple factors like crop, site, fertilization, and climate, as well as their complex interactions. A large proportion of the variability of the CO2 exchange can be attributed to interannual climatic variability. Productive crops like maize and sorghum generally feature the most intensive CO2 exchange, while less productive crops can compensate for this by means of longer cultivation times. Regardless of the extreme variability, pronounced and partly significant differences of NEE and C budgets between sites were observed. On average, SOC stocks declined over a full crop rotation, but with highly variable positive and negative C budgets. This indicates that, in most cases, neither the selected crops nor the application of anaerobic digestates were sufficient to compensate for SOC losses. Apparently, the potential of anaerobic digestates to maintain or increase SOC stocks is considerably smaller than expected. If continuous decreases of SOC stocks due to energy crop cultivation are to be avoided, additional studies on the optimization of crop rotations (selection of plants with high C input), and digestate fertilization (type of digestate, amount and application technique) are required. A continuously improved version of the methodology used in this study promises faster and more precise results than classic long-term field trials.

Hormone balance and abiotic stress tolerance in crop plants.

PubMed

Peleg, Zvi; Blumwald, Eduardo

2011-06-01

Plant hormones play central roles in the ability of plants to adapt to changing environments, by mediating growth, development, nutrient allocation, and source/sink transitions. Although ABA is the most studied stress-responsive hormone, the role of cytokinins, brassinosteroids, and auxins during environmental stress is emerging. Recent evidence indicated that plant hormones are involved in multiple processes. Cross-talk between the different plant hormones results in synergetic or antagonic interactions that play crucial roles in response of plants to abiotic stress. The characterization of the molecular mechanisms regulating hormone synthesis, signaling, and action are facilitating the modification of hormone biosynthetic pathways for the generation of transgenic crop plants with enhanced abiotic stress tolerance. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of sorghum germplasm from Burkina Faso and South Africa to identify new sources of resistance to grain mold and anthracnose

USDA-ARS?s Scientific Manuscript database

Sorghum is an important worldwide crop whose yield can be significantly reduced by anthracnose (Colletotrichum sublineola) and grain mold diseases (multiple fungi). The identification of new genetic sources of resistance to both diseases is imperative for the development of new sorghum varieties. T...

Phenotypic variation and identification of quantitative trait loci for ozone injury in a Fiskeby III x Mandarin (Ottawa) soybean population

USDA-ARS?s Scientific Manuscript database

Ground-level ozone reduces yield in crops such as soybean (Glycine max (L.) Merr.). Phenotypic variation has been observed for this trait in multiple species; however, breeding for ozone tolerance has been limited. A recombinant inbred population was developed from soybean genotypes differing in tol...

Storage rot in sugar beet: variable response over time and with different host germplasm

USDA-ARS?s Scientific Manuscript database

Sugar beet (Beta vulgaris) is commonly stored in outdoor piles prior to processing for food and animal feed. While in storage the crop is subject to multiple post-harvest rots. In the Michigan growing region, little loss due to storage rots is observed until beets have been in storage for several mo...

Response of sugar beet recombinant inbred lines to post-harvest rot fungi

USDA-ARS?s Scientific Manuscript database

Sugar beet is commonly stored in outdoor piles prior to processing. During this storage period the crop is subject to multiple post-harvest rots. Resistance to three post harvest rots was identified in two sugar beet germplasm in the 1970s, but there has been little work done on host resistance to p...

Response of sugar beet (Beta vulgaris) recombinant inbred lines to post-harvest rot fungi

USDA-ARS?s Scientific Manuscript database

Sugar beet (Beta vulgaris) is commonly stored in outdoor piles prior to processing for food and animal feed. During this storage period the crop is subject to multiple post-harvest rots. Resistance to three post harvest rots was identified in two sugar beet germplasm in the 1970s, but there has been...

Transcriptomics reveals multiple resistance mechanisms against cotton leaf curl disease in a naturally immune cotton species, Gossypium arboreum

USDA-ARS?s Scientific Manuscript database

Cotton is an economically important crop affected by a number of abiotic and biotic stresses. Cotton leaf curl disease (CLCuD) is caused by virus in the genus Begomovirus (family Geminiviridae), collectively called cotton leaf curl viruses (CLCuVs). It is one of the most devastating virual diseases ...

Landscape, community, countryside: linking biophysical and social scales in US Corn Belt agricultural landscapes

Treesearch

Ryan C. Atwell; Lisa A. Schulte; Lynne M. Westphal

2009-01-01

Understanding the interplay between ecological and social factors across multiple scales is integral to landscape change initiatives in productive agricultural regions such as the rural US Corn Belt. We investigated the cultural context surrounding the use of perennial cover types--such as stream buffers, wetlands, cellulosic bioenergy stocks, and diverse cropping...

Variation in grain arsenic assessed in a diverse panel of rice (Oryza sativa)in multiple sites

USDA-ARS?s Scientific Manuscript database

According to the World Health Organization, more than half of the world’s population suffers from some form of nutrient deficiency, largely attributed to the relatively poor nutritional value of crop grains. With about half of the world’s people dependent on rice as their main food source, improving...

Multiple post-domestication origins of kabuli chickpea through allelic variation in a diversification-associated transcription factor

USDA-ARS?s Scientific Manuscript database

Chickpea (Cicer arietieum) is a widely cultivated food legume and one of the Neolitic founder crops domesticated in the Fertile Crescent. Cultivated chickpea is classified into two types, a ‘desi’ type with smaller and darker seed coats, and a light-colored large-seeded ‘kabuli’ type, with the two t...

Ecosystem evapotranspiration: challenges in measurements, estimates, and modeling

Treesearch

Devendra Amatya; S. Irmak; P. Gowda; Ge Sun; J.E. Nettles; K.R. Douglas-Mankin

2016-01-01

Evapotranspiration (ET) processes at the leaf to landscape scales in multiple land uses have important controls and feedbacks for local, regional, and global climate and water resource systems. Innovative methods, tools, and technologies for improved understanding and quantification of ET and crop water use are critical for adapting more effective management strategies...

USDA-ARS and US EPA scientific investigations concerning biochars impact on soil health characteristics, microbial transport, and environmental restoration of mine-impacted soils

EPA Science Inventory

Biochar is being evaluated by scientists from the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) for its potential to sequester soil C, to improve soil health, and to increase crop yields. ARS scientists from multiple locations (Florence SC, K...

Attraction of pollinators to atemoya (Magnoliales: Annonaceae) in Puerto Rico: A synergetic approach using multiple nitidulid lures

USDA-ARS?s Scientific Manuscript database

Atemoya, a cross between Annona squamosa and A. cherimola (Annonaceae), has the potential to be a major fruit crop in tropical and subtropical areas. A major setback to production throughout the world is low fruit-set due to inadequate visits by pollinators, typically beetles in the family Nitidulid...

Genetic diversity and population structure of castor (Ricinus communis L.) germplasm within the U.S. collection assessed with EST-SSR markers

USDA-ARS?s Scientific Manuscript database

Castor is an important oilseed crop and although its oil is inedible, it has multiple industrial and pharmaceutical applications. The entire U.S. castor germplasm collection was previously screened for oil content and fatty acid composition, but its genetic diversity and population structure has not...

First report of downy mildew caused by Plasmopara halstedii on black-eyed susan (Rudbeckia fulgida cv. ‘Goldsturm’) in Maryland

USDA-ARS?s Scientific Manuscript database

The North American perennial black-eyed Susan (Rudbeckia fulgida cv. ‘Goldsturm’) is an important nursery crop, prized by gardeners and landscapers for its persistent bloom and ease of cultivation. In September 2013 disease symptoms characteristic of downy mildew were observed from multiple plants a...

Development of next-generation mapping populations: Multi-parent Advanced Generation Inter-Cross (MAGIC) and Marker-Assisted Recurrent Selection (MARS) populations in peanut

USDA-ARS?s Scientific Manuscript database

Generation Inter-Cross (MAGIC) and Marker-Assisted Recurrent Selection (MARS) have been proposed and used in many crops to dissect complex traits or QTL. MAGIC allows for dissecting genomic structure, and for improving breeding populations by integrating multiple alleles from different parents. MAR...

Utilization of high performance liquid chromatography coupled to tandem mass spectrometry for characterization of 8-O-methylbostrycoidin production by species of the fungus Fusarium

USDA-ARS?s Scientific Manuscript database

The pigment, 8-O-methylbostrycoidin is a polyketide metabolite produced by multiple species of the fungus Fusarium that infects plant crops, including maize. A technique was developed for the analysis of 8-O-methylbostrycoidin by high performance liquid chromatography coupled to electrospray ionizat...

Identification and validation of single nucleotide polymorphic markers linked to Ug99 stem rust resistance in spring wheat

USDA-ARS?s Scientific Manuscript database

Wheat stem rust (Puccinia graminis f. sp. tritici Eriks. and E. Henn.) is one of the most destructive diseases world-wide. Races belonging to Ug99 (or TTKSK) continue to cause crop losses in East Africa and threaten global wheat production. Developing and deploying wheat varieties with multiple race...

Landscape epidemiology and control of pathogens with cryptic and long-distance dispersal: Sudden oak death in northern Californian forests

Treesearch

Joao A. N. Filipe; Richard C. Cobb; Ross K. Meentemeyer; Christopher A. Lee; Yana S. Valachovic; Alex R. Cook; David M. Rizzo; Christopher A. Gilligan

2012-01-01

Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also...

First report of Bemisia tabaci biotype Q in Costa Rica and detection of viruliferous whiteflies in greenhouses

USDA-ARS?s Scientific Manuscript database

Whiteflies are a complex that comprises multiple species and biotypes or races which are capable of affecting crops by phloem feeding, virus transmission and promotion of fungal colonization. The distribution of these pests is worldwide. In Costa Rica, a country located in the tropics, the most prob...

Little white lies: pericarp color provides insights into the origins and evolution of Southeast Asian weedy rice

USDA-ARS?s Scientific Manuscript database

Weedy rice is a conspecific form of cultivated rice (Oryza sativa L.) that infests rice fields and results in severe crop losses. Weed strains in different world regions appear to have originated multiple times from different domesticated and/or wild rice progenitors. In the case of Malaysian weedy ...

Food for Thought: Crop Yields in the Columbia River Basin in an Altered Future

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Nelson, R.; Stockle, C.; Kruger, C.; Brady, M.; Adam, J. C.

2013-12-01

Growth of global population and food consumption in the next several decades is expected to result in a food security challenge. Strategies to address this challenge, such as enhancing agricultural productivity and resiliency, need to be considered within the context of a full range of plausible consequences so as to identify investments that create win-win-win scenarios for the environment, economy, and society. Regional earth systems models can provide the necessary scale-appropriate framework to inform the decision making context for adaptation strategies, especially in the context of global change. In an altered future, changes to climate, technology and socioeconomics affect regional agriculture both directly and indirectly. These effects are not independent and an integrated process-based model may better capture unanticipated non-linear and non-monotonic responses and feedbacks over time . BioEarth is a research initiative designed to explore the coupling of multiple stand-alone earth systems models to generate usable information for agricultural and natural resource decision making at the regional scale at decadal time-steps. This project focuses on the U.S. Pacific Northwest (PNW) region and is a framework that integrates atmospheric, terrestrial, aquatic, and economic models. We apply component models of BioEarth to the Columbia River basin in the PNW to study the direct and indirect impacts of climate change on regional irrigated and dryland crop yields for a variety of annual and perennial crops. Results indicate that the net effect of climate change on crop yields is dependent on the crop type. There is a negative effect of temperature on yields for most crops. Dryland winter wheat is a notable exception. With warming, although the available growing season increases, faster thermal accumulation results in a shorter time to maturity. Precipitation changes in the region have a positive impact on dryland agriculture. Carbon dioxide (CO2) fertilization has a positive impact on crop yields for most crops. This positive impact is minimal for corn which is a C4 crop that is already CO2 efficient. The net response is an increase in yields for dryland agriculture and depends on the crop type for irrigated agriculture. Although, climate change results in increased water shortages and water rights curtailment in the region, this does not translate into an increased negative effect on yields. This could be attributed to higher water use efficiency under elevated CO2 levels as well crops getting through growth stages earlier in the season with wetter spring conditions. The non linear and non monotonic nature of the response of climate change on crop yields is discussed. In accounting for biophysical effects of climate change on crop yields, socio-economic effects cannot be ignored because biophysical effects are nested with the framework of human decision making. We also discuss our results in the context of socioeconomic factors . Current results assume no adaptation strategies and incorporating this is our next step.

Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

USGS Publications Warehouse

Marshall, Michael T.; Thenkabail, Prasad S.

2015-01-01

Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for alfalfa (R2 = 0.81); 722 and 732 nm for cotton (R2 = 0.97); and 529 and 895 nm for maize (R2 = 0.94). The higher spectral resolution of the EO-1 Hyperion hyperspectral sensor and the ability of users to choose distinct HNBs for improved crop biomass estimation outweigh the benefits that come with higher spatial resolution of MSBBs.

Sustainable land management practices as providers of several ecosystem services under rainfed Mediterranean agroecosystems

NASA Astrophysics Data System (ADS)

Almagro, María; de Vente, Joris; Boix-Fayós, Carolina; García-Franco, Noelia; Melgares de Aguilar, Javier; González, David; Solé-Benet, Albert; Martínez-Mena, María

2015-04-01

Little is known about the multiple impacts of sustainable land management practices on soil and water conservation, carbon sequestration, mitigation of global warming, and crop yield productivity in semiarid Mediterranean agroecosystems. We hypothesized that a shift from intensive tillage to more conservative tillage management practices (reduced tillage optionally combined with green manure) leads to an improvement in soil structure and quality and will reduce soil erosion and enhance carbon sequestration in semiarid Mediterranean rainfed agroecosystems. To test the hypothesis, we assessed the effects of different tillage treatments (conventional (CT), reduced (RT), reduced tillage combined with green manure (RTG), and no tillage (NT)) on soil structure and soil water content, runoff and erosion control, soil CO2 emissions, crop yield and carbon sequestration in two semiarid agroecosystems with organic rainfed almond in the Murcia Region southeast Spain). It was found that reduction and suppression of tillage under almonds led to an increase in soil water content in both agroecosystems. Crop yields ranged from 775 to 1766 kg ha-1 between tillage 18 treatments, but we did not find a clear relation between soil water content and crop yield. RT and RTG treatments showed lower soil erosion rates and higher crop yields of almonds than under CT treatment. Overall, higher soil organic carbon contents and aggregate stability were observed under RTG treatment than under RT or CT treatment. It is concluded that conversion from CT to RTG is suitable to increase carbon inputs without enhancing soil CO2 emissions in semiarid Mediterranean agroecosystems.

Effects of acid deposition on terrestrial ecosystems and their rehabilitation strategies in China.

PubMed

Feng, Zong-wei; Miao, Hong; Zhang, Fu-zhu; Huang, Yi-zong

2002-04-01

South China has become the third largest region associated with acid deposition following Europe and North America, the area subject to damage by acid deposition increased from 1.75 million km2 in 1985 to 2.8 million km2 in 1993. Acid deposition has caused serious damage to ecosystem. Combined pollution of acid rain and SO2 showed the obvious multiple effects on crops. Vegetable was more sensitive to acid deposition than foodstuff crops. Annual economic loss of crops due to acid deposition damage in eleven provinces of south China was 4.26 billion RMB Yuan. Acid deposition caused serious damage to forest. Annual economic loss of wood volume was about 1.8 billion RMB Yuan and forest ecological benefit loss 16.2 billion in eleven provinces of south China. Acid deposition in south China was typical "sulfuric acid type". According to the thoughts of sustainable development, some strategies were brought forward as follows: (1) enhancing environmental management, specifying acid-controlling region, controlling and abating the total emission amount of SO2; (2) selecting practical energy technologies of clean coal, for example, cleansing and selecting coal, sulfur-fixed-type industrial briqutting, abating sulfur from waste gas and so on; (3) developing other energy sources to replace coal, including water electricity, atomic energy and the new energy such as solar energy, wind energy and so on; (4) in acid deposition region of south China, selecting acid-resistant type of crop and tree to decrease agricultural losses, planting more green fertilizer crops, using organic fertilizers and liming, in order to improve buffer capacities of soil.

Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

NASA Astrophysics Data System (ADS)

Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

2018-04-01

Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

Corn response to climate stress detected with satellite-based NDVI time series

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

Wang, Ruoyu; Cherkauer, Keith; Bowling, Laura

Corn growth conditions and yield are closely dependent on climate variability. Leaf growth, measured as the leaf area index, can be used to identify changes in crop growth in response to climate stress. This research was conducted to capture patterns of spatial and temporal corn leaf growth under climate stress for the St. Joseph River watershed, in northeastern Indiana. Leaf growth is represented by the Normalized Difference Vegetative Index (NDVI) retrieved from multiple years (2000–2010) of Landsat 5 TM images. By comparing NDVI values for individual image dates with the derived normal curve, the response of crop growth to environmentalmore » factors is quantified as NDVI residuals. Regression analysis revealed a significant relationship between yield and NDVI residual during the pre-silking period, indicating that NDVI residuals reflect crop stress in the early growing period that impacts yield. Both the mean NDVI residuals and the percentage of image pixels where corn was under stress (risky pixel rate) are significantly correlated with water stress. Dry weather is prone to hamper potential crop growth, with stress affecting most of the observed corn pixels in the area. Oversupply of rainfall at the end of the growing season was not found to have a measurable effect on crop growth, while above normal precipitation earlier in the growing season reduces the risk of yield loss at the watershed scale. Furthermore, the spatial extent of stress is much lower when precipitation is above normal than under dry conditions, masking the impact of small areas of yield loss at the watershed scale.« less

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

Corn response to climate stress detected with satellite-based NDVI time series

DOE PAGES

Wang, Ruoyu; Cherkauer, Keith; Bowling, Laura

2016-03-23

Corn growth conditions and yield are closely dependent on climate variability. Leaf growth, measured as the leaf area index, can be used to identify changes in crop growth in response to climate stress. This research was conducted to capture patterns of spatial and temporal corn leaf growth under climate stress for the St. Joseph River watershed, in northeastern Indiana. Leaf growth is represented by the Normalized Difference Vegetative Index (NDVI) retrieved from multiple years (2000–2010) of Landsat 5 TM images. By comparing NDVI values for individual image dates with the derived normal curve, the response of crop growth to environmentalmore » factors is quantified as NDVI residuals. Regression analysis revealed a significant relationship between yield and NDVI residual during the pre-silking period, indicating that NDVI residuals reflect crop stress in the early growing period that impacts yield. Both the mean NDVI residuals and the percentage of image pixels where corn was under stress (risky pixel rate) are significantly correlated with water stress. Dry weather is prone to hamper potential crop growth, with stress affecting most of the observed corn pixels in the area. Oversupply of rainfall at the end of the growing season was not found to have a measurable effect on crop growth, while above normal precipitation earlier in the growing season reduces the risk of yield loss at the watershed scale. Furthermore, the spatial extent of stress is much lower when precipitation is above normal than under dry conditions, masking the impact of small areas of yield loss at the watershed scale.« less

Optimized production planning model for a multi-plant cultivation system under uncertainty

NASA Astrophysics Data System (ADS)

Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

2015-02-01

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

Assessment of relevant factors and relationships concerning human dermal exposure to pesticides in greenhouse applications.

PubMed

Martínez Vidal, Jose L; Egea González, Francisco J; Garrido Frenich, Antonia; Martínez Galera, María; Aguilera, Pedro A; López Carrique, Enrique

2002-08-01

Principal component analysis (PCA) was applied to the gas chromatographic data obtained from 23 different greenhouse trials. This was used to establish which factors, including application technique (very small, small, medium and large drop-size), crop characteristics (short/tall, thin/dense) and pattern application of the operator (walking towards or away from the treated area) are relevant to the dermal exposure levels of greenhouse applicators. The results showed that the highest exposure by pesticides during field applications in greenhouses, in the climatic conditions and in the crop conditions typical of a southern European country, occurs on the lower legs and front thighs of the applicators. Similar results were obtained by hierarchical cluster analysis (HCA). Drop-size seems to be very important in determining total exposure, while height and density of crops have little influence on total exposure under the conditions of the present study. No pesticide type is a major factor in total exposure. The application of multiple regression analysis (MRA) allowed assessment of the relationships between the pesticide exposure of the less affected parts of the body with the most affected parts.

Potential health risk assessment of potato (Solanum tuberosum L.) grown on metal contaminated soils in the central zone of Punjab, Pakistan.

PubMed

Khan, Zafar Iqbal; Ahmad, Kafeel; Yasmeen, Sumaira; Akram, Nudrat Aisha; Ashraf, Muhammad; Mehmood, Naunain

2017-01-01

Metal buildup was estimated in potato (Solanum tuberosum L.), grown in central Punjab, Pakistan. This crop was irrigated with multiple water sources like ground, sewage and canal water. Concentrations of different metals like zinc (Zn), arsenic (As), lead (Pb), iron (Fe), nickel (Ni), molybdenum (Mo), copper (Cu), and selenium (Se) were assessed in the potato crop irrigated with different types of waters. Sewage water treated crop and soil had higher metal concentrations than those treated with other two treatments. All metals had positive and significant correlation except for Mo which was non-significantly correlated between the vegetable and soil. Highest daily intake was observed for Fe (0.267), whereas the lowest was seen for Se (0.003). The enrichment factor and health index varied between 0.135-15.08 and 0.285-83.77, respectively. This study concludes that vegetables cultivated on soil treated with sewage water is a potent threat for human health as the metals manifest toxicity after entering the food chain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Handling Complexity in Animal and Plant Science Research-From Single to Functional Traits: Are We There Yet?

PubMed

Roberts, Jessica; Power, Aoife; Chandra, Shaneel; Chapman, James; Cozzolino, Daniel

2018-05-28

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

Soil management shapes ecosystem service provision and trade-offs in agricultural landscapes.

PubMed

Tamburini, Giovanni; De Simone, Serena; Sigura, Maurizia; Boscutti, Francesco; Marini, Lorenzo

2016-08-31

Agroecosystems are principally managed to maximize food provisioning even if they receive a large array of supporting and regulating ecosystem services (ESs). Hence, comprehensive studies investigating the effects of local management and landscape composition on the provision of and trade-offs between multiple ESs are urgently needed. We explored the effects of conservation tillage, nitrogen fertilization and landscape composition on six ESs (crop production, disease control, soil fertility, water quality regulation, weed and pest control) in winter cereals. Conservation tillage enhanced soil fertility and pest control, decreased water quality regulation and weed control, without affecting crop production and disease control. Fertilization only influenced crop production by increasing grain yield. Landscape intensification reduced the provision of disease and pest control. We also found tillage and landscape composition to interactively affect water quality regulation and weed control. Under N fertilization, conventional tillage resulted in more trade-offs between ESs than conservation tillage. Our results demonstrate that soil management and landscape composition affect the provision of several ESs and that soil management potentially shapes the trade-offs between them. © 2016 The Author(s).

Long term plant biomonitoring in the vicinity of waste incinerators in The Netherlands.

PubMed

van Dijk, Chris; van Doorn, Wim; van Alfen, Bert

2015-03-01

Since the mid-nineties new waste incineration plants have come into operation in the Netherlands. Burning of waste can result in the emission of potentially toxic compounds. Although the incineration plants must comply with strict conditions concerning emission control, public concern on the possible impact on human health and the environment still exists. Multiple year (2004-2013) biomonitoring programs were set up around three waste incinerators for early detection of possible effects of stack emissions on the quality of crops and agricultural products. The results showed that the emissions did not affect the quality of crops and cow milk. Concentrations of heavy metals, PAHs and dioxins/PCBs were generally similar to background levels and did not exceed standards for maximum allowable concentrations in foodstuffs (e.g. vegetables and cow milk). Some exceedances of the fluoride standard for cattle feed were found almost every year in the maximum deposition areas of two incinerators. Biomonitoring with leafy vegetables can be used to monitor the real impact of these emissions on agricultural crops and to communicate with all stakeholders. Copyright © 2014 Elsevier Ltd. All rights reserved.

New Help for MS Patients

NASA Technical Reports Server (NTRS)

1993-01-01

The Mark VII MicroClimate Medical Personal Cooling system enables multiple sclerosis' victims, as well as cerebral palsy, spinabifida patients and others to lower their body temperatures. Although this is not a cure, cooling can produce a dramatic improvement in symptoms. The Multiple Sclerosis Association of America has placed cool suits in MS research care centers. This technology originated in the need for cooling systems in spa@esuits. "Cool Suits" are now used by hazardous materials workers, armored vehicle crews, firefighters and crop dusters. A surgical personal cooling system has also been developed for medical personnel working in hot operating room environments.

Managing Bioenergy Production on Arable Field Margins for Multiple Ecosystem Services: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Ferrarini, Andrea; Serra, Paolo; Amaducci, Stefano; Trevisan, Marco; Puglisi, Edoardo

2013-04-01

Growing crops for bioenergy is increasingly viewed as conflicting with food production. However, energy use continues to rise and food production requires fuel inputs, which have increased with intensification. The debate should shift from "food or fuel" to the more challenging target: how the increasing demand for food and energy can be met in the future, particularly when water and land availability will be limited. As for food crops, also for bioenergy crops it is questioned whether it is preferable to manage cultivation to enhance ecosystem services ("land sharing" strategy) or to grow crops with lower ecosystem services but higher yield, thereby requiring less land to meet bioenergy demand ("land sparing" strategy). Energy crop production systems differ greatly in the supply of ecosystem services. The use of perennial biomass (e.g. Switchgrass, Mischantus, Giant reed) for energy production is considered a promising way to reduce net carbon emissions and mitigate climate change. In addition, regulating and supporting ecosystem services could be provided when specific management of bioenergy crops is implemented. The idea of HEDGE-BIOMASS* project is to convert the arable field margins to bioenergy crop production fostering a win-win strategy at landscape level. Main objective of the project is to improve land management to generate environmental benefits and increase farmer income. The various options available in literature for an improved field boundary management are presented. The positive/unknown/negative effects of growing perennial bioenergy crops on field margins will be discussed relatively to the following soil-related ecosystem services: (I) biodiversity conservation and enhancement, (II) soil nutrient cycling, (III) climate regulation (reduction of GHG emissions and soil carbon sequestration/stabilization, (IV) water regulation (filtering and buffering), (V) erosion regulation, (VI) pollination and pest regulation. From the analysis of available data, it emerges that production of biomass for bioenergy on field margins improves ecosystem services, depending upon the soil/agroecosystem health status of arable land displaced by the bioenergy crop. Considering that climate change is a dominant driver for agroecosystem health and perennial bionergy crops tend to stabilize soil C in arable land, it will be necessary to focus our attention to the improvement of climate regulation ecosystem service value in ecologically-degraded arable field margins. This management option seems to be the most sustainable strategy to enhance a win-win strategy: namely, sequestering carbon, producing biomasses for energetic purposes, improving the whole set of ecosystem services affected by soil organic matter, leaving, at the same time, more arable land for food and fiber crops. * The HEDGE-BIOMASS project is funded by Italian Minister of Agriculture for the period 2013-2016 and is being followed by BIOMASS Research Center at Università Cattolica del Sacro Cuore (Piacenza, Italy).

Factors Affecting Conservation Practice Behavior of CRP Participants in Alabama

Treesearch

Okwudili Onianwa; Gerald Wheelock; Shannon Hendrix

1999-01-01

This study examines the factors that affect conservation practice choices of CRP farmers in Alabama. From over 9,000 contracts enrolled in the state between 1986 and 1995, 594 were randomly selected for the study. A multiple-regression analysis was employed to analyze the data. Results indicate that education, ratio ofcropland in CRP, farm size, gender, prior crop...

Stand Dynamics and Plant Associates of Loblolly Pine Plantations to Midrotation after Early Intensive Vegetation Management-A Southeastern United States Regional Study

Treesearch

James H. Miller; Bruce R. Zutter; Ray A. Newbold; M. Boyd Edwards; Shepard M. Zedaker

2003-01-01

Increasingly, pine plantations worldwide are grown using early control of woodv and/or herbaceous vegetation. Assuredsustainablepractices require long-term data on pine plantation development detailing patterns and processes to understand both crop-competition dynamics and the role of stand participants in providing multiple attributes such as biodiversity conservation...

Environmentally relevant mixing ratios in cumulative assessments: a study on the correlation of blood and brain concentrations of a mixture of pyrethroid insecticides to neurotoxicity in the rat

EPA Science Inventory

Human exposure to multiple pyrethroid insecticides may occur because of their broad use on crops and for residential pest control. To address the potential health risk from co-exposure to pyrethroids, it is important to understand their disposition and toxicity in target organs ...

Duplicate and conquer: multiple homologs of phosphorus-starvation tolerance 1 enhance phosphorus acquisition and sorghum performance on low-P soils

USDA-ARS?s Scientific Manuscript database

Low soil phosphorus (P) availability is a major constraint for crop production in tropical regions. The rice protein kinase, OsPSTOL1, was previously shown to enhance P acquisition and grain yield in rice under P deficiency. We investigated the role of homologs of OsPSTOL1 in sorghum performance und...

A radarsat-2 quad-polarized time series for monitoring crop and soil conditions in Barrax, Spain

USDA-ARS?s Scientific Manuscript database

The European Space Agency (ESA) along with multiple university and agency investigators joined to conduct the AgriSAR Campaign in 2009. The main objective was to analyze a dense time series of RADARSAT-2 quad-pol data to define and quantify the performance of Sentinel-1 and other future ESA C-Band ...

Potato virus Y transmission efficiency from different potato cultivars infected with single or multiple virus strains

USDA-ARS?s Scientific Manuscript database

There has been a shift in the prevalence of Potato virus Y (PVY) strains affecting the U.S. potato crop in recent years. The incidence of the ordinary strain, PVYO, is now significantly less than the emerging recombinant strains, e.g. PVYNTN, PVYN:O/NWi. It is not uncommon to find several PVY strai...

Virulence of Meloidogyne spp. and Induced Resistance in Grape Rootstocks.

PubMed

McKenry, Michael V; Anwar, Safdar A

2007-03-01

Harmony grape rootstock displays resistance to several Meloidogyne spp. but that resistance is not durable in commercial vineyard settings. A 2-year experiment in a microplot setting revealed host specificities of two virulent populations of Meloidogyne arenaria and an avirulent population of Meloidogyne incognita. In a subsequent split-root experiment, the avirulent nematode population was demonstrated to induce resistance to the virulent nematode population. To quantify the level of resistance, reproduction of the virulent nematode population was determined 63 days after being challenged by an avirulent nematode population using a range of inoculum densities and timeframes. Induction of resistance became apparent when the virulent nematode population was inoculated 7 days after the avirulent nematode population and increased thereafter. The level of induced resistance increased with increased inoculum levels of the avirulent nematode population. Root systems of perennial crops are commonly fed upon simultaneously by multiple nematode species. These two studies indicate that field populations can become preferentially virulent upon one or multiple rootstocks and that co-inhabiting populations may induce existing resistance mechanisms. In perennial crops, it is common for numerous nematode species besides Meloidogyne spp. to be present, including some that feed without causing apparent damage.

Competitive interaction of Axonopus compressus and Asystasia gangetica under contrasting sunlight intensity.

PubMed

Samedani, B; Juraimi, A S; Anwar, M P; Rafii, M Y; Sheikh Awadz, S H; Anuar, A R

2013-01-01

Axonopus compressus is one of the native soft grass species in oil palm in Malaysia which can be used as a cover crop. The competitive ability of A. compressus to overcome A. gangetica was studied using multiple-density, multiple-proportion replacements series under a glasshouse and full sunlight conditions in a poly bag for 10 weeks. A. compressus produced more dry weight and leaf area when competing against A. gangetica than in monoculture at both densities in the full sunlight and at high density in the shade. Moreover, the relative yield and relative crowding coefficients also indicated A. compressus is a stronger competitor than A. gangetica at both densities in the full sunlight and high density in the shade. It seemed that A. gangetica plants in the shade did not compete with each other and were more competitive against A. compressus as could influence A. compressus height in the shade. It is concluded that although suppression of A. gangetica by A. compressus occurred under full sunlight, irrespective of plant density, this ability reduced under shade as A. compressus density decreased. The result suggests that A. compressus in high density could be considered as a candidate for cover crops under oil palm canopy.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

Evolution of finger millet: evidence from random amplified polymorphic DNA.

PubMed

Hilu, K W

1995-04-01

Finger millet (Eleusine coracana ssp. coracana) is an annual tetraploid member of a predominantly African genus. The crop is believed to have been domesticated from the tetraploid E. coracana ssp. africana. Cytogenetic and isozyme data point to the allopolyploid nature of the species and molecular information has shown E. indica to be one of the genomic donors. A recent isozyme study questioned the proposed phylogenetic relationship between finger millet and its direct ancestor subspecies africana. An approach using random amplified polymorphic DNA (RAPD) was employed in this study to examine genetic diversity and to evaluate hypotheses concerning the evolution of domesticated and wild annual species of Eleusine. Unlike previous molecular approaches, the RAPD study revealed genetic diversity in the crop. The pattern of genetic variation was loosely correlated to geographic distribution. The allotetraploid nature of the crop was confirmed and molecular markers that can possibly identify the other genomic donor were proposed. Genotypes of subspecies africana did not group closely with those of the crop but showed higher affinities to E. indica, reflecting the pattern of similarity revealed by the isozyme study. The multiple origin of subspecies africana could explain the discrepancy between the isozyme-RAPD evidence and previous information. The RAPD study showed the close genetic affinity of E. tristachya to the E. coracana--E. indica group and understood the distinctness of E. multiflora.

Nitrogen Recycling and Flowering Time in Perennial Bioenergy Crops

PubMed Central

Schwartz, Christopher; Amasino, Richard

2013-01-01

Perennials have a number of traits important for profitability and sustainability of a biofuel crop. Perennialism is generally defined as the ability to grow and reproduce in multiple years. In temperate climates, many perennial plants enter dormancy during winter and recycle nutrients, such as nitrogen, to below ground structures for the next growing season. Nitrogen is expensive to produce and application of nitrogen increases the potent greenhouse gas NOx. Perennial bioenergy crops have been evaluated for biomass yields with nitrogen fertilization, location, year, and genotype as variables. Flowering time and dormancy are closely related to the N recycling program. Substantial variation for flowering time and dormancy has been identified in the switchgrass (Panicum virgatum L.) species, which provides a source to identify the genetic components of N recycling, and for use in breeding programs. Some studies have addressed recycling specifically, but flowering time and developmental differences were largely ignored, complicating interpretation of the results. Future studies on recycling need to appreciate plant developmental stage to allow comparison between experiments. A perennial/annual model(s) and more environmentally controlled experiments would be useful to determine the genetic components of nitrogen recycling. Increasing biomass yield per unit of nitrogen by maximizing recycling might mean the difference for profitability of a biofuel crop and has the added benefit of minimizing negative environmental effects from agriculture. PMID:23626592

Using Bayesian methods to predict climate impacts on groundwater availability and agricultural production in Punjab, India

NASA Astrophysics Data System (ADS)

Russo, T. A.; Devineni, N.; Lall, U.

2015-12-01

Lasting success of the Green Revolution in Punjab, India relies on continued availability of local water resources. Supplying primarily rice and wheat for the rest of India, Punjab supports crop irrigation with a canal system and groundwater, which is vastly over-exploited. The detailed data required to physically model future impacts on water supplies agricultural production is not readily available for this region, therefore we use Bayesian methods to estimate hydrologic properties and irrigation requirements for an under-constrained mass balance model. Using measured values of historical precipitation, total canal water delivery, crop yield, and water table elevation, we present a method using a Markov chain Monte Carlo (MCMC) algorithm to solve for a distribution of values for each unknown parameter in a conceptual mass balance model. Due to heterogeneity across the state, and the resolution of input data, we estimate model parameters at the district-scale using spatial pooling. The resulting model is used to predict the impact of precipitation change scenarios on groundwater availability under multiple cropping options. Predicted groundwater declines vary across the state, suggesting that crop selection and water management strategies should be determined at a local scale. This computational method can be applied in data-scarce regions across the world, where water resource management is required to resolve competition between food security and available resources in a changing climate.

Effects of urban sprawl on arthropod communities in peri-urban farmed landscape in Shenbei New District, Shenyang, Liaoning Province, China.

PubMed

Bian, Zhen-Xing; Wang, Shuai; Wang, Qiu-Bing; Yu, Miao; Qian, Feng-Kui

2018-01-08

Peri-urban farmland provides a diversity of ecological services. However, it is experiencing increasing pressures from urban sprawl. While the effects of land use associated with farming on arthropod assemblages has received increasing attention, most of this research has been conducted by comparing conventional and organic cropping systems. The present study identifies the effects of urban sprawl and the role of non-cropped habitat in defining arthropod diversity in peri-urban farmed landscapes. Multi-scale arthropod data from 30 sampling plots were used with linear-mixed models to elucidate the effects of distance from urban areas (0-13 km; 13-25 km and >25 km, zones I, II, and III, respectively) on arthropods. Results showed that urban sprawl, disturbed farm landscapes, and disturbance in non-cropped habitats had negative effects on arthropods, the latter requiring arthropods to re-establish annually from surrounding landscapes via dispersal. While arthropod species richness showed no obvious changes, arthropod abundance was lowest in zone II. Generally, patch density (PD), Shannon diversity index (SHDI), and aggregate index (AI) of non-cropped habitat were major drivers of changes in arthropod populations. This study contributes to identifying the effects of urban sprawl on arthropod diversity and documenting the multiple functions of farm landscapes in peri-urban regions.

Policy Design of Multi-Year Crop Insurance Contracts with Partial Payments

PubMed Central

Chen, Ying-Erh; Goodwin, Barry K.

2015-01-01

Current crop insurance is designed to mitigate monetary fluctuations resulting from yield losses for a specific year. However, yield realization tendency can vary from year to year and may depend on the correlation of yield realizations across years. When the current single-year Yield Protection (YP) and Area Risk Protection Insurance (ARPI) contracts are extended to multiple periods, actuarially fair premium rate is expected to decrease as poor yield realizations in a year can be offset by another year’s better yield realizations. In this study, we first use simulations to demonstrate how significant premium savings are possible when coverage is based on the sum of yields across years rather than on a year-by-year basis. We then describe the design of a multi-year framework of crop insurance and model the insurance using a copula approach. Insurance terms are extended to more than a year and the premium, liability, and indemnity are determined by a multi-year term. Moreover, partial payment is provided at the end of each term to offset the possibility of significant loss in a single term. County-level data obtained from the U.S. Department of Agriculture are used to demonstrate the implementations of the proposed multi-year crop insurance. The proposed multi-year plan would benefit farmers by offering insurance guarantees across years for significantly lower costs. PMID:26695074

High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction

NASA Astrophysics Data System (ADS)

Hong, Hyundae; Benac, Jasenka; Riggsbee, Daniel; Koutsky, Keith

2014-03-01

High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

PubMed

Harrigan, George G; Harrison, Jay M

2012-01-01

New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

Regeneration of multiple shoots from transgenic potato events facilitates the recovery of phenotypically normal lines: assessing a cry9Aa2 gene conferring insect resistance

PubMed Central

2011-01-01

Background The recovery of high performing transgenic lines in clonal crops is limited by the occurrence of somaclonal variation during the tissue culture phase of transformation. This is usually circumvented by developing large populations of transgenic lines, each derived from the first shoot to regenerate from each transformation event. This study investigates a new strategy of assessing multiple shoots independently regenerated from different transformed cell colonies of potato (Solanum tuberosum L.). Results A modified cry9Aa2 gene, under the transcriptional control of the CaMV 35S promoter, was transformed into four potato cultivars using Agrobacterium-mediated gene transfer using a nptII gene conferring kanamycin resistance as a selectable marker gene. Following gene transfer, 291 transgenic lines were grown in greenhouse experiments to assess somaclonal variation and resistance to potato tuber moth (PTM), Phthorimaea operculella (Zeller). Independently regenerated lines were recovered from many transformed cell colonies and Southern analysis confirmed whether they were derived from the same transformed cell. Multiple lines regenerated from the same transformed cell exhibited a similar response to PTM, but frequently exhibited a markedly different spectrum of somaclonal variation. Conclusions A new strategy for the genetic improvement of clonal crops involves the regeneration and evaluation of multiple shoots from each transformation event to facilitate the recovery of phenotypically normal transgenic lines. Most importantly, regenerated lines exhibiting the phenotypic appearance most similar to the parental cultivar are not necessarily derived from the first shoot regenerated from a transformed cell colony, but can frequently be a later regeneration event. PMID:21995716

Heterogeneity in the distribution of genetically modified and conventional oilseed rape within fields and seed lots.

PubMed

Begg, Graham S; Elliott, Martin J; Cullen, Danny W; Iannetta, Pietro P M; Squire, Geoff R

2008-10-01

The implementation of co-existence in the commercialisation of GM crops requires GM and non-GM products to be segregated in production and supply. However, maintaining segregation in oilseed rape will be made difficult by the highly persistent nature of this species. An understanding of its population dynamics is needed to predict persistence and develop potential strategies for control, while to ensure segregation is being achieved, the production of GM oilseed rape must be accompanied by the monitoring of GM levels in crop or seed populations. Heterogeneity in the spatial distribution of oilseed rape has the potential to affect both control and monitoring and, although a universal phenomenon in arable weeds and harvested seed lots, spatial heterogeneity in oilseed rape populations remains to be demonstrated and quantified. Here we investigate the distribution of crop and volunteer populations in a commercial field before and during the cultivation of the first conventional oilseed rape (winter) crop since the cultivation of a GM glufosinate-tolerant oilseed rape crop (spring) three years previously. GM presence was detected by ELISA for the PAT protein in each of three morphologically distinguishable phenotypes: autumn germinating crop-type plants (3% GM), autumn-germinating 'regrowths' (72% GM) and spring germinating 'small-type' plants (17% GM). Statistical models (Poisson log-normal and binomial logit-normal) were used to describe the spatial distribution of these populations at multiple spatial scales in the field and of GM presence in the harvested seed lot. Heterogeneity was a consistent feature in the distribution of GM and conventional oilseed rape. Large trends across the field (50 x 400 m) and seed lot (4 x 1.5 x 1.5 m) were observed in addition to small-scale heterogeneity, less than 20 m in the field and 20 cm in the seed lot. The heterogeneity was greater for the 'regrowth' and 'small' phenotypes, which were likely to be volunteers and included most of the GM plants detected, than for the largely non-GM 'crop' phenotype. The implications of the volunteer heterogeneity for field management and GM-sampling are discussed.

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments

PubMed Central

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments. PMID:28377779

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

PubMed

Truong, Sandra K; McCormick, Ryan F; Mullet, John E

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments.

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE PAGES

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

2017-03-21

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

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

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

Temporal variability of green and blue water footprint worldwide

NASA Astrophysics Data System (ADS)

Tamea, Stefania; Lomurno, Marianna; Tuninetti, Marta; Laio, Francesco; Ridolfi, Luca

2016-04-01

Water footprint assessment is becoming widely used in the scientific literature and it is proving useful in a number of multidisciplinary contexts. Given this increasing popularity, measures of green and blue water footprint (or virtual water content, VWC) require evaluations of uncertainty and variability to quantify the reliability of proposed analyses. As of today, no studies are known to assess the temporal variability of crop VWC at the global scale; the present contribution aims at filling this gap. We use a global high-resolution distributed model to compute the VWC of staple crops (wheat and maize), basing on the soil water balance, forced by hydroclimatic imputs, and on the total crop evapotranspiration in multiple growing seasons. Crop actual yield is estimated using country-based yield data, adjusted to account for spatial variability, allowing for the analysis of the different role played by climatic and management factors in the definition of crop yield. The model is then run using hydroclimatic data, i.e., precipitation and potential evapotranspiration, for the period 1961-2013 as taken from the CRU database (CRU TS v. 3.23) and using the corresponding country-based yield data from FAOSTAT. Results provide the time series of total evapotranspiration, actual yield and VWC, with separation between green and blue VWC, and the overall volume of water used for crop production, both at the cell scale (5x5 arc-min) and aggregated at the country scale. Preliminary results indicate that total (green+blue) VWC is, in general, weekly dependent on hydroclimatic forcings if water for irrigation is unlimited, because irrigated agriculture allows to compensate temporary water shortage. Conversely, most part of the VWC variability is found to be determined by the temporal evolution of crop yield. At the country scale, the total water used by countries for agricultural production has seen a limited change in time, but the marked increase in the water-use efficiency expressed by VWC has determined an increase of production. Such increase has helped to meet the increasing global food demand in the past 50 years.

Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

NASA Astrophysics Data System (ADS)

Hack-ten Broeke, Mirjam J. D.; Kroes, Joop G.; Bartholomeus, Ruud P.; van Dam, Jos C.; de Wit, Allard J. W.; Supit, Iwan; Walvoort, Dennis J. J.; van Bakel, P. Jan T.; Ruijtenberg, Rob

2016-08-01

For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

Spatial interactions among ecosystem services in an urbanizing agricultural watershed

PubMed Central

Qiu, Jiangxiao; Turner, Monica G.

2013-01-01

Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are “win–win” exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services. PMID:23818612

The heat-shock protein/chaperone network and multiple stress resistance.

PubMed

Jacob, Pierre; Hirt, Heribert; Bendahmane, Abdelhafid

2017-04-01

Crop yield has been greatly enhanced during the last century. However, most elite cultivars are adapted to temperate climates and are not well suited to more stressful conditions. In the context of climate change, stress resistance is a major concern. To overcome these difficulties, scientists may help breeders by providing genetic markers associated with stress resistance. However, multistress resistance cannot be obtained from the simple addition of single stress resistance traits. In the field, stresses are unpredictable and several may occur at once. Consequently, the use of single stress resistance traits is often inadequate. Although it has been historically linked with the heat stress response, the heat-shock protein (HSP)/chaperone network is a major component of multiple stress responses. Among the HSP/chaperone 'client proteins', many are primary metabolism enzymes and signal transduction components with essential roles for the proper functioning of a cell. HSPs/chaperones are controlled by the action of diverse heat-shock factors, which are recruited under stress conditions. In this review, we give an overview of the regulation of the HSP/chaperone network with a focus on Arabidopsis thaliana. We illustrate the role of HSPs/chaperones in regulating diverse signalling pathways and discuss several basic principles that should be considered for engineering multiple stress resistance in crops through the HSP/chaperone network. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Spatial interactions among ecosystem services in an urbanizing agricultural watershed.

PubMed

Qiu, Jiangxiao; Turner, Monica G

2013-07-16

Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are "win-win" exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services.

Detection of stress factors in crop and weed species using hyperspectral remote sensing reflectance

NASA Astrophysics Data System (ADS)

Henry, William Brien

The primary objective of this work was to determine if stress factors such as moisture stress or herbicide injury stress limit the ability to distinguish between weeds and crops using remotely sensed data. Additional objectives included using hyperspectral reflectance data to measure moisture content within a species, and to measure crop injury in response to drift rates of non-selective herbicides. Moisture stress did not reduce the ability to discriminate between species. Regardless of analysis technique, the trend was that as moisture stress increased, so too did the ability to distinguish between species. Signature amplitudes (SA) of the top 5 bands, discrete wavelet transforms (DWT), and multiple indices were promising analysis techniques. Discriminant models created from one year's data set and validated on additional data sets provided, on average, approximately 80% accurate classification among weeds and crop. This suggests that these models are relatively robust and could potentially be used across environmental conditions in field scenarios. Distinguishing between leaves grown at high-moisture stress and no-stress was met with limited success, primarily because there was substantial variation among samples within the treatments. Leaf water potential (LWP) was measured, and these were classified into three categories using indices. Classification accuracies were as high as 68%. The 10 bands most highly correlated to LWP were selected; however, there were no obvious trends or patterns in these top 10 bands with respect to time, species or moisture level, suggesting that LWP is an elusive parameter to quantify spectrally. In order to address herbicide injury stress and its impact on species discrimination, discriminant models were created from combinations of multiple indices. The model created from the second experimental run's data set and validated on the first experimental run's data provided an average of 97% correct classification of soybean and an overall average classification accuracy of 65% for all species. This suggests that these models are relatively robust and could potentially be used across a wide range of herbicide applications in field scenarios. From the pooled data set, a single discriminant model was created with multiple indices that discriminated soybean from weeds 88%, on average, regardless of herbicide, rate or species. Several analysis techniques including multiple indices, signature amplitude with spectral bands as features, and wavelet analysis were employed to distinguish between herbicide-treated and nontreated plants. Classification accuracy using signature amplitude (SA) analysis of paraquat injury on soybean was better than 75% for both 1/2 and 1/8X rates at 1, 4, and 7 DAA. Classification accuracy of paraquat injury on corn was better than 72% for the 1/2X rate at 1, 4, and 7 DAA. These data suggest that hyperspectral reflectance may be used to distinguish between healthy plants and injured plants to which herbicides have been applied; however, the classification accuracies remained at 75% or higher only when the higher rates of herbicide were applied. (Abstract shortened by UMI.)

Modelling impacts of second generation bioenergy production on Ecosystem Services in Europe

NASA Astrophysics Data System (ADS)

Henner, D. N.; Smith, P.; Davies, C.; McNamara, N. P.

2016-12-01

Bioenergy crops are an important source of renewable energy and likely to play a major role in transitioning to a lower CO2 energy system. There is, however, uncertainty about the impacts of the growth of bioenergy crops on broader sustainability encompassed by ecosystem services, further enhanced by ongoing climate change. The goal of this project is to develop a comprehensive model that covers ecosystem services at a continental scale including biodiversity and pollination, water and air security, erosion control and soil security, GHG emissions, soil C and cultural services like tourism value. The technical distribution potential and likely yield of second generation energy crops, such as Miscanthus, Short Rotation Coppice (SRC; willow and poplar) was modelled using ECOSSE, DayCent, SalixFor and MiscanFor models. In addition, methods like water footprint tools, tourism value maps and ecosystem valuation tools and models are utilised. We will present results for synergies and trade-offs between land use change and ecosystem services, impact on food security and land management. Further, we will show modelled yield maps for different cultivars of Miscanthus, willow and poplar in Europe and constraint/opportunity maps based on projected yield and other factors e.g. total economic value, technical potential, current land use, climate change and trade-offs and synergies. It will be essential to include multiple ecosystem services when assessing the potential for bioenergy production/expansion that does not impact other land uses or provisioning services. Considering that the soil GHG balance is dominated by change in soil organic carbon (SOC) and the difference among Miscanthus and SRC is largely determined by yield, an important target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation. This research could inform future policy decisions on bioenergy crops in Europe.

Assessment of Land Degradation and Greening in Ken River Basin of Central India

NASA Astrophysics Data System (ADS)

Pandey, Ashish; Palmate, Santosh S.

2017-04-01

Natural systems have significant impact of land degradation on biodiversity loss, food and water insecurity. To achieve the sustainable development goals, advances in remote sensing and geographical information systems (GIS) are progressively utilized to combat climate change, land degradation and poverty issues of developing country. The Ken River Basin (KRB) has dominating land cover pattern of agriculture and forest area. Nowadays, this pattern is affected due to climate change and anthropogenic activity like deforestation. In this study, land degradation and greening status of KRB of Central India during the years 2001 to 2013 have been assessed using MODIS land cover (MCD12Q1) data sets. International Geosphere Biosphere Programme (IGBP) land cover data has been extracted from the MCD12Q1 data product. Multiple rasters of MODIS landcover were analyzed and compared for assigning unique combination of land cover dynamics employing ArcGIS software. Result reveals that 14.38% natural vegetation was degraded, and crop land and woody savannas were greened by 9.68% to 6.94% respectively. Natural vegetation degradation have been observed in the upper KRB area, and resulted to increase in crop land (3418.87 km2) and woody savannas (1242.23 km2) area. Due to transition of 1043.6 km2 area of deciduous broadleaf forest to woody savannas greening was also observed. Moreover, both crop land and woody savannas showed inter-transitions of 669.31 km2 into crop land to woody savannas, and 874.09 km2 into woody savannas to crop land. The present analysis reveals that natural vegetation has more land conversions into woody savannas and crop land in the KRB area. Further, Spatial change analysis shows that land degradation and greening has occurred mostly in the upper part of the KRB. The study reveals that the land transition information can be useful for proper planning and management of natural resources.

Observed Variation in Carbon and Water Exchange Across Crop Types, Seasons, and Years in Un-irrigated Land of the Southern Great Plains

NASA Astrophysics Data System (ADS)

Fischer, M. L.; Billesbach, D. P.; Riley, W. J.; Berry, J. A.; Torn, M. S.

2004-12-01

Accurate prediction of the regional responses of carbon and water fluxes to changing climate, land use, and management requires models that are parameterized and tested against measurements made in multiple land cover types and over seasonal and inter-annual time scales. In particular, modelers predicting fluxes for un-irrigated agriculture are posed with the additional challenge of characterizing the onset and severity of water stress. We report results from three years of an ongoing series of measurement campaigns that quantify the spatial heterogeneity of land surface-atmosphere exchanges of carbon dioxide, water, and energy. Eddy covariance flux measurements were made in pastures and dominant crop types surrounding the US-DOE Atmospheric Radiation Measurement Program central facility near Lamont, Oklahoma (36.605 N, 97.485 W). Ancillary measurements included radiation budget, meteorology, soil moisture and temperature, leaf area index, plant biomass, and plant and soil carbon and nitrogen content. Within a given year, the dominant spatial variation in fluxes of carbon, water, and energy are caused by variations of land cover due to the distinct phenology of winter-spring (winter wheat) versus summer crops (e.g., pasture, sorghum, soybeans). Within crop and yearly variations were smaller. In 2002, variations in net ecosystem carbon exchange (NEE), for three closely spaced winter wheat fields was 10-20%. Variations between years for the same crop types were also large. Net primary production (NPP) of winter wheat in the spring of 2003 versus 2002 increased by a factor of two, while NEE increased by 35%. The large increase in production and NEE are positively correlated with precipitation, integrated over the previous summer-fall periods. We discuss the implications of these results by extracting and comparing factors relevant for parameterization of land surface models and by comparing crop yield with historic variations in yield at the landscape scale.

Honey bee diet in intensive farmland habitats reveals an unexpectedly high flower richness and a major role of weeds.

PubMed

Requier, Fabrice; Odoux, Jean-François; Tamic, Thierry; Moreau, Nathalie; Henry, Mickaël; Decourtye, Axel; Bretagnolle, Vincent

2015-06-01

In intensive farmland habitats, pollination of wild flowers and crops may be threatened by the widespread decline of pollinators. The honey bee decline, in particular, appears to result from the combination of multiple stresses, including diseases, pathogens, and pesticides. The reduction of semi-natural habitats is also suspected to entail floral resource scarcity for bees. Yet, the seasonal dynamics and composition of the honey bee diet remains poorly documented to date. In this study, we studied the seasonal contribution of mass-flowering crops (rapeseed and sunflower) vs. other floral resources, as well as the influence of nutritional quality and landscape composition on pollen diet composition over five consecutive years. From April to October, the mass of pollen and nectar collected by honey bees followed a bimodal seasonal trend, marked by a two-month period of low food supply between the two oilseed crop mass-flowerings (ending in May for rapeseed and July for sunflower). Bees collected nectar mainly from crops while pollen came from a wide diversity of herbaceous and woody plant species in semi-natural habitats or from weeds in crops. Weed species constituted the bulk of the honey bee diet between the mass flowering crop periods (up to 40%) and are therefore suspected to play a critical role at this time period. The pollen diet composition was related to the nutritional value of the collected pollen and by the local landscape composition. Our study highlights (1) a food supply depletion period of both pollen and nectar resources during late spring, contemporaneously with the demographic peak of honey bee populations, (2) a high botanical richness of pollen diet, mostly proceeding from trees and weeds, and (3) a pollen diet composition influenced by the local landscape composition. Our results therefore support the Agri-Environmental Schemes intended to promote honey bees and beekeeping sustainability through the enhancement of flower availability in agricultural landscapes.

A Global Meta-Analysis on the Impact of Management Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Cropland Soils.

PubMed

Sainju, Upendra M

2016-01-01

Management practices, such as tillage, crop rotation, and N fertilization, may affect net global warming potential (GWP) and greenhouse gas intensity (GHGI), but their global impact on cropland soils under different soil and climatic conditions need further evaluation. Available global data from 57 experiments and 225 treatments were evaluated for individual and combined effects of tillage, cropping systems, and N fertilization rates on GWP and GHGI which accounted for CO2 equivalents from N2O and CH4 emissions with or without equivalents from soil C sequestration rate (ΔSOC), farm operations, and N fertilization. The GWP and GHGI were 66 to 71% lower with no-till than conventional till and 168 to 215% lower with perennial than annual cropping systems, but 41 to 46% greater with crop rotation than monocroppping. With no-till vs. conventional till, GWP and GHGI were 2.6- to 7.4-fold lower when partial than full accounting of all sources and sinks of greenhouse gases (GHGs) were considered. With 100 kg N ha-1, GWP and GHGI were 3.2 to 11.4 times greater with partial than full accounting. Both GWP and GHGI increased curvilinearly with increased N fertilization rate. Net GWP and GHGI were 70 to 87% lower in the improved combined management that included no-till, crop rotation/perennial crop, and reduced N rate than the traditional combined management that included conventional till, monocopping/annual crop, and recommended N rate. An alternative soil respiration method, which replaces ΔSOC by soil respiration and crop residue returned to soil in the previous year, similarly reduced GWP and GHGI by 133 to 158% in the improved vs. the traditional combined management. Changes in GWP and GHGI due to improved vs. traditional management varied with the duration of the experiment and inclusion of soil and climatic factors in multiple linear regressions improved their relationships. Improved management practices reduced GWP and GHGI compared with traditional management practices and combined management practices were even more effective than individual management practices in reducing net GHG emissions from cropland soils. Partial accounting overestimated GWP and GHGI values as sinks or sources of net GHGs compared with full accounting when evaluating the effect of management practices.

A Global Meta-Analysis on the Impact of Management Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Cropland Soils

PubMed Central

Sainju, Upendra M.

2016-01-01

Management practices, such as tillage, crop rotation, and N fertilization, may affect net global warming potential (GWP) and greenhouse gas intensity (GHGI), but their global impact on cropland soils under different soil and climatic conditions need further evaluation. Available global data from 57 experiments and 225 treatments were evaluated for individual and combined effects of tillage, cropping systems, and N fertilization rates on GWP and GHGI which accounted for CO2 equivalents from N2O and CH4 emissions with or without equivalents from soil C sequestration rate (ΔSOC), farm operations, and N fertilization. The GWP and GHGI were 66 to 71% lower with no-till than conventional till and 168 to 215% lower with perennial than annual cropping systems, but 41 to 46% greater with crop rotation than monocroppping. With no-till vs. conventional till, GWP and GHGI were 2.6- to 7.4-fold lower when partial than full accounting of all sources and sinks of greenhouse gases (GHGs) were considered. With 100 kg N ha-1, GWP and GHGI were 3.2 to 11.4 times greater with partial than full accounting. Both GWP and GHGI increased curvilinearly with increased N fertilization rate. Net GWP and GHGI were 70 to 87% lower in the improved combined management that included no-till, crop rotation/perennial crop, and reduced N rate than the traditional combined management that included conventional till, monocopping/annual crop, and recommended N rate. An alternative soil respiration method, which replaces ΔSOC by soil respiration and crop residue returned to soil in the previous year, similarly reduced GWP and GHGI by 133 to 158% in the improved vs. the traditional combined management. Changes in GWP and GHGI due to improved vs. traditional management varied with the duration of the experiment and inclusion of soil and climatic factors in multiple linear regressions improved their relationships. Improved management practices reduced GWP and GHGI compared with traditional management practices and combined management practices were even more effective than individual management practices in reducing net GHG emissions from cropland soils. Partial accounting overestimated GWP and GHGI values as sinks or sources of net GHGs compared with full accounting when evaluating the effect of management practices. PMID:26901827

Land management: data availability and process understanding for global change studies.

PubMed

Erb, Karl-Heinz; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Pongratz, Julia; Don, Axel; Kloster, Silvia; Kuemmerle, Tobias; Fetzel, Tamara; Fuchs, Richard; Herold, Martin; Haberl, Helmut; Jones, Chris D; Marín-Spiotta, Erika; McCallum, Ian; Robertson, Eddy; Seufert, Verena; Fritz, Steffen; Valade, Aude; Wiltshire, Andrew; Dolman, Albertus J

2017-02-01

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling. © 2016 John Wiley & Sons Ltd.

Molecular Breeding Strategy and Challenges Towards Improvement of Blast Disease Resistance in Rice Crop

PubMed Central

Ashkani, Sadegh; Rafii, Mohd Y.; Shabanimofrad, Mahmoodreza; Miah, Gous; Sahebi, Mahbod; Azizi, Parisa; Tanweer, Fatah A.; Akhtar, Mohd Sayeed; Nasehi, Abbas

2015-01-01

Rice is a staple and most important security food crop consumed by almost half of the world’s population. More rice production is needed due to the rapid population growth in the world. Rice blast caused by the fungus, Magnaporthe oryzae is one of the most destructive diseases of this crop in different part of the world. Breakdown of blast resistance is the major cause of yield instability in several rice growing areas. There is a need to develop strategies providing long-lasting disease resistance against a broad spectrum of pathogens, giving protection for a long time over a broad geographic area, promising for sustainable rice production in the future. So far, molecular breeding approaches involving DNA markers, such as QTL mapping, marker-aided selection, gene pyramiding, allele mining and genetic transformation have been used to develop new resistant rice cultivars. Such techniques now are used as a low-cost, high-throughput alternative to conventional methods allowing rapid introgression of disease resistance genes into susceptible varieties as well as the incorporation of multiple genes into individual lines for more durable blast resistance. The paper briefly reviewed the progress of studies on this aspect to provide the interest information for rice disease resistance breeding. This review includes examples of how advanced molecular method have been used in breeding programs for improving blast resistance. New information and knowledge gained from previous research on the recent strategy and challenges towards improvement of blast disease such as pyramiding disease resistance gene for creating new rice varieties with high resistance against multiple diseases will undoubtedly provide new insights into the rice disease control. PMID:26635817

Sorption, Uptake, and Translocation of Pharmaceuticals across Multiple Interfaces in Soil Environment

NASA Astrophysics Data System (ADS)

Zhang, W.; Liu, C. H.; Bhalsod, G.; Zhang, Y.; Chuang, Y. H.; Boyd, S. A.; Teppen, B. J.; Tiedje, J. M.; Li, H.

2015-12-01

Pharmaceuticals are contaminants of emerging concern frequently detected in soil and water environments, raising serious questions on their potential impact on human and ecosystem health. Overuse and environmental release of antibiotics (i.e., a group of pharmaceuticals extensively used in human medicine and animal agriculture) pose enormous threats to the health of human, animal, and the environment, due to proliferation of antibiotic resistant bacteria. Recently, we have examined interactions of pharmaceuticals with soil geosorbents, bacteria, and vegetable crops in order to elucidate pathways of sorption, uptake, and translocation of pharmaceuticals across the multiple interfaces in soils. Sorption of pharmaceuticals by biochars was studied to assess the potential of biochar soil amendment for reducing the transport and bioavailability of antibiotics. Our preliminary results show that carbonaceous materials such as biochars and activated carbon had strong sorption capacities for antibiotics, and consequently decreased the uptake and antibiotic resistance gene expression by an Escherichia coli bioreporter. Thus, biochar soil amendment showed the potential for reducing selection pressure on antibiotic resistant bacteria. Additionally, since consumption of pharmaceutical-tainted food is a direct exposure pathway for humans, it is important to assess the uptake and accumulation of pharmaceuticals in food crops grown in contaminated soils or irrigated with reclaimed water. Therefore, we have investigated the uptake and accumulations of pharmaceuticals in greenhouse-grown lettuce under contrasting irrigation practices (i.e., overhead or surface irrigations). Preliminary results indicate that greater pharmaceutical concentrations were measured in overhead irrigated lettuce than in surface irrigated lettuce. This could have important implications when selecting irrigation scheme to use the reclaimed water for crop irrigation. In summary, proper soil and water management is needed to minimize the transfer of pharmaceuticals from soil and water to biota.

Global genetic differentiation in a cosmopolitan pest of stored beans: effects of geography, host-plant usage and anthropogenic factors.

PubMed

Tuda, Midori; Kagoshima, Kumiko; Toquenaga, Yukihiko; Arnqvist, Göran

2014-01-01

Genetic differentiation can be promoted allopatrically by geographic isolation of populations due to limited dispersal ability and diversification over time or sympatrically through, for example, host-race formation. In crop pests, the trading of crops across the world can lead to intermixing of genetically distinct pest populations. However, our understanding of the importance of allopatric and sympatric genetic differentiation in the face of anthropogenic genetic intermixing is limited. Here, we examined global sequence variation in two mitochondrial and one nuclear genes in the seed beetle Callosobruchus maculatus that uses different legumes as hosts. We analyzed 180 samples from 42 populations of this stored bean pest from tropical and subtropical continents and archipelagos: Africa, the Middle East, South and Southeast Asia, Oceania and South America. For the mitochondrial genes, there was weak but significant genetic differentiation across continents/archipelagos. Further, we found pronounced differentiation among subregions within continents/archipelagos both globally and within Africa but not within Asia. We suggest that multiple introductions into Asia and subsequent intermixing within Asia have generated this pattern. The isolation by distance hypothesis was supported globally (with or without continents controlled) but not when host species was restricted to cowpeas Vigna unguiculata, the ancestral host of C. maculatus. We also document significant among-host differentiation both globally and within Asia, but not within Africa. We failed to reject a scenario of a constant population size in the recent past combined with selective neutrality for the mitochondrial genes. We conclude that mitochondrial DNA differentiation is primarily due to geographic isolation within Africa and to multiple invasions by different alleles, followed by host shifts, within Asia. The weak inter-continental differentiation is most likely due to frequent inter-continental gene flow mediated by human crop trade.

A Passive Method for Detecting Vegetation Stress from Orbit: Chlorophyll Fluorescence Spectra from Fraunhofer Lines

NASA Technical Reports Server (NTRS)

Theisen, Arnold F.

2000-01-01

Solar-stimulated chlorophyll fluorescence measured with the Fraunhofer line depth method has correlated well with vegetation stress in previous studies. However, the instruments used in those studies were limited to a single solar absorption line (e.g. 656.3 nm), obviating the red/far-red ratio (R/FR) method. Optics and detector technology have reached the level whereby multiple, very narrow Fraunhofer lines are resolvable. Thirteen such lines span the visible spectrum in the red to far-red region where chlorophyll fluorescence occurs. Fluorescence intensities at the 13 Fraunhofer line wavelengths were used to model emission spectra. The source data were collected for summer and fall bean crops (Phaseolus vulgaris L.) subjected to various levels of nitrogen fertilization. The intensities were adjusted to account for Fraunhofer line depth and atmospheric transmittance. Multiple R/FR fluorescence ratios, calculated from the modeled fluorescence spectra, correlated strongly with leaf chlorophyll concentration and well with applied nitrogen. The ratio yielding the best correlation with chlorophyll utilized red fluorescence at the 694.5 nm Fraunhofer line and farred fluorescence at the 755.6 nm Fraunhofer line. Twenty R/FR ratios, each evaluated for the maximum differential between low and high (optimal) nitrogen treatments, ranked higher in some cases and lower in others, possibly related to the time of year the crops were grown and the stage of growth of the crops. Ratios with 728.9 nm and 738.9 nm in the denominator consistently ranked in the lowest and next lowest quartile, respectively. Ratios of the 656.3 nm Fraunhofer line and the 755.6 nm line consistently ranked highest for the summer crop. Ratios with 755.6 nm in the denominator ranked in the upper quartile for 10 out of 12 measurement dates. Differences in ratio ranking indicate that physiological conditions may be estimated using selected ratios of Fraunhofer lines within the context of R/FR analysis. A passive instrument designed to monitor R/FR chlorophyll fluorescence (i.e. vegetation stress) from orbit could be built today.

Evaluation of Salmonella enteritidis in molting hens after administration of an experimental chlorate product (for nine days) in the drinking water and feeding an alfalfa molt diet.

PubMed

McReynolds, J; Kubena, L; Byrd, J; Anderson, R; Ricke, S; Nisbet, D

2005-08-01

The method most commonly used to induce molting and stimulate multiple egg-laying cycles in laying hens for commercial egg production is to fast the hens. Unfortunately, increased risk of Salmonella enteritidis (SE) infection may result from the use of this method. Methods to stimulate multiple egg-laying cycles without increasing the risk of SE infection are needed. Hens over 50 wk of age were divided into 12 groups of 11 hens each and placed in individual laying cages. One week prior to dietary changes, hens were placed on an 8-h light and 16-h dark photoperiod that continued for the 9-d molt. All hens were challenged orally with 10(6) cfu of SE on the fourth day of the molt. Treatments were nonfed hens with distilled water (NFD), nonfed hens with the experimental chlorate product (ECP, which provided 15 mM chlorate ion) water (NFECP), alfalfa diets with distilled water (ALD), and alfalfa diets with ECP water (ALECP). In the NFD hens, 67% (log10 2.74) of the crops and 94% (log10 5.62) of the ceca were colonized, whereas for the NFECP hens significant reductions to 22% (log10 1.05) of the crops and 61% (log10 2.44) of the ceca were observed. In the ALD hens, 61% (log10 2.52) of the crops and 94% (log10 4.06) of the ceca were colonized. In the ALECP hens, highly significant reductions to 11% (log10 1.26) of the crops and 39% (log10 1.12) of the ceca were observed. When compared with the NFD hens, significant reductions in SE invasion of the ovary, liver, and spleen occurred in all other treatments, except the ovary in the ALD hens. The low alfalfa intake is probably a factor in our lowered protection against SE when compared with previous results. For several parameters, these results suggest that ECP or the combination of ECP and alfalfa may be a useful tool to reduce the risk of SE during an induced molt.

Diversity pattern in Sesamum mutants selected for a semi-arid cropping system.

PubMed

Murty, B R; Oropeza, F

1989-02-01

Due to the complex requirements of moisture stress, substantial genetic diversity with a wide array of character combinations and effective simultaneous selection for several variables is necessary for improving the productivity and adaptation of a component crop in order for it to fit into a cropping system under semi-arid tropical conditions. Sesamum indicum L. is grown in Venezuela after rice/sorghum/or maize under such conditions. A mutation breeding program was undertaken using six locally adapted varieties to develop genotypes suitable for the above system. The diversity pattern for nine variables was assessed by multivariate analysis in 301 M4 progenies. Analysis of the characteristic roots and principal components in three methods of selection, i.e., M2 bulks (A), individual plant selection throughout (B), and selection in M3 for single variable (C), revealed differences in the pattern of variation between varieties, selection methods, and varieties x methods interactions. Method B was superior to the others and gave 17 of the 21 best M5 progenies. 'Piritu' and 'CF' varieties yielded the most productive progenies in M5 and M6. Diversity was large and selection was effective for such developmental traits as earliness and synchrony, combined with multiple disease resistance, which could be related to their importance by multivariate analyses. Considerable differences in the variety of character combinations among the high yielding. M5 progenies of 'CF' and 'Piritu' suggested possible further yield improvement. The superior response of 'Piritu' and 'CF' over other varieties in yield and adaptation was due to major changes in plant type and character associations. Multilocation testing of M5 generations revealed that the mutant progenies had a 40%-100% yield superiority over the parents; this was combined with earliness, synchrony, and multiple disease resistance, and was confirmed in the M6 generation grown on a commercial scale. This study showed that multivariate analysis is an effective tool for assessing diversity patterns, choice of appropriate variety, and selection methodology in order to make rapid progress in meeting the complex requirements of semi-arid cropping systems.

Effect of the time of application of phosphorus fertilizer on yield and quality parameters of melon crop amended with winery waste compost.

NASA Astrophysics Data System (ADS)

Requejo Mariscal, María Isabel; Cartagena, María Carmen; Villena Gordo, Raquel; Arce Martínez, Augusto; Ribas Elcorobarrutia, Francisco; Jesús Cabello Cabello, María; Castellanos Serrano, María Teresa

2016-04-01

In Spain, drip irrigation systems are widely used for horticultural crop production. In drip irrigation systems, emitter clogging has been identified as one of the most important concerns. Clogging is closely related to the quality of the irrigation water and the structure of the emitter flow path, and occurs as a result of multiple physical, biological and chemical factors. So, the use of acid fertilizers (e.g. phosphoric acid) in these systems is common to avoid the emitter clogging. Moreover, in this country the use of exhausted grape marc compost as source of nutrients and organic matter has been identified as a good management option of soil fertility, especially in grape-growing areas with a large generation of wastes from the wine and distillery industries. The purpose of this work was to study the effect of the time of application of phosphorus fertilizer with fertirrigation in a melon crop amended with winery waste compost on yield and quality parameters. During two years, the melon crop was grown under field conditions and beside the control treatment, three doses of compost were applied: 6.7, 13.3 and 20.0 t ha-1. All the compost treatments received 120 kg ha-1 of phosphorus fertilizer (phosphoric acid) for the season varying the time of application: The first year phosphorus application started after male and female flowering, and the second year the application started before flowering. Yield and quality parameters were evaluated to assess the suitability of these practices. Acknowledgements: This project has been supported by INIA-RTA2010-00110-C03. Keywords: Phosphorus fertilizer, exhausted grape marc compost, melon crop, yield and quality parameters.

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.

Estimating 20-year land-use change and derived CO2 emissions associated with crops, pasture and forestry in Brazil and each of its 27 states.

PubMed

Novaes, Renan M L; Pazianotto, Ricardo A A; Brandão, Miguel; Alves, Bruno J R; May, André; Folegatti-Matsuura, Marília I S

2017-09-01

Land-use change (LUC) in Brazil has important implications on global climate change, ecosystem services and biodiversity, and agricultural expansion plays a critical role in this process. Concerns over these issues have led to the need for estimating the magnitude and impacts associated with that, which are increasingly reported in the environmental assessment of products. Currently, there is an extensive debate on which methods are more appropriate for estimating LUC and related emissions and regionalized estimates are lacking for Brazil, which is a world leader in agricultural production (e.g. food, fibres and bioenergy). We developed a method for estimating scenarios of past 20-year LUC and derived CO 2 emission rates associated with 64 crops, pasture and forestry in Brazil as whole and in each of its 27 states, based on time-series statistics and in accordance with most used carbon-footprinting standards. The scenarios adopted provide a range between minimum and maximum rates of CO 2 emissions from LUC according to different possibilities of land-use transitions, which can have large impacts in the results. Specificities of Brazil, like multiple cropping and highly heterogeneous carbon stocks, are also addressed. The highest CO 2 emission rates are observed in the Amazon biome states and crops with the highest rates are those that have undergone expansion in this region. Some states and crops showing large agricultural areas have low emissions associated, especially in southern and eastern Brazil. Native carbon stocks and time of agricultural expansion are the most decisive factors to the patterns of emissions. Some implications on LUC estimation methods and standards and on agri-environmental policies are discussed. © 2017 John Wiley & Sons Ltd.

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

Suppression of Plutella xylostella and Trichoplusia ni in cole crops with attracticide formulations.

PubMed

Maxwell, Elly M; Fadamiro, Henry Y; McLaughlin, John R

2006-08-01

The three key lepidopteran pests of cole, Brassica oleracea L., crops in North America are diamondback moth, Plutella xylostella (L.) (Lepidoptera: Plutellidae); cabbage looper; Trichoplusia ni (Hübner) (Lepidoptera: Noctuidae); and imported cabbageworm, Pieris rapae (L.) (Lepidoptera: Pieridae). Two species-specific pheromone-based experimental attracticide formulations were evaluated against these pests: LastCall DBM for P. xylostella and LastCall CL for T. ni. No LastCall formulation was available against P. rapae. Laboratory toxicity experiments confirmed the effectiveness of each LastCall formulations in killing conspecific males that made contact. In replicated small plots of cabbage and collards in central Alabama, over four growing seasons (fall 2003, spring 2004, fall 2004, and spring 2005), an attracticide treatment receiving the two LastCall formulations, each applied multiple times at the rate of 1,600 droplets per acre, was compared against Bacillus thuringiensis. subspecies kursatki (Bt) spray at action threshold and a negative untreated control. Efficacy was measured by comparing among the three treatments male capture in pheromone-baited traps, larval counts in plots, and crop damage rating at harvest. LastCall provided significant reductions in crop damage comparable to Bt in three of the four seasons. Efficacy of LastCall was dependent upon lepidopteran population densities, which fluctuated from season to season. In general, reduction in crop damage was achieved with LastCall at low-to-moderate population densities of the three species, such as typically occurs in the fall in central Alabama, but not in the spring when high P. rapae population pressure typically occurs in central Alabama. Significant reductions in pheromone trap captures did not occur in LastCall plots, suggesting that elimination of males by the toxicant (permethrin), rather than interruption of sexual communication, was the main mechanism of effect.

SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

NASA Astrophysics Data System (ADS)

Kotsuki, S.; Tanaka, K.

2015-01-01

To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

Farm residence and lymphohematopoietic cancers in the Iowa Women’s Health Study

PubMed Central

Jones, Rena R.; Yu, Chu-Ling; Nuckols, John R.; Cerhan, James R.; Airola, Matthew; Ross, Julie A.; Robien, Kim; Ward, Mary H.

2014-01-01

Background Cancer incidence in male farmers has been studied extensively; however, less is known about risk among women residing on farms or in agricultural areas, who may be exposed to pesticides by their proximity to crop fields. We extended a previous follow-up of the Iowa Women’s Health Study cohort to examine farm residence and the incidence of lymphohematopoietic cancers. Further, we investigated crop acreage within 750 m of residences, which has been associated with higher herbicide levels in Iowa homes. Methods We analyzed data for a cohort of 37,099 Iowa women aged 55–69 years who reported their residence location (farm, rural (not a farm), town size based on population) at enrollment in 1986. We identified incident lymphohematopoietic cancers (1986–2009) by linkage with the Iowa Cancer Registry. Using a geographic information system, we geocoded addresses and calculated acreage of pasture and row crops within 750 m of homes using the 1992 National Land Cover Database. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) in multivariate analyses of cancer risk in relation to both residence location and crop acreage. Results As found in an earlier analysis of residence location, risk of acute myeloid leukemia (AML) was higher among women living on farms (HR= 2.23, 95%CI: 1.25–3.99) or rural areas (but not on a farm) (HR= 1.95, 95%CI: 0.89–4.29) compared with women living in towns of > 10,000 population. We observed no association between farm or rural residence and non-Hodgkin lymphoma (NHL; overall or for major subtypes) or multiple myeloma. In analyses of crop acreage, we observed no association between pasture or row crop acreage within 750 m of homes and risk of leukemia overall or for the AML subtype. Chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) risk was nonsignificantly elevated among women with pasture acreage within 750 m of their home (HRs for increasing tertiles= 1.8, 1.8 and 1.5) and with row crop acreage within 750 m (HRs for increasing tertiles of acreage= 1.4, 1.5 and 1.6) compared to women with no pasture or row crop acreage, respectively. Conclusions Iowa women living on a farm or in a rural area were at increased risk of developing AML, which was not related to crop acreage near the home. Living near pasture or row crops may confer an increased risk of CLL/SLL regardless of residence location. Further investigation of specific farm-related exposures and these cancers among women living on farms and in agricultural areas is warranted. PMID:25038451

Farm residence and lymphohematopoietic cancers in the Iowa Women's Health Study.

PubMed

Jones, Rena R; Yu, Chu-Ling; Nuckols, John R; Cerhan, James R; Airola, Matthew; Ross, Julie A; Robien, Kim; Ward, Mary H

2014-08-01

Cancer incidence in male farmers has been studied extensively; however, less is known about risk among women residing on farms or in agricultural areas, who may be exposed to pesticides by their proximity to crop fields. We extended a previous follow-up of the Iowa Women's Health Study cohort to examine farm residence and the incidence of lymphohematopoietic cancers. Further, we investigated crop acreage within 750 m of residences, which has been associated with higher herbicide levels in Iowa homes. We analyzed data for a cohort of 37,099 Iowa women aged 55-69 years who reported their residence location (farm, rural (not a farm), town size based on population) at enrollment in 1986. We identified incident lymphohematopoietic cancers (1986-2009) by linkage with the Iowa Cancer Registry. Using a geographic information system, we geocoded addresses and calculated acreage of pasture and row crops within 750 m of homes using the 1992 National Land Cover Database. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) in multivariate analyses of cancer risk in relation to both residence location and crop acreage. As found in an earlier analysis of residence location, risk of acute myeloid leukemia (AML) was higher among women living on farms (HR=2.23, 95%CI: 1.25-3.99) or rural areas (but not on a farm) (HR=1.95, 95%CI: 0.89-4.29) compared with women living in towns of >10,000 population. We observed no association between farm or rural residence and non-Hodgkin lymphoma (NHL; overall or for major subtypes) or multiple myeloma. In analyses of crop acreage, we observed no association between pasture or row crop acreage within 750 m of homes and risk of leukemia overall or for the AML subtype. Chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) risk was nonsignificantly elevated among women with pasture acreage within 750 m of their home (HRs for increasing tertiles=1.8, 1.8 and 1.5) and with row crop acreage within 750 m (HRs for increasing tertiles of acreage=1.4, 1.5 and 1.6) compared to women with no pasture or row crop acreage, respectively. Iowa women living on a farm or in a rural area were at increased risk of developing AML, which was not related to crop acreage near the home. Living near pasture or row crops may confer an increased risk of CLL/SLL regardless of residence location. Further investigation of specific farm-related exposures and these cancers among women living on farms and in agricultural areas is warranted. Copyright © 2014. Published by Elsevier Inc.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

Low pH, aluminum and phosphorus coordinately regulate malate exudation through GmALMT1 to improve soybean adaptation to acid soils

USDA-ARS?s Scientific Manuscript database

Low pH, aluminum (Al) toxicity and low phosphorus (P) often coexist in acid soils where crops need to cope with these multiple limiting factors. In this study we found that P addition to acid soils alleviates Al toxicity and enhanced soybean adaptation to acid soils, especially for the P-efficient g...

Distribution and Biocontrol Potential of phlD(+) Pseudomonads in Corn and Soybean Fields.

PubMed

McSpadden Gardener, Brian B; Gutierrez, Laura J; Joshi, Raghavendra; Edema, Richard; Lutton, Elizabeth

2005-06-01

ABSTRACT The abundance and diversity of phlD(+) Pseudomonas spp. colonizing the rhizospheres of young, field-grown corn and soybean plants were assayed over a 3-year period. Populations of these bacteria were detected on the large majority of plants sampled in the state of Ohio, but colonization was greater on corn. Although significant variation in the incidence of rhizosphere colonization was observed from site to site and year to year on both crops, the magnitude of the variation was greatest for soybean. The D genotype was detected on plants collected from all 15 counties examined, and it represented the most abundant subpopulation on both crops. Additionally, six other genotypes (A, C, F, I, R, and S) were found to predominate in the rhizosphere of some plants. The most frequently observed of these were the A genotype and a newly discovered S genotype, both of which were found on corn and soybean roots obtained from multiple locations. Multiple isolates of the most abundant genotypes were recovered and characterized. The S genotype was found to be phylogenetically and phenotypically similar to the D genotype. In addition, the novel R genotype was found to be most similar to the A genotype. All of the isolates displayed significant capacities to inhibit the growth of an oomycete pathogen in vitro, but such phenotypes were highly dependent on media used. When tested against multiple oomycete pathogens isolated from soybean, the A genotype was significantly more inhibitory than the D genotype when incubated on 1/10x tryptic soy agar and 1/5x corn meal agar. Seed inoculation with different isolates of the A, D, and S genotypes indicated that significant root colonization, generally in excess of log 5 cells per gram of root, could be attained on both crops. Field trials of the A genotype isolate Wayne1R indicated the capacity of inoculant populations to supplement the activities of native populations so as to increase soybean stands and yields. The relevance of these findings to natural and augmentative biocontrol of root pathogens by these bacteria is discussed.

From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

NASA Astrophysics Data System (ADS)

JÉGO, G.; Pattey, E.; Liu, J.

2013-12-01

The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%

An inventory of irrigated lands for selected counties within the state of California based on LANDSAT and supporting aircraft data

NASA Technical Reports Server (NTRS)

Colwell, R. N. (Principal Investigator)

1977-01-01

The author has identified the following significant results: (1) Goals of the irrigated lands project were addressed by the design and implementation of a multiphase sampling scheme that was founded on the utilization of a LANDSAT-based remote sensing system. (2) The synoptic coverage of LANDSAT and the eighteen day orbit cycle allowed the project to study agricultural test sites in a variety of environmental regions and monitor the development of crops throughout the major growing season. (3) The capability to utilize multidate imagery is crucial to the reliable estimation of irrigated acreage in California where multiple cropping is widespread and current estimation systems must rely on single data survey techniques. (4) In addition, the magnitude of agricultural acreage in California makes estimation by conventional methods impossible.

Effects of irrigation water supply variations on limited resource farming in Conejos County, Colorado

NASA Astrophysics Data System (ADS)

Eckert, Jerry B.; Wang, Erda

1993-02-01

Farms in NE Conejos County, Colorado, are characterized by limited resources, uncertain surface flow irrigation systems, and mixed crop-livestock enterprise combinations which are dependent on public grazing resources. To model decision making on these farms, a linear program is developed stressing enterprise choices under conditions of multiple resource constraints. Differential access to grazing resources and irrigation water is emphasized in this research. Regarding the water resource, the model reflects farms situated alternatively on high-, medium-, and low-priority irrigation ditches within the Alamosa-La Jara river system, each with and without supplemental pumping. Differences are found in optimum enterprise mixes, net returns, choice of cropping technology, level of marketings, and other characteristics in response to variations in the availability of irrigation water. Implications are presented for alternative improvement strategies.

Biodiversity of complexes of mycotoxigenic fungal species associated with Fusarium ear rot of maize and Aspergillus rot of grape.

PubMed

Logrieco, A; Moretti, A; Perrone, G; Mulè, G

2007-10-20

Fusarium ear rot of maize and Aspergillus rot of grape are two examples of important plant diseases caused by complexes of species of mycotoxigenic fungi. These complexes of species tend to be closely related, produce different classes of mycotoxins, and can induce disease under different environmental conditions. The infection of maize and grape with multiple fungal species and the resulting production of large classes of mycotoxins is an example of mutual aggressiveness of microorganisms toward host species as well as to humans and animals that eat feed or food derived from the infected and contaminated plants. Infection of crop plant with a complex of microbial species certainly represents a greater threat to a crop plant and to human and animal health than infection of the plant with a single fungal species.

Modeling the Interactions Between Multiple Crack Closure Mechanisms at Threshold

NASA Technical Reports Server (NTRS)

Newman, John A.; Riddell, William T.; Piascik, Robert S.

2003-01-01

A fatigue crack closure model is developed that includes interactions between the three closure mechanisms most likely to occur at threshold; plasticity, roughness, and oxide. This model, herein referred to as the CROP model (for Closure, Roughness, Oxide, and Plasticity), also includes the effects of out-of plane cracking and multi-axial loading. These features make the CROP closure model uniquely suited for, but not limited to, threshold applications. Rough cracks are idealized here as two-dimensional sawtooths, whose geometry induces mixed-mode crack- tip stresses. Continuum mechanics and crack-tip dislocation concepts are combined to relate crack face displacements to crack-tip loads. Geometric criteria are used to determine closure loads from crack-face displacements. Finite element results, used to verify model predictions, provide critical information about the locations where crack closure occurs.

Contribution of wetlands to nitrate removal at the watershed scale

NASA Astrophysics Data System (ADS)

Hansen, Amy T.; Dolph, Christine L.; Foufoula-Georgiou, Efi; Finlay, Jacques C.

2018-02-01

Intensively managed row crop agriculture has fundamentally changed Earth surface processes within the Mississippi River basin through large-scale alterations of land cover, hydrology and reactive nitrogen availability. These changes have created leaky landscapes where excess agriculturally derived nitrate degrades riverine water quality at local, regional and continental scales. Individually, wetlands are known to remove nitrate but the conditions under which multiple wetlands meaningfully reduce riverine nitrate concentration have not been established. Only one region of the Mississippi River basin—the 44,000 km2 Minnesota River basin—still contains enough wetland cover within its intensively agriculturally managed watersheds to empirically address this question. Here we combine high-resolution land cover data for the Minnesota River basin with spatially extensive repeat water sampling data. By clearly isolating the effect of wetlands from crop cover, we show that, under moderate-high streamflow, wetlands are five times more efficient per unit area at reducing riverine nitrate concentration than the most effective land-based nitrogen mitigation strategies, which include cover crops and land retirement. Our results suggest that wetland restorations that account for the effects of spatial position in stream networks could provide a much greater benefit to water quality then previously assumed.

How can we make plants grow faster? A source–sink perspective on growth rate

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

White, Angela C.; Rogers, Alistair; Rees, Mark

Growth is a major component of fitness in all organisms, an important mediator of competitive interactions in plant communities, and a central determinant of yield in crops. Understanding what limits plant growth is therefore of fundamental importance to plant evolution, ecology, and crop science, but each discipline views the process from a different perspective. This review highlights the importance of source–sink interactions as determinants of growth. The evidence for source- and sink-limitation of growth, and the ways in which regulatory molecular feedback systems act to maintain an appropriate source:sink balance, are first discussed. Evidence clearly shows that future increases inmore » crop productivity depend crucially on a quantitative understanding of the extent to which sources or sinks limit growth, and how this changes during development. In addition, to identify bottlenecks limiting growth and yield, a holistic view of growth is required at the whole-plant scale, incorporating mechanistic interactions between physiology, resource allocation, and plant development. Such a holistic perspective on source–sink interactions will allow the development of a more integrated, whole-system level understanding of growth, with benefits across multiple disciplines.« less

Phospholipase Dε enhances Braasca napus growth and seed production in response to nitrogen availability.

PubMed

Lu, Shaoping; Yao, Shuaibing; Wang, Geliang; Guo, Liang; Zhou, Yongming; Hong, Yueyun; Wang, Xuemin

2016-03-01

Phospholipase D (PLD), which hydrolyses phospholipids to produce phosphatidic acid, has been implicated in plant response to macronutrient availability in Arabidopsis. This study investigated the effect of increased PLDε expression on nitrogen utilization in Brassica napus to explore the application of PLDε manipulation to crop improvement. In addition, changes in membrane lipid species in response to nitrogen availability were determined in the oil seed crop. Multiple PLDε over expression (PLDε-OE) lines displayed enhanced biomass accumulation under nitrogen-deficient and nitrogen-replete conditions. PLDε-OE plants in the field produced more seeds than wild-type plants but have no impact on seed oil content. Compared with wild-type plants, PLDε-OE plants were enhanced in nitrate transporter expression, uptake and reduction, whereas the activity of nitrite reductase was higher under nitrogen-depleted, but not at nitrogen-replete conditions. The level of nitrogen altered membrane glycerolipid metabolism, with greater impacts on young than mature leaves. The data indicate increased expression of PLDε has the potential to improve crop plant growth and production under nitrogen-depleted and nitrogen-replete conditions. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Plant MYB Transcription Factors: Their Role in Drought Response Mechanisms

PubMed Central

Baldoni, Elena; Genga, Annamaria; Cominelli, Eleonora

2015-01-01

Water scarcity is one of the major causes of poor plant performance and limited crop yields worldwide and it is the single most common cause of severe food shortage in developing countries. Several molecular networks involved in stress perception, signal transduction and stress responses in plants have been elucidated so far. Transcription factors are major players in water stress signaling. In recent years, different MYB transcription factors, mainly in Arabidopsis thaliana (L.) Heynh. but also in some crops, have been characterized for their involvement in drought response. For some of them there is evidence supporting a specific role in response to water stress, such as the regulation of stomatal movement, the control of suberin and cuticular waxes synthesis and the regulation of flower development. Moreover, some of these genes have also been characterized for their involvement in other abiotic or biotic stresses, an important feature considering that in nature, plants are often simultaneously subjected to multiple rather than single environmental perturbations. This review summarizes recent studies highlighting the role of the MYB family of transcription factors in the adaptive responses to drought stress. The practical application value of MYBs in crop improvement, such as stress tolerance engineering, is also discussed. PMID:26184177