Assessment of time-series MODIS data for cropland mapping in the U.S. central Great Plains

NASA Astrophysics Data System (ADS)

Masialeti, Iwake

This study had three general objectives. First, to explore ways of creating and refining a reference data set when reference data set is unobtainable. Second, extend work previously done in Kansas by Wardlow et al. (2007) to Nebraska, several exploratory approaches were used to further investigate the potential of MODIS NDVI 250-m data in agricultural-related land cover research other parts of the Great Plains. The objective of this part of the research was to evaluate the applicability of time-series MODIS 250-m NDVI data for crop-type discrimination by spectrally characterizing and discriminating major crop types in Nebraska using the reference data set collected and refined under research performed for the first objective. Third, conduct an initial investigation into whether time-series NDVI response curves for crops over a growing season for one year could be used to classify crops for a different year. In this case, time-series NDVI response curves for 2001 and 2005 were investigated to ascertain whether or not the 2001 data set could be used to classify crops for 2005. GIS operations, and reference data refinement using clustering and visual assessment of each crop's NDVI cluster profiles in Nebraska, demonstrated that it is possible to devise an alternative reference data set and refinement plan that redresses the unexpected loss of training and validation data. The analysis enabled the identification and removal of crop pattern outliers and sites atypical of crop phenology under consideration, and after editing, a total of 1,288 field sites remained, which were used as a reference data set for classification of Nebraska crop types. A pixel-level analysis of the time-series MODIS 250-m NDVI for 1,288 field sites representing each of the eight cover types under investigation across Nebraska found that each crop type had a distinctive MODIS 250-m NDVI profile corresponding to the crop calendar. A visual and statistical comparison of the average NDVI profiles showed that the crop types were separable at different times of the growing season based on their phenology-driven spectral-temporal differences. Winter wheat and alfalfa, winter wheat and summer crops, and alfalfa and summer crops were clearly separable. Specific summer crop types were not easily distinguishable from each other due to their similar crop calendars. Their greatest separability however occurred during the initial spring green up and/or senescence plant growth phases. In Kansas, an initial investigation revealed that there was near-complete agreement between the winter wheat crop profiles but that there were some minor differences in the crop profiles for alfalfa and summer crops between 2001 and 2005. However, the profiles of summer crops---corn, grain sorghum, and soybeans---displayed a shift to the right by at least 1 composite date, indicative of possible late crop planting and emergence. Alfalfa and summer crops, seem to suggest that time series NDVI response curves for crops over a growing period for one year of valid ground reference data may not be used to map crops for a different year without taking into account the climatic and/or environmental conditions of each year.

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.

Soil acidity amelioration in a no-till system in west Tennessee USA differs by cover crop type and nitrogen application rate

USDA-ARS?s Scientific Manuscript database

Conservation soil management practices may influence the soil acidity. Surface application of lime may be required in no-till systems to ameliorate soil acidity and to improve crop yields. The application of lime may also increase microbial activity on soil. Specifically, the microbial activity of s...

Real-time PCR array as a universal platform for the detection of genetically modified crops and its application in identifying unapproved genetically modified crops in Japan.

PubMed

Mano, Junichi; Shigemitsu, Natsuki; Futo, Satoshi; Akiyama, Hiroshi; Teshima, Reiko; Hino, Akihiro; Furui, Satoshi; Kitta, Kazumi

2009-01-14

We developed a novel type of real-time polymerase chain reaction (PCR) array with TaqMan chemistry as a platform for the comprehensive and semiquantitative detection of genetically modified (GM) crops. Thirty primer-probe sets for the specific detection of GM lines, recombinant DNA (r-DNA) segments, endogenous reference genes, and donor organisms were synthesized, and a 96-well PCR plate was prepared with a different primer-probe in each well as the real-time PCR array. The specificity and sensitivity of the array were evaluated. A comparative analysis with the data and publicly available information on GM crops approved in Japan allowed us to assume the possibility of unapproved GM crop contamination. Furthermore, we designed a Microsoft Excel spreadsheet application, Unapproved GMO Checker version 2.01, which helps process all the data of real-time PCR arrays for the easy assumption of unapproved GM crop contamination. The spreadsheet is available free of charge at http://cse.naro.affrc.go.jp/jmano/index.html .

Advances in crop proteomics: PTMs of proteins under abiotic stress.

PubMed

Wu, Xiaolin; Gong, Fangping; Cao, Di; Hu, Xiuli; Wang, Wei

2016-03-01

Under natural conditions, crop plants are frequently subjected to various abiotic environmental stresses such as drought and heat wave, which may become more prevalent in the coming decades. Plant acclimation and tolerance to an abiotic stress are always associated with significant changes in PTMs of specific proteins. PTMs are important for regulating protein function, subcellular localization and protein activity and stability. Studies of plant responses to abiotic stress at the PTMs level are essential to the process of plant phenotyping for crop improvement. The ability to identify and quantify PTMs on a large-scale will contribute to a detailed protein functional characterization that will improve our understanding of the processes of crop plant stress acclimation and stress tolerance acquisition. Hundreds of PTMs have been reported, but it is impossible to review all of the possible protein modifications. In this review, we briefly summarize several main types of PTMs regarding their characteristics and detection methods, review the advances in PTMs research of crop proteomics, and highlight the importance of specific PTMs in crop response to abiotic stress. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An evaluation of time-series MODIS 250-meter vegetation index data for crop mapping in the United States Central Great Plains

NASA Astrophysics Data System (ADS)

Wardlow, Brian Douglas

The objectives of this research were to: (1) investigate time-series MODIS (Moderate Resolution Imaging Spectroradiometer) 250-meter EVI (Enhanced Vegetation Index) and NDVI (Normalized Difference Vegetation Index) data for regional-scale crop-related land use/land cover characterization in the U.S. Central Great Plains and (2) develop and test a MODIS-based crop mapping protocol. A pixel-level analysis of the time-series MODIS 250-m VIs for 2,000+ field sites across Kansas found that unique spectral-temporal signatures were detected for the region's major crop types, consistent with the crops' phenology. Intra-class variations were detected in VI data associated with different land use practices, climatic conditions, and planting dates for the crops. The VIs depicted similar seasonal variations and were highly correlated. A pilot study in southwest Kansas found that accurate and detailed cropping patterns could be mapped using the MODIS 250-m VI data. Overall and class-specific accuracies were generally greater than 90% for mapping crop/non-crop, general crops (alfalfa, summer crops, winter wheat, and fallow), summer crops (corn, sorghum, and soybeans), and irrigated/non-irrigated crops using either VI dataset. The classified crop areas also had a high level of agreement (<5% difference) with the USDA reported crop areas. Both VIs produced comparable crop maps with only a 1-2% difference between their classification accuracies and a high level of pixel-level agreement (>90%) between their classified crop patterns. This hierarchical crop mapping protocol was tested for Kansas and produced similar classification results over a larger and more diverse area. Overall and class-specific accuracies were typically between 85% and 95% for the crop maps. At the state level, the maps had a high level of areal agreement (<5% difference) with the USDA crop area figures and their classified patterns were consistent with the state's cropping practices. In general, the protocol's performance was relatively consistent across the state's range of environmental conditions, landscape patterns, and cropping practices. The largest areal differences occurred in eastern Kansas due to the omission of many small cropland areas that were not resolvable at MODIS' 250-m resolution. Notable regional deviations in classified areas also occurred for selected classes due to localized precipitation patterns and specific cropping practices.

Effect of Nutrient Management Planning on Crop Yield, Nitrate Leaching and Sediment Loading in Thomas Brook Watershed

NASA Astrophysics Data System (ADS)

Amon-Armah, Frederick; Yiridoe, Emmanuel K.; Ahmad, Nafees H. M.; Hebb, Dale; Jamieson, Rob; Burton, David; Madani, Ali

2013-11-01

Government priorities on provincial Nutrient Management Planning (NMP) programs include improving the program effectiveness for environmental quality protection, and promoting more widespread adoption. Understanding the effect of NMP on both crop yield and key water-quality parameters in agricultural watersheds requires a comprehensive evaluation that takes into consideration important NMP attributes and location-specific farming conditions. This study applied the Soil and Water Assessment Tool (SWAT) to investigate the effects of crop and rotation sequence, tillage type, and nutrient N application rate on crop yield and the associated groundwater leaching and sediment loss. The SWAT model was applied to the Thomas Brook Watershed, located in the most intensively managed agricultural region of Nova Scotia, Canada. Cropping systems evaluated included seven fertilizer application rates and two tillage systems (i.e., conventional tillage and no-till). The analysis reflected cropping systems commonly managed by farmers in the Annapolis Valley region, including grain corn-based and potato-based cropping systems, and a vegetable-horticulture system. ANOVA models were developed and used to assess the effects of crop management choices on crop yield and two water-quality parameters (i.e., leaching and sediment loading). Results suggest that existing recommended N-fertilizer rate can be reduced by 10-25 %, for grain crop production, to significantly lower leaching ( P > 0.05) while optimizing the crop yield. The analysis identified the nutrient N rates in combination with specific crops and rotation systems that can be used to manage leaching while balancing impacts on crop yields within the watershed.

Genome editing for crop improvement: Challenges and opportunities

PubMed Central

Abdallah, Naglaa A; Prakash, Channapatna S; McHughen, Alan G

2015-01-01

ABSTRACT Genome or gene editing includes several new techniques to help scientists precisely modify genome sequences. The techniques also enables us to alter the regulation of gene expression patterns in a pre-determined region and facilitates novel insights into the functional genomics of an organism. Emergence of genome editing has brought considerable excitement especially among agricultural scientists because of its simplicity, precision and power as it offers new opportunities to develop improved crop varieties with clear-cut addition of valuable traits or removal of undesirable traits. Research is underway to improve crop varieties with higher yields, strengthen stress tolerance, disease and pest resistance, decrease input costs, and increase nutritional value. Genome editing encompasses a wide variety of tools using either a site-specific recombinase (SSR) or a site-specific nuclease (SSN) system. Both systems require recognition of a known sequence. The SSN system generates single or double strand DNA breaks and activates endogenous DNA repair pathways. SSR technology, such as Cre/loxP and Flp/FRT mediated systems, are able to knockdown or knock-in genes in the genome of eukaryotes, depending on the orientation of the specific sites (loxP, FLP, etc.) flanking the target site. There are 4 main classes of SSN developed to cleave genomic sequences, mega-nucleases (homing endonuclease), zinc finger nucleases (ZFNs), transcriptional activator-like effector nucleases (TALENs), and the CRISPR/Cas nuclease system (clustered regularly interspaced short palindromic repeat/CRISPR-associated protein). The recombinase mediated genome engineering depends on recombinase (sub-) family and target-site and induces high frequencies of homologous recombination. Improving crops with gene editing provides a range of options: by altering only a few nucleotides from billions found in the genomes of living cells, altering the full allele or by inserting a new gene in a targeted region of the genome. Due to its precision, gene editing is more precise than either conventional crop breeding methods or standard genetic engineering methods. Thus this technology is a very powerful tool that can be used toward securing the world's food supply. In addition to improving the nutritional value of crops, it is the most effective way to produce crops that can resist pests and thrive in tough climates. There are 3 types of modifications produced by genome editing; Type I includes altering a few nucleotides, Type II involves replacing an allele with a pre-existing one and Type III allows for the insertion of new gene(s) in predetermined regions in the genome. Because most genome-editing techniques can leave behind traces of DNA alterations evident in a small number of nucleotides, crops created through gene editing could avoid the stringent regulation procedures commonly associated with GM crop development. For this reason many scientists believe plants improved with the more precise gene editing techniques will be more acceptable to the public than transgenic plants. With genome editing comes the promise of new crops being developed more rapidly with a very low risk of off-target effects. It can be performed in any laboratory with any crop, even those that have complex genomes and are not easily bred using conventional methods. PMID:26930114

Derived crop management data for the LandCarbon Project

USGS Publications Warehouse

Schmidt, Gail; Liu, Shu-Guang; Oeding, Jennifer

2011-01-01

The LandCarbon project is assessing potential carbon pools and greenhouse gas fluxes under various scenarios and land management regimes to provide information to support the formulation of policies governing climate change mitigation, adaptation and land management strategies. The project is unique in that spatially explicit maps of annual land cover and land-use change are created at the 250-meter pixel resolution. The project uses vast amounts of data as input to the models, including satellite, climate, land cover, soil, and land management data. Management data have been obtained from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) and USDA Economic Research Service (ERS) that provides information regarding crop type, crop harvesting, manure, fertilizer, tillage, and cover crop (U.S. Department of Agriculture, 2011a, b, c). The LandCarbon team queried the USDA databases to pull historic crop-related management data relative to the needs of the project. The data obtained was in table form with the County or State Federal Information Processing Standard (FIPS) and the year as the primary and secondary keys. Future projections were generated for the A1B, A2, B1, and B2 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) scenarios using the historic data values along with coefficients generated by the project. The PBL Netherlands Environmental Assessment Agency (PBL) Integrated Model to Assess the Global Environment (IMAGE) modeling framework (Integrated Model to Assess the Global Environment, 2006) was used to develop coefficients for each IPCC SRES scenario, which were applied to the historic management data to produce future land management practice projections. The LandCarbon project developed algorithms for deriving gridded data, using these tabular management data products as input. The derived gridded crop type, crop harvesting, manure, fertilizer, tillage, and cover crop products are used as input to the LandCarbon models to represent the historic and the future scenario management data. The overall algorithm to generate each of the gridded management products is based on the land cover and the derived crop type. For each year in the land cover dataset, the algorithm loops through each 250-meter pixel in the ecoregion. If the current pixel in the land cover dataset is an agriculture pixel, then the crop type is determined. Once the crop type is derived, then the crop harvest, manure, fertilizer, tillage, and cover crop values are derived independently for that crop type. The following is the overall algorithm used for the set of derived grids. The specific algorithm to generate each management dataset is discussed in the respective section for that dataset, along with special data handling and a description of the output product.

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

NASA Astrophysics Data System (ADS)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is well suited for the use of Sentinel-2's continuous and manifold data stream.

Statistical theory and methodology for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Odell, P. L.

1974-01-01

A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.

New insights to lateral rooting: Differential responses to heterogeneous nitrogen availability among maize root types

PubMed Central

Yu, Peng; White, Philip J; Li, Chunjian

2015-01-01

Historical domestication and the "Green revolution" have both contributed to the evolution of modern, high-performance crops. Together with increased irrigation and application of chemical fertilizers, these efforts have generated sufficient food for the growing global population. Root architecture, and in particular root branching, plays an important role in the acquisition of water and nutrients, plant performance, and crop yield. Better understanding of root growth and responses to the belowground environment could contribute to overcoming the challenges faced by agriculture today. Manipulating the abilities of crop root systems to explore and exploit the soil environment could enable plants to make the most of soil resources, increase stress tolerance and improve grain yields, while simultaneously reducing environmental degradation. In this article it is noted that the control of root branching, and the responses of root architecture to nitrate availability, differ between root types and between plant species. Since the control of root branching depends upon both plant species and root type, further work is urgently required to determine the appropriate genes to manipulate to improve resource acquisition by specific crops. PMID:26443081

New insights to lateral rooting: Differential responses to heterogeneous nitrogen availability among maize root types.

PubMed

Yu, Peng; White, Philip J; Li, Chunjian

2015-01-01

Historical domestication and the "Green revolution" have both contributed to the evolution of modern, high-performance crops. Together with increased irrigation and application of chemical fertilizers, these efforts have generated sufficient food for the growing global population. Root architecture, and in particular root branching, plays an important role in the acquisition of water and nutrients, plant performance, and crop yield. Better understanding of root growth and responses to the belowground environment could contribute to overcoming the challenges faced by agriculture today. Manipulating the abilities of crop root systems to explore and exploit the soil environment could enable plants to make the most of soil resources, increase stress tolerance and improve grain yields, while simultaneously reducing environmental degradation. In this article it is noted that the control of root branching, and the responses of root architecture to nitrate availability, differ between root types and between plant species. Since the control of root branching depends upon both plant species and root type, further work is urgently required to determine the appropriate genes to manipulate to improve resource acquisition by specific crops.

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.

Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping

USGS Publications Warehouse

Maxwell, S.K.; Craig, M.E.

2008-01-01

Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

Effect of non-crop vegetation types on conservation biological control of pests in olive groves

PubMed Central

Cayuela, Luis; Gurr, Geoff M.; Campos, Mercedes

2013-01-01

Conservation biological control (CBC) is an environmentally sound potential alternative to the use of chemical insecticides. It involves modifications of the environment to promote natural enemy activity on pests. Despite many CBC studies increasing abundance of natural enemies, there are far fewer demonstrations of reduced pest density and very little work has been conducted in olive crops. In this study we investigated the effects of four forms of non-crop vegetation on the abundance of two important pests: the olive psyllid (Euphyllura olivina) and the olive moth (Prays oleae). Areas of herbaceous vegetation and areas of woody vegetation near olive crops, and smaller patches of woody vegetation within olive groves, decreased pest abundance in the crop. Inter-row ground covers that are known to increase the abundance of some predators and parasitoids had no effect on the pests, possibly as a result of lack of synchrony between pests and natural enemies, lack of specificity or intra-guild predation. This study identifies examples of the right types of diversity for use in conservation biological control in olive production systems. PMID:23904994

Comparing soil functions for a wide range of agriculture soils focusing on production for bioenergy using a combined isotope-based observation and modelling approach

NASA Astrophysics Data System (ADS)

Leistert, Hannes; Herbstritt, Barbara; Weiler, Markus

2017-04-01

Increase crop production for bioenergy will result in changes in land use and the resulting soil functions and may generate new chances and risks. However, detailed data and information are still missing how soil function may be altered under changing crop productions for bioenergy, in particular for a wide range of agricultural soils since most data are currently derived from individual experimental sites studying different bioenergy crops at one location. We developed a new, rapid measurement approach to investigate the influence of bioenergy plants on the water cycle and different soil functions (filter and buffer of water and N-cycling). For this approach, we drilled 89 soil cores (1-3 m deep) in spring and fall at 11 sites with different soil properties and climatic conditions comparing different crops (grass, corn, willow, poplar, and other less common bioenergy crops) and analyzing 1150 soil samples for water content, nitrate concentration and stable water isotopes. We benchmarked a soil hydrological model (1-D numerical Richards equation, ADE, water isotope fractionation including liquid and vapor composition of isotopes) using longer-term climate variables and water isotopes in precipitation to derive crop specific parameterization and to specifically validate the differences in water transport and water partitioning into evaporation, transpiration and groundwater recharge among the sites and crops using the water isotopes in particular. The model simulation were in good agreement with the observed isotope profiles and allowed us to differentiate among the different crops. We defined different indicators for the soil functions considered in this study. These indicators included the proportion of groundwater recharge, transit time of water (different percentiles) though the upper 2m and nutrient leaching potential (e.g. nitrate) during the dormant season from the rooting zone. The parameterized model was first used to calculate the indicators for the sampled locations and to derive the changes in soil functions by altering the land cover among the different bioenergy crops in comparison to the grassland as a reference. We could show that percolation is strongly influenced by the crops and climate, the transit time is influenced by a combination of soil type, climate and land use, but the effect of soil type is very strong and the nitrate leaching is strongly influenced by soil type. The high variability of transit times and nitrate leaching are due to high variability of the temporal distribution of precipitation. Finally, the model was used to regionalized the indicators to a wide range of soils in the state of Baden-Württemberg and to assess if there are locations where bioenergy crops may improve the considered soil function. Our idea behind this was to propose location where specific bioenergy crops may be highly suitable to improve the current soil function to increase for example the protection of groundwater for drinking water, reduce erosion risk or increase water availability. The proposed method allows to assess the influence of different bioenergy crops on soil functions without costly multi-year measurement systems for assessing the soil functions using soil water content measurements or/and soil water suction devices.

Agriculture: Nurseries and Greenhouses

EPA Pesticide Factsheets

Nurseries and Greenhouses. Information about environmental requirements specifically relating to the production of many types of agricultural crops grown in nurseries and greenhouses, such as ornamental plants and specialty fruits and vegetables.

A Data-driven Approach to Integrate Crop Rotation Agronomic Practices in a Global Gridded Land-use Forcing Dataset

NASA Astrophysics Data System (ADS)

Sahajpal, R.; Hurtt, G. C.; Chini, L. P.; Frolking, S. E.; Izaurralde, R. C.

2016-12-01

Agro-ecosystems are the dominant land-use type on Earth, covering more than a third of ice-free land surface. Agricultural practices have influenced the Earth's climate system by significantly altering the biogeophysical and biogeochemical properties from hyper-local to global scales. While past work has focused largely on characterizing the effects of net land cover changes, the magnitude and nature of gross transitions and agricultural management practices on climate remains highly uncertain. To address this issue, a new set of global gridded land-use forcing datasets (LUH2) have been developed in a standard format required by climate models for CMIP6. For the first time, this dataset includes information on key agricultural management practices including crop rotations. Crop rotations describe the practice of growing crops on the same land in sequential seasons and are essential to agronomic management as they influence key ecosystem services such as crop yields, water quality, carbon and nutrient cycling, pest and disease control. Here, we present a data-driven approach to infer crop rotations based on crop specific land cover data, derived from moderate resolution satellite imagery and created at an annual time-step for the continental United States. Our approach compresses the more than 100,000 unique crop rotations prevalent in the United States from 2013 - 2015 to about 200 representative crop rotations that account for nearly 80% of the spatio-temporal variability. Further simplification is achieved by mapping individual crops to crop functional types, which identify crops based on their photosynthetic pathways (C3/C4), life strategy (annual/perennial) and whether they are N-fixing or not. The resulting matrix of annual transitions between crop functional types averages 41,000 km2/yr for rotations between C3 and C4 annual crops, and 140,000 km2/yr between C3 N-fixing and C4 annual crops. The crop rotation matrix is combined with information on other land-use states to compute annual changes between these states, thereby producing a detailed land-use transition information that can help close regional and global carbon budgets. We also validate the quality of the crop rotations identified in our product in countries with agronomic practices different from the United States.

Remote sensing in agriculture. [using Earth Resources Technology Satellite photography

NASA Technical Reports Server (NTRS)

Downs, S. W., Jr.

1974-01-01

Some examples are presented of the use of remote sensing in cultivated crops, forestry, and range management. Areas of concern include: the determination of crop areas and types, prediction of yield, and detection of disease; the determination of forest areas and types, timber volume estimation, detection of insect and disease attack, and forest fires; and the determination of range conditions and inventory, and livestock inventory. Articles in the literature are summarized and specific examples of work being performed at the Marshall Space Flight Center are given. Primarily, aerial photographs and photo-like ERTS images are considered.

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.

Determining the probability of pesticide exposures among migrant farmworkers: results from a feasibility study.

PubMed

Ward, M H; Prince, J R; Stewart, P A; Zahm, S H

2001-11-01

Migrant and seasonal farmworkers are exposed to pesticides through their work with crops and livestock. Because workers are usually unaware of the pesticides applied, specific pesticide exposures cannot be determined by interviews. We conducted a study to determine the feasibility of identifying probable pesticide exposures based on work histories. The study included 162 farm workers in seven states. Interviewers obtained a lifetime work history including the crops, tasks, months, and locations worked. We investigated the availability of survey data on pesticide use for crops and livestock in the seven pilot states. Probabilities of use for pesticide types (herbicides, insecticides, fungicides, etc.) and specific chemicals were calculated from the available data for two farm workers. The work histories were chosen to illustrate how the quality of the pesticide use information varied across crops, states, and years. For most vegetable and fruit crops there were regional pesticide use data in the late 1970s, no data in the 1980s, and state-specific data every other year in the 1990s. Annual use surveys for cotton and potatoes began in the late 1980s. For a few crops, including asparagus, broccoli, lettuce, strawberries, plums, and Christmas trees, there were no federal data or data from the seven states before the 1990s. We conclude that identifying probable pesticide exposures is feasible in some locations. However, the lack of pesticide use data before the 1990s for many crops will limit the quality of historic exposure assessment for most workers. Published 2001 Wiley-Liss, Inc.

Conjecture Regarding Posttranslational Modifications to the Arabidopsis Type I Proton-Pumping Pyrophosphatase (AVP1)

PubMed Central

Pizzio, Gaston A.; Hirschi, Kendal D.; Gaxiola, Roberto A.

2017-01-01

Agbiotechnology uses genetic engineering to improve the output and value of crops. Altering the expression of the plant Type I Proton-pumping Pyrophosphatase (H+-PPase) has already proven to be a useful tool to enhance crop productivity. Despite the effective use of this gene in translational research, information regarding the intracellular localization and functional plasticity of the pump remain largely enigmatic. Using computer modeling several putative phosphorylation, ubiquitination and sumoylation target sites were identified that may regulate Arabidopsis H+-PPase (AVP1- Arabidopsis Vacuolar Proton-pump 1) subcellular trafficking and activity. These putative regulatory sites will direct future research that specifically addresses the partitioning and transport characteristics of this pump. We posit that fine-tuning H+-PPases activity and cellular distribution will facilitate rationale strategies for further genetic improvements in crop productivity. PMID:28955362

Seed fates in crop-wild hybrid sunflower: crop allele and maternal effects.

PubMed

Pace, Brian A; Alexander, Helen M; Emry, Jason D; Mercer, Kristin L

2015-02-01

Domestication has resulted in selection upon seed traits found in wild populations, yet crop-wild hybrids retain some aspects of both parental phenotypes. Seed fates of germination, dormancy, and mortality can influence the success of crop allele introgression in crop-wild hybrid zones, especially if crop alleles or crop-imparted seed coverings result in out-of-season germination. We performed a seed burial experiment using crop, wild, and diverse hybrid sunflower (Helianthus annuus) cross types to test how a cross type's maternal parent and nuclear genetic composition might affect its fate under field conditions. We observed higher maladaptive fall germination in the crop- and F1- produced seeds than wild-produced seeds and, due to an interaction with percent crop alleles, fall germination was higher for cross types with more crop-like nuclear genetics. By spring, crop-produced cross types had the highest overwintering mortality, primarily due to higher fall germination. Early spring germination was identical across maternal types, but germination continued for F1-produced seeds. In conclusion, the more wild-like the maternal parent or the less proportion of the cross type's genome contributed by the crop, the greater likelihood a seed will remain ungerminated than die. Wild-like dormancy may facilitate introgression through future recruitment from the soil seed bank.

Shoot Na+ exclusion and increased salinity tolerance engineered by cell type-specific alteration of Na+ transport in Arabidopsis.

PubMed

Møller, Inge S; Gilliham, Matthew; Jha, Deepa; Mayo, Gwenda M; Roy, Stuart J; Coates, Juliet C; Haseloff, Jim; Tester, Mark

2009-07-01

Soil salinity affects large areas of cultivated land, causing significant reductions in crop yield globally. The Na+ toxicity of many crop plants is correlated with overaccumulation of Na+ in the shoot. We have previously suggested that the engineering of Na+ exclusion from the shoot could be achieved through an alteration of plasma membrane Na+ transport processes in the root, if these alterations were cell type specific. Here, it is shown that expression of the Na+ transporter HKT1;1 in the mature root stele of Arabidopsis thaliana decreases Na+ accumulation in the shoot by 37 to 64%. The expression of HKT1;1 specifically in the mature root stele is achieved using an enhancer trap expression system for specific and strong overexpression. The effect in the shoot is caused by the increased influx, mediated by HKT1;1, of Na+ into stelar root cells, which is demonstrated in planta and leads to a reduction of root-to-shoot transfer of Na+. Plants with reduced shoot Na+ also have increased salinity tolerance. By contrast, plants constitutively expressing HKT1;1 driven by the cauliflower mosaic virus 35S promoter accumulated high shoot Na+ and grew poorly. Our results demonstrate that the modification of a specific Na+ transport process in specific cell types can reduce shoot Na+ accumulation, an important component of salinity tolerance of many higher plants.

A 5-year analysis of crop phenologies from the United States Heartland (Invited)

NASA Astrophysics Data System (ADS)

Johnson, D. M.

2010-12-01

Time series imagery data from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) was intersected with annually updated field-level crop data from the United States Department of Agriculture (USDA) Farm Service Agency (FSA). Phenological metrics were derived for major crop types found in the United States (US) Heartland region. The specific MODIS data consisted of the 16-day composited Normalized Difference Vegetation Index (NDVI) 250 meter spatial resolution imagery from the Terra satellite. Crops evaluated included corn, soybeans, wheat, cotton, sorghum, rice, and other small grains. Charts showing the annual average state-level NDVI phenologies by crop were constructed for the five years between 2006 and 2010. The states of interest covered the intensively cultivated regions in the US Great Plains, Corn Belt, and Mississippi River Alluvial Plain. Results demonstrated the recent biophysical growth cycles of prevalent and widespread US crops and how they varied by geography and year. Linkages between the time series data and planting practices, weather impacts, crop progress reports, and yields were also investigated.

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.

Satellite Based Cropland Carbon Monitoring System

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Disaggregated N2O emission factors in China based on cropping parameters create a robust approach to the IPCC Tier 2 methodology

PubMed Central

Shepherd, Anita; Yan, Xiaoyuan; Nayak, Dali; Newbold, Jamie; Moran, Dominic; Dhanoa, Mewa Singh; Goulding, Keith; Smith, Pete; Cardenas, Laura M.

2015-01-01

China accounts for a third of global nitrogen fertilizer consumption. Under an International Panel on Climate Change (IPCC) Tier 2 assessment, emission factors (EFs) are developed for the major crop types using country-specific data. IPCC advises a separate calculation for the direct nitrous oxide (N2O) emissions of rice cultivation from that of cropland and the consideration of the water regime used for irrigation. In this paper we combine these requirements in two independent analyses, using different data quality acceptance thresholds, to determine the influential parameters on emissions with which to disaggregate and create N2O EFs. Across China, the N2O EF for lowland horticulture was slightly higher (between 0.74% and 1.26% of fertilizer applied) than that for upland crops (values ranging between 0.40% and 1.54%), and significantly higher than for rice (values ranging between 0.29% and 0.66% on temporarily drained soils, and between 0.15% and 0.37% on un-drained soils). Higher EFs for rice were associated with longer periods of drained soil and the use of compound fertilizer; lower emissions were associated with the use of urea or acid soils. Higher EFs for upland crops were associated with clay soil, compound fertilizer or maize crops; lower EFs were associated with sandy soil and the use of urea. Variation in emissions for lowland vegetable crops was closely associated with crop type. The two independent analyses in this study produced consistent disaggregated N2O EFs for rice and mixed crops, showing that the use of influential cropping parameters can produce robust EFs for China. PMID:26865831

Disaggregated N2O emission factors in China based on cropping parameters create a robust approach to the IPCC Tier 2 methodology

NASA Astrophysics Data System (ADS)

Shepherd, Anita; Yan, Xiaoyuan; Nayak, Dali; Newbold, Jamie; Moran, Dominic; Dhanoa, Mewa Singh; Goulding, Keith; Smith, Pete; Cardenas, Laura M.

2015-12-01

China accounts for a third of global nitrogen fertilizer consumption. Under an International Panel on Climate Change (IPCC) Tier 2 assessment, emission factors (EFs) are developed for the major crop types using country-specific data. IPCC advises a separate calculation for the direct nitrous oxide (N2O) emissions of rice cultivation from that of cropland and the consideration of the water regime used for irrigation. In this paper we combine these requirements in two independent analyses, using different data quality acceptance thresholds, to determine the influential parameters on emissions with which to disaggregate and create N2O EFs. Across China, the N2O EF for lowland horticulture was slightly higher (between 0.74% and 1.26% of fertilizer applied) than that for upland crops (values ranging between 0.40% and 1.54%), and significantly higher than for rice (values ranging between 0.29% and 0.66% on temporarily drained soils, and between 0.15% and 0.37% on un-drained soils). Higher EFs for rice were associated with longer periods of drained soil and the use of compound fertilizer; lower emissions were associated with the use of urea or acid soils. Higher EFs for upland crops were associated with clay soil, compound fertilizer or maize crops; lower EFs were associated with sandy soil and the use of urea. Variation in emissions for lowland vegetable crops was closely associated with crop type. The two independent analyses in this study produced consistent disaggregated N2O EFs for rice and mixed crops, showing that the use of influential cropping parameters can produce robust EFs for China.

Identifying obstacles and ranking common biological control research priorities for Europe to manage most economically important pests in arable, vegetable and perennial crops.

PubMed

Lamichhane, Jay Ram; Bischoff-Schaefer, Monika; Bluemel, Sylvia; Dachbrodt-Saaydeh, Silke; Dreux, Laure; Jansen, Jean-Pierre; Kiss, Jozsef; Köhl, Jürgen; Kudsk, Per; Malausa, Thibaut; Messéan, Antoine; Nicot, Philippe C; Ricci, Pierre; Thibierge, Jérôme; Villeneuve, François

2017-01-01

EU agriculture is currently in transition from conventional crop protection to integrated pest management (IPM). Because biocontrol is a key component of IPM, many European countries recently have intensified their national efforts on biocontrol research and innovation (R&I), although such initiatives are often fragmented. The operational outputs of national efforts would benefit from closer collaboration among stakeholders via transnationally coordinated approaches, as most economically important pests are similar across Europe. This paper proposes a common European framework on biocontrol R&I. It identifies generic R&I bottlenecks and needs as well as priorities for three crop types (arable, vegetable and perennial crops). The existing gap between the market offers of biocontrol solutions and the demand of growers, the lengthy and expensive registration process for biocontrol solutions and their varying effectiveness due to variable climatic conditions and site-specific factors across Europe are key obstacles hindering the development and adoption of biocontrol solutions in Europe. Considering arable, vegetable and perennial crops, a dozen common target pests are identified for each type of crop and ranked by order of importance at European level. Such a ranked list indicates numerous topics on which future joint transnational efforts would be justified. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Global Estimates of Trace Gas Fluxes Affected by Land Use Change and Irrigation of Major Crops

NASA Astrophysics Data System (ADS)

Ojima, D. S.; del Grosso, S.; Parton, W. J.; Keough, C.

2005-12-01

Cropland conversions have altered many fertile regions of the earth and have modified the biogeochemical and hydrological cycling in these regions. These croplands are significant sources of N trace gas emissions however, the extent of changing trace gas emission due to land management changes and irrigation need further analysis. We use the DAYCENT biogeochemical model which is a daily time step version of the CENTURY model. DAYCENT simulates fluxes of N2O between croplands and the atmosphere for major crop types, and allows for a dynamic representation of GHG fluxes that accounts for environmental conditions, soil characteristics, climate, specific crop qualities, and fertilizer and irrigation management practices. DAYCENT is applied to all world cropland regions. Global datasets of weather, soils, native vegetation and cropping fractions were mapped to an approximate 2° x 2° resolution. Non-spatial data (such as planting date and fertilizer application rates) were assigned as point values for each region (i.e. country), and were assumed to be similar within crop types across the region. Three major crops were simulated (corn, wheat and soybeans) under both irrigated and non-irrigated conditions. Results indicate that N2O emission for maize and soy bean increase between 3 to 10%, where as wheat emission decline by about 1% when irrigated systems are compared to non-irrigated systems.

GEOGLAM Crop Assessment Tool: Adapting from global agricultural monitoring to food security monitoring

NASA Astrophysics Data System (ADS)

Humber, M. L.; Becker-Reshef, I.; Nordling, J.; Barker, B.; McGaughey, K.

2014-12-01

The GEOGLAM Crop Monitor's Crop Assessment Tool was released in August 2013 in support of the GEOGLAM Crop Monitor's objective to develop transparent, timely crop condition assessments in primary agricultural production areas, highlighting potential hotspots of stress/bumper crops. The Crop Assessment Tool allows users to view satellite derived products, best available crop masks, and crop calendars (created in collaboration with GEOGLAM Crop Monitor partners), then in turn submit crop assessment entries detailing the crop's condition, drivers, impacts, trends, and other information. Although the Crop Assessment Tool was originally intended to collect data on major crop production at the global scale, the types of data collected are also relevant to the food security and rangelands monitoring communities. In line with the GEOGLAM Countries at Risk philosophy of "foster[ing] the coordination of product delivery and capacity building efforts for national and regional organizations, and the development of harmonized methods and tools", a modified version of the Crop Assessment Tool is being developed for the USAID Famine Early Warning Systems Network (FEWS NET). As a member of the Countries at Risk component of GEOGLAM, FEWS NET provides agricultural monitoring, timely food security assessments, and early warnings of potential significant food shortages focusing specifically on countries at risk of food security emergencies. While the FEWS NET adaptation of the Crop Assessment Tool focuses on crop production in the context of food security rather than large scale production, the data collected is nearly identical to the data collected by the Crop Monitor. If combined, the countries monitored by FEWS NET and GEOGLAM Crop Monitor would encompass over 90 countries representing the most important regions for crop production and food security.

Managing soil microbial communities in grain production systems through cropping practices

NASA Astrophysics Data System (ADS)

Gupta, Vadakattu

2013-04-01

Cropping practices can significantly influence the composition and activity of soil microbial communities with consequences to plant growth and production. Plant type can affect functional capacity of different groups of biota in the soil surrounding their roots, rhizosphere, influencing plant nutrition, beneficial symbioses, pests and diseases and overall plant health and crop production. The interaction between different players in the rhizosphere is due to the plethora of carbon and nutritional compounds, root-specific chemical signals and growth regulators that originate from the plant and are modulated by the physico-chemical properties of soils. A number of plant and environmental factors and management practices can influence the quantity and quality of rhizodeposition and in turn affect the composition of rhizosphere biota communities, microbe-fauna interactions and biological processes. Some of the examples of rhizosphere interactions that are currently considered important are: proliferation of plant and variety specific genera or groups of microbiota, induction of genes involved in symbiosis and virulence, promoter activity in biocontrol agents and genes correlated with root adhesion and border cell quality and quantity. The observation of variety-based differences in rhizodeposition and associated changes in rhizosphere microbial diversity and function suggests the possibility for the development of varieties with specific root-microbe interactions targeted for soil type and environment i.e. designer rhizospheres. Spatial location of microorganisms in the heterogeneous field soil matrix can have significant impacts on biological processes. Therefore, for rhizosphere research to be effective in variable seasonal climate and soil conditions, it must be evaluated in the field and within a farming systems context. With the current focus on security of food to feed the growing global populations through sustainable agricultural production systems there is a need to develop innovative cropping systems that are both economically and environmentally sustainable.

Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

NASA Technical Reports Server (NTRS)

Stoner, E. R.

1982-01-01

The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

First attempts to obtain a reference drift curve for traditional olive grove's plantations following ISO 22866.

PubMed

Gil, Emilio; Llorens, Jordi; Gallart, Montserrat; Gil-Ribes, Jesús A; Miranda-Fuentes, Antonio

2018-06-15

The current standard for the field measurements of spray drift (ISO 22866) is the only official standard for drift measurements in field conditions for all type of crops, including bushes and trees. A series of field trials following all the requirements established in the standard were arranged in a traditional olive grove in Córdoba (south of Spain). The aims of the study were to evaluate the applicability of the current standard procedure to the particular conditions of traditional olive trees plantations, to evaluate the critical requirements for performing the tests and to obtain a specific drift curve for such as important and specific crop as olive trees in traditional plantations, considering the enormous area covered by this type of crop all around the world. Results showed that the field trials incur a very complex process due to the particular conditions of the crop and the very precise environmental requirements. Furthermore, the trials offered a very low level of repeatability as the drift values varied significantly from one spray application to the next, with the obtained results being closely related to the wind speed, even when considering the standard minimum value of 1 m·s -1 . The collector's placement with respect to the position of the isolated trees was determined as being critical since this substantially modifies the ground deposit in the first 5 m. Even though, a new drift curve for olive trees in traditional plantation has been defined, giving an interesting tool for regulatory aspects. Conclusions indicated that a deep review of the official standard is needed to allow its application to the most relevant orchard/fruit crops. Copyright © 2018 Elsevier B.V. All rights reserved.

Phenology satellite experiment

NASA Technical Reports Server (NTRS)

Dethier, B. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The detection of a phenological event (the Brown Wave-vegetation sensescence) for specific forest and crop types using ERTS-1 imagery is described. Data handling techniques including computer analysis and photointerpretation procedures are explained. Computer analysis of multspectral scanner digital tapes in all bands was used to give the relative changes of spectral reflectance with time of forests and specified crops. These data were obtained for a number of the twenty-four sites located within four north-south corridors across the United States. Analysis of ground observation photography and ERTS-1 imagery for sites in the Appalachian Corridor and Mississippi Valley Corridor indicates that the recession of vegetation development can be detected very well. Tentative conclusions are that specific phenological events such as crop maturity or leaf fall can be mapped for specific sites and possible for different regions. Preliminary analysis based on a number of samples in mixed deciduous hardwood stands indicates that as senescence proceeds both the rate of change and differences in color among species can be detected. The results to data show the feasibility of the development and refinement of phenoclimatic models.

Efficient crop type mapping based on remote sensing in the Central Valley, California

NASA Astrophysics Data System (ADS)

Zhong, Liheng

Most agricultural systems in California's Central Valley are purposely flexible and intentionally designed to meet the demands of dynamic markets. Agricultural land use is also impacted by climate change and urban development. As a result, crops change annually and semiannually, which makes estimating agricultural water use difficult, especially given the existing method by which agricultural land use is identified and mapped. A minor portion of agricultural land is surveyed annually for land-use type, and every 5 to 8 years the entire valley is completely evaluated. So far no effort has been made to effectively and efficiently identify specific crop types on an annual basis in this area. The potential of satellite imagery to map agricultural land cover and estimate water usage in the Central Valley is explored. Efforts are made to minimize the cost and reduce the time of production during the mapping process. The land use change analysis shows that a remote sensing based mapping method is the only means to map the frequent change of major crop types. The traditional maximum likelihood classification approach is first utilized to map crop types to test the classification capacity of existing algorithms. High accuracy is achieved with sufficient ground truth data for training, and crop maps of moderate quality can be timely produced to facilitate a near-real-time water use estimate. However, the large set of ground truth data required by this method results in high costs in data collection. It is difficult to reduce the cost because a trained classification algorithm is not transferable between different years or different regions. A phenology based classification (PBC) approach is developed which extracts phenological metrics from annual vegetation index profiles and identifies crop types based on these metrics using decision trees. According to the comparison with traditional maximum likelihood classification, this phenology-based approach shows great advantages when the size of the training set is limited by ground truth availability. Once developed, the classifier is able to be applied to different years and a vast area with only a few adjustments according to local agricultural and annual weather conditions. 250 m MODIS imagery is utilized as the main input to the PBC algorithm and displays promising capacity in crop identification in several counties in the Central Valley. A time series of Landsat TM/ETM+ images at a 30 m resolution is necessary in the crop mapping of counties with smaller land parcels, although the processing time is longer. Spectral characteristics are also employed to identify crops in PBC. Spectral signatures are associated with phenological stages instead of imaging dates, which highly increases the stability of the classifier performance and overcomes the problem of over-fitting. Moderate accuracies are achieved by PBC, with confusions mostly within the same crop categories. Based on a quantitative analysis, misclassification in PBC has very trivial impacts on the accuracy of agricultural water use estimate. The cost of the entire PBC procedure is controlled to a very low level, which will enable its usage in routine annual crop mapping in the Central Valley.

Profiling agricultural land cover change in the North Central U.S. using ten years of the Cropland Data Layer

NASA Astrophysics Data System (ADS)

Sandborn, A.; Ebinger, L.

2016-12-01

The Cropland Data Layer (CDL), produced by the USDA/National Agricultural Statistics Service, provides annual, georeferenced crop specific land cover data over the contiguous United States. Several analyses were performed on ten years (2007-2016) of CDL data in order to visualize and quantify agricultural change over the North Central region (North Dakota, South Dakota, and Minnesota). Crop masks were derived from the CDL and layered to produce a ten-year time stack of corn, soybeans, and spring wheat at 30m spatial resolution. Through numerous image analyses, a temporal profile of each crop type was compiled and portrayed cartographically. For each crop, analyses included calculating the mean center of crop area over the ten year sequence, identifying the first and latest year the crop was grown on each pixel, and distinguishing crop rotation patterns and replacement statistics. Results show a clear north-western expansion trend for corn and soybeans, and a western migration trend for spring wheat. While some change may be due to commonly practiced crop rotation, this analysis shows that crop footprints have extended into areas that were previously other crops, idle cropland, and pasture/rangeland. Possible factors contributing to this crop migration pattern include profit advantages of row crops over small grains, improved crop genetics, climate change, and farm management program changes. Identifying and mapping these crop planting differences will better inform agricultural best practices, help to monitor the latest crop migration patterns, and present researchers with a way to quantitatively measure and forecast future agricultural trends.

Geology and Our Environment. Environmental Education Curriculum. Revised.

ERIC Educational Resources Information Center

Topeka Public Schools, KS.

Rocks, and the soil formed from rock, play a major role in determining such particulars as the type of crops that can be grown in a specific area and the type of housing that can be constructed. Also, rocks may supply fuel and building materials, and provide information about the history of an area. This unit is constructed to expose secondary…

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

USGS Publications Warehouse

Lokupitiya, E.; Denning, A. Scott; Schaefer, K.; Ricciuto, D.; Anderson, R.; Arain, M. A.; Baker, I.; Barr, A. G.; Chen, G.; Chen, J.M.; Ciais, P.; Cook, D.R.; Dietze, M.C.; El Maayar, M.; Fischer, M.; Grant, R.; Hollinger, D.; Izaurralde, C.; Jain, A.; Kucharik, C.J.; Li, Z.; Liu, S.; Li, L.; Matamala, R.; Peylin, P.; Price, D.; Running, S. W.; Sahoo, A.; Sprintsin, M.; Suyker, A.E.; Tian, H.; Tonitto, Christina; Torn, M.S.; Verbeeck, Hans; Verma, S.B.; Xue, Y.

2016-01-01

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

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

Lokupitiya, E.; Denning, A. S.; Schaefer, K.

2016-06-03

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fedmore » sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO 2 seasonal uptake over agricultural regions.« less

Germany wide seasonal flood risk analysis for agricultural crops

NASA Astrophysics Data System (ADS)

Klaus, Stefan; Kreibich, Heidi; Kuhlmann, Bernd; Merz, Bruno; Schröter, Kai

2016-04-01

In recent years, large-scale flood risk analysis and mapping has gained attention. Regional to national risk assessments are needed, for example, for national risk policy developments, for large-scale disaster management planning and in the (re-)insurance industry. Despite increasing requests for comprehensive risk assessments some sectors have not received much scientific attention, one of these is the agricultural sector. In contrast to other sectors, agricultural crop losses depend strongly on the season. Also flood probability shows seasonal variation. Thus, the temporal superposition of high flood susceptibility of crops and high flood probability plays an important role for agricultural flood risk. To investigate this interrelation and provide a large-scale overview of agricultural flood risk in Germany, an agricultural crop loss model is used for crop susceptibility analyses and Germany wide seasonal flood-frequency analyses are undertaken to derive seasonal flood patterns. As a result, a Germany wide map of agricultural flood risk is shown as well as the crop type most at risk in a specific region. The risk maps may provide guidance for federal state-wide coordinated designation of retention areas.

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.

Agricultural Adaptations to Climate Changes in West Africa

NASA Astrophysics Data System (ADS)

Guan, K.; Sultan, B.; Lobell, D. B.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.

2014-12-01

Agricultural production in West Africa is highly vulnerable to climate variability and change and a fast growing demand for food adds yet another challenge. Assessing possible adaptation strategies of crop production in West Africa under climate change is thus critical for ensuring regional food security and improving human welfare. Our previous efforts have identified as the main features of climate change in West Africa a robust increase in temperature and a complex shift in the rainfall pattern (i.e. seasonality delay and total amount change). Unaddressed, these robust climate changes would reduce regional crop production by up to 20%. In the current work, we use two well-validated crop models (APSIM and SARRA-H) to comprehensively assess different crop adaptation options under future climate scenarios. Particularly, we assess adaptations in both the choice of crop types and management strategies. The expected outcome of this study is to provide West Africa with region-specific adaptation recommendations that take into account both climate variability and climate change.

A spatially-explicit data driven approach to assess the effect of agricultural land occupation on species groups

NASA Astrophysics Data System (ADS)

Elshout, P.; van Zelm, R.; Karuppiah, R.; Laurenzi, I.; Huijbregts, M.

2013-12-01

Change of vegetation cover and increased land use intensity can directly affect the natural habitat and the wildlife it houses. The actual impact of agricultural land use is region specific as crops are grown under various climatic conditions and ways of cultivation and refining. Furthermore, growing a specific crop in a tropical region may require clearance of rainforest while the same crop may replace natural grasslands in temperate regions. Within life cycle impact assessment (LCIA), methods to address impacts of land use on a global scale are still in need of development. We aim to extend existing methods to improve the robustness of LCIA by allowing spatial differentiation of agricultural land use impacts. The goal of this study is to develop characterization factors for the direct impact of land use on biodiversity, which results from the replacement of natural habitat with farmland. The characterization factor expresses the change in species richness under crop cultivation compared to the species richness in the natural situation over a certain area. A second goal was to identify the differences in impacts caused by cultivation of different crop types, sensitivity of different taxonomic groups, and differences in natural land cover. Empirical data on species richness were collected from literature for both natural reference situations and agricultural land use situations. Reference situations were selected on an ecoregion or biome basis. We calculated characterization factors for four crop groups (oil palm, low crops, cereals, and perennial grasses), four species groups (arthropods, birds, mammals, vascular plants), and six biomes.

Energy requirements in pressure irrigation systems

NASA Astrophysics Data System (ADS)

Sánchez, R.; Rodríguez-Sinobas, L.; Juana, L.; Laguna, F. V.; Castañón, G.; Gil, M.; Benítez, J.

2012-04-01

Modernization of irrigation schemes, generally understood as transformation of surface irrigation systems into pressure -sprinkler and trickle- irrigation systems, aims at, among others, improving irrigation efficiency and reduction of operation and maintenance efforts made by the irrigators. However, pressure irrigation systems, in contrast, carry a serious energy cost. Energy requirements depend on decisions taken on management strategies during the operation phase, which are conditioned by previous decisions taken on the design project of the different elements which compose the irrigation system. Most of the countries where irrigation activity is significant bear in mind that modernization irrigation must play a key role in the agricultural infrastructure policies. The objective of this study is to characterize and estimate the mean and variation of the energy consumed by common types of irrigation systems and their management possibilities. The work includes all processes involved from the diversion of water into irrigation specific infrastructure to water discharge by the emitters installed on the crop fields. Simulation taking into account all elements comprising the irrigation system has been used to estimate the energy requirements of typical irrigation systems of several crop production systems. It has been applied to extensive and intensive crop systems, such us extensive winter crops, summer crops and olive trees, fruit trees and vineyards and intensive horticulture in greenhouses. The simulation of various types of irrigation systems and management strategies, in the framework imposed by particular cropping systems, would help to develop criteria for improving the energy balance in relation to the irrigation water supply productivity.

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.

Tracing crop-specific sediment sources in agricultural catchments

NASA Astrophysics Data System (ADS)

Blake, William H.; Ficken, Katherine J.; Taylor, Philip; Russell, Mark A.; Walling, Desmond E.

2012-02-01

A Compound Specific Stable Isotope (CSSI) sediment tracing approach is evaluated for the first time in an agricultural catchment setting against established geochemical fingerprinting techniques. The work demonstrates that novel CSSI techniques have the potential to provide important support for soil resource management policies and inform sediment risk assessment for the protection of aquatic habitats and water resources. Analysis of soil material from a range of crop covers in a mixed land-use agricultural catchment shows that the carbon CSSI signatures of particle-reactive fatty acids label surface agricultural soil with distinct crop-specific signatures, thus permitting sediment eroded from each land-cover to be tracked downstream. High resolution sediment sampling during a storm event and analysis for CSSI and conventional geochemical fingerprints elucidated temporal patterns of sediment mobilisation under different crop regimes and the specific contribution that each crop type makes to downstream sediment load. Pasture sources (65% of the catchment area) dominated the sediment load but areal yield (0.13 ± 0.02 t ha - 1 ) was considerably less than that for winter wheat (0.44 ± 0.15 t ha - 1 ). While temporal patterns in crop response matched runoff and erosion response predictions based on plot-scale rainfall simulation experiments, comparison of biomarker and geochemical fingerprinting data indicated that the latter overestimated cultivated land inputs to catchment sediment yield due to inability to discriminate temporary pasture (in rotation) from cultivated land. This discrepancy, however, presents an opportunity since combination of the two datasets revealed the extremely localised nature of erosion from permanent pasture fields in this system (estimated at up to 0.5 t ha - 1 ). The novel use of CSSI and geochemical tracers in tandem provided unique insights into sediment source dynamics that could not have been derived from each method alone. Research into CSSI signature development (plant and soil processes) and the influence of cultivation regimes are required to support future development of this new tool.

Global crop production forecasting: An analysis of the data system problems and their solutions

NASA Technical Reports Server (NTRS)

Neiers, J.; Graf, H.

1978-01-01

Data related problems in the acquisition and use of satellite data necessary for operational forecasting of global crop production are considered for the purpose of establishing a measurable baseline. For data acquisition the world was divided into 37 crop regions in 22 countries. These regions represent approximately 95 percent of the total world production of the selected crops of interest, i.e., wheat, corn, soybeans, and rice. Targets were assigned to each region. Limited time periods during which data could be taken (windows) were assigned to each target. Each target was assigned to a cloud region. The DSDS was used to measure the success of obtaining data for each target during the specified windows for the regional cloud conditions and the specific alternatives being analyzed. The results of this study suggest several approaches for an operational system that will perform satisfactorily with two LANDSAT type satellites.

Modeling landscape evapotranspiration by integrating land surface phenology and a water balance algorithm

USGS Publications Warehouse

Senay, Gabriel B.

2008-01-01

The main objective of this study is to present an improved modeling technique called Vegetation ET (VegET) that integrates commonly used water balance algorithms with remotely sensed Land Surface Phenology (LSP) parameter to conduct operational vegetation water balance modeling of rainfed systems at the LSP’s spatial scale using readily available global data sets. Evaluation of the VegET model was conducted using Flux Tower data and two-year simulation for the conterminous US. The VegET model is capable of estimating actual evapotranspiration (ETa) of rainfed crops and other vegetation types at the spatial resolution of the LSP on a daily basis, replacing the need to estimate crop- and region-specific crop coefficients.

Monterey Bay study. [analysis of Landsat 1 multispectral band scanner data

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Wade, L. C.

1975-01-01

The multispectral scanner capabilities of LANDSAT 1 were tested over California's Monterey Bay area and portions of the San Joaquin Valley. Using both computer aided and image interpretive processing techniques, the LANDSAT 1 data were analyzed to determine their potential application in terms of land use and agriculture. Utilizing LANDSAT 1 data, analysts were able to provide the identifications and areal extent of the individual land use categories ranging from very general to highly specific levels (e.g., from agricultural lands to specific field crop types and even the different stages of growth). It is shown that the LANDSAT system is useful in the identification of major crop species and the delineation of numerous land use categories on a global basis and that repeated surveillance would permit the monitoring of changes in seasonal growth characteristics of crops as well as the assessment of various cultivation practices with a minimum of onsite observation. The LANDSAT system is demonstrated to be useful in the planning and development of resource programs on earth.

Interaction of soil pH and phosphorus efficacy: Long-term effects of P fertilizer and lime applications on wheat, barley, and sugar beet.

PubMed

von Tucher, Sabine; Hörndl, Dorothea; Schmidhalter, Urs

2018-01-01

Phosphorus (P), a plant macronutrient, must be adequately supplied for crop growth. In Germany, many soils are high in plant-available P; specifically in arable farming, P fertilizer application has been reduced or even omitted in the last decade. Therefore, it is important to understand how long these soils can support sustainable crop production, and what concentrations of soil P are required for it. We analyzed a 36-year long-term field experiment regarding the effects of different P application and liming rates on plant growth and soil P concentrations with a crop rotation of sugar beet, wheat, and barley. Sugar beet reacted to low soil P and low soil pH levels more sensitively than wheat, which was not significantly affected by the long-term omitted P application. All three crop species showed adequate growth at soil P levels lower than the currently recommended levels, if low soil pH was optimized by liming. The increase in efficacy of soil and fertilizer P by reduced P application rates therefore requires the adaptation of the soil pH to a soil type-specific optimal level.

Effects of Nitrogen Fixing Pre-Crops and Fertilizers on Physical and Chemical Properties Down the Soil Profile

NASA Astrophysics Data System (ADS)

Hobley, E.; Honermeier, B.; Don, A.; Gocke, M. I.; Amelung, W.; Kogel-Knabner, I.

2016-12-01

We investigated the effects of pre-crops with and without biological nitrogen fixation capacity (fava beans, clover mulch, fodder maize) and fertilization (no fertilizer, NPK fertilizer, PK fertilizer) on soil physico-chemical properties (bulk density, electrical conductivity, soil organic carbon (SOC) concentration and stocks, N concentration and stocks) and their depth distribution (down to 1 m) at a long-term field experiment set up in 1982 in Gießen, Germany. Fertilization had significant but small impacts on the soil chemical environment, most particularly the salt content of the soil, with PK fertilization increasing electrical conductivity throughout the soil profile. Similarly, fertilization resulted in a small reduction of soil pH throughout the entire soil profile. The soil was physically and chemically affected by the type of pre-crop. Plots with fava beans and maize had lower bulk densities in the subsoil than those with clover. Pre-crop type also significantly affected the depth distribution of both N and SOC. Specifically, clover pre-cropping led to an enrichment of N at the surface compared with fava beans and maize. SOC enrichment at the surface was also observed under clover, with the effect most pronounced under PK fertilization. Combined with the bulk density effects, this shift in N distribution resulted in significantly higher N stocks under clover than under fava beans. However, the total stocks of SOC were not affected by pre-crop or fertilizer regime. Our results indicate that humans influence C and N cycling and distribution in soils through the selection of pre-crops and that the influence of crop type is greater than that of fertilization regimes. Pre-cropping with clover, which is used as a mulch, leads to N enrichment in the topsoil, reducing the need for N fertilizer for the subsequent cereal crop. In contrast, the use of fava beans as a pre-crop does not lead to N enrichment. We believe this is due to the greater rooting depth of fava beans compared with clover, resulting in lower bulk density in the subsoil and associated lower stocks. Additionally, the harvest of fava beans removes N-rich biomass from the soil, lowering N-input. Lastly, the uptake of water at depth may facilitate subsoil N uptake, so that fava bean N is utilized by the cereal crop but does not lead to its enrichment in the subsoil.

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

From forest to farm: systematic review of cultivar feeding by chimpanzees--management implications for wildlife in anthropogenic landscapes.

PubMed

Hockings, Kimberley J; McLennan, Matthew R

2012-01-01

Crop-raiding is a major source of conflict between people and wildlife globally, impacting local livelihoods and impeding conservation. Conflict mitigation strategies that target problematic wildlife behaviours such as crop-raiding are notoriously difficult to develop for large-bodied, cognitively complex species. Many crop-raiders are generalist feeders. In more ecologically specialised species crop-type selection is not random and evidence-based management requires a good understanding of species' ecology and crop feeding habits. Comprehensive species-wide studies of crop consumption by endangered wildlife are lacking but are important for managing human-wildlife conflict. We conducted a comprehensive literature search of crop feeding records by wild chimpanzees (Pan troglodytes), a ripe-fruit specialist. We assessed quantitatively patterns of crop selection in relation to species-specific feeding behaviour, agricultural exposure, and crop availability. Crop consumption by chimpanzees is widespread in tropical Africa. Chimpanzees were recorded to eat a considerable range of cultivars (51 plant parts from 36 species). Crop part selection reflected a species-typical preference for fruit. Crops widely distributed in chimpanzee range countries were eaten at more sites than sparsely distributed crops. We identified 'high' and 'low' conflict crops according to their attractiveness to chimpanzees, taking account of their importance as cash crops and/or staple foods to people. Most (86%) high conflict crops were fruits, compared to 13% of low conflict crops. Some widely farmed cash or staple crops were seldom or never eaten by chimpanzees. Information about which crops are most frequently consumed and which are ignored has enormous potential for aiding on-the-ground stakeholders (i.e. farmers, wildlife managers, and conservation and agricultural extension practitioners) develop sustainable wildlife management schemes for ecologically specialised and protected species in anthropogenic habitats. However, the economic and subsistence needs of local people, and the crop-raiding behaviour of sympatric wildlife, must be considered when assessing suitability of particular crops for conflict prevention and mitigation.

Changes in water budgets and sediment yields from a hypothetical agricultural field as a function of landscape and management characteristics--A unit field modeling approach

USGS Publications Warehouse

Roth, Jason L.; Capel, Paul D.

2012-01-01

Crop agriculture occupies 13 percent of the conterminous United States. Agricultural management practices, such as crop and tillage types, affect the hydrologic flow paths through the landscape. Some agricultural practices, such as drainage and irrigation, create entirely new hydrologic flow paths upon the landscapes where they are implemented. These hydrologic changes can affect the magnitude and partitioning of water budgets and sediment erosion. Given the wide degree of variability amongst agricultural settings, changes in the magnitudes of hydrologic flow paths and sediment erosion induced by agricultural management practices commonly are difficult to characterize, quantify, and compare using only field observations. The Water Erosion Prediction Project (WEPP) model was used to simulate two landscape characteristics (slope and soil texture) and three agricultural management practices (land cover/crop type, tillage type, and selected agricultural land management practices) to evaluate their effects on the water budgets of and sediment yield from agricultural lands. An array of sixty-eight 60-year simulations were run, each representing a distinct natural or agricultural scenario with various slopes, soil textures, crop or land cover types, tillage types, and select agricultural management practices on an isolated 16.2-hectare field. Simulations were made to represent two common agricultural climate regimes: arid with sprinkler irrigation and humid. These climate regimes were constructed with actual climate and irrigation data. The results of these simulations demonstrate the magnitudes of potential changes in water budgets and sediment yields from lands as a result of landscape characteristics and agricultural practices adopted on them. These simulations showed that variations in landscape characteristics, such as slope and soil type, had appreciable effects on water budgets and sediment yields. As slopes increased, sediment yields increased in both the arid and humid environments. However, runoff did not increase with slope in the arid environment as was observed in the humid environment. In both environments, clayey soils exhibited the greatest amount of runoff and sediment yields while sandy soils had greater recharge and lessor runoff and sediment yield. Scenarios simulating the effects of the timing and type of tillage practice showed that no-till, conservation, and contouring tillages reduced sediment yields and, with the exception of no-till, runoff in both environments. Changes in land cover and crop type simulated the changes between the evapotransporative potential and surface roughness imparted by specific vegetations. Substantial differences in water budgets and sediment yields were observed between most agricultural crops and the natural covers selected for each environment: scrub and prairie grass for the arid environment and forest and prairie grass for the humid environment. Finally, a group of simulations was performed to model selected agricultural management practices. Among the selected practices subsurface drainage and strip cropping exhibited the largest shifts in water budgets and sediment yields. The practice of crop rotation (corn/soybean) and cover cropping (corn/rye) were predicted to increase sediment yields from a field planted as conventional corn.

EnviroAtlas - Synthetic N fertilizer application to agricultural lands by 12-digit HUC in the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean synthetic nitrogen (N) fertilizer application to cultivated crop and hay/pasture lands per 12-digit Hydrologic Unit (HUC) in 2006. Synthetic N fertilizer inputs in 2006 were estimated using county-level estimates of farm N fertilizer inputs. We acquired county-level data describing total farm-level inputs (kg N/yr) of synthetic N fertilizer to individual counties in 2006 from the United States Geological Survey (USGS) (http://pubs.usgs.gov/sir/2012/5207/). These data were converted to per area rates (kg N/ha/yr) of synthetic N fertilizer application by dividing the total N input by the land area (ha) of combined cultivated crop and hay/pasture lands within a county as determined from county-level (http://cta.ornl.gov/transnet/Boundaries.html) summarization of the 2006 National Land Cover Database (NLCD; http://www.mrlc.gov/nlcd06_data.php). We distributed county-specific, annual per area N inputs rates (kg N/ha/yr) to cultivated crop and hay/pasture lands (30 x 30 m pixels) within the corresponding county using the raster calculator tool in ArcMap 10.0 (ESRI, Inc., Redlands, CA). Fertilizer data described here represent an average input to a typical agricultural land type within a county, i.e., they are not specific to individual crop types. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the us

Global gridded crop specific agricultural areas from 1961-2014

NASA Astrophysics Data System (ADS)

Konar, M.; Jackson, N. D.

2017-12-01

Current global cropland datasets are limited in crop specificity and temporal resolution. Time series maps of crop specific agricultural areas would enable us to better understand the global agricultural geography of the 20th century. To this end, we develop a global gridded dataset of crop specific agricultural areas from 1961-2014. To do this, we downscale national cropland information using a probabilistic approach. Our method relies upon gridded Global Agro-Ecological Zones (GAEZ) maps, the History Database of the Global Environment (HYDE), and crop calendars from Sacks et al. (2010). We estimate crop-specific agricultural areas for a 0.25 degree spatial grid and annual time scale for all major crops. We validate our global estimates for the year 2000 with Monfreda et al. (2008) and our time series estimates within the United States using government data. This database will contribute to our understanding of global agricultural change of the past century.

CROP type analysis using Landsat digital data

NASA Technical Reports Server (NTRS)

Brown, C. E.; Thomas, R. W.; Wall, S. L.

1981-01-01

Classification and statistical sampling techniques for crop type discrimination using Landsat digital data have been developed by the University of California in cooperation with NASA and the California Department of Water Resources. Ratioed bands (MSS 7/5 and 5/4) and a sun-angle corrected Euclidean albedo band were prepared from data for the Sacramento Valley for five different dates. The test area was stratified into general crop groupings based on the particular patterns of irrigation timing for each crop. Data classified within each stratum were used to produce a crop type map. Comparison with ground data indicates that certain crops and crop groups are discernable. Small grains and rice are easily identifiable, as are deciduous fruit varieties as a group. However, it is not feasible to separate various fruit and nut varieties, or separate vegetable crops with these techniques at present.

Carbon budget over 12 years in a production crop under temperate climate

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

Carbon dioxide (CO2) exchanges between crops and the atmosphere are influenced by both climatic and crop management drivers. The investigated crop, situated at the Lonzée Terrestrial Observatory (LTO, candidate ICOS site) in Belgium and managed for more than 70 years using conventional farming practices, was monitored over three complete sugar beet (or maize)/winter wheat/potato/winter wheat rotation cycles from 2004 to 2016. Continuous eddy-covariance measurements and regular biomass samplings were performed in order to obtain the daily and seasonal Net Ecosystem Exchange (NEE), Gross Primary Productivity, Total Ecosystem Respiration, Net Primary Productivity, and Net Biome Production (NBP). Meteorological data and crop management practices were also recorded. The main objectives were to analyze the CO2 flux responses to climatic drivers and to establish the C budget of the cropland. Crop type significantly influenced the measured CO2 fluxes. In addition to crop season duration, which had an obvious impact on cumulated NEE values for each crop type, the CO2 flux response to photosynthetic photon flux density, vapor pressure deficit and temperature differed between crop types, while no significant response to soil water content was observed in any of them. Besides, a significant positive relationship between crop residue amount and ecosystem respiration was observed. Over the 12 years, NEE was negative (-4.34 ± 0.21 kg C m-2) but NBP was positive (1.05 ± 0.30 kg C m-2), i.e. as soon as all lateral carbon fluxes - dominated by carbon exportation - are included in the budget, the site behaves as a carbon source. Intercrops were seen to play a major role in the carbon budget, being mostly due to the long time period it represented (59 % of the 12 year time period). An in-depth analysis of intercrop periods and, more specifically, growing cover crops (mustard in the case of our study), is developed in a companion poster (ref. abstract EGU2017-12216, session SSS9.14/BG9.46/CL3.13). Although in line with preceding studies, the large C loss rate observed at LTO (NBP = + 87 ± 25 kg C m-2 yr-1) raises several questions as it corresponds to 1.8 % of the C stock in the top soil: is it realistic? Wouldn't it be affected by an undetected systematic error? If correct, could soil properties be preserved on the long term? This result at least calls for extensive C stock inventory for (in)validation.

Using Geostatistical Data Fusion Techniques and MODIS Data to Upscale Simulated Wheat Yield

NASA Astrophysics Data System (ADS)

Castrignano, A.; Buttafuoco, G.; Matese, A.; Toscano, P.

2014-12-01

Population growth increases food request. Assessing food demand and predicting the actual supply for a given location are critical components of strategic food security planning at regional scale. Crop yield can be simulated using crop models because is site-specific and determined by weather, management, length of growing season and soil properties. Crop models require reliable location-specific data that are not generally available. Obtaining these data at a large number of locations is time-consuming, costly and sometimes simply not feasible. An upscaling method to extend coverage of sparse estimates of crop yield to an appropriate extrapolation domain is required. This work is aimed to investigate the applicability of a geostatistical data fusion approach for merging remote sensing data with the predictions of a simulation model of wheat growth and production using ground-based data. The study area is Capitanata plain (4000 km2) located in Apulia Region, mostly cropped with durum wheat. The MODIS EVI/NDVI data products for Capitanata plain were downloaded from the Land Processes Distributed Active Archive Center (LPDAAC) remote for the whole crop cycle of durum wheat. Phenological development, biomass growth and grain quantity of durum wheat were simulated by the Delphi system, based on a crop simulation model linked to a database including soil properties, agronomical and meteorological data. Multicollocated cokriging was used to integrate secondary exhaustive information (multi-spectral MODIS data) with primary variable (sparsely distributed biomass/yield model predictions of durum wheat). The model estimates looked strongly spatially correlated with the radiance data (red and NIR bands) and the fusion data approach proved to be quite suitable and flexible to integrate data of different type and support.

FIREX mission requirements document for renewable resources

NASA Technical Reports Server (NTRS)

Carsey, F.; Dixon, T.

1982-01-01

The initial experimental program and mission requirements for a satellite synthetic aperture radar (SAR) system FIREX (Free-Flying Imaging Radar Experiment) for renewable resources is described. The spacecraft SAR is a C-band and L-band VV polarized system operating at two angles of incidence which is designated as a research instrument for crop identification, crop canopy condition assessments, soil moisture condition estimation, forestry type and condition assessments, snow water equivalent and snow wetness assessments, wetland and coastal land type identification and mapping, flood extent mapping, and assessment of drainage characteristics of watersheds for water resources applications. Specific mission design issues such as the preferred incidence angles for vegetation canopy measurements and the utility of a dual frequency (L and C-band) or dual polarization system as compared to the baseline system are addressed.

Genomics-Based Exploration of Virulence Determinants and Host-Specific Adaptations of Pseudomonas syringae Strains Isolated from Grasses

PubMed Central

Dudnik, Alexey; Dudler, Robert

2014-01-01

The Pseudomonas syringae species complex has recently been named the number one plant pathogen, due to its economic and environmental impacts, as well as for its role in scientific research. The bacterium has been repeatedly reported to cause outbreaks on bean, cucumber, stone fruit, kiwi and olive tree, as well as on other crop and non-crop plants. It also serves as a model organism for research on the Type III secretion system (T3SS) and plant-pathogen interactions. While most of the current work on this pathogen is either carried out on one of three model strains found on dicot plants with completely sequenced genomes or on isolates obtained from recent outbreaks, not much is known about strains isolated from grasses (Poaceae). Here, we use comparative genomics in order to identify putative virulence-associated genes and other Poaceae-specific adaptations in several newly available genome sequences of strains isolated from grass species. All strains possess only a small number of known Type III effectors, therefore pointing to the importance of non-Type III secreted virulence factors. The implications of this finding are discussed. PMID:25437611

Energy Department Selects Partners...

Science.gov Websites

agricultural and forest wastes and other types of biomass. Six partnerships totaling $1 million in cost shared industrial chemical. Feedstocks are organic material, such as agricultural wastes or crops grown specifically are developed. Agricultural residues, such as corn stover, are the most likely candidates to help meet

Irrigation and Fertilization Type, Rate, and Frequency of Application

Treesearch

Thomas E. Starkey

2002-01-01

There is no "cookbook" formula for growing longleaf pine (Pinus palustris Mill.). However, some very definite minimum guidelines must be followed to successfully produce an acceptable crop of trees. Irrigation and fertilization are the two most important management practices in the growth of the seedlings. Specific guidelines and...

Beta vulgaris crop types: Genomic signatures of selection (GSS) using next generation sequencing of pooled samples

USDA-ARS?s Scientific Manuscript database

Beta vulgaris crop types represent highly diverged populations with distinct phenotypes resulting from long-term selection. Differential end use in the crop types includes: leaf quality (chard/leaf beet), root enlargement and biomass, (table beet, fodder beet, sugar beet), and secondary metabolite a...

Effects on crops of irrigation with treated municipal wastewaters.

PubMed

Fasciolo, G E; Meca, M I; Gabriel, E; Morábito, J

2002-01-01

The fertilizing potential of treated municipal wastewater (oxidation ditch) and crop sanitary acceptability for direct human consumption were evaluated in Mendoza, Argentina. Two experiments were performed on a pilot plot planted with garlic (1998) and onions (1999) using furrow irrigation with three types of water in 10 random blocks: treated effluent (2.5 x 10(3) MPN Escherichia coli/100 ml, 3 helminth eggs/l, and Salmonella (positive); and well water (free of microorganisms), with and without fertilizer. Two responses were evaluated: (1) crop yield, and (2) crop microbiological quality for human consumption at different times after harvest. Crop yields were compared using Variance analysis. Crops' sanitary acceptability was assessed using a two-class sampling program for Salmonella (n=10; c=0), and a three-class program for E. coli (n=5, c=2, M=10(3) and m=10 MPN/g) as proposed by the International Commission on Microbiological Specifications for Foods (ICMSF) for fresh vegetables. Wastewater irrigation acted as well water with fertilizer, increasing garlic and onion yields by 10% and 15%, respectively, compared to irrigation with well water with no fertilizer. Wastewater-irrigated garlic reached sanitary acceptability 90 days after harvest, once attached roots and soil were removed. Onions, which were cleaned immediately after harvest, met this qualification earlier than garlic (55 days). Neither the wastewater-irrigated crops nor the control crops were microbiologically acceptable for consumption raw at harvest.

Current and Future Greenhouse Gas Emissions from Global Crop Intensification and Expansion

NASA Astrophysics Data System (ADS)

Carlson, K. M.; Gerber, J. S.; Mueller, N. D.; O'Connell, C.; West, P. C.

2014-12-01

Food systems currently contribute up to one-third of total anthropogenic greenhouse gas emissions, and these emissions are expected to rise as demand for agricultural products increases. Thus, improving the greenhouse gas emissions efficiency of agriculture - the tons or kilocalories of production per ton of CO2 equivalent emissions - will be critical to support a resilient future global system. Here, we model and evaluate global, 2000-era, spatially explicit relationships between a suite of greenhouse gas emissions from various agronomic practices (i.e., fertilizer application, peatland draining, and rice cultivation) and crop yields. Then, we predict potential emissions from future crop production increases achieved through intensification and extensification, including CO2 emissions from croplands replacing non-urban land cover. We find that 2000-era yield-scaled agronomic emissions are highly heterogeneous across crops types, crop management practices, and regions. Rice agriculture produces more total CO2-equivalent emissions than any other crop. Moreover, inundated rice in just a few countries contributes the vast majority of these rice emissions. Crops such as sunflower and cotton have low efficiency on a caloric basis. Our results suggest that intensification tends to be a more efficient pathway to boost greenhouse gas emissions efficiency than expansion. We conclude by discussing potential crop- and region-specific agricultural development pathways that may boost the greenhouse gas emissions efficiency of agriculture.

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

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.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Plant/soil concentration ratios for paired field and garden crops, with emphasis on iodine and the role of soil adhesion.

PubMed

Sheppard, S C; Long, J M; Sanipelli, B

2010-12-01

In the effort to predict the risks associated with contaminated soils, considerable reliance is placed on plant/soil concentration ratio (CR) values measured at sites other than the contaminated site. This inevitably results in the need to extrapolate among the many soil and plant types. There are few studies that compare CR among plant types that encompass both field and garden crops. Here, CRs for 40 elements were measured for 25 crops from farm and garden sites chosen so the grain crops were in close proximity to the gardens. Special emphasis was placed on iodine (I) because data for this element are sparse. For many elements, there were consistent trends among CRs for the various crop types, with leafy crops > root crops ≥ fruit crops ≈ seed crops. Exceptions included CR values for As, K, Se and Zn which were highest in the seed crops. The correlation of CRs from one plant type to another was evident only when there was a wide range in soil concentrations. In comparing CRs between crop types, it became apparent that the relationships differed for the rare earth elements (REE), which also had very low CR values. The CRs for root and leafy crops of REE converged to a minimum value. This was attributed to soil adhesion, despite the samples being washed, and the average soil adhesion for root crops was 500 mg soil kg⁻¹ dry plant and for leafy crops was 5 g kg⁻¹. Across elements, the log CR was negatively correlated with log Kd (the soil solid/liquid partition coefficient), as expected. Although, this correlation is expected, measures of correlation coefficients suitable for stochastic risk assessment are not frequently reported. The results suggest that r ≈ -0.7 would be appropriate for risk assessment. Copyright © 2010 Elsevier Ltd. All rights reserved.

Agricultural Capacity to Increase the Production of Select Fruits and Vegetables in the US: A Geospatial Modeling Analysis.

PubMed

Conrad, Zach; Peters, Christian J; Chui, Kenneth; Jahns, Lisa; Griffin, Timothy S

2017-09-23

The capacity of US agriculture to increase the output of specific foods to accommodate increased demand is not well documented. This research uses geospatial modeling to examine the capacity of the US agricultural landbase to increase the per capita availability of an example set of nutrient-dense fruits and vegetables. These fruits and vegetables were selected based on nutrient content and an increasing trend of domestic production and consumption. Geographic information system models were parameterized to identify agricultural land areas meeting crop-specific growing requirements for monthly precipitation and temperature; soil depth and type; cropland availability; and proximity to existing production centers. The results of these analyses demonstrate that crop production can be expanded by nearly 144,000 ha within existing national production centers, generating an additional 0.05 cup-equivalents of fruits and vegetables per capita per day, representing a 1.7% increase above current total F&V availability. Expanding the size of national crop production centers can further increase the availability of all F&V by 2.5%-5.4%, which is still less than the recommended amount. Challenges to increasing F&V production in the US include lack of labor availability, barriers to adoption among producers, and threats to crop yields from environmental concerns.

Agricultural Capacity to Increase the Production of Select Fruits and Vegetables in the US: A Geospatial Modeling Analysis

PubMed Central

Peters, Christian J.; Chui, Kenneth; Jahns, Lisa; Griffin, Timothy S.

2017-01-01

The capacity of US agriculture to increase the output of specific foods to accommodate increased demand is not well documented. This research uses geospatial modeling to examine the capacity of the US agricultural landbase to increase the per capita availability of an example set of nutrient-dense fruits and vegetables. These fruits and vegetables were selected based on nutrient content and an increasing trend of domestic production and consumption. Geographic information system models were parameterized to identify agricultural land areas meeting crop-specific growing requirements for monthly precipitation and temperature; soil depth and type; cropland availability; and proximity to existing production centers. The results of these analyses demonstrate that crop production can be expanded by nearly 144,000 ha within existing national production centers, generating an additional 0.05 cup-equivalents of fruits and vegetables per capita per day, representing a 1.7% increase above current total F&V availability. Expanding the size of national crop production centers can further increase the availability of all F&V by 2.5%–5.4%, which is still less than the recommended amount. Challenges to increasing F&V production in the US include lack of labor availability, barriers to adoption among producers, and threats to crop yields from environmental concerns. PMID:28946618

Agricultural irrigated land-use inventory for Osceola County, Florida, October 2013-April 2014

USGS Publications Warehouse

Marella, Richard L.; Dixon, Joann F.

2014-01-01

A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to increase the accuracy of current water-use estimates or to project future water demands in many Florida counties. This report provides a detailed digital map and summary of irrigated areas within Osceola County for the agricultural growing period October 2013–April 2014. The irrigated areas were first delineated using land-use data and satellite imagery and then field verified between February and April 2014. Selected attribute data were collected for the irrigated areas, including crop type, primary water source, and type of irrigation system. Results indicate that an estimated 27,450 acres were irrigated during the study period. This includes 4,370 acres of vegetables, 10,970 acres of orchard crops, 1,620 acres of field crops, and 10,490 acres of ornamentals and grasses. Specifically, irrigated acreage included citrus (10,860 acres), sod (5,640 acres), pasture (4,580 acres), and potatoes (3,320 acres). Overall, groundwater was used to irrigate 18,350 acres (67 percent of the total acreage), and surface water was used to irrigate the remaining 9,100 acres (33 percent). Microirrigation systems accounted for 45 percent of the total acreage irrigated, flood systems 30 percent, and sprinkler systems the remaining 25 percent. An accurate, detailed, spatially referenced, and field-verified inventory of irrigated crop acreage can be used to assist resource managers making current and future county-level water-use estimates in Osceola County.

Nucleic Acid-Based Detection and Identification of Bacterial and Fungal Plant Pathogens - Final Report

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

Kingsley, Mark T.

2001-03-13

The threat to American interests from terrorists is not limited to attacks against humans. Terrorists might seek to inflict damage to the U.S. economy by attacking our agricultural sector. Infection of commodity crops by bacterial or fungal crop pathogens could adversely impact U.S. agriculture, either directly from damage to crops or indirectly from damage to our ability to export crops suspected of contamination. Recognizing a terrorist attack against U.S. agriculture, to be able to prosecute the terrorists, is among the responsibilities of the members of Hazardous Material Response Unit (HMRU) of the Federal Bureau of Investigation (FBI). Nucleic acid analysismore » of plant pathogen strains by the use of polymerase chain reaction (PCR) amplification techniques is a powerful method for determining the exact identity of pathogens, as well as their possible region of origin. This type of analysis, however, requires that PCR assays be developed specific to each particular pathogen strain, and analysis protocols developed that are specific to the particular instrument used for detection. The objectives of the work described here were threefold: 1) to assess the potential terrorist threat to U.S. agricultural crops, 2) to determine whether suitable assays exist to monitor that threat, and 3) where assays are needed for priority plant pathogen threats, to modify or develop those assays for use by specialists at the HMRU. The assessment of potential threat to U.S. commodity crops and the availability of assays for those threats were described in detail in the Technical Requirements Document (9) and will be summarized in this report. This report addresses development of specific assays identified in the Technical Requirements Document, and offers recommendations for future development to ensure that HMRU specialists will be prepared with the PCR assays they need to protect against the threat of economic terrorism.« less

Nucleic Acid-Based Detection and Identification of Bacterial and Fungal Plant Pathogens - Final Report

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

Kingsley, Mark T

2001-03-13

The threat to American interests from terrorists is not limited to attacks against humans. Terrorists might seek to inflict damage to the U.S. economy by attacking our agricultural sector. Infection of commodity crops by bacterial or fungal crop pathogens could adversely impact U.S. agriculture, either directly from damage to crops or indirectly from damage to our ability to export crops suspected of contamination. Recognizing a terrorist attack against U.S. agriculture, to be able to prosecute the terrorists, is among the responsibilities of the members of Hazardous Material Response Unit (HMRU) of the Federal Bureau of Investigation (FBI). Nucleic acid analysismore » of plant pathogen strains by the use of polymerase chain reaction (PCR) amplification techniques is a powerful method for determining the exact identity of pathogens, as well as their possible region of origin. This type of analysis, however, requires that PCR assays be developed specific to each particular pathogen strain, an d analysis protocols developed that are specific to the particular instrument used for detection. The objectives of the work described here were threefold: (1) to assess the potential terrorist threat to U.S. agricultural crops, (2) to determine whether suitable assays exist to monitor that threat, and (3) where assays are needed for priority plant pathogen threats, to modify or develop those assays for use by specialists at the HMRU. The assessment of potential threat to U.S. commodity crops and the availability of assays for those threats were described in detail in the Technical Requirements Document (9) and will be summarized in this report. This report addresses development of specific assays identified in the Technical Requirements Document, and offers recommendations for future development to ensure that HMRU specialists will be prepared with the PCR assays they need to protect against the threat of economic terrorism.« less

Using Imaging Spectrometry to Approach Crop Classification from a Water Management Perspective

NASA Astrophysics Data System (ADS)

Shivers, S.; Roberts, D. A.

2017-12-01

We use hyperspectral remote sensing imagery to classify crops in the Central Valley of California at a level that would be of use to water managers. In California irrigated agriculture uses 80 percent of the state's water supply with differences in water application rate varying by as large as a factor of three, dependent on crop type. Therefore, accurate water resource accounting is dependent upon accurate crop mapping. While on-the-ground crop accounting at the county level requires significant labor and time inputs, remote sensing has the potential to map crops over a greater spatial area with more frequent time intervals. Specifically, imaging spectrometry with its wide spectral range has the ability to detect small spectral differences at the field-level scale that may be indiscernible to multispectral sensors such as Landsat. In this study, crops in the Central Valley were classified into nine categories defined and used by the California Department of Water Resources as having similar water usages. We used the random forest classifier on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery from June 2013, 2014 and 2015 to analyze accuracy of multi-temporal images and to investigate the extent to which cropping patterns have changed over the course of the 2013-2015 drought. Initial results show accuracies of over 90% for all three years, indicating that hyperspectral imagery has the potential to identify crops by water use group at a single time step with a single sensor, allowing cropping patterns to be monitored in anticipation of water needs.

Assessing the impact of climate change upon hydrology and agriculture in the Indrawati Basin, Nepal.

NASA Astrophysics Data System (ADS)

Palazzoli, Irene; Bocchiola, Daniele; Nana, Ester; Maskey, Shreedhar; Uhlenbrook, Stefan

2014-05-01

Agriculture is sensitive to climate change, especially to temperature and precipitation changes. The purpose of this study was to evaluate the climate change impacts upon rain-fed crops production in the Indrawati river basin, Nepal. The Soil and Water Assessment Tool SWAT model was used to model hydrology and cropping systems in the catchment, and to predict the influence of different climate change scenarios therein. Daily weather data collected from about 13 weather stations during 4 decades were used to constrain the SWAT model, and data from two hydrometric stations used to calibrate/validate it. Then management practices (crop calendar) were applied to specific Hydrological Response Units (HRUs) for the main crops of the region, rice, corn and wheat. Manual calibration of crop production was also carried, against values of crop yield in the area from literature. The calibrated and validated model was further applied to assess the impact of three future climate change scenarios (RCPs) upon the crop productivity in the region. Three climate models (GCMs) were adopted, each with three RCPs (2.5, 4.5, 8.5). Hence, impacts of climate change were assessed considering three time windows, namely a baseline period (1995-2004), the middle of century (2045-2054) and the end of century (2085-2094). For each GCM and RCP future hydrology and yield was compared to baseline scenario. The results displayed slightly modified hydrological cycle, and somewhat small variation in crop production, variable with models and RCPs, and for crop type, the largest being for wheat. Keywords: Climate Change, Nepal, hydrological cycle, crop yield.

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.

East Europe Report, Economic and Industrial Affairs

DTIC Science & Technology

1984-05-25

participation of all workers in this process. An effective production intensification with differentiation according to agroecological conditions, with...to concrete agroecological and economic conditions. 16 In connection with crop production specialization, particular attention must be paid to...locality in the CSSR possesses specific agroecological conditions. They predetermine the natural propriety of growing individual types of field

Shoot Na+ Exclusion and Increased Salinity Tolerance Engineered by Cell Type–Specific Alteration of Na+ Transport in Arabidopsis[W][OA

PubMed Central

Møller, Inge S.; Gilliham, Matthew; Jha, Deepa; Mayo, Gwenda M.; Roy, Stuart J.; Coates, Juliet C.; Haseloff, Jim; Tester, Mark

2009-01-01

Soil salinity affects large areas of cultivated land, causing significant reductions in crop yield globally. The Na+ toxicity of many crop plants is correlated with overaccumulation of Na+ in the shoot. We have previously suggested that the engineering of Na+ exclusion from the shoot could be achieved through an alteration of plasma membrane Na+ transport processes in the root, if these alterations were cell type specific. Here, it is shown that expression of the Na+ transporter HKT1;1 in the mature root stele of Arabidopsis thaliana decreases Na+ accumulation in the shoot by 37 to 64%. The expression of HKT1;1 specifically in the mature root stele is achieved using an enhancer trap expression system for specific and strong overexpression. The effect in the shoot is caused by the increased influx, mediated by HKT1;1, of Na+ into stelar root cells, which is demonstrated in planta and leads to a reduction of root-to-shoot transfer of Na+. Plants with reduced shoot Na+ also have increased salinity tolerance. By contrast, plants constitutively expressing HKT1;1 driven by the cauliflower mosaic virus 35S promoter accumulated high shoot Na+ and grew poorly. Our results demonstrate that the modification of a specific Na+ transport process in specific cell types can reduce shoot Na+ accumulation, an important component of salinity tolerance of many higher plants. PMID:19584143

Mapping Cropland and Crop-type Distribution Using Time Series MODIS Data

NASA Astrophysics Data System (ADS)

Lu, D.; Chen, Y.; Moran, E. F.; Batistella, M.; Luo, L.; Pokhrel, Y.; Deb, K.

2016-12-01

Mapping regional and global cropland distribution has attracted great attention in the past decade, but the separation of crop types is challenging due to the spectral confusion and cloud cover problems during the growing season in Brazil. The objective of this study is to develop a new approach to identify crop types (including soybean, cotton, maize) and planting patterns (soybean-maize, soybean-cotton, and single crop) in Mato Grosso, Goias and Tocantins States, Brazil. The time series moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) (MOD13Q1) in 2015/2016 were used in this research and field survey data were collected in May 2016. The major steps include: (1) reconstruct time series NDVI data contaminated by noise and clouds using the temporal interpolation algorithm; (2) identify the best periods and develop temporal indices and phenology parameters to distinguish cropland from other land cover types based on time series NDVI data; (3) develop a crop temporal difference index (CTDI) to extract crop types and patterns using time series NDVI data. This research shows that (1) the cropland occupied approximately 16.85% of total land in these three states; (2) soybean-maize and soybean-cotton were two major crop patterns which occupied 54.80% and 19.30% of total cropland area. This research indicates that the proposed approach is promising for accurately and rapidly mapping cropland and crop-type distribution in these three states of Brazil.

Agricultural conversion of floodplain ecosystems: implications for groundwater quality.

PubMed

Schilling, Keith E; Jacobson, Peter J; Vogelgesang, Jason A

2015-04-15

With current trends of converting grasslands to row crop agriculture in vulnerable areas, there is a critical need to evaluate the effects of land use on groundwater quality in large river floodplain systems. In this study, groundwater hydrology and nutrient dynamics associated with three land cover types (grassland, floodplain forest and cropland) were assessed at the Cedar River floodplain in southeastern Iowa. The cropland site consisted of newly-converted grassland, done specifically for our study. Our objectives were to evaluate spatial and temporal variations in groundwater hydrology and quality, and quantify changes in groundwater quality following land conversion from grassland to row crop in a floodplain. We installed five shallow and one deep monitoring wells in each of the three land cover types and recorded water levels and quality over a three year period. Crop rotations included soybeans in year 1, corn in year 2 and fallow with cover crops during year 3 due to river flooding. Water table levels behaved nearly identically among the sites but during the second and third years of our study, NO₃-N concentrations in shallow floodplain groundwater beneath the cropped site increased from 0.5 mg/l to more than 25 mg/l (maximum of 70 mg/l). The increase in concentration was primarily associated with application of liquid N during June of the second year (corn rotation), although site flooding may have exacerbated NO₃-N leaching. Geophysical investigation revealed differences in ground conductivity among the land cover sites that related significantly to variations in groundwater quality. Study results provide much-needed information on the effects of different land covers on floodplain groundwater and point to challenges ahead for meeting nutrient reduction goals if row crop land use expands into floodplains. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Brassica oleracea early stage abiotic stress responses reveals tolerance in multiple crop types and for multiple sources of stress.

PubMed

Beacham, Andrew M; Hand, Paul; Pink, David Ac; Monaghan, James M

2017-12-01

Brassica oleracea includes a number of important crop types such as cabbage, cauliflower, broccoli and kale. Current climate conditions and weather patterns are causing significant losses in these crops, meaning that new cultivars with improved tolerance of one or more abiotic stress types must be sought. In this study, genetically fixed B. oleracea lines belonging to a Diversity Fixed Foundation Set (DFFS) were assayed for their response to seedling stage-imposed drought, flood, salinity, heat and cold stress. Significant (P ≤ 0.05) variation in stress tolerance response was found for each stress, for each of four measured variables (relative fresh weight, relative dry weight, relative leaf number and relative plant height). Lines tolerant to multiple stresses were found to belong to several different crop types. There was no overall correlation between the responses to the different stresses. Abiotic stress tolerance was identified in multiple B. oleracea crop types, with some lines exhibiting resistance to multiple stresses. For each stress, no one crop type appeared significantly more or less tolerant than others. The results are promising for the development of more environmentally robust lines of different B. oleracea crops by identifying tolerant material and highlighting the relationship between responses to different stresses. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Forecasting model for Pea seed-borne mosaic virus epidemics in field pea crops in a Mediterranean-type environment.

PubMed

Congdon, B S; Coutts, B A; Jones, R A C; Renton, M

2017-09-15

An empirical model was developed to forecast Pea seed-borne mosaic virus (PSbMV) incidence at a critical phase of the annual growing season to predict yield loss in field pea crops sown under Mediterranean-type conditions. The model uses pre-growing season rainfall to calculate an index of aphid abundance in early-August which, in combination with PSbMV infection level in seed sown, is used to forecast virus crop incidence. Using predicted PSbMV crop incidence in early-August and day of sowing, PSbMV transmission from harvested seed was also predicted, albeit less accurately. The model was developed so it provides forecasts before sowing to allow sufficient time to implement control recommendations, such as having representative seed samples tested for PSbMV transmission rate to seedlings, obtaining seed with minimal PSbMV infection or of a PSbMV-resistant cultivar, and implementation of cultural management strategies. The model provides a disease forecast risk indication, taking into account predicted percentage yield loss to PSbMV infection and economic factors involved in field pea production. This disease risk forecast delivers location-specific recommendations regarding PSbMV management to end-users. These recommendations will be delivered directly to end-users via SMS alerts with links to web support that provide information on PSbMV management options. This modelling and decision support system approach would likely be suitable for use in other world regions where field pea is grown in similar Mediterranean-type environments. Copyright © 2017 Elsevier B.V. All rights reserved.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Orphan Crops Browser: a bridge between model and orphan crops.

PubMed

Kamei, Claire Lessa Alvim; Severing, Edouard I; Dechesne, Annemarie; Furrer, Heleen; Dolstra, Oene; Trindade, Luisa M

2016-01-01

Many important crops have received little attention by the scientific community, either because they are not considered economically important or due to their large and complex genomes. De novo transcriptome assembly, using next-generation sequencing data, is an attractive option for the study of these orphan crops. In spite of the large amount of sequencing data that can be generated, there is currently a lack of tools which can effectively help molecular breeders and biologists to mine this type of information. Our goal was to develop a tool that enables molecular breeders, without extensive bioinformatics knowledge, to efficiently study de novo transcriptome data from any orphan crop (http://www.bioinformatics.nl/denovobrowser/db/species/index). The Orphan Crops Browser has been designed to facilitate the following tasks (1) search and identification of candidate transcripts based on phylogenetic relationships between orthologous sequence data from a set of related species and (2) design specific and degenerate primers for expression studies in the orphan crop of interest. To demonstrate the usability and reliability of the browser, it was used to identify the putative orthologues of 17 known lignin biosynthetic genes from maize and sugarcane in the orphan crop Miscanthus sinensis . Expression studies in miscanthus stem internode tissue differing in maturation were subsequently carried out, to follow the expression of these genes during lignification. Our results showed a negative correlation between lignin content and gene expression. The present data are in agreement with recent findings in maize and other crops, and it is further discussed in this paper.

Understanding Cultivar-Specificity and Soil Determinants of the Cannabis Microbiome

DOE PAGES

Winston, Max E.; Hampton-Marcell, Jarrad; Zarraonaindia, Iratxe; ...

2014-06-16

Understanding microbial partnerships with the medicinally and economically important crop Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. In conclusion, the influence of soilmore » type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.« less

Understanding Cultivar-Specificity and Soil Determinants of the Cannabis Microbiome

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

Winston, Max E.; Hampton-Marcell, Jarrad; Zarraonaindia, Iratxe

Understanding microbial partnerships with the medicinally and economically important crop Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. In conclusion, the influence of soilmore » type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.« less

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.

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.

EnviroAtlas - Cultivated biological nitrogen fixation in agricultural lands by 12-digit HUC in the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean cultivated biological nitrogen fixation (C-BNF) in cultivated crop and hay/pasture lands per 12-digit Hydrologic Unit (HUC) in 2006. Nitrogen (N) inputs from the cultivation of legumes, which possess a symbiotic relationship with N-fixing bacteria, were calculated with a recently developed model relating county-level yields of various leguminous crops with BNF rates. We accessed county-level data on annual crop yields for soybeans (Glycine max L.), alfalfa (Medicago sativa L.), peanuts (Arachis hypogaea L.), various dry beans (Phaseolus, Cicer, and Lens spp.), and dry peas (Pisum spp.) for 2006 from the USDA Census of Agriculture (http://www.agcensus.usda.gov/index.php). We estimated the yield of the non-alfalfa leguminous component of hay as 32% of the yield of total non-alfalfa hay (http://www.agcensus.usda.gov/index.php). Annual rates of C-BNF by crop type were calculated using a model that relates yield to C-BNF. We assume yield data reflect differences in soil properties, water availability, temperature, and other local and regional factors that can influence root nodulation and rate of N fixation. We distributed county-specific, C-BNF rates to cultivated crop and hay/pasture lands delineated in the 2006 National Land Cover Database (30 x 30 m pixels) within the corresponding county. C-BNF data described here represent an average input to a typical agricultural land type within a county, i.e., they are not

Integrating multiple satellite data for crop monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing provides a valuable data source for detecting crop types, monitoring crop condition and predicting crop yields from space. Routine and continuous remote sensing data are critical for agricultural research and operational applications. Since crop field dimensions tend to be relatively ...

Shifts and disruptions in resource-use trait syndromes during the evolution of herbaceous crops.

PubMed

Milla, Rubén; Morente-López, Javier; Alonso-Rodrigo, J Miguel; Martín-Robles, Nieves; Chapin, F Stuart

2014-10-22

Trait-based ecology predicts that evolution in high-resource agricultural environments should select for suites of traits that enable fast resource acquisition and rapid canopy closure. However, crop breeding targets specific agronomic attributes rather than broad trait syndromes. Breeding for specific traits, together with evolution in high-resource environments, might lead to reduced phenotypic integration, according to predictions from the ecological literature. We provide the first comprehensive test of these hypotheses, based on a trait-screening programme of 30 herbaceous crops and their wild progenitors. During crop evolution plants became larger, which enabled them to compete more effectively for light, but they had poorly integrated phenotypes. In a subset of six herbaceous crop species investigated in greater depth, competitiveness for light increased during early plant domestication, whereas diminished phenotypic integration occurred later during crop improvement. Mass-specific leaf and root traits relevant to resource-use strategies (e.g. specific leaf area or tissue density of fine roots) changed during crop evolution, but in diverse and contrasting directions and magnitudes, depending on the crop species. Reductions in phenotypic integration and overinvestment in traits involved in competition for light may affect the chances of upgrading modern herbaceous crops to face current climatic and food security challenges. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Analysis of thematic mapper simulator data collected over eastern North Dakota

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1982-01-01

The results of the analysis of aircraft-acquired thematic mapper simulator (TMS) data, collected to investigate the utility of thematic mapper data in crop area and land cover estimates, are discussed. Results of the analysis indicate that the seven-channel TMS data are capable of delineating the 13 crop types included in the study to an overall pixel classification accuracy of 80.97% correct, with relative efficiencies for four crop types examined between 1.62 and 26.61. Both supervised and unsupervised spectral signature development techniques were evaluated. The unsupervised methods proved to be inferior (based on analysis of variance) for the majority of crop types considered. Given the ground truth data set used for spectral signature development as well as evaluation of performance, it is possible to demonstrate which signature development technique would produce the highest percent correct classification for each crop type.

Annual crop type classification of the U.S. Great Plains for 2000 to 2011

USGS Publications Warehouse

Howard, Daniel M.; Wylie, Bruce K.

2014-01-01

The purpose of this study was to increase the spatial and temporal availability of crop classification data. In this study, nearly 16.2 million crop observation points were used in the training of the US Great Plains classification tree crop type model (CTM). Each observation point was further defined by weekly Normalized Difference Vegetation Index, annual climate, and a number of other biogeophysical environmental characteristics. This study accounted for the most prevalent crop types in the region, including, corn, soybeans, winter wheat, spring wheat, cotton, sorghum, and alfalfa. Annual CTM crop maps of the US Great Plains were created for 2000 to 2011 at a spatial resolution of 250 meters. The CTM achieved an 87 percent classification success rate on 1.8 million observation points that were withheld from model training. Product validation was performed on greater than 15,000 county records with a coefficient of determination of R2 = 0.76.

Quantification of pesticides used in agriculture in the EU-27

NASA Astrophysics Data System (ADS)

Wagner, Susanne; Fantke, Peter; Theloke, Jochen; Friedrich, Rainer

2010-05-01

Pesticides have become relatively ubiquitous pollutants. They may affect non-targeted organisms and can be found as contaminants in agricultural soils, groundwater, rivers, lakes and in the food chain (Margni et al., 2002; Hamilton & Crossley, 2004; Arias-Estévez et al., 2008). As "it has been common knowledge that many pesticides cause harm to the environment and to human health" (Pretty & Waibel, 2005), it is essential to account for a quantitative assessment of impacts of current agricultural practice at the European scale. Therefore, inventory data sets of applications and related emissions of the most relevant active substances are necessary. A review of publicly available data sets evidenced that data on consumption of active substances and releases into the environment for EU member states are of low quality or lacking entirely. Either only few substances are covered (e.g. EPER, E-PRTR) or data are highly aggregated in terms of total amount of active substances. Sales or consumption data are differentiated by target organisms and crop types (Eurostat) or by chemical classes (FAOSTAT, OECD.StatExtracts). In Germany, sales data categorised into target organisms and chemical classes are available. To our knowledge, Denmark and the United Kingdom are the only European countries providing application rates for specific active substances and crops. As a basis for analysing the relation between source, environmental fate and sink of pesticides and for considering the importance of crop-specific properties on the fate of pesticides (Trapp and Kulhanek, 2006), crop-specific emission inventories for individual active substances are required. Thus, the aim of our work was to develop a crop-specific inventory for active substances currently used in agriculture in the EU-27. Based on Eurostat (2007), the five most important active substances applied to the crop categories of cereals, maize, oilseeds, potatoes, sugar-beets, grapes and vine, fruit trees and vegetables were identified for each EU member state. The focus was on herbicides and insecticides. Also, the average dosage (i.e. application rate [kg active substance/ha]) for chemical classes per crop category and country was provided. Each active substance was then related to the average dosage of its chemical class for each crop category and country. The amount of active substance applied on a specific crop type in a country was calculated by multiplying the country specific crop production area with the respective dosage. Based on the loss fraction of applied substance to air, the emission into air can be calculated. With this approach we identified 89 active substances of relevance (63 herbicides, 26 insecticides) in the EU-27. The analysis showed a high variation of active substances between the member states, i.e. each country uses particular herbicides and insecticides for particular commodities according to specific climate conditions. For the majority of the member states, our approach covers more than 70 % of total use compared to the aggregated consumption of active substances per country as published in Eurostat. For some specific countries with substance-specific application data available, our results can be compared to real application rates. Discrepancies can be considered as an indicator for the variation of our estimates. By relating the emission inventory data sets to land use maps, they can be spatially disaggregated and thus may serve as input for a subsequent exposure and impact assessment modelling of individual pesticides. References: Arias-Estévez, M., López-Periago, E., Martínez-Carballo, E., Simal-Gándara, J., Mejuto, J.-C., García-Río, L. (2008). The mobility and degradation of pesticides in soils and the pollution of groundwater resources. Agriculture, Ecosystems and Environment 123(4): 247-260. EPER. The European Pollutant Emission Register. Available online at: http://www.eper.ec.europa.eu/. E-PRTR. The European Pollutant Release and Transfer Register. Available online at: http://prtr.ec.europa.eu/. Eurostat (2007). The use of plant protection products in the European Union. Data 1992-2003. Eurostat Statistical books, 2007 edition. Eurostat. Pesticides consumption and sales data. Available online at: http://epp.eurostat.ec.europa.eu/portal/page/portal/environment/data/database. FAOSTAT. Pesticides Consumption Data. Available online at: http://faostat.fao.org/site/424/default.aspx. Hamilton, D. and S. Crossley (2004). Pesticide Residues in Food and Drinking Water: Human Exposure and Risks. Chichester, John Wiley & Sons. Margni, M., Jolliet, O., Rossier, D., Crettaz, P. (2002). Life cycle impact assessment of pesticides on human health and ecosystems. Agriculture, Ecosystems and Environment 93: 379-392. OECD.StatExtracts. Pesticides use data. Available online at: http://stats.oecd.org/Index.aspx. Pretty, J.N., H. Waibel (2005). Paying the price: the full cost of pesticides. In: Pretty, J.N. (Ed.) The Pesticide Detox. London, Earthscan, pp. 39-54. Trapp, S., A. Kulhanek (2006). Human Exposure Assessment for Food - One Equation for all Crops is not enough. In: Mackova, M., D. Dowling, T. Macek. Phytoremediation and Rhizoremediation. Dordrecht, The Netherlands, Springer Press: 285-300.

Camera sensor arrangement for crop/weed detection accuracy in agronomic images.

PubMed

Romeo, Juan; Guerrero, José Miguel; Montalvo, Martín; Emmi, Luis; Guijarro, María; Gonzalez-de-Santos, Pablo; Pajares, Gonzalo

2013-04-02

In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes. Accuracy of identification and detection is an important issue to be addressed in image processing. There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others. Moreover, in agricultural applications, the uncontrolled illumination, existing in outdoor environments, is also an important factor affecting the image accuracy. This paper is exclusively focused on two main issues, always with the goal to achieve the highest image accuracy in Precision Agriculture applications, making the following two main contributions: (a) camera sensor arrangement, to adjust extrinsic parameters and (b) design of strategies for controlling the adverse illumination effects.

[Effect of conservation tillage on weeds in a rotation system on the Loess Plateau of eastern Gansu, Northwest China].

PubMed

Zhao, Yu-xin; Lu, Jiao-yun; Yang, Hui-min

2015-04-01

A field study was conducted to investigate the influences of no-tillage, stubble retention and crop type on weed density, species composition and community feature in a rotation system (winter wheat-common vetch-maize) established 12 years ago on the Loess Plateau of eastern Gansu. This study showed that the weed species composition, density and community feature varied with the change of crop phases. No-tillage practice increased the weed density at maize phase, while rotation with common vetch decreased the density in the no-tillage field. Stubble retention reduced the weed density under maize phase and the lowest density was observed in the no-tillage plus stubble retention field. No-tillage practice significantly increased the weed species diversity under winter wheat phase and decreased the diversity under common vetch phase. At maize phase, a greater species diversity index was observed in the no-tillage field. These results suggested that no-tillage practice and stubble retention possibly suppress specific weeds with the presence of some crops and crop rotation is a vital way to controlling weeds in a farming system.

Manual LANDSAT data analysis for crop type identification

NASA Technical Reports Server (NTRS)

Hay, C. M. (Principal Investigator)

1979-01-01

The process of manual identification of crop type by human analysts and problems associated in LACIE that were associated with manual crop identification measurement procedures are described. Research undertaken in cooperation with LACIE operations by the supporting research community to effect solutions to, or obtain greater understanding of the problems is discussed.

Planter closing wheel effects on cotton emergence in a conservation tillage system

USDA-ARS?s Scientific Manuscript database

Closing wheels on a row crop planter help provide good seed-soil contact during planting and can influence emergence and crop stand. Various types of closing wheels are available to producers for use on planters. Seven closing wheel types were used on a row crop planter planting cotton in a conser...

Satellite Estimation of Fractional Cover in Several California Specialty Crops

NASA Technical Reports Server (NTRS)

Johnson, Lee; Cahn, Michael; Rosevelt, Carolyn; Guzman, Alberto; Farrara, Barry; Melton, Forrest S.

2016-01-01

Past research in California and elsewhere has revealed strong relationships between satellite NDVI, photosynthetically active vegetation fraction (Fc), and crop evapotranspiration (ETc). Estimation of ETc can support efficiency of irrigation practice, which enhances water security and may mitigate nitrate leaching. The U.C. Cooperative Extension previously developed the CropManage (CM) web application for evaluation of crop water requirement and irrigation scheduling for several high-value specialty crops. CM currently uses empirical equations to predict daily Fc as a function of crop type, planting date and expected harvest date. The Fc prediction is transformed to fraction of reference ET and combined with reference data from the California Irrigation Management Information System to estimate daily ETc. In the current study, atmospherically-corrected Landsat NDVI data were compared with in-situ Fc estimates on several crops in the Salinas Valley during 2011-2014. The satellite data were observed on day of ground collection or were linearly interpolated across no more than an 8-day revisit period. Results will be presented for lettuce, spinach, celery, broccoli, cauliflower, cabbage, peppers, and strawberry. An application programming interface (API) allows CM and other clients to automatically retrieve NDVI and associated data from NASA's Satellite Irrigation Management Support (SIMS) web service. The SIMS API allows for queries both by individual points or user-defined polygons, and provides data for individual days or annual timeseries. Updates to the CM web app will convert these NDVI data to Fc on a crop-specific basis. The satellite observations are expected to play a support role in Salinas Valley, and may eventually serve as a primary data source as CM is extended to crop systems or regions where Fc is less predictable.

Satellite Estimation of Fractional Cover in Several California Specialty Crops

NASA Astrophysics Data System (ADS)

Johnson, L.; Cahn, M.; Rosevelt, C.; Guzman, A.; Lockhart, T.; Farrara, B.; Melton, F. S.

2016-12-01

Past research in California and elsewhere has revealed strong relationships between satellite NDVI, photosynthetically active vegetation fraction (Fc), and crop evapotranspiration (ETc). Estimation of ETc can support efficiency of irrigation practice, which enhances water security and may mitigate nitrate leaching. The U.C. Cooperative Extension previously developed the CropManage (CM) web application for evaluation of crop water requirement and irrigation scheduling for several high-value specialty crops. CM currently uses empirical equations to predict daily Fc as a function of crop type, planting date and expected harvest date. The Fc prediction is transformed to fraction of reference ET and combined with reference data from the California Irrigation Management Information System to estimate daily ETc. In the current study, atmospherically-corrected Landsat NDVI data were compared with in-situ Fc estimates on several crops in the Salinas Valley during 2011-2014. The satellite data were observed on day of ground collection or were linearly interpolated across no more than an 8-day revisit period. Results will be presented for lettuce, spinach, celery, broccoli, cauliflower, cabbage, peppers, and strawberry. An application programming interface (API) allows CM and other clients to automatically retrieve NDVI and associated data from NASA's Satellite Irrigation Management Support (SIMS) web service. The SIMS API allows for queries both by individual points or user-defined polygons, and provides data for individual days or annual timeseries. Updates to the CM web app will convert these NDVI data to Fc on a crop-specific basis. The satellite observations are expected to play a support role in Salinas Valley, and may eventually serve as a primary data source as CM is extended to crop systems or regions where Fc is less predictable.

Combining Remote Sensing imagery of both fine and coarse spatial resolution to Estimate Crop Evapotranspiration and quantifying its Influence on Crop Growth Monitoring.

NASA Astrophysics Data System (ADS)

Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio; Duveiller, Gregory; Piccard, Isabelle; de Wit, Allard; Tychon, Bernard; Bakary, Djaby; Defourny, Pierre

2010-05-01

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. Evapotranspiration (ET) is a valuable parameter in the crop monitoring context since it provides information on the plant water stress status, which strongly influences crop development and, by extension, crop yield. To assess crop evapotranspiration over the GLOBAM study areas (300x300 km sites in Northern Europe and Central Ethiopia), a Soil-Vegetation-Atmosphere Transfer (SVAT) model forced with remote sensing and numerical weather prediction data has been used. This model runs at pre-operational level in the framework of the EUMETSAT LSA-SAF (Land Surface Analysis Satellite Application Facility) using SEVIRI and ECMWF data, as well as the ECOCLIMAP database to characterize the vegetation. The model generates ET images at the Meteosat Second Generation (MSG) spatial resolution (3 km at subsatellite point),with a temporal resolution of 30 min and monitors the entire MSG disk which covers Europe, Africa and part of Sud America . The SVAT model was run for 2007 using two approaches. The first approach is at the standard pre-operational mode. The second incorporates remote sensing information at various spatial resolutions going from LANDSAT (30m) to SEVIRI (3-5 km) passing by AWIFS (56m) and MODIS (250m). Fine spatial resolution data consists of crop type classification which enable to identify areas where pure crop specific MODIS time series can be compiled and used to derive Leaf Area Index estimations for the most important crops (wheat and maize). The use of this information allowed to characterize the type of vegetation and its state of development in a more accurate way than using the ECOCLIMAP database. Finally, the CASA method was applied using the evapotranspiration images with FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) images from LSA-SAF to obtain Dry Matter Productivity (DMP) and crop yield. The potential of using evapotranspiration obtained from remote sensing in crop growth modeling is studied and discussed. Results of comparing the evapotranspiration obtained with ground truth data are shown as well as the influence of using high resolution information to characterize the vegetation in the evapotranspiration estimation. The values of DMP and yield obtained with the CASA method are compared with those obtained using crop growth modeling and field data, showing the potential of using this simplified remote sensing method for crop monitoring and yield forecasting. This methodology could be applied in an operative way to the entire MSG disk, allowing the continuous crop growth monitoring.

Introgression from cultivated rice alters genetic structures of wild relative populations: implications for in situ conservation

PubMed Central

Jin, Xin; Chen, Yu; Liu, Ping; Li, Chen; Cai, Xingxing; Rong, Jun

2018-01-01

Abstract Maintaining genetic integrity is essential for in situ and ex situ conservation of crop wild relative (CWR) species. However, introgression of crop alleles into CWR species/populations may change their genetic structure and diversity, resulting in more invasive weeds or, in contrast, the extinction of endangered populations. To determine crop-wild introgression and its consequences, we examined the genetic structure and diversity of six wild rice (Oryza rufipogon) populations under in situ conservation in China. Thirty-four simple sequence repeat (SSR) and 34 insertion/deletion markers were used to genotype the wild rice populations and two sets of rice cultivars (O. sativa), corresponding to the two types of molecular markers. Shared alleles and STRUCTURE analyses suggested a variable level of crop-wild introgression and admixture. Principal coordinates and cluster analyses indicated differentiation of wild rice populations, which was associated with the spatial distances to cultivated rice fields. The level of overall genetic diversity was comparable between wild rice populations and rice cultivars, but a great number of wild-specific alleles was detected in the wild populations. We conclude based on the results that crop-wild introgression can considerably alter the pattern of genetic structure and relationships of CWR populations. Appropriate measures should be taken for effective in situ conservation of CWR species under the scenario of crop-wild introgression. PMID:29308123

Introgression from cultivated rice alters genetic structures of wild relative populations: implications for in situ conservation.

PubMed

Jin, Xin; Chen, Yu; Liu, Ping; Li, Chen; Cai, Xingxing; Rong, Jun; Lu, Bao-Rong

2018-02-01

Maintaining genetic integrity is essential for in situ and ex situ conservation of crop wild relative (CWR) species. However, introgression of crop alleles into CWR species/populations may change their genetic structure and diversity, resulting in more invasive weeds or, in contrast, the extinction of endangered populations. To determine crop-wild introgression and its consequences, we examined the genetic structure and diversity of six wild rice ( Oryza rufipogon ) populations under in situ conservation in China. Thirty-four simple sequence repeat (SSR) and 34 insertion/deletion markers were used to genotype the wild rice populations and two sets of rice cultivars ( O. sativa ), corresponding to the two types of molecular markers. Shared alleles and STRUCTURE analyses suggested a variable level of crop-wild introgression and admixture. Principal coordinates and cluster analyses indicated differentiation of wild rice populations, which was associated with the spatial distances to cultivated rice fields. The level of overall genetic diversity was comparable between wild rice populations and rice cultivars, but a great number of wild-specific alleles was detected in the wild populations. We conclude based on the results that crop-wild introgression can considerably alter the pattern of genetic structure and relationships of CWR populations. Appropriate measures should be taken for effective in situ conservation of CWR species under the scenario of crop-wild introgression.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.

PubMed

Zhou, Luxi; Baker, Kirk R; Napelenok, Sergey L; Pouliot, George; Elleman, Robert; O'Neill, Susan M; Urbanski, Shawn P; Wong, David C

2018-06-15

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy. Copyright © 2018 Elsevier B.V. All rights reserved.

GEOGLAM Crop Monitor Assessment Tool: Developing Monthly Crop Condition Assessments

NASA Astrophysics Data System (ADS)

McGaughey, K.; Becker Reshef, I.; Barker, B.; Humber, M. L.; Nordling, J.; Justice, C. O.; Deshayes, M.

2014-12-01

The Group on Earth Observations (GEO) developed the Global Agricultural Monitoring initiative (GEOGLAM) to improve existing agricultural information through a network of international partnerships, data sharing, and operational research. This presentation will discuss the Crop Monitor component of GEOGLAM, which provides the Agricultural Market Information System (AMIS) with an international, multi-source, and transparent consensus assessment of crop growing conditions, status, and agro-climatic conditions likely to impact global production. This activity covers the four primary crop types (wheat, maize, rice, and soybean) within the main agricultural producing regions of the AMIS countries. These assessments have been produced operationally since September 2013 and are published in the AMIS Market Monitor Bulletin. The Crop Monitor reports provide cartographic and textual summaries of crop conditions as of the 28th of each month, according to crop type. This presentation will focus on the building of international networks, data collection, and data dissemination.

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations

NASA Astrophysics Data System (ADS)

Wong, A.; Jin, Y.; Snyder, R. L.; Daniele, Z.; Gao, F.

2016-12-01

Irrigation accounts for 80% of human freshwater consumption, and most of it return to the atmosphere through Evapotranspiration (ET). Given the challenges of already-stressed water resources and ground water regulation in California, a cost-effective, timely, and consistent spatial estimate of crop ET, from the farm to watershed level, is becoming increasingly important. The Priestley-Taylor (PT) approach, calibrated with field data and driven by satellite observations, shows great promise for accurate ET estimates across diverse ecosystems. We here aim to improve the robustness of the PT approach in agricultural lands, to enable growers and farm managers to tailor irrigation management based on in-field spatial variability and in-season variation. We optimized the PT coefficients for each crop type with available ET measurements from eddy covariance towers and/or surface renewal stations at six crop fields (Alfalfa, Almond, Citrus, Corn, Pistachio and Rice) in California. Good agreement was found between satellite-based estimates and field measurements of net radiation, with a RMSE of less than 36 W m-2. The crop type specific optimization performed well, with a RMSE of 30 W m-2 and a correlation of 0.81 for predicted daily latent heat flux. The calibrated algorithm was used to estimate ET at 30 m resolution over the Sacramento-San Joaquin Delta region for 2015 water year. It captures well the seasonal dynamics and spatial distribution of ET in Sacramento-San Joaquin Delta. A continuous monitoring of the dynamics and spatial heterogeneity of canopy and consumptive water use at a field scale, will help the growers to be well prepared and informed to adaptively manage water, canopy, and grove density to maximize the yield with the least amount of water.

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.

CESM-simulated 21st Century Changes in Large Scale Crop Water Requirements and Yields

NASA Astrophysics Data System (ADS)

Levis, S.; Badger, A.; Drewniak, B. A.; O'Neill, B. C.; Ren, X.

2014-12-01

We assess potential changes in crop water requirements and corresponding yields relative to the late 20th century in major crop producing regions of the world by using the Community Land Model (CLM) driven with 21st century meteorology from RCP8.5 and RCP4.5 Community Earth System Model (CESM) simulations. The RCP4.5 simulation allows us to explore the potential for averted societal impacts when compared to the RCP8.5 simulation. We consider the possibility for increased yields and improved water use efficiency under conditions of elevated atmospheric CO2 due to the CO2 fertilization effect (also known as concentration-carbon feedback). We address uncertainty in the current understanding of plant CO2 fertilization by repeating the simulations with and without the CO2 fertilization effect. Simulations without CO2 fertilization represent the radiative effect of elevated CO2 (i.e., warming) without representing the physiological effect of elevated CO2 (enhanced carbon uptake and increased water use efficiency by plants during photosynthesis). Preliminary results suggest that some plants may suffer from increasing heat and drought in much of the world without the CO2 fertilization effect. On the other hand plants (especially C3) tend to grow more with less water when models include the CO2 fertilization effect. Performing 21st century simulations with and without the CO2 fertilization effect brackets the potential range of outcomes. In this work we use the CLM crop model, which includes specific crop types that differ from the model's default plant functional types in that the crops get planted, harvested, and potentially fertilized and irrigated according to algorithms that attempt to capture human management decisions. We use an updated version of the CLM4.5 that includes cotton, rice, and sugarcane, spring wheat, spring barley, and spring rye, as well as temperate and tropical maize and soybean.

Spatial methods for deriving crop rotation history

USDA-ARS?s Scientific Manuscript database

Converting multi-year remote sensing classification data into crop rotations is beneficial by defining length of crop rotation cycles and the specific sequences of intervening crops grown between the final year of a grass seed stand and establishment of a new perennial ryegrass seed crop. Markov mod...

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

PubMed

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

2016-01-01

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

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.

Sorghum to Ethanol Research

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

Dahlberg, Jeffrey A.; Wolfrum, Edward J.

2010-09-28

The development of a robust source of renewable transportation fuel will require a large amount of biomass feedstocks. It is generally accepted that in addition to agricultural and forestry residues, we will need crops grown specifically for subsequent conversion into fuels. There has been a lot of research on several of these so-called "dedicated bioenergy crops" including switchgrass, miscanthus, sugarcane, and poplar. It is likely that all of these crops will end up playing a role as feedstocks, depending on local environmental and market conditions. Many different types of sorghum have been grown to produce syrup, grain, and animal feedmore » for many years. It has several features that may make it as compelling as other crops mentioned above as a renewable, sustainable biomass feedstock; however, very little work has been done to investigate sorghum as a dedicated bioenergy crop. The goal of this project was to investigate the feasibility of using sorghum biomass to produce ethanol. The work performed included a detailed examination of the agronomics and composition of a large number of sorghum varieties, laboratory experiments to convert sorghum to ethanol, and economic and life-cycle analyses of the sorghum-to-ethanol process. This work showed that sorghum has a very wide range of composition, which depended on the specific sorghum cultivar as well as the growing conditions. The results of laboratory- and pilot-scale experiments indicated that a typical high-biomass sorghum variety performed very similarly to corn stover during the multi-step process required to convert biomass feedstocks to ethanol; yields of ethanol for sorghum were very similar to the corn stover used as a control in these experiments. Based on multi-year agronomic data and theoretical ethanol production, sorghum can achieve more than 1,300 gallons of ethanol per acre given the correct genetics and environment. In summary, sorghum may be a compelling dedicated bioenergy crop that could help provide a major portion of the feedstocks required to produce renewable domestic transportation fuels.« less

Selection during crop diversification involves correlated evolution of the circadian clock and ecophysiological traits in Brassica rapa.

PubMed

Yarkhunova, Yulia; Edwards, Christine E; Ewers, Brent E; Baker, Robert L; Aston, Timothy Llewellyn; McClung, C Robertson; Lou, Ping; Weinig, Cynthia

2016-04-01

Crop selection often leads to dramatic morphological diversification, in which allocation to the harvestable component increases. Shifts in allocation are predicted to impact (as well as rely on) physiological traits; yet, little is known about the evolution of gas exchange and related anatomical features during crop diversification. In Brassica rapa, we tested for physiological differentiation among three crop morphotypes (leaf, turnip, and oilseed) and for correlated evolution of circadian, gas exchange, and phenological traits. We also examined internal and surficial leaf anatomical features and biochemical limits to photosynthesis. Crop types differed in gas exchange; oilseed varieties had higher net carbon assimilation and stomatal conductance relative to vegetable types. Phylogenetically independent contrasts indicated correlated evolution between circadian traits and both gas exchange and biomass accumulation; shifts to shorter circadian period (closer to 24 h) between phylogenetic nodes are associated with higher stomatal conductance, lower photosynthetic rate (when CO2 supply is factored out), and lower biomass accumulation. Crop type differences in gas exchange are also associated with stomatal density, epidermal thickness, numbers of palisade layers, and biochemical limits to photosynthesis. Brassica crop diversification involves correlated evolution of circadian and physiological traits, which is potentially relevant to understanding mechanistic targets for crop improvement. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Irrigation and Maize Cultivation Erode Plant Diversity Within Crops in Mediterranean Dry Cereal Agro-Ecosystems.

PubMed

Fagúndez, Jaime; Olea, Pedro P; Tejedo, Pablo; Mateo-Tomás, Patricia; Gómez, David

2016-07-01

The intensification of agriculture has increased production at the cost of environment and biodiversity worldwide. To increase crop yield in dry cereal systems, vast farmland areas of high conservation value are being converted into irrigation, especially in Mediterranean countries. We analyze the effect of irrigation-driven changes on the farm biota by comparing species diversity, community composition, and species traits of arable plants within crop fields from two contrasting farming systems (dry and irrigated) in Spain. We sampled plant species within 80 fields of dry wheat, irrigated wheat, and maize (only cultivated under irrigation). Wheat crops held higher landscape and per field species richness, and beta diversity than maize. Within the same type of crop, irrigated wheat hosted lower plant diversity than dry wheat at both field and landscape scales. Floristic composition differed between crop types, with higher frequencies of perennials, cosmopolitan, exotic, wind-pollinated and C4 species in maize. Our results suggest that irrigation projects, that transform large areas of dry cereal agro-ecosystems into irrigated crop systems dominated by maize, erode plant diversity. An adequate planning on the type and proportion of crops used in the irrigated agro-ecosystems is needed in order to balance agriculture production and biodiversity conservation.

Near-Real-Time Monitoring and Reporting of Crop Growth Condition and Harvest Status Using an Integrated Optical and Radar Approach at the National-Scale in Canada

NASA Astrophysics Data System (ADS)

Shang, J.

2015-12-01

There has been an increasing need to have accurate and spatially detailed information on crop growth condition and harvest status over Canada's agricultural land so that the impacts of environmental conditions, market supply and demand, and transportation network limitations on crop production can be understood fully and acted upon in a timely manner. Presently, Canada doesn't have a national dataset that can provide near-real-time geospatial information on crop growth stage and harvest systematically so that reporting on risk events can be linked directly to the grain supply chain and crop production fluctuations. The intent of this study is to develop an integrated approach using Earth observation (EO) technology to provide a consistent, comprehensive picture of crop growth cycles (growth conditions and stages) and agricultural management activities (field preparation for seeding, harvest, and residue management). Integration of the optical and microwave satellite remote sensing technologies is imperative for robust methodology development and eventually for operational implementation. Particularly, the current synthetic aperture radar (SAR) system Radarsat-2 and to be launched Radarsat Constellation Mission (RCM) are unique EO resources to Canada. Incorporating these Canadian SAR resources with international SAR missions such as the Cosmesky-Med and TerraSAR, could be of great potential for developing change detection technologies particularly useful for monitoring harvest as well as other types of agricultural management events. The study revealed that radar and multi-scale (30m and 250m) optical satellite data can directly detect or infer 1) seeding date, 2) crop growth stages and gross primary productivity (GPP), and 3) harvest progress. Operational prototypes for providing growing-season information at the crop-specific level will be developed across the Canadian agricultural land base.

Regression model estimation of early season crop proportions: North Dakota, some preliminary results

NASA Technical Reports Server (NTRS)

Lin, K. K. (Principal Investigator)

1982-01-01

To estimate crop proportions early in the season, an approach is proposed based on: use of a regression-based prediction equation to obtain an a priori estimate for specific major crop groups; modification of this estimate using current-year LANDSAT and weather data; and a breakdown of the major crop groups into specific crops by regression models. Results from the development and evaluation of appropriate regression models for the first portion of the proposed approach are presented. The results show that the model predicts 1980 crop proportions very well at both county and crop reporting district levels. In terms of planted acreage, the model underpredicted 9.1 percent of the 1980 published data on planted acreage at the county level. It predicted almost exactly the 1980 published data on planted acreage at the crop reporting district level and overpredicted the planted acreage by just 0.92 percent.

Genome-Wide Analysis of miRNA targets in Brachypodium and Biomass Energy Crops

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

Green, Pamela J.

2015-08-11

MicroRNAs (miRNAs) contribute to the control of numerous biological processes through the regulation of specific target mRNAs. Although the identities of these targets are essential to elucidate miRNA function, the targets are much more difficult to identify than the small RNAs themselves. Before this work, we pioneered the genome-wide identification of the targets of Arabidopsis miRNAs using an approach called PARE (German et al., Nature Biotech. 2008; Nature Protocols, 2009). Under this project, we applied PARE to Brachypodium distachyon (Brachypodium), a model plant in the Poaceae family, which includes the major food grain and bioenergy crops. Through in-depth global analysismore » and examination of specific examples, this research greatly expanded our knowledge of miRNAs and target RNAs of Brachypodium. New regulation in response to environmental stress or tissue type was found, and many new miRNAs were discovered. More than 260 targets of new and known miRNAs with PARE sequences at the precise sites of miRNA-guided cleavage were identified and characterized. Combining PARE data with the small RNA data also identified the miRNAs responsible for initiating approximately 500 phased loci, including one of the novel miRNAs. PARE analysis also revealed that differentially expressed miRNAs in the same family guide specific target RNA cleavage in a correspondingly tissue-preferential manner. The project included generation of small RNA and PARE resources for bioenergy crops, to facilitate ongoing discovery of conserved miRNA-target RNA regulation. By associating specific miRNA-target RNA pairs with known physiological functions, the research provides insights about gene regulation in different tissues and in response to environmental stress. This, and release of new PARE and small RNA data sets should contribute basic knowledge to enhance breeding and may suggest new strategies for improvement of biomass energy crops.« less

Seasonal forecasts for the agricultural sector in Peru through user-tailored indices

NASA Astrophysics Data System (ADS)

Sedlmeier, Katrin; Gubler, Stefanie; Spierig, Christoph; Quevedo, Karim; Escajadillo, Yury; Avalos, Griña; Liniger, Mark A.; Schwierz, Cornelia

2017-04-01

In the agricultural sector, the demand for seasonal forecast information is high since agriculture depends strongly on climatic conditions during the growing season. Unfavorable weather and climate events, such as droughts or frost events, can lead to crop losses and thereby to large economic damages or life-threatening conditions in case of subsistence farming. The generally used presentation form of tercile probabilities of seasonally averaged meteorological quantities are not specific enough for end users. More user-tailored seasonal information is necessary. For example, warmer than average temperatures might be favorable for a crop as long as they remain below a plant-specific critical threshold. If, on the other hand, too many days show temperatures above this critical threshold, a mitigation action such as e.g. changing the crop type would be required. In the framework of the CLIMANDES project (a pilot project of the Global Framework for Climate Services led by WMO [http://www.wmo.int/gfcs/climandes]), user-tailored seasonal forecast products are developed for the agricultural sector in the Peruvian Andes. Such products include indices such as e.g. the frost risk, the occurrence of long dry periods, or the start of the rainy season which is crucial to schedule sowing. Furthermore, more specific indices derived from crop requirement studies are elaborated such as the number of days exceeding or falling below plant specific temperature thresholds for given phenological stages. The applicability of these products highly depends on forecast skill. In this study, the potential predictability and the skill of selected indicators are presented using seasonal hindcast data of the ECMWF system 4 for Peru during the time period 1981-2010. Furthermore, the influence of ENSO on the prediction skill is investigated. In this study, reanalysis data, ground measurements, and a gridded precipitation dataset are used for verification. The results indicate that temperature-based indicators show sizeable skill in the Peruvian highlands while precipitation-based forecasts are much more challenging.

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

USGS Publications Warehouse

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

2000-01-01

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

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

A comprehensive data processing plan for crop calendar MSS signature development from satellite imagery: Crop identification using vegetation phenology

NASA Technical Reports Server (NTRS)

Hlavka, C. A. (Principal Investigator); Carlyle, S. M.; Haralick, R. M.; Yokoyama, R.

1978-01-01

The author has identified the following significant results. The phenological method of crop identification involves the creation of crop signatures which characterize multispectral observations as phenological growth states. The phenological signature models spectral reflectance explicitly as a function of crop maturity rather than as a function of date. A correspondence of time to growth state is established which minimizes the smallest difference between the given multispectral multitemporal vector and a category mean vector. The application of the method to the identification of winter wheat and corn shows (1) the method is capable of discriminating crop type with about the same degree of accuracy as more traditional classifiers; (2) the use of LANDSAT observations on two or more dates yields better results than the use of a single observation; and (3) some potential is demonstrated for labeling the degree of maturity of the crop, as well as the crop type.

Crop suitability monitoring for improved yield estimations with 100m PROBA-V data

NASA Astrophysics Data System (ADS)

Özüm Durgun, Yetkin; Gilliams, Sven; Gobin, Anne; Duveiller, Grégory; Djaby, Bakary; Tychon, Bernard

2015-04-01

This study has been realised within the framework of a PhD targeting to advance agricultural monitoring with improved yield estimations using SPOT VEGETATION remotely sensed data. For the first research question, the aim was to improve dry matter productivity (DMP) for C3 and C4 plants by adding a water stress factor. Additionally, the relation between the actual crop yield and DMP was studied. One of the limitations was the lack of crop specific maps which leads to the second research question on 'crop suitability monitoring'. The objective of this work is to create a methodological approach based on the spectral and temporal characteristics of PROBA-V images and ancillary data such as meteorology, soil and topographic data to improve the estimation of annual crop yields. The PROBA-V satellite was launched on 6th May 2013, and was designed to bridge the gap in space-borne vegetation measurements between SPOT-VGT (March 1998 - May 2014) and the upcoming Sentinel-3 satellites scheduled for launch in 2015/2016. PROBA -V has products in four spectral bands: BLUE (centred at 0.463 µm), RED (0.655 µm), NIR (0.845 µm), and SWIR (1.600 µm) with a spatial resolution ranging from 1km to 300m. Due to the construction of the sensor, the central camera can provide a 100m data product with a 5 to 8 days revisiting time. Although the 100m data product is still in test phase a methodology for crop suitability monitoring was developed. The multi-spectral composites, NDVI (Normalised Difference Vegetation Index) (NIR_RED/NIR+RED) and NDII (Normalised Difference Infrared Index) (NIR-SWIR/NIR+SWIR) profiles are used in addition to secondary data such as digital elevation data, precipitation, temperature, soil types and administrative boundaries to improve the accuracy of crop yield estimations. The methodology is evaluated on several FP7 SIGMA test sites for the 2014 - 2015 period. Reference data in the form of vector GIS with boundaries and cover type of agricultural fields are available through the SIGMA site partners. References http://proba-v.vgt.vito.be/ http://www.geoglam-sigma.info/

Landscape configurational heterogeneity by small-scale agriculture, not crop diversity, maintains pollinators and plant reproduction in western Europe.

PubMed

Hass, Annika L; Kormann, Urs G; Tscharntke, Teja; Clough, Yann; Baillod, Aliette Bosem; Sirami, Clélia; Fahrig, Lenore; Martin, Jean-Louis; Baudry, Jacques; Bertrand, Colette; Bosch, Jordi; Brotons, Lluís; Burel, Françoise; Georges, Romain; Giralt, David; Marcos-García, María Á; Ricarte, Antonio; Siriwardena, Gavin; Batáry, Péter

2018-02-14

Agricultural intensification is one of the main causes for the current biodiversity crisis. While reversing habitat loss on agricultural land is challenging, increasing the farmland configurational heterogeneity (higher field border density) and farmland compositional heterogeneity (higher crop diversity) has been proposed to counteract some habitat loss. Here, we tested whether increased farmland configurational and compositional heterogeneity promote wild pollinators and plant reproduction in 229 landscapes located in four major western European agricultural regions. High-field border density consistently increased wild bee abundance and seed set of radish ( Raphanus sativus ), probably through enhanced connectivity. In particular, we demonstrate the importance of crop-crop borders for pollinator movement as an additional experiment showed higher transfer of a pollen analogue along crop-crop borders than across fields or along semi-natural crop borders. By contrast, high crop diversity reduced bee abundance, probably due to an increase of crop types with particularly intensive management. This highlights the importance of crop identity when higher crop diversity is promoted. Our results show that small-scale agricultural systems can boost pollinators and plant reproduction. Agri-environmental policies should therefore aim to halt and reverse the current trend of increasing field sizes and to reduce the amount of crop types with particularly intensive management. © 2018 The Author(s).

Multi-temporal UAV based data for mapping crop type and structure in smallholder dominated Tanzanian agricultural landscape

NASA Astrophysics Data System (ADS)

Nagol, J. R.; Chung, C.; Dempewolf, J.; Maurice, S.; Mbungu, W.; Tumbo, S.

2015-12-01

Timely mapping and monitoring of crops like Maize, an important food security crop in Tanzania, can facilitate timely response by government and non-government organizations to food shortage or surplus conditions. Small UAVs can play an important role in linking the spaceborne remote sensing data and ground based measurement to improve the calibration and validation of satellite based estimates of in-season crop metrics. In Tanzania most of the growing season is often obscured by clouds. UAV data, if collected within a stratified statistical sampling framework, can also be used to directly in lieu of spaceborne data to infer mid-season yield estimates at regional scales.Here we present an object based approach to estimate crop metrics like crop type, area, and height using multi-temporal UAV based imagery. The methods were tested at three 1km2 plots in Kilosa, Njombe, and Same districts in Tanzania. At these sites both ground based and UAV based data were collected on a monthly time-step during the year 2015 growing season. SenseFly eBee drone with RGB and NIR-R-G camera was used to collect data. Crop type classification accuracies of above 85% were easily achieved.

Improvement of enzymatic saccharification of Populus and switchgrass by combined pretreatment with steam and wet disk milling

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

Kumagai, Akio; Wu, Long; Iwamoto, Shinichiro

In this study, to reduce the recalcitrance of lignocellulosic biomass for subsequent biological processing, we pretreated energy crop feedstocks with mild steam treatment (ST; 130 and 150 °C for 60 min) and wet disk milling (WDM). We tested two phylogenetically different, but typical energy crop feedstocks: Populus trichocarpa and switchgrass ( Panicum virgatum). WDM after ST facilitated the fibrillation of both types of biomass, resulting in an increase of specific surface area, improved enzymatic saccharification yield, and decrease in cellulose crystallinity. Lastly, after steam treatment at 150 °C followed by 17 cycles of WDM, enzymatic hydrolysis resulted in almost completemore » glucan to glucose conversion in both feedstocks.« less

Improvement of enzymatic saccharification of Populus and switchgrass by combined pretreatment with steam and wet disk milling

DOE PAGES

Kumagai, Akio; Wu, Long; Iwamoto, Shinichiro; ...

2014-12-15

In this study, to reduce the recalcitrance of lignocellulosic biomass for subsequent biological processing, we pretreated energy crop feedstocks with mild steam treatment (ST; 130 and 150 °C for 60 min) and wet disk milling (WDM). We tested two phylogenetically different, but typical energy crop feedstocks: Populus trichocarpa and switchgrass ( Panicum virgatum). WDM after ST facilitated the fibrillation of both types of biomass, resulting in an increase of specific surface area, improved enzymatic saccharification yield, and decrease in cellulose crystallinity. Lastly, after steam treatment at 150 °C followed by 17 cycles of WDM, enzymatic hydrolysis resulted in almost completemore » glucan to glucose conversion in both feedstocks.« less

Biogas crops grown in energy crop rotations: Linking chemical composition and methane production characteristics.

PubMed

Herrmann, Christiane; Idler, Christine; Heiermann, Monika

2016-04-01

Methane production characteristics and chemical composition of 405 silages from 43 different crop species were examined using uniform laboratory methods, with the aim to characterise a wide range of crop feedstocks from energy crop rotations and to identify main parameters that influence biomass quality for biogas production. Methane formation was analysed from chopped and over 90 days ensiled crop biomass in batch anaerobic digestion tests without further pre-treatment. Lignin content of crop biomass was found to be the most significant explanatory variable for specific methane yields while the methane content and methane production rates were mainly affected by the content of nitrogen-free extracts and neutral detergent fibre, respectively. The accumulation of butyric acid and alcohols during the ensiling process had significant impact on specific methane yields and methane contents of crop silages. It is proposed that products of silage fermentation should be considered when evaluating crop silages for biogas production. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Development and characterization of transgenic dominant male sterile rice toward an outcross-based breeding system.

PubMed

Abe, Kiyomi; Oshima, Masao; Akasaka, Maiko; Konagaya, Ken-Ichi; Nanasato, Yoshihiko; Okuzaki, Ayako; Taniguchi, Yojiro; Tanaka, Junichi; Tabei, Yutaka

2018-03-01

Genomic selection is attracting attention in the field of crop breeding. To apply genomic selection effectively for autogamous (self-pollinating) crops, an efficient outcross system is desired. Since dominant male sterility is a powerful tool for easy and successive outcross of autogamous crops, we developed transgenic dominant male sterile rice ( Oryza sativa L.) using the barnase gene that is expressed by the tapetum-specific promoter BoA9 . Barnase -induced male sterile rice No. 10 (BMS10) was selected for its stable male sterility and normal growth characteristics. The BMS10 flowering habits, including heading date, flowering date, and daily flowering time of BMS10 tended to be delayed compared to wild type. When BMS10 and wild type were placed side-by-side and crossed under an open-pollinating condition, the seed-setting rate was <1.5%. When the clipping method was used to avoid the influence of late flowering habits, the seed-setting rate of BMS10 increased to a maximum of 86.4%. Although flowering synchronicity should be improved to increase the seed-setting rate, our results showed that this system can produce stable transgenic male sterility with normal female fertility in rice. The transgenic male sterile rice would promote a genomic selection-based breeding system in rice.

Dedicated Industrial Oilseed Crops as Metabolic Engineering Platforms for Sustainable Industrial Feedstock Production

PubMed Central

Zhu, Li-Hua; Krens, Frans; Smith, Mark A.; Li, Xueyuan; Qi, Weicong; van Loo, Eibertus N.; Iven, Tim; Feussner, Ivo; Nazarenus, Tara J.; Huai, Dongxin; Taylor, David C.; Zhou, Xue-Rong; Green, Allan G.; Shockey, Jay; Klasson, K. Thomas; Mullen, Robert T.; Huang, Bangquan; Dyer, John M.; Cahoon, Edgar B.

2016-01-01

Feedstocks for industrial applications ranging from polymers to lubricants are largely derived from petroleum, a non-renewable resource. Vegetable oils with fatty acid structures and storage forms tailored for specific industrial uses offer renewable and potentially sustainable sources of petrochemical-type functionalities. A wide array of industrial vegetable oils can be generated through biotechnology, but will likely require non-commodity oilseed platforms dedicated to specialty oil production for commercial acceptance. Here we show the feasibility of three Brassicaceae oilseeds crambe, camelina, and carinata, none of which are widely cultivated for food use, as hosts for complex metabolic engineering of wax esters for lubricant applications. Lines producing wax esters >20% of total seed oil were generated for each crop and further improved for high temperature oxidative stability by down-regulation of fatty acid polyunsaturation. Field cultivation of optimized wax ester-producing crambe demonstrated commercial utility of these engineered crops and a path for sustainable production of other industrial oils in dedicated specialty oilseeds. PMID:26916792

Dedicated Industrial Oilseed Crops as Metabolic Engineering Platforms for Sustainable Industrial Feedstock Production.

PubMed

Zhu, Li-Hua; Krens, Frans; Smith, Mark A; Li, Xueyuan; Qi, Weicong; van Loo, Eibertus N; Iven, Tim; Feussner, Ivo; Nazarenus, Tara J; Huai, Dongxin; Taylor, David C; Zhou, Xue-Rong; Green, Allan G; Shockey, Jay; Klasson, K Thomas; Mullen, Robert T; Huang, Bangquan; Dyer, John M; Cahoon, Edgar B

2016-02-26

Feedstocks for industrial applications ranging from polymers to lubricants are largely derived from petroleum, a non-renewable resource. Vegetable oils with fatty acid structures and storage forms tailored for specific industrial uses offer renewable and potentially sustainable sources of petrochemical-type functionalities. A wide array of industrial vegetable oils can be generated through biotechnology, but will likely require non-commodity oilseed platforms dedicated to specialty oil production for commercial acceptance. Here we show the feasibility of three Brassicaceae oilseeds crambe, camelina, and carinata, none of which are widely cultivated for food use, as hosts for complex metabolic engineering of wax esters for lubricant applications. Lines producing wax esters >20% of total seed oil were generated for each crop and further improved for high temperature oxidative stability by down-regulation of fatty acid polyunsaturation. Field cultivation of optimized wax ester-producing crambe demonstrated commercial utility of these engineered crops and a path for sustainable production of other industrial oils in dedicated specialty oilseeds.

Remote sensing inputs to water demand modeling

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

1975-01-01

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

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.

Climate change and farmers’ cropping patterns in Cemoro watershed area, Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

2018-03-01

Cropping pattern applied by farmers is usually based on the availability of water. Farmers cultivate rice when water is available. If it is unavailable, farmers will choose to plant crops that need less water. Climate change greatly affects to farmers in determining the cropping pattern as it alters the rainfall pattern and distribution in the region. This condition requires farmers to adjust the cropping pattern so that they can do the farming successfully. This study aims to examine the application of cropping patterns applied by the farmers in the Cemoro Watershed, Central Java, Indonesia. Descriptive analysis approach is employed in this research. The results showed that farmers’ cropping pattern is not based on the availability of water. However, it adopts a habit that has been practiced since long time ago or just adopt others farmer's habit. The cropping pattern applied by irrigated paddy farmers in Cemoro watershed area consists of two types: rice-rice-rice and rice-rice-secondary crops. Among those two types, most farmers apply the rice-rice-rice pattern. Meanwhile, there are three cropping patterns applied in the rain-land, namely rice-rice-rice, rice-rice-secondary crop, and rice-rice-fallow. The majority of farmers apply the second pattern (rice-rice-secondary crops). It was also found that farmers’ cropping pattern was not in accordance with the recommendation of the local government.

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 27 2012-07-01 2012-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 26 2011-07-01 2011-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 27 2013-07-01 2013-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 26 2014-07-01 2014-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

NASA Technical Reports Server (NTRS)

Lewis, David; Copenhaver, Ken; Anderson, Daniel; Hilbert, Kent

2007-01-01

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Combined Analysis of SENTINEL-1 and Rapideye Data for Improved Crop Type Classification: AN Early Season Approach for Rapeseed and Cereals

NASA Astrophysics Data System (ADS)

Lussem, U.; Hütt, C.; Waldhoff, G.

2016-06-01

Timely availability of crop acreage estimation is crucial for maintaining economic and ecological sustainability or modelling purposes. Remote sensing data has proven to be a reliable source for crop mapping and acreage estimation on parcel-level. However, when relying on a single source of remote sensing data, e.g. multispectral sensors like RapidEye or Landsat, several obstacles can hamper the desired outcome, for example cloud cover or haze. Another limitation may be a similarity in optical reflectance patterns of crops, especially in an early season approach by the end of March, early April. Usually, a reliable crop type map for winter-crops (winter wheat/rye, winter barley and rapeseed) in Central Europe can be obtained by using optical remote sensing data from late April to early May, given a full coverage of the study area and cloudless conditions. These prerequisites can often not be met. By integrating dual-polarimetric SAR-sensors with high temporal and spatial resolution, these limitations can be overcome. SAR-sensors are not influenced by clouds or haze and provide an additional source of information due to the signal-interaction with plant-architecture. The overall goal of this study is to investigate the contribution of Sentinel-1 SAR-data to regional crop type mapping for an early season map of disaggregated winter-crops for a subset of the Rur-Catchment in North Rhine-Westphalia (Germany). For this reason, RapidEye data and Sentinel-1 data are combined and the performance of Support Vector Machine and Maximum Likelihood classifiers are compared. Our results show that a combination of Sentinel-1 and RapidEye is a promising approach for most crops, but consideration of phenology for data selection can improve results. Thus the combination of optical and radar remote sensing data indicates advances for crop-type classification, especially when optical data availability is limited.

Crop yield responses to a hardwood biochar across varied soils and climate conditions

USDA-ARS?s Scientific Manuscript database

Biochars applied to soil for crop yield improvements have produced mixed results. The assorted crop yield responses may be linked to employing biochars with diverse chemical and physical characteristics. To clarify if biochars can improve crop yields, it may be prudent to evaluate one biochar type...

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

Partitioning Residue-derived and Residue-induced Emissions of N2O Using 15N-labelled Crop Residues

NASA Astrophysics Data System (ADS)

Farrell, R. E.; Carverhill, J.; Lemke, R.; Knight, J. D.

2014-12-01

Estimates of N2O emissions in Canada indicate that 17% of all agriculture-based emissions are associated with the decomposition of crop residues. However, research specific to the western Canadian prairies (including Saskatchewan) has shown that the N2O emission factor for N sources in this region typically ranges between 0.2 and 0.6%, which is well below the current IPCC default emission factor of 1.0%. Thus, it stands to reason that emissions from crop residues should also be lower than those calculated using the current IPCC emission factor. Current data indicates that residue decomposition, N mineralization and N2O production are affected by a number of factors such as C:N ratio and chemical composition of the residue, soil type, and soil water content; thus, a bench-scale incubation study was conducted to examine the effects of soil type and water content on N2O emissions associated with the decomposition of different crop residues. The study was carried out using soils from the Black, Dark Brown, Brown, and Gray soil zones and was conducted at both 50% and 70% water-filled pore space (WFPS); the soils were amended with 15N-labeled residues of wheat, pea, canola, and flax, or with an equivalent amount of 15N-labeled urea; 15N2O production was monitored using a Picarro G5101-i isotopic N2O analyzer. Crop residue additions to the soils resulted in both direct and indirect emissions of N2O, with residue derived emissions (RDE; measured as 15N2O) generally exceeding residue-induced emissions (RIE) at 50% WFPS—with RDEs ranging from 42% to 88% (mean = 58%) of the total N2O. Conversely, at 70% WFPS, RDEs were generally lower than RIEs—ranging from 21% to 83% (mean = 48%). Whereas both water content and soil type had an impact on N2O production, there was a clear and consistent trend in the emission factors for the residues; i.e., emissions were always greatest for the canola residue and lowest for the wheat residue and urea fertilizer; and intermediate for pea and flax. Results of this research demonstrate that—under the right environmental conditions—there is considerable potential for both direct and indirect N2O emissions during crop residue decomposition. Moreover, emission factors for the various crop residues tended to increase in the order: wheat ≤ urea < pea < flax << canola.

Plant genome editing made easy: targeted mutagenesis in model and crop plants using the CRISPR/Cas system.

PubMed

Belhaj, Khaoula; Chaparro-Garcia, Angela; Kamoun, Sophien; Nekrasov, Vladimir

2013-10-11

Targeted genome engineering (also known as genome editing) has emerged as an alternative to classical plant breeding and transgenic (GMO) methods to improve crop plants. Until recently, available tools for introducing site-specific double strand DNA breaks were restricted to zinc finger nucleases (ZFNs) and TAL effector nucleases (TALENs). However, these technologies have not been widely adopted by the plant research community due to complicated design and laborious assembly of specific DNA binding proteins for each target gene. Recently, an easier method has emerged based on the bacterial type II CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated) immune system. The CRISPR/Cas system allows targeted cleavage of genomic DNA guided by a customizable small noncoding RNA, resulting in gene modifications by both non-homologous end joining (NHEJ) and homology-directed repair (HDR) mechanisms. In this review we summarize and discuss recent applications of the CRISPR/Cas technology in plants.

Morphological and genetic characterization of a new cytoplasmic male sterility system (oxa CMS) in stem mustard (Brassica juncea).

PubMed

Heng, Shuangping; Liu, Sansan; Xia, Chunxiu; Tang, HongYu; Xie, Fei; Fu, Tingdong; Wan, Zhengjie

2018-01-01

KEY MESSAGE: oxa CMS is a new cytoplasmic male sterility type in Brassica juncea. oxa CMS is a cytoplasmic male sterility (CMS) line that has been widely used in the production and cultivation of stem mustard in the southwestern China. In this study, different CMS-type specific mitochondrial markers were used to confirm that oxa CMS is distinct from the pol CMS, ogu CMS, nap CMS, hau CMS, tour CMS, Moricandia arvensis CMS, orf220-type CMS, etc., that have been previously reported in Brassica crops. Pollen grains of the oxa CMS line are sterile with a self-fertility rate of almost 0% and the sterility strain rate and sterility degree of oxa CMS is 100% due to a specific flower structure and flowering habit. Scanning electron microscopy revealed that most pollen grains in mature anthers of the oxa CMS line are empty, flat and deflated. Semi-thin section further showed that the abortive stage of anther development in oxa CMS is initiated at the late uninucleate stage. Abnormally vacuolated microspores caused male sterility in the oxa CMS line. This cytological study combined with marker-assisted selection showed that oxa CMS is a novel CMS type in stem mustard (Brassica juncea). Interestingly, the abortive stage of oxa CMS is later than those in other CMS types reported in Brassica crops, and there is no negative effect on the oxa CMS line growth period. This study demonstrated that this novel oxa CMS has a unique flower structure with sterile pollen grains at the late uninucleate stage. Our results may help to uncover the mechanism of oxa CMS in Brassica juncea.

7 CFR 400.137 - Procedures for salary offset; types of collection.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Procedures for salary offset; types of collection. 400.137 Section 400.137 Agriculture Regulations of the Department of Agriculture (Continued) FEDERAL CROP...-Regulations for the 1986 and Succeeding Crop Years § 400.137 Procedures for salary offset; types of collection...

Single season effects of mixed-species cover crops on tomato health (cultivar Celebrity) in multi-state field trials

USDA-ARS?s Scientific Manuscript database

Cover crop use can help mitigate the deleterious effects of common cropping practices (e.g., tillage) and is, therefore, an important component of soil health maintenance. While known to be beneficial in the long term, the short-term effects of cover crops, specifically mixed-species cover crops in ...

Agricultural climate impacts assessment for economic modeling and decision support

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

2013-12-01

A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a mitigation level of 3.7 W/m2, as well as consideration of different levels of climate sensitivity (2, 3, 4.5 and 6oC) and different initial conditions for addressing uncertainty. Since the CMIP 3 and CMIP5 protocols did not include this mitigation level or consider alternative levels of climate sensitivity, additional climate projections were required. These two cases will be discussed to illustrate some of the trade-offs made in development of methodologies for climate impact assessments that are intended for a specific user or audience, and oriented towards addressing a specific topic of interest and providing useable results. This involvement of stakeholders from the design phase of climate impacts methodology serves to both define the appropriate method for the question at hand and also to engage and inform the stakeholders of the myriad options and uncertainties associated with different methodology choices. This type of engagement should benefit decision making in the long run through greater stakeholder understanding of the science of future climate model projections, scenarios, the climate impacts sector models and the types of outputs that can be generated by each along with the respective uncertainties at each step of the climate impacts assessment process.

Mapping Agricultural Land-Use Change in the U.S. 2008-2012

NASA Astrophysics Data System (ADS)

Lark, T.; Salmon, M.; Gibbs, H.

2014-12-01

Cultivation of corn and soybeans in the United States reached record levels following the biofuels boom of the late 2000s. Debate churns about whether expansion of these crops caused conversion of carbon-rich natural ecosystems or instead replaced other crops on existing fields. Here we describe a novel trajectory-based methodology for analyzing satellite-derived land cover products that enables integration of all available and intermediate-year data to improve consistency across data sources, time, and geographic boundaries. Using this approach, we track crop-specific expansion pathways across the conterminous U.S., 2008-2012, and identify the types, amount, and locations of all land converted to and from cropland. We find total cropland area increased by a net of 3 million acres over the study period, with gross land conversion to cropland 2.5 times greater than net expansion. Grasslands were the source of 77% of all new cropland, and we estimate 1.6 million acres (22%) were virgin grasslands that had not been previously planted or plowed. Corn was the most common crop planted directly on new land, as well as the largest indirect contributor to change through its displacement of other crops. Results identify holes in federal policies including improper enforcement of the Renewable Fuels Standard and insufficient coverage of recent Farm Bill provisions, suggesting current implementations of federal policies are likely insufficient to protect remaining grassland habitat.

Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950

PubMed Central

Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P

2015-01-01

Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Key Points Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands PMID:26709335

Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950.

PubMed

Imbach, P; Manrow, M; Barona, E; Barretto, A; Hyman, G; Ciais, P

2015-06-01

Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage. Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands.

Assessing the impact of climate variability on cropping patterns in Kenya

NASA Astrophysics Data System (ADS)

Wahome, A.; Ndungu, L. W.; Ndubi, A. O.; Ellenburg, W. L.; Flores Cordova, A. I.

2017-12-01

Climate variability coupled with over-reliance on rain-fed agricultural production on already strained land that is facing degradation and declining soil fertility; highly impacts food security in Africa. In Kenya, dependence on the approximately 20% of land viable for agricultural production under climate stressors such as variations in amount and frequency of rainfall within the main growing season in March-April-May(MAM) and changing temperatures influence production. With time, cropping zones have changed with the changing climatic conditions. In response, the needs of decision makers to effectively assess the current cropped areas and the changes in cropping patterns, SERVIR East and Southern Africa developed updated crop maps and change maps. Specifically, the change maps depict the change in cropping patterns between 2000 and 2015 with a further assessment done on important food crops such as maize. Between 2001 and 2015 a total of 5394km2 of land was converted to cropland with 3370km2 being conversion to maize production. However, 318 sq km were converted from maize to other crops or conversion to other land use types. To assess the changes in climatic conditions, climate parameters such as precipitation trends, variation and averages over time were derived from CHIRPs (Climate Hazards Infra-red Precipitation with stations) which is a quasi-global blended precipitation dataset available at a resolution of approximately 5km. Water Requirements Satisfaction Index (WRSI) water balance model was used to assess long term trends in crop performance as a proxy for maize yields. From the results, areas experiencing declining and varying precipitation with a declining WRSI index during the long rains displayed agricultural expansion with new areas being converted to cropland. In response to climate variability, farmers have converted more land to cropland instead of adopting better farming methods such as adopting drought resistant cultivars and using better farm inputs.

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

NASA Technical Reports Server (NTRS)

Price, Kevin P.; Nellis, M. Duane

1996-01-01

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Marginal cost curves for water footprint reduction in irrigated agriculture: guiding a cost-effective reduction of crop water consumption to a permit or benchmark level

NASA Astrophysics Data System (ADS)

Chukalla, Abebe D.; Krol, Maarten S.; Hoekstra, Arjen Y.

2017-07-01

Reducing the water footprint (WF) of the process of growing irrigated crops is an indispensable element in water management, particularly in water-scarce areas. To achieve this, information on marginal cost curves (MCCs) that rank management packages according to their cost-effectiveness to reduce the WF need to support the decision making. MCCs enable the estimation of the cost associated with a certain WF reduction target, e.g. towards a given WF permit (expressed in m3  ha-1 per season) or to a certain WF benchmark (expressed in m3  t-1 of crop). This paper aims to develop MCCs for WF reduction for a range of selected cases. AquaCrop, a soil-water-balance and crop-growth model, is used to estimate the effect of different management packages on evapotranspiration and crop yield and thus the WF of crop production. A management package is defined as a specific combination of management practices: irrigation technique (furrow, sprinkler, drip or subsurface drip); irrigation strategy (full or deficit irrigation); and mulching practice (no, organic or synthetic mulching). The annual average cost for each management package is estimated as the annualized capital cost plus the annual costs of maintenance and operations (i.e. costs of water, energy and labour). Different cases are considered, including three crops (maize, tomato and potato); four types of environment (humid in UK, sub-humid in Italy, semi-arid in Spain and arid in Israel); three hydrologic years (wet, normal and dry years) and three soil types (loam, silty clay loam and sandy loam). For each crop, alternative WF reduction pathways were developed, after which the most cost-effective pathway was selected to develop the MCC for WF reduction. When aiming at WF reduction one can best improve the irrigation strategy first, next the mulching practice and finally the irrigation technique. Moving from a full to deficit irrigation strategy is found to be a no-regret measure: it reduces the WF by reducing water consumption at negligible yield reduction while reducing the cost for irrigation water and the associated costs for energy and labour. Next, moving from no to organic mulching has a high cost-effectiveness, reducing the WF significantly at low cost. Finally, changing from sprinkler or furrow to drip or subsurface drip irrigation reduces the WF, but at a significant cost.

Influence of Agricultural Practice on Surface Temperature

NASA Astrophysics Data System (ADS)

Czajkowski, K.; Ault, T.; Hayase, R.; Benko, T.

2006-12-01

Changes in land uses/covers can have a significant effect on the temperature of the Earth's surface. Agricultural fields exhibit a significant change in land cover within a single year and from year to year as different crops are planted. These changes in agricultural practices including tillage practice and crop type influence the energy budget as reflected in differences in surface temperature. In this project, Landsat 5 and 7 imagery were used to investigate the influence of crop type and tillage practice on surface temperature in Iowa and NW Ohio. In particular, the three crop rotation of corn, soybeans and wheat, as well as no-till, conservation tillage and tradition tillage methods, were investigated. Crop type and conservation tillage practices were identified using supervised classification. Student surface temperature observations from the GLOBE program were used to correct for the effects of the atmosphere for some of the satellite thermal observations. Students took surface temperature observations in field sites near there schools using hand- held infrared thermometers.

Improving crop classification through attention to the timing of airborne radar acquisitions

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Protz, R.

1984-01-01

Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Contribution of land use to rodent flea load distribution in the plague endemic area of Lushoto District, Tanzania.

PubMed

Hieronimo, Proches; Kihupi, Nganga I; Kimaro, Didas N; Gulinck, Hubert; Mulungu, Loth S; Msanya, Balthazar M; Leirs, Herwig; Deckers, Jozef A

2014-07-01

Fleas associated with different rodent species are considered as the major vectors of bubonic plague, which is still rampant in different parts of the world. The objective of this study was to investigate the contribution of land use to rodent flea load distribution at fine scale in the plague endemic area of north-eastern Tanzania. Data was collected in three case areas namely, Shume, Lukozi and Mwangoi, differing in plague incidence levels. Data collection was carried out during both wet and dry seasons of 2012. Analysis of Variance and Boosted Regression Tree (BRT) statistical methods were used to clarify the relationships between fleas and specific land use characteristics. There was a significant variation (P ≤ 0.05) of flea indices in different land use types. Fallow and natural forest had higher flea indices whereas plantation forest mono-crop and mixed annual crops had the lowest flea indices among the aggregated land use types. The influence of individual land use types on flea indices was variable with fallow having a positive effect and land tillage showing a negative effect. The results also demonstrated a seasonal effect, part of which can be attributed to different land use practices such as application of pesticides, or the presence of grass strips around fields. These findings suggest that land use factors have a major influence on rodent flea abundance which can be taken as a proxy for plague infection risk. The results further point to the need for a comprehensive package that includes land tillage and crop type considerations on one hand and the associated human activities on the other, in planning and implementation of plague control interventions.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Effects of crop management, soil type, and climate on N2O emissions from Austrian Soils

NASA Astrophysics Data System (ADS)

Zechmeister-Boltenstern, Sophie; Sigmund, Elisabeth; Kasper, Martina; Kitzler, Barbara; Haas, Edwin; Wandl, Michael; Strauss, Peter; Poetzelsberger, Elisabeth; Dersch, Georg; Winiwarter, Wilfried; Amon, Barbara

2015-04-01

Within the project FarmClim ("Farming for a better climate") we assessed recent N2O emissions from two selected regions in Austria. Our aim was to deepen the understanding of Austrian N2O fluxes regarding region specific properties. Currently, N2O emissions are estimated with the IPCC default emission factor which only considers the amount of N-input as an influencing factor for N2O emissions. We evaluated the IPCC default emission factor for its validity under spatially distinct environmental conditions. For this two regions for modeling with LandscapeDNDC have been identified in this project. The benefit of using LandscapeDNDC is the detailed illustration of microbial processes in the soil. Required input data to run the model included daily climate data, vegetation properties, soil characteristics and land management. The analysis of present agricultural practices was basis for assessing the hot spots and hot moments of nitrogen emissions on a regional scale. During our work with LandscapeDNDC we were able to adapt specific model algorithms to Austrian agricultural conditions. The model revealed a strong dependency of N2O emissions on soil type. We could estimate how strongly soil texture affects N2O emissions. Based on detailed soil maps with high spatial resolution we calculated region specific contribution to N2O emissions. Accordingly we differentiated regions with deviating gas fluxes compared to the predictions by the IPCC inventory methodology. Taking region specific management practices into account (tillage, irrigation, residuals) calculation of crop rotation (fallow, catch crop, winter wheat, barley, winter barley, sugar beet, corn, potato, onion and rapeseed) resulted in N2O emissions differing by a factor of 30 depending on preceding crop and climate. A maximum of 2% of N fertilizer input was emitted as N2O. Residual N in the soil was a major factor stimulating N2O emissions. Interannual variability was affected by varying N-deposition even in case of constant management practices. High temporal resolution of model outputs enabled us to identify hot moments of N-turnover and total N2O emissions according to extreme weather events. We analysed how strongly these event based emissions, which are not accounted for by classical inventories, affect emission factors. The evaluation of the IPCC default emission factor for its validity under spatially distinct environmental conditions revealed which environmental conditions are responsible for major deviations of actual emissions from the theoretical values. Scrutinizing these conditions can help to improve climate reporting and greenhouse gas mitigation measures.

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

PubMed

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

2012-01-01

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

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

African Orphan Crops under Abiotic Stresses: Challenges and Opportunities.

PubMed

Tadele, Zerihun

2018-01-01

A changing climate, a growing world population, and a reduction in arable land devoted to food production are all problems facing the world food security. The development of crops that can yield under uncertain and extreme climatic and soil growing conditions can play a key role in mitigating these problems. Major crops such as maize, rice, and wheat are responsible for a large proportion of global food production but many understudied crops (commonly known as "orphan crops") including millets, cassava, and cowpea feed millions of people in Asia, Africa, and South America and are already adapted to the local environments in which they are grown. The application of modern genetic and genomic tools to the breeding of these crops can provide enormous opportunities for ensuring world food security but is only in its infancy. In this review, the diversity and types of understudied crops will be introduced, and the beneficial traits of these crops as well as their role in the socioeconomics of Africa will be discussed. In addition, the response of orphan crops to diverse types of abiotic stresses is investigated. A review of the current tools and their application to the breeding of enhanced orphan crops will also be described. Finally, few examples of global efforts on tackling major abiotic constraints in Africa are presented.

Vegetable production facility as a part of a closed life support system in a Russian Martian space flight scenario

NASA Astrophysics Data System (ADS)

Berkovich, Yu. A.; Smolyanina, S. O.; Krivobok, N. M.; Erokhin, A. N.; Agureev, A. N.; Shanturin, N. A.

2009-07-01

A Manned Mars Mission scenario had been developed in frame of the Project 1172 supported International Science & Technology Center in Moscow. The Mars transit vehicle (MTV) supposed to have a crew of 4-6 with Pilot Laboratory compartment volume of 185 m 3 and with inner diameter of 4.1 m. A vegetable production facility with power consumption up to 10 kW is being considered as a component of the life support system to supply crew members by fresh vegetables during the mission. Proposed design of conveyor-type plant growth facility (PGF) comprised of 4-modules. Each module has a cylindrical planting surface and spiral cylindrical LED assembly to provide a high specific productivity relative to utilized onboard resources. Each module has a growth chamber that will be from 0.7 m to 1.5 m in length, and a crop illuminated area from 1.7 m 2 to 4.0 m 2. Leafy crops (cabbage, lettuce, spinach, chard, etc.) have been selected for module 1, primarily because of the highest specific productivity per consumed resources. Dietitians have recommended also carrot crop for module 2, pepper for module 3 and tomato for module 4. The maximal total PGF light energy estimated as 1.16 kW and total power consumption as about 7 kW. The module 1 characteristics have been calculated using own experimental data, information from the best on ground plant growth experiments with artificial light were used to predict crop productivity and biomass composition in the another modules. 4-module PGF could produce nearly 0.32 kg per crew member per day of fresh edible biomass, which would be about 50% of recommended daily vegetable supplement. An average crop harvest index is estimated as 0.75. The MTV food system could be entirely closed in terms of vitamins C and A with help of the PGF. In addition the system could provide 10-25% of essential minerals and vitamins of group B, and about 20% of food fibers. The present state of plant growth technology allows formulating of requirements specification for the flight-qualified modules.

TAL effector-DNA specificity.

PubMed

Scholze, Heidi; Boch, Jens

2010-01-01

TAL effectors are important virulence factors of bacterial plant pathogenic Xanthomonas, which infect a wide variety of plants including valuable crops like pepper, rice, and citrus. TAL proteins are translocated via the bacterial type III secretion system into host cells and induce transcription of plant genes by binding to target gene promoters. Members of the TAL effector family differ mainly in their central domain of tandemly arranged repeats of typically 34 amino acids each with hypervariable di-amino acids at positions 12 and 13. We recently showed that target DNA-recognition specificity of TAL effectors is encoded in a modular and clearly predictable mode. The repeats of TAL effectors feature a surprising one repeat-to-one-bp correlation with different repeat types exhibiting a different DNA base pair specificity. Accordingly, we predicted DNA specificities of TAL effectors and generated artificial TAL proteins with novel DNA recognition specificities. We describe here novel artificial TALs and discuss implications for the DNA recognition specificity. The unique TAL-DNA binding domain allows design of proteins with potentially any given DNA recognition specificity enabling many uses for biotechnology.

Screening DNA chip and event-specific multiplex PCR detection methods for biotech crops.

PubMed

Lee, Seong-Hun

2014-11-01

There are about 80 biotech crop events that have been approved by safety assessment in Korea. They have been controlled by genetically modified organism (GMO) and living modified organism (LMO) labeling systems. The DNA-based detection method has been used as an efficient scientific management tool. Recently, the multiplex polymerase chain reaction (PCR) and DNA chip have been developed as simultaneous detection methods for several biotech crops' events. The event-specific multiplex PCR method was developed to detect five biotech maize events: MIR604, Event 3272, LY 038, MON 88017 and DAS-59122-7. The specificity was confirmed and the sensitivity was 0.5%. The screening DNA chip was developed from four endogenous genes of soybean, maize, cotton and canola respectively along with two regulatory elements and seven genes: P35S, tNOS, pat, bar, epsps1, epsps2, pmi, cry1Ac and cry3B. The specificity was confirmed and the sensitivity was 0.5% for four crops' 12 events: one soybean, six maize, three cotton and two canola events. The multiplex PCR and DNA chip can be available for screening, gene-specific and event-specific analysis of biotech crops as efficient detection methods by saving on workload and time. © 2014 Society of Chemical Industry. © 2014 Society of Chemical Industry.

Determination of actual crop evapotranspiration (ETc) and dual crop coefficients (Kc) for cotton, wheat and maize in Fergana Valley: integration of the FAO-56 approach and BUDGET

NASA Astrophysics Data System (ADS)

Kenjabaev, Shavkat; Dernedde, Yvonne; Frede, Hans-Georg; Stulina, Galina

2014-05-01

Determination of the actual crop evapotranspiration (ETc) during the growing period is important for accurate irrigation scheduling in arid and semi-arid regions. Development of a crop coefficient (Kc) can enhance ETc estimations in relation to specific crop phenological development. This research was conducted to determine daily and growth-stage-specific Kc and ETc values for cotton (Gossypium hirsutum L.), winter wheat (Triticum aestivum L.) and maize (Zea mays L.) for silage at fields in Fergana Valley (Uzbekistan). The soil water balance model - Budget with integration of the dual crop procedure of the FAO-56 was used to estimate the ETc and separate it into evaporation (Ec) and transpiration (Tc) components. An empirical equation was developed to determine the daily Kc values based on the estimated Ec and Tc. The ETc, Kc determination and comparison to existing FAO Kc values were performed based on 10, 5 and 6 study cases for cotton, wheat and maize, respectively. Mean seasonal amounts of crop water consumption in terms of ETc were 560±50, 509±27 and 243±39 mm for cotton, wheat and maize, respectively. The growth-stage-specific Kc for cotton, wheat and maize was 0.15, 0.27 and 0.11 at initial; 1.15, 1.03 and 0.56 at mid; and 0.45, 0.89 and 0.53 at late season stages. These values correspond to those reported by the FAO-56. Development of site specific Kc helps tremendously in irrigation management and furthermore provides precise water applications in the region. The developed simple approach to estimate daily Kc for the three main crops grown in the Fergana region was a first attempt to meet this issue. Keywords: Actual crop evapotranspiration, evaporation and transpiration, crop coefficient, model BUDGET, Fergana Valley.

Soybean Physiology Calibration in the Community Land Model

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Engineering Camelina sativa (L.) Crantz for enhanced oil and seed yields by combining diacylglycerol acyltransferase1 and glycerol-3-phosphate dehydrogenase expression.

PubMed

Chhikara, Sudesh; Abdullah, Hesham M; Akbari, Parisa; Schnell, Danny; Dhankher, Om Parkash

2018-05-01

Plant seed oil-based liquid transportation fuels (i.e., biodiesel and green diesel) have tremendous potential as environmentally, economically and technologically feasible alternatives to petroleum-derived fuels. Due to their nutritional and industrial importance, one of the major objectives is to increase the seed yield and oil production of oilseed crops via biotechnological approaches. Camelina sativa, an emerging oilseed crop, has been proposed as an ideal crop for biodiesel and bioproduct applications. Further increase in seed oil yield by increasing the flux of carbon from increased photosynthesis into triacylglycerol (TAG) synthesis will make this crop more profitable. To increase the oil yield, we engineered Camelina by co-expressing the Arabidopsis thaliana (L.) Heynh. diacylglycerol acyltransferase1 (DGAT1) and a yeast cytosolic glycerol-3-phosphate dehydrogenase (GPD1) genes under the control of seed-specific promoters. Plants co-expressing DGAT1 and GPD1 exhibited up to 13% higher seed oil content and up to 52% increase in seed mass compared to wild-type plants. Further, DGAT1- and GDP1-co-expressing lines showed significantly higher seed and oil yields on a dry weight basis than the wild-type controls or plants expressing DGAT1 and GPD1 alone. The oil harvest index (g oil per g total dry matter) for DGTA1- and GPD1-co-expressing lines was almost twofold higher as compared to wild type and the lines expressing DGAT1 and GPD1 alone. Therefore, combining the overexpression of TAG biosynthetic genes, DGAT1 and GPD1, appears to be a positive strategy to achieve a synergistic effect on the flux through the TAG synthesis pathway, and thereby further increase the oil yield. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Tree establishment in floodplain agroforestry practices

Treesearch

Daniel C. Dey; John M. Kabrick; Michael A. Gold

2004-01-01

The benefits of soil mounding, a cover crop, and various nursery stock types were evaluated for establishing pin and swamp white oaks in floodplain crop fields. The two stock types were 1-0 bareroot and large (3- and 5-gallon) container seedlings grown by the RPMTM method.

Combination of reversible male sterility and doubled haploid production by targeted inactivation of cytoplasmic glutamine synthetase in developing anthers and pollen.

PubMed

Ribarits, Alexandra; Mamun, A N K; Li, Shipeng; Resch, Tatiana; Fiers, Martijn; Heberle-Bors, Erwin; Liu, Chun-Ming; Touraev, Alisher

2007-07-01

Reversible male sterility and doubled haploid plant production are two valuable technologies in F(1)-hybrid breeding. F(1)-hybrids combine uniformity with high yield and improved agronomic traits, and provide self-acting intellectual property protection. We have developed an F(1)-hybrid seed technology based on the metabolic engineering of glutamine in developing tobacco anthers and pollen. Cytosolic glutamine synthetase (GS1) was inactivated in tobacco by introducing mutated tobacco GS genes fused to the tapetum-specific TA29 and microspore-specific NTM19 promoters. Pollen in primary transformants aborted close to the first pollen mitosis, resulting in male sterility. A non-segregating population of homozygous doubled haploid male-sterile plants was generated through microspore embryogenesis. Fertility restoration was achieved by spraying plants with glutamine, or by pollination with pollen matured in vitro in glutamine-containing medium. The combination of reversible male sterility with doubled haploid production results in an innovative environmentally friendly breeding technology. Tapetum-mediated sporophytic male sterility is of use in foliage crops, whereas microspore-specific gametophytic male sterility can be applied to any field crop. Both types of sterility preclude the release of transgenic pollen into the environment.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

An 11-year history of crop rotation into new perennial ryegrass and tall fescue

USDA-ARS?s Scientific Manuscript database

Converting multi-year remote sensing classification data into crop rotations is beneficial by defining the length of crop rotation cycles and the specific sequences of intervening crops grown between the final year of a grass seed stand and establishment of new perennial ryegrass and tall fescue see...

Tuning growth cycles of Brassica crops via natural antisense transcripts of BrFLC.

PubMed

Li, Xiaorong; Zhang, Shaofeng; Bai, Jinjuan; He, Yuke

2016-03-01

Several oilseed and vegetable crops of Brassica are biennials that require a prolonged winter cold for flowering, a process called vernalization. FLOWERING LOCUS C (FLC) is a central repressor of flowering. Here, we report that the overexpression of natural antisense transcripts (NATs) of Brassica rapa FLC (BrFLC) greatly shortens plant growth cycles. In rapid-, medium- and slow-cycling crop types, there are four copies of the BrFLC genes, which show extensive variation in sequences and expression levels. In Bre, a biennial crop type that requires vernalization, five NATs derived from the BrFLC2 locus are rapidly induced under cold conditions, while all four BrFLC genes are gradually down-regulated. The transgenic Bre lines overexpressing a long NAT of BrFLC2 do not require vernalization, resulting in a gradient of shortened growth cycles. Among them, a subset of lines both flower and set seeds as early as Yellow sarson, an annual crop type in which all four BrFLC genes have non-sense mutations and are nonfunctional in flowering repression. Our results demonstrate that the growth cycles of biennial crops of Brassica can be altered by changing the expression levels of BrFLC2 NATs. Thus, BrFLC2 NATs and their transgenic lines are useful for the genetic manipulation of crop growth cycles. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

African Orphan Crops under Abiotic Stresses: Challenges and Opportunities

PubMed Central

2018-01-01

A changing climate, a growing world population, and a reduction in arable land devoted to food production are all problems facing the world food security. The development of crops that can yield under uncertain and extreme climatic and soil growing conditions can play a key role in mitigating these problems. Major crops such as maize, rice, and wheat are responsible for a large proportion of global food production but many understudied crops (commonly known as “orphan crops”) including millets, cassava, and cowpea feed millions of people in Asia, Africa, and South America and are already adapted to the local environments in which they are grown. The application of modern genetic and genomic tools to the breeding of these crops can provide enormous opportunities for ensuring world food security but is only in its infancy. In this review, the diversity and types of understudied crops will be introduced, and the beneficial traits of these crops as well as their role in the socioeconomics of Africa will be discussed. In addition, the response of orphan crops to diverse types of abiotic stresses is investigated. A review of the current tools and their application to the breeding of enhanced orphan crops will also be described. Finally, few examples of global efforts on tackling major abiotic constraints in Africa are presented. PMID:29623231

Multiple transgene traits may create un-intended fitness effects in Brassica napus

EPA Science Inventory

Increasingly, genetically modified crops are being developed to express multiple “stacked” traits for different types of transgenes, for example, herbicide resistance, insect resistance, crop quality and resistance to environmental factors. The release of crops that express mult...

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

USGS Publications Warehouse

Draeger, William C.

1976-01-01

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

Climate change impacts on risks of groundwater pollution by herbicides: a regional scale assessment

NASA Astrophysics Data System (ADS)

Steffens, Karin; Moeys, Julien; Lindström, Bodil; Kreuger, Jenny; Lewan, Elisabet; Jarvis, Nick

2014-05-01

Groundwater contributes nearly half of the Swedish drinking water supply, which therefore needs to be protected both under present and future climate conditions. Pesticides are sometimes found in Swedish groundwater in concentrations exceeding the EU-drinking water limit and thus constitute a threat. The aim of this study was to assess the present and future risks of groundwater pollution at the regional scale by currently approved herbicides. We identified representative combinations of major crop types and their specific herbicide usage (product, dose and application timing) based on long-term monitoring data from two agricultural catchments in the South-West of Sweden. All these combinations were simulated with the regional version of the pesticide fate model MACRO (called MACRO-SE) for the periods 1970-1999 and 2070-2099 for a major crop production region in South West Sweden. To represent the uncertainty in future climate data, we applied a five-member ensemble based on different climate model projections downscaled with the RCA3-model (Swedish Meteorological and Hydrological Institute). In addition to the direct impacts of changes in the climate, the risks of herbicide leaching in the future will also be affected by likely changes in weed pressure and land use and management practices (e.g. changes in crop rotations and application timings). To assess the relative importance of such factors we performed a preliminary sensitivity analysis which provided us with a hierarchical structure for constructing future herbicide use scenarios for the regional scale model runs. The regional scale analysis gave average concentrations of herbicides leaching to groundwater for a large number of combinations of soils, crops and compounds. The results showed that future scenarios for herbicide use (more autumn-sown crops, more frequent multiple applications on one crop, and a shift from grassland to arable crops such as maize) imply significantly greater risks of herbicide leaching to groundwater in a changing climate, and that these indirect effects outweigh the direct effects of changes in climate driving variables. Due to the large uncertainties in climate change impact assessments, drawing firm conclusions is not possible, but this type of analysis provides indications of likely future concerns and can be used as an early-warning tool to inform the general public, responsible public authorities and decision makers.

Water Stress & Biomass Monitoring and SWAP Modeling of Irrigated Crops in Saratov Region of Russia

NASA Astrophysics Data System (ADS)

Zeyliger, Anatoly; Ermolaeva, Olga

2016-04-01

Development of modern irrigation technologies are balanced between the need to maximize production and the need to minimize water use which provides harmonious interaction of irrigated systems with closely-spaced environment. Thus requires an understanding of complex interrelationships between landscape and underground of irrigated and adjacent areas in present and future conditions aiming to minimize development of negative scenarios. In this way in each irrigated areas a combination of specific factors and drivers must be recognized and evaluated. Much can be obtained by improving the efficiency use of water applied for irrigation. Modern RS monitoring technologies offers the opportunity to develop and implement an effective irrigation control program permitting today to increase efficiency of irrigation water use. These technologies provide parameters with both high temporal and adequate spatial needed to monitor agrohydrological parameters of irrigated agricultural crops. Combination of these parameters with meteorological and biophysical parameters can be used to estimate crop water stress defined as ratio between actual (ETa) and potential (ETc) evapotranspiration. Aggregation of actual values of crop water stress with biomass (yield) data predicted by agrohydrological model based on weather forecasting and scenarios of irrigation water application may be used for indication of both rational timing and amount of irrigation water allocation. This type of analysis facilitating an efficient water management can be easily extended to irrigated areas by developing maps of water efficiency application serving as an irrigation advice system for farmers at his fields and as a decision support tool for the authorities on the large perimeter irrigation management. This contribution aims to communicate an illustrative explanation about the practical application of a data combination of agrohydrological modeling and ground & space based monitoring. For this aim some results of analyzing water stress during growing season of 2012 and yielded biomass of crops three types of crops alfalfa, corn and soya irrigated by sprinkling machines at left bank of Volga River at Saratov Region of Russia are presented and analyzed. For that a combination of data received from satellite, local meteorological station and farmers as well as SWAP model was used. Analyze of data sets of monitored water deficit of each crop averaged for irrigation period was done by linear regression with yielded biomass values. Following analyze of effectiveness of irrigation water application was done by SWAP agrohydrological model.

Detecting crop growth stages of maize and soybeans by using time-series MODIS data

NASA Astrophysics Data System (ADS)

Sakamoto, T.; Wardlow, B. D.; Gitelson, A. A.; Verma, S. B.; Suyker, A. E.; Arkebauer, T. J.

2009-12-01

The crop phenological stages are one of essential parameters for evaluating crop productivity based on a crop simulation model. In this study, we improved a method named the Wavelet-based Filter for detecting Crop Phenology (WFCP) for detecting the specific phenological dates of maize and soybeans. The improved method was applied to MODIS-derived Wide Dynamic Range Vegetation Index (WDRVI) over a 6-year period (2003 to 2008) for three experimental fields planted to either maize or soybeans as part of the Carbon Sequestration Program (CSP) at the University of Nebraska-Lincoln (UNL). Using the ground-based crop growth stage observations collected by the CSP, it was confirmed that the improved method can estimate the specific phenological dates of maize (V2.5, R1, R5 and R6) and soybeans (V1, R5, R6 and R7) with reasonable accuracy.

Improving preparedness of farmers to Climate Variability: A case study of Vidarbha region of Maharashtra, India

NASA Astrophysics Data System (ADS)

Swami, D.; Parthasarathy, D.; Dave, P.

2016-12-01

A key objective of the ongoing research is to understand the risk and vulnerability of agriculture and farming communities with respect to multiple climate change attributes, particularly monsoon variability and hydrology such as ground water availability. Climate Variability has always been a feature affecting Indian agriculture but the nature and characteristics of this variability is not well understood. Indian monsoon patterns are highly variable and most of the studies focus on larger domain such as Central India or Western coast (Ghosh et al., 2009) but district level analysis is missing i.e. the linkage between agriculture and climate variables at finer scale has not been investigated comprehensively. For example, Eastern Vidarbha region in Maharashtra is considered as one of the most agriculturally sensitive region in India, where every year a large number of farmers commit suicide. The main reasons for large number of suicides are climate related stressors such as droughts, hail storms, and monsoon variability aggravated with poor socio-economic conditions. Present study has tried to explore the areas in Vidarbha region of Maharashtra where famers and crop productivity, specifically cotton, sorghum, is highly vulnerable to monsoon variability, hydrological and socio-economic variables which are further modelled to determine the maximal contributing factor towards crops and farmers' vulnerability. After analysis using primary and secondary data, it will aid in decision making regarding field operations such as time of sowing, harvesting and irrigation requirements by optimizing the cropping pattern with climatic, hydrological and socio-economic variables. It also suggests the adaptation strategies to farmers regarding different types of cropping and water harvesting practices, optimized dates and timings for harvesting, sowing, water and nutrient requirements of particular crops according to the specific region. Primarily along with secondary analysis captured here can be highly beneficial for the farmers and policy makers while formulating agricultural policies related to climate change.

Global climate change increases risk of crop yield losses and food insecurity in the tropical Andes.

PubMed

Tito, Richard; Vasconcelos, Heraldo L; Feeley, Kenneth J

2018-02-01

One of the greatest current challenges to human society is ensuring adequate food production and security for a rapidly growing population under changing climatic conditions. Climate change, and specifically rising temperatures, will alter the suitability of areas for specific crops and cultivation systems. In order to maintain yields, farmers may be forced to change cultivation practices, the timing of cultivation, or even the type of crops grown. Alternatively, farmers can change the location where crops are cultivated (e.g., to higher elevations) to track suitable climates (in which case the plants will have to grow in different soils), as cultivated plants will otherwise have to tolerate warmer temperatures and possibly face novel enemies. We simulated these two last possible scenarios (for temperature increases of 1.3°C and 2.6°C) in the Peruvian Andes through a field experiment in which several traditionally grown varieties of potato and maize were planted at different elevations (and thus temperatures) using either the local soil or soil translocated from higher elevations. Maize production declined by 21%-29% in response to new soil conditions. The production of maize and potatoes declined by >87% when plants were grown under warmer temperatures, mainly as a result of the greater incidence of novel pests. Crop quality and value also declined under simulated migration and warming scenarios. We estimated that local farmers may experience severe economic losses of up to 2,300 US$ ha -1  yr -1 . These findings reveal that climate change is a real and imminent threat to agriculture and that there is a pressing need to develop effective management strategies to reduce yield losses and prevent food insecurity. Importantly, such strategies should take into account the influences of non-climatic and/or biotic factors (e.g., novel pests) on plant development. © 2017 John Wiley & Sons Ltd.

Estimating crop net primary production using inventory data and MODIS-derived parameters

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

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois inmore » years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.« less

Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

NASA Technical Reports Server (NTRS)

Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

2001-01-01

Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative sensitivity of each stress index; and (3) Comparative sensitivity of stress indices to realistic measurement uncertainties. We compare the stress indices calculated with several levels of spectral uncertainty (by shifting the wavelengths) and reflectance uncertainty (by systematically varying the reflectance retrieval code initialization).

Improving Snow Process Modeling with Satellite-Based Estimation of Near-Surface-Air-Temperature Lapse Rate

NASA Astrophysics Data System (ADS)

Wahome, A.; Ndungu, L. W.; Ndubi, A. O.; Ellenburg, W. L.; Flores Cordova, A. I.

2016-12-01

Climate variability coupled with over-reliance on rain-fed agricultural production on already strained land that is facing degradation and declining soil fertility; highly impacts food security in Africa. In Kenya, dependence on the approximately 20% of land viable for agricultural production under climate stressors such as variations in amount and frequency of rainfall within the main growing season in March-April-May(MAM) and changing temperatures influence production. With time, cropping zones have changed with the changing climatic conditions. In response, the needs of decision makers to effectively assess the current cropped areas and the changes in cropping patterns, SERVIR East and Southern Africa developed updated crop maps and change maps. Specifically, the change maps depict the change in cropping patterns between 2000 and 2015 with a further assessment done on important food crops such as maize. Between 2001 and 2015 a total of 5394km2 of land was converted to cropland with 3370km2 being conversion to maize production. However, 318 sq km were converted from maize to other crops or conversion to other land use types. To assess the changes in climatic conditions, climate parameters such as precipitation trends, variation and averages over time were derived from CHIRPs (Climate Hazards Infra-red Precipitation with stations) which is a quasi-global blended precipitation dataset available at a resolution of approximately 5km. Water Requirements Satisfaction Index (WRSI) water balance model was used to assess long term trends in crop performance as a proxy for maize yields. From the results, areas experiencing declining and varying precipitation with a declining WRSI index during the long rains displayed agricultural expansion with new areas being converted to cropland. In response to climate variability, farmers have converted more land to cropland instead of adopting better farming methods such as adopting drought resistant cultivars and using better farm inputs.

Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data

NASA Astrophysics Data System (ADS)

Jiao, Xianfeng; Kovacs, John M.; Shang, Jiali; McNairn, Heather; Walters, Dan; Ma, Baoluo; Geng, Xiaoyuan

2014-10-01

The aim of this paper is to assess the accuracy of an object-oriented classification of polarimetric Synthetic Aperture Radar (PolSAR) data to map and monitor crops using 19 RADARSAT-2 fine beam polarimetric (FQ) images of an agricultural area in North-eastern Ontario, Canada. Polarimetric images and field data were acquired during the 2011 and 2012 growing seasons. The classification and field data collection focused on the main crop types grown in the region, which include: wheat, oat, soybean, canola and forage. The polarimetric parameters were extracted with PolSAR analysis using both the Cloude-Pottier and Freeman-Durden decompositions. The object-oriented classification, with a single date of PolSAR data, was able to classify all five crop types with an accuracy of 95% and Kappa of 0.93; a 6% improvement in comparison with linear-polarization only classification. However, the time of acquisition is crucial. The larger biomass crops of canola and soybean were most accurately mapped, whereas the identification of oat and wheat were more variable. The multi-temporal data using the Cloude-Pottier decomposition parameters provided the best classification accuracy compared to the linear polarizations and the Freeman-Durden decomposition parameters. In general, the object-oriented classifications were able to accurately map crop types by reducing the noise inherent in the SAR data. Furthermore, using the crop classification maps we were able to monitor crop growth stage based on a trend analysis of the radar response. Based on field data from canola crops, there was a strong relationship between the phenological growth stage based on the BBCH scale, and the HV backscatter and entropy.

Impact of crop residue management on crop production and soil chemistry after seven years of crop rotation in temperate climate, loamy soils.

PubMed

Hiel, Marie-Pierre; Barbieux, Sophie; Pierreux, Jérôme; Olivier, Claire; Lobet, Guillaume; Roisin, Christian; Garré, Sarah; Colinet, Gilles; Bodson, Bernard; Dumont, Benjamin

2018-01-01

Society is increasingly demanding a more sustainable management of agro-ecosystems in a context of climate change and an ever growing global population. The fate of crop residues is one of the important management aspects under debate, since it represents an unneglectable quantity of organic matter which can be kept in or removed from the agro-ecosystem. The topic of residue management is not new, but the need for global conclusion on the impact of crop residue management on the agro-ecosystem linked to local pedo-climatic conditions has become apparent with an increasing amount of studies showing a diversity of conclusions. This study specifically focusses on temperate climate and loamy soil using a seven-year data set. Between 2008 and 2016, we compared four contrasting residue management strategies differing in the amount of crop residues returned to the soil (incorporation vs. exportation of residues) and in the type of tillage (reduced tillage (10 cm depth) vs. conventional tillage (ploughing at 25 cm depth)) in a field experiment. We assessed the impact of the crop residue management on crop production (three crops-winter wheat, faba bean and maize-cultivated over six cropping seasons), soil organic carbon content, nitrate ([Formula: see text]), phosphorus (P) and potassium (K) soil content and uptake by the crops. The main differences came primarily from the tillage practice and less from the restitution or removal of residues. All years and crops combined, conventional tillage resulted in a yield advantage of 3.4% as compared to reduced tillage, which can be partly explained by a lower germination rate observed under reduced tillage, especially during drier years. On average, only small differences were observed for total organic carbon (TOC) content of the soil, but reduced tillage resulted in a very clear stratification of TOC and also of P and K content as compared to conventional tillage. We observed no effect of residue management on the [Formula: see text] content, since the effect of fertilization dominated the effect of residue management. To confirm the results and enhance early tendencies, we believe that the experiment should be followed up in the future to observe whether more consistent changes in the whole agro-ecosystem functioning are present on the long term when managing residues with contrasted strategies.

Food safety assessment of planting patterns of four vegetable-type crops grown in soil contaminated by electronic waste activities.

PubMed

Liu, Ling; Hu, Liangliang; Tang, Jianjun; Li, Yuefang; Zhang, Qian; Chen, Xin

2012-01-01

A field experiment was conducted to assess the effect of crop and planting pattern on levels of cadmium (Cd), lead (Pb), and copper (Cu) in crops grown in soil contaminated by electronic waste. The crops were maize (Zea mays L. var. Shentian-1), tomato (Solanum lycopersicum L. var. Zhongshu-4), cabbage (Brassica oleracea L. var. Jingfeng-1), and pakchoi (Brassica chinensis (L.) Makino. var. Youdonger-Hangzhou). The planting patterns were crop monoculture, crop co-planted with a legume, and crop co-planted with another crop. Metal concentrations in the edible parts of the crops varied with types of metals and crops. Pb concentration was higher in leafy vegetables (cabbage and pakchoi) than in maize or tomato, Cd concentration was higher in tomato and pakchoi than in maize or cabbage, and Cu concentration was higher in maize and pakchoi than in tomato or cabbage. Metal concentrations in the edible part were also influenced by planting pattern. Relative to monoculture, co-planting and especially co-planting with Japanese clover tended to decrease Pb accumulation and increase Cd accumulation. According to the maximum permissible concentration (MPC) standard of the National Standard Agency in China, only maize (under all planting patterns) could be safely consumed. Because co-planting tended to increase Cd accumulation even in maize, however, the results suggest that maize monoculture is the optimal crop and planting pattern for this kind of contaminated soil. Copyright © 2011 Elsevier Ltd. All rights reserved.

CRISPR/Cas9 Mediated Genome Engineering for Improvement of Horticultural Crops

PubMed Central

Karkute, Suhas G.; Singh, Achuit K.; Gupta, Om P.; Singh, Prabhakar M.; Singh, Bijendra

2017-01-01

Horticultural crops are an important part of agriculture for food as well as nutritional security. However, several pests and diseases along with adverse abiotic environmental factors pose a severe threat to these crops by affecting their quality and productivity. This warrants the effective and accelerated breeding programs by utilizing innovative biotechnological tools that can tackle aforementioned issues. The recent technique of genome editing by Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated 9 (CRISPR/Cas9) has greatly advanced the breeding for crop improvement due to its simplicity and high efficiency over other nucleases such as Zinc Finger Nucleases and Transcription Activator Like Effector Nucleases. CRISPR/Cas9 tool contains a non-specific Cas9 nuclease and a single guide RNA that directs Cas9 to the specific genomic location creating double-strand breaks and subsequent repair process creates insertion or deletion mutations. This is currently the widely adopted tool for reverse genetics, and crop improvement in large number of agricultural crops. The use of CRISPR/Cas9 in horticultural crops is limited to few crops due to lack of availability of regeneration protocols and sufficient sequence information in many horticultural crops. In this review, the present status of applicability of CRISPR/Cas9 in horticultural crops was discussed along with the challenges and future potential for possible improvement of these crops for their yield, quality, and resistance to biotic and abiotic stress. PMID:28970844

CRISPR/Cas9 Mediated Genome Engineering for Improvement of Horticultural Crops.

PubMed

Karkute, Suhas G; Singh, Achuit K; Gupta, Om P; Singh, Prabhakar M; Singh, Bijendra

2017-01-01

Horticultural crops are an important part of agriculture for food as well as nutritional security. However, several pests and diseases along with adverse abiotic environmental factors pose a severe threat to these crops by affecting their quality and productivity. This warrants the effective and accelerated breeding programs by utilizing innovative biotechnological tools that can tackle aforementioned issues. The recent technique of genome editing by Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated 9 (CRISPR/Cas9) has greatly advanced the breeding for crop improvement due to its simplicity and high efficiency over other nucleases such as Zinc Finger Nucleases and Transcription Activator Like Effector Nucleases. CRISPR/Cas9 tool contains a non-specific Cas9 nuclease and a single guide RNA that directs Cas9 to the specific genomic location creating double-strand breaks and subsequent repair process creates insertion or deletion mutations. This is currently the widely adopted tool for reverse genetics, and crop improvement in large number of agricultural crops. The use of CRISPR/Cas9 in horticultural crops is limited to few crops due to lack of availability of regeneration protocols and sufficient sequence information in many horticultural crops. In this review, the present status of applicability of CRISPR/Cas9 in horticultural crops was discussed along with the challenges and future potential for possible improvement of these crops for their yield, quality, and resistance to biotic and abiotic stress.

A Site-sPecific Agricultural water Requirement and footprint Estimator (SPARE:WATER 1.0)

NASA Astrophysics Data System (ADS)

Multsch, S.; Al-Rumaikhani, Y. A.; Frede, H.-G.; Breuer, L.

2013-07-01

The agricultural water footprint addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). By considering site-specific properties when calculating the crop water footprint, this methodology can be used to support decision making in the agricultural sector on local to regional scale. We therefore developed the spatial decision support system SPARE:WATER that allows us to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirements and water footprints are assessed on a grid basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume inefficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water is defined as the water needed to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept, we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr-1 for 2008, with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional estimation of crop water footprints.

THE POTENTIAL ROLE OF REMOTE SENSING IN TRANSGENIC CROP MONITORING PROGRAMS

EPA Science Inventory

Sustainable agriculture combines efficient production with wise stewardship of the earth's resources. Development of environmentally benign production techniques is one focus of sustainable agriculture. The new transgenic crops producing toxic proteins that target specific crop p...

Assessment of Climate Change Impacts on Agricultural Water Demands and Crop Yields in California's Central Valley

NASA Astrophysics Data System (ADS)

Tansey, M. K.; Flores-Lopez, F.; Young, C. A.; Huntington, J. L.

2012-12-01

Long term planning for the management of California's water resources requires assessment of the effects of future climate changes on both water supply and demand. Considerable progress has been made on the evaluation of the effects of future climate changes on water supplies but less information is available with regard to water demands. Uncertainty in future climate projections increases the difficulty of assessing climate impacts and evaluating long range adaptation strategies. Compounding the uncertainty in the future climate projections is the fact that most readily available downscaled climate projections lack sufficient meteorological information to compute evapotranspiration (ET) by the widely accepted ASCE Penman-Monteith (PM) method. This study addresses potential changes in future Central Valley water demands and crop yields by examining the effects of climate change on soil evaporation, plant transpiration, growth and yield for major types of crops grown in the Central Valley of California. Five representative climate scenarios based on 112 bias corrected spatially downscaled CMIP 3 GCM climate simulations were developed using the hybrid delta ensemble method to span a wide range future climate uncertainty. Analysis of historical California Irrigation Management Information System meteorological data was combined with several meteorological estimation methods to compute future solar radiation, wind speed and dew point temperatures corresponding to the GCM projected temperatures and precipitation. Future atmospheric CO2 concentrations corresponding to the 5 representative climate projections were developed based on weighting IPCC SRES emissions scenarios. The Land, Atmosphere, and Water Simulator (LAWS) model was used to compute ET and yield changes in the early, middle and late 21st century for 24 representative agricultural crops grown in the Sacramento, San Joaquin and Tulare Lake basins. Study results indicate that changes in ET and yield vary between crops due to plant specific sensitivities to temperature, solar radiation and the vapor pressure deficits. Shifts in the growth period to earlier in the year, shortened growth period for annual crops as well as extended fall growth can also exert important influences. Projected increases in CO2 concentrations in the late 21st century exert very significant influences on ET and yield for many crops. To characterize potential impacts and the range of uncertainty, changes in total agricultural water demands and yields were computed assuming that current crop types and acreages in 21 Central Valley regional planning areas remained constant throughout the 21st century for each of the 5 representative future climate scenarios.

An integrated model for assessing both crop productivity and agricultural water resources at a large scale

NASA Astrophysics Data System (ADS)

Okada, M.; Sakurai, G.; Iizumi, T.; Yokozawa, M.

2012-12-01

Agricultural production utilizes regional resources (e.g. river water and ground water) as well as local resources (e.g. temperature, rainfall, solar energy). Future climate changes and increasing demand due to population increases and economic developments would intensively affect the availability of water resources for agricultural production. While many studies assessed the impacts of climate change on agriculture, there are few studies that dynamically account for changes in water resources and crop production. This study proposes an integrated model for assessing both crop productivity and agricultural water resources at a large scale. Also, the irrigation management to subseasonal variability in weather and crop response varies for each region and each crop. To deal with such variations, we used the Markov Chain Monte Carlo technique to quantify regional-specific parameters associated with crop growth and irrigation water estimations. We coupled a large-scale crop model (Sakurai et al. 2012), with a global water resources model, H08 (Hanasaki et al. 2008). The integrated model was consisting of five sub-models for the following processes: land surface, crop growth, river routing, reservoir operation, and anthropogenic water withdrawal. The land surface sub-model was based on a watershed hydrology model, SWAT (Neitsch et al. 2009). Surface and subsurface runoffs simulated by the land surface sub-model were input to the river routing sub-model of the H08 model. A part of regional water resources available for agriculture, simulated by the H08 model, was input as irrigation water to the land surface sub-model. The timing and amount of irrigation water was simulated at a daily step. The integrated model reproduced the observed streamflow in an individual watershed. Additionally, the model accurately reproduced the trends and interannual variations of crop yields. To demonstrate the usefulness of the integrated model, we compared two types of impact assessment of climate change on crop productivity in a watershed. The first was carried out by the large-scale crop model alone. The second was carried out by the integrated model of the large-scale crop model and the H08 model. The former projected that changes in temperature and precipitation due to future climate change would give rise to increasing the water stress in crops. Nevertheless, the latter projected that the increasing amount of agricultural water resources in the watershed would supply sufficient amount of water for irrigation, consequently reduce the water stress. The integrated model demonstrated the importance of taking into account the water circulation in watershed when predicting the regional crop production.

A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

NASA Astrophysics Data System (ADS)

Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

2012-12-01

Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter crop, however, has a moderately strong correlation with wet season start date (ρ = .577). In addition, winter crop yield (ton/ha) has a moderate correlation with wet season end date (ρ = .624), number of rainy days during the wet season (ρ = .492), and during the dry season (ρ = .410). Future work will assess which other factors influence cropping intensity (e.g. access to irrigation among many other), since a complex interplay of bio-physical and socio-economic factors governs the decision-making at the farm-level, ultimately leading to inter-annual variability in cropping intensity and/or yield.

Seed crops of forest trees in the pine region of California

Treesearch

H.A Fowells; G.H. Schubert

1956-01-01

To provide a better basis for silvicultural practices in the pine region of California, we are reporting the results of 28 years of study of seed crops. The study covered the development of cones, periodicity of cone crops, types of trees bearing cones, climatic and biotic factors affecting cone crops, and the dispersal of seed. The findings reported here should help...

Stem-quality changes on young, mixed upland hardwoods after crop-tree release

Treesearch

David L. Sonderman; David L. Sonderman

1987-01-01

Relative change of several types of stem defects was studied over an 8-year period to determine the effects of crop-tree thinning on the development of tree quality. Special interest was given to changes in relative quality associated with defect indicators of crop trees compared to trees in unthinned plots. The relative quality classes of the crop trees went from...

The development, evaluation, and application of O3 flux and flux-response models for additional agricultural crops

Treesearch

L. D. Emberson; W. J. Massman; P. Buker; G. Soja; I. Van De Sand; G. Mills; C. Jacobs

2006-01-01

Currently, stomatal O3 flux and flux-response models only exist for wheat and potato (LRTAP Convention, 2004), as such there is a need to extend these models to include additional crop types. The possibility of establishing robust stomatal flux models for five agricultural crops (tomato, grapevine, sugar beet, maize and sunflower) was investigated. These crops were...

Imputing historical statistics, soils information, and other land-use data to crop area

NASA Technical Reports Server (NTRS)

Perry, C. R., Jr.; Willis, R. W.; Lautenschlager, L.

1982-01-01

In foreign crop condition monitoring, satellite acquired imagery is routinely used. To facilitate interpretation of this imagery, it is advantageous to have estimates of the crop types and their extent for small area units, i.e., grid cells on a map represent, at 60 deg latitude, an area nominally 25 by 25 nautical miles in size. The feasibility of imputing historical crop statistics, soils information, and other ancillary data to crop area for a province in Argentina is studied.

[Use of Remote Sensing for Crop and Soil Analysis

NASA Technical Reports Server (NTRS)

Johannsen, Chris J.

1997-01-01

The primary agricultural objective of this research is to determine what soil and crop information can be verified from remotely sensed images during the growing season. Specifically: (1) Elements of crop stress due to drought, weeds, disease and nutrient deficiencies will be documented with ground truth over specific agricultural sites and (2) Use of remote sensing with GPS and GIS technology for providing a safe and environmentally friendly application of fertilizers and chemicals will be documented.

Tradeoffs between vigor and yield for crops grown under different management systems

NASA Astrophysics Data System (ADS)

Simic Milas, Anita; Keller Vincent, Robert; Romanko, Matthew; Feitl, Melina; Rupasinghe, Prabha

2016-04-01

Remote sensing can provide an effective means for rapid and non-destructive monitoring of crop status and biochemistry. Monitoring pattern of traditional vigor algorithms generated from Landsat 8 OLI satellite data represents a robust method that can be widely used to differentiate the status of crops, as well as to monitor nutrient uptake functionality of differently treated seeds grown under different managements. This study considers 24 factorial parcels of winter wheat in 2013, corn in 2014, and soybeans in 2015, grown under four different types of agricultural management. The parcels are located at the Kellogg Biological Station, Long-Term Ecological Research site in the State of Michigan USA. At maturity, the organic crops exhibit significantly higher vigor and significantly lower yield than conventionally managed crops under different treatments. While organic crops invest in their metabolism at the expense of their yield, the conventional crops manage to increase their yield at the expense of their vigor. Landsat 8 OLI is capable of 1) differentiating the biochemical status of crops under different treatments at maturity, and 2) monitoring the tradeoff between crop yield and vigor that can be controlled by the seed treatments and proper conventional applications, with the ultimate goal of increasing food yield and food availability, and 3) distinguishing between organic and conventionally treated crops. Timing, quantity and types of herbicide applications have a great impact on early and pre-harvest vigor, maturity and yield of conventionally treated crops. Satellite monitoring using Landsat 8 is an optimal tool for coordinating agricultural applications, soil practices and genetic coding of the crop to produce higher yield as well as have early crop maturity, desirable in northern climates.

Crop yield response to increasing biochar rates

USDA-ARS?s Scientific Manuscript database

The benefit or detriment to crop yield from biochar application varies with biochar type/rate, soil, crop, or climate. The objective of this research was to identify yield response of cotton (Gossypium hirsutum L.), corn (Zea mayes L.), and peanut (Arachis hypogaea L.) to hardwood biochar applied at...

Towards social acceptance of plant breeding by genome editing.

PubMed

Araki, Motoko; Ishii, Tetsuya

2015-03-01

Although genome-editing technologies facilitate efficient plant breeding without introducing a transgene, it is creating indistinct boundaries in the regulation of genetically modified organisms (GMOs). Rapid advances in plant breeding by genome-editing require the establishment of a new global policy for the new biotechnology, while filling the gap between process-based and product-based GMO regulations. In this Opinion article we review recent developments in producing major crops using genome-editing, and we propose a regulatory model that takes into account the various methodologies to achieve genetic modifications as well as the resulting types of mutation. Moreover, we discuss the future integration of genome-editing crops into society, specifically a possible response to the 'Right to Know' movement which demands labeling of food that contains genetically engineered ingredients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impacts of Near-Term Climate Change on Irrigation Demands and Crop Yields in the Columbia River Basin

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K. J.; Stockle, C. O.; Nelson, R. L.; Kruger, C. E.; Brady, M. P.; Malek, K.; Dinesh, S. T.; Barber, M. E.; Hamlet, A. F.; Yorgey, G. G.; Adam, J. C.

2018-03-01

Adaptation to a changing climate is critical to address future global food and water security challenges. While these challenges are global, successful adaptation strategies are often generated at regional scales; therefore, regional-scale studies are critical to inform adaptation decision making. While climate change affects both water supply and demand, water demand is relatively understudied, especially at regional scales. The goal of this work is to address this gap, and characterize the direct impacts of near-term (for the 2030s) climate change and elevated CO2 levels on regional-scale crop yields and irrigation demands for the Columbia River basin (CRB). This question is addressed through a coupled crop-hydrology model that accounts for site-specific and crop-specific characteristics that control regional-scale response to climate change. The overall near-term outlook for agricultural production in the CRB is largely positive, with yield increases for most crops and small overall increases in irrigation demand. However, there are crop-specific and location-specific negative impacts as well, and the aggregate regional response of irrigation demands to climate change is highly sensitive to the spatial crop mix. Low-value pasture/hay varieties of crops—typically not considered in climate change assessments—play a significant role in determining the regional response of irrigation demands to climate change, and thus cannot be overlooked. While, the overall near-term outlook for agriculture in the region is largely positive, there may be potential for a negative outlook further into the future, and it is important to consider this in long-term planning.

Origins of food crops connect countries worldwide.

USDA-ARS?s Scientific Manuscript database

Crop genetic diversity is concentrated within specific geographic regions worldwide. While access to this diversity is critical to continued increases in agricultural productivity, the geopolitical significance of the geography of crop diversity has not been quantified. We assess the degree to which...

Molecular and morphological differentiation between the crop and weedy types in velvetleaf (Abutilon theophrasti Medik.) using a chloroplast DNA marker: seed source of the present invasive velvetleaf in Japan.

PubMed

Kurokawa, S; Shibaike, H; Akiyama, H; Yoshimura, Y

2004-12-01

A comparison of chloroplast DNA (cpDNA) sequences was carried out between the crop and weed types of Abutilon theophrasti to clarify the seed source of the present weedy velvetleaf in Japan. A sequencing analysis of approx. 6% of the chloroplast genome (ca 10 kbp) detected three nucleotide substitutions, one six-base-pair insertion/deletion (indel) and one 30-base pair inversion, which distinguish two haplotypes of cpDNA. A PCR-based survey of the indel and the inversion revealed that the 93 accessions of velvetleaf collected from the world could be divided into two groups. A morphological marker (capsule color) could be used to discriminate the crop type and the weed type, and hence, along with cpDNA haplotype, to distinguish three genotypes (Type I, II, and III). All Japanese cultivars and crop accessions from other countries were Type I. Weed types were divided into Type II and III. All of the samples from the USA, and the samples taken from grain imports to Japan were Type III. Since most of the weedy types distributed in Japan were of Type III, it is argued that they were introduced as seeds in the imported grain. We also found that the Type II plants sporadically occurred in Japan. It is suggested that they originated as hybrids, with indigenous cultivars as the maternal ancestor. Such hybrids must have survived since the cessation of velvetleaf cultivation about a century ago.

Identification of bacteria in total mixed ration silage produced with and without crop silage as an ingredient.

PubMed

Nishino, Naoki; Ogata, Yu; Han, Hongyan; Yamamoto, Yasunari

2015-01-01

As a forage source for total mixed ration (TMR) silage production, locally produced crop silage is now used in addition to imported hay. This type of TMR ensiling is regarded as a two-step fermentation process; hence, a survey was carried out to determine whether the bacteria in crop silage affect the subsequent TMR ensiling. Fermentation product contents and bacterial community were determined for TMR silage and its ingredient silages collected in August, October and November. August product contained corn, sorghum and Italian ryegrass silages, October product had wheat silage exclusively and November product did not include any crop silages. Acetic acid, lactic acid, 2,3-butanediol and ethanol were predominant fermentation products in corn, sorghum, Italian ryegrass and wheat silages, respectively. Robust lactic acid fermentation was seen in TMR silage, even if acetate-type and alcohol-type silages were mixed as ingredients. The finding that bacterial community of the TMR silage appeared unrelated to those of ingredient silage supported this. Silages of various fermentation types can therefore be formulated without interfering with lactate-type fermentation in TMR silage. © 2014 Japanese Society of Animal Science.

The effects of different types of crop straw on the transformation of pentachlorophenol in flooded paddy soil.

PubMed

Lin, Jiajiang; Meng, Jun; He, Yan; Xu, Jianming; Chen, Zuliang; Brookes, Philip C

2018-02-01

The incorporation of various types of crop straw to agricultural soils has long been practiced to improve soil fertility. However, the effects of crop straw on the fate of organo-chlorine pesticides in flooded paddy soils are not well understood. The dechlorination of pentachlorophenol (PCP) in four vertical profiles (0-10, 10-20, 20-30, 30-50 mm depth) of two flooded paddy soils, a Plinthudult (Soil 1) and a Tropudult (Soil 2) was investigated following the application of four crop straws (rice, wheat, rape and Chinese milk vetch) to them. In all treatments, PCP dechlorination decreased with increasing soil depth. In the crop straw treatments, PCP was almost completely dechlorinated within 60 days, and rapidly transformed to 2,3,4,5-tetrachlorophenol, and further to 3,4,5-trichlorophenol. Further dechlorination of 3,4,5-trichlorophenol also occurred in all treatments except for the rape straw. It is possible that the NH 4 + and NO 3 - derived from the straw are responsible for the inhibition of the 3,4,5-trichlorophenol dechlorination. The reduction of Fe (III) and SO 4 2- increased following application of the crop straws. The RDA analysis indicated that the Fe (III) reducing bacteria might be involved in the ortho-dechlorination, while SO 4 2- reducing bacteria were involved in para- and meta-dechlorination of PCP. The complete detoxification of PCP depended upon both the crop straw type and soil properties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Nitrogen in Streams: A Comparison of Two Estimates of Fertilizer Application

NASA Astrophysics Data System (ADS)

Mehaffey, M.; Neale, A.

2011-12-01

Decision makers frequently rely on water and air quality models to develop nutrient management strategies. Obviously, the results of these models (e.g., SWAT, SPARROW, CMAQ) are only as good as the nutrient source input data and recently the Nutrient Innovations Task Group has called for a better accounting of nonpoint nutrient sources. Currently, modelers frequently rely on county level fertilizer sales records combined with acreage of crops to estimate nitrogen sources from fertilizer for counties or watersheds. However, since fertilizer sales data are based on reported amounts they do not necessarily reflect actual use on the fields. In addition the reported sales data quality varies by state resulting in differing accuracy between states. In this study we examine an alternative method potentially providing a more uniform, spatially explicit, estimate of fertilizer use. Our nitrogen application data is estimated at a 30m pixel resolution which allows for scalable inputs for use in water and air quality models. To develop this dataset we combined raster data from the National Cropland data layer (CDL) data with the National Land Cover Data (NLCD). This process expanded the NLCD's 'cultivated crops' classes to included major grains, cover crops, and vegetable and fruits. The Agriculture Resource Management Survey chemical fertilizer application rate data were summarized by crop type and year for each state, encompassing the corn, soybean, spring wheat, and winter wheat crop types (ARMS, 2002-2005). The chemical fertilizer application rate data were then used to estimate annual application parameters for nitrogen, phosphate, potash, herbicide, pesticide, and total pesticide, all expressed on a mass-per-unit-crop-area basis for each state for each crop type. By linking crop types to nitrogen application rates, we can better estimate where applied fertilizer would likely be in excess of the amounts used by crops or where conservation practices may improve retention and uptake helping offset the impacts to water. To test the accuracy of our finer resolution nitrogen application data, we compare its ability to predict nitrogen concentrations in streams with the ability of the county sales data to do the same.

Estimation of different data compositions for early-season crop type classification.

PubMed

Hao, Pengyu; Wu, Mingquan; Niu, Zheng; Wang, Li; Zhan, Yulin

2018-01-01

Timely and accurate crop type distribution maps are an important inputs for crop yield estimation and production forecasting as multi-temporal images can observe phenological differences among crops. Therefore, time series remote sensing data are essential for crop type mapping, and image composition has commonly been used to improve the quality of the image time series. However, the optimal composition period is unclear as long composition periods (such as compositions lasting half a year) are less informative and short composition periods lead to information redundancy and missing pixels. In this study, we initially acquired daily 30 m Normalized Difference Vegetation Index (NDVI) time series by fusing MODIS, Landsat, Gaofen and Huanjing (HJ) NDVI, and then composited the NDVI time series using four strategies (daily, 8-day, 16-day, and 32-day). We used Random Forest to identify crop types and evaluated the classification performances of the NDVI time series generated from four composition strategies in two studies regions from Xinjiang, China. Results indicated that crop classification performance improved as crop separabilities and classification accuracies increased, and classification uncertainties dropped in the green-up stage of the crops. When using daily NDVI time series, overall accuracies saturated at 113-day and 116-day in Bole and Luntai, and the saturated overall accuracies (OAs) were 86.13% and 91.89%, respectively. Cotton could be identified 40∼60 days and 35∼45 days earlier than the harvest in Bole and Luntai when using daily, 8-day and 16-day composition NDVI time series since both producer's accuracies (PAs) and user's accuracies (UAs) were higher than 85%. Among the four compositions, the daily NDVI time series generated the highest classification accuracies. Although the 8-day, 16-day and 32-day compositions had similar saturated overall accuracies (around 85% in Bole and 83% in Luntai), the 8-day and 16-day compositions achieved these accuracies around 155-day in Bole and 133-day in Luntai, which were earlier than the 32-day composition (170-day in both Bole and Luntai). Therefore, when the daily NDVI time series cannot be acquired, the 16-day composition is recommended in this study.

Estimation of different data compositions for early-season crop type classification

PubMed Central

Wu, Mingquan; Wang, Li; Zhan, Yulin

2018-01-01

Timely and accurate crop type distribution maps are an important inputs for crop yield estimation and production forecasting as multi-temporal images can observe phenological differences among crops. Therefore, time series remote sensing data are essential for crop type mapping, and image composition has commonly been used to improve the quality of the image time series. However, the optimal composition period is unclear as long composition periods (such as compositions lasting half a year) are less informative and short composition periods lead to information redundancy and missing pixels. In this study, we initially acquired daily 30 m Normalized Difference Vegetation Index (NDVI) time series by fusing MODIS, Landsat, Gaofen and Huanjing (HJ) NDVI, and then composited the NDVI time series using four strategies (daily, 8-day, 16-day, and 32-day). We used Random Forest to identify crop types and evaluated the classification performances of the NDVI time series generated from four composition strategies in two studies regions from Xinjiang, China. Results indicated that crop classification performance improved as crop separabilities and classification accuracies increased, and classification uncertainties dropped in the green-up stage of the crops. When using daily NDVI time series, overall accuracies saturated at 113-day and 116-day in Bole and Luntai, and the saturated overall accuracies (OAs) were 86.13% and 91.89%, respectively. Cotton could be identified 40∼60 days and 35∼45 days earlier than the harvest in Bole and Luntai when using daily, 8-day and 16-day composition NDVI time series since both producer’s accuracies (PAs) and user’s accuracies (UAs) were higher than 85%. Among the four compositions, the daily NDVI time series generated the highest classification accuracies. Although the 8-day, 16-day and 32-day compositions had similar saturated overall accuracies (around 85% in Bole and 83% in Luntai), the 8-day and 16-day compositions achieved these accuracies around 155-day in Bole and 133-day in Luntai, which were earlier than the 32-day composition (170-day in both Bole and Luntai). Therefore, when the daily NDVI time series cannot be acquired, the 16-day composition is recommended in this study. PMID:29868265

Crop-associated virus reduces the rooting depth of non-crop perennial native grass more than non-crop-associated virus with known viral suppressor of RNA silencing (VSR).

PubMed

Malmstrom, Carolyn M; Bigelow, Patrick; Trębicki, Piotr; Busch, Anna K; Friel, Colleen; Cole, Ellen; Abdel-Azim, Heba; Phillippo, Colin; Alexander, Helen M

2017-09-15

As agricultural acreage expanded and came to dominate landscapes across the world, viruses gained opportunities to move between crop and wild native plants. In the Midwestern USA, virus exchange currently occurs between widespread annual Poaceae crops and remnant native perennial prairie grasses now under consideration as bioenergy feedstocks. In this region, the common aphid species Rhopalosiphum padi L. (the bird cherry-oat aphid) transmits several virus species in the family Luteoviridae, including Barley yellow dwarf virus (BYDV-PAV, genus Luteovirus) and Cereal yellow dwarf virus (CYDV-RPV and -RPS, genus Polerovirus). The yellow dwarf virus (YDV) species in these two genera share genetic similarities in their 3'-ends, but diverge in the 5'-regions. Most notably, CYDVs encode a P0 viral suppressor of RNA silencing (VSR) absent in BYDV-PAV. Because BYDV-PAV has been reported more frequently in annual cereals and CYDVs in perennial non-crop grasses, we examine the hypothesis that the viruses' genetic differences reflect different affinities for crop and non-crop hosts. Specifically, we ask (i) whether CYDVs might persist within and affect a native non-crop grass more strongly than BYDV-PAV, on the grounds that the polerovirus VSR could better moderate the defenses of a well-defended perennial, and (ii) whether the opposite pattern of effects might occur in a less defended annual crop. Because previous work found that the VSR of CYDV-RPS possessed greater silencing suppressor efficiency than that of CYDV-RPV, we further explored (iii) whether a novel grass-associated CYDV-RPS isolate would influence a native non-crop grass more strongly than a comparable CYDV-RPV isolate. In growth chamber studies, we found support for this hypothesis: only grass-associated CYDV-RPS stunted the shoots and crowns of Panicum virgatum L. (switchgrass), a perennial native North American prairie grass, whereas crop-associated BYDV-PAV (and coinfection with BYDV-PAV and CYDV-RPS) most stunted annual Avena sativa L. (oats). These findings suggest that some of the diversity in grass-infecting Luteoviridae reflects viral capacity to modulate defenses in different host types. Intriguingly, while all virus treatments also reduced root production in both host species, only crop-associated BYDV-PAV (or co-infection) reduced rooting depths. Such root effects may increase host susceptibility to drought, and indicate that BYDV-PAV pathogenicity is determined by something other than a P0 VSR. These findings contribute to growing evidence that pathogenic crop-associated viruses may harm native species as well as crops. Critical next questions include the extent to which crop-associated selection pressures drive viral pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Low altitude remote sensing technologies for crop stress monitoring: a case study on spatial and temporal monitoring of irrigated pinto bean

USDA-ARS?s Scientific Manuscript database

Site-specific crop management is a promising approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of high resolution crop data at critical growth stages is a key for real-time data-driven decisions during the production season. The goal of this study ...

An overview of CERES-Sorghum as implemented in the cropping systems model version 4.5

USDA-ARS?s Scientific Manuscript database

Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important grain crop globally. It stands out for its diversity of plant types, end-uses, and roles in cropping systems. This diversity presents opportunities but also complicates evaluation of production options, especially under climate uncert...

40 CFR 158.100 - Pesticide use patterns.

Code of Federal Regulations, 2010 CFR

2010-07-01

... use patterns. There are six broad use categories used in the data tables. The six broad categories... outdoor uses, and indoor uses of all types. The 6 broad use categories are further subdivided into 12... part are: (1) Terrestrial food crop use. (2) Terrestrial feed crop use. (3) Terrestrial nonfood crop...

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Correlations between the modelled potato crop yield and the general atmospheric circulation

NASA Astrophysics Data System (ADS)

Sepp, Mait; Saue, Triin

2012-07-01

Biology-related indicators do not usually depend on just one meteorological element but on a combination of several weather indicators. One way to establish such integral indicators is to classify the general atmospheric circulation into a small number of circulation types. The aim of present study is to analyse connections between general atmospheric circulation and potato crop yield in Estonia. Meteorologically possible yield (MPY), calculated by the model POMOD, is used to characterise potato crop yield. Data of three meteorological stations and the biological parameters of two potato sorts were applied to the model, and 73 different classifications of atmospheric circulation from catalogue 1.2 of COST 733, domain 05 are used to qualify circulation conditions. Correlation analysis showed that there is at least one circulation type in each of the classifications with at least one statistically significant (99%) correlation with potato crop yield, whether in Kuressaare, Tallinn or Tartu. However, no classifications with circulation types correlating with MPY in all three stations at the same time were revealed. Circulation types inducing a decrease in the potato crop yield are more clearly represented. Clear differences occurred between the observed geographical locations as well as between the seasons: derived from the number of significant circulation types, summer and Kuressaare stand out. Of potato varieties, late 'Anti' is more influenced by circulation. Analysis of MSLP maps of circulation types revealed that the seaside stations (Tallinn, Kuressaare) suffer from negative effects of anti-cyclonic conditions (drought), while Tartu suffers from the cyclonic activity (excessive water).

20 CFR 220.144 - Evaluation guides for a self-employed claimant.

Code of Federal Regulations, 2012 CFR

2012-04-01

... farm. (B) The claimant will have presented strong evidence that he or she is materially participating... land. (iii) Production. The term “production” refers to the physical work performed and the expenses... on matters, such as rotation of crops, the type of crops to be grown, the type of livestock to be...

Conjecture regarding posttranslational modifications to the arabidopsis type I proton-pumping pyrophosphatase (AVP1)

USDA-ARS?s Scientific Manuscript database

Agbiotechnology uses genetic engineering to improve the output and value of crops. Altering the expression of the plant Type I Proton-pumping Pyrophosphatase (H+-PPase) has already proven to be a useful tool to enhance crop productivity. Despite the effective use of this gene in translational resear...

Conservation of polypyrimidine tract binding proteins and their putative target RNAs in several storage root crops.

PubMed

Kondhare, Kirtikumar R; Kumar, Amit; Hannapel, David J; Banerjee, Anjan K

2018-02-07

Polypyrimidine-tract binding proteins (PTBs) are ubiquitous RNA-binding proteins in plants and animals that play diverse role in RNA metabolic processes. PTB proteins bind to target RNAs through motifs rich in cytosine/uracil residues to fine-tune transcript metabolism. Among tuber and root crops, potato has been widely studied to understand the mobile signals that activate tuber development. Potato PTBs, designated as StPTB1 and StPTB6, function in a long-distance transport system by binding to specific mRNAs (StBEL5 and POTH1) to stabilize them and facilitate their movement from leaf to stolon, the site of tuber induction, where they activate tuber and root growth. Storage tubers and root crops are important sustenance food crops grown throughout the world. Despite the availability of genome sequence for sweet potato, cassava, carrot and sugar beet, the molecular mechanism of root-derived storage organ development remains completely unexplored. Considering the pivotal role of PTBs and their target RNAs in potato storage organ development, we propose that a similar mechanism may be prevalent in storage root crops as well. Through a bioinformatics survey utilizing available genome databases, we identify the orthologues of potato PTB proteins and two phloem-mobile RNAs, StBEL5 and POTH1, in five storage root crops - sweet potato, cassava, carrot, radish and sugar beet. Like potato, PTB1/6 type proteins from these storage root crops contain four conserved RNA Recognition Motifs (characteristic of RNA-binding PTBs) in their protein sequences. Further, 3´ UTR (untranslated region) analysis of BEL5 and POTH1 orthologues revealed the presence of several cytosine/uracil motifs, similar to those present in potato StBEL5 and POTH1 RNAs. Using RT-qPCR assays, we verified the presence of these related transcripts in leaf and root tissues of these five storage root crops. Similar to potato, BEL5-, PTB1/6- and POTH1-like orthologue RNAs from the aforementioned storage root crops exhibited differential accumulation patterns in leaf and storage root tissues. Our results suggest that the PTB1/6-like orthologues and their putative targets, BEL5- and POTH1-like mRNAs, from storage root crops could interact physically, similar to that in potato, and potentially, could function as key molecular signals controlling storage organ development in root crops.

Crop physiology calibration in the CLM

DOE PAGES

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

2015-04-15

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Crop physiology calibration in the CLM

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

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

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

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.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress

PubMed Central

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C.

2014-01-01

Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Methods Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. Key Results To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait ‘total crop nitrogen uptake’ (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10–36 % more yield than those based on markers for yield per se. Conclusions This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. PMID:24984712

7 CFR 407.9 - Area risk protection insurance policy.

Code of Federal Regulations, 2014 CFR

2014-01-01

... FCIC, whose research or occupation is related to the specific crop or practice for which such expertise... following organizations: Appropriate Technology Transfer for Rural Areas, Sustainable Agriculture Research... other persons approved by FCIC, whose research or occupation is related to the specific organic crop or...

Development of Unmanned Aerial Vehicles for Site-Specific Crop Production Management

USDA-ARS?s Scientific Manuscript database

Unmanned Aerial Vehicles (UAV) have been developed and applied to support the practice of precision agriculture. Compared to piloted aircrafts, an Unmanned Aerial Vehicle can focus on much smaller crop fields with much lower flight altitude than regular airplanes to perform site-specific management ...

A future scenario of the global regulatory landscape regarding genome-edited crops

PubMed Central

Araki, Motoko

2017-01-01

ABSTRACT The global agricultural landscape regarding the commercial cultivation of genetically modified (GM) crops is mosaic. Meanwhile, a new plant breeding technique, genome editing is expected to make genetic engineering-mediated crop breeding more socially acceptable because it can be used to develop crop varieties without introducing transgenes, which have hampered the regulatory review and public acceptance of GM crops. The present study revealed that product- and process-based concepts have been implemented to regulate GM crops in 30 countries. Moreover, this study analyzed the regulatory responses to genome-edited crops in the USA, Argentina, Sweden and New Zealand. The findings suggested that countries will likely be divided in their policies on genome-edited crops: Some will deregulate transgene-free crops, while others will regulate all types of crops that have been modified by genome editing. These implications are discussed from the viewpoint of public acceptance. PMID:27960622

Effects of cropping systems on soil biology

USDA-ARS?s Scientific Manuscript database

The need for fertilizer use to enhance soil nutrient pools to achieve good crop yield is essential to modern agriculture. Specific management practices, including cover cropping, that increase the activities of soil microorganisms to fix N and mobilize P and micronutrients may reduce annual inputs ...

How Universal Is the Relationship Between Remotely Sensed Vegetation Indices (VI) and Crop Leaf Area Index (LAI)?

NASA Technical Reports Server (NTRS)

Kang, Yanghui; Ozdogan, Mutlu; Zipper, Samuel C.; Roman, Miguel

2016-01-01

Global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. This research enables the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Alternative scenarios of bioenergy crop production in an agricultural landscape and implications for bird communities.

PubMed

Blank, Peter J; Williams, Carol L; Sample, David W; Meehan, Timothy D; Turner, Monica G

2016-01-01

Increased demand and government mandates for bioenergy crops in the United States could require a large allocation of agricultural land to bioenergy feedstock production and substantially alter current landscape patterns. Incorporating bioenergy landscape design into land-use decision making could help maximize benefits and minimize trade-offs among alternative land uses. We developed spatially explicit landscape scenarios of increased bioenergy crop production in an 80-km radius agricultural landscape centered on a potential biomass-processing energy facility and evaluated the consequences of each scenario for bird communities. Our scenarios included conversion of existing annual row crops to perennial bioenergy grasslands and conversion of existing grasslands to annual bioenergy row crops. The scenarios explored combinations of four biomass crop types (three potential grassland crops along a gradient of plant diversity and one annual row crop [corn]), three land conversion percentages to bioenergy crops (10%, 20%, or 30% of row crops or grasslands), and three spatial configurations of biomass crop fields (random, clustered near similar field types, or centered on the processing plant), yielding 36 scenarios. For each scenario, we predicted the impact on four bird community metrics: species richness, total bird density, species of greatest conservation need (SGCN) density, and SGCN hotspots (SGCN birds/ha ≥ 2). Bird community metrics consistently increased with conversion of row crops to bioenergy grasslands and consistently decreased with conversion of grasslands to bioenergy row crops. Spatial arrangement of bioenergy fields had strong effects on the bird community and in some cases was more influential than the amount converted to bioenergy crops. Clustering grasslands had a stronger positive influence on the bird community than locating grasslands near the central plant or at random. Expansion of bioenergy grasslands onto marginal agricultural lands will likely benefit grassland bird populations, and bioenergy landscapes could be designed to maximize biodiversity benefits while meeting targets for biomass production.

Chili peppers: Challenges and advances in transitioning harvesting of New Mexico's signature crop

USDA-ARS?s Scientific Manuscript database

New Mexico-type chile (Capsicum annuum L.), often referred to as ‘Anaheim’, is the signature crop of New Mexico. Both the red and green (fully sized, but physiologically immature) crops are celebrated in local cuisine, culture and art, and production and processing of chile is an integral contributo...

Carbon budgets of thirteen years at the FLUXNET cropland site Oensingen, Switzerland

NASA Astrophysics Data System (ADS)

Emmel, Carmen; Revill, Andrew; Hörtnagl, Lukas; Eugster, Werner

2017-04-01

The FLUXNET cropland site at Oensingen, Switzerland (CH-Oe2) is located on the Swiss Plateau, which is representative for the average domain of agricultural crop production in Switzerland. The site is managed under the low pesticide integrated production (IP) farming protocol and features a crop rotation focusing on winter wheat, but also includes winter barley, rapeseed, peas and potatoes as well as intermediate cover crops. Thirteen years of eddy covariance and meteorological measurements are available for the site. The carbon imports through manure applications and sowing, along with the exports through harvests, were quantified. In this study, we analyze the carbon budgets of all crop types and measurement years. These results will be compared to changes in soil carbon content. We will answer the questions: (1) Has the crop rotation and field management resulted in a net carbon source or sink? (2) To what extent are the different crop types linked to net carbon exchanges? (3) What are the climatic potential drivers for the interannual cropland carbon budget? (4) Is the carbon budget reflected in the changes in soil carbon content?

Using remote sensing and soil physical properties for predicting the spatial distribution of cotton lint yield

USDA-ARS?s Scientific Manuscript database

Timely reflectance data from cotton (Gossypium hirsutum L.) production fields provide a useful tool for crop health assessment and site-specific crop management decisions. This field study investigated the relationships among site-specific normalized difference vegetation index (NDVI), soil physical...

Glyphosate Effects on Plant Mineral Nutrition, Crop Rhizosphere Microbiota, and Plant Disease in Glyphosate-Resistant Crops

PubMed Central

2012-01-01

Claims have been made recently that glyphosate-resistant (GR) crops sometimes have mineral deficiencies and increased plant disease. This review evaluates the literature that is germane to these claims. Our conclusions are: (1) although there is conflicting literature on the effects of glyphosate on mineral nutrition on GR crops, most of the literature indicates that mineral nutrition in GR crops is not affected by either the GR trait or by application of glyphosate; (2) most of the available data support the view that neither the GR transgenes nor glyphosate use in GR crops increases crop disease; and (3) yield data on GR crops do not support the hypotheses that there are substantive mineral nutrition or disease problems that are specific to GR crops. PMID:23013354

Impact of parameterization choices on the restitution of ozone deposition over vegetation

NASA Astrophysics Data System (ADS)

Le Morvan-Quéméner, Aurélie; Coll, Isabelle; Kammer, Julien; Lamaud, Eric; Loubet, Benjamin; Personne, Erwan; Stella, Patrick

2018-04-01

Ozone is a potentially phyto-toxic air pollutant, which can cause leaf damage and drastically alter crop yields, causing serious economic losses around the world. The VULNOZ (VULNerability to OZone in Anthropised Ecosystems) project is a biology and modeling project that aims to understand how plants respond to the stress of high ozone concentrations, then use a set of models to (i) predict the impact of ozone on plant growth, (ii) represent ozone deposition fluxes to vegetation, and finally (iii) estimate the economic consequences of an increasing ozone background the future. In this work, as part of the VULNOZ project, an innovative representation of ozone deposition to vegetation was developed and implemented in the CHIMERE regional chemistry-transport model. This type of model calculates the average amount of ozone deposited on a parcel each hour, as well as the integrated amount of ozone deposited to the surface at the regional or country level. Our new approach was based on a refinement of the representation of crop types in the model and the use of empirical parameters specific to each crop category. The results obtained were compared with a conventional ozone deposition modeling approach, and evaluated against observations from several agricultural areas in France. They showed that a better representation of the distribution between stomatal and non-stomatal ozone fluxes was obtained in the empirical approach, and they allowed us to produce a new estimate of the total amount of ozone deposited on the subtypes of vegetation at the national level.

78 FR 53370 - Common Crop Insurance Regulations; Forage Seed Crop Provisions

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-29

... process of good farming practices, as applicable, must be exhausted before any action against FCIC may be... for all producers regardless of the size of their farming operation. For instance, all producers are... guarantee per acre for each type and practice in the unit by the insured acreage of that type and practice...

77 FR 3227 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-23

... year experience, weather occurrences and projections, market demand, new farming techniques and... elements, as required: crop planted, planting date, crop's intended use, type or variety, practice...

Increasing diveristy of arbuscular mycorrhizal fungi in agroecosystems using specific cover crops

USDA-ARS?s Scientific Manuscript database

Fall-planted cover crops provide a plant host for obligate symbiotic arbuscular mycorrhizal fungi (AMF) during otherwise fallow periods and thus may increase AMF numbers in agroecosystems. Increased AMF numbers should increase mycorrhizal colonization of the subsequent cash crops, which has been li...

Evaluation of Learning Group Approaches for Fostering Integrated Cropping Systems Management

ERIC Educational Resources Information Center

Blissett, Hana; Simmons, Steve; Jordan, Nicholas; Nelson, Kristen

2004-01-01

Cropping systems management requires integration of multiple forms of knowledge, practice, and learning by farmers, extension educators, and researchers. We evaluated the outcomes of participation in collaborative learning groups organized to address cropping systems and, specifically, challenges of integrated weed management. Groups were…

Topsoil depth effects on corn yield and nitrogen uptake efficiency

USDA-ARS?s Scientific Manuscript database

Decades of erosion on claypan soil fields under row crop production has led to varying topsoil thickness across fields of the Midwest, resulting in variable crop fertilizer requirements across landscapes. Determining how these crop needs, specifically nitrogen, vary across fields is crucial for gett...

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

NASA Technical Reports Server (NTRS)

Ulaby, F. T.

1975-01-01

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

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).

Erosion control in orchards and vineyards by a new soil and cover crop management method

NASA Astrophysics Data System (ADS)

Hartl, Wilfried; Guettler, Hans; Auer, Karl; Erhart, Eva

2016-04-01

Cover crops are the basis for an erosion-free soil management in orchards and vineyards. The soil cover provided by the foliage and the intensive root formation counteract erosion. Cover crops provide the soil microfauna with fresh organic matter which improves soil structure and porosity. The water demand of cover crops, however, may pose problems for the water supply of the trees and vines in dry seasons. Therefore it is necessary to adjust the growth of the cover crops to the actual water conditions. In years with ample precipitation cover crops may be allowed lush vegetative growth till flowering and formation of seeds. In dry years, the growth of the cover crop must be restricted to stop the competition for water, sometimes even by cutting off the cover crop roots. The course of the weather is incalculable and rainfall may be very variable during the year, so it is sometimes necessary to adust the cover crop management several times a year. A new special equipment, which can perform all the tasks necessary for the flexible cover crop management has been developed together with the agricultural machinery manufacturers Bodenwerkstatt Ertl-Auer GmbH and Güttler GmbH. The GreenManager® device consists of three modules, namely a specific type of cultivator, a harrow and a prismatic roller with seeding equipment, which can be used separately or in combination. The GreenManager® can reduce cover crops by flattening the plants in the whole row middle, by bringing down the cover crops with the harrow, or by horizontally cutting the cover crop roots a few centimetres beneath the soil surface in the central part of the row middle or in the whole row middle. These measures reduce the water competition by cover crops without generating further losses of soil moisture through intensive soil cultivation. At the same time the risk of soil erosion is kept to a minimum, because the soil remains covered by dead plant biomass. In one passage the GreenManager® can direct-drill large-grain cover crop seeds and simultaneously cut the roots of the standing vegetation in the row middle, plus at the same time sow small-grain seeds over the whole middle. The large grains are placed several centimetres deep with the cultivator, while the small grains are spread on the surface in a seedbed prepared by the prismatic roller or the harrow module. So it is secured that on rewetting of the soil the next generation of cover crops will be established straight away. In all cases, however, the soil remains covered with living or dead plant biomass, so that the erosion risk is minimized. Uppermost goals of the flexible cover crop management are the well-being of the fruit trees and vines and maximum erosion protection of the soil.

Sparse graph regularization for robust crop mapping using hyperspectral remotely sensed imagery with very few in situ data

NASA Astrophysics Data System (ADS)

Xue, Zhaohui; Du, Peijun; Li, Jun; Su, Hongjun

2017-02-01

The generally limited availability of training data relative to the usually high data dimension pose a great challenge to accurate classification of hyperspectral imagery, especially for identifying crops characterized with highly correlated spectra. However, traditional parametric classification models are problematic due to the need of non-singular class-specific covariance matrices. In this research, a novel sparse graph regularization (SGR) method is presented, aiming at robust crop mapping using hyperspectral imagery with very few in situ data. The core of SGR lies in propagating labels from known data to unknown, which is triggered by: (1) the fraction matrix generated for the large unknown data by using an effective sparse representation algorithm with respect to the few training data serving as the dictionary; (2) the prediction function estimated for the few training data by formulating a regularization model based on sparse graph. Then, the labels of large unknown data can be obtained by maximizing the posterior probability distribution based on the two ingredients. SGR is more discriminative, data-adaptive, robust to noise, and efficient, which is unique with regard to previously proposed approaches and has high potentials in discriminating crops, especially when facing insufficient training data and high-dimensional spectral space. The study area is located at Zhangye basin in the middle reaches of Heihe watershed, Gansu, China, where eight crop types were mapped with Compact Airborne Spectrographic Imager (CASI) and Shortwave Infrared Airborne Spectrogrpahic Imager (SASI) hyperspectral data. Experimental results demonstrate that the proposed method significantly outperforms other traditional and state-of-the-art methods.

Spatial methods for deriving crop rotation history

NASA Astrophysics Data System (ADS)

Mueller-Warrant, George W.; Trippe, Kristin M.; Whittaker, Gerald W.; Anderson, Nicole P.; Sullivan, Clare S.

2017-08-01

Benefits of converting 11 years of remote sensing classification data into cropping history of agricultural fields included measuring lengths of rotation cycles and identifying specific sequences of intervening crops grown between final years of old grass seed stands and establishment of new ones. Spatial and non-spatial methods were complementary. Individual-year classification errors were often correctable in spreadsheet-based non-spatial analysis, whereas their presence in spatial data generally led to exclusion of fields from further analysis. Markov-model testing of non-spatial data revealed that year-to-year cropping sequences did not match average frequencies for transitions among crops grown in western Oregon, implying that rotations into new grass seed stands were influenced by growers' desires to achieve specific objectives. Moran's I spatial analysis of length of time between consecutive grass seed stands revealed that clustering of fields was relatively uncommon, with high and low value clusters only accounting for 7.1 and 6.2% of fields.

Weather based risks and insurances for agricultural production

NASA Astrophysics Data System (ADS)

Gobin, Anne

2015-04-01

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

Australia’s food system is highly dependent on foreign crop diversity

USDA-ARS?s Scientific Manuscript database

The food crops that are now produced or consumed in Australia were initially domesticated and evolved over time in specific geographic regions across the planet. Genetic diversity within these crops and their wild relatives is considered to be historically particularly rich within these regions. Los...

Cover Crop Species and Management Influence Predatory Arthropods and Predation in an Organically Managed, Reduced-Tillage Cropping System.

PubMed

Rivers, Ariel N; Mullen, Christina A; Barbercheck, Mary E

2018-04-05

Agricultural practices affect arthropod communities and, therefore, have the potential to influence the activities of arthropods. We evaluated the effect of cover crop species and termination timing on the activity of ground-dwelling predatory arthropods in a corn-soybean-wheat rotation in transition to organic production in Pennsylvania, United States. We compared two cover crop treatments: 1) hairy vetch (Vicia villosa Roth) planted together with triticale (×Triticosecale Wittmack) after wheat harvest, and 2) cereal rye (Secale cereale Linnaeus) planted after corn harvest. We terminated the cover crops in the spring with a roller-crimper on three dates (early, middle, and late) based on cover crop phenology and standard practices for cash crop planting in our area. We characterized the ground-dwelling arthropod community using pitfall traps and assessed relative predation using sentinel assays with live greater waxworm larvae (Galleria mellonella Fabricius). The activity density of predatory arthropods was significantly higher in the hairy vetch and triticale treatments than in cereal rye treatments. Hairy vetch and triticale favored the predator groups Araneae, Opiliones, Staphylinidae, and Carabidae. Specific taxa were associated with cover crop condition (e.g., live or dead) and termination dates. Certain variables were positively or negatively associated with the relative predation on sentinel prey, depending on cover crop treatment and stage, including the presence of predatory arthropods and various habitat measurements. Our results suggest that management of a cover crop by roller-crimper at specific times in the growing season affects predator activity density and community composition. Terminating cover crops with a roller-crimper can conserve generalist predators.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

PubMed

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

An Analysis of Aircraft Requirements to Meet United States Department of Agriculture Remote Sensing Goals

NASA Technical Reports Server (NTRS)

Arno, R. D.

1977-01-01

The survey needs of the U.S. De pa rtment of Agriculture are immense, ranging from individual crop coverage at specific intervals to general land use classification. The aggregate of all desirable resolutions and sensor types applicable to airborne platforms yields an annual survey coverage rate eqivalent to about 6 times the U.S. land area. An intermediate annual survey level equal to the U. S. area can meet all currently perceived crop survey needs and provide sample imagery over many other resource areas. This decreased survey level can be accomplished with one or two high altitude aircraft (e.g., U-2 or WB-57) or medium altitude aircraft ( such as the Learjet or Jetstar). Survey costs range from about 25 cents to several dollars per square nautical mile depending primarily on resolution requirements and the aircraft used.

78 FR 17627 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-22

... variables such as previous year experience, weather occurrences and projections, market demand, new farming..., as required: crop planted, planting date, crop's intended use, type or variety, practice (irrigated...

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Identification and discrimination of herbicide residues using a conducting polymer electronic nose

Treesearch

Alphus Dan Wilson

2016-01-01

The identification of herbicide residues on crop foliage is necessary to make crop-management decisions for weed pest control and to monitor pesticide residue levels on food crops. Electronic-nose (e-nose) methods were tested as a cheaper, alternative means of discriminating between herbicide residue types (compared with conventional chromatography methods), by...

Mechanizing chile peppers: Challenges and advances in transitioning harvest of New Mexico's signature crop

USDA-ARS?s Scientific Manuscript database

New Mexican-type chile (Capsicum annuum L.), often referred to as 'Anaheim', is the signature crop of New Mexico. Both the red and green (fully sized, but physiologically immature) crops are integral to the state's culture and economy. Lack of a predictable labor supply and higher input costs have p...

Whole genome comparison of Aspergillus flavus L-morphotype strain NRRL 3357 (type) and S-morphotype strain AF70

USDA-ARS?s Scientific Manuscript database

Aspergillus flavus is a saprophytic fungus that infects corn, peanuts, tree nuts and other agriculturally important crops. Once the crop is infected the fungus has the potential to secrete one or more mycotoxins, the most carcinogenic of which is aflatoxin. Aflatoxin contaminated crops are deemed un...

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Developing Land Surface Type Map with Biome Classification Scheme Using Suomi NPP/JPSS VIIRS Data

NASA Astrophysics Data System (ADS)

Zhang, Rui; Huang, Chengquan; Zhan, Xiwu; Jin, Huiran

2016-08-01

Accurate representation of actual terrestrial surface types at regional to global scales is an important element for a wide range of applications, such as land surface parameterization, modeling of biogeochemical cycles, and carbon cycle studies. In this study, in order to meet the requirement of the retrieval of global leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by the vegetation (fPAR) and other studies, a global map generated from Suomi National Polar- orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance data in six major biome classes based on their canopy structures, which include: Grass/Cereal Crops, Shrubs, Broadleaf Crops, Savannas, Broadleaf Forests, and Needleleaf Forests, was created. The primary biome classes were converted from an International Geosphere-Biosphere Program (IGBP) legend global surface type data that was created in previous study, and the separation of two crop types are based on a secondary classification.

Convolutional Neural Network for Multi-Source Deep Learning Crop Classification in Ukraine

NASA Astrophysics Data System (ADS)

Lavreniuk, M. S.

2016-12-01

Land cover and crop type maps are one of the most essential inputs when dealing with environmental and agriculture monitoring tasks [1]. During long time neural network (NN) approach was one of the most efficient and popular approach for most applications, including crop classification using remote sensing data, with high an overall accuracy (OA) [2]. In the last years the most popular and efficient method for multi-sensor and multi-temporal land cover classification is convolution neural networks (CNNs). Taking into account presence clouds in optical data, self-organizing Kohonen maps (SOMs) are used to restore missing pixel values in a time series of optical imagery from Landsat-8 satellite. After missing data restoration, optical data from Landsat-8 was merged with Sentinel-1A radar data for better crop types discrimination [3]. An ensemble of CNNs is proposed for multi-temporal satellite images supervised classification. Each CNN in the corresponding ensemble is a 1-d CNN with 4 layers implemented using the Google's library TensorFlow. The efficiency of the proposed approach was tested on a time-series of Landsat-8 and Sentinel-1A images over the JECAM test site (Kyiv region) in Ukraine in 2015. Overall classification accuracy for ensemble of CNNs was 93.5% that outperformed an ensemble of multi-layer perceptrons (MLPs) by +0.8% and allowed us to better discriminate summer crops, in particular maize and soybeans. For 2016 we would like to validate this method using Sentinel-1 and Sentinel-2 data for Ukraine territory within ESA project on country level demonstration Sen2Agri. 1. A. Kolotii et al., "Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine," The Int. Arch. of Photogram., Rem. Sens. and Spatial Inform. Scie., vol. 40, no. 7, pp. 39-44, 2015. 2. F. Waldner et al., "Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity," Int. Journal of Rem. Sens. vol. 37, no. 14, pp 3196-3231, 2016. 3. S. Skakun et al., "Efficiency assessment of multitemporal C-band Radarsat-2 intensity and Landsat-8 surface reflectance satellite imagery for crop classification in Ukraine," IEEE Journal of Selected Topics in Applied Earth Observ. and Rem. Sens., 2015, DOI: 10.1109/JSTARS.2015.2454297.

A comparative analysis of transcriptomic, biochemical and physiological responses to elevated ozone identifies species-specific mechanisms of resilience in legume crops

USDA-ARS?s Scientific Manuscript database

Current concentrations of tropospheric ozone (O3) pollution negatively impact plant metabolism, which can result in decreased crop yields. Interspecific variation in the physiological response of plants to elevated [O3] exists; however, the underlying cellular responses explaining species-specific d...

High yielding tropical energy crops for bioenergy production: Effects of plant components, harvest years and locations on biomass composition.

PubMed

Surendra, K C; Ogoshi, Richard; Zaleski, Halina M; Hashimoto, Andrew G; Khanal, Samir Kumar

2018-03-01

The composition of lignocellulosic feedstock, which depends on crop type, crop management, locations and plant parts, significantly affects the conversion efficiency of biomass into biofuels and biobased products. Thus, this study examined the composition of different parts of two high yielding tropical energy crops, Energycane and Napier grass, collected across three locations and years. Significantly higher fiber content was found in the leaves of Energycane than stems, while fiber content was significantly higher in the stems than the leaves of Napier grass. Similarly, fiber content was higher in Napier grass than Energycane. Due to significant differences in biomass composition between the plant parts within a crop type, neither biological conversion, including anaerobic digestion, nor thermochemical pretreatment alone is likely to efficiently convert biomass components into biofuels and biobased products. However, combination of anaerobic digestion with thermochemical conversion technologies could efficiently utilize biomass components in generating biofuels and biobased products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifiers more or less quantify online: ERP evidence for partial incremental interpretation

PubMed Central

Urbach, Thomas P.; Kutas, Marta

2010-01-01

Event-related brain potentials were recorded during RSVP reading to test the hypothesis that quantifier expressions are incrementally interpreted fully and immediately. In sentences tapping general knowledge (Farmers grow crops/worms as their primary source of income), Experiment 1 found larger N400s for atypical (worms) than typical objects (crops). Experiment 2 crossed object typicality with non-logical subject-noun phrase quantifiers (most, few). Off-line plausibility ratings exhibited the crossover interaction predicted by full quantifier interpretation: Most farmers grow crops and Few farmers grow worms were rated more plausible than Most farmers grow worms and Few farmers grow crops. Object N400s, although modulated in the expected direction, did not reverse. Experiment 3 replicated these findings with adverbial quantifiers (Farmers often/rarely grow crops/worms). Interpretation of quantifier expressions thus is neither fully immediate nor fully delayed. Furthermore, object atypicality was associated with a frontal slow positivity in few-type/rarely quantifier contexts, suggesting systematic processing differences among quantifier types. PMID:20640044

Models that predict standing crop of stream fish from habitat variables: 1950-85.

Treesearch

K.D. Fausch; C.L. Hawkes; M.G. Parsons

1988-01-01

We reviewed mathematical models that predict standing crop of stream fish (number or biomass per unit area or length of stream) from measurable habitat variables and classified them by the types of independent habitat variables found significant, by mathematical structure, and by model quality. Habitat variables were of three types and were measured on different scales...

A system of regional agricultural land use mapping tested against small scale Apollo 9 color infrared photography of the Imperial Valley (California)

USGS Publications Warehouse

Johnson, Claude W.; Browden, Leonard W.; Pease, Robert W.

1969-01-01

Interpretation results of the small scale ClR photography of the Imperial Valley (California) taken on March 12, 1969 by the Apollo 9 earth orbiting satellite have shown that world wide agricultural land use mapping can be accomplished from satellite ClR imagery if sufficient a priori information is available for the region being mapped. Correlation of results with actual data is encouraging although the accuracy of identification of specific crops from the single image is poor. The poor results can be partly attributed to only one image taken during mid-season when the three major crops were reflecting approximately the same and their ClR image appears to indicate the same crop type. However, some incapacity can be attributed to lack of understanding of the subtle variations of visual and infrared color reflectance of vegetation and surrounding environment. Analysis of integrated color variations of the vegetation and background environment recorded on ClR imagery is discussed. Problems associated with the color variations may be overcome by development of a semi-automatic processing system which considers individual field units or cells. Design criteria for semi-automatic processing system are outlined.

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.

NASA crop calendars: Wheat, barley, oats, rye, sorghum, soybeans, corn

NASA Technical Reports Server (NTRS)

Stuckey, M. R.; Anderson, E. N.

1975-01-01

Crop calenders used to determine when Earth Resources Technology Satellite ERTS data would provide the most accurate wheat acreage information and to minimize the amount of ground verified information needed are presented. Since barley, oats, and rye are considered 'confusion crops, i.e., hard to differentiate from wheat in ERTS imagery, specific dates are estimated for these crops in the following stages of development: (1) seed-bed operation, (2) planting or seeding, (3) intermediate growth, (4) dormancy, (5) development of crop to full ground cover, (6) heading or tasseling, and flowering, (7) harvesting, and (8) posting-harvest operations. Dormancy dates are included for fall-snow crops. A synopsis is given of each states' growing conditions, special cropping practices, and other characteristics which are helpful in identifying crops from ERTS imagery.

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

NASA Astrophysics Data System (ADS)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields and thus has potential to be used for yield prediction, or for ingestion into a crop simulation model as a crop-specific moisture stress function.

WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops

NASA Astrophysics Data System (ADS)

Li, Dong; Cheng, Tao; Zhou, Kai; Zheng, Hengbiao; Yao, Xia; Tian, Yongchao; Zhu, Yan; Cao, Weixing

2017-07-01

Red edge position (REP), defined as the wavelength of the inflexion point in the red edge region (680-760 nm) of the reflectance spectrum, has been widely used to estimate foliar chlorophyll content from reflectance spectra. A number of techniques have been developed for REP extraction in the past three decades, but most of them require data-specific parameterization and the consistence of their performance from leaf to canopy levels remains poorly understood. In this study, we propose a new technique (WREP) to extract REPs based on the application of continuous wavelet transform to reflectance spectra. The REP is determined by the zero-crossing wavelength in the red edge region of a wavelet transformed spectrum for a number of scales of wavelet decomposition. The new technique is simple to implement and requires no parameterization from the user as long as continuous wavelet transforms are applied to reflectance spectra. Its performance was evaluated for estimating leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) of cereal crops (i.e. rice and wheat) and compared with traditional techniques including linear interpolation, linear extrapolation, polynomial fitting and inverted Gaussian. Our results demonstrated that WREP obtained the best estimation accuracy for both LCC and CCC as compared to traditional techniques. High scales of wavelet decomposition were favorable for the estimation of CCC and low scales for the estimation of LCC. The difference in optimal scale reveals the underlying mechanism of signature transfer from leaf to canopy levels. In addition, crop-specific models were required for the estimation of CCC over the full range. However, a common model could be built with the REPs extracted with Scale 5 of the WREP technique for wheat and rice crops when CCC was less than 2 g/m2 (R2 = 0.73, RMSE = 0.26 g/m2). This insensitivity of WREP to crop type indicates the potential for aerial mapping of chlorophyll content between growth seasons of cereal crops. The new REP extraction technique provides us a new insight for understanding the spectral changes in the red edge region in response to chlorophyll variation from leaf to canopy levels.

Estimating the agricultural fertilizer NH3 emission in China based on the bi-directional CMAQ model and an agro-ecosystem model

NASA Astrophysics Data System (ADS)

Wang, S.

2014-12-01

Atmospheric ammonia (NH3) plays an important role in fine particle formation. Accurate estimates of ammonia can reduce uncertainties in air quality modeling. China is one of the largest countries emitting ammonia with the majority of NH3 emissions coming from the agricultural practices, such as fertilizer applications and animal operations. The current ammonia emission estimates in China are mainly based on pre-defined emission factors. Thus, there are considerable uncertainties in estimating NH3 emissions, especially in time and space distribution. For example, fertilizer applications vary in the date of application and amount by geographical regions and crop types. In this study, the NH3 emission from the agricultural fertilizer use in China of 2011 was estimated online by an agricultural fertilizer modeling system coupling a regional air-quality model and an agro-ecosystem model, which contains three main components 1) the Environmental Policy Integrated Climate (EPIC) model, 2) the meso-scale meteorology Weather Research and Forecasting (WRF) model and 3) the CMAQ air quality model with bi-directional ammonia fluxes. The EPIC output information about daily fertilizer application and soil characteristics would be the input of the CMAQ model. In order to run EPIC model, much Chinese local information is collected and processed. For example, Crop land data are computed from the MODIS land use data at 500-m resolution and crop categories at Chinese county level; the fertilizer use rate for different fertilizer types, crops and provinces are obtained from Chinese statistic materials. The system takes into consideration many influencing factors on agriculture ammonia emission, including weather, the fertilizer application method, timing, amount, and rate for specific pastures and crops. The simulated fertilizer data is compared with the NH3 emissions and fertilizer application data from other sources. The results of CMAQ modeling are also discussed and analyzed with field measurements. The estimated agricultural fertilizer NH3 emission in this study is about 3Tg in 2011. The regions with the highest emission rates are located in the North China Plain. Monthly, the peak ammonia emissions occur in April to July.

Organic marker compounds in surface soils of crop fields from the San Joaquin Valley fugitive dust characterization study

NASA Astrophysics Data System (ADS)

Rogge, Wolfgang F.; Medeiros, Patricia M.; Simoneit, Bernd R. T.

Fugitive dust from the erosion of arid and fallow land, after harvest and during agricultural activities, can at times be the dominant source of airborne particulate matter. In order to assess the source contributions to a given site, chemical mass balance (CMB) modeling is typically used together with source-specific profiles for organic and inorganic constituents. Yet, the mass balance closure can be achieved only if emission profiles for all major sources are considered. While a higher degree of mass balance closure has been achieved by adding individual organic marker compounds to elements, ions, EC, and organic carbon (OC), major source profiles for fugitive dust are not available. Consequently, neither the exposure of the population living near fugitive dust sources from farm land, nor its chemical composition is known. Surface soils from crop fields are enriched in plant detritus from both above and below ground plant parts; therefore, surface soil dust contains natural organic compounds from the crops and soil microbiota. Here, surface soils derived from fields growing cotton, safflower, tomato, almonds, and grapes have been analyzed for more than 180 organic compounds, including natural lipids, saccharides, pesticides, herbicides, and polycyclic aromatic hydrocarbon (PAH). The major result of this study is that selective biogenically derived organic compounds are suitable markers of fugitive dust from major agricultural crop fields in the San Joaquin Valley. Aliphatic homologs exhibit the typical biogenic signatures of epicuticular plant waxes and are therefore indicative of fugitive dust emissions and mechanical abrasion of wax protrusions from leaf surfaces. Saccharides, among which α- and β-glucose, sucrose, and mycose show the highest concentrations in surface soils, have been proposed to be generic markers for fugitive dust from cultivated land. Similarly, steroids are strongly indicative of fugitive dust. Yet, triterpenoids reveal the most pronounced distribution differences for all types of cultivated soils examined here and are by themselves powerful markers for fugitive dust that allow differentiation between the types of crops cultivated. PAHs are also found in some surface soils, as well as persistent pesticides, e.g., DDE, Fosfall, and others.

Analysis of scanner data for crop inventories

NASA Technical Reports Server (NTRS)

Horvath, R. (Principal Investigator); Cicone, R. C.; Kauth, R. J.; Malila, W. A.; Pont, W.; Thelen, B.; Sellman, A.

1981-01-01

Accomplishments for a machine-oriented small grains labeler T&E, and for Argentina ground data collection are reported. Features of the small grains labeler include temporal-spectral profiles, which characterize continuous patterns of crop spectral development, and crop calendar shift estimation, which adjusts for planting date differences of fields within a crop type. Corn and soybean classification technology development for area estimation for foreign commodity production forecasting is reported. Presentations supporting quarterly project management reviews and a quarterly technical interchange meeting are also included.

The Impact of Environmental Factors on the Amount of Nitrates and Nitrites in Different Types of Soils and Ways of Their Utilization

NASA Astrophysics Data System (ADS)

Bachvarova, Darina; Rafi, Renay; Doichinov, Aleksandar

2017-03-01

Despite the last decade considerable advances in the study of nitrate and nitrite pollution of soil, there are still some gaps in research related to neglecting or ignoring the role of soil in the food chain and its effects on upper trophic units. The article presents the results of a study on the impact of air and soil humidity and temperature, as well as soil type and utilization on the amount of nitrates and nitrites in the soil solution at the end of vegetation period. It was proved that statistically significant impact on the amounts of residual nitrate and nitrite ions was caused by the temperature and moisture of soil, its type, and the specific properties of the crops grown.

Gene Flow in Genetically Engineered Perennial Grasses: Lessons for Modification of Dedicated Bioenergy Crops

USDA-ARS?s Scientific Manuscript database

Genetic modification of dedicated bioenergy crops, such as switchgrass, will play a major role in crop improvement for a wide range of beneficial traits specific to biofuels. One obstacle that arises regarding transgenic improvement of perennials used for biofuels is the propensity of these plants t...

Using Satellite Imagery with ET Weather Station Networks to Map Crop Water Use for Irrigation Scheduling: TOPS-SIMS.

USDA-ARS?s Scientific Manuscript database

Evapotranspiration estimates for scheduling irrigation must be field specific and real time. Weather station networks provide daily reference ET values, but users need to select crop coefficients for their particular crop and field. A prototype system has been developed that combines satellite image...

Dynamics of predation on Lygus hesperus (Hemiptera: Miridae) in alfalfa trap cropped organic strawberry

USDA-ARS?s Scientific Manuscript database

Alfalfa (Medicago sativa L.) can be strategically planted as a trap crop for Lygus spp. in California’s organic strawberry fields. Alfalfa has been shown to attract both Lygus spp. and, in turn, a Lygus-specific parasitoid, Peristenus relictus (Ruthe). However, the impact of alfalfa trap-cropped st...

Linking groundwater use and stress to specific crops using the groundwater footprint in the Central Valley and High Plains aquifer systems, U.S.

NASA Astrophysics Data System (ADS)

Esnault, Laurent; Gleeson, Tom; Wada, Yoshihide; Heinke, Jens; Gerten, Dieter; Flanary, Elizabeth; Bierkens, Marc F. P.; van Beek, Ludovicus P. H.

2014-06-01

A number of aquifers worldwide are being depleted, mainly by agricultural activities, yet groundwater stress has not been explicitly linked to specific agricultural crops. Using the newly developed concept of the groundwater footprint (the area required to sustain groundwater use and groundwater-dependent ecosystem services), we develop a methodology to derive crop-specific groundwater footprints. We illustrate this method by calculating high-resolution groundwater footprint estimates of crops in two heavily used aquifer systems: the Central Valley and High Plains, U.S. In both aquifer systems, hay and haylage, corn, and cotton have the largest groundwater footprints, which highlights that most of the groundwater stress is induced by crops meant for cattle feed. Our results are coherent with other studies in the High Plains but suggest lower groundwater stress in the Central Valley, likely due to artificial recharge from surface water diversions which were not taken into account in previous estimates. Uncertainties of recharge and irrigation application efficiency contribute the most to the total relative uncertainty of the groundwater footprint to aquifer area ratios. Our results and methodology will be useful for hydrologists, water resource managers, and policy makers concerned with which crops are causing the well-documented groundwater stress in semiarid to arid agricultural regions around the world.

Linking Groundwater Use and Stress to Specific Crops Using the Groundwater Footprint in the Central Valley and High Plains Aquifer Systems, U.S.

NASA Astrophysics Data System (ADS)

Wada, Y.; Esnault, L.; Gleeson, T.; Heinke, J.; Gerten, D.; Flanary, E.; Bierkens, M. F.; Van Beek, L. P.

2014-12-01

A number of aquifers worldwide are being depleted, mainly by agricultural activities, yet groundwater stress has not been explicitly linked to specific agricultural crops. Using the newly-developed concept of the groundwater footprint (the area required to sustain groundwater use and groundwater-dependent ecosystem services), we develop a methodology to derive crop-specific groundwater footprints. We illustrate this method by calculating high resolution groundwater footprint estimates of crops in two heavily used aquifer systems: the Central Valley and High Plains, U.S. In both aquifer systems, hay and haylage, corn and cotton have the largest groundwater footprints, which highlights that most of the groundwater stress is induced by crops meant for cattle feed. Our results are coherent with other studies in the High Plains but suggest lower groundwater stress in the Central Valley, likely due to artificial recharge from surface water diversions which were not taken into account in previous estimates. Uncertainties of recharge and irrigation application efficiency contribute the most to the total relative uncertainty of the groundwater footprint to aquifer area ratios. Our results and methodology will be useful for hydrologists, water resource managers, and policy makers concerned with which crops are causing the well-documented groundwater stress in semiarid to arid agricultural regions around the world.

Transport and fate of nitrate within soil units of glacial origin

NASA Astrophysics Data System (ADS)

Moore, Suzanna L.; Peterson, Eric W.

2007-08-01

Questions concerning the influence of soil type and crop cover on the fate and transport of nitrate (NO{3/-}) were examined. During a growing season, soils derived from glacial material underlying either corn or soybeans were sampled for levels of NO{3/-} within the pore water. Measured levels of NO{3/-} ranged from below detection limit to 14.9 g NO{3/-} per kilogram of soil (g/kg). In fields with the same crop cover, the silty-clayey soil exhibited a greater decrease in NO{3/-} levels with depth than the sandier soil. Crop uptake of NO{3/-} occurs within the root zone; however, the type of crop cover did not have a direct impact on the fate or transport during the growing season. The soils underlying soybeans had an increase in NO{3/-} levels following harvest, suggesting that the decomposition of the soybean roots contributed to the net gain of NO{3/-} in the shallow soil. For all of the soil types, conditions below 100 cm are conducive for microbial denitrification, with both a high water saturation level (>60%) and moderate organic carbon content (1-2%). At depths below 100 cm, temporal differences in NO{3/-} levels of over a magnitude, up to a 95% reduction, were recorded in the soil units as the growing season progressed. Physical properties that control the transport of NO{3/-} or denitrification have a larger influence on NO{3/-} levels than crop type.

Biofuels on the landscape: Is "land sharing" preferable to "land sparing"?

NASA Astrophysics Data System (ADS)

DeLucia, E. H.; Anderson-Teixeira, K. J.; Duval, B. D.; Long, S. P.

2012-12-01

Widespread land use changes—and ensuing effects on biodiversity and ecosystem services—are expected as a result of expanding bioenergy production. Although almost all US production of ethanol today is from corn, it is envisaged that future ethanol production will also draw from cellulosic sources such as perennial grasses. In selecting optimal bioenergy crops, there is debate as to whether it is preferable from an environmental standpoint to cultivate bioenergy crops with high ecosystem services (a "land sharing" strategy) or to grow crops with lower ecosystem services but higher yield, thereby requiring less land to meet bioenergy demand (a "land sparing" strategy). Here, we develop a simple model to address this question. Assuming that bioenergy crops are competing with uncultivated land, our model calculates land requirements to meet a given bioenergy demand intensity based upon the yields of bioenergy crops and combines fractional land cover of each ecosystem type with its associated ecosystem services to determine whether land sharing or land sparing strategies maximize ecosystem services at the landscape level. We apply this model to a case in which climate protection through GHG regulation—an ecosystem's greenhouse gas value (GHGV)—is the ecosystem service of interest. We consider five bioenergy crops competing for land area with five unfarmed ecosystem types in the central and eastern US. Our results show that the relative advantages of land sparing and land sharing depend upon the type of ecosystem with which the bioenergy crop is competing for land; as the GHGV value of the unfarmed land increases, the preferable strategy shifts from land sharing to land sparing. This implies that, while it may be preferable to replace ecologically degraded land with high-GHGV, lower yielding bioenergy crops, average landscape GHGV will most often be maximized through high yielding bioenergy crops that leave more land for uncultivated, high-GHGV ecosystems. While our case study focuses on GHGV, the same principles will be generally applicable to any ecosystem service whose value does not depend upon the spatial configuration of the landscape. Whenever bioenergy crops have substantially lower ecosystem services than the ecosystems with which they are competing for land, the most effective strategy for meeting bioenergy demand while maximizing ecosystem services on a landscape level is one of land sparing—that is, focusing simultaneously on maximizing the yield of bioenergy crops while preserving or restoring natural ecosystems.

Specificity determinants for Cry insecticidal proteins: Insights from their mode of action.

PubMed

Jurat-Fuentes, Juan Luis; Crickmore, Neil

2017-01-01

Insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) are used as active components of biopesticides and as plant incorporated protectants in transgenic crops. One of the most relevant attributes of these Bt protein-based insecticidal technologies is their high specificity, which assures lack of detrimental effects on non-target insects, vertebrates and the environment. The identification of specificity determinants in Bt insecticidal proteins could guide risk assessment for novel insecticidal proteins currently considered for commercialization. In this work we review the available data on specificity determinants of crystal (Cry) insecticidal proteins as the Bt toxins most well characterized and used in transgenic crops. The multi-step mode of action of the Cry insecticidal proteins allows various factors to potentially affect specificity determination and here we define seven levels that could influence specificity. The relative relevance of each of these determinants on efficacy of transgenic crops producing Cry insecticidal proteins is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Changing pollutants to green biogases for the crop food cycle chain.

PubMed

Zong, B Y; Xu, F J; Zong, B D; Zhang, Z G

2012-09-01

When fossil fuels on the Earth are used up, which kind of green energy can be used to replace them? Do every bioenergy generation or crop food chain results in environmental pollution? These questions are major concerns in a world facing restricted supplies of energy and food as well as environmental pollutions. To alleviate these issues, option biogases are explored in this paper. Two types of biogas generators were used for modifying the traditional crop food chain [viz. from atmospheric CO(2) photosynthesis to crops, crop stem/husk biowastes (burnt in cropland or as home fuels), to livestock droppings (dumping away), pork and people foods, then to CO(2)], via turning the biowaste pollutants into green bioenergies. By analyzing the traditional food chain via observation method, the drawbacks of by-product biowastes were revealed. Also, the whole cycle chain was further analyzed to assess its "greenness," using experimental data and other information, such as the material balance (e.g., the absorbed CO(2), investment versus generated food, energy, and wastes). The data show that by using the two types of biogas generators, clean renewable bioenergy, crop food, and livestock meat could be continuously produced without creating any waste to the world. The modification chain largely reduced CO(2) greenhouse gas and had a low-cost investment. The raw materials for the gas generators were only the wastes of crop stems and livestock droppings. Thus, the recommended CO(2) bioenergy cycle chain via the modification also greatly solved the environmental biowaste pollutions in the world. The described two type biogases effectively addressed the issues on energy, food, and environmental pollution. The green renewable bioenergy from the food cycle chain may be one of suitable alternatives to fossil and tree fuels for agricultural countries.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE PAGES

Blanc, Elodie; Caron, Justin; Fant, Charles; ...

2017-06-27

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

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

Blanc, Elodie; Caron, Justin; Fant, Charles

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.

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.

Meteorological risks and impacts on crop production systems in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2013-04-01

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

Sampling Simulations for Assessing the Accuracy of U.S. Agricultural Crop Mapping from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Dwyer, Linnea; Yadav, Kamini; Congalton, Russell G.

2017-04-01

Providing adequate food and water for a growing, global population continues to be a major challenge. Mapping and monitoring crops are useful tools for estimating the extent of crop productivity. GFSAD30 (Global Food Security Analysis Data at 30m) is a program, funded by NASA, that is producing global cropland maps by using field measurements and remote sensing images. This program studies 8 major crop types, and includes information on cropland area/extent, if crops are irrigated or rainfed, and the cropping intensities. Using results from the US and the extensive reference data available, CDL (USDA Crop Data Layer), we will experiment with various sampling simulations to determine optimal sampling for thematic map accuracy assessment. These simulations will include varying the sampling unit, the sampling strategy, and the sample number. Results of these simulations will allow us to recommend assessment approaches to handle different cropping scenarios.

Encounter risk analysis of rainfall and reference crop evapotranspiration in the irrigation district

NASA Astrophysics Data System (ADS)

Zhang, Jinping; Lin, Xiaomin; Zhao, Yong; Hong, Yang

2017-09-01

Rainfall and reference crop evapotranspiration are random but mutually affected variables in the irrigation district, and their encounter situation can determine water shortage risks under the contexts of natural water supply and demand. However, in reality, the rainfall and reference crop evapotranspiration may have different marginal distributions and their relations are nonlinear. In this study, based on the annual rainfall and reference crop evapotranspiration data series from 1970 to 2013 in the Luhun irrigation district of China, the joint probability distribution of rainfall and reference crop evapotranspiration are developed with the Frank copula function. Using the joint probability distribution, the synchronous-asynchronous encounter risk, conditional joint probability, and conditional return period of different combinations of rainfall and reference crop evapotranspiration are analyzed. The results show that the copula-based joint probability distributions of rainfall and reference crop evapotranspiration are reasonable. The asynchronous encounter probability of rainfall and reference crop evapotranspiration is greater than their synchronous encounter probability, and the water shortage risk associated with meteorological drought (i.e. rainfall variability) is more prone to appear. Compared with other states, there are higher conditional joint probability and lower conditional return period in either low rainfall or high reference crop evapotranspiration. For a specifically high reference crop evapotranspiration with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is increased with the decrease in frequency. For a specifically low rainfall with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is decreased with the decrease in frequency. When either the high reference crop evapotranspiration exceeds a certain frequency or low rainfall does not exceed a certain frequency, the higher conditional joint probability and lower conditional return period of various combinations likely cause a water shortage, but the water shortage is not severe.

Crop phenology and LANDSAT-based irrigated lands inventory in the high plains. [United States of America

NASA Technical Reports Server (NTRS)

Martinko, E. A. (Principal Investigator); Poracsky, J.; Kipp, E. R.; Krieger, H.

1980-01-01

The activity concentrated on identifying crop and irrigation data sources for the eight states within the High Plains Aquifer and making contacts concerning the nature of these data. A mail questionnaire was developed to gather specific data not routinely reported through standard data collection channels. Input/output routines were designed for High Plains crop and irrigation data and initial statistical data on crops were input to computer files.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

PubMed

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Microbial community structure and abundance in the rhizosphere and bulk soil of a tomato cropping system that includes cover crops

USDA-ARS?s Scientific Manuscript database

In this report we use Terminal Restriction Fragment Length Polymorphisms (TRFLP) in a tomato production system to “finger printing” the soil microbial community structure with Phylum specific primer sets. Factors influencing the soil microbes are a cover crop of Hairy Vetch (Vicia villosa) or Rye (...

Crop Identification Technolgy Assessment for Remote Sensing (CITARS). Volume 1: Task design plan

NASA Technical Reports Server (NTRS)

Hall, F. G.; Bizzell, R. M.

1975-01-01

A plan for quantifying the crop identification performances resulting from the remote identification of corn, soybeans, and wheat is described. Steps for the conversion of multispectral data tapes to classification results are specified. The crop identification performances resulting from the use of several basic types of automatic data processing techniques are compared and examined for significant differences. The techniques are evaluated also for changes in geographic location, time of the year, management practices, and other physical factors. The results of the Crop Identification Technology Assessment for Remote Sensing task will be applied extensively in the Large Area Crop Inventory Experiment.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Remote-sensing-based rapid assessment of flood crop loss to support USDA flooding decision-making

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Yang, Z.; Hipple, J.; Shrestha, R.

2016-12-01

Floods often cause significant crop loss in the United States. Timely and objective assessment of flood-related crop loss is very important for crop monitoring and risk management in agricultural and disaster-related decision-making in USDA. Among all flood-related information, crop yield loss is particularly important. Decision on proper mitigation, relief, and monetary compensation relies on it. Currently USDA mostly relies on field surveys to obtain crop loss information and compensate farmers' loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. Recent studies have demonstrated that Earth observation (EO) data are useful in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. There are three stages of flood damage assessment, including rapid assessment, early recovery assessment, and in-depth assessment. EO-based flood assessment methods currently rely on the time-series of vegetation index to assess the yield loss. Such methods are suitable for in-depth assessment but are less suitable for rapid assessment since the after-flood vegetation index time series is not available. This presentation presents a new EO-based method for the rapid assessment of crop yield loss immediately after a flood event to support the USDA flood decision making. The method is based on the historic records of flood severity, flood duration, flood date, crop type, EO-based both before- and immediate-after-flood crop conditions, and corresponding crop yield loss. It hypotheses that a flood of same severity occurring at the same pheonological stage of a crop will cause the similar damage to the crop yield regardless the flood years. With this hypothesis, a regression-based rapid assessment algorithm can be developed by learning from historic records of flood events and corresponding crop yield loss. In this study, historic records of MODIS-based flood and vegetation products and USDA/NASS crop type and crop yield data are used to train the regression-based rapid assessment algorithm. Validation of the rapid assessment algorithm indicates it can predict the yield loss at 90% accuracy, which is accurate enough to support USDA on flood-related quick response and mitigation.

Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado

USGS Publications Warehouse

Carrollo, Emily M.; Johnson, Heather E.; Fischer, Justin W.; Hammond, Matthew; Dorsey, Patricia D.; Anderson, Charles; Vercauteren, Kurt C.; Walter, W. David

2017-01-01

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Influence of Precipitation and Crop Germination on Resource Selection by Mule Deer (Odocoileus hemionus) in Southwest Colorado.

PubMed

Carrollo, Emily M; Johnson, Heather E; Fischer, Justin W; Hammond, Matthew; Dorsey, Patricia D; Anderson, Charles; Vercauteren, Kurt C; Walter, W David

2017-11-09

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km 2 , and for two summer seasons that ranged between 5.51 and 6.24 km 2 . Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

NASA Astrophysics Data System (ADS)

Tamiminia, Haifa; Homayouni, Saeid; McNairn, Heather; Safari, Abdoreza

2017-06-01

Polarimetric Synthetic Aperture Radar (PolSAR) data, thanks to their specific characteristics such as high resolution, weather and daylight independence, have become a valuable source of information for environment monitoring and management. The discrimination capability of observations acquired by these sensors can be used for land cover classification and mapping. The aim of this paper is to propose an optimized kernel-based C-means clustering algorithm for agriculture crop mapping from multi-temporal PolSAR data. Firstly, several polarimetric features are extracted from preprocessed data. These features are linear polarization intensities, and several statistical and physical based decompositions such as Cloude-Pottier, Freeman-Durden and Yamaguchi techniques. Then, the kernelized version of hard and fuzzy C-means clustering algorithms are applied to these polarimetric features in order to identify crop types. The kernel function, unlike the conventional partitioning clustering algorithms, simplifies the non-spherical and non-linearly patterns of data structure, to be clustered easily. In addition, in order to enhance the results, Particle Swarm Optimization (PSO) algorithm is used to tune the kernel parameters, cluster centers and to optimize features selection. The efficiency of this method was evaluated by using multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Manitoba, Canada, during June and July in 2012. The results demonstrate more accurate crop maps using the proposed method when compared to the classical approaches, (e.g. 12% improvement in general). In addition, when the optimization technique is used, greater improvement is observed in crop classification, e.g. 5% in overall. Furthermore, a strong relationship between Freeman-Durden volume scattering component, which is related to canopy structure, and phenological growth stages is observed.

Community and household socioeconomic factors associated with pesticide-using, small farm household members' health: a multi-level, longitudinal analysis

PubMed Central

2011-01-01

Background Longitudinal studies using multi-level models to examine health inequalities in lower and middle income countries (LMICs) are rare. We explored socio-economic gradients in health among small farm members participating in a pesticide-related health and agriculture program in highland Ecuador. Methods We profiled 24 communities through key informant interviews, secondary data (percent of population with unsatisfied basic needs), and intervention implementation indicators. Pre (2005) and post (2007) surveys of the primary household and crop managers included common questions (education, age, and the health outcome - digit span scaled 0-10)) and pesticide-related practice questions specific to each. Household assets and pesticide use variables were shared across managers. We constructed multi-level models predicting 2007 digit span for each manager type, with staged introduction of predictor variables. Results 376 household managers (79% of 2005 participants) and 380 crop managers (76% of 2005 participants) had complete data for analysis. The most important predictor of 2007 digit span was 2005 digit span: β (Standard Error) of 0.31(0.05) per unit for household and 0.17(0.04) for crop managers. Household asset score was next most important: 0.14(0.06) per unit for household and 0.14(0.05) for crop managers. Community percent with unsatisfied basic needs was associated with reductions in 2007 digit span: -0.04(0.01) per percent for household and -0.03(0.01) for crop managers. Conclusions The important roles of life endowments and/or persistent neurotoxicity were exemplified by limited change in the health outcome. Gradients by household assets and community deprivation were indicative of ongoing, structural inequities within this LMIC. PMID:22094171

Origin and Effect of Alpha 2.2 Acetobacteraceae in Honey Bee Larvae and Description of Parasaccharibacter apium gen. nov., sp. nov.

PubMed Central

Snyder, Lucy A.; Schwan, Melissa R.; Maes, Patrick; McFrederick, Quinn S.; Anderson, Kirk E.

2014-01-01

The honey bee hive environment contains a rich microbial community that differs according to niche. Acetobacteraceae Alpha 2.2 (Alpha 2.2) bacteria are present in the food stores, the forager crop, and larvae but at negligible levels in the nurse and forager midgut and hindgut. We first sought to determine the source of Alpha 2.2 in young larvae by assaying the diversity of microbes in nurse crops, hypopharyngeal glands (HGs), and royal jelly (RJ). Amplicon-based pyrosequencing showed that Alpha 2.2 bacteria occupy each of these environments along with a variety of other bacteria, including Lactobacillus kunkeei. RJ and the crop contained fewer bacteria than the HGs, suggesting that these tissues are rather selective environments. Phylogenetic analyses showed that honey bee-derived Alpha 2.2 bacteria are specific to bees that “nurse” the hive's developing brood with HG secretions and are distinct from the Saccharibacter-type bacteria found in bees that provision their young differently, such as with a pollen ball coated in crop-derived contents. Acetobacteraceae can form symbiotic relationships with insects, so we next tested whether Alpha 2.2 increased larval fitness. We cultured 44 Alpha 2.2 strains from young larvae that grouped into nine distinct clades. Three isolates from these nine clades flourished in royal jelly, and one isolate increased larval survival in vitro. We conclude that Alpha 2.2 bacteria are not gut bacteria but are prolific in the crop-HG-RJ-larva niche, passed to the developing brood through nurse worker feeding behavior. We propose the name Parasaccharibacter apium for this bacterial symbiont of bees in the genus Apis. PMID:25239902

Agricultural interventions for water saving and crop yield improvement, in a Mediterranean area - an experimental design

NASA Astrophysics Data System (ADS)

Morianou, Giasemi; Kourgialas, Nektarios; Psarras, George; Koubouris, George; Arampatzis, George; Karatzas, George; Pavlidou, Elisavet

2017-04-01

This work is a part of LIFE+ AGROCLIMAWATER project and the aim is to improve the water efficiency, increase the adaptive capacity of tree corps and save water, in a Mediterranean area, under different climatic conditions and agricultural practices. The experimental design as well as preliminary results at farm and river basin scales are presented in this work. Specifically, ten (10) pilot farms, both organic and conventional ones have been selected in the sub-basin of Platanias in western Crete - Greece. These ten pilot farms were selected representing the most typical crops in Platanias area (olive trees and citrus trees), as well as the typical soil, landscape and agricultural practices differentiation for each crop (field slope, water availability, soil type, management regime). From the ten pilot farms, eight were olive farms and the rest two citrus. This proportion correspond adequacy to the presentence of olive and citrus crops in the extended area of Platanias prefecture. Each of the ten pilot farm has been divided in two parts, the first one will be used as a control part, while the other one as the demonstration part where the interventions will be applied. The action plans for each selected farm are based on the following groups of possible interventions: a) reduction of water evaporation losses from soil surface, b) reduction of transpiration water losses through winter pruning and summer pruning, c) reduction of deep percolation water and nutrient losses, d) reduction of surface runoff, e) measures in order to maximize the efficiency of irrigation and f) rationalization of fertilizers and agrochemicals utilized. Preliminary results indicate that water saving and crop yield can be significantly improved based on the above innervations both at farm and river basin scale.

Agricultural pesticide emissions associated with common crops in the United States

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

Benjey, W.G.

Annual emissions for the year 1987 from the application of agricultural pesticides have been estimated by crop type by county for the United States using a geographic information system. The emissions estimates are based upon computed volatilization rates accounting for the properties of each pesticide, evaporation rates, mode of application (surface or soil incorporation) and percent of interception by leaves. Key pesticide properties include the Henry's Law constant, half-life in soil and the organic carbon partitioning coefficient. The volatilization rates are multiplied by the amount of pesticide applied by crop acreage in each county as determined from agricultural census andmore » pesticide sales data. The geographic distribution of the dominant emissions, such as atrazine and diazinon, etc. are presented by crop type and state. For a given pesticide, the geographic variability is controlled principally by amount applied and water availability as reflected in evaporation rates.« less

Impact of bioenergy production on carbon storage and soil functions

NASA Astrophysics Data System (ADS)

Prays, Nadia; Franko, Uwe

2016-04-01

An important renewable energy source is methane produced in biogas plants (BGPs) that convert plant material and animal excrements to biogas and a residue (BGR). If the plant material stems from crops produced specifically for that purpose, a BGP have a 'footprint' that is defined by the area of arable land needed for the production of these energy crops and the area for distributing the BGRs. The BGR can be used to fertilize these lands (reducing the need for carbon and nitrogen fertilizers), and the crop land can be managed to serve as a carbon sink, capturing atmospheric CO2. We focus on the ecological impact of different BGPs in Central Germany, with a specific interest in the long-term effect of BGR-fertilization on carbon storage within the footprint of a BGP. We therefore studied nutrient fluxes using the CANDY (CArbon and Nitrogen Dynamics) model, which processes site-specific information on soils, crops, weather, and land management to compute stocks and fluxes of carbon and nitrogen for agricultural fields. We used CANDY to calculated matter fluxes within the footprints of BGPs of different sizes, and studied the effect of the substrate mix for the BGP on the carbon dynamics of the soil. This included the land requirement of the BGR recycling when used as a fertilizer: the footprint of a BGP required for the production of the energy crop generally differs from its footprint required to take up its BGR. We demonstrate how these findings can be used to find optimal cropping choices and land management for sustainable soil use, maintaining soil fertility and other soil functions. Furthermore, site specific potentials and limitations for agricultural biogas production can be identified and applied in land-use planning.

76 FR 18798 - Comment Request for Information Collection for The National Agricultural Workers Survey: Revision...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-05

...: (1) The amount of time per day farm workers are engaged working in specific crops and tasks, and (2... the length of the work day for specific crop-task combinations. The Office of Management and Budget (OMB) authorization for the current NAWS questionnaire will expire on October 31, 2013. A copy of the...

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.

Variation in Biomass Composition Components among Forage, Biomass, Sorghum-Sudangrass, and Sweet Sorghum Types

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

Stefaniak, T. R.; Dahlberg, J. A.; Bean, B. W.

2012-07-01

Alternative biomass sources must be developed if the United States is to meet the goal in the U.S. Energy Security Act of 2007 to derive 30% of its petroleum from renewable sources, and several different biomass crops are currently in development. Sorghum [Sorghum bicolor (L.) Moench] is one such crop that will be an important feedstock source for biofuel production. As composition influences productivity, there exists a need to understand the range in composition observed within the crop. The goal of this research was to assess the range in dietary fiber composition observed within different types of biomass sorghums. Amore » total of 152 sorghum samples were divided into the four end-use types of sorghum: biomass, forage, sorghum-sudangrass, and sweet. These samples were analyzed chemically using dietary fiber analysis performed at the National Renewable Energy Laboratory using published protocols. Significant variation among the groups was detected for glucan and ash. Positive and highly significant correlations were detected between structural carbohydrates in the biomass and sweet sorghums while many of these correlations were negative or not significant in the forage and sorghum-sudangrass types. In addition, a wide range of variation was present within each group indicating that there is potential to manipulate the composition of the crop.« less

EnviroAtlas - Manure application to agricultural lands from confined animal feeding operations by 12-digit HUC for the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean livestock manure application to cultivated crop and hay/pasture lands by 12-digit Hydrologic Unit (HUC) in 2006. Livestock manure inputs to cultivated crop and hay/pasture lands were estimated using county-level estimates of recoverable animal manure from confined feeding operations compiled for 2007. Recoverable manure is defined as manure that is collected, stored, and available for land application from confined feeding operations. County-scale data on livestock populations -- needed to calculate manure inputs -- were only available for the year 2007 from the USDA Census of Agriculture (http://www.agcensus.usda.gov/index.php). We acquired county-level data describing total farm-level inputs (kg N/yr) of recoverable manure to individual counties in 2007 from the International Plant Nutrition Institute (IPNI) Nutrient Geographic Information System (NuGIS; http://www.ipni.net/nugis). These data were converted to per area rates (kg N/ha/yr) of manure N inputs by dividing the total N input by the land area (ha) of combined cultivated crop and hay/pasture (agricultural) lands within a county as determined from county-level summarization of the 2006 NLCD. We distributed county-specific, per area N inputs rates to cultivated crop and hay/pasture lands (30 x 30 m pixels) within the corresponding county. Manure data described here represent an average input to a typical agricultural land type within a county, i.e., the

Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand.

PubMed

Phairuang, Worradorn; Hata, Mitsuhiko; Furuuchi, Masami

2017-02-01

Annual and monthly-based emission inventories in northern, central and north-eastern provinces in Thailand, where agriculture and related agro-industries are very intensive, were estimated to evaluate the contribution of agricultural activity, including crop residue burning, forest fires and related agro-industries on air quality monitored in corresponding provinces. The monthly-based emission inventories of air pollutants, or, particulate matter (PM), NOx and SO 2 , for various agricultural crops were estimated based on information on the level of production of typical crops: rice, corn, sugarcane, cassava, soybeans and potatoes using emission factors and other parameters related to country-specific values taking into account crop type and the local residue burning period. The estimated monthly emission inventory was compared with air monitoring data obtained at monitoring stations operated by the Pollution Control Department, Thailand (PCD) for validating the estimated emission inventory. The agro-industry that has the greatest impact on the regions being evaluated, is the sugar processing industry, which uses sugarcane as a raw material and its residue as fuel for the boiler. The backward trajectory analysis of the air mass arriving at the PCD station was calculated to confirm this influence. For the provinces being evaluated which are located in the upper northern, lower northern and northeast in Thailand, agricultural activities and forest fires were shown to be closely correlated to the ambient PM concentration while their contribution to the production of gaseous pollutants is much less. Copyright © 2016. Published by Elsevier B.V.

A blended approach to analyze staple and high-value crops using remote sensing with radiative transfer and crop models.

NASA Astrophysics Data System (ADS)

Davitt, A. W. D.; Winter, J.; McDonald, K. C.; Escobar, V. M.; Steiner, N.

2017-12-01

The monitoring of staple and high-value crops is important for maintaining food security. The recent launch of numerous remote sensing satellites has created the ability to monitor vast amounts of crop lands, continuously and in a timely manner. This monitoring provides users with a wealth of information on various crop types over different regions of the world. However, a challenge still remains on how to best quantify and interpret the crop and surface characteristics that are measured by visible, near-infrared, and active and passive microwave radar. Currently, two NASA funded projects are examining the ability to monitor different types of crops in California with different remote sensing platforms. The goal of both projects is to develop a cost-effective monitoring tool for use by vineyard and crop managers. The first project is designed to examine the capability to monitor vineyard water management and soil moisture in Sonoma County using Soil Moisture Active Passive (SMAP), Sentinel-1A and -2, and Landsat-8. The combined mission products create thorough and robust measurements of surface and vineyard characteristics that can potentially improve the ability to monitor vineyard health. Incorporating the Michigan Microwave Canopy Scattering (MIMICS), a radiative transfer model, enables us to better understand surface and vineyard features that influence radar measurements from Sentinel-1A. The second project is a blended approach to analyze corn, rice, and wheat growth using Sentinel-1A products with Decision Support System for Agrotechnology Transfer (DSSAT) and MIMICS models. This project aims to characterize the crop structures that influence Sentinel-1A radar measurements. Preliminary results have revealed the corn, rice, and wheat structures that influence radar measurements during a growing season. The potential of this monitoring tool can be used for maintaining food security. This includes supporting sustainable irrigation practices, identifying crop health and yield across and within fields, and improving the identification of crop areas ready for harvest.

MaizeGDB: The Maize Genetics and Genomics Database.

PubMed

Harper, Lisa; Gardiner, Jack; Andorf, Carson; Lawrence, Carolyn J

2016-01-01

MaizeGDB is the community database for biological information about the crop plant Zea mays. Genomic, genetic, sequence, gene product, functional characterization, literature reference, and person/organization contact information are among the datatypes stored at MaizeGDB. At the project's website ( http://www.maizegdb.org ) are custom interfaces enabling researchers to browse data and to seek out specific information matching explicit search criteria. In addition, pre-compiled reports are made available for particular types of data and bulletin boards are provided to facilitate communication and coordination among members of the community of maize geneticists.

Summer Crop Classification by Multi-Temporal COSMO-SkyMed® Data

NASA Astrophysics Data System (ADS)

Guarini, Rocchina; Bruzzone, Lorenzo; Santoni, Massimo; Vuolo, Francesco; Luigi, Dini

2016-08-01

In this study, we propose a multi-temporal and multi- polarization approach to discriminate different crop types in the Marchefel region, Austria. The sensitivity of X-band COSMO-SkyMed® (CSK®) data with respect to five crop classes, namely carrot, corn, potato, soybean and sugarbeet is investigated. In particular, the capabilities of dual-polarization (StripMap PingPong) HH/HV, and single-polarization (StripMap Himage), HH and VH, in distinguishing among the five crop types are evaluated. A total of twenty-one Himage and ten PingPong images were acquired in a seven-months period, from April to October 2014. Therefore, the backscattering coefficient was extracted for each dataset and the classification was performed using a pixel-based support vector machine (SVM) approach. The accuracy of the obtained crop classifications was assessed by comparing them with ground truth. The dual-polarization results are contrasted between the HH and HV polarization, and with single-polarization ones (HH and VH polarizations). The best accuracy is obtained by using time-series of StripMap Himage data, at VH polarization, covering the whole season period.

Functional invertebrate prey groups reflect dietary responses to phenology and farming activity and pest control services in three sympatric species of aerially foraging insectivorous birds.

PubMed

Orłowski, Grzegorz; Karg, Jerzy; Karg, Grzegorz

2014-01-01

Farming activity severely impacts the invertebrate food resources of farmland birds, with direct mortality to populations of above-ground arthropods thorough mechanical damage during crop harvests. In this study we assessed the effects of phenological periods, including the timing of harvest, on the composition and biomass of prey consumed by three species of aerial insectivorous birds. Common Swifts Apus apus, Barn Swallows Hirundo rustica and House Martins Delichon urbica breed sympatrically and most of their diet is obtained from agricultural sources of invertebrate prey, especially from oil-seed rape crops. We categorized invertebrate prey into six functional groups, including oil-seed rape pests; pests of other arable crops; other crop-provisioned taxa; coprophilous taxa; and taxa living in non-crop and mixed crop/non-crop habitats. Seasonality impacted functional groups differently, but the general direction of change (increase/decrease) of all groups was consistent as indexed by prey composition of the three aerial insectivores studied here. After the oil-seed rape crop harvest (mid July), all three species exhibited a dietary shift from oil-seed rape insect pests to other aerial invertebrate prey groups. However, Common Switfts also consumed a relative large quantity of oil-seed rape insect pests in the late summer (August), suggesting that they could reduce pest insect emigration beyond the host plant/crop. Since these aerially foraging insectivorous birds operate in specific conditions and feed on specific pest resources unavailable to foliage/ground foraging avian predators, our results suggest that in some crops like oil-seed rape cultivations, the potential integration of the insectivory of aerial foraging birds into pest management schemes might provide economic benefits. We advise further research into the origin of airborne insects and the role of aerial insectivores as agents of the biological control of crop insect pests, especially the determination of depredation rates and the cascading effects of insectivory on crop damage and yield.

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing.

PubMed

Duncan, John M A; Dash, Jadunandan; Atkinson, Peter M

2015-04-01

Remote sensing-derived wheat crop yield-climate models were developed to highlight the impact of temperature variation during thermo-sensitive periods (anthesis and grain-filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north-west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start-of-season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature-induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands. © 2014 John Wiley & Sons Ltd.

Climate change vulnerability, adaptation and risk perceptions at farm level in Punjab, Pakistan.

PubMed

Abid, Muhammad; Schilling, Janpeter; Scheffran, Jürgen; Zulfiqar, Farhad

2016-03-15

Pakistan is among the countries highly exposed and vulnerable to climate change. The country has experienced many severe floods, droughts and storms over the last decades. However, little research has focused on the investigation of vulnerability and adaptation to climate-related risks in Pakistan. Against this backdrop, this article investigates the farm level risk perceptions and different aspects of vulnerability to climate change including sensitivity and adaptive capacity at farm level in Pakistan. We interviewed a total of 450 farming households through structured questionnaires in three districts of Punjab province of Pakistan. This study identified a number of climate-related risks perceived by farm households such as extreme temperature events, insect attacks, animal diseases and crop pests. Limited water availability, high levels of poverty and a weak role of local government in providing proper infrastructure were the factors that make farmers more sensitive to climate-related risks. Uncertainty or reduction in crop and livestock yields; changed cropping calendars and water shortage were the major adverse impacts of climate-related risks reported by farmers in the study districts. Better crop production was reported as the only positive effect. Further, this study identified a number of farm level adaptation methods employed by farm households that include changes in crop variety, crop types, planting dates and input mix, depending upon the nature of the climate-related risks. Lack of resources, limited information, lack of finances and institutional support were some constraints that limit the adaptive capacity of farm households. This study also reveals a positive role of cooperation and negative role of conflict in the adaptation process. The study suggests to address the constraints to adaptation and to improve farm level cooperation through extended outreach and distribution of institutional services, particularly climate-specific farm advisory services. Copyright © 2015 Elsevier B.V. All rights reserved.

Mind the Roots: Phenotyping Below-Ground Crop Diversity and Its Influence on Final Yield

NASA Astrophysics Data System (ADS)

Nieters, C.; Guadagno, C. R.; Lemli, S.; Hosseini, A.; Ewers, B. E.

2017-12-01

Changes in global climate patterns and water regimes are having profound impacts on worldwide crop production. An ever-growing population paired with increasing temperatures and unpredictable periods of severe drought call for accurate modeling of future crop yield. Although novel approaches are being developed in high-throughput, above-ground image phenotyping, the below-ground plant system is still poorly phenotyped. Collection of plant root morphology and hydraulics are needed to inform mathematical models to reliably estimate yields of crops grown in sub-optimal conditions. We used Brassica rapa to inform our model as it is a globally cultivated crop with several functionally diverse cultivars. Specifically, we use 7 different accessions from oilseed (R500 and Yellow Sarson), leafy type (Pac choi and Chinese cabbage), a vegetable turnip, and two Wisconsin Fast Plants (Imb211 and Fast Plant self-compatible), which have shorter life cycles and potentially large differences in allocation to roots. Bi-weekly, we harvested above and below-ground biomass to compare the varieties in terms of carbon allocation throughout their life cycle. Using WinRhizo software, we analyzed root system length and surface area to compare and contrast root morphology among cultivars. Our results confirm that root structural characteristics are crucial to explain plant water use and carbon allocation. The root:shoot ratio reveals a significant (p < 0.01) difference among crop accession. To validate the procedure across different varieties and life stages we also compared surface area results from the image-based technology to dry biomass finding a strong linear relationship (R2= 0.85). To assess the influence of a diverse above-ground morphology on the root system we also measured above-ground anatomical and physiological traits such as gas exchange, chlorophyll content, and chlorophyll a fluorescence. A thorough analysis of the root system will clarify carbon dynamics and hydraulics at the whole-plant level, improving final yield predictions.

Weather based risks and insurances for crop production in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

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

Genotype x environment interaction and its implication in identification of common bean populations with high calcium content.

PubMed

Fernandes, S B; Abreu, A F B; Ramalho, M A P

2016-06-24

The common bean is a food with high mineral content. Of the various types of beans cultivated in Brazil, carioca type beans are the most consumed. The aim of this study was to identify promising common bean populations with an emphasis toward the selection of carioca type bean lines with high calcium content. We also aimed to verify whether and how the crop season and the genotype (parental line and hybrid populations) x crop season interaction affect calcium content. A group of 3 lines of good agronomic characteristics were crossed with a group of 4 lines with high calcium content in a 3 x 4 partial diallel design. Great variability was identified among both the parental lines and the hybrid populations derived from the diallel crosses among the parental lines. We found significant interactions between crop season and both parental line and hybrid population. In the diallel analysis, only the general combining ability was significant, explaining 89.4% of the sum of squares. The RP-1, CNF05, and Safira lines exhibited the greatest calcium contents and a positive GCA. RP-1 is a line that presents high calcium content, in addition to having carioca type beans and an upright plant with high yield. To further increase the calcium content of the RP-1 line, we suggest crossing it with the CNF05 and Safira lines. Although there was a hybrid population x crop season interaction, it was possible to identify populations that performed best in terms of calcium content in both crop seasons.

The impact of cotton growing practices on soil microbiology and its relation to plant and soil health

NASA Astrophysics Data System (ADS)

Pereg, Lily

2013-04-01

Crop production and agricultural practices heavily impact the soil microbial communities, which differ among varying types of soils and environmental conditions. Soil-borne microbial communities in cotton production systems, as in every other cropping system, consist of microbial populations that may either be pathogenic, beneficial or neutral with respect to the cotton crop. Crop production practices have major roles in determining the composition of microbial communities and function of microbial populations in soils. The structure and function of any given microbial community is determined by various factors, including those that are influenced by farming and those not controlled by farming activities. Examples of the latter are environmental conditions such as soil type, temperature, daylight length and UV radiation, air humidity, atmospheric pressure and some abiotic features of the soil. On the other hand, crop production practices may determine other abiotic soil properties, such as water content, density, oxygen levels, mineral and elemental nutrient levels and the load of other crop-related soil amendments. Moreover, crop production highly influences the biotic properties of the soil and has a major role in determining the fate of soil-borne microbial communities associated with the crop plant. Various microbial strains react differently to the presence of certain plants and plant exudates. Therefore, the type of plant and crop rotations are important factors determining microbial communities. In addition, practice management, e.g. soil cultivation versus crop stubble retention, have a major effect on the soil conditions and, thus, on microbial community structure and function. All of the above-mentioned factors can lead to preferential selection of certain microbial population over others. It may affect not only the composition of microbial communities (diversity and abundance of microbial members) but also the function of the community (the ability of different microbes to perform certain activities). Therefore, agricultural practices may determine the ability of beneficial microbes to realise their plant growth promoting potential or the pathogenic expression of others. This presentation will review the current knowledge about the impact of cotton growing practices on microbial communities and soil health in different environments as well as endeavour to identify gaps worthwhile exploring in future research for promoting plant growth in healthy soils.

Field Note: A Disease Specific Expert System for the Indian Mango Crop

ERIC Educational Resources Information Center

Chakrabarti, Dilip Kumar; Chakraborty, Pinaki

2007-01-01

Mango ("Mangifera indica") is a popular fruit and an important cash crop of southeast Asia. The mango malformation disease has been responsible for the degraded yield of the crop now for a long time (Kumar and Chakrabarti, 1997). The disease is difficult to cure and often takes the shape of an epidemic. Though much study has been done…

Improved conversion of herbaceous biomass to biofuels: Potential for modification of key plant characteristics

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

Sladden, S.E.; Bransby, D.I.

1989-10-01

Biomass crops are converted to fuels via biochemical and thermochemical processes. The process preferred depends on properties and cost of available feedstocks, and on the specific products desired. Since most mature biomass crops are composed of up to 80% cell wall fibers, the properties of these fibers determine, to a large degree, the conversion potential of the crop. However, biomass crops also contain small amounts of proteins, soluble carbohydrates and interfering materials (e.g., tannins and silica) which also influence the desirability of the feedstock in specific conversion processes. Fortunately, wide variation exists in the chemical composition of potential biomass crops.more » Although the chemical composition of feedstocks can be influenced significantly with judicious management has species selection, some traits are sufficiently heritable to permit breeding for improved feedstock composition. In addition to breeding for specific compositional traits directly, selection for in vitro digestibility or for easily-measured canopy or physiological traits may lead to more rapid and efficient progress in feedstock improvement, provided those measurements are highly-correlated with desirable feedstock composition. At the same time breeders must improve, or at least avoid damaging, stand longevity, tendency of plants to lodge, and establishment traits (e.g., disease resistance and seedling vigor). 46 refs., 8 tabs.« less

Probabilistic assessment of phenophase-wise agricultural drought risk under different sowing windows: a case study with rainfed soybean.

PubMed

Dhakar, Rajkumar; Sarath Chandran, M A; Nagar, Shivani; Visha Kumari, V

2017-11-23

A new methodology for crop-growth stage-specific assessment of agricultural drought risk under a variable sowing window is proposed for the soybean crop. It encompasses three drought indices, which include Crop-Specific Drought Index (CSDI), Vegetation Condition Index (VCI), and Standardized Precipitation Evapotranspiration Index (SPEI). The unique features of crop-growth stage-specific nature and spatial and multi-scalar coverage provide a comprehensive assessment of agricultural drought risk. This study was conducted in 10 major soybean-growing districts of Madhya Pradesh state of India. These areas contribute about 60% of the total soybean production for the country. The phenophase most vulnerable to agricultural drought was identified (germination and flowering in our case) for each district across four sowing windows. The agricultural drought risk was quantified at various severity levels (moderate, severe, and very severe) for each growth stage and sowing window. Validation of the proposed new methodology also yielded results with a high correlation coefficient between percent probability of agricultural drought risk and yield risk (r = 0.92). Assessment by proximity matrix yielded a similar statistic. Expectations for the proposed methodology are better mitigation-oriented management and improved crop contingency plans for planners and decision makers.

Quantifying Crop Specific Blue and Green Water Footprints and the Spatial Allocation of Virtual Water in China

NASA Astrophysics Data System (ADS)

Pan, J.; Smith, T.; McLaughlin, D.

2016-12-01

China, which had a population of 1.38 billion in 2013, is expected to peak at about 1.45 billion around 2030, with per capita food demand likely to increase significantly. The population growth and diet change make prospects of future available water and food worrisome for China. Quantitative estimates of crop specific blue and green water footprints provide useful insight about the roles of different water sources and give guidance for agricultural and water resource planning. This study uses reanalysis methods to merge diverse datasets, including information on water fluxes and land use, to estimate crop-specific green and blue water consumption at 0.5 degree spatial resolution. The estimates incorporate, through constraints in the reanalysis procedure, important physical connections between the water and land resources that support agriculture. These connections are important since land use affects evapotranspiration and runoff while water availability and crop area affect crop production and virtual water content. The results show that green water accounts for 86% and blue water accounts for 14% of the total national agricultural water footprint, respectively. The water footprints of cereals (wheat, maize and rice) and soybeans account for 51% of the total agricultural water footprint. Cereals and soybeans together account for 85% of the total blue water footprint.

Real-time x-ray fluorescence analysis of crop canopy to spatially assess phytoextraction efficiency and subsurface status of low-Z elements: a case study for phosphorus

NASA Astrophysics Data System (ADS)

Dao, Thanh

2017-04-01

Leaf analysis has been extensively used to interpret results of nutrient supplementation studies about crop growth and yield responses, and to define availability thresholds for a wide range of soils and climatic conditions. The compositional results reflect the nutritional status, uptake efficiency, and the geo-chemical environment of the element in the subsurface. An X-ray fluorescence (XRF)-based proximal sensing approach was evaluated and proposed for real-time determination of water content and element-specific composition of corn seedling leaves, which was comprised mostly of essential macronutrients of low-atomic number Z, such as phosphorus (P) or potassium. Intensities of scattered radiation associated with the X-ray tube Ag anode were significantly correlated with leaf water content (θw), which was used to normalize fluorescence intensities of P. Crop canopy water status was also obtained as ancillary data. The θw - P relative concentration relationship was best described by a sigmoidal function (r2 = 0.938 and RMSE=0.02). The Ag-Lα line was deemed to be effective for normalizing the intensities of Kα lines of P and other low-Z elements, in addition to the commonly used Kα and Kβ lines. Its intensity was significantly correlated to leaf water content and was used to develop calibrations and obtain P concentration on a dry weight basis and unbiased estimates of crop P status. Therefore, the in situ fluorescence sensing system presents a new paradigm in nutrient management to re-evaluate calibrations of observed crop responses against those predicted by current soil testing and fertility recommendations. Updates to the rates of supplemental P and crop growth response relationships are critically needed as crop cultivars, supplemental P sources, or alternative soil-crop management systems are continually changing. Changes in soil microenvironments that are site- or field-specific, and climate are expected to continue to be the norm and can modify those soil-plant relationships. The high-throughput of hand-held XRFS enhances our ability to make management adjustment, particularly at the short early stages of growth, when crop plants are most susceptible to P deficiency. The precision of macronutrient management can be applied at a field-specific scale. As the process can be repeated for each growing season, the knowledge base of soil fertility, crop extraction efficiency and uptake, and elemental availability can only grow in time to improve the predictability of site-specific plant responses to given yield goals and levels of nutrient and soil management inputs. Matching nutrient supply to actual levels needed by the crop minimizes loss of excess agricultural inputs and reduces the risks of adverse impact on the health of the surrounding soil and water resources.

Spillover from adjacent crop and forest habitats shapes carabid beetle assemblages in fragmented semi-natural grasslands.

PubMed

Schneider, Gudrun; Krauss, Jochen; Boetzl, Fabian A; Fritze, Michael-Andreas; Steffan-Dewenter, Ingolf

2016-12-01

Semi-natural grasslands in Europe are insect biodiversity hotspots and important source habitats delivering ecosystem services to adjacent agricultural land by species spillover. However, this spillover might also occur in the opposite direction, affecting the diversity of semi-natural grasslands. This opposite spillover has got little attention in scientific literature even though generalist species penetrating into the grasslands can affect local biotic interactions, community composition and the conservation value of grassland habitats. In this study, we examined spillover effects from two different adjacent habitat types on carabid beetle assemblages in 20 semi-natural calcareous grasslands. The grasslands were either adjacent to a cereal crop field or to a coniferous forest. We found distinct differences in carabid beetle assemblages in calcareous grasslands depending on adjacent habitat type. Species richness and activity density were higher, but the evenness was lower in calcareous grasslands adjacent to crop fields compared with calcareous grasslands adjacent to coniferous forests. Further, we found a strong spillover of carabid beetles from adjacent crop fields after crop harvest, which may result in transiently increased predation pressure and resource competition in calcareous grasslands. Our results highlight that species composition, diversity and presumably ecosystem functions within semi-natural habitats are affected by the type and management of surrounding habitats. This needs to be considered by nature conservation measures, which aim to protect the unique insect communities of semi-natural European grasslands.

Altered pesticide use on transgenic crops and the associated general impact from an environmental perspective.

PubMed

Kleter, Gijs A; Bhula, Raj; Bodnaruk, Kevin; Carazo, Elizabeth; Felsot, Allan S; Harris, Caroline A; Katayama, Arata; Kuiper, Harry A; Racke, Kenneth D; Rubin, Baruch; Shevah, Yehuda; Stephenson, Gerald R; Tanaka, Keiji; Unsworth, John; Wauchope, R Donald; Wong, Sue-Sun

2007-11-01

The large-scale commercial cultivation of transgenic crops has undergone a steady increase since their introduction 10 years ago. Most of these crops bear introduced traits that are of agronomic importance, such as herbicide or insect resistance. These traits are likely to impact upon the use of pesticides on these crops, as well as the pesticide market as a whole. Organizations like USDA-ERS and NCFAP monitor the changes in crop pest management associated with the adoption of transgenic crops. As part of an IUPAC project on this topic, recent data are reviewed regarding the alterations in pesticide use that have been observed in practice. Most results indicate a decrease in the amounts of active ingredients applied to transgenic crops compared with conventional crops. In addition, a generic environmental indicator -- the environmental impact quotient (EIQ) -- has been applied by these authors and others to estimate the environmental consequences of the altered pesticide use on transgenic crops. The results show that the predicted environmental impact decreases in transgenic crops. With the advent of new types of agronomic trait and crops that have been genetically modified, it is useful to take also their potential environmental impacts into account.

The bacterial communities associated with honey bee (Apis mellifera) foragers.

PubMed

Corby-Harris, Vanessa; Maes, Patrick; Anderson, Kirk E

2014-01-01

The honey bee is a key pollinator species in decline worldwide. As part of a commercial operation, bee colonies are exposed to a variety of agricultural ecosystems throughout the year and a multitude of environmental variables that may affect the microbial balance of individuals and the hive. While many recent studies support the idea of a core microbiota in guts of younger in-hive bees, it is unknown whether this core is present in forager bees or the pollen they carry back to the hive. Additionally, several studies hypothesize that the foregut (crop), a key interface between the pollination environment and hive food stores, contains a set of 13 lactic acid bacteria (LAB) that inoculate collected pollen and act in synergy to preserve pollen stores. Here, we used a combination of 454 based 16S rRNA gene sequencing of the microbial communities of forager guts, crops, and corbicular pollen and crop plate counts to show that (1) despite a very different diet, forager guts contain a core microbiota similar to that found in younger bees, (2) corbicular pollen contains a diverse community dominated by hive-specific, environmental or phyllosphere bacteria that are not prevalent in the gut or crop, and (3) the 13 LAB found in culture-based studies are not specific to the crop but are a small subset of midgut or hindgut specific bacteria identified in many recent 454 amplicon-based studies. The crop is dominated by Lactobacillus kunkeei, and Alpha 2.2 (Acetobacteraceae), highly osmotolerant and acid resistant bacteria found in stored pollen and honey. Crop taxa at low abundance include core hindgut bacteria in transit to their primary niche, and potential pathogens or food spoilage organisms seemingly vectored from the pollination environment. We conclude that the crop microbial environment is influenced by worker task, and may function in both decontamination and inoculation.

The Bacterial Communities Associated with Honey Bee (Apis mellifera) Foragers

PubMed Central

Corby-Harris, Vanessa; Maes, Patrick; Anderson, Kirk E.

2014-01-01

The honey bee is a key pollinator species in decline worldwide. As part of a commercial operation, bee colonies are exposed to a variety of agricultural ecosystems throughout the year and a multitude of environmental variables that may affect the microbial balance of individuals and the hive. While many recent studies support the idea of a core microbiota in guts of younger in-hive bees, it is unknown whether this core is present in forager bees or the pollen they carry back to the hive. Additionally, several studies hypothesize that the foregut (crop), a key interface between the pollination environment and hive food stores, contains a set of 13 lactic acid bacteria (LAB) that inoculate collected pollen and act in synergy to preserve pollen stores. Here, we used a combination of 454 based 16S rRNA gene sequencing of the microbial communities of forager guts, crops, and corbicular pollen and crop plate counts to show that (1) despite a very different diet, forager guts contain a core microbiota similar to that found in younger bees, (2) corbicular pollen contains a diverse community dominated by hive-specific, environmental or phyllosphere bacteria that are not prevalent in the gut or crop, and (3) the 13 LAB found in culture-based studies are not specific to the crop but are a small subset of midgut or hindgut specific bacteria identified in many recent 454 amplicon-based studies. The crop is dominated by Lactobacillus kunkeei, and Alpha 2.2 (Acetobacteraceae), highly osmotolerant and acid resistant bacteria found in stored pollen and honey. Crop taxa at low abundance include core hindgut bacteria in transit to their primary niche, and potential pathogens or food spoilage organisms seemingly vectored from the pollination environment. We conclude that the crop microbial environment is influenced by worker task, and may function in both decontamination and inoculation. PMID:24740297

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.

Characteristics of AVIRIS Band Measurements in Desert Agroecosystems in the Area of Blythe, California. 1; Studies of Cotton Spectra

NASA Technical Reports Server (NTRS)

Hanna, Safwat H. Shakir

2001-01-01

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from Blythe, California, were acquired in June 1997 to study agricultural spectra from different crops and to identify crops in other areas with similar environmental factors and similar spectral properties. The main objectives of this study are: (1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with ground spectra measured by a FieldSpec ASD spectrometer; (2) to explore the use of AVIRIS spectral images for identifying agricultural crops; (3) to study the spectral expression of environmental factors on selected crops; and (4) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. To support our study, on July 18 and 19, 2000, we collected spectra using the FieldSpec spectrometer from selected fields with different crops in the Blythe area of California (longitude 114 deg 33.28 W and latitude 33 deg 25.42 N to longitude 1140 44.53 W and latitude 33 deg 39.77 N). These crops were cotton in different stages of growth, varieties of grass pure or mixed, Sudan grass, Bermuda grass, Teff grass, and alfalfa. Some of the fields were treated with different types of irrigation (i.e., wet to dry conditions). Additional parameters were studied such as the soil water content (WC), pH, and organic matter (OM). The results of this study showed that for crops known to be similar, there is a significant correlation between the spectra that were collected by AVIRIS in 1997 and spectra measured by the FieldSpec (registered) spectrometer in 2000. This correlation allowed development of a spectral library to be used in ENVI-IDL analysis software. This library was used successfully to identify different crops. Furthermore, using IDL algorithms of Spectral Angle Mapper classification (SAM), spectral feature fitting (SFF) and spectral binary encoding (SPE) showed that there is excellent agreement between the predicted and the actual crop type (i.e., the correlation is between 85-90% match). Further use of the AVIRIS images can be of a value to crop identification or crop yield for commercial use.

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Fungus-Farming Termites Selectively Bury Weedy Fungi that Smell Different from Crop Fungi.

PubMed

Katariya, Lakshya; Ramesh, Priya B; Gopalappa, Thejashwini; Desireddy, Sathish; Bessière, Jean-Marie; Borges, Renee M

2017-10-01

Mutualistic associations such as the fungal farms of insects are prone to parasitism and are consequently vulnerable to attack by weeds and pests. Therefore, efficient farm management requires quick detection of weeds for their elimination. Furthermore, if the available weedicides are non-specific, then the ability of insects to discriminate between crop and weeds becomes essential for targeted application of such compounds. Here, we demonstrate for the first time in fungus-farming insects, that worker castes of the fungus-growing termite Odontotermes obesus discriminate between their crop (Termitomyces) and the weedy (Pseudoxylaria) fungi, even if exposed to only fungal scents. Termites respond to the presence of fungal mycelium or scent alone, by burying the weed with the offered material such as soil or agar, possibly anointing the weed with chemicals in the process. The scent profiles of crop and weedy fungi are distinct and the differences are likely exploited by termites to selectively mount their defences. Sesquiterpene compounds such as aristolene and viridiflorol, which are absent from crop odours, may constitute the "weedy scent". Our results provide a general mechanism of how other fungus-farming insects could avoid indiscriminate application of non-specific fungicides which could lead to poisoning their crops, and have bearing on the stability of the mutualism between termites and their crop fungus in the face of parasitism by weedy fungi.

Engineering of CRISPR/Cas9‐mediated potyvirus resistance in transgene‐free Arabidopsis plants

PubMed Central

Pyott, Douglas E.; Sheehan, Emma

2016-01-01

Summary Members of the eukaryotic translation initiation factor (eIF) gene family, including eIF4E and its paralogue eIF(iso)4E, have previously been identified as recessive resistance alleles against various potyviruses in a range of different hosts. However, the identification and introgression of these alleles into important crop species is often limited. In this study, we utilise CRISPR/Cas9 technology to introduce sequence‐specific deleterious point mutations at the eIF(iso)4E locus in Arabidopsis thaliana to successfully engineer complete resistance to Turnip mosaic virus (TuMV), a major pathogen in field‐grown vegetable crops. By segregating the induced mutation from the CRISPR/Cas9 transgene, we outline a framework for the production of heritable, homozygous mutations in the transgene‐free T2 generation in self‐pollinating species. Analysis of dry weights and flowering times for four independent T3 lines revealed no differences from wild‐type plants under standard growth conditions, suggesting that homozygous mutations in eIF(iso)4E do not affect plant vigour. Thus, the established CRISPR/Cas9 technology provides a new approach for the generation of Potyvirus resistance alleles in important crops without the use of persistent transgenes. PMID:27103354

Do whole-food animal feeding studies have any value in the safety assessment of GM crops?

PubMed

Herman, Rod A; Ekmay, Ricardo

2014-02-01

The use of whole-food (grain meal contained in feed) animal-feeding studies to support the safety assessment of genetically modified crops has been contentious. This may be, in part, a consequence of poorly agreed upon study objectives. Whole-food animal-feeding studies have been postulated to be useful in detecting both expected and unexpected effects on the composition of genetically modified crops. While the justification of animal feeding studies to detect unexpected effects may be inadequately supported, there may be better justification to conduct such studies in specific cases to investigate the consequences of expected compositional effects including expression of transgenic proteins. Such studies may be justified when (1) safety cannot reasonably be predicted from other evidence, (2) reasonable hypothesis for adverse effects are postulated, (3) the compositional component in question cannot be isolated or enriched in an active form for inclusion in animal feeding studies, and (4) reasonable multiples of exposure can be accomplished relative to human diets. The study design for whole-food animal-feeding studies should be hypotheses-driven, and the types of data collected should be consistent with adverse effects that are known to occur from dietary components of biological origin. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Crop changes from the XVI century to the present in a hill/mountain area of eastern Liguria (Italy)

PubMed Central

Gentili, Rodolfo; Gentili, Elio; Sgorbati, Sergio

2009-01-01

Background Chronological information on the composition and structure of agrocenoses and detailed features of land cover referring to specific areas are uncommon in ethnobotanical studies, especially for periods before the XIX century. The aim of this study was to analyse the type of crop or the characteristics of soil cover from the XVI century to the present. Methods This diachronic analysis was accomplished through archival research on the inventories of the Parish of St. Mary and those of the Municipality of Pignone and from recent surveys conducted in an area of eastern Liguria (Italy). Results Archival data revealed that in study area the primary means of subsistence during the last five centuries, until the first half of the XX century, was chestnuts. In the XVIII and XIX centuries, crop diversification strongly increased in comparison with previous and subsequent periods. In more recent times, the abandonment of agricultural practices has favoured the re-colonisation of mixed woodland or cluster-pine woodland. Conclusion Ancient documents in the ecclesiastic or municipal inventories can be a very useful tool for enhancing the knowledge of agricultural practice, as well as of subsistence methods favoured by local populations during a particular time and for reconstructing land use change over time. PMID:19361339

Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities

USGS Publications Warehouse

Nogeire, Theresa M.; Davis, Frank W.; Crooks, Kevin R.; McRae, Brad H.; Lyren, Lisa M.; Boydston, Erin E.

2015-01-01

As natural habitats become fragmented by human activities, animals must increasingly move through human-dominated systems, particularly agricultural landscapes. Mapping areas important for animal movement has therefore become a key part of conservation planning. Models of landscape connectivity are often parameterized using expert opinion and seldom distinguish between the risks and barriers presented by different crop types. Recent research, however, suggests different crop types, such as row crops and orchards, differ in the degree to which they facilitate or impede species movements. Like many mammalian carnivores, bobcats (Lynx rufus) are sensitive to fragmentation and loss of connectivity between habitat patches. We investigated how distinguishing between different agricultural land covers might change conclusions about the relative conservation importance of different land uses in a Mediterranean ecosystem. Bobcats moved relatively quickly in row crops but relatively slowly in orchards, at rates similar to those in natural habitats of woodlands and scrub. We found that parameterizing a connectivity model using empirical data on bobcat movements in agricultural lands and other land covers, instead of parameterizing the model using habitat suitability indices based on expert opinion, altered locations of predicted animal movement routes. These results emphasize that differentiating between types of agriculture can alter conservation planning outcomes.

Determining crop residue type and class using satellite acquired data. M.S. Thesis Progress Report, Jun. 1990

NASA Technical Reports Server (NTRS)

Zhuang, Xin

1990-01-01

LANDSAT Thematic Mapper (TM) data for March 23, 1987 with accompanying ground truth data for the study area in Miami County, IN were used to determine crop residue type and class. Principle components and spectral ratioing transformations were applied to the LANDSAT TM data. One graphic information system (GIS) layer of land ownership was added to each original image as the eighth band of data in an attempt to improve classification. Maximum likelihood, minimum distance, and neural networks were used to classify the original, transformed, and GIS-enhanced remotely sensed data. Crop residues could be separated from one another and from bare soil and other biomass. Two types of crop residue and four classes were identified from each LANDSAT TM image. The maximum likelihood classifier performed the best classification for each original image without need of any transformation. The neural network classifier was able to improve the classification by incorporating a GIS-layer of land ownership as an eighth band of data. The maximum likelihood classifier was unable to consider this eighth band of data and thus, its results could not be improved by its consideration.

Assuring the safety of genetically modified (GM) foods: the importance of an holistic, integrative approach.

PubMed

Cockburn, Andrew

2002-09-11

Genes change continuously by natural mutation and recombination enabling man to select and breed crops having the most desirable traits such as yield or flavour. Genetic modification (GM) is a recent development which allows specific genes to be identified, isolated, copied and inserted into other plants with a high level of specificity. The food safety considerations for GM crops are basically the same as those arising from conventionally bred crops, very few of which have been subject to any testing yet are generally regarded as being safe to eat. In contrast a rigorous safety testing paradigm has been developed for GM crops, which utilises a systematic, stepwise and holistic approach. The resultant science based process, focuses on a classical evaluation of the toxic potential of the introduced novel trait and the wholesomeness of the transformed crop. In addition, detailed consideration is given to the history and safe use of the parent crop as well as that of the gene donor. The overall safety evaluation is conducted under the concept known as substantial equivalence which is enshrined in all international crop biotechnology guidelines. This provides the framework for a comparative approach to identify the similarities and differences between the GM product and its comparator which has a known history of safe use. By building a detailed profile on each step in the transformation process, from parent to new crop, and by thoroughly evaluating the significance from a safety perspective, of any differences that may be detected, a very comprehensive matrix of information is constructed which enables the conclusion as to whether the GM crop, derived food or feed is as safe as its traditional counterpart. Using this approach in the evaluation of more than 50 GM crops which have been approved worldwide, the conclusion has been that foods and feeds derived from genetically modified crops are as safe and nutritious as those derived from traditional crops. The lack of any adverse effects resulting from the production and consumption of GM crops grown on more than 300 million cumulative acres over the last 5 years supports these safety conclusions.

Targeting the right input data to improve crop modeling at global level

NASA Astrophysics Data System (ADS)

Adam, M.; Robertson, R.; Gbegbelegbe, S.; Jones, J. W.; Boote, K. J.; Asseng, S.

2012-12-01

Designed for location-specific simulations, the use of crop models at a global level raises important questions. Crop models are originally premised on small unit areas where environmental conditions and management practices are considered homogeneous. Specific information describing soils, climate, management, and crop characteristics are used in the calibration process. However, when scaling up for global application, we rely on information derived from geographical information systems and weather generators. To run crop models at broad, we use a modeling platform that assumes a uniformly generated grid cell as a unit area. Specific weather, specific soil and specific management practices for each crop are represented for each of the cell grids. Studies on the impacts of the uncertainties of weather information and climate change on crop yield at a global level have been carried out (Osborne et al, 2007, Nelson et al., 2010, van Bussel et al, 2011). Detailed information on soils and management practices at global level are very scarce but recognized to be of critical importance (Reidsma et al., 2009). Few attempts to assess the impact of their uncertainties on cropping systems performances can be found. The objectives of this study are (i) to determine sensitivities of a crop model to soil and management practices, inputs most relevant to low input rainfed cropping systems, and (ii) to define hotspots of sensitivity according to the input data. We ran DSSAT v4.5 globally (CERES-CROPSIM) to simulate wheat yields at 45arc-minute resolution. Cultivar parameters were calibrated and validated for different mega-environments (results not shown). The model was run for nitrogen-limited production systems. This setting was chosen as the most representative to simulate actual yield (especially for low-input rainfed agricultural systems) and assumes crop growth to be free of any pest and diseases damages. We conducted a sensitivity analysis on contrasting management practices, initial soil conditions, and soil characteristics information. Management practices were represented by planting date and the amount of fertilizer, initial conditions estimates for initial nitrogen, soil water, and stable soil carbon, and soil information is based on a simplified version of the WISE database, characterized by soil organic matter, texture and soil depth. We considered these factors as the most important determinants of nutrient supply to crops during their growing season. Our first global results demonstrate that the model is most sensitive to the initial conditions in terms of soil carbon and nitrogen (CN): wheat yields decreased by 45% when soil CN is null and increase by 15% when twice the soil CN content of the reference run is used. The yields did not appear to be very sensitive to initial soil water conditions, varying from 0% yield increase when initial soil water is set to wilting point to 6% yield increase when it was set to field capacity. They are slightly sensitive to nitrogen application: 8% yield decrease when no N is applied to 9% yield increase when 150 kg.ha-1 is applied. However, with closer examination of results, the model is more sensitive to nitrogen application than to initial soil CN content in Vietnam, Thailand and Japan compared to the rest of the world. More analyses per region and results on the planting dates and soil properties will be presented.

Soil thresholds and a decision tool to manage food safety of crops grown in chlordecone polluted soil in the French West Indies.

PubMed

Clostre, Florence; Letourmy, Philippe; Lesueur-Jannoyer, Magalie

2017-04-01

Due to the persistent pollution of soils by an organochlorine, chlordecone (CLD also known as Kepone © ) in the French West Indies, some crops may be contaminated beyond the European regulatory threshold, the maximum residue limit (MRL). Farmers need to be able to foresee the risk of not complying with the regulatory threshold in each field and for each crop, if not, farmers whose fields are contaminated would have to stop cultivating certain crops in the fields concerned. To help farmers make the right choices, we studied the relationship between contamination of the soil and contamination of crops. We showed that contamination of a crop by CLD depended on the crop concerned, the soil CLD content and the type of soil. We grouped crop products in three categories: (i) non-uptakers and low-uptakers, (ii) medium-uptakers, and (iii) high-uptakers, according to their level of contamination and the resulting risk of exceeding MRL. Using a simulation model, we computed the soil threshold required to ensure the risk of not complying with MRL was sufficiently low for each crop product and soil type. Threshold values ranged from 0.02 μgkg -1 for dasheen grown in nitisol to 1.7 μgkg -1 for yam grown in andosol in the high-uptake category, and from 1 μgkg -1 for lettuce grown in nitisol to 45 μgkg -1 for the leaves of spring onions grown in andosol in the medium-uptake category. Contamination of non-uptakers and low-uptakers did not depend on soil contamination. With these results, we built an easy-to-use decision support tool based on two soil thresholds (0.1 and 1 μgkg -1 ) to enable growers to adapt their cropping system and hence to be able to continue farming. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Understanding the contribution of habitats and regional variation to long-term population trends in tricolored blackbirds

PubMed Central

Graves, Emily E; Holyoak, Marcel; Rodd Kelsey, T; Meese, Robert J

2013-01-01

Population trends represent a minimum amount of information required to assess the conservation status of a species. However, understanding and detecting trends can be complicated by variation among habitats and regions, and by dispersal connecting habitats through source-sink dynamics. We analyzed trends in breeding populations between habitats and regions to better understand the overall dynamics of a species' decline. Specifically, we analyzed historical trends in breeding populations of tricolored blackbirds (Agelaius tricolor) using breeding records from 1907 to 2009. The species breeds itinerantly and ephemerally uses multiple habitat types and breeding areas, which make interpretation of trends complex. We found overall abundance declines of 63% between 1935 and 1975. Since 1980 overall declines became nonsignificant and obscure despite large amounts of data from 1980 to 2009. Temporal trends differed between breeding habitat types and were associated with regional differences in population declines. A new habitat, triticale crops (a wheat-rye hybrid grain) produced colonies 40× larger, on average, than other breeding habitats, and contributed to a change in regional distribution since it primarily occurred in a single region. The mechanism for such an effect is not clear, but could represent the local availability of foodstuffs in the landscape rather than something specific to triticale crops. While variation in trends among habitats clearly occurred, they could not easily be ascribed to source-sink dynamics, ecological traps, habitat selection or other detailed ecological mechanisms. Nonetheless, such exchanges provide valuable information to guide management of dynamic systems. PMID:24101977

[Nitrogen stress measurement of canola based on multi-spectral charged coupled device imaging sensor].

PubMed

Feng, Lei; Fang, Hui; Zhou, Wei-Jun; Huang, Min; He, Yong

2006-09-01

Site-specific variable nitrogen application is one of the major precision crop production management operations. Obtaining sufficient crop nitrogen stress information is essential for achieving effective site-specific nitrogen applications. The present paper describes the development of a multi-spectral nitrogen deficiency sensor, which uses three channels (green, red, near-infrared) of crop images to determine the nitrogen level of canola. This sensor assesses the nitrogen stress by means of estimated SPAD value of the canola based on canola canopy reflectance sensed using three channels (green, red, near-infrared) of the multi-spectral camera. The core of this investigation is the calibration methods between the multi-spectral references and the nitrogen levels in crops measured using a SPAD 502 chlorophyll meter. Based on the results obtained from this study, it can be concluded that a multi-spectral CCD camera can provide sufficient information to perform reasonable SPAD values estimation during field operations.

Controlled Ecological Life Support System (CELSS) modeling

NASA Technical Reports Server (NTRS)

Drysdale, Alan; Thomas, Mark; Fresa, Mark; Wheeler, Ray

1992-01-01

Attention is given to CELSS, a critical technology for the Space Exploration Initiative. OCAM (object-oriented CELSS analysis and modeling) models carbon, hydrogen, and oxygen recycling. Multiple crops and plant types can be simulated. Resource recovery options from inedible biomass include leaching, enzyme treatment, aerobic digestion, and mushroom and fish growth. The benefit of using many small crops overlapping in time, instead of a single large crop, is demonstrated. Unanticipated results include startup transients which reduce the benefit of multiple small crops. The relative contributions of mass, energy, and manpower to system cost are analyzed in order to determine appropriate research directions.

Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

NASA Astrophysics Data System (ADS)

Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

2010-09-01

In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross-calibration and co-registration. In order to avoid such problems and to generate spatially distributed values of Kc capturing field-specific crop development, the employment of vegetation indices derived from medium resolution MODIS data having a higher temporal sampling has been investigated. The spatial and temporal correlation between NDVI (Normalized Difference Vegetation Index) and crop coefficients for different herbaceous and arboreal cultivations has been investigated to define their relationships. Through this approach site-specific crop coefficients were derived taking into account the effective ground coverage and status. The analysis has been applied on the 2005-2008 time series for the Basilicata region, Southern Italy.

Sustainable Agriculture: Cover Cropping

ERIC Educational Resources Information Center

Webster, Megan

2018-01-01

Sustainable agriculture practices are increasingly being used by farmers to maintain soil quality, increase biodiversity, and promote production of food that is environmentally safe. There are several types of sustainable agriculture practices such as organic farming, crop rotation, and aquaculture. This lesson plan focuses on the sustainable…

Remote sensing in Iowa agriculture. [cropland inventory, soils, forestland, and crop diseases

NASA Technical Reports Server (NTRS)

Mahlstede, J. P. (Principal Investigator); Carlson, R. E.

1973-01-01

The author has identified the following significant results. Results include the estimation of forested and crop vegetation acreages using the ERTS-1 imagery. The methods used to achieve these estimates still require refinement, but the results appear promising. Practical applications would be directed toward achieving current land use inventories of these natural resources. This data is presently collected by sampling type surveys. If ERTS-1 can observe this and area estimates can be determined accurately, then a step forward has been achieved. Cost benefit relationship will have to be favorable. Problems still exist in these estimation techniques due to the diversity of the scene observed in the ERTS-1 imagery covering other part of Iowa. This is due to influence of topography and soils upon the adaptability of the vegetation to specific areas of the state. The state mosaic produced from ERTS-1 imagery shows these patterns very well. Research directed to acreage estimates is continuing.

Impact of crop residue management on crop production and soil chemistry after seven years of crop rotation in temperate climate, loamy soils

PubMed Central

Hiel, Marie-Pierre; Barbieux, Sophie; Pierreux, Jérôme; Olivier, Claire; Lobet, Guillaume; Roisin, Christian; Garré, Sarah; Colinet, Gilles; Bodson, Bernard

2018-01-01

Society is increasingly demanding a more sustainable management of agro-ecosystems in a context of climate change and an ever growing global population. The fate of crop residues is one of the important management aspects under debate, since it represents an unneglectable quantity of organic matter which can be kept in or removed from the agro-ecosystem. The topic of residue management is not new, but the need for global conclusion on the impact of crop residue management on the agro-ecosystem linked to local pedo-climatic conditions has become apparent with an increasing amount of studies showing a diversity of conclusions. This study specifically focusses on temperate climate and loamy soil using a seven-year data set. Between 2008 and 2016, we compared four contrasting residue management strategies differing in the amount of crop residues returned to the soil (incorporation vs. exportation of residues) and in the type of tillage (reduced tillage (10 cm depth) vs. conventional tillage (ploughing at 25 cm depth)) in a field experiment. We assessed the impact of the crop residue management on crop production (three crops—winter wheat, faba bean and maize—cultivated over six cropping seasons), soil organic carbon content, nitrate (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${\\mathrm{NO}}_{3}^{-}$\\end{document}NO3−), phosphorus (P) and potassium (K) soil content and uptake by the crops. The main differences came primarily from the tillage practice and less from the restitution or removal of residues. All years and crops combined, conventional tillage resulted in a yield advantage of 3.4% as compared to reduced tillage, which can be partly explained by a lower germination rate observed under reduced tillage, especially during drier years. On average, only small differences were observed for total organic carbon (TOC) content of the soil, but reduced tillage resulted in a very clear stratification of TOC and also of P and K content as compared to conventional tillage. We observed no effect of residue management on the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${\\mathrm{NO}}_{3}^{-}$\\end{document}NO3− content, since the effect of fertilization dominated the effect of residue management. To confirm the results and enhance early tendencies, we believe that the experiment should be followed up in the future to observe whether more consistent changes in the whole agro-ecosystem functioning are present on the long term when managing residues with contrasted strategies. PMID:29844983

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.

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

Automated observation of diurnal solar-induced chlorophyll fluorescence for better understanding of crop photosynthesis

NASA Astrophysics Data System (ADS)

Huang, C.; Zhang, L.; Wang, S.; Qiao, N.

2016-12-01

Remotely sensed solar-induced chlorophyll fluorescence (SIF) has been considered an ideal probe in monitoring vegetation photosynthesis. However, numerous challenges have greatly limited its wide applications, including accurate estimate of faint SIF from the observed apparent reflected radiation, uncertainties in inferring the vegetation photosynthesis as well as lack of validation. These difficulties should be resolved at ground-based controlled scales before the launch of SIF satellite platforms such as ESA's FLEX (to be launched 2021). Currently, increasing continuous and long-term automated SIF measurement systems have been reported for better understanding the diurnal and seasonal changes of vegetation photosynthesis. This study introduces a newly developed automated SIF field measurement system (Auto-SIF, 500-800 nm, FWHM=0.74 nm, SSI=0.38 nm, SNR=1000:1, see figure 1) in China and its initial results for inferring photosynthesis of different crops including soybean (three types), maize (two types) and rice (two types). The experiments were conducted at the test crop field affiliated to the Institute of Genetics and Development Biology, Chinese Academy of Sciences. The Auto-SIF incorporates two observation modes, i.e., reference panel mode and target mode (see figure 1), and the two modes can be switched very quickly through an electrical motor. All diurnal super-spectra data and SIFs of crops were collected in clear days and with a finer time interval of 1minute, therefore they can be easily resampled to different time intervals (see figure 2) in order for convenient comparisons with other data from different observation platforms, like 30-minute tower-flux GPP data. For better understanding of crop photosynthesis, Li-6400 XT (LI-COR, Inc.) and TES-1339R light meter were respectively used in this study to simultaneously obtain diurnal dynamics of leaf-level SIFs and sun incoming flux. Due to the availability of wide spectral range of Auto-SIF (500-800 nm), the photochemical reflectance index (PRI) and NDVI were also calculated to assess the diurnal SIFs and photosynthesis performances among different crops. This study presents a primary analyses of field diurnal canopy/leaf SIFs, PRI, NDVI of different crops , and may provide a better understanding of crop photosynthesis.

Advancing environmental risk assessment for transgenic biofeedstock crops

PubMed Central

Wolt, Jeffrey D

2009-01-01

Transgenic modification of plants is a key enabling technology for developing sustainable biofeedstocks for biofuels production. Regulatory decisions and the wider acceptance and development of transgenic biofeedstock crops are considered from the context of science-based risk assessment. The risk assessment paradigm for transgenic biofeedstock crops is fundamentally no different from that of current generation transgenic crops, except that the focus of the assessment must consider the unique attributes of a given biofeedstock crop and its environmental release. For currently envisioned biofeedstock crops, particular emphasis in risk assessment will be given to characterization of altered metabolic profiles and their implications relative to non-target environmental effects and food safety; weediness and invasiveness when plants are modified for abiotic stress tolerance or are domesticated; and aggregate risk when plants are platforms for multi-product production. Robust risk assessments for transgenic biofeedstock crops are case-specific, initiated through problem formulation, and use tiered approaches for risk characterization. PMID:19883509

Attributing Crop Production in the United States Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ma, Y.; Zhang, Z.; Pan, B.

2017-12-01

Crop production plays key role in supporting life, economy and shaping environment. It is on one hand influenced by natural factors including precipitation, temperature, energy, and on the other hand shaped by the investment of fertilizers, pesticides and human power. Successful attributing of crop production to different factors can help optimize resources and improve productivity. Based on the meteorological records from National Center for Environmental Prediction and state-wise crop production related data provided by the United States Department of Agriculture Economic Research Service, an artificial neural network was constructed to connect crop production with precipitation and temperature anormlies, capital input, labor input, energy input, pesticide consumption and fertilizer consumption. Sensitivity analysis were carried out to attribute their specific influence on crop production for each grid. Results confirmed that the listed factors can generally determine the crop production. Different state response differently to the pertubation of predictands. Their spatial distribution is visulized and discussed.

Comparison of Sub-pixel Classification Approaches for Crop-specific Mapping

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) data has been increasingly used for crop mapping and other agricultural applications. Phenology-based classification approaches using the NDVI (Normalized Difference Vegetation Index) 16-day composite (250 m) data product...

High-Density Livestock Production and Molecularly Characterized MRSA Infections in Pennsylvania

PubMed Central

Casey, Joan A.; Shopsin, Bo; Cosgrove, Sara E.; Nachman, Keeve E.; Curriero, Frank C.; Rose, Hannah R.

2014-01-01

Background: European studies suggest that living near high-density livestock production increases the risk of sequence type (ST) 398 methicillin-resistant Staphylococcus aureus (MRSA) colonization. To our knowledge, no studies have evaluated associations between livestock production and human infection by other strain types. Objectives: We evaluated associations between MRSA molecular subgroups and high-density livestock production. Methods: We conducted a yearlong 2012 prospective study on a stratified random sample of patients with culture-confirmed MRSA infection; we oversampled patients from the Geisinger Health System with exposure to high-density livestock production in Pennsylvania. Isolates were characterized using S. aureus protein A (spa) typing and detection of Panton-Valentine leukocidin (PVL) and scn genes. We compared patients with one of two specific MRSA strains with patients with all other strains of MRSA isolates, using logistic regression that accounted for the sampling design, for two different exposure models: one based on the location of the animals (livestock model) and the other on crop field application of manure (crop field model). Results: Of 196 MRSA isolates, we identified 30 spa types, 47 PVL-negative and 15 scn-negative isolates, and no ST398 MRSA. Compared with quartiles 1–3 combined, the highest quartiles of swine livestock and dairy/veal crop field exposures were positively associated with community-onset-PVL-negative MRSA (CO-PVL-negative MRSA vs. all other MRSA), with adjusted odds ratios of 4.24 (95% CI: 1.60, 11.25) and 4.88 (95% CI: 1.40, 17.00), respectively. The association with CO-PVL-negative MRSA infection increased across quartiles of dairy/veal livestock exposure (trend p = 0.05). Conclusions: Our findings suggest that other MRSA strains, beyond ST398, may be involved in livestock-associated MRSA infection in the United States. Citation: Casey JA, Shopsin B, Cosgrove SE, Nachman KE, Curriero FC, Rose HR, Schwartz BS. 2014. High-density livestock production and molecularly characterized MRSA infections in Pennsylvania. Environ Health Perspect 122:464–470; http://dx.doi.org/10.1289/ehp.1307370 PMID:24509131

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE PAGES

Blanc, Élodie

2017-01-26

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

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

Blanc, Élodie

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Molecular, Genetic and Agronomic Approaches to Utilizing Pulses as Cover Crops and Green Manure into Cropping Systems

PubMed Central

Tani, Eleni; Abraham, Eleni; Chachalis, Demosthenis; Travlos, Ilias

2017-01-01

Cover crops constitute one of the most promising agronomic practices towards a more sustainable agriculture. Their beneficial effects on main crops, soil and environment are many and various, while risks and disadvantages may also appear. Several legumes show a high potential but further research is required in order to suggest the optimal legume cover crops for each case in terms of their productivity and ability to suppress weeds. The additional cost associated with cover crops should also be addressed and in this context the use of grain legumes such as cowpea, faba bean and pea could be of high interest. Some of the aspects of these grain legumes as far as their use as cover crops, their genetic diversity and their breeding using conventional and molecular approaches are discussed in the present review. The specific species seem to have a high potential for use as cover crops, especially if their noticeable genetic diversity is exploited and their breeding focuses on several desirable traits. PMID:28587254

Identifying representative crop rotation patterns and grassland loss in the US Western Corn Belt

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

Sahajpal, Ritvik; Zhang, Xuesong; Izaurralde, Roberto C.

2014-10-01

Crop rotations (the practice of growing crops on the same land in sequential seasons) reside at the core of agronomic management as they can influence key ecosystem services such as crop yields, carbon and nutrient cycling, soil erosion, water quality, pest and disease control. Despite the availability of the Cropland Data Layer (CDL) which provides remotely sensed data on crop type in the US on an annual basis, crop rotation patterns remain poorly mapped due to the lack of tools that allow for consistent and efficient analysis of multi-year CDLs. This study presents the Representative Crop Rotations Using Edit Distancemore » (RECRUIT) algorithm, implemented as a Python software package, to select representative crop rotations by combining and analyzing multi-year CDLs. Using CDLs from 2010 to 2012 for 5 states in the US Midwest, we demonstrate the performance and parameter sensitivity of RECRUIT in selecting representative crop rotations that preserve crop area and capture land-use changes. Selecting only 82 representative crop rotations accounted for over 90% of the spatio-temporal variability of the more than 13,000 rotations obtained from combining the multi-year CDLs. Furthermore, the accuracy of the crop rotation product compared favorably with total state-wide planted crop area available from agricultural census data. The RECRUIT derived crop rotation product was used to detect land-use conversion from grassland to crop cultivation in a wetland dominated part of the US Midwest. Monoculture corn and monoculture soybean cropping were found to comprise the dominant land-use on the newly cultivated lands.« less

Influence of crop residues on trifluralin mineralization in a silty clay loam soil.

PubMed

Farenhorst, Annemieke

2007-01-01

Trifluralin is typically applied onto crop residues (trash, stubble) at the soil surface, or onto the bare soil surface after the incorporation of crop residues into the soil. The objective of this study was to quantify the effect of the type and amount of crop residues in soil on trifluralin mineralization in a Wellwood silty clay loam soil. Leaves and stubble of Potato (Solanum tuberosum) (P); Canola (Brassica napus) (C), Wheat (Triticum aestivum) (W), Oats (Avena sativa), (O), and Alfalfa (Medicago sativa) (A) were added to soil microcosms at rates of 2%, 4%, 8% and 16% of the total soil weight (25 g). The type and amount of crop residues in soil had little influence on the trifluralin first-order mineralization rate constant, which ranged from 3.57E-03 day(-1) in soil with 16% A to 2.89E-02 day(-1) in soil with 8% W. The cumulative trifluralin mineralization at 113 days ranged from 1.15% in soil with 16% P to 3.21% in soil with 4% C, again demonstrating that the observed differences across the treatments are not of agronomic or environmental importance.

The Imperial Valley of California is critical to wintering Mountain Plovers

USGS Publications Warehouse

Wunder, Michael B.; Knopf, F.L.

2003-01-01

We surveyed Mountain Plovers (Charadrius montanus) wintering in the Imperial Valley of California in January 2001, and also recorded the types of crop fields used by plovers in this agricultural landscape. We tallied 4037 plovers in 36 flocks ranging in size from 4 to 596 birds. Plovers were more common on alfalfa and Bermudagrass fields than other field types. Further, most birds were on alfalfa fields that were currently being (or had recently been) grazed, primarily by domestic sheep. Plovers used Bermudagrass fields only after harvest and subsequent burning. Examination of Christmas Bird Count data from 1950–2000 indicated that the Mountain Plover has abandoned its historical wintering areas on the coastal plains of California. Numbers in the Central Valley seem to have undergone recent declines also. We believe that the cultivated landscape of the Imperial Valley provides wintering habitats for about half of the global population of Mountain Plovers. We attribute the current importance of the Imperial Valley for Mountain Plovers to loss of native coastal and Central Valley habitats rather than to a behavioral switching of wintering areas through time. Future changes in specific cropping or management practices in the Imperial Valley will have a major impact on the conservation status of this species.

Meteorological and associated data collected over agricultural fields in Pinal County, Arizona, 1989 and 1990

USGS Publications Warehouse

Owen-Joyce, Sandra J.; Brown, Paul W.

1995-01-01

Data were collected at temporary meteorological stations installed in agricultural fields in Pinal County, Arizona, to evaluate the spatial and temporal variability of point data and to examine how station location affects ground-based meteorological data and the resulting values of evapotranspiration calculated using remotely sensed multispectral data from satellites. Time-specific data were collected to correspond with satellite overpasses from April to October 1989, and June 27-28, 1990. Meteorological data consisting of air temperature, relative humidity, wind speed, solar radiation, and net radiation were collected at each station during all periods of the project. Supplementary measurements of soil temperature, soil heat flux density, and surface or canopy temperature were obtained at some locations during certain periods of the project. Additional data include information on data-collection periods, station positions, instrumentation, sensor heights, and field dimensions. Other data, which correspond to the extensive field measurements made in con- junction with satellite overpasses in 1989 and 1990, include crop type, canopy cover, canopy height, irrigation, cultivation, and orientation of rows. Field boundaries and crop types were mapped in a 2- to 3-square-kilometer area surrounding each meteorological station. Field data are presented in tabular and graphic form. Meteorological and supplementary data are available, upon request, in digital form.

Rigid polyurethane foam – kenaf core composites for structural applications

USDA-ARS?s Scientific Manuscript database

Kenaf (Hibiscus cannabinus L.) is a fast growing summer annual crop with numerous commercial applications (fibers, biofuels, bioremediation, paper pulp, building materials, cover crops, and livestock forages). The stalks of the kenaf plants contain two distinct fiber types, bast and core fibers. The...

Australia ground data collection 1981-82 crop year, volume 1

NASA Technical Reports Server (NTRS)

Quinones, C. R.

1982-01-01

Under AgRISTARS management, ground data were collected at 20 agricultural sites within Australia during the crop year 1981-82. The data collection activity is summarized. Specifically, the following information is provided: discussion of data procedures, methods, and products; crop production results; photographs of the Australia agriculture scene, map sheets of segments, LANDSAT full frames, and aerial photographs of data collection areas; and summarizations of district agronomist reports.

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

PubMed Central

de Castro, Ana-Isabel; Jurado-Expósito, Montserrat; Gómez-Casero, María-Teresa; López-Granados, Francisca

2012-01-01

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops. PMID:22629171

Applying neural networks to hyperspectral and multispectral field data for discrimination of cruciferous weeds in winter crops.

PubMed

de Castro, Ana-Isabel; Jurado-Expósito, Montserrat; Gómez-Casero, María-Teresa; López-Granados, Francisca

2012-01-01

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops.

Accounting for soil biotic effects on soil health and crop productivity in the design of crop rotations.

PubMed

Dias, Teresa; Dukes, Angela; Antunes, Pedro M

2015-02-01

There is an urgent need for novel agronomic improvements capable of boosting crop yields while alleviating environmental impacts. One such approach is the use of optimized crop rotations. However, a set of measurements that can serve as guiding principles for the design of crop rotations is lacking. Crop rotations take advantage of niche complementarity, enabling the optimization of nutrient use and the reduction of pests and specialist pathogen loads. However, despite the recognized importance of plant-soil microbial interactions and feedbacks for crop yield and soil health, this is ignored in the selection and management of crops for rotation systems. We review the literature and propose criteria for the design of crop rotations focusing on the roles of soil biota and feedback on crop productivity and soil health. We consider that identifying specific key organisms or consortia capable of influencing plant productivity is more important as a predictor of soil health and crop productivity than assessing the overall soil microbial diversity per se. As such, we propose that setting up soil feedback studies and applying genetic sequencing tools towards the development of soil biotic community databases has a strong potential to enable the establishment of improved soil health indicators for optimized crop rotations. © 2014 Society of Chemical Industry.

Use of Landsat imagery to estimate ground-water pumpage for irrigation on the Columbia Plateau in eastern Washington, 1985

USGS Publications Warehouse

Van Metre, P.C.; Seevers, Paul

1991-01-01

A method for estimating ground-water pumpage for irrigation was developed for the Columbia Plateau in eastern Washington. The method combines water-application rates estimated from pumpage data with acreage of irrigated crops that was mapped by using Landsat imagery. The study area consisted of Grant, Lincoln, Adams, and Franklin Counties, an area of approximately 8,900 square miles, and accounts for approximately three-fourths of the ground-water pumpage in the Columbia Plateau in eastern Washington. Data from two passes of Landsat's multispectral scanner were analyzed by using a spectral band ratioing procedure to map irrigated crops for the study area. Data from one pass of Landsat's thematic mapper, covering approximately two-thirds of the study area, also were analyzed for determining irrigated crops in the area resulting in a 6-percent improvement in accuracy over the multispectral scanner analysis. A total of 576 annual water-application rates associated with particular crops, for the 1982 through 1985 seasons, were calculated. A regression equation was developed for estimating annual water-application rates as a function of crop type, annual precipitation, irrigation system type, and available water capacity of the soil. Crops were grouped into three water-use categories: (1) small grains, primarily wheat and barley; (2) high water-use crops consisting of corn, alfalfa, and potatoes; and (3) miscellaneous vegetable and row crops. Annual water-application rates, expressed as a depth of water, then were multiplied by irrigated area determined by Landsat to estimate a volume of water pumped for irrigation for 1985-620,000 acre-feet. An assessment of accuracy for estimating pumpage for 28 of the sites showed that total predicted pumpage was within 4 percent of the total observed pumpage.

Pesticides use by smallholder farmers in vegetable production in Northern Tanzania.

PubMed Central

Ngowi, A.V.F.; Mbise, T.J.; Ijani, A.S.M.; London, L.; Ajayi, O. C.

2007-01-01

Small-scale farmers in Northern Tanzania grow vegetables that include tomatoes, cabbages and onions and use many types of pesticides to control pests and diseases that attack these crops. Based on the use of questionnaires and interviews that were conducted in Arumeru, Monduli, Karatu, and Moshi rural districts, this study investigates farmers’ practices on vegetable pest management using pesticides and related cost and health effects. The types of pesticides used by the farmers in the study areas were insecticides (59%), fungicides (29%) and herbicides (10%) with the remaining 2% being rodenticides. About a third of the farmers applied pesticides in mixtures. Up to 90% had a maximum of 3 pesticides in a mixture. In all cases there were no specific instructions either from the labels or extension workers regarding these tank mixtures. Fifty three percent of the farmers reported that the trend of pesticide use was increasing, while 33% was constant and 14% was decreasing. More than 50 percent of the respondents applied pesticides up to 5 times or more per cropping season depending on the crop. Insecticides and fungicides were routinely applied by 77% and 7%, respectively by these farmers. Sixty eight percent of farmers reported having felt sick after routine application of pesticides. Pesticide-related health symptoms that were associated with pesticides use included skin problems and neurological system disturbances (dizziness, headache). Sixty one percent of farmers reported spending no money on health due to pesticides. These results can be used to develop a tool to quantify the cost of pesticide use in pest management by small-scale vegetable farmers in Northern Tanzania and contribute to the reformation of pesticide policy for safe and effective use of pesticides. PMID:18528532

Dynamics of Weeds in the Soil Seed Bank: A Hidden Markov Model to Estimate Life History Traits from Standing Plant Time Series.

PubMed

Borgy, Benjamin; Reboud, Xavier; Peyrard, Nathalie; Sabbadin, Régis; Gaba, Sabrina

2015-01-01

Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies.

Dynamics of Weeds in the Soil Seed Bank: A Hidden Markov Model to Estimate Life History Traits from Standing Plant Time Series

PubMed Central

Borgy, Benjamin; Reboud, Xavier; Peyrard, Nathalie; Sabbadin, Régis; Gaba, Sabrina

2015-01-01

Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies. PMID:26427023

Estimating irrigation water use in the humid eastern United States

USGS Publications Warehouse

Levin, Sara B.; Zarriello, Phillip J.

2013-01-01

Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas. The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop. The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use. Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to develop the models as well as two independent validation datasets from Georgia and Virginia that were not used in model development. Irrigation water-use estimates from the logistic regression method more closely matched mean reported irrigation rates than estimates from the crop-water-demand model when compared to the irrigation data used to develop the equations. The root mean squared errors (RMSEs) for the logistic regression estimates of mean annual irrigation ranged from 0.3 to 2.0 inches (in.) for the five crop types; RMSEs for the crop-water-demand models ranged from 1.4 to 3.9 in. However, when the models were applied and compared to the independent validation datasets from southwest Georgia from 2010, and from Virginia from 1999 to 2007, the crop-water-demand model estimates were as good as or better at predicting the mean irrigation volume than the logistic regression models for most crop types. RMSEs for logistic regression estimates of mean annual irrigation ranged from 1.0 to 7.0 in. for validation data from Georgia and from 1.8 to 4.9 in. for validation data from Virginia; RMSEs for crop-water-demand model estimates ranged from 2.1 to 5.8 in. for Georgia data and from 2.0 to 3.9 in. for Virginia data. In general, regression-based models performed better in areas that had quality daily or weekly irrigation data from which the regression equations were developed; however, the regression models were less reliable than the crop-water-demand models when applied outside the area for which they were developed. In most eastern coastal states that do not have quality irrigation data, the crop-water-demand model can be used more reliably. The development of predictive models of irrigation water use in this study was hindered by a lack of quality irrigation data. Many mid-Atlantic and New England states do not require irrigation water use to be reported. A survey of irrigation data from 14 eastern coastal states from Maine to Georgia indicated that, with the exception of the data in Georgia, irrigation data in the states that do require reporting commonly did not contain requisite ancillary information such as irrigated area or crop type, lacked precision, or were at an aggregated temporal scale making them unsuitable for use in the development of predictive models. Confidence in the reliability of either modeling method is affected by uncertainty in the reported data from which the models were developed or validated. Only through additional collection of quality data and further study can the accuracy and uncertainty of irrigation water-use estimates be improved in the humid eastern United States.

Colonization dynamic of various crop residues by Fusarium graminearum monitored through real-time PCR measurements.

PubMed

Leplat, J; Heraud, C; Gautheron, E; Mangin, P; Falchetto, L; Steinberg, C

2016-11-01

To evaluate the effect of the type of crop residues on the colonization dynamic of Fusarium graminearum in soil. The ability of F. graminearum to survive in the presence of various crop residues was assessed on Petri dishes and in microcosms. These microcosms comprised soil that had or had not been previously disinfested with or without amendment with various crop residues. The colonization dynamic of F. graminearum was monitored through real-time PCR. Fusarium graminearum development was higher in disinfested soil than in non-disinfested one. The fungal growth was enhanced to various extents according to the type of crop residues, except for mustard residues which inhibited it. The biochemical and physical properties of the residues were likely to account for the differences in the survival of F. graminearum. Fusarium graminearum is a poor competitor in soil but it can use maize, wheat, and rape residues to ensure its survival. Conversely alfalfa, which is assimilated by micro-organisms very easily, avoids long-lasting survival of the fungus. And finally, mustard producing glucosinolates could be used as an intermediate crop to reduce the inoculum amount. This study is contributing to the knowledge about F. graminearum saprotophic abilities and proposes interesting paths to limit its survival in soil. © 2016 The Society for Applied Microbiology.

Fecundity of transgenic wild-crop hybrids of Cucurbita pepo (Cucurbitaceae): implications for crop-to-wild gene flow.

PubMed

Spencer, L J; Snow, A A

2001-06-01

Hybridization between crops and their weedy or wild relatives is an area of concern because the widespread use of genetically engineered crops may allow novel, beneficial transgenes to enter nearby populations. We compared fitness components of wild Cucurbita pepo from Arkansas, USA, with wild-crop hybrids derived from yellow squash (a cultivar of C. pepo with transgenic resistance to two viruses). Wild and hybrid progeny were grown in agricultural fields in Arkansas (1996-98) and Ohio (1996) in six similar experiments. Cross types (wild and hybrid) did not differ significantly in seedling survival, which exceeded 85% in all cases. In Ohio, where more detailed observations were made, hybrid plants produced 41% as many male flowers, 21% as many female flowers, and 28% as many seeds as wild plants. At all sites, flowering periods of the two cross types overlapped extensively. Putative virus symptoms were more common in wild plants than in hybrids. Lifetime fecundity varied considerably among sites and years. The average fecundity of hybrids ranged from 453 to 4497 seeds per plant and represented 15% - 53% of the numbers of seeds produced by wild plants in the same experiments. These results suggest that the F1 generation does not represent a strong barrier to the introgression of neutral or beneficial crop genes into free-living populations of C. pepo.

Simulating the fate of water in field soil crop environment

NASA Astrophysics Data System (ADS)

Cameira, M. R.; Fernando, R. M.; Ahuja, L.; Pereira, L.

2005-12-01

This paper presents an evaluation of the Root Zone Water Quality Model(RZWQM) for assessing the fate of water in the soil-crop environment at the field scale under the particular conditions of a Mediterranean region. The RZWQM model is a one-dimensional dual porosity model that allows flow in macropores. It integrates the physical, biological and chemical processes occurring in the root zone, allowing the simulation of a wide spectrum of agricultural management practices. This study involved the evaluation of the soil, hydrologic and crop development sub-models within the RZWQM for two distinct agricultural systems, one consisting of a grain corn planted in a silty loam soil, irrigated by level basins and the other a forage corn planted in a sandy soil, irrigated by sprinklers. Evaluation was performed at two distinct levels. At the first level the model capability to fit the measured data was analyzed (calibration). At the second level the model's capability to extrapolate and predict the system behavior for conditions different than those used when fitting the model was assessed (validation). In a subsequent paper the same type of evaluation is presented for the nitrogen transformation and transport model. At the first level a change in the crop evapotranspiration (ETc) formulation was introduced, based upon the definition of the effective leaf area, resulting in a 51% decrease in the root mean square error of the ETc simulations. As a result the simulation of the root water uptake was greatly improved. A new bottom boundary condition was implemented to account for the presence of a shallow water table. This improved the simulation of the water table depths and consequently the soil water evolution within the root zone. The soil hydraulic parameters and the crop variety specific parameters were calibrated in order to minimize the simulation errors of soil water and crop development. At the second level crop yield was predicted with an error of 1.1 and 2.8% for grain and forage corn, respectively. Soil water was predicted with an efficiency ranging from 50 to 95% for the silty loam soil and between 56 and 72% for the sandy soil. The purposed calibration procedure allowed the model to predict crop development, yield and the water balance terms, with accuracy that is acceptable in practical applications for complex and spatially variable field conditions. An iterative method was required to account for the strong interaction between the different model components, based upon detailed experimental data on soils and crops.

Climate change effects on agriculture: Economic responses to biophysical shocks

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

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

Combining Fungicides and Prospective NPR1-Based "Just-in-Time" Immunomodulating Chemistries for Crop Protection.

PubMed

Kuai, Xiahezi; Barraco, Charles; Després, Charles

2017-01-01

Each year, crop yield is lost to weeds competing for resources, insect herbivory and diseases caused by pathogens. To thwart these insults and preserve yield security and a high quality of traits, conventional agriculture makes use of improved cultivars combined with fertilizer and agrochemical applications. However, given that regulatory bodies and consumers are demanding environmentally safer agrochemicals, while at the same time resistance to agrochemicals is mounting, it is crucial to adopt a "holistic" approach to agriculture by not excluding any number of management tools at our disposal. One such tool includes chemicals that stimulate plant immunity. The development of this particular type of alternative crop protection strategy has been of great interest to us. We have approached this paradigm by studying plant immunity, specifically systemic acquired resistance (SAR). The deployment of SAR immunity requires the production by the crop plant of an endogenous small molecule metabolite called salicylic acid (SA). Furthermore, immunity can only be deployed if SA can bind to its receptor and activate the genes responsible for the SAR program. The key receptor for SAR is a transcription coactivator called NPR1. Since discovering this NPR1-SA receptor-ligand pair, we have embarked on a journey to develop novel chemistries capable of deploying SAR in the field. The journey begins with the development of a scalable assay to identify these novel chemistries. One such assay, presented here, is based on differential scanning fluorimetry technology and demonstrates that NPR1 is destabilized by binding to SA.

Combining Fungicides and Prospective NPR1-Based “Just-in-Time” Immunomodulating Chemistries for Crop Protection

PubMed Central

Kuai, Xiahezi; Barraco, Charles; Després, Charles

2017-01-01

Each year, crop yield is lost to weeds competing for resources, insect herbivory and diseases caused by pathogens. To thwart these insults and preserve yield security and a high quality of traits, conventional agriculture makes use of improved cultivars combined with fertilizer and agrochemical applications. However, given that regulatory bodies and consumers are demanding environmentally safer agrochemicals, while at the same time resistance to agrochemicals is mounting, it is crucial to adopt a “holistic” approach to agriculture by not excluding any number of management tools at our disposal. One such tool includes chemicals that stimulate plant immunity. The development of this particular type of alternative crop protection strategy has been of great interest to us. We have approached this paradigm by studying plant immunity, specifically systemic acquired resistance (SAR). The deployment of SAR immunity requires the production by the crop plant of an endogenous small molecule metabolite called salicylic acid (SA). Furthermore, immunity can only be deployed if SA can bind to its receptor and activate the genes responsible for the SAR program. The key receptor for SAR is a transcription coactivator called NPR1. Since discovering this NPR1-SA receptor–ligand pair, we have embarked on a journey to develop novel chemistries capable of deploying SAR in the field. The journey begins with the development of a scalable assay to identify these novel chemistries. One such assay, presented here, is based on differential scanning fluorimetry technology and demonstrates that NPR1 is destabilized by binding to SA. PMID:29046686

Transgenic Studies on the Involvement of Cytokinin and Gibberellin in Male Development

PubMed Central

Huang, Shihshieh; Cerny, R. Eric; Qi, Youlin; Bhat, Deepti; Aydt, Carrie M.; Hanson, Doris D.; Malloy, Kathleen P.; Ness, Linda A.

2003-01-01

Numerous plant hormones interact during plant growth and development. Elucidating the role of these various hormones on particular tissue types or developmental stages has been difficult with exogenous applications or constitutive expression studies. Therefore, we used tissue-specific promoters expressing CKX1 and gai, genes involved in oxidative cytokinin degradation and gibberellin (GA) signal transduction, respectively, to study the roles of cytokinin and GA in male organ development. Accumulation of CKX1 in reproductive tissues of transgenic maize (Zea mays) resulted in male-sterile plants. The male development of these plants was restored by applications of kinetin and thidiazuron. Similarly, expression of gai specifically in anthers and pollen of tobacco (Nicotiana tabacum) and Arabidopsis resulted in the abortion of these respective tissues. The gai-induced male-sterile phenotype exhibited by the transgenic plants was reversible by exogenous applications of kinetin. Our results provide molecular evidence of the involvement of cytokinin and GA in male development and support the hypothesis that the male development is controlled in concert by multiple hormones. These studies also suggest a potential method for generating maintainable male sterility in plants by using existing agrochemicals that would reduce the expense of seed production for existing hybrid crops and provide a method to produce hybrid varieties of traditionally non-hybrid crops. PMID:12644677

A tale of two toxicities: malformed selenoproteins and oxidative stress both contribute to selenium stress in plants

PubMed Central

Van Hoewyk, Doug

2013-01-01

Background Despite selenium's toxicity in plants at higher levels, crops supply most of the essential dietary selenium in humans. In plants, inorganic selenium can be assimilated into selenocysteine, which can replace cysteine in proteins. Selenium toxicity in plants has been attributed to the formation of non-specific selenoproteins. However, this paradigm can be challenged now that there is increasingly abundant evidence suggesting that selenium-induced oxidative stress also contributes to toxicity in plants. Scope This Botanical Briefing summarizes the evidence indicating that selenium toxicity in plants is attributable to both the accumulation of non-specific selenoproteins and selenium-induced oxidative stress. Evidence is also presented to substantiate the claim that inadvertent selenocysteine replacement probably impairs or misfolds proteins, which supports the malformed selenoprotein hypothesis. The possible physiological ramifications of selenoproteins and selenium-induced oxidative stress are discussed. Conclusions Malformed selenoproteins and oxidative stress are two distinct types of stress that drive selenium toxicity in plants and could impact cellular processes in plants that have yet to be thoroughly explored. Although challenging, deciphering whether the extent of selenium toxicity in plants is imparted by selenoproteins or oxidative stress could be helpful in the development of crops with fortified levels of selenium. PMID:23904445

Different cucumber CsYUC genes regulate response to abiotic stresses and flower development.

PubMed

Yan, Shuangshuang; Che, Gen; Ding, Lian; Chen, Zijing; Liu, Xiaofeng; Wang, Hongyin; Zhao, Wensheng; Ning, Kang; Zhao, Jianyu; Tesfamichael, Kiflom; Wang, Qian; Zhang, Xiaolan

2016-02-09

The phytohormone auxin is essential for plant growth and development, and YUCCA (YUC) proteins catalyze a rate-limiting step for endogenous auxin biosynthesis. Despite YUC family genes have been isolated from several species, systematic expression analyses of YUCs in response to abiotic stress are lacking, and little is known about the function of YUC homologs in agricultural crops. Cucumber (Cucumis sativus L.) is a world cultivated vegetable crop with great economical and nutritional value. In this study, we isolated 10 YUC family genes (CsYUCs) from cucumber and explored their expression pattern under four types of stress treatments. Our data showed that CsYUC8 and CsYUC9 were specifically upregulated to elevate the auxin level under high temperature. CsYUC10b was dramatically increased but CsYUC4 was repressed in response to low temperature. CsYUC10a and CsYUC11 act against the upregulation of CsYUC10b under salinity stress, suggesting that distinct YUC members participate in different stress response, and may even antagonize each other to maintain the proper auxin levels in cucumber. Further, CsYUC11 was specifically expressed in the male flower in cucumber, and enhanced tolerance to salinity stress and regulated pedicel and stamen development through auxin biosynthesis in Arabidopsis.

Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation

NASA Astrophysics Data System (ADS)

Siebert, Stefan; Döll, Petra

2010-04-01

SummaryCrop production requires large amounts of green and blue water. We developed the new global crop water model GCWM to compute consumptive water use (evapotranspiration) and virtual water content (evapotranspiration per harvested biomass) of crops at a spatial resolution of 5' by 5', distinguishing 26 crop classes, and blue versus green water. GCWM is based on the global land use data set MIRCA2000 that provides monthly growing areas for 26 crop classes under rainfed and irrigated conditions for the period 1998-2002 and represents multi-cropping. By computing daily soil water balances, GCWM determines evapotranspiration of blue and green water for each crop and grid cell. Cell-specific crop production under both rainfed and irrigated conditions is computed by downscaling average crop yields reported for 402 national and sub-national statistical units, relating rainfed and irrigated crop yields reported in census statistics to simulated ratios of actual to potential crop evapotranspiration for rainfed crops. By restricting water use of irrigated crops to green water only, the potential production loss without any irrigation was computed. For the period 1998-2002, the global value of total crop water use was 6685 km 3 yr -1, of which blue water use was 1180 km 3 yr -1, green water use of irrigated crops was 919 km 3 yr -1 and green water use of rainfed crops was 4586 km 3 yr -1. Total crop water use was largest for rice (941 km 3 yr -1), wheat (858 km 3 yr -1) and maize (722 km 3 yr -1). The largest amounts of blue water were used for rice (307 km 3 yr -1) and wheat (208 km 3 yr -1). Blue water use as percentage of total crop water use was highest for date palms (85%), cotton (39%), citrus fruits (33%), rice (33%) and sugar beets (32%), while for cassava, oil palm and cocoa, almost no blue water was used. Average crop yield of irrigated cereals was 442 Mg km -2 while average yield of rainfed cereals was only 266 Mg km -2. Average virtual water content of cereal crops was 1109 m 3 Mg -1 of green water and 291 m 3 Mg -1 of blue water, while average crop water productivity of cereal crops was 714 g m -3. If currently irrigated crops were not irrigated, global production of dates, rice, cotton, citrus and sugar cane would decrease by 60%, 39%, 38%, 32% and 31%, respectively. Forty-three per cent of cereal production was on irrigated land, and without irrigation, cereal production on irrigated land would decrease by 47%, corresponding to a 20% loss of total cereal production. The largest cereal production losses would occur in Northern Africa (66%) and Southern Asia (45%) while losses would be very low for Northern Europe (0.001%), Western Europe (1.2%), Eastern Europe (1.5%) and Middle Africa (1.6%). Uncertainties and limitations are discussed in the manuscript, and a comparison of GCWM results to statistics or results of other studies shows good agreement at the regional scale, but larger differences for specific countries.

A Method of High Throughput Monitoring Crop Physiology Using Chlorophyll Fluorescence and Multispectral Imaging.

PubMed

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

2018-01-01

We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

Model-based surface soil moisture (SSM) retrieval algorithm using multi-temporal RISAT-1 C-band SAR data

NASA Astrophysics Data System (ADS)

Pandey, Dharmendra K.; Maity, Saroj; Bhattacharya, Bimal; Misra, Arundhati

2016-05-01

Accurate measurement of surface soil moisture of bare and vegetation covered soil over agricultural field and monitoring the changes in surface soil moisture is vital for estimation for managing and mitigating risk to agricultural crop, which requires information and knowledge to assess risk potential and implement risk reduction strategies and deliver essential responses. The empirical and semi-empirical model-based soil moisture inversion approach developed in the past are either sensor or region specific, vegetation type specific or have limited validity range, and have limited scope to explain physical scattering processes. Hence, there is need for more robust, physical polarimetric radar backscatter model-based retrieval methods, which are sensor and location independent and have wide range of validity over soil properties. In the present study, Integral Equation Model (IEM) and Vector Radiative Transfer (VRT) model were used to simulate averaged backscatter coefficients in various soil moisture (dry, moist and wet soil), soil roughness (smooth to very rough) and crop conditions (low to high vegetation water contents) over selected regions of Gujarat state of India and the results were compared with multi-temporal Radar Imaging Satellite-1 (RISAT-1) C-band Synthetic Aperture Radar (SAR) data in σ°HH and σ°HV polarizations, in sync with on field measured soil and crop conditions. High correlations were observed between RISAT-1 HH and HV with model simulated σ°HH & σ°HV based on field measured soil with the coefficient of determination R2 varying from 0.84 to 0.77 and RMSE varying from 0.94 dB to 2.1 dB for bare soil. Whereas in case of winter wheat crop, coefficient of determination R2 varying from 0.84 to 0.79 and RMSE varying from 0.87 dB to 1.34 dB, corresponding to with vegetation water content values up to 3.4 kg/m2. Artificial Neural Network (ANN) methods were adopted for model-based soil moisture inversion. The training datasets for the NNs were obtained from theoretical forward-scattering models with controlled parameters, thus allowing the control of wide range of soil and crop parameters with which the network was trained. A preliminary performance analysis showed good results with estimation of soil moisture with RMSE better than 6%.

A small variation in diet influences the Lactobacillus strain composition in the crop of broiler chickens.

PubMed

Hammons, Susan; Oh, Phaik Lyn; Martínez, Inés; Clark, Kenzi; Schlegel, Vicki L; Sitorius, Emily; Scheideler, Sheila E; Walter, Jens

2010-08-01

Feed composition has the potential to influence the activities of bacteria that colonize the digestive tract of broiler chickens with important consequences for animal health, well being, and food safety. In this study, the gut microbiota of two groups of broiler chickens raised in immediate vicinity but fed either a standard corn/soybean meal ration (corn-soy, CS) or a ration high in wheat middlings (high wheat, HW) was characterized. The findings revealed that this small variation in feed composition did not influence the distribution of microbial species present in the microbial community throughout the digestive tract. However, diet variation markedly influenced the Lactobacillus strain composition in the crop. Most striking, the dominant type in birds on the CS diet (Lactobacillus agilis type R5), which comprised 25% of the isolates, was not detected in birds fed the HW diet. The latter birds harbored a different strain of L. agilis (type R1) in a significantly higher ratio than birds on the CS diet. Several other strains were also specific to the particular diet. In conclusion, this study showed that a small variation in the composition of chicken feed that does not result in detectable differences in species composition can still have an impact on which microbial strains become dominant in the digestive tract. This finding has relevance in the application of probiotics and other direct-fed microbials in poultry husbandry. Copyright 2010 Elsevier GmbH. All rights reserved.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums.

PubMed

Shakoor, Nadia; Nair, Ramesh; Crasta, Oswald; Morris, Geoffrey; Feltus, Alex; Kresovich, Stephen

2014-01-23

Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

PubMed Central

2014-01-01

Background Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community. PMID:24456189

Second annual report of the Botany Field Station

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

Cline, J.F.; Porter, J.W.

This report presents data which show that during 1950 the radioactivity of several types of crops, irrigated with water pumped from the Columbia River below the Hanford piles, differed but slightly from that of similar crops grown in a control area. 3 refs., 1 fig., 4 tabs.

Acquisition and management of continuous data streams for crop water management

USDA-ARS?s Scientific Manuscript database

Wireless sensor network systems for decision support in crop water management offer many advantages including larger spatial coverage and multiple types of data input. However, collection and management of multiple and continuous data streams for near real-time post analysis can be problematic. Thi...

Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations.

PubMed

Amon, Thomas; Amon, Barbara; Kryvoruchko, Vitaliy; Machmüller, Andrea; Hopfner-Sixt, Katharina; Bodiroza, Vitomir; Hrbek, Regina; Friedel, Jürgen; Pötsch, Erich; Wagentristl, Helmut; Schreiner, Matthias; Zollitsch, Werner

2007-12-01

Biogas production is of major importance for the sustainable use of agrarian biomass as renewable energy source. Economic biogas production depends on high biogas yields. The project aimed at optimising anaerobic digestion of energy crops. The following aspects were investigated: suitability of different crop species and varieties, optimum time of harvesting, specific methane yield and methane yield per hectare. The experiments covered 7 maize, 2 winter wheat, 2 triticale varieties, 1 winter rye, and 2 sunflower varieties and 6 variants with permanent grassland. In the course of the vegetation period, biomass yield and biomass composition were measured. Anaerobic digestion was carried out in eudiometer batch digesters. The highest methane yields of 7500-10200 m(N)(3)ha(-1) were achieved from maize varieties with FAO numbers (value for the maturity of the maize) of 300 to 600 harvested at "wax ripeness". Methane yields of cereals ranged from 3200 to 4500 m(N)(3)ha(-1). Cereals should be harvested at "grain in the milk stage" to "grain in the dough stage". With sunflowers, methane yields between 2600 and 4550 m(N)(3)ha(-1) were achieved. There were distinct differences between the investigated sunflower varieties. Alpine grassland can yield 2700-3500 m(N)(3)CH(4)ha(-1). The methane energy value model (MEVM) was developed for the different energy crops. It estimates the specific methane yield from the nutrient composition of the energy crops. Energy crops for biogas production need to be grown in sustainable crop rotations. The paper outlines possibilities for optimising methane yield from versatile crop rotations that integrate the production of food, feed, raw materials and energy. These integrated crop rotations are highly efficient and can provide up to 320 million t COE which is 96% of the total energy demand of the road traffic of the EU-25 (the 25 Member States of the European Union).

Inoculation of Soil with Plant Growth Promoting Bacteria Producing 1-Aminocyclopropane-1-Carboxylate Deaminase or Expression of the Corresponding acdS Gene in Transgenic Plants Increases Salinity Tolerance in Camelina sativa

PubMed Central

Heydarian, Zohreh; Yu, Min; Gruber, Margaret; Glick, Bernard R.; Zhou, Rong; Hegedus, Dwayne D.

2016-01-01

Camelina sativa (camelina) is an oilseed crop touted for use on marginal lands; however, it is no more tolerant of soil salinity than traditional crops, such as canola. Plant growth-promoting bacteria (PGPB) that produce 1-aminocyclopropane-1-carboxylate deaminase (ACC deaminase) facilitate plant growth in the presence of abiotic stresses by reducing stress ethylene. Rhizospheric and endophytic PGPB and the corresponding acdS- mutants of the latter were examined for their ability to enhance tolerance to salt in camelina. Stimulation of growth and tolerance to salt was correlated with ACC deaminase production. Inoculation of soil with wild-type PGPB led to increased shoot length in the absence of salt, and increased seed production by approximately 30–50% under moderately saline conditions. The effect of ACC deaminase was further examined in transgenic camelina expressing a bacterial gene encoding ACC deaminase (acdS) under the regulation of the CaMV 35S promoter or the root-specific rolD promoter. Lines expressing acdS, in particular those using the rolD promoter, showed less decline in root length and weight, increased seed production, better seed quality and higher levels of seed oil production under salt stress. This study clearly demonstrates the potential benefit of using either PGPB that produce ACC deaminase or transgenic plants expressing the acdS gene under the control of a root-specific promoter to facilitate plant growth, seed production and seed quality on land that is not normally suitable for the majority of crops due to high salt content. PMID:28018305

Origins of food crops connect countries worldwide

PubMed Central

Achicanoy, Harold A.; Bjorkman, Anne D.; Navarro-Racines, Carlos; Guarino, Luigi; Flores-Palacios, Ximena; Engels, Johannes M. M.; Wiersema, John H.; Dempewolf, Hannes; Sotelo, Steven; Ramírez-Villegas, Julian; Castañeda-Álvarez, Nora P.; Fowler, Cary; Jarvis, Andy; Rieseberg, Loren H.; Struik, Paul C.

2016-01-01

Research into the origins of food plants has led to the recognition that specific geographical regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not been quantified. Here we determine the origins (‘primary regions of diversity’) of the crops comprising the food supplies and agricultural production of countries worldwide. We estimate the degree to which countries use crops from regions of diversity other than their own (‘foreign crops’), and quantify changes in this usage over the past 50 years. Countries are highly interconnected with regard to primary regions of diversity of the crops they cultivate and/or consume. Foreign crops are extensively used in food supplies (68.7% of national food supplies as a global mean are derived from foreign crops) and production systems (69.3% of crops grown are foreign). Foreign crop usage has increased significantly over the past 50 years, including in countries with high indigenous crop diversity. The results provide a novel perspective on the ongoing globalization of food systems worldwide, and bolster evidence for the importance of international collaboration on genetic resource conservation and exchange.

Dynamic drought risk assessment using crop model and remote sensing techniques

NASA Astrophysics Data System (ADS)

Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.

2017-02-01

Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.

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.

A half-century analysis of landscape dynamics in southern Québec, Canada.

PubMed

Jobin, Benoît; Latendresse, Claudie; Baril, Alain; Maisonneuve, Charles; Boutin, Céline; Côté, Dominique

2014-04-01

We studied landscape dynamics for three time periods (<1950, 1965, and 1997) along a gradient of agricultural intensity from highly intensive agriculture to forested areas in southern Québec. Air photos were analyzed to obtain long-term information on land cover (crop and habitat types) and linear habitats (hedgerows and riparian habitats) and landscape metrics were calculated to quantify changes in habitat configuration. Anthropogenic areas increased in all types of landscapes but mostly occurred in the highly disturbed cash crop dominated landscape. Perennial crops (pasture and hayfields) were largely converted into annual crops (corn and soybean) between 1965 and 1997. The coalescence of annual crop fields resulted in a more homogeneous agricultural landscape. Old fields and forest cover was consistently low and forest fragmentation remained stable through time in the intensive agriculture landscapes. However, forest cover increased and forest fragmentation receded in the forest-dominated landscapes following farm abandonment and the transition of old fields into forests. Tree-dominated hedgerows and riparian habitats increased in areas with intensive agriculture. Observed changes in land cover classes are related to proximate factors, such as surficial deposits and topography. Agriculture intensification occurred in areas highly suitable for agriculture whereas farm abandonment was observed in poor-quality agriculture terrains. Large-scale conversion of perennial crops into annual crops along with continued urbanization exerts strong pressures on residual natural habitats and their inhabiting wildlife. The afforestation process occurring in the more forested landscapes along with the addition of tree-dominated hedgerows and riparian habitats in the agriculture-dominated landscapes should improve landscape ecological value.

Comparison of soil microbial respiration and carbon turnover under perennial and annual biofuel crops in two agricultural soils

NASA Astrophysics Data System (ADS)

Szymanski, L. M.; Marin-Spiotta, E.; Sanford, G. R.; Jackson, R. D.; Heckman, K. A.

2015-12-01

Bioenergy crops have the potential to provide a low carbon-intensive alternative to fossil fuels. More than a century of agricultural research has shown that conventional cropping systems can reduce soil organic matter (SOM) reservoirs, which cause long-term soil nutrient loss and C release to the atmosphere. In the face of climate change and other human disruptions to biogeochemical cycles, identifying biofuel crops that can maintain or enhance soil resources is desirable for the sustainable production of bioenergy. The objective of our study was to compare the effects of four biofuel crop treatments on SOM dynamics in two agricultural soils: Mollisols at Arlington Agricultural Research Station in Wisconsin and Alfisols at Kellogg Biological Station in Michigan, USA. We used fresh soils collected in 2013 and archived soils from 2008 to measure the effects of five years of crop management. Using a one-year long laboratory soil incubation coupled with a regression model and radiocarbon measurements, we separated soils into three SOM pools and their corresponding C turnover times. We found that the active pool, or biologically available C, was more sensitive to management and is an earlier indicator of changes to soil C dynamics than bulk soil C measurements. There was no effect of treatment on the active pool size at either site; however, the percent C in the active pool decreased, regardless of crop type, in surface soils with high clay content. At depth, the response of the slow pool differed between annual and perennial cropping systems. The distribution of C among SOM fractions varied between the two soil types, with greater C content associated with the active fraction in the coarser textured-soil and greater C content associated with the slow-cycling fraction in the soils with high clay content. These results suggest that the effects of bioenergy crops on soil resources will vary geographically, with implications for the carbon-cost of biocrop production.

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

Vogel, John P.

The goal of this project was to apply high-throughput, non-destructive phenotyping (phenomics) to collections of natural variants and induced mutants of the model grass Brachypodium distachyon and characterize a small subset of that material in detail. B. distachyon is well suited to this phenomic approach because its small size and rapid generation time allow researchers to grow many plants under carefully controlled conditions. In addition, the simple diploid genetics, high quality genome sequence and existence of numerous experimental tools available for B. distachyon allow us to rapidly identify genes affecting specific phenotypes. Our phenomic analysis revealed great diversity in biofuel-relevantmore » traits like growth rate, biomass and photosynthetic rate. This clearly demonstrated the feasibility of applying a phenomic approach to the model grass B. distachyon. We also demonstrated the utility of B. distachyon for studying mature root system, something that is virtually impossible to do with biomass crops. We showed tremendous natural variation in root architecture that can potentially be used to design crops with superior nutrient and water harvesting capability. Finally, we demonstrated the speed with which we can link specific genes to specific phenotypes by studying two mutants in detail. Importantly, in both cases, the specific biological lessons learned were grass-specific and could not have been learned from a dicot model system. Furthermore, one of the genes affects cell wall integrity and thus may be a useful target in the context of biomass crop improvement. Ultimately, all this information can be used to accelerate the creation of improved biomass crops.« less

Structure and location of macronutrients in ancient and alternative crops (abstract)

USDA-ARS?s Scientific Manuscript database

Structure, histochemistry and composition of mature seeds of several ancient or alternative crops were studied by light and electron microscopies to localize specific macronutrients including protein, starch, non-starch carbohydrates and lipid. Botanically, these seeds fall into different classifica...

Interactions of transgenic Bacillus thuringiensis insecticidal crops with spiders (Araneae)

USDA-ARS?s Scientific Manuscript database

Genetically modified crops expressing insecticidal proteins from Bacillus thuringiensis (Bt) have dramatically increased in acreage since their introduction in the mid-1990’s. Although the insecticidal mechanisms of Bt target specific pests, concerns persist regarding direct and indirect effects on...

Monitoring Agricultural Cropping Patterns in the Great Lakes Basin Using MODIS-NDVI Time Series Data

EPA Science Inventory

This research examined changes in agricultural cropping patterns across the Great Lakes Basin (GLB) using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data. Specific research objectives were to characterize the distribut...

Spatio-temporal trends in crop damage inform recent climate-mediated expansion of a large boreal herbivore into an agro-ecosystem.

PubMed

Laforge, Michel P; Michel, Nicole L; Brook, Ryan K

2017-11-09

Large-scale climatic fluctuations have caused species range shifts. Moose (Alces alces) have expanded their range southward into agricultural areas previously not considered moose habitat. We found that moose expansion into agro-ecosystems is mediated by broad-scale climatic factors and access to high-quality forage (i.e., crops). We used crop damage records to quantify moose presence across the Canadian Prairies. We regressed latitude of crop damage against North Atlantic Oscillation (NAO) and crop area to test the hypotheses that NAO-mediated wetland recharge and occurrence of more nutritious crop types would result in more frequent occurrences of crop damage by moose at southerly latitudes. We examined local-scale land use by generating a habitat selection model to test our hypothesis that moose selected for areas of high crop cover in agro-ecosystems. We found that crop damage by moose occurred farther south during dry winters and in years with greater coverage of oilseeds. The results of our analyses support our hypothesis that moose movement into cropland is mediated by high-protein crops, but not by thermoregulatory habitat at the scale examined. We conclude that broad-scale climate combined with changing land-use regimes are causal factors in species' range shifts and are important considerations when studying changing animal distributions.

Spatio-temporal dynamics of Fusarium head blight and Trichothecene toxin types in Canada

USDA-ARS?s Scientific Manuscript database

In many parts of the world Fusarium graminearum is the primary causal agent of Fusarium head blight (FHB), a disease of cereal crops that adversely affects crop yield, food safety, and animal health. We previously demonstrated population structure associated with differences in trichothecene toxin t...

7 CFR 457.107 - Florida citrus fruit crop insurance provisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...; (2) Remained on the tree after damage occurred; (3) Except as provided in (b), was missing, damaged... policies: Florida Citrus Fruit Crop Insurance Provisions 1. Definitions Age class. Trees in the unit are... applicable combination of commodity type, intended use, and age class of trees, within a citrus fruit...

HyspIRI Measurements of Agricultural Systems in California: 2013-2015

NASA Astrophysics Data System (ADS)

Townsend, P. A.; Kruger, E. L.; Singh, A.; Jablonski, A. D.; Kochaver, S.; Serbin, S.

2015-12-01

During 2013-2015, NASA collected high-altitude AVIRIS hyperspectral and MASTER thermal infrared imagery across large swaths of California in support of the HyspIRI planning and prototyping activities. During these campaigns, we made extensive measurements of photosynthetic capacity—Vcmax and Jmax—and their temperature sensitivities across a range of sites, crop types and environmental conditions. Our objectives were to characterize the physiological diversity of agricultural vegetation in California and develop generalizable algorithms to map these physiological parameters across several image acquisitions, regardless of crop type and canopy temperatures. We employed AVIRIS imagery to scale and estimate the vegetation parameters and MASTER surface temperature to provide context, since physiology responds exponentially to leaf temperature. We demonstrate a segmentation approach to disentangling leaf and background soil temperature, and then illustrate our retrievals of Vcmax and Jmax during overflight conditions across a large number of the 2013-2015 HyspIRI acquisitions. Our results show >80% repeatability (R2) across split sample jack-knifing, with RMSEs within 15% of the range of our data. The approach was robust across crop types (e.g., grape, almond, pistachio, avocado, pomegranate, oats, peppers, citrus, date palm, alfalfa, melons, beets) and leaf temperatures. A global imaging spectroscopy system such as HyspIRI will offer unprecedented ability to monitor agricultural crop performance under widely varying surface conditions.

Large and Small-Scale Cropland Classification on the Foothills of Mount Kenya Based on SPOT-5 Take-5 Data Time Series

NASA Astrophysics Data System (ADS)

Eckert, Sandra

2016-08-01

The SPOT-5 Take 5 campaign provided SPOT time series data of an unprecedented spatial and temporal resolution. We analysed 29 scenes acquired between May and September 2015 of a semi-arid region in the foothills of Mount Kenya, with two aims: first, to distinguish rainfed from irrigated cropland and cropland from natural vegetation covers, which show similar reflectance patterns; and second, to identify individual crop types. We tested several input data sets in different combinations: the spectral bands and the normalized difference vegetation index (NDVI) time series, principal components of NDVI time series, and selected NDVI time series statistics. For the classification we used random forests (RF). In the test differentiating rainfed cropland, irrigated cropland, and natural vegetation covers, the best classification accuracies were achieved using spectral bands. For the differentiation of crop types, we analysed the phenology of selected crop types based on NDVI time series. First results are promising.

MorTAL Kombat: the story of defense against TAL effectors through loss-of-susceptibility

PubMed Central

Hutin, Mathilde; Pérez-Quintero, Alvaro L.; Lopez, Camilo; Szurek, Boris

2015-01-01

Many plant-pathogenic xanthomonads rely on Transcription Activator-Like (TAL) effectors to colonize their host. This particular family of type III effectors functions as specific plant transcription factors via a programmable DNA-binding domain. Upon binding to the promoters of plant disease susceptibility genes in a sequence-specific manner, the expression of these host genes is induced. However, plants have evolved specific strategies to counter the action of TAL effectors and confer resistance. One mechanism is to avoid the binding of TAL effectors by mutations of their DNA binding sites, resulting in resistance by loss-of-susceptibility. This article reviews our current knowledge of the susceptibility hubs targeted by Xanthomonas TAL effectors, possible evolutionary scenarios for plants to combat the pathogen with loss-of-function alleles, and how this knowledge can be used overall to develop new pathogen-informed breeding strategies and improve crop resistance. PMID:26236326

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

NASA Astrophysics Data System (ADS)

Osborne, T.; Gornall, J.; Hooker, J.; Williams, K.; Wiltshire, A.; Betts, R.; Wheeler, T.

2014-10-01

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

Crop Surveillance Demonstration Using a Near-Daily MODIS Derived Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Ryan, Robert E.; Blonski, Slawomir; Prados, Don

2005-01-01

Effective response to crop disease outbreaks requires rapid identification and diagnosis of an event. A near-daily vegetation index product, such as a Normalized Difference Vegetation Index (NDVI), at moderate spatial resolution may serve as a good method for monitoring quick-acting diseases. NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flown on the Terra and Aqua satellites has the temporal, spatial, and spectral properties to make it an excellent coarse-resolution data source for rapid, comprehensive surveillance of agricultural areas. A proof-of-concept wide area crop surveillance system using daily MODIS imagery was developed and tested on a set of San Joaquin cotton fields over a growing season. This area was chosen in part because excellent ground truth data were readily available. Preliminary results indicate that, at least in the southwestern part of the United States, near-daily NDVI products can be generated that show the natural variations in the crops as well as specific crop practices. Various filtering methods were evaluated and compared with standard MOD13 NDVI MODIS products. We observed that specific chemical applications that produce defoliation, which would have been missed using the standard 16-day product, were easily detectable with the filtered daily NDVI products.

Food security: increasing yield and improving resource use efficiency.

PubMed

Parry, Martin A J; Hawkesford, Malcolm J

2010-11-01

Food production and security will be a major issue for supplying an increasing world population. The problem will almost certainly be exacerbated by climate change. There is a projected need to double food production by 2050. In recent times, the trend has been for incremental modest yield increases for most crops. There is an urgent need to develop integrated and sustainable approaches that will significantly increase both production per unit land area and the resource use efficiency of crops. This review considers some key processes involved in plant growth and development with some examples of ways in which molecular technology, plant breeding and genetics may increase the yield and resource use efficiency of wheat. The successful application of biotechnology to breeding is essential to provide the major increases in production required. However, each crop and each specific agricultural situation presents specific requirements and targets for optimisation. Some increases in production will come about as new varieties are developed which are able to produce satisfactory crops on marginal land presently not considered appropriate for arable crops. Other new varieties will be developed to increase both yield and resource use efficiency on the best land.

Lettuce germplasm collection in the National Plant Germplasm System

USDA-ARS?s Scientific Manuscript database

The National Plant Germplasm System (NPGS) holds more than half million accessions of crop plants and their related species that are coordinately assigned to four major Regional Plant Introduction Stations and an additional 21 crop-specific repositories. These Stations and repositories acquire, main...

The ten years (2004-2014): Progress in peanut genetics and genomics

USDA-ARS?s Scientific Manuscript database

Plant breeding, genetics, and genomics play a critical role in sustainable agriculture specifically in improving crop productivity, quality, and resistance to pests and diseases. The germplasm collections have been treasures of crop genetic resources. Utilization of the collections of wild peanut sp...

Agro-ecoregionalization of Iowa using multivariate geographical clustering

Treesearch

Carol L. Williams; William W. Hargrove; Matt Leibman; David E. James

2008-01-01

Agro-ecoregionalization is categorization of landscapes for use in crop suitability analysis, strategic agroeconomic development, risk analysis, and other purposes. Past agro-ecoregionalizations have been subjective, expert opinion driven, crop specific, and unsuitable for statistical extrapolation. Use of quantitative analytical methods provides an opportunity for...

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

WEBGIS based CropWatch online agriculture monitoring system

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

Spatially-Explicit Estimates of Greenhouse Gas Emissions from Fire and Land-Use Change in the Brazilian Cerrado

NASA Astrophysics Data System (ADS)

Galford, G. L.; Spera, S. A.; Coe, M. T.; Costa, C., Jr.

2014-12-01

Understanding the multiple types of land-use changes that can occur within an ecosystem provides a comprehensive picture of the human's impact on natural systems. We use the Cerrado (savanna) of Brazil to examine the primary and secondary impacts of land-use change on greenhouse gas emissions. The primary land-use changes include fires for land-clearing, conversions to pasture and row-crop agriculture, and shifting management practices of agricultural lands. Secondary land-use changes include savanna degradation due to fires that escape from intended burn areas. These escape fires typically have a lower combustion completion coefficient than clearing fires, so it is important to distinguish them to correctly estimate the regional greenhouse gas budget. We have created a first-order spatio-temporal model of greenhouse gas emissions that can be easily modified for other savanna regions using globally available data products as inputs. Our data inputs are derived from publically available remote sensing imagery. Initial biomass is estimated by Baccini et al. 2012, which is derived from LiDAR and MODIS imagery. All other input data sets give annual estimates. Clearing of the savanna is documented by LAPIG of Universidade Federal de Goias using MODIS (MOD13Q1), LANDSAT and CBERS images. MODIS burned area products delineate annual fires; in combination with the savanna clearing database we determine primary and escape fires. Pastures and row-crop agriculture are documented by LAPIG and Spera et al. 2014, respectively. The row-crop agriculture dataset enables us to estimate greenhouse gas emissions associated with specific crops (e.g., soy or maize) and management (e.g., fertilizer use). Recent contributions to the literature have provided many in situ measurements from the land-use changes of interest needed to estimate a regional greenhouse gas budget, including combustion coefficients of savanna sub-types, carbon emission soil stocks, nitrogen emissions from fertilizer, and carbon storage in pastures. With this wealth of information, we present a complete greenhouse gas portfolio including a sensitivity analysis for this dynamic region with an eye to applications for other savanna regions.

[Effects of agricultural activities and transgenic crops on agricultural biodiversity].

PubMed

Zhang, Xi-Tao; Luo, Hong-Bing; Li, Jun-Sheng; Huang, Hai; Liu, Yong-Bo

2014-09-01

Agricultural biodiversity is a key part of the ecosystem biodiversity, but it receives little concern. The monoculture, environmental pollution and habitat fragmentation caused by agricultural activities have threatened agricultural biodiversity over the past 50 years. To optimize agricultural management measures for crop production and environmental protection, we reviewed the effects of agricultural activities, including cultivation patterns, plastic mulching, chemical additions and the cultivation of transgenic crops, on agricultural biodiversity. The results showed that chemical pesticides and fertilizers had the most serious influence and the effects of transgenic crops varied with other factors like the specific transgene inserted in crops. The environmental risk of transgenic crops should be assessed widely through case-by-case methods, particularly its potential impacts on agricultural biodiversity. It is important to consider the protection of agricultural biodiversity before taking certain agricultural practices, which could improve agricultural production and simultaneously reduce the environmental impacts.

Environmental risk assessments for transgenic crops producing output trait enzymes

PubMed Central

Tuttle, Ann; Shore, Scott; Stone, Terry

2009-01-01

The environmental risks from cultivating crops producing output trait enzymes can be rigorously assessed by testing conservative risk hypotheses of no harm to endpoints such as the abundance of wildlife, crop yield and the rate of degradation of crop residues in soil. These hypotheses can be tested with data from many sources, including evaluations of the agronomic performance and nutritional quality of the crop made during product development, and information from the scientific literature on the mode-of-action, taxonomic distribution and environmental fate of the enzyme. Few, if any, specific ecotoxicology or environmental fate studies are needed. The effective use of existing data means that regulatory decision-making, to which an environmental risk assessment provides essential information, is not unnecessarily complicated by evaluation of large amounts of new data that provide negligible improvement in the characterization of risk, and that may delay environmental benefits offered by transgenic crops containing output trait enzymes. PMID:19924556

Coupling AVHRR imagery with biogeochemical models of methane emission from rice crops

NASA Astrophysics Data System (ADS)

Paliouras, Eleni Joyce

2000-10-01

Rice is a staple food source for much of the world and most of it is grown in paddies which remain flooded for a large part of the growing season. This anaerobic environment is ideal for the activities of methanogenic bacteria, that are responsible for the production of methane gas, some of which is released into the atmosphere. In order to better understand the role that rice cropping plays in the levels of atmospheric methane, several models have been developed to predict the methane flux from the paddies. These models generally utilize some type of nominal plant growth curve based on one or two pieces of ground truth data. Ideally, satellite data could be used instead to provide these models with an estimate of biomass change over the growing season, eliminating the need for related ground truth. A technique proposed to accomplish this is presented here, and results that demonstrate its success when applied to rice cropping areas of Texas are discussed. Also presented is a method for utilizing satellite data to map rice cropping areas that could eventually aid in a scheme for populating a GIS-type database with information on exact rice cropping areas. Such a database could then be directly tied to the methane emission models to obtain flux estimates for extensive regional areas.

The Potential of Small Satellites for Crop Monitoring in Emerging Economies

NASA Astrophysics Data System (ADS)

Bydekerke, L.; Meuleman, K.

2008-08-01

The use of low resolution data for monitoring of the overall vegetation condition and crops is nowadays wide spread in emerging economies. Various initiatives, global and local, have promoted the use of this type of imagery for assessing the progress of the growing season since the eighties. The normalized difference vegetation Index (NDVI), from various sensors with 250m to 8 km resolution, are used to identify potential anomalies in vegetation development which, in combination with other data, are used to identify emerging crisis situations in crop development and production before harvest time. Satellite data is analyzed by specialized centers and crop / vegetation assessments are summarized into bulletins, which are then used for communication with non-remote sensing specialists at the policy level. Satellite data is currently provided by large expensive space infrastructures and centrally distributed to the users. In this paper the current flow of information from satellite to information for agriculture is analyzed and the potential contribution of low cost small satellite in addressing the needs of the users is discussed. Two scenario's are presented: i. a centralized system whereby a few institutes have access to data generated by small satellites which process and analyze the data for use by analysts; ii. a decentralized system whereby a variety of users have direct access to data generated by small satellites who are capable of extracting, processing and analyzing information relevant for crop monitoring. The work shows that with affordable space infrastructure, as small satellites, the second scenario may become possible, but the complexity and the cost of the ground segment service remain limiting factors. Expertise and knowledge for processing, analysis and maintenance of IT/infrastructure is currently not enough, specifically in Institutions whose mandate is dealing with crop monitoring, such as the Ministries of Agriculture. However, in the short term, a limited number of specialized centers, can play a key role in gradually facilitating the integration of remote sensing information into the daily workflow, and gradually optimizing costs and efforts. The potential use of future small satellite missions such as e.g. SPOT-Vegetation continuity mission (Proba-V) is also addressed.

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

Nisbet, A.F.; Woodman, R.F.M.

A database of soil-to-plant transfer factors for radiocesium and radiostrontium has been compiled for arable crops from published and unpublished sources. The database is more extensive than previous compilations of data published by the International Union of Radioecologists, containing new information for Scandinavia and Greece in particular. It also contains ancillary data on important soil characteristics. The database is sub-divided into 28 soil-crop combinations, covering four soil types and seven crop groups. Statistical analyses showed that transfer factors for radiocesium could not generally be predicted as a function of climatic region, type of experiment, age of contamination, or silt characteristics.more » However, significant relationships accounting for more than 30% of the variability in transfer factor were identified between transfer factors for radiostrontium and soil pH/organic matter status for a few soil-crop combinations. Best estimate transfer factors for radiocesium and radiostrontium were calculated for 28 soil-crop combinations, based on their geometric means: only the edible parts were considered. To predict the likely value of future individual transfer factors, 95% confidence intervals were also derived. A comparison of best estimate transfer factors derived in this study with recommended values published by the International Union of Radioecologists in 1989 and 1992 was made for comparable soil-crop groupings. While there were no significant differences between the best estimate values derived in this study and the 1992 data, radiological assessments that still use 1989 data may be unnecessarily cautious.« less

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

NASA Astrophysics Data System (ADS)

Berardy, Andrew; Chester, Mikhail V.

2017-03-01

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

New methodology for estimating biofuel consumption for cooking: Atmospheric emissions of black carbon and sulfur dioxide from India

NASA Astrophysics Data System (ADS)

Habib, Gazala; Venkataraman, Chandra; Shrivastava, Manish; Banerjee, Rangan; Stehr, J. W.; Dickerson, Russell R.

2004-09-01

The dominance of biofuel combustion emissions in the Indian region, and the inherently large uncertainty in biofuel use estimates based on cooking energy surveys, prompted the current work, which develops a new methodology for estimating biofuel consumption for cooking. This is based on food consumption statistics, and the specific energy for food cooking. Estimated biofuel consumption in India was 379 (247-584) Tg yr-1. New information on the user population of different biofuels was compiled at a state level, to derive the biofuel mix, which varied regionally and was 74:16:10%, respectively, of fuelwood, dung cake and crop waste, at a national level. Importantly, the uncertainty in biofuel use from quantitative error assessment using the new methodology is around 50%, giving a narrower bound than in previous works. From this new activity data and currently used black carbon emission factors, the black carbon (BC) emissions from biofuel combustion were estimated as 220 (65-760) Gg yr-1. The largest BC emissions were from fuelwood (75%), with lower contributions from dung cake (16%) and crop waste (9%). The uncertainty of 245% in the BC emissions estimate is now governed by the large spread in BC emission factors from biofuel combustion (122%), implying the need for reducing this uncertainty through measurements. Emission factors of SO2 from combustion of biofuels widely used in India were measured, and ranged 0.03-0.08 g kg-1 from combustion of two wood species, 0.05-0.20 g kg-1 from 10 crop waste types, and 0.88 g kg-1 from dung cake, significantly lower than currently used emission factors for wood and crop waste. Estimated SO2 emissions from biofuels of 75 (36-160) Gg yr-1 were about a factor of 3 lower than that in recent studies, with a large contribution from dung cake (73%), followed by fuelwood (21%) and crop waste (6%).

Bioenergy Ecosystem Land-Use Modelling and Field Flux Trial

NASA Astrophysics Data System (ADS)

McNamara, Niall; Bottoms, Emily; Donnison, Iain; Dondini, Marta; Farrar, Kerrie; Finch, Jon; Harris, Zoe; Ineson, Phil; Keane, Ben; Massey, Alice; McCalmont, Jon; Morison, James; Perks, Mike; Pogson, Mark; Rowe, Rebecca; Smith, Pete; Sohi, Saran; Tallis, Mat; Taylor, Gail; Yamulki, Sirwan

2013-04-01

Climate change impacts resulting from fossil fuel combustion and concerns about the diversity of energy supply are driving interest to find low-carbon energy alternatives. As a result bioenergy is receiving widespread scientific, political and media attention for its potential role in both supplying energy and mitigating greenhouse (GHG) emissions. It is estimated that the bioenergy contribution to EU 2020 renewable energy targets could require up to 17-21 million hectares of additional land in Europe (Don et al., 2012). There are increasing concerns that some transitions into bioenergy may not be as sustainable as first thought when GHG emissions from the crop growth and management cycle are factored into any GHG life cycle assessment (LCA). Bioenergy is complex and encapsulates a wide range of crops, varying from food crop based biofuels to dedicated second generation perennial energy crops and forestry products. The decision on the choice of crop for energy production significantly influences the GHG mitigation potential. It is recognised that GHG savings or losses are in part a function of the original land-use that has undergone change and the management intensity for the energy crop. There is therefore an urgent need to better quantify both crop and site-specific effects associated with the production of conventional and dedicated energy crops on the GHG balance. Currently, there is scarcity of GHG balance data with respect to second generation crops meaning that process based models and LCAs of GHG balances are weakly underpinned. Therefore, robust, models based on real data are urgently required. In the UK we have recently embarked on a detailed program of work to address this challenge by combining a large number of field studies with state-of-the-art process models. Through six detailed experiments, we are calculating the annual GHG balances of land use transitions into energy crops across the UK. Further, we are quantifying the total soil carbon gain or loss after land use change at 100 fieldsites which encapsulate a range of UK climates and soil types. Our overall objective is to use our measured data to parameterise and validate the models that we will use to predict the implications of bioenergy crop deployment in the UK up to 2050. The resultant output will be a meta-model which will help facilitate decision making on the sustainable development of bioenergy in the UK, with potential deployment in other temperate climates around the world. Here we report on the outcome of the first of three years of work. This work is based on the Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial (ELUM) project, which was commissioned and funded by the Energy Technologies Institute (ETI). Don et al. (2012) Land-use change to bioenergy production in Europe: implications for the greenhouse gas balance and soil carbon. GCB Bioenergy 4, 372-379.

Patterns of nucleotide diversity and phenotypes of two domestication related genes (OsC1 and Wx) in indigenous rice varieties in Northeast India

PubMed Central

2014-01-01

Background During the domestication of crops, individual plants with traits desirable for human needs have been selected from their wild progenitors. Consequently, genetic and nucleotide diversity of genes associated with these selected traits in crop plants are expected to be lower than their wild progenitors. In the present study, we surveyed the pattern of nucleotide diversity of two selected trait specific genes, Wx and OsC1, which regulate amylose content and apiculus coloration respectively in cultivated rice varieties. The analyzed samples were collected from a wide geographic area in Northeast (NE) India, and included contrasting phenotypes considered to be associated with selected genes, namely glutinous and nonglutinous grains and colored and colorless apiculus. Results No statistically significant selection signatures were detected in both Wx and OsC1gene sequences. However, low level of selection that varied across the length of each gene was evident. The glutinous type varieties showed higher levels of nucleotide diversity at the Wx locus (πtot = 0.0053) than nonglutinous type varieties (πtot = 0.0043). The OsC1 gene revealed low levels of selection among the colorless apiculus varieties with lower nucleotide diversity (πtot = 0.0010) than in the colored apiculus varieties (πtot = 0.0023). Conclusions The results revealed that functional mutations at Wx and OsC1genes considered to be associated with specific phenotypes do not necessarily correspond to the phenotypes in indigenous rice varieties in NE India. This suggests that other than previously reported genomic regions may also be involved in determination of these phenotypes. PMID:24935343

Evaluating the potential of vegetation indices for winter wheat LAI estimation under different fertilization and water conditions

NASA Astrophysics Data System (ADS)

Xie, Qiaoyun; Huang, Wenjiang; Dash, Jadunandan; Song, Xiaoyu; Huang, Linsheng; Zhao, Jinling; Wang, Renhong

2015-12-01

Leaf area index (LAI) is an important indicator for monitoring crop growth conditions and forecasting grain yield. Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques. Spectral vegetation indices, mathematical combination of reflectance bands, are widely used for LAI estimation due to their computational simplicity and their applications ranged from the leaf scale to the entire globe. However, in many cases, their applicability is limited to specific vegetation types or local conditions due to species specific nature of the relationship used to transfer the vegetation indices to LAI. The overall objective of this study is to investigate the most suitable vegetation index for estimating winter wheat LAI under eight different types of fertilizer and irrigation conditions. Regression models were used to estimate LAI using hyperspectral reflectance data from the Pushbroom Hyperspectral Imager (PHI) and in-situ measurements. Our results showed that, among six vegetation indices investigated, the modified soil-adjusted vegetation index (MSAVI) and the normalized difference vegetation index (NDVI) exhibited strong and significant relationships with LAI, and thus were sensitive across different nitrogen and water treatments. The modified triangular vegetation index (MTVI2) confirmed its potential on crop LAI estimation, although second to MSAVI and NDVI in our study. The enhanced vegetation index (EVI) showed moderate performance. However, the ratio vegetation index (RVI) and the modified simple ratio index (MSR) predicted the least accurate estimations of LAI, exposing the simple band ratio index's weakness under different treatment conditions. The results support the use of vegetation indices for a quick and effective LAI mapping procedure that is suitable for winter wheat under different management practices.

Origins of Host-Specific Populations of the Blast Pathogen Magnaporthe oryzae in Crop Domestication With Subsequent Expansion of Pandemic Clones on Rice and Weeds of Rice

PubMed Central

Couch, Brett C.; Fudal, Isabelle; Lebrun, Marc-Henri; Tharreau, Didier; Valent, Barbara; van Kim, Pham; Nottéghem, Jean-Loup; Kohn, Linda M.

2005-01-01

Rice, as a widely and intensively cultivated crop, should be a target for parasite host shifts and a source for shifts to co-occurring weeds. Magnaporthe oryzae, of the M. grisea species complex, is the most important fungal pathogen of rice, with a high degree of host specificity. On the basis of 10 loci from six of its seven linkage groups, 37 multilocus haplotypes among 497 isolates of M. oryzae from rice and other grasses were identified. Phylogenetic relationships among isolates from rice (Oryza sativa), millet (Setaria spp.), cutgrass (Leersia hexandra), and torpedo grass (Panicum repens) were predominantly tree like, consistent with a lack of recombination, but from other hosts were reticulate, consistent with recombination. The single origin of rice-infecting M. oryzae followed a host shift from a Setaria millet and was closely followed by additional shifts to weeds of rice, cutgrass, and torpedo grass. Two independent estimators of divergence time indicate that these host shifts predate the Green Revolution and could be associated with rice domestication. The rice-infecting lineage is characterized by high copy number of the transposable element MGR586 (Pot3) and, except in two haplotypes, by a loss of AVR-Co39. Both mating types have been retained in ancestral, well-distributed rice-infecting haplotypes 10 (mainly temperate) and 14 (mainly tropical), but only one mating type was recovered from several derived, geographically restricted haplotypes. There is evidence of a common origin of both ACE1 virulence genotypes in haplotype 14. Host-haplotype association is evidenced by low pathogenicity on hosts associated with other haplotypes. PMID:15802503

[Effects of crop tree release on stand growth and stand structure of Cunninghamia lanceolata plantation].

PubMed

Wu, Jian-qiang; Wang, Yi-xiang; Yang, Yi; Zhu, Ting-ting; Zhu, Xu-dan

2015-02-01

Crop trees were selected in a 26-year-old even-aged Cunninghamia lanceolata plantation in Lin' an, and compared in plots that were released and unreleased to examine growth and structure responses for 3 years after thinning. Crop tree release significantly increased the mean increments of diameter and volume of individual tree by 1.30 and 1.25 times relative to trees in control stands, respectively. The increments of diameter and volume of crop trees were significantly higher than those of general trees in thinning plots, crop trees and general trees in control plots, which suggested that the responses from different tree types to crop tree release treatment were different. Crop tree release increased the average distances of crop trees to the nearest neighboring trees, reducing competition among crop trees by about 68.2%. 3-year stand volume increment for thinning stands had no significant difference with that of control stands although the number of trees was only 81.5% of the control. Crop trees in thinned plots with diameters over than 14 cm reached 18.0% over 3 years, compared with 12.0% for trees without thinning, suggesting that crop tree release benefited the larger individual trees. The pattern of tree locations in thinning plots tended to be random, complying with the rule that tree distribution pattern changes with growth. Crop tree release in C. lanceolata plantation not only promoted the stand growth, but also optimized the stand structure, benefiting crop trees sustained rapid growth and larger diameter trees production.

Characterization of agricultural land using singular value decomposition

NASA Astrophysics Data System (ADS)

Herries, Graham M.; Danaher, Sean; Selige, Thomas

1995-11-01

A method is defined and tested for the characterization of agricultural land from multi-spectral imagery, based on singular value decomposition (SVD) and key vector analysis. The SVD technique, which bears a close resemblance to multivariate statistic techniques, has previously been successfully applied to problems of signal extraction for marine data and forestry species classification. In this study the SVD technique is used as a classifier for agricultural regions, using airborne Daedalus ATM data, with 1 m resolution. The specific region chosen is an experimental research farm in Bavaria, Germany. This farm has a large number of crops, within a very small region and hence is not amenable to existing techniques. There are a number of other significant factors which render existing techniques such as the maximum likelihood algorithm less suitable for this area. These include a very dynamic terrain and tessellated pattern soil differences, which together cause large variations in the growth characteristics of the crops. The SVD technique is applied to this data set using a multi-stage classification approach, removing unwanted land-cover classes one step at a time. Typical classification accuracy's for SVD are of the order of 85-100%. Preliminary results indicate that it is a fast and efficient classifier with the ability to differentiate between crop types such as wheat, rye, potatoes and clover. The results of characterizing 3 sub-classes of Winter Wheat are also shown.

Recessive Resistance to Plant Viruses: Potential Resistance Genes Beyond Translation Initiation Factors

PubMed Central

Hashimoto, Masayoshi; Neriya, Yutaro; Yamaji, Yasuyuki; Namba, Shigetou

2016-01-01

The ability of plant viruses to propagate their genomes in host cells depends on many host factors. In the absence of an agrochemical that specifically targets plant viral infection cycles, one of the most effective methods for controlling viral diseases in plants is taking advantage of the host plant’s resistance machinery. Recessive resistance is conferred by a recessive gene mutation that encodes a host factor critical for viral infection. It is a branch of the resistance machinery and, as an inherited characteristic, is very durable. Moreover, recessive resistance may be acquired by a deficiency in a negative regulator of plant defense responses, possibly due to the autoactivation of defense signaling. Eukaryotic translation initiation factor (eIF) 4E and eIF4G and their isoforms are the most widely exploited recessive resistance genes in several crop species, and they are effective against a subset of viral species. However, the establishment of efficient, recessive resistance-type antiviral control strategies against a wider range of plant viral diseases requires genetic resources other than eIF4Es. In this review, we focus on recent advances related to antiviral recessive resistance genes evaluated in model plants and several crop species. We also address the roles of next-generation sequencing and genome editing technologies in improving plant genetic resources for recessive resistance-based antiviral breeding in various crop species. PMID:27833593

Engineering of CRISPR/Cas9-mediated potyvirus resistance in transgene-free Arabidopsis plants.

PubMed

Pyott, Douglas E; Sheehan, Emma; Molnar, Attila

2016-10-01

Members of the eukaryotic translation initiation factor (eIF) gene family, including eIF4E and its paralogue eIF(iso)4E, have previously been identified as recessive resistance alleles against various potyviruses in a range of different hosts. However, the identification and introgression of these alleles into important crop species is often limited. In this study, we utilise CRISPR/Cas9 technology to introduce sequence-specific deleterious point mutations at the eIF(iso)4E locus in Arabidopsis thaliana to successfully engineer complete resistance to Turnip mosaic virus (TuMV), a major pathogen in field-grown vegetable crops. By segregating the induced mutation from the CRISPR/Cas9 transgene, we outline a framework for the production of heritable, homozygous mutations in the transgene-free T2 generation in self-pollinating species. Analysis of dry weights and flowering times for four independent T3 lines revealed no differences from wild-type plants under standard growth conditions, suggesting that homozygous mutations in eIF(iso)4E do not affect plant vigour. Thus, the established CRISPR/Cas9 technology provides a new approach for the generation of Potyvirus resistance alleles in important crops without the use of persistent transgenes. © 2016 The Authors. Molecular Plant Pathology Published by British Society for Plant Pathology and John Wiley & Sons Ltd.

Root development of winter wheat in erosion-affected soils depending on the position in a hummocky ground moraine soil landscape

NASA Astrophysics Data System (ADS)

Herbrich, Marcus; Gerke, Horst H.; Sommer, Michael

2017-04-01

The soil water uptake by crops is a key process in the hydrological cycle of agricultural ecosystems. In the arable hummocky ground moraines soil landscapes, an erosion-induced spatial differentiation of soil types has been established due to water and tillage erosion. Crop development may reflect soil landscape patterns and erosion-induced soil profile modifications, respectively, by increased or reduced plant and root growth. The objective was analyze field data of the root density and the root lengths of winter wheat for a non-eroded reference soil at the plateau (Albic Luvisol), an extremely eroded soil at steep midslope (Calcaric Regosol), and depositional soil at the footslope (Colluvic Regosol) using the minirhizotron technique. From 9/14 to 8/15 results indicate that root density values were highest for the Colluvic Regosol, followed by the Albic Luvisol and lowest for the Calcaric Regosol. In turn, the lowest maximum root penetration depth was found in the Colluvic Regosol because of the relatively high and fluctuating water table at this landscape position. The analyzed field root data revealed positive relations to above-ground plant parameters and corroborated the hypothesis that the crop root system was reflecting erosion-induced soil profile modifications. When accounting for the position-specific root development, the simulation of water and solute movement suggested differences in the balances as compared to assuming a spatially uniform development.

Relationship between cotton yield and soil electrical conductivity, topography, and landsat imagery

USDA-ARS?s Scientific Manuscript database

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this stu...

Response of Pennsylvania native plant species to dicamba and/or glyphosate

EPA Science Inventory

Weeds may become resistant to intensive and extensive use of specific herbicides associated with the growth of herbicide tolerant crops, e.g., the use of glyphosate for weed control with glyphosate tolerant soybeans. To counter this resistance, crops modified to contain genes for...

Automation of irrigation systems to control irrigation applications and crop water use efficiency

USDA-ARS?s Scientific Manuscript database

Agricultural irrigation management to slow water withdrawals from non-replenishing quality water resources is a global endeavor and vital to sustaining irrigated agriculture and dependent rural economies. Research in site-specific irrigation management has shown that water use efficiency, and crop p...

Origins of food crops connect countries worldwide

USDA-ARS?s Scientific Manuscript database

Research into the origins of food plants has led to the recognition that specific geographic regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not...

It's just grass, isn't it?

USDA-ARS?s Scientific Manuscript database

The theme of the Calvin Sperling Memorial Lectureship is "biodiversity" specifically with regard to crop germplasm. Could any other theme be nearer to the heart and soul of a plant breeder or geneticist? In 40 years of working on crop germplasm biodiversity, I've (hopefully) learned some lessons abo...

29 CFR 575.4 - Information to be included in application.

Code of Federal Regulations, 2013 CFR

2013-07-01

... identifying each employer's farm(s) or field(s) where 10 and 11 year old hand-harvest laborers are to be employed. (d) The specific crop or crops to be hand-harvested at each designated farm or field. (e... will be employed outside school hours. ...

29 CFR 575.4 - Information to be included in application.

Code of Federal Regulations, 2012 CFR

2012-07-01

... identifying each employer's farm(s) or field(s) where 10 and 11 year old hand-harvest laborers are to be employed. (d) The specific crop or crops to be hand-harvested at each designated farm or field. (e... will be employed outside school hours. ...

29 CFR 575.4 - Information to be included in application.

Code of Federal Regulations, 2014 CFR

2014-07-01

... identifying each employer's farm(s) or field(s) where 10 and 11 year old hand-harvest laborers are to be employed. (d) The specific crop or crops to be hand-harvested at each designated farm or field. (e... will be employed outside school hours. ...

Measuring natural enemy dispersal from cover crops in a California vineyard

USDA-ARS?s Scientific Manuscript database

Dispersal of natural enemies from buckwheat cover crop plots embedded within a southern California vineyard during spring and summer was investigated by using an arthropod mark-capture technique. Specifically, arthropods were marked in flowering buckwheat plots by spraying plants with a “triple mark...

A True-Color Sensor and Suitable Evaluation Algorithm for Plant Recognition

PubMed Central

Schmittmann, Oliver; Schulze Lammers, Peter

2017-01-01

Plant-specific herbicide application requires sensor systems for plant recognition and differentiation. A literature review reveals a lack of sensor systems capable of recognizing small weeds in early stages of development (in the two- or four-leaf stage) and crop plants, of making spraying decisions in real time and, in addition, are that are inexpensive and ready for practical use in sprayers. The system described in this work is based on free cascadable and programmable true-color sensors for real-time recognition and identification of individual weed and crop plants. The application of this type of sensor is suitable for municipal areas and farmland with and without crops to perform the site-specific application of herbicides. Initially, databases with reflection properties of plants, natural and artificial backgrounds were created. Crop and weed plants should be recognized by the use of mathematical algorithms and decision models based on these data. They include the characteristic color spectrum, as well as the reflectance characteristics of unvegetated areas and areas with organic material. The CIE-Lab color-space was chosen for color matching because it contains information not only about coloration (a- and b-channel), but also about luminance (L-channel), thus increasing accuracy. Four different decision making algorithms based on different parameters are explained: (i) color similarity (ΔE); (ii) color similarity split in ΔL, Δa and Δb; (iii) a virtual channel ‘d’ and (iv) statistical distribution of the differences of reflection backgrounds and plants. Afterwards, the detection success of the recognition system is described. Furthermore, the minimum weed/plant coverage of the measuring spot was calculated by a mathematical model. Plants with a size of 1–5% of the spot can be recognized, and weeds in the two-leaf stage can be identified with a measuring spot size of 5 cm. By choosing a decision model previously, the detection quality can be increased. Depending on the characteristics of the background, different models are suitable. Finally, the results of field trials on municipal areas (with models of plants), winter wheat fields (with artificial plants) and grassland (with dock) are shown. In each experimental variant, objects and weeds could be recognized. PMID:28786922

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.

A True-Color Sensor and Suitable Evaluation Algorithm for Plant Recognition.

PubMed

Schmittmann, Oliver; Schulze Lammers, Peter

2017-08-08

Plant-specific herbicide application requires sensor systems for plant recognition and differentiation. A literature review reveals a lack of sensor systems capable of recognizing small weeds in early stages of development (in the two- or four-leaf stage) and crop plants, of making spraying decisions in real time and, in addition, are that are inexpensive and ready for practical use in sprayers. The system described in this work is based on free cascadable and programmable true-color sensors for real-time recognition and identification of individual weed and crop plants. The application of this type of sensor is suitable for municipal areas and farmland with and without crops to perform the site-specific application of herbicides. Initially, databases with reflection properties of plants, natural and artificial backgrounds were created. Crop and weed plants should be recognized by the use of mathematical algorithms and decision models based on these data. They include the characteristic color spectrum, as well as the reflectance characteristics of unvegetated areas and areas with organic material. The CIE-Lab color-space was chosen for color matching because it contains information not only about coloration (a- and b-channel), but also about luminance (L-channel), thus increasing accuracy. Four different decision making algorithms based on different parameters are explained: (i) color similarity (ΔE); (ii) color similarity split in ΔL, Δa and Δb; (iii) a virtual channel 'd' and (iv) statistical distribution of the differences of reflection backgrounds and plants. Afterwards, the detection success of the recognition system is described. Furthermore, the minimum weed/plant coverage of the measuring spot was calculated by a mathematical model. Plants with a size of 1-5% of the spot can be recognized, and weeds in the two-leaf stage can be identified with a measuring spot size of 5 cm. By choosing a decision model previously, the detection quality can be increased. Depending on the characteristics of the background, different models are suitable. Finally, the results of field trials on municipal areas (with models of plants), winter wheat fields (with artificial plants) and grassland (with dock) are shown. In each experimental variant, objects and weeds could be recognized.

[Development of APSIM (agricultural production systems simulator) and its application].

PubMed

Shen, Yuying; Nan, Zhibiao; Bellotti, Bill; Robertson, Michael; Chen, Wen; Shao, Xinqing

2002-08-01

Soil-crop simulator model is an effective tool for providing decision on agricultural management. APSIM (Agricultural Production Systems Simulator) was developed to simulate the biophysical process in farming system, and particularly in the economic and ecological features of the systems under climatic risk. The current literatures revealed that APSIM could be applied in wide zone, including temperate continental, temperate maritime, sub-tropic and arid climate, and Mediterranean climates, with the soil type of clay, duplex soil, vertisol, silt sandy, silt loam and silt clay loam. More than 20 crops have been simulated well. APSIM is powerful on describing crop structure, crop sequence, yield prediction, and quality control as well as erosion estimation under different planting pattern.

Identification of technology options for reducing nitrogen pollution in cropping systems of Pujiang*

PubMed Central

Fang, Bin; Wang, Guang-huo; Van den berg, Marrit; Roetter, Reimund

2005-01-01

This work analyses the potential role of nitrogen pollution technology of crop systems of Pujiang, County in Eastern China’s Zhejiang Province, rice and vegetables are important cropping systems. We used a case study approach involving comparison of farmer practices and improved technologies. This approach allows assessing the impact of technology on pollution, is forward looking, and can yield information on the potential of on-the-shelf technology and provide opportunities for technology development. The approach particularly suits newly developed rice technologies with large potential of reducing nitrogen pollution and for future rice and vegetables technologies. The results showed that substantial reductions in nitrogen pollution are feasible for both types of crops. PMID:16187411

Identification of technology options for reducing nitrogen pollution in cropping systems of Pujiang.

PubMed

Fang, Bin; Wang, Guang-Huo; Van, Den Berg Marrit; Roetter, Reimund

2005-10-01

This work analyses the potential role of nitrogen pollution technology of crop systems of Pujiang, County in Eastern China's Zhejiang Province, rice and vegetables are important cropping systems. We used a case study approach involving comparison of farmer practices and improved technologies. This approach allows assessing the impact of technology on pollution, is forward looking, and can yield information on the potential of on-the-shelf technology and provide opportunities for technology development. The approach particularly suits newly developed rice technologies with large potential of reducing nitrogen pollution and for future rice and vegetables technologies. The results showed that substantial reductions in nitrogen pollution are feasible for both types of crops.

The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

NASA Astrophysics Data System (ADS)

Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

2016-06-01

Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower relationship to vegetation indices. Total amount of aboveground biomass was identified as the most important factor influencing the values of vegetation indices. Based on the results can be assumed that UAV and satellite monitoring provide reliable information about crop parameters for site specific crop management. The main difference of their utilization is coming from their specification and technical limits. Satellite survey can be used for periodic monitoring of crops as the indicator of their spatial heterogeneity within fields, but with low resolution (30 m per pixel for OLI). On the other hand UAV represents a special campaign aimed on the mapping of high-detailed spatial inputs for site specific crop management and variable rate application of fertilizers.

The ebb and flow of airborne pathogens: Monitoring and use in disease management decisions

USDA-ARS?s Scientific Manuscript database

Perhaps the earliest form of monitoring the regional spread of plant disease was a group of growers gathering together at the market and discussing what they see in their crops. This type of reporting continues to this day through regional extension blogs, by crop consultants and more formal scoutin...

Vulnerability of crops and native grasses to summer drying in the U.S. Southern Great Plains

USDA-ARS?s Scientific Manuscript database

The Southern Great Plains are characterized by a fine-scale mixture of different land cover types, predominantly winter-wheat and pasture lands, with relatively small areas of other crops, native prairie, and switchgrass. Recent droughts and predictions of increased drought (especially during the s...

Evaluation of alfalfa (Medicago sativa L.) populations' response to salinity stress

USDA-ARS?s Scientific Manuscript database

Alfalfa is a moderately salt tolerant crop with high economic return, therefore more suitable for production with lower quality water than most high value crops. This study was conducted to examine the effects of the irrigation water salt type (ST=Cl- or SO4 2-) and five salinity levels (ECiw= 0.85,...

A global trait-based approach to estimate leaf nitrogen functional allocation from observations

DOE PAGES

Ghimire, Bardan; Riley, William J.; Koven, Charles D.; ...

2017-03-28

Nitrogen is one of the most important nutrients for plant growth and a major constituent of proteins that regulate photosynthetic and respiratory processes. However, a comprehensive global analysis of nitrogen allocation in leaves for major processes with respect to different plant functional types is currently lacking. This study integrated observations from global databases with photosynthesis and respiration models to determine plant-functional-type-specific allocation patterns of leaf nitrogen for photosynthesis (Rubisco, electron transport, light absorption) and respiration (growth and maintenance), and by difference from observed total leaf nitrogen, an unexplained “residual” nitrogen pool. Based on our analysis, crops partition the largest fractionmore » of nitrogen to photosynthesis (57%) and respiration (5%) followed by herbaceous plants (44% and 4%). Tropical broadleaf evergreen trees partition the least to photosynthesis (25%) and respiration (2%) followed by needle-leaved evergreen trees (28% and 3%). In trees (especially needle-leaved evergreen and tropical broadleaf evergreen trees) a large fraction (70% and 73% respectively) of nitrogen was not explained by photosynthetic or respiratory functions. Compared to crops and herbaceous plants, this large residual pool is hypothesized to emerge from larger investments in cell wall proteins, lipids, amino acids, nucleic acid, CO2 fixation proteins (other than Rubisco), secondary compounds, and other proteins. Our estimates are different from previous studies due to differences in methodology and assumptions used in deriving nitrogen allocation estimates. Unlike previous studies, we integrate and infer nitrogen allocation estimates across multiple plant functional types, and report substantial differences in nitrogen allocation across different plant functional types. Furthermore, the resulting pattern of nitrogen allocation provides insights on mechanisms that operate at a cellular scale within leaves, and can be integrated with ecosystem models to derive emergent properties of ecosystem productivity at local, regional, and global scales.« less

A global trait-based approach to estimate leaf nitrogen functional allocation from observations

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

Ghimire, Bardan; Riley, William J.; Koven, Charles D.

Nitrogen is one of the most important nutrients for plant growth and a major constituent of proteins that regulate photosynthetic and respiratory processes. However, a comprehensive global analysis of nitrogen allocation in leaves for major processes with respect to different plant functional types is currently lacking. This study integrated observations from global databases with photosynthesis and respiration models to determine plant-functional-type-specific allocation patterns of leaf nitrogen for photosynthesis (Rubisco, electron transport, light absorption) and respiration (growth and maintenance), and by difference from observed total leaf nitrogen, an unexplained “residual” nitrogen pool. Based on our analysis, crops partition the largest fractionmore » of nitrogen to photosynthesis (57%) and respiration (5%) followed by herbaceous plants (44% and 4%). Tropical broadleaf evergreen trees partition the least to photosynthesis (25%) and respiration (2%) followed by needle-leaved evergreen trees (28% and 3%). In trees (especially needle-leaved evergreen and tropical broadleaf evergreen trees) a large fraction (70% and 73% respectively) of nitrogen was not explained by photosynthetic or respiratory functions. Compared to crops and herbaceous plants, this large residual pool is hypothesized to emerge from larger investments in cell wall proteins, lipids, amino acids, nucleic acid, CO2 fixation proteins (other than Rubisco), secondary compounds, and other proteins. Our estimates are different from previous studies due to differences in methodology and assumptions used in deriving nitrogen allocation estimates. Unlike previous studies, we integrate and infer nitrogen allocation estimates across multiple plant functional types, and report substantial differences in nitrogen allocation across different plant functional types. Furthermore, the resulting pattern of nitrogen allocation provides insights on mechanisms that operate at a cellular scale within leaves, and can be integrated with ecosystem models to derive emergent properties of ecosystem productivity at local, regional, and global scales.« less

Radar spectral measurements of vegetation

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Moore, R. K.

1973-01-01

Spectral data of 4-8 GHz radar backscatter were gathered during the 1972 growing season at look angles between 0 and 70 deg and for all four possible polarization linear combinations. The data covers four crop types (corn, milo, alfalfa, and soybeans) and a wide range of soil moisture content. To insure statistical representation of the results, measurements were conducted over 128 fields corresponding to a total of about 40,000 data points. The use of spectral response signatures to separate different crop types and to separate healthy corn from blighted corn was investigated.

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations.

PubMed

Corbari, Chiara; Ravazzani, Giovanni; Galvagno, Marta; Cremonese, Edoardo; Mancini, Marco

2017-11-18

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

The Effects of Crop Intensification on the Diversity of Native Pollinator Communities.

PubMed

Mogren, Christina L; Rand, Tatyana A; Fausti, Scott W; Lundgren, Jonathan G

2016-08-01

Increases in agricultural conversion are leading to declines in native grasslands and natural resources critical for beneficial insects. However, little is known regarding how these changes affect pollinator diversity. Land use types were categorized within 300 m and 3 km radii of pollinator sampling locations in Brookings County, SD. Pollinator abundance and species richness were regressed on the proportion of the landscape dedicated to row crops, grass and pasture, forage crops, small grains, and aquatic habitats using variance components modeling. Row crops had a negative effect on bee abundance at 300 m, after fixed effects modeling accounted for outliers skewing this relationship. At 3 km, corn positively affected bee abundance and richness, while soybean acreage decreased species richness. The landscape matrix of outlying sites consisted of large monocultured areas with few alternative habitat types available, leading to inflated populations of Melissodes and Halictidae. Syrphids had a positive parabolic relationship between diversity and row crops, indicating potential for competitive exclusion from intermediate landscapes. Unlike other studies, landscape diversity within 300 m was not found to significantly benefit pollinator diversity. Within especially agriculturally developed areas of the region, high abundances of pollinators suggest selection for a few dominant species. There was no effect of forage crops or aquatic habitats on pollinator diversity, indicating that less highly managed areas still represent degraded habitat within the landscape. Incorporating pollinator-friendly crops at the farm level throughout the region is likely to enhance pollinator diversity by lessening the negative effects of large monocultures. © 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.

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.

[Emission inventory of greenhouse gases from agricultural residues combustion: a case study of Jiangsu Province].

PubMed

Liu, Li-hua; Jiang, Jing-yan; Zong, Liang-gang

2011-05-01

Burning of agricultural crop residues was a major source greenhouse gases. In this study, the proportion of crop straws (rice, wheat, maize, oil rape, cotton and soja) in Jiangsu used as household fuel and direct open burning in different periods (1990-1995, 1996-2000, 2001-2005 and 2006-2008) was estimated through questionnaire. The emission factors of CO2, CO, CH4 and NO20 from the above six types of crop straws were calculated by the simulated burning experiment. Thus the emission inventory of greenhouse gases from crop straws burning was established according to above the burning percentages and emission factors, ratios of dry residues to production and crop productions of different periods in Jiangsu province. Results indicated that emission factors of CO2, CO, CH4 and N2O depended on crop straw type. The emission factors of CO2 and CH4 were higher for oil rape straw than the other straws, while the maize and the rice straw had the higher N2O and CO emission factor. Emission inventory of greenhouse gases from agricultural residues burning in Jiangsu province showed, the annual average global warming potential (GWP) of six tested crop straws were estimated to be 9.18 (rice straw), 4.35 (wheat straw), 2.55 (maize straw), 1.63 (oil rape straw), 0.55 (cotton straw) and 0. 39 (soja straw) Tg CO2 equivalent, respectively. Among the four study periods, the annual average GWP had no obvious difference between the 1990-1995 and 2006-2008 periods, while the maximal annual average GWP (23.83 Tg CO2 equivalent) happened in the 1996-2000 period, and the minimum (20.30 Tg CO2 equivalent) in 1996-2000 period.

Intensification of tropical agriculture as seen by satellite

NASA Astrophysics Data System (ADS)

Galford, G. L.; Michelson, H. C.; Spera, S. A.; Hadnott, B.

2013-12-01

We present case studies from Latin America and Africa on intensification of tropical agriculture. The Brazilian Amazon of the early 2000s experienced intensification and extensification. We use time series analysis of MODIS vegetation indices to track changes in cropping intensity and crop types over time. The state of Mato Grosso is Brazil's leading producer of soy, corn and cotton. Using 250 m MODIS EVI data and a new decision-tree algorithm tuned to phenological patterns characteristic of Mato Grosso's major natural vegetation and crop rotations, we mapped land-cover across the state over 11 growing seasons (2001-2011). Between 2000 and 2011, a majority of the cultivated land in Mato Grosso transitioned from the cultivation of one commercial crop per growing season (soy or cotton) to two commercial crops (a soy crop followed by a corn or cotton crop). Over our study period, the cultivated area of double cropped land in Mato Grosso steadily increased over 6-fold from .46 million hectares to 2.9 million hectares, 92% of which was in a soy-corn double cropping rotation. In the sub-Saharan country of Malawi, 70% of the land is dedicated to food production yet yields of the primary staple crop, maize, have stagnated around 1 ton ha-1 (developed nations' maize yields are 12-16 tons ha-1). Due to the limited land area, improving yields through intensification is a necessary objective of development. Poverty and food insecurity were widespread and persistent for smallholder farmers cultivating less than 1 hectare of land until the implementation of a government intervention, funded through foreign aid, subsidized allocations of fertilizer and improved seed to small farmers. Since implementation of the policy, the number of food insecure, or people in need of food aid, has decreased from 5 million to half a million people. We present indicators that levels of poverty have decreased since the subsidy. National yields have doubled. Applying modified methods from Brazil, we are able to detect cropland intensification through remote sensing. We present remote sensing analysis of social and economic correlates to changes in yields and build an empirical model of sustainable intensification. Together, these case studies demonstrate that remote sensing techniques can be easily adapted across very different crop types, field sizes and environments.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

PubMed

Bengochea-Guevara, José M; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-02-24

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot

PubMed Central

Bengochea-Guevara, José M.; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-01-01

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them. PMID:26927102

Land-use legacies regulate decomposition dynamics following bioenergy crop conversion

DOE PAGES

Kallenbach, Cynthia M.; Stuart Grandy, A.

2014-07-14

Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter andmore » when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.« less

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

NASA Astrophysics Data System (ADS)

Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

2015-02-01

Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance resampling, VIs inter-calibration and spatial resampling.

Brachypodium distachyon as a new model system for understanding iron homeostasis in grasses: phylogenetic and expression analysis of Yellow Stripe-Like (YSL) transporters

PubMed Central

Yordem, Burcu K.; Conte, Sarah S.; Ma, Jian Feng; Yokosho, Kengo; Vasques, Kenneth A.; Gopalsamy, Srinivasa N.; Walker, Elsbeth L.

2011-01-01

Background and Aims Brachypodium distachyon is a temperate grass with a small stature, rapid life cycle and completely sequenced genome that has great promise as a model system to study grass-specific traits for crop improvement. Under iron (Fe)-deficient conditions, grasses synthesize and secrete Fe(III)-chelating agents called phytosiderophores (PS). In Zea mays, Yellow Stripe1 (ZmYS1) is the transporter responsible for the uptake of Fe(III)–PS complexes from the soil. Some members of the family of related proteins called Yellow Stripe-Like (YSL) have roles in internal Fe translocation of plants, while the function of other members remains uninvestigated. The aim of this study is to establish brachypodium as a model system to study Fe homeostasis in grasses, identify YSL proteins in brachypodium and maize, and analyse their expression profiles in brachypodium in response to Fe deficiency. Methods The YSL family of proteins in brachypodium and maize were identified based on sequence similarity to ZmYS1. Expression patterns of the brachypodium YSL genes (BdYSL genes) were determined by quantitative RT–PCR under Fe-deficient and Fe-sufficient conditions. The types of PS secreted, and secretion pattern of PS in brachypodium were analysed by high-performance liquid chromatography. Key Results Eighteen YSL family members in maize and 19 members in brachypodium were identified. Phylogenetic analysis revealed that some YSLs group into a grass-specific clade. The Fe status of the plant can regulate expression of brachypodium YSL genes in both shoots and roots. 3-Hydroxy-2′-deoxymugineic acid (HDMA) is the dominant type of PS secreted by brachypodium, and its secretion is diurnally regulated. Conclusions PS secretion by brachypodium parallels that of related crop species such as barley and wheat. A single grass species-specific YSL clade is present, and expression of the BdYSL members of this clade could not be detected in shoots or roots, suggesting grass-specific functions in reproductive tissues. Finally, the Fe-responsive expression profiles of several YSLs suggest roles in Fe homeostasis. PMID:21831857