Agricultural Research Service

ABSTRACT: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins. The model is currently being utilized in several large area projects by EPA, NOAA, NRCS and others to estimate the off‐site impacts of climate and management on water use, non‐point source loadings, and pesticide contamination. Model development, operation, limitations, and assumptions are discussed and components of the model are described. In Part II, a GIS input/output interface is presented along with model validation on three basins within the Upper Trinity basin in Texas.

Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.

Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously. Algorithms were derived and computer programs tested with simulated data for 2,967 bulls and 50,000 markers distributed randomly across 30 chromosomes. Estimation of genomic inbreeding coefficients required accurate estimates of allele frequencies in the base population. Linear model predictions of breeding values were computed by 3 equivalent methods: 1) iteration for individual allele effects followed by summation across loci to obtain estimated breeding values, 2) selection index including a genomic relationship matrix, and 3) mixed model equations including the inverse of genomic relationships. A blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects. Reliability of predicted net merit for young bulls was 63% compared with 32% using the traditional relationship matrix. Nonlinear predictions were also computed using iteration on data and nonlinear regression on marker deviations; an additional (about 3%) gain in reliability for young bulls increased average reliability to 66%. Computing times increased linearly with number of genotypes. Estimation of allele frequencies required 2 processor days, and genomic predictions required <1 d per trait, and traits were processed in parallel. Information from genotyping was equivalent to about 20 daughters with phenotypic records. Actual gains may differ because the simulation did not account for linkage disequilibrium in the base population or selection in subsequent generations.

Fundamental features of microbial cellulose utilization are examined at successively higher levels of aggregation encompassing the structure and composition of cellulosic biomass, taxonomic diversity, cellulase enzyme systems, molecular biology of cellulase enzymes, physiology of cellulolytic microorganisms, ecological aspects of cellulase-degrading communities, and rate-limiting factors in nature. The methodological basis for studying microbial cellulose utilization is considered relative to quantification of cells and enzymes in the presence of solid substrates as well as apparatus and analysis for cellulose-grown continuous cultures. Quantitative description of cellulose hydrolysis is addressed with respect to adsorption of cellulase enzymes, rates of enzymatic hydrolysis, bioenergetics of microbial cellulose utilization, kinetics of microbial cellulose utilization, and contrasting features compared to soluble substrate kinetics. A biological perspective on processing cellulosic biomass is presented, including features of pretreated substrates and alternative process configurations. Organism development is considered for "consolidated bioprocessing" (CBP), in which the production of cellulolytic enzymes, hydrolysis of biomass, and fermentation of resulting sugars to desired products occur in one step. Two organism development strategies for CBP are examined: (i) improve product yield and tolerance in microorganisms able to utilize cellulose, or (ii) express a heterologous system for cellulose hydrolysis and utilization in microorganisms that exhibit high product yield and tolerance. A concluding discussion identifies unresolved issues pertaining to microbial cellulose utilization, suggests approaches by which such issues might be resolved, and contrasts a microbially oriented cellulose hydrolysis paradigm to the more conventional enzymatically oriented paradigm in both fundamental and applied contexts.

The lignin biosynthetic pathway has been studied for more than a century but has undergone major revisions over the past decade. Significant progress has been made in cloning new genes by genetic and combined bioinformatics and biochemistry approaches. In vitro enzymatic assays and detailed analyses of mutants and transgenic plants altered in the expression of lignin biosynthesis genes have provided a solid basis for redrawing the monolignol biosynthetic pathway, and structural analyses have shown that plant cell walls can tolerate large variations in lignin content and structure. In some cases, the potential value for agriculture of transgenic plants with modified lignin structure has been demonstrated. This review presents a current picture of monolignol biosynthesis, polymerization, and lignin structure.

The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey. SMAP will make global measurements of the soil moisture present at the Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy, and carbon transfers between the land and the atmosphere. The accuracy of numerical models of the atmosphere used in weather prediction and climate projections are critically dependent on the correct characterization of these transfers. Soil moisture measurements are also directly applicable to flood assessment and drought monitoring. SMAP observations can help monitor these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept will utilize L-band radar and radiometer instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP is scheduled for launch in the 2014-2015 time frame.

Abstract Spatial distributions of soil properties at the field and watershed scale may affect yield potential, hydrologic responses, and transport of herbicides and NO − 3 to surface or groundwater. Our research describes field‐scale distributions and spatial trends for 28 different soil parameters at two sites within a watershed in central Iowa. Two of 27 parameters measured at one site and 10 of 14 parameters measured at the second site were normally distributed. Spatial variability was investigated using semivariograms and the ratio of nugget to total semivariance, expressed as a percentage, was used to classify spatial dependence. A ratio of &lt;25% indicated strong spatial dependence, between 25 and 75% indicated moderate spatial dependence, and &gt;75% indicated weak spatial dependence. Twelve parameters at Site one, including organic C, total N, pH, and macroaggregation, and four parameters at Site two, including organic C and total N, were strongly spatially dependent. Six parameters at Site one, including biomass C and N, bulk density, and denitrification, and 9 parameters at Site two, including biomass C and N and bulk density, were moderately spatially dependent. Three parameters at Site one, including NO − 3 N and ergosterol, and one parameter at Site two, mineral‐associated N, were weakly spatially dependent. Distributions of exchangeable Ca and Mg at Site one were not spatially dependent. Spatial distributions for some soil properties were similar for both field sites. We will be able to exploit these similarities to improve our ability to extrapolate information taken from one field to other fields within similar landscapes.

Beneficial microbes in the microbiome of plant roots improve plant health. Induced systemic resistance (ISR) emerged as an important mechanism by which selected plant growth-promoting bacteria and fungi in the rhizosphere prime the whole plant body for enhanced defense against a broad range of pathogens and insect herbivores. A wide variety of root-associated mutualists, including Pseudomonas, Bacillus, Trichoderma, and mycorrhiza species sensitize the plant immune system for enhanced defense without directly activating costly defenses. This review focuses on molecular processes at the interface between plant roots and ISR-eliciting mutualists, and on the progress in our understanding of ISR signaling and systemic defense priming. The central role of the root-specific transcription factor MYB72 in the onset of ISR and the role of phytohormones and defense regulatory proteins in the expression of ISR in aboveground plant parts are highlighted. Finally, the ecological function of ISR-inducing microbes in the root microbiome is discussed.

Mycotoxins are secondary metabolites produced by microfungi that are capable of causing disease and death in humans and other animals. Because of their pharmacological activity, some mycotoxins or mycotoxin derivatives have found use as antibiotics, growth promotants, and other kinds of drugs; still others have been implicated as chemical warfare agents. This review focuses on the most important ones associated with human and veterinary diseases, including aflatoxin, citrinin, ergot akaloids, fumonisins, ochratoxin A, patulin, trichothecenes, and zearalenone.

Advancement of DNA sequencing technology allows the routine use of genome sequences in the various fields of microbiology. The information held in genome sequences proved to provide objective and reliable means in the taxonomy of prokaryotes. Here, we describe the minimal standards for the quality of genome sequences and how they can be applied for taxonomic purposes.

Phosphorus (P) is limiting for crop yield on > 30% of the world's arable land and, by some estimates, world resources of inexpensive P may be depleted by 2050. Improvement of P acquisition and use by plants is critical for economic, humanitarian and environmental reasons. Plants have evolved a diverse array of strategies to obtain adequate P under limiting conditions, including modifications to root architecture, carbon metabolism and membrane structure, exudation of low molecular weight organic acids, protons and enzymes, and enhanced expression of the numerous genes involved in low-P adaptation. These adaptations may be less pronounced in mycorrhizal-associated plants. The formation of cluster roots under P-stress by the nonmycorrhizal species white lupin (Lupinus albus), and the accompanying biochemical changes exemplify many of the plant adaptations that enhance P acquisition and use. Physiological, biochemical, and molecular studies of white lupin and other species response to P-deficiency have identified targets that may be useful for plant improvement. Genomic approaches involving identification of expressed sequence tags (ESTs) found under low-P stress may also yield target sites for plant improvement. Interdisciplinary studies uniting plant breeding, biochemistry, soil science, and genetics under the large umbrella of genomics are prerequisite for rapid progress in improving nutrient acquisition and use in plants. Contents I. Introduction 424 II. The phosphorus conundrum 424 III. Adaptations to low P 424 IV. Uptake of P 424 V. P deficiency alters root development and function 426 VI. P deficiency modifies carbon metabolism 431 VII. Acid phosphatase 436 VIII. Genetic regulation of P responsive genes 437 IX. Improving P acquisition 439 X. Synopsis 440.

We developed stage of development descriptions which we believe apply to all soybean ( Glycine max (L.) Merr.) genotypes grown in any environment. The descriptions apply to single plants or a community of plants and are precise and objective. Vegetative and reproductive development are described separately. Vegetative stages are determined by counting the number of nodes on the main stem, beginning with the unifoliolate node, that have or have had a completely unrolled leaf. Reproductive stages Rl and R2 are based on flowering, R3 and R4 on pod development, R5 and R6 on seed development, and R7 and R8 on maturation. The stage descriptions should enhance soybean research by standardizing descriptions of soybean plant development. The system also will be used by the soybean hail insurance industry for stage determination in adjustment of losses.

The antioxidant capacities (oxygen radical absorbance capacity, ORAC) and total phenolic contents in extracts of 27 culinary herbs and 12 medicinal herbs were determined. The ORAC values and total phenolic contents for the medicinal herbs ranged from 1.88 to 22.30 micromol of Trolox equivalents (TE)/g of fresh weight and 0.23 to 2.85 mg of gallic acid equivalents (GAE)/g of fresh weight, respectively. Origanum x majoricum, O. vulgare ssp. hirtum, and Poliomintha longiflora have higher ORAC and phenolic contents as compared to other culinary herbs. The ORAC values and total phenolic content for the culinary herbs ranged from 2.35 to 92.18 micromol of TE/g of fresh weight and 0.26 to 17.51 mg of GAE/g of fresh weight, respectively. These also were much higher than values found in the medicinal herbs. The medicinal herbs with the highest ORAC values were Catharanthus roseus, Thymus vulgaris, Hypericum perforatum, and Artemisia annua. A linear relationship existed between ORAC values and total phenolic contents of the medicinal herbs (R = 0.919) and culinary herbs (R = 0.986). High-performance liquid chromatography (HPLC) coupled with diode-array detection was used to identify and quantify the phenolic compounds in selected herbs. Among the identified phenolic compounds, rosmarinic acid was the predominant phenolic compound in Salvia officinalis, Thymus vulgaris, Origanum x majoricum, and P. longiflora, whereas quercetin-3-O-rhamnosyl-(1 --> 2)-rhamnosyl-(1 --> 6)-glucoside and kaempferol-3-O-rhamnosyl-(1 --> 2)-rhamnosyl-(1 --> 6)-glucoside were predominant phenolic compounds in Ginkgo biloba leaves.

In determining aggregate stability, known amounts of some size fraction of aggregates are commonly subjected to a disintegrating force designed to simulate some important field phenomenon. The amount of disintegration is measured by determining the portion (by weight) of the aggregates that is broken down into aggregates and primary particles smaller than some selected size. This determination is usually made by sieving or sedimentation. This chapter discusses the principles underlying the development of methods for measuring aggregate stability and size distribution. Multiple-sieve techniques give data on the amount of aggregates in each of several size groupings. To evaluate treatments or to rank soils, a single parameter to represent a soil sample is necessary. Aggregate size distribution often is measured to gain information on the size of the aggregates as they exist in the mass of soil. This requires a wetting treatment that will cause as little disintegration as possible.

We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.

Hydrologic analyses often involve the evaluation of soil water infiltration, conductivity, storage, and plant‐water relationships. To define the hydrologic soil water effects requires estimating soil water characteristics for water potential and hydraulic conductivity using soil variables such as texture, organic matter (OM), and structure. Field or laboratory measurements are difficult, costly, and often impractical for many hydrologic analyses. Statistical correlations between soil texture, soil water potential, and hydraulic conductivity can provide estimates sufficiently accurate for many analyses and decisions. This study developed new soil water characteristic equations from the currently available USDA soil database using only the readily available variables of soil texture and OM. These equations are similar to those previously reported by Saxton et al. but include more variables and application range. They were combined with previously reported relationships for tensions and conductivities and the effects of density, gravel, and salinity to form a comprehensive predictive system of soil water characteristics for agricultural water management and hydrologic analyses. Verification was performed using independent data sets for a wide range of soil textures. The predictive system was programmed for a graphical computerized model to provide easy application and rapid solutions and is available at http://hydrolab.arsusda.gov/soilwater/Index.htm

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Abstract A rapid procedure for determining cellwall constituents of plants consists of the determination of the fiber insoluble in neutral detergent and is applicable to all feedstuffs. The standardization of the method is based on a nutritional concept which defines fiber as insoluble vegetable matter which is indigestible by proteolytic and diastatic enzymes and which cannot be utilized except by microbial fermentation in the digestive tracts of animals.

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.

SUMMARY: Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. AVAILABILITY: http://www.maizegenetics.net/GAPIT. CONTACT: zhiwu.zhang@cornell.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.