United States Department of Agriculture

Journal Article A Method of Computing the Effectiveness of an Insecticide Get access W. S. Abbott W. S. Abbott Bureau of Entomology, United States Department of Agriculture Search for other works by this author on: Oxford Academic PubMed Google Scholar Journal of Economic Entomology, Volume 18, Issue 2, 1 April 1925, Pages 265–267, https://doi.org/10.1093/jee/18.2.265a Published: 01 April 1925

Watershed models are powerful tools for simulating the effect of watershed processes and management on soil and water resources. However, no comprehensive guidance is available to facilitate model evaluation in terms of the accuracy of simulated data compared to measured flow and constituent values. Thus, the objectives of this research were to: (1) determine recommended model evaluation techniques (statistical and graphical), (2) review reported ranges of values and corresponding performance ratings for the recommended statistics, and (3) establish guidelines for model evaluation based on the review results and project-specific considerations; all of these objectives focus on simulation of streamflow and transport of sediment and nutrients. These objectives were achieved with a thorough review of relevant literature on model application and recommended model evaluation methods. Based on this analysis, we recommend that three quantitative statistics, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR), in addition to the graphical techniques, be used in model evaluation. The following model evaluation performance ratings were established for each recommended statistic. In general, model simulation can be judged as satisfactory if NSE > 0.50 and RSR < 0.70, and if PBIAS + 25% for streamflow, PBIAS + 55% for sediment, and PBIAS + 70% for N and P. For PBIAS, constituent-specific performance ratings were determined based on uncertainty of measured data. Additional considerations related to model evaluation guidelines are also discussed. These considerations include: single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude. A case study illustrating the application of the model evaluation guidelines is also provided.

Abstract Summary: Association analyses that exploit the natural diversity of a genome to map at very high resolutions are becoming increasingly important. In most studies, however, researchers must contend with the confounding effects of both population and family structure. TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) implements general linear model and mixed linear model approaches for controlling population and family structure. For result interpretation, the program allows for linkage disequilibrium statistics to be calculated and visualized graphically. Database browsing and data importation is facilitated by integrated middleware. Other features include analyzing insertions/deletions, calculating diversity statistics, integration of phenotypic and genotypic data, imputing missing data and calculating principal components. Availability: The TASSEL executable, user manual, example data sets and tutorial document are freely available at http://www.maizegenetics.net/tassel. The source code for TASSEL can be found at http://sourceforge.net/projects/tassel. Contact: pjb39@cornell.edu

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.

This paper reports the genome sequence of domesticated tomato, a major crop plant, and a draft sequence for its closest wild relative; comparative genomics reveal very little divergence between the two genomes but some important differences with the potato genome, another important food crop in the genus Solanum. Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera1 and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium2, and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness.

Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the ∼730-megabase Sorghum bicolor (L.) Moench genome, placing ∼98% of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the ∼75% larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidization ∼70 million years ago, most duplicated gene sets lost one member before the sorghum–rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24% of genes are grass-specific and 7% are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum’s drought tolerance. The Sorghum bicolor genome sequence is published this week. Sorghum is a cereal grown widely as food, animal feed, fibre and fuel. Tolerant to hot, dry conditions, it is a staple for large populations in the West African Sahel region. Comparisons of the genome with those of maize and rice shed light on the evolution of grasses and of C4 photosynthesis, which is particularly efficient at assimilating carbon at high temperatures. In addition, protein coding genes and miRNAs that could contribute to sorghum's drought tolerance may also be found. Sorghum yield improvement has lagged behind that of other crops and the availability of the genome sequence could provide a vital boost to work on its improvement. Sorghum is an African grass that is grown for food, animal feed and fuel. The current paper presents an initial analysis of the ∼730 megabase genome of Sorghum bicolor. Genome analysis and its comparison with maize and rice shed light on grass genome evolution and also provide insights into the evolution of C4 photosynthesis, as well as protein coding genes and miRNAs that might contribute to sorghum's drought tolerance.

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.

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 analysis of color is frequently an important consideration when determining the efficacy of a variety of postharvest treatments. Consumers can easily be influenced by preconceived ideas of how a particular fruit or vegetable should appear, and marketers often attempt to improve upon what nature has painted. In spite of the significance of color in our work, however, many researchers continue to analyze this characteristic inappropriately. The confusion that results is unnecessary; easily computed and readily understood measures are available to clarify color descriptions for researchers and marketers alike.

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.

The first public product of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is its Conceptual Framework. This conceptual and analytical tool, presented here in detail, will underpin all IPBES functions and provide structure and comparability to the syntheses that IPBES will produce at different spatial scales, on different themes, and in different regions. Salient innovative aspects of the IPBES Conceptual Framework are its transparent and participatory construction process and its explicit consideration of diverse scientific disciplines, stakeholders, and knowledge systems, including indigenous and local knowledge. Because the focus on co-construction of integrative knowledge is shared by an increasing number of initiatives worldwide, this framework should be useful beyond IPBES, for the wider research and knowledge-policy communities working on the links between nature and people, such as natural, social and engineering scientists, policy-makers at different levels, and decision-makers in different sectors of society.

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.

Macrophage infiltration of white adipose tissue (WAT) is implicated in the metabolic complications of obesity. The precipitating event(s) and function(s) of macrophage infiltration into WAT are unknown. We demonstrate that >90% of all macrophages in WAT of obese mice and humans are localized to dead adipocytes, where they fuse to form syncytia that sequester and scavenge the residual "free" adipocyte lipid droplet and ultimately form multinucleate giant cells, a hallmark of chronic inflammation. Adipocyte death increases in obese (db/db) mice (30-fold) and humans and exhibits ultrastructural features of necrosis (but not apoptosis). These observations identify necrotic-like adipocyte death as a pathologic hallmark of obesity and suggest that scavenging of adipocyte debris is an important function of WAT macrophages in obese individuals. The frequency of adipocyte death is positively correlated with increased adipocyte size in obese mice and humans and in hormone-sensitive lipase-deficient (HSL-/-) mice, a model of adipocyte hypertrophy without increased adipose mass. WAT of HSL-/- mice exhibited a 15-fold increase in necrotic-like adipocyte death and formation of macrophage syncytia, coincident with increased tumor necrosis factor-alpha gene expression. These results provide a novel framework for understanding macrophage recruitment, function, and persistence in WAT of obese individuals.

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.

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.

The above-ground parts of plants are normally colonized by a variety of bacteria, yeasts, and fungi. While a few microbial species can be isolated from within plant tissues, many more are recovered from the surfaces of healthy plants. The aerial habitat colonized by these microbes is termed the

The U.S. Department of Energy (DOE) and the U.S. Department of Agriculture (USDA) are both strongly committed to expanding the role of biomass as an energy source. In particular, they support biomass fuels and products as a way to reduce the need for oil and gas imports; to support the growth of agriculture, forestry, and rural economies; and to foster major new domestic industries--biorefineries--making a variety of fuels, chemicals, and other products. As part of this effort, the Biomass R&D Technical Advisory Committee, a panel established by the Congress to guide the future direction of federally funded biomass R&D, envisioned a 30 percent replacement of the current U.S. petroleum consumption with biofuels by 2030. Biomass--all plant and plant-derived materials including animal manure, not just starch, sugar, oil crops already used for food and energy--has great potential to provide renewable energy for America's future. Biomass recently surpassed hydropower as the largest domestic source of renewable energy and currently provides over 3 percent of the total energy consumption in the United States. In addition to the many benefits common to renewable energy, biomass is particularly attractive because it is the only current renewable source of liquid transportation fuel. This, of course, makes it invaluable in reducing oil imports--one of our most pressing energy needs. A key question, however, is how large a role could biomass play in responding to the nation's energy demands. Assuming that economic and financial policies and advances in conversion technologies make biomass fuels and products more economically viable, could the biorefinery industry be large enough to have a significant impact on energy supply and oil imports? Any and all contributions are certainly needed, but would the biomass potential be sufficiently large to justify the necessary capital replacements in the fuels and automobile sectors? The purpose of this report is to determine whether the land resources of the United States are capable of producing a sustainable supply of biomass sufficient to displace 30 percent or more of the country's present petroleum consumption--the goal set by the Advisory Committee in their vision for biomass technologies. Accomplishing this goal would require approximately 1 billion dry tons of biomass feedstock per year.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of near‐infrared reflectance spectroscopy (NIRS) to predict diverse soil properties. Near‐infrared reflectance spectra, obtained from a Perstrop NIR Systems 6500 scanning monochromator (Foss NIRSystems, Silver Spring, MD), and 33 chemical, physical, and biochemical properties were studied for 802 soil samples collected from four Major Land Resource Areas (MLRAs). Calibrations were based on principal component regression (PCR) using the first derivatives of optical density [log(1/ R )] for the 1300‐ to 2500‐nm spectral range. Total C, total N, moisture, cation‐exchange capacity (CEC), 1.5 MPa water, basal respiration rate, sand, silt, and Mehlich III extractable Ca were successfully predicted by NIRS ( r 2 &gt; 0.80). Some Mehlich III extractable metals (Fe, K, Mg, Mn) and exchangeable cations (Ca, Mg, and K), sum of exchangeable bases, exchangeable acidity, clay, potentially mineralizable N, total respiration rate, biomass C, and pH were also estimated by NIRS but with less accuracy ( r 2 = 0.80∼0.50). The predicted results for aggregation (wt% &gt; 2, 1, 0.5, 0.25 mm, and macroaggregation) were not reliable ( r 2 = 0.46∼0.60). Mehlich III extractable Cu, P, and Zn, and exchangeable Na could not be predicted using the NIRS–PCR technique ( r 2 &lt; 0.50). The results indicate that NIRS can be used as a rapid analytical technique to simultaneously estimate several soil properties with acceptable accuracy in a very short time.