United States Department of Agriculture
  • Washington, D.C., District of Columbia, United States
Recent publications
Cattle graze approximately 30% of global land, making their interactions with Earth's social and ecological systems of critical importance. Cattle have experienced a long process of evolution and domestication. Certain breeds are more adapted to specific environments, differentially affecting those breeds' impact on the environment, their interaction with ecosystems experiencing climate change impacts, and their capacity to provide goods and landscape management services. Emerging evidence suggests that, compared to more artificially selected conventional breeds, some less specialized, or ‘heritage’ beef cattle breeds exhibit unique foraging behaviors that could support desired outcomes such as biodiversity or climate change adaptation. We provide a novel, systematic characterization of breed-based behavioral differences to assist researchers and beef producers in selecting breed-based management strategies for achieving adaptation goals. We conducted a systematic search of studies that compared beef cattle breeds for behavioral trends, and found 54 studies conducted between 1966 and present day, located in 9 of the 14 major terrestrial world biomes, with 60 beef or dual-purpose breeds represented. We created a typology of the studies with respect to decade, continent, breed provenance (Continental, Criollo, Hybrid, B. indicus, Mediterranean, Sanga, British Isles), breed selection intensity (heritage, conventional, hybrid), biome, study intent, and whether breeds met desired outcomes described by the study authors. Most studies (69%) were conducted in arid rangeland settings in developed nations where researchers sought to minimize the environmental impacts of beef production. In comparisons of grazing behavior of heritage versus conventional types (n = 25 studies), and hybrid versus conventional types (n = 18 studies), heritage and hybrid displayed more adapted traits (e.g., better grazing distribution) in 88% and 78% of the studies, respectively. No differences were found in grazing behaviors among most studies wherein heritage breeds were compared to other heritage breeds or conventional with conventional (n = 6 and 15 studies, respectively). In the subset of studies coded with the intent of “foraging behavior,” heritage types traveled faster across a range of pasture sizes, suggesting a lighter environmental footprint and adaptive capacity to heat impacts. Overall, our review suggests that locally derived breeds display grazing behaviors that demonstrate adaptation to their respective native environments and may help producers meet production goals in similar environments. We conclude that breeds with more natural selection tend to exhibit less rigid grazing behaviors, which is a necessary coping strategy in variable climates and locales with heterogeneous forage availability, both of which are increasingly common scenarios caused by climate change.
Plants compete for light partly by over-producing chlorophyll in leaves. The resulting high light absorption is an effective strategy for out competing neighbors in mixed communities, but it prevents light transmission to lower leaves and limits photosynthesis in dense agricultural canopies. We used a CRISPR/Cas9-mediated approach to engineer rice plants with truncated light-harvesting antenna (TLA) via knockout mutations to individual antenna assembly component genes CpSRP43, CpSRP54a, and its paralog, CpSRP54b. We compared the photosynthetic contributions of these components in rice by studying the growth rates of whole plants, quantum yield of photosynthesis, chlorophyll density and distribution, and phenotypic abnormalities. Additionally, we investigated a Poales-specific duplication of CpSRP54. The Poales are an important family that includes staple crops such as rice, wheat, corn, millet, and sorghum. Mutations in any of these three genes involved in antenna assembly decreased chlorophyll content and light absorption and increased photosynthesis per photon absorbed (quantum yield). These results have significant implications for the improvement of high leaf-area-index crop monocultures.
Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4) is a soil-borne fungal pathogen threatening US cotton production. The objective of this study was to develop a reliable and efficient method to evaluate cotton for FOV4 resistance based on taproot rot during seed germination through five growth chamber tests and two greenhouse tests. Seeds from eight cotton cultivars (Set 1) were germinated in a paper towel for 6 days, and taproots were inoculated with a FOV4 conidial suspension using three inoculation methods, i.e., taproot dipping, taproot wounding, and paper towel drenching, in addition to seed soaking before germination. Taproot rot-based disease incidence (DI) and disease severity rating (DSR), seed germination percentage (SGP), and plant fresh weight (PFW) were measured 7 days after inoculation. Taproot dipping was the most efficient and reliable evaluation method. SGP and PFW were not significantly correlated with DI and DSR, making them inappropriate to use in resistance evaluation. Pima DP 359 RF and PHY 881 RF were the most resistant with the lowest root rot. The taproot dipping method was repeated in another test and confirmed in two tests using another set of eight cultivars (Set 2). The taproot rot-based DSR at germination was significantly correlated with DSR at the seedling stage in the greenhouse in both sets and with previous results in seedling mortality in the greenhouse and field in Set 2. The results suggest that the response to FOV4 infections at the seed germination stage is overall congruent with that at the seedling stage.
Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract
Whitebark pine ( Pinus albicaulis ) forest ecosystems in California are diverse and unique, yet their current status and condition are uncertain. Using a combination of geospatial and field plot data, we assessed patterns in the structure, composition, and health of whitebark pine ecosystems on national forests throughout the state of California to evaluate potential signs of declining ecosystem integrity. We found whitebark pine ecosystems to be structurally, compositionally, and functionally distinct among subregions of California, and all subregions displayed some evidence of declining ecological integrity. Whitebark pine forests in northern California exhibited signs of greater stand densification (Cascade-Klamath), potential encroachment by shade-tolerant conifer species (Cascade-Klamath and Warner Mountains), and increased tree mortality associated with mountain pine beetle outbreaks (Warner Mountains) than elsewhere in California. Whitebark pine stands in the Sierra Nevada showed signs of stand densification (central Sierra) and localized mountain pine beetle outbreaks (southern Sierra east). Notwithstanding these negative signs, much of the state’s whitebark pine ecosystems on national forestlands appear to be relatively healthy and intact compared to more northern latitudes. Active management may be required to restore whitebark pine ecosystems on national forests in California with declining integrity, including stands experiencing substantial stand densification, encroachment by shade-tolerant conifers, and mountain pine beetle outbreaks.
Introduction Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. Methods To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. Results Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. Conclusion We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.
Field studies of hyporheic exchange in mountain systems are often conducted using short study reaches and a limited number of observations. It is common practice to assume these study reaches represent hyporheic exchange at larger scales or different sites and to infer general relationships among potential causal mechanisms from the limited number of observations. However, these assumptions of representativeness are rarely tested. In this study, we develop numerical models from four segments of mountain streams in different geomorphologic settings and extract shorter reaches to test how representative exchange metrics are in shorter reaches compared to their reference segments. We also map the locations of the representative reaches to determine if a pattern exists based on location. Finally, we compare variance of these shorter within‐site reaches to 29 additional reaches across the same basin to understand the impacts of inferring causal mechanisms, for example, the expectation that wide and narrow valley bottoms will yield different hyporheic exchange patterns. Our results show that the location and length strategy of the study reach must be considered before assuming an exchange metric to be representative of anything other than the exact segment studied. Further, it is necessary to quantify within and between site variations before making causal inferences based on observable characteristics, such as valley width or stream morphology. Our findings have implications for future field practices and how those practices are translated into models.
Chiggers are larval ectoparasites of the Trombiculidae that can transmit pathogens to their hosts. In this study, chiggers collected from birds in Brazil were morphologically identified as Blankaartia sinnamaryi, Eutrombicula batatas, Eutrombicula daemoni, Eutrombicula goeldii, Eutrombicula tinami, and Parasecia gilbertoi. For these specimens, a beginning attempt at molecular identification were also provided, as well as, were genetically screened to detect bacterial pathogens. The species B. sinnamaryi and E. tinami were positive for Rickettsia felis-like and 'Candidatus Rickettsia colombianensi'-like, respectively. For the other agents (Anaplasmataceae, Borrelia spp. and Orientia tsutsugamushi), the tests were negative. This is the first report of 'Ca. R. colombianensi'-like and the second record of R. felis-like in chigger collected on birds from Brazil.
Maternal effects are an important source of phenotypic variance, whereby females influence offspring developmental trajectory beyond direct genetic contributions, often in response to changing environmental conditions. However, relatively little is known about the mechanisms by which maternal experience is translated into molecular signals that shape offspring development. One such signal may be maternal RNA transcripts (mRNAs and miRNAs) deposited into maturing oocytes. These regulate the earliest stages of development of all animals, but are understudied in most insects. Here we investigated the effects of female internal (body condition) and external (time of season) environmental conditions on maternal RNA in the maturing oocytes and 24-h-old eggs (24-h eggs) of alfalfa leafcutting bees. Using gene expression and WGCNA analysis, we found that females adjust the quantity of mRNAs related to protein phosphorylation, transcriptional regulation, and nuclease activity deposited into maturing oocytes in response to both poor body condition and shorter day lengths that accompany the late season. However, the magnitude of these changes was higher for time of season. Females also adjusted miRNA deposition in response to seasonal changes, but not body condition. We did not observe significant changes in maternal RNAs in response to either body condition or time of season in 24-h eggs, which were past the maternal-to-zygotic transition. Our results suggest that females adjust the RNA transcripts they provide for offspring to regulate development in response to both internal and external environmental cues. Variation in maternal RNAs may, therefore, be important for regulating offspring phenotype in response to environmental change.
Introduction Childhood obesity is associated with adult obesity, which is a risk factor for chronic diseases. Obesity, as an environmental cue, alters circadian rhythms. The hypothesis of this study was that consumption of a high-fat diet alters metabolic rhythms in pubertal mice. Methods Weanling female C57BL/6NHsd mice were fed a standard AIN93G diet or a high-fat diet (HFD) for 3 weeks. Livers were collected from six-week-old mice every 4 h over a period of 48 h for transcriptome analysis. Results and discussion The HFD altered rhythmicity of differentially rhythmic transcripts in liver. Specifically, the HFD elevated expression of circadian genes Clock , Per1 , and Cry1 and genes encoding lipid metabolism Fads1 and Fads2 , while decreased expression of circadian genes Bmal1 and Per2 and lipid metabolism genes Acaca , Fasn , and Scd1 . Hierarchical clustering analysis of differential expression genes showed that the HFD-mediated metabolic disturbance was most active in the dark phase, ranging from Zeitgeber time 16 to 20. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis of differentially expressed genes showed that the HFD up-regulated signaling pathways related to fatty acid and lipid metabolism, steroid and steroid hormone biosynthesis, amino acid metabolism and protein processing in the endoplasmic reticulum, glutathione metabolism, and ascorbate and aldarate metabolism in the dark phase. Down-regulations included MAPK pathway, lipolysis in adipocytes, Ras and Rap1 pathways, and pathways related to focal adhesion, cell adhesion molecules, and extracellular matrix-receptor interaction. In summary, the HFD altered metabolic rhythms in pubertal mice with the greatest alterations in the dark phase. These alterations may disrupt metabolic homeostasis in puberty and lead to metabolic disorders.
In insect-pollinated plants, the foraging behavior of pollinators affects their pattern of movement. If distinct bee species vary in their foraging behaviors, different models may best describe their movement. In this study, we quantified and compared the fine scale movement of three bee species foraging on patches of Medicago sativa. Bee movement was described using distances and directions traveled between consecutive racemes. Bumble bees and honey bees traveled shorter distances after visiting many flowers on a raceme, while the distance traveled by leafcutting bees was independent of flower number. Transition matrices and vectors were calculated for bumble bees and honey bees to reflect their directionality of movement within foraging bouts; leafcutting bees were as likely to move in any direction. Bee species varied in their foraging behaviors, and for each bee species, we tested four movement models that differed in how distances and directions were selected, and identified the model that best explained the movement data. The fine-scale, within-patch movement of bees could not always be explained by a random movement model, and a general model of movement could not be applied to all bee species.
Cassava brown streak disease (CBSD) is a major threat to food security in East and central Africa. Breeding for resistance against CBSD is the most economical and sustainable way of addressing this challenge. This study seeks to assess the (1) performance of CBSD incidence and severity; (2) identify genomic regions associated with CBSD traits and (3) candidate genes in the regions of interest, in the Cycle 2 population of the National Crops Resources Research Institute. A total of 302 diverse clones were screened, revealing that CBSD incidence across growing seasons was 44%. Severity scores for both foliar and root symptoms ranged from 1.28 to 1.99 and 1.75 to 2.28, respectively across seasons. Broad sense heritability ranged from low to high (0.15 - 0.96), while narrow sense heritability ranged from low to moderate (0.03 - 0.61). Five QTLs, explaining approximately 19% phenotypic variation were identified for CBSD severity at 3 months after planting on chromosomes 1, 13, and 18 in the univariate GWAS analysis. Multivariate GWAS analysis identified 17 QTLs that were consistent with the univariate analysis including additional QTLs on chromosome 6. Seventy-seven genes were identified in these regions with functions such as catalytic activity, ATP-dependent activity, binding, response to stimulus, translation regulator activity, transporter activity among others. These results suggest variation in virulence in the C2 population, largely due to genetics and annotated genes in these QTLs regions may play critical roles in virus initiation and replication, thus increasing susceptibility to CBSD.
Togni reagent II is a synthetically useful hypervalent iodine reagent for direct trifluoromethylation. Herein, we report a new reaction of Togni reagent II: α-C–H ester-functionalization of tertiary amides. This α-acyloxylation reaction proceeds smoothly in the presence of a mild base at 25–30 oC and produces moderate-to-high yields. This newly discovered reaction adds another dimension to the utility of Togni reagent II and provides direct and easy access to α-acyloxy amides and α-hydroxy amides.
The valorization of lignin into value-added products by oxidative conversion is a widely studied strategy. However, in many cases, this approach has limited scope for integration into industrial processes. The objective of our work is to maximize overall lignin utilization to produce diverse value-added products with a focus on integration in the existing industrial pulp and paper processes. The utilization of the sequential oxidation strategy using oxygen and ozone resulted in kraft lignin with a marked improvement in carboxyl content and also allowed the formation of vanillin and vanillic acid in the oxygen stage. The sequentially oxidized lignin (OxL-COOH) was then cured with poly(ethylene glycol) diglycidyl ether (PEG-epoxy) to form high-lignin-content (>48 wt %) vitrimers with high thermal stability, fast relaxation, swelling, and self-healing due to the presence of bond-exchangeable cross-linked networks. Overall, this study provides a novel approach for the multidimensional valorization of lignin and demonstrates an integrated approach for kraft lignin valorization in the pulp and paper industry.
There are four major soilborne pathogens of strawberries in California, but their distribution and prevalence in the Watsonville-Salinas production district are unknown. To fill this knowledge gap, 74 symptomatic strawberry plant samples were collected from 69 fields in the Watsonville-Salinas growing district between 11 August and 15 October 2021. Each sample consisted of eight plants exhibiting moderate to severe plant collapse. Crown tissue from each plant was excised and pooled for recombinase polymerase amplification (RPA) to detect Macrophomina phaseolina, Fusarium oxysporum f. sp. fragariae, Verticillium dahliae, and Phytophthora spp. Root, petiole and crown tissue from plant samples in which no pathogens were detected by RPA was plated on semi-selective media to verify the absence of the four pathogens and screen for other pathogenic fungi. At least one of the four pathogens was detected in 55 of the 74 samples (74.3%). All four of the major soilborne pathogens are prevalent in this growing district, as F. oxysporum f. sp. fragariae, M. phaseolina, Phytophthora spp. and V. dahliae were detected in 23 samples (31.1%), 22 samples (29.7%), 18 samples (24.3%), and 16 samples (22.0%), respectively. No strong associations were found between the pathogens and growing practices.
Genomic selection has been promising in situations where phenotypic assessments are expensive, laborious, and/or inefficient. This work evaluated the efficiency of genomic prediction methods combined with genetic models in clone and parent selection with the goal of increasing fresh root yield, dry root yield, as well as dry matter content in cassava roots. The bias and predictive ability of the combinations of prediction methods Genomic Best Linear Unbiased Prediction (G-BLUP), Bayes B, Bayes Cπ, and Reproducing Kernel Hilbert Spaces with additive and additive-dominant genetic models were estimated. Fresh and dry root yield exhibited predominantly dominant heritability, while dry matter content exhibited predominantly additive heritability. The combination of prediction methods and genetic models did not show significant differences in the predictive ability for dry matter content. On the other hand, the prediction methods with additive-dominant genetic models had significantly higher predictive ability than the additive genetic models for fresh and dry root yield, allowing higher genetic gains in clone selection. However, higher predictive ability for genotypic values did not result in differences in breeding value predictions between additive and additive-dominant genetic models. G-BLUP with the classical additive-dominant genetic model had the best predictive ability and bias estimates for fresh and dry root yield. For dry matter content, the highest predictive ability was obtained by G-BLUP with the additive genetic model. Dry matter content exhibited the highest heritability, predictive ability, and bias estimates compared with other traits. The prediction methods showed similar selection gains with approximately 67% of the phenotypic selection gain. By shortening the breeding cycle time by 40%, genomic selection may overcome phenotypic selection by 10%, 13%, and 18% for fresh root yield, dry root yield, and dry matter content, respectively, with a selection proportion of 15%. The most suitable genetic model for each trait allows for genomic selection optimization in cassava with high selection gains, thereby accelerating the release of new varieties.
Wood packaging material (WPM) used in international trade, such as crating and pallets, is recognized as a high-risk pathway for the introduction of bark- and wood-infesting insects (borers). The International Standards for Phytosanitary Measures No. 15 (ISPM 15), which sets treatment requirements for WPM, was adopted in 2002. The United States (US) implemented ISPM 15 during 2005–2006. We used 2003–2020 AQIM (Agriculture Quarantine Inspection Monitoring, conducted by USDA APHIS) data, based on standard random sampling, to compare pre-ISPM 15 borer detection rates in WPM entering the US (2003–2004) to detection rates during 2005–2006 (implementation phase), 2007–2009 (post-ISPM 15 when bark was not regulated) and 2010–2020 (post-ISPM 15 when bark was regulated). We examined borer detection rates overall for all AQIM WPM records and individually for the three main cargo survey programs within AQIM [Italian tiles, perishables, and general WPM (GWPM) for any WPM associated with containerized maritime imports], and individually for three major US trading partners (China, Italy, and Mexico). During 2003–2020, wood borers were detected in 180 of 87,571 consignments with WPM (0.21%). When compared to 2003–2004 (detection rate of 0.34%), detection rates fell 61% during 2005–2006, 47% during 2007–2009, and 36% during 2010–2020. Similar declines occurred for WPM associated with Italian tiles and perishables. However, for GWPM there was no significant reduction post-ISPM 15. WPM infestation rates were reduced significantly during various post-ISPM 15 periods for Italy and Mexico, but not for China. Seven families or subfamilies of borers were recorded in WPM with Cerambycidae and Scolytinae being most frequent. The incidence of WPM with bark fell significantly after the 2009 change to ISPM 15 that required debarked WPM. We discuss several factors that could influence the apparent effectiveness of ISPM 15.
Pasture-based and grass-fed branding are often associated with consumer perceptions of improved human health, environmental performance and animal welfare. Here, to examine the impacts of dairy production in detail, we contrasted global observational (n = 156) data for nitrogen and phosphorus losses from land by the duration of outdoor livestock grazing in confined, grazed and hybrid systems. Observational nitrogen losses for confined systems were lowest on a productivity—but not area—basis. No differences were noted for phosphorus losses between the systems. Modelling of the three dairy systems in New Zealand, the United States and the Netherlands yielded similar results. We found insufficient evidence that grazed dairy systems have lower nutrient losses than confined ones, but trade-offs exist between systems at farm scale. The use of a hybrid system may allow for uniform distribution of stored excreta, controlled dietary intake, high productivity and mitigation of animal welfare issues arising from climatic extremes.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
3,334 members
David P Horvath
  • Agricultural Research Service (ARS)
Gary L Peterson
  • Agricultural Research Service (ARS)
Steven Skoda
  • Agricultural Research Service (ARS)
Debra P C Peters
  • Agricultural Research Service (ARS)
Komala Arsi
  • Agricultural Research Service (ARS)
1400 Independence Ave., S.W. , 20250 , Washington, D.C., District of Columbia, United States
Head of institution
Secretary of Agriculture
(202) 720-2791