1,818,193 research outputs found
USDA-ARS bagrada bug transcriptome
No full textUSDA-ARS bagrada bug (Bagrada hilaris) transcriptome: three bioreps of egg mass, 2nd & 4th instar nymphs, and male & female adults
USDA-RDQMA
No full textThe goal of this project is to develop a general methodology for incorporating bacterial phylogenetics based on WGS into predictive models for infectious diseases using transformative and interdisciplinary research incorporating ecology, economics, molecular biology, and epidemiology. These methods and models will be applied towards better understanding the principles and dynamics governing transmission of mycobacterial infection.This work was supported by the USDA-NIFA AFRI [grant number # 2014-67015-2240] as part of the joint USDA-NSF-NIH-BBSRC-BSF Ecology and Evolution of Infectious Diseases program
DOES THE MARKET ANTICIPATE SMOOTHING IN USDA CROP PRODUCTION FORECASTS?
No full textThis study examines whether market participants anticipate the predictable component in USDA revisions of corn and soybean production forecasts during 1970/71 through 2003/04 marketing years. The analysis revealed that markets consistently under-predicted October corn production revisions and over-predicted September soybean production revisions. These biases may be attributable to inefficient use of information about smoothing in USDA revisions. In all other cases market analysts seemed to be aware of USDA smoothing practices and generally efficiently incorporated this information into their own forecasts.Marketing,
USDA PRODUCTION FORECASTS FOR PORK, BEEF, AND BROILERS: AN EVALUATION
No full textOne-step-ahead forecasts of quarterly beef, pork, and poultry production are examined and evaluated based on traditional criteria for optimality-efficiency and unbiasedness-as well as their performance versus a univariate time-series model. However, traditional regression methodology for evaluating forecasts is avoided due to interpretive issues. Instead, an empirical framework focusing on forecast errors in employed. Results suggest USDA forecasts are unbiased, but generally not efficient. That is, they do not fully incorporate the information contained in past forecasts. Moreover, USDAÂ’'s predictions do not encompass all the information contained in forecasts generated by simple time-series models. Thus, practitioners who use the USDA forecasts may want to supplement them with time-series forecasts.Agribusiness,
AN EVALUATION OF CROP FORECAST ACCURACY FOR CORN AND SOYBEANS: USDA AND PRIVATE INFORMATION SERVICES
No full textUsing 1971-2000 data, we examine the accuracy of corn and soybean production forecasts provided by the USDA and two private services. All agencies improved their forecasts as the harvest progressed, and forecast errors across the agencies were highly correlated. Relative accuracy varied by crop and month. In corn, USDA 's forecasts ranked as most accurate in all periods except in August during recent times, and improved more markedly as harvest progressed. In soybeans, forecast errors were very similar with the private agencies ranking as most accurate in August and September and making largest relative improvements in August during recent times. The USDA provided the most accurate October and November forecasts.Crop Production/Industries,
USDA-ARS-FAESRU 14Jul2017 Salmonella enterica sequencing
No full textSalmonella isolates were recovered from mink feces and feed samples from a mink farm in the United States
USDA-ARS antibiosis-associated Serratia marcescens
No full textSerratia marcescens strain associated with antibiosis in pupal cells of the pecan weevil, Curculio carya
USDA-FSIS: Isolated strains of Campylobacter spp. genome sequencing
No full textWhole genome sequencing of Campylobacter isolate
USDA-ARS-GBRU/itsxpress: v1.7.2
No full text<p>This release fixes an issue here <a href="https://github.com/USDA-ARS-GBRU/itsxpress/issues/8">https://github.com/USDA-ARS-GBRU/itsxpress/issues/8</a></p>
What Can we Learn from our Mistakes? Evaluating the Benefits of Correcting Inefficiencies in USDA Cotton Forecasts.
No full textThis study investigated the magnitude of forecast improvements resulting from correction of inefficiencies in USDA cotton forecasts over 1999/00 to 2008/09 marketing years. The aspects of forecast performance included in this study were 1) bias and trends in bias, 2) correlation between forecast error and forecast level, 3) autocorrelation in forecast errors, 4) correlation in forecast revisions. Overall the results of this study demonstrated that some corrections of forecast inefficiencies, such as correction of correlation of error with forecast levels and correlation of error with previous year’s error resulted in consistent improvement of USDA cotton forecasts, while correction for correlation in forecast revisions did not benefit the forecasts. Correction for bias yielded mixed results likely because USDA has already been applying those corrections to some of the categories and thus our analysis resulted in over-correcting. The framework developed in this study can be used by USDA and other agencies to monitor and improve the performance of their forecasts.Commodity, Forecast evaluation, Fixed-event forecasts, Government forecasting, Forecast improvement, Agribusiness, Demand and Price Analysis, E37, E3, Q13,
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