Agricultural Statistics


Book Description




Agricultural Statistics 2020


Book Description

Agricultural Statistics is published each year to meet the diverse need for a reliable reference book on agricultural production, supplies, consumption, facilities, costs, and returns. Its tables of annual data cover a wide variety of facts in forms suited to most common use. The estimates for crops, livestock, and poultry made by the U.S. Department of Agriculture are prepared mainly to give timely current state and national totals and averages. They are based on data obtained by sample surveys of farmers and of people who do business with farmers. The survey data are supplemented by information from the Census of Agriculture taken every five years. Being estimates, they are subject to revision as more data become available from commercial or government sources. Unless otherwise indicated, the totals for the United States shown in the various tables on area, production, numbers, price, value, supplies, and disposition are based on official Department estimates. They exclude states for which no official estimates are compiled. Extensive data includes statistics for the following: -Grain and Feed -Cotton, Tobacco, Sugar Crops, and Honey -Oilseeds, Fats, and Oils -Vegetables and Melons -Hay, Seeds, and Minor Field Crops -Cattle, Hogs, and Sheep -Dairy and Poultry -Insurance, Credit & Cooperatives -Agricultural Conservation & Forestry -Consumption & Family Living -Fertilizers & Pesticides Miscellaneous Agricultural Statistics such as Foreign Agricultural Trade Statistics including exports, fisheries and more. Professionals in the following fields to include farmers, ranchers, soil conservationists, surveyors, agricultural economist consultants, livestock manufacturers, livestock feedlot operators, food distributors, animal scientists, food chemists, food brokers, farm and land appraisers (and more) may have the greatest interest in this volume.










Local Food Systems; Concepts, Impacts, and Issues


Book Description

This comprehensive overview of local food systems explores alternative definitions of local food, estimates market size and reach, describes the characteristics of local consumers and producers, and examines early indications of the economic and health impacts of local food systems. Defining ¿local¿ based on marketing arrangements, such as farmers selling directly to consumers at regional farmers¿ markets or to schools, is well recognized. Statistics suggest that local food markets account for a small, but growing, share of U.S. agricultural production. For smaller farms, direct marketing to consumers accounts for a higher percentage of their sales than for larger farms. Charts and tables.




Wisconsin Crop Progress


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Statistical Rethinking


Book Description

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.







Agriculture, Forestry, and Fishing Research at NIOSH


Book Description

The agriculture, forestry, and fishing sectors are the cornerstone of industries that produce food, fiber, and biofuel. The National Institute for Occupational Safety and Health (NIOSH) conducts research in order to improve worker safety and health in these sectors. This National Research Council book reviews the NIOSH Agriculture, Forestry, and Fishing Program to evaluate the 1) relevance of its work to improvements in occupational safety and health and 2) the impact of research in reducing workplace illnesses and injuries. The assessment reveals that the program has made meaningful contributions to improving worker safety and health in these fields. To enhance the relevance and impact of its work and fulfill its mission, the NIOSH Agriculture, Forestry, and Fishing Program should provide national leadership, coordination of research, and activities to transfer findings, technologies, and information into practice. The program will also benefit from establishing strategic goals and implementing a comprehensive surveillance system in order to better identify and track worker populations at risk.




Agricultural Internet of Things and Decision Support for Precision Smart Farming


Book Description

Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies. - Presents the science behind smart technologies for agricultural management - Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space - Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable