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Available Time to Plant and Harvest Peanuts
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Farm Data: Ownership and Protections
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Legal and Economic Implications of Farm Data: Ownership and Possible Protections
In: Drake Journal of Agricultural Law, Forthcoming
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Group Assessment and Structured Learning
In: Journal of visual impairment & blindness: JVIB, Band 74, Heft 6, S. 225-228
ISSN: 1559-1476
Describes two new techniques used in a residential program for blind, multiply handicapped young adults. The first, Goldstein's Structured Learning Therapy, is a social skills training technique. The second, group assessment, is a form of "program evaluation on a shoestring" that enables professionals to plan programs based on client needs. Both can be applied in small programs with existing personnel.
Big Data in Agriculture: A Challenge for the Future
In: Applied economic perspectives and policy, Band 40, Heft 1, S. 79-96
ISSN: 2040-5804
AbstractThis article examines the challenge and opportunities of Big Data, and concludes that these technologies will lead to relevant analysis at every stage of the agricultural value chain. Big Data is defined by several characteristics beyond size, particularly, the volume, velocity, variety, and veracity of the data. We discuss a set of analytical techniques that are increasingly relevant to our profession as one addresses these issues. Ultimately, we resolve that agricultural and applied economists are uniquely positioned to contribute to the research and outreach agenda on Big Data. We believe there are relevant policy, farm management, supply chain, consumer demand, and sustainability issues where our profession can make major contributions. The authors are thankful to the anonymous reviewers and editor Craig Gundersen for helpful comments. Support was provided by the Mississippi Agricultural and Forestry Experiment Station Special Research Initiative.
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Development of high-speed camera hardware and software package to evaluate real-time electric seed meter accuracy of a variable rate planter
In: Computers and Electronics in Agriculture, Band 142, S. 314-325
Spatial econometric analysis of a field-scale site-specific nitrogen fertilizer experiment on wheat (Triticum aestuvum L.) yield and quality
In: Computers and Electronics in Agriculture, Band 74, Heft 1, S. 73-79
Three Digital Agriculture Problems in Cotton Solved by Distributed Ledger Technology
In: Applied economic perspectives and policy, Band 44, Heft 1, S. 237-252
ISSN: 2040-5804
AbstractDistributed ledger technology applied to Big Data in agriculture presents challenges and opportunities. Opportunities exist to solve decades‐old farm data management problems. Real‐world examples of applying distributed ledger technology to current farm data problems in cotton include (1) yield monitor data quality assurance, (2) sustainability metrics and resource tracking of cotton lint quality data from ginner back to subfield locations, and (3) increasing supply chain coordination by providing more information to warehouse managers. The culmination of the discussion across three aspects of cotton production data is of interest to farmers, researchers, policy makers, and consumers.