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Mooney, D.F
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Authors
Larson, J.A
Mooney, D.F
Roberts, R.K
English, B.C
Velandia, M
Mooney, D.F
Roberts, R.K
English, B.C
Larson, J.A
Lambert, D.M
Larkin, S.L
Marra, M.C
Rejesus, R
Martin, S.W
Paxton, K.W
Mishra, A
Wang, C
Segarra, E
Reeves, J.M
Harper, D.C
Lambert, D.M
English, B.C
Larson, J.A
Roberts, R.K
Velandia, M
Mooney, D.F
Larkin, S.L
Topics
Profitability, Sustainability, and Adoption
Precision Nutrient Management
Type
Oral
Year
2010
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Filter results3 paper(s) found.

1. A Computer Decision Aid For The Cotton Precision Agriculture Investment Decision

This article introduces the Cotton Precision Agriculture Investment Decision Aid (CPAIDA), a software decision tool for analyzing the precision agriculture investment decision. CPAIDA was developed to provide improved educational information about precision farming equipment ownership costs, and the required returns to pay for their investment. The partial budgeting and breakeven analysis framework is documented along with use of the decision aid. With care in specifying values, program users... J.A. Larson, D.F. Mooney, R.K. Roberts, B.C. English

2. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

3. Adoption And Perceived Usefulness Of Precision Soil Sampling Information In Cotton Production

  Soil testing assists farmers in identifying nutrient variability to optimize input placement and timing. Anecdotal evidence suggests that soil test information has a useful life of 3–4 years. However, perceived usefulness may depend on a variety of factors, including field variability, farmer experience and education, farm size, Extension, and factors indirectly related to farming. In 2009, a survey of cotton farmers in 12 Southeastern states collected information... D.C. Harper, D.M. Lambert, B.C. English, J.A. Larson, R.K. Roberts, M. Velandia, D.F. Mooney, S.L. Larkin