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| Filter results6 paper(s) found. |
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1. The Adoption of Information Technologies and Subsequent Changes in Input Use in Cotton ProductionThe use of precision farming has become increasingly important in cotton production. It allows farmers to take advantage of knowledge about infield variability by applying expensive inputs at levels appropriate to crop needs. Essential to the success of the precision... N.M. Thompson, J.A. Larson, B.C. English, D.M. Lambert, R.K. Roberts, M. Velandia, C. Wang |
2. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 SurveyThe 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 ProductionSoil 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 |
4. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen RatesNitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf |
5. Using Profitability Map to Make Precision Farming Decisions: A Case Study in MississippiRecent development in precision agriculture technologies have generated massive amount of geospatial data of farming, such as yield mapping, seeding rates, input applications, and so on. However, producers are still struggling to convert those precision data into farm management decisions to improve productivity and profitability of farming. Indeed, deriving accurate decisions at each site of the field requires complex and comprehensive modeling of crop yield responses to various... X. Li, K. Coble |
6. All for One and One for All: a Simulation Assessment of the Economic Value of Large-scale On-farm Experiment NetworkWhile on-farm experiments offer invaluable insights for precision management decisions, their scope is usually confined to the specific conditions of individual farms and years, which limits the derivation of more broad and reliable decisions. To address this limitation, aggregating data from numerous farms of various crop growth conditions into a comprehensive dataset appears promising. However, the quantifiable value of this experiment network remains elusive, despite the common agreement of... X. Li |