Authors
| Filter results6 paper(s) found. |
|---|
1. Spatial Variability Of Measured Soil Properties Across Site- Specific Management ZonesThe spatial variation of productivity across farm fields can be classified by delineating site-specific management zones. Since productivity is influenced by soil characteristics, the spatial pattern of productivity could be caused by a corresponding variation in certain soil properties. Determining the source of variation in productivity can help achieve more effective site-specific management, the objectives of this study were (i) to characterize the spatial variability of soil physical properties... M. Mzuku, R. Khosla, R. Reich, G. Http://icons.paqinteractive.com/16x16/ac, F. Smith, L. Macdonald |
2. A Computer Decision Aid For The Cotton Precision Agriculture Investment DecisionThis 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 |
3. 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 |
4. 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 |
5. Performance Evaluation Of Single And Multi-GNSS Receivers In Agricultural Field ConditionsSelection of appropriate receivers and utilization methods of positioning systems are important for better positioning in different applications of precision agriculture. Objective of this research was to evaluate the performance of single and multi-GNSS receivers at stationary and moving conditions in typical Korean agricultural sites such as open field, orchard area, and mountainous area A single-GNSS receiver (Model: R100; Hemisphere GNSS, Scottsdale, AZ, USA) and a multi-GNSS... Y. Kim, M. Song, S. Chung , M.S. Kabir, Y. Huh |
6. An Efficient Data Warehouse for Crop Yield PredictionNowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi |