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Hefley, T
Larson, J.A
Valencia Ramirez, P
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Authors
Lambert, D.M
Larson, J.A
English, B.C
Rejesus, R.M
Marra, M.C
Mishra, A.K
Wang, C
Watcharaanantapong, P
Roberts, R.K
Velandia, M
Valencia Ramirez, P
Carcedo, A
Antunes de Almeida, L.F
Horbe, T
Corassa, G
Pott, L.P
Ciampitti, I
Hintz, G.D
Hefley, T
Schwalbert, R.A
Prasad, V
Topics
Global Proliferation of Precision Agriculture and its Applications
Data Analytics for Production Ag
Weather and Models for Precision Agriculture
Type
Poster
Oral
Year
2012
2024
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Filter results3 paper(s) found.

1. Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton Production

Technology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of... D.M. Lambert, J.A. Larson, B.C. English, R.M. Rejesus, M.C. Marra, A.K. Mishra, C. Wang, P. Watcharaanantapong, R.K. Roberts, M. Velandia

2. Analytics Model for Predicting Sucrose Percentage in Sugarcane Using Machine Learning Techniques

Sucrose is one of the most important indicators in the final profitability of Colombian sugar mills, therefore, its understanding and forecast are fundamental for the business. In this work, a proposal is formulated for an analysis model that allows predicting the percentage of sucrose based on historical data from mechanically harvested farms with the objective of knowing the numerical value of sucrose for each month of milling and be able to plan monthly and annual sugar production. Regarding... P. Valencia ramirez

3. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico Approach

Water stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad