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Paxton, Kenneth W.; Mishra, Ashok K.; Chintawar, Sachin; Larson, James A.; Roberts, Roland K.; English, Burton C.; Lambert, Dayton M.; Marra, Michele C.; Larkin, Sherry L.; Reeves, Jeanne M.; Martin, Steven W.. |
Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the number of specific types of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the influence of spatial yield variability on the number of precision farming technologies adopted, using a Count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a larger number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies were significantly correlated. Finally, farmers using computers for... |
Tipo: Conference Paper or Presentation |
Palavras-chave: Precision technologies; Poisson; Negative Binomial; Count-data method; GIS; Education; Cotton; Agricultural and Food Policy; Farm Management; Labor and Human Capital; Land Economics/Use; Productivity Analysis; Resource /Energy Economics and Policy. |
Ano: 2010 |
URL: http://purl.umn.edu/56486 |
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Paxton, Kenneth W.; Mishra, Ashok K.; Chintawar, Sachin; Roberts, Roland K.; Larson, James A.; English, Burton C.; Lambert, Dayton M.; Marra, Michele C.; Larkin, Sherry L.; Reeves, Jeanne M.; Martin, Steven W.. |
Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions... |
Tipo: Journal Article |
Palavras-chave: Precision technologies; Poisson; Negative binomial count data method; GPS; Education; Cotton; Crop Production/Industries; Farm Management; Production Economics; Research and Development/Tech Change/Emerging Technologies. |
Ano: 2011 |
URL: http://purl.umn.edu/105464 |
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Pandit, Mahesh; Mishra, Ashok K.; Paudel, Krishna P.; Larkin, Sherry L.; Rejesus, Roderick M.; Lambert, Dayton M.; English, Burton C.; Larson, James A.; Velandia, Margarita M.; Roberts, Roland K.; Kotsiri, Sofia. |
We used survey data collected from cotton farmers in 12 southern U.S. states to identify factors influencing cotton farmers’ decisions to adopt precision farming. Using a seemingly unrelated ordered probit model, we found that younger, educated and computer literate farmers chose precision farming for profit reason. Farmers who perceived precision farming to be profitable adopt it to be at the forefront of agricultural technology. We also found that farmers who were concerned with environment emphasize precision farming adoption as a reason to improve environmental quality. Our results also indicate that farmers in coastal states such as Alabama, Mississippi, and North Carolina chose environmental benefits as a reason for precision farming technology... |
Tipo: Conference Paper or Presentation |
Palavras-chave: Precision technologies; Seemingly unrelated ordered probit; Cotton; Agricultural Finance; Farm Management; Q16; C35. |
Ano: 2011 |
URL: http://purl.umn.edu/98575 |
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