Adoption of Precision Agriculture for Cotton in the Southern United States (original) (raw)
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Precision agriculture is gaining acceptance all over the world as a management strategy that increases the input use efficiency and reduces the negative environmental impacts of intensive agriculture production. Even with these advantages, the rate of adoption of precision agriculture practices is low in the US especially among the cotton producers. Using farm level data from the2009 Southern Precision farming Survey, this study analyses the farm and farmer characteristics that influence the adoption of specific variability detection technologies by the cotton farmers in the southern United States. A multinomial logit model with different technologies to detect field variability as choices was used to analyze the data. The results indicated that cotton farmers in Texas are less likely to adopt cotton yield monitor or employing a consultant to detect field variability, whereas they are more likely to use soil survey maps compared to other southern states. Younger farmers with higher ...
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We analyzed data obtained from the 2009 Southern Cotton Precision Farming Survey of farmers in twelve states (Alabama, Arkansas, Florida, Georgia, Louisiana, Missouri, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia) to identify reasons for adoption/nonadoption of precision farming technologies. Farmers provided cost, time constraint, satisfaction with the current practice and other as reasons for not adopting precision farming technology. Profit, environmental benefit and to be at the forefront of agricultural technology are main reasons for adopting precision farming technology. Results from a nested logit model indicated that formal education, farm size, and number of precision farming meeting attend by farmers have positive effect on adoption of PF technologies. Moreover, spatial yield variability increases probability of adopting precision farming technologies for profit reasons.
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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 management decisions also adopted a larger number of precision agriculture technologies.
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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 also adopted a higher number of precision agriculture technologies.
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We used the 2009 Southern Cotton Precision Farming Survey data collected from farmers in twelve U.S. states (Alabama, Arkansas, Florida, Georgia, Louisiana, Missouri, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia) to understand why farmers do not adopt seemingly profitable precision farming technology. Farmers provided cost, time constraint, satisfaction with the current practice and other as reasons for not adopting precision farming technology. Results from a multinomial logit regression model indicated that manure application on field, more formal education, larger farm size, participation in conservation easement or agricultural easement generally decreases the probability of nonadoption of precision agriculture in cotton production.
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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 adoption.
Precision application technology has been an important topic in agriculture in recent years. This technology has the promise to improve farm management through improved information and control over in-field variability of soil characteristics and productivity. Despite this apparent promise, recent studies have shown that adoption has been low. However, little is known about the adoption of this technology in Mississippi or the reasons for or against adoption as seen through the eyes of the producer. This survey was designed to collect basic information on producer perceptions about precision agriculture technology and to assess potential reasons for or against adoption.