Adoption of Information Technologies in Cotton Production

Thursday, January 5, 2012: 4:00 PM
Canary 4 (Orlando World Center Marriott)
Nathanael Thompson , University of Tennessee
James A. Larson , University of Tennessee
Burton C. English , University of Tennessee
Dayton M. Lambert , University of Tennessee
Roland K. Roberts , University of Tennessee
Margarita Velandia , University of Tennessee
Chenggang Wang , Texas Tech University
Adoption of Information Technologies in Cotton Production

Abstract

The use of precision farming has become increasingly important in cotton production due to its ability to allow farmers to take advantage of knowledge about infield variability by applying increasingly expensive inputs at levels appropriate to crop needs. Essential to the success of the precision farming system is the adoption of site-specific information technologies such as yield monitors, passive remote sensing, handheld GPD/PDA devices, active remote sensing, and electrical conductivity. The objective of this study is to evaluate the factors influencing the decision by cotton producers to adopt one or more of the selected information technologies. While the adoptions of some of the technologies in this study have been evaluated individually in previous literature, there exists a gap in knowledge of the factors affecting the adoption of some of the newer information technologies such as active remote sensing and electrical conductivity. Data for this study were collected from the Cotton Incorporated 2009 Southern Cotton Precision Farming Survey. A Probit model will allow for the evaluation of the factors affecting farmers’ decision to adopt. The factors to be evaluated include farmer characteristics such as age and education; farm characteristic such as farm size and region; as well as farmers’ sources regarding precision farming information. This analysis will permit the identification of factors significantly affecting farmers’ decision to adopt which can be beneficial to entities such as agricultural extension and agribusiness firms looking to help farmers take advantage of the potential benefits these technologies can provide. This information will also allow for the evaluation of the probability of a given farmer adopting given his or her specific set of characteristics.