Margarita Velandia

Factors Affecting Farmers' Utilization of Agricultural Risk Management Tools: The Case of Crop Insurance, Forward Contracting, and Spreading Sales

Factors affecting the adoption of crop insurance, forward contracting, and spreading sales are analyzed using multivariate and multinomial probit approaches that account for simultaneous adoption and/or correlation among the three risk management adoption decisions. Our empirical results suggest that the decision to adopt crop insurance, forward contracting, and/or spreading sales are correlated. Richer insights can be drawn from our multivariate and multinomial probit analysis than from separate, single-equation probit estimation that assumes independence of adoption decisions. Some factors significantly affecting the adoption of the risk management tools analyzed are proportion of owned acres, off-farm income, education, age, and level of business risks.

Timing of precision agriculture technology adoption in US cotton production

The timing of technology adoption is influenced by profitability and farmer ability to bear risk. Innovators are typically more risk tolerant than laggards. Understanding the factors influencing early adoption of precision agriculture (PA) technologies by cotton farmers is important for anticipating technology diffusion over time. The factors influencing the timing of grid soil sampling (GSS), yield monitoring (YMR) and remote sensing (RMS) adoption by cotton producers was evaluated using multivariate censored regression. Data for cotton farmers in 12 states were obtained from a survey conducted in 2009. The factors hypothesized to influence the timing of adoption included farm characteristics, operator characteristics, PA information sources, adoption of other PA technologies, and farm location. The results suggest that different factors influenced when cotton farmers adopted GSS, YMR and RMS after these technologies became commercially available. For example, land ownership was associated with the timing of GSS adoption, but not YMR or RMS adoption; farmer age was correlated with the timing of GSS and YMR adoption, but not RMS adoption; and obtaining PA information from consultants affected the timing of GSS and RMS adoption, but not YMR adoption. The only factors correlated with the early adoption of all three technologies were beliefs that PA would improve environmental quality and the adoption of at least one other PA technology. Thus, the potential for improved environmental quality appears to be a strong adoption motivator across PA technologies, as is the earlier adoption of other PA technologies. This research may be useful for farmers, researchers, Extension personnel, machinery manufacturers, PA information providers and agricultural retailers to anticipate the future adoption of new and emerging PA technologies.

Factors Influencing the Selection of Precision Farming Information Sources by Cotton Producers

Precision farming information demanded by cotton producers is provided by various suppliers, including consultants, farm input dealerships, University Extension systems, and media sources. Factors associated with the decisions to select among information sources to search for precision farming information are analyzed using a multivariate probit regression accounting for correlation among the different selection decisions. Factors influencing these decisions are age, education, and income. These findings should be valuable to precision farming information providers who may be able to better meet their target clientele needs.

Factors Affecting Producer Participation in State-sponsored Marketing Programs: The Case of Fruit and Vegetable Growers in Tennessee

State programs promoting their agricultural products have proliferated in response to increased consumer interest in locally grown foods. Tennessee, for example, currently has two state-funded programs promoting its agricultural products. This study examines the factors associated with participation by Tennessee fruit and vegetable farmers in those programs. The results suggest that farmer participation is associated with farm income, use of extension resources, and fresh produce sales. These results should be of interest to anyone attempting to increase producer participation in such programs.

Automatic Section Control Technologies and GPS Auto-guidance Systems Adoption in Cotton Production

Using data from a survey of cotton producers in 14 US states, and a bivariate probit regression, this study examined the effects of the following measured parameters on the adoption of Automatic Section Control (ASC) technologies and GPS Auto-Guidance (AG) systems: age, education, farm size, field geometry, information sources, as well as the use of specific production practices and other Precision Agriculture (PA) technologies. Results suggest that younger, more educated producers, consulting farm dealers for information about PA technologies, using other PA technologies, and managing larger farming operations located in counties with more irregularly shaped fields are more likely to adopt ASC technologies and AG systems. Predicted adoption probabilities estimated using regression results suggest the use of other PA technologies and farm dealers as a source of precision farming information have the largest impact on the probability of adopting ASC by cotton farmers. Additionally, these results suggest farmers with operations in eastern Arkansas, western Tennessee, and a couple of counties in middle Tennessee are more likely to adopt ASC technologies. Producers in these regions had the highest percentages of users of other PA technologies and farm dealers to obtain PA information.

Factors Influencing Organic and Fair Trade Coffee Growers Level of Engagement with Cooperatives: The Case of Coffee Farmers in Mexico

Abstract We study the factors influencing the percentage of organic and fair trade certified coffee sold through a cooperative by growers of five cooperatives in Mexico. The percentage of coffee sold through the cooperative was used as a proxy of growers’ engagement with a cooperative. Using factor analysis and a fractional probit regression, we evaluated the proposition that the level of engagement can be explained by transaction cost economics, social norms and connections, and farmer and farm business characteristics. We found that farm size, uncertainty regarding cooperative time of payment to the members and cooperative commitment on price to be paid negatively influence the level of engagement. In contrast, asset specificity, relational commitment, and price have a positive impact on engagement. Our results may help cooperatives and policy makers to build strategies aiming to increase this level of engagement. This is relevant because lower grower engagement has been found to be positively correlated with weak performing cooperatives.

EFFECT OF BALE SIZE AND DENSITY ON TSNA FORMATION IN BALED BURLEY TOBACCO

Abstract Nitrosamines are nitrogen-containing compounds that occur in trace amounts in everyday items. Tobacco-specific nitrosamines (TSNA) have been identified as some of the most potent carcinogens in tobacco products. The objective of this study was to evaluate market preparation conditions affecting TSNA levels in cured burley tobacco. The data for this study were based on a market-preparation experiment design to study bale density and size effects on TSNA levels during storage in Greenville, TN following the 2005, 2006, and 2007 growing seasons. Standard and flue-cured sized bales were evaluated at standard and high density levels. The effects of bale size and density were estimated by evaluating TSNA content changes between the baling and sale time. Analysis of variance (ANOVA) was performed for all the years combined. Results show that bale size and density do not have a significant effect on TSNA level changes.