Larkin, Sherry L.

By: Boyer, Christopher N.; Lambert, Dayton M.; Velandia, Margarita; English, Burton C.; Robert, Roland K.; Larson, James A.; Larkin, Sherry L.; Paudel, Krishna P.; Reeves, Jeanne M.
Factors influencing adoption of variable-rate nutrient management (VRM) and georeferenced precision soil sampling (PSS) for fertilizer management among cotton producers and the factors affecting awareness of and participation in cost-share programs encouraging the adoption of nutrient-management practices were analyzed using multivariate probit regression with sample selection. Data were collected from a fourteen-state cotton producer survey. Factors including farm size, operator age, and farm location were correlated with the adoption of VRM and PSS, awareness of cost-sharing programs, and program participation. The results may help agencies target farms with the specific attributes most likely to participate in cost-share programs.
By: Lambert, Dayton M.; English, Burton; Harper, David; Larkin, Sherry L.; Laron, James; Mooney, Daniel F.; Roberts, Roland; Velandia, Margarita; Reeves, Jeanne
The authors regret that the above paper contained an error in the calculation of the survey expansion weights (Lambert et al., 2014, p. 110). Using the notation of the paper, the expansion factor for the lth stratum was introduced as wl =agbh=ngh, where g indexes states and h indexes farm size class. This is in fact the correct expression if Sinkhorn’s (1964) RAS method were used. However, Ireland and Kullback’s (1968) cross-entropy method was used to estimate the expansion factors, and division of variables a and b by the survey response frequency (ngh) is unnecessary. The typographical error has no bearing on the empirical analysis. References
By: Lambert, Dayton M.; English, Burton C.; Harper, David C.; Larkin, Sherry L.; Larson, James A.; Mooney, Daniel F.; Roberts, Roland K.; Velandia, Margarita; Reeves, Jeanne M.
A 2009 survey of cotton farmers in twelve states collected information about the use of georeferenced precision soil testing (PST). Adoption of PST technology and the interval until retesting were examined with a Poisson hurdle regression. Survey data were calibrated using a post-stratification weighting protocol. Farming experience, farm size, land ownership, variable rate fertilizer management plans, and the use of soil electrical conductivity devices were correlated the with period until PST adopters retested soil. Understanding how producers perceive the useful life of soil-test information may be important for monitoring the effectiveness of best nutrient management practice adoption.
By: Walton, Jonathan C.; Lambert, Dayton M.; Roberts, Roland K.; Larson, James A.; English, Burton C.; Larkin, Sherry L.; Martin, Steven W.; Marra, Michele C.; Paxton, Kenneth W.; Reeves, Jeanne M.
Adoption of precision agriculture technology has arrived considerable attention, but abandonment has received little. This paper identified factors motivating adoption and abandonment of precision soils sampling in cotton. Younger producers who farmed more cotton area, owned more of their cropland, planted more non-cotton area, or used a computer were more likely to adopt precision soil sampling. Those with more cotton area or who owned livestock were more likely to abandon, while those who used precision soil sampling longer, or used variable-rate fertilizer application were less likely to abandon precision soil sampling.
By: Sylvia, Gilbert; Tuininga, Chris; Larkin, Sherry L.
Future harvests from commercial fish stocks are unlikely to increase substantially due to biological and regulatory constraints. Developing alternative sets of processed seafood products is one strategy for increasing welfare while managing the risks inherent in a variable and renewable natural resource. To quantify the risk-benefit tradeoffs of alternative strategies, a portfolio decision framework is embedded into a multi-period bioeconomic model. The model is used to generate an efficient portfolio frontier to estimate possible rent dissipation from status quo management. Frontiers are also generated for seafood processors and brokers. Implications for the different industry agents are discussed.