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Abstract
Agriculture is a vital industry in the state of Georgia; therefore, the sustainability of agricultural production is critical to the area. Best management practices (BMPs) can decrease production inputs, aiding in reducing agricultural pollution, often without reducing farm productivity. Additionally, more efficient resource use can help to combat rising input prices. However, concern about the impacts of BMP adoption on yield and profitability can hinder producers’ decision to adopt. Current literature on BMP adoption is evaluated at the individual conservation technique and fails to address a bundle of BMP’s joint effects on yield and profitability, and the risk attitudes of producers. To quantify the risk of BMP implementation for cotton and peanut production in Georgia, we investigated the variability in net returns between alternative BMP systems. Data were collected from producers and extension agents to create enterprise budgets to represent current land-use practices in the region, including farm-scale production costs for management systems that were evaluated at three scenario levels: intensive, typical, and minimal adoption of BMP technologies and practices. Using Simetar modeling software, we simulated net returns to compare alternative scenarios and stochastically determine the financial viability of BMP adoption. Stochastic efficiency with respect to a function (SERF) was used to rank cotton and peanut BMP bundles in terms of certainty equivalents at each level of absolute risk aversion. This research aims to determine the economic sustainability of BMP bundles by evaluating changes in net returns when a BMP system is adopted and identifying the risk-efficient management system. Findings indicate that, as producers’ risk-aversion grows, the typical BMP system becomes the most preferred by both peanut and cotton producers. The results can inform grower decision-making about regional BMP adoption.