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Presentation 21043

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Natural disasters such as hurricanes, floods, and droughts often cause significant economic damages for agricultural producers and agribusinesses. Agricultural economics departments and colleges of agriculture are often asked to help compute economic losses resulting from such events. The resulting loss estimates are used to lobby for various forms of disaster relief and to show that regions, states, or commodities are eligible for existing government programs. This paper documents how agricultural economists and their colleagues at The University of Georgia went about estimating losses suffered in Georgia from Hurricane Michael in October 2018.

This paper compares precision farming technology with calendar-based approaches in scheduling fungicide applications to manage tomato late blight disease. Two fungicide scheduling strategies were evaluated: calendar-based strategy and BlightPro decision support system based strategy (DSS-based strategy). Using results from 14 years of computer simulation experiments for 25 locations in the United States, we constructed distributions of net return to all costs excluding fungicide cost and application cost (net return per acre) for the calendar-based and DSS-based strategies at each location. These distributions were then compared using three risk management methods: stochastic dominance, stochastic dominance with respect to a function, and stochastic efficiency with respect to a function. Results show that in terms of disease control, the DSS recommended spray schedule is more effective. Depends on the percentage of tomato yield improvement for DSS, the preferred strategy is different. Average net income over fungicide cost and average risk-adjusted net income for the DSS recommended spray schedule is lower for susceptible cultivars and higher for moderately susceptible cultivars and moderately resistant cultivars with no yield improvement for DSS strategy. The value added by DSS ranges from -$17.69 to $48.33 per acre with no tomato yield improvement for DSS strategy. When there are more than 5% yield improvement, DSS strategy is strong preferred strategy by tomato growers. Our research contributes to the literature by providing a method to evaluate the economic benefit of adopting DSS.

This study evaluates economic thresholds for a new web-based decision support system developed for precision fungicide management for potato production. We extend previous work (Zhang and Swinton, 2009), by developing an intra-seasonal dynamic economic optimization model. This model allows us to evaluate economic thresholds for disease control. The suggested model is applied to the problem of controlling potato late blight disease in 152 locations for 5 major potato producing states in the United States. The empirical results show that the economic thresholds improved disease suppression and farming profit relative to the previous critical thresholds while maintaining fungicide use efficiency.

Precision agriculture has emerged as a revolutionary technology in helping make farm decisions. It transforms farm related data into information, and then coverts information into useful knowledge for decision-making. This study evaluates economic thresholds for a new web-based decision support system developed for precision fungicide management for potato production. Using 10 years of computer simulation experiments from 152 locations in the United States, we compared different thresholds in terms of disease severity, fungicide usage efficiency, and net income over fungicide cost to manage potato late blight disease. The empirical results show that the economic thresholds improved disease suppression and farming profit relative to the previous critical thresholds while maintaining fungicide use efficiency.

Stochastic dominance, stochastic dominance with respect to a function, and stochastic efficiency with respect to a function are used to compare late blight management strategies between a calendar spray schedule and a spray schedule recommended by Potato/Tomato Late Blight Decision Support System (DSS). Results show that the DSS recommended spray schedule is a more effective management strategy for controlling late blight in terms of disease control, net income over fungicide cost, and risk-adjusted net income. The value added by DSS ranges from $30 to $544 per acre. Our research contributes to the literature by providing a method to evaluate the economic benefits of adopting DSS.

This study used experimental data from West Lafayette, Indiana to examine the economic benefits of applying fungicide to corn. The average improvements in yield, gross revenue, and net return (gross revenue minus fungicide and application cost) were 4 bushels per acre, $19 per acre, and -$9 per acre, respectively. Stochastic dominance was used to compare the fungicide application treatments to a no fungicide application alternative. Individual fungicides were part of the stochastic dominance efficient sets. However, with recent corn prices, the improvement in yields and gross revenue would not be high enough to make the individual fungicides economically viable.