Controlling the Risk for an Agricultural Harvest

Abstract

Gathering the harvest represents a complex managerial problem for agricultural cooperatives involved in harvesting and processing operations: balancing the risk of overinvestment with the risk of underproduction. The rate to harvest crops and the corresponding capital investment are critical strategic decisions in situations where poor weather conditions present a risk of crop loss. In this article, we discuss a case study of the Concord grape harvest and develop a mathematical model to control harvest risk. The model involves differentiation of a joint probability distribution that represents risks associated with the length of the harvest season and the size of the crop. This approach is becoming popular as a means of dealing with complex problems involving operational and supply chain risk. Significant cost avoidance, in the millions of dollars, results from practical implementation of the Harvest Model. Using real data, we found that the Harvest Model provides lower-cost solutions in situations involving moderate variability in both the length of season and the crop size as compared to solutions based on imposed risk policies determined by management.harvest risk, agriculture

Contract farming with possible reneging in a developing country: Can it work?

“…When the yield is uncertain, there is a risk of supply and demand mismatch and such a risk is managed and mitigated by the capacity-production decision that accounts for such uncertainty (Allen & Schuster, 2004;Kazaz, 2008), or by the second production opportunity (Jones, Kegler, Lowe, & Traub, 2003;Jones, Lowe, Traub, & Kegler, 2001;Jones, Lowe, & Traub, 2002;Kazaz, 2008). All these papers are presented in the context of a single decision maker and do not consider any contract structure.…”

Use of MIP for planning temporary immigrant farm labor force

“…For those interested in quality summaries of such literature, Glen (1987) provides a review of early work while Ahumada and Villalobos (2009), Shukla and Jharkharia (2013), and Zhang and Wilhelm (2011) summarize much of the recent literature devoted to planning within the agricultural industry. Research which is specifically related to the model presented in this article are those which focus on harvesting decisions specifically (Caixeta-Filho, 2006;Allen and Schuster, 2004;Bohle et al, 2010) as well as those focusing on the overall agricultural scheduling methodology (Caixeta-Filho et al, 2002, Hazell, 1971. It should also be noted that mathematical models are found in other areas of the agricultural supply chain as demonstrated by those focusing on distribution (Broekmeulen, 1998;Cholette, 2007;Rantala, 2004), packaging (Blanco et al, 2005;Davis et al, 2002), storage (Starbird, 1988), and the complete production and logistics planning process (Kopanos et al, 2012;Amorim et al, 2012;Yu and Nagurney, 2013).…”

Hybrid modeling for vineyard harvesting operations

“…These algorithms aim to optimize the number of machines and workers for harvesting process in order to improve crop productivity, total distance travelled, fuel consumption and operational cost (Bochtis and Vougioukas, 2008;Sørensen and Bochtis, 2010). For grape crop however, few studies have been published to study the dynamics of harvesting process and its performance (Allen and Schuster 2004). Grape producers are highly dependent on the seasonal labor market to provide the required resources for the manual activities during harvesting season (Whatman and Van Beek 2008).…”