Exploring options for farm‐level strategic and tactical decision‐making in fruit production systems of South Patagonia, Argentina

In South Patagonia, Argentina, sweet cherry is the main fruit‐tree crop grown for export, resulting in a highly seasonal labour demand. Managers of deciduous perennial fruit orchards must consider both biological and economic relationships in selecting crop species and orchard design. This makes decisions at the farm‐level extremely complex, as especially in such perennial crops, strategic (‘what to plant’, ‘with which technology’ and ‘how much area of each activity’, i.e. the final design) and tactical (‘when, what and how to plant in time’, the pathway to the planned farm) decisions have a long‐term effect. The objective of this study was to explore the consequences of different strategic and tactical decisions at farm scale in fruit production systems of South Patagonia, considering the variation in interests and aims of different stakeholders, and using a sensitivity analysis to evaluate the consequences of possible changes in external conditions. A dynamic farm‐scale optimization model called OPTIFROP was developed to generate alternative farm development plans, by allocating, in the course of the time horizon of the run, production activities to different land units, while optimising different objective functions, subject to several constraints. Although time‐dependent, dynamic, mathematical programming models for analysing farming systems have been described in literature, the dynamic aspects of long‐term decision‐making in orchard design and their impact on the sequential (annual) nature of orchards in different growth phases (i.e. medium‐term decision‐making), need a higher time‐staged dynamic approach with a staircase matrix structure. The model includes two objective functions at farm level: (1) maximization of the present value of cumulative financial result, which is the main objective for growers, and (2) maximization of cumulative farm labour, which is an objective often mentioned by policy makers. The inter‐months deviation for labour demand (during the period of high labour demand, November–April) was included as an upper‐bound. Input and output coefficients for the land use options considered in OPTIFROP were quantified using the Technical Coefficient Generator FRUPAT. Model results indicated that the present value of cumulative financial result and the cumulative farm labour are conflicting to a very limited extent. Timing and feasibility of implementing certain combinations of production technologies are affected by resource endowments and initial conditions, but these factors do not influence land use selection in the long term. Land use selection is driven by the objectives of the stakeholders. OPTIFROP showed that, through introduction of alternative crops, substantial reductions in labour peaks in the period November–April could be achieved with a relatively small reduction in farm income. The sensitivity of the model solution to the cherry price suggests that the fruit production sector of South Patagonia should pay more attention to the robustness of their land use plans and take preventive measures to avoid being caught by a possible crisis due to changes in the context.