Abstract
Pig delivery weight optimisation (PDWO) has been studied extensively and has resulted in several optimisation models. A previous participatory analysis of the problem has revealed that existing models are too complex and might therefore be under-valorised. Farmers desire a simple but reliable model based on available farm data to learn about the problem. A spreadsheet simulation model was therefore developed based on empirical animal performance models. The present study aims at conceptualising a stakeholder-driven model concerning PDWO that should provide insights into four key questions: I) how do the driving forces behind the optimisation determine the optima, II) what is the dependency of the optimal delivery weight on market conditions, III) how do the opportunity costs due to suboptimal delivery evolve, in addition to the mere optimisation results and IV) what is the effect of differences in animal performance profile, in terms of growth, feed intake and average carcass quality on the optimal delivery results? The results generated by the simulation model generally align with those generated using more sophisticated modelling approaches in previous studies. Our results indicate that the animal's growth and feed intake profile can more importantly affect the location of the optima, the stability of the optima and economic importance of delivery weight optimisation compared to market conditions. Moreover, the effect of market conditions on the optimisation was dependent on the animal profile, which determines the flatness of the payoff curve per pig. The possible flat payoff curves imply that the benefits of accurate PDWO can be limited and that some error margin in decisions on PDWO can be exploited. Moreover, this finding illustrates and corroborates the increased benefit of a shift in technology, i.e. an improved animal performance, compared to striving for the optimum on the production function of an inferior technology. Using this simplified model, farmers can investigate the flatness of their farm-specific payoff curve and the stability of their farm-specific optima. That information may help them to determine the appropriateness of a robust decision-supportive rule about optimal delivery weight on their farm.
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