Improving a dynamic farm level model by coupling empirically estimated pre-crop values with crop rotation optimization

Abstract

The dominance of cereal-based rotations in Finnish agriculture contributes to adverse environmental impacts, and shifting towards diversified cropping systems has been minimal. Since economic viability and profit motives are strong among farmers, there is a need for analysis tools investigating profitability of agronomically feasible, diversified cropping systems and rotations. While there is consensus on pre-crop effects, their impact is unclear and often overlooked in decision-making. We integrate recent empirically estimated pre-crop values into farm models to assess their influence on land use and farm economy and use dynamic optimization to solve the economically optimal crop rotations. The results show that including empirically estimated pre-crop values improves on subjective expert estimates of pre-crop effects and can eliminate the need for additional rotational constraints. Utilizing pre-crop effects consistently over time may lead to significant economic gains. This approach can contribute to sustainable agriculture by encouraging diversification and resilience, even amidst changing climates or novel crops.