Modeling economic, biophysical, and environmental dynamics of potato production system

The adoption and use of diversified cropping practices has become widely accepted by producers. However, the profitability of an enterprise is dependent on the biophysical and economic factors. The biophysical factors determine the enterprise relationship among the various crops, their interactions with the ecosystem, and how each of them fits into the overall management plan. The economic factors determine the relative advantage of each crop and service in the farm plan. Although there have been experimental studies in Canada examining the impacts of rotations on the agronomics of field crops, there is limited research in modeling economic and environmental dynamics of the potato production system. Potato production in Manitoba has rapidly increased in recent years and became the second largest potato producer in Canada producing about 22.2% of the total Canada’s potato production as of 2004. Alberta has had similar expansion with the highest yield per acre in Canada. The expansion of potato industry in these two provinces and other parts of Canada has created some concerns about agroenvironmental indicators such as water contamination, soil erosion and long-term profitability of potato production practices. The objective of this study was to address some of these concerns and develop a dynamic model that integrates environmental and economic components of potato production systems and estimates sustainability of some of the agricultural practices. A Stella Modeling framework was developed to provide crop production and environmental input to an economic model of potato rotations. The economic performance of different potato rotations ranging from two to four years in duration, and containing potatoes in combination with oilseed, cereal, forage, and legume crops was evaluated based on standard budgeting techniques. Net income was estimated as the income remaining above cash costs (i.e., seed, fertilizer, chemical, fuel and oil, repairs, crop insurance premium, miscellaneous, land taxes, and interest cost on variable inputs), ownership costs (depreciation, interest on investment, and insurance and housing) for machinery and grain storage, and labour. All annual inputs used in each phase of rotation for each management treatment, the type and frequency of field operation, year and replicate including pre-plant activities, tillage, fertilization, planting, insects and pests control, harvesting, storage, and transportation were included in the analysis.