Keywords
whole-farm planning model, mathematical programming, optimisation, decision support, farm machinery
Start Date
16-9-2020 11:00 AM
End Date
16-9-2020 11:20 AM
Abstract
Climatic change holds considerable challenges for farm management. On the one hand, climate change increases uncertainty about future trends and the inter-annual variability of farming conditions. On the other hand, economic pressure and climate mitigation efforts require farmers to be efficient economically as well as efficient in natural resource use. Strategic decisions, especially machinery investments, fix resources for a long time span and affect both the future capacity to adapt to environmental variability and the efficiency of resource use on-farm. Improving decision support tools to inform such strategic management decisions is demanded by both farmers and farm machinery suppliers. The Kuratorium für Technik und Bauwesen in der Landwirtschaft (KTBL) holds a constantly updated, comprehensive collection of farm technical coefficients on more than 5,000 fieldwork processes and more than 2,400 machinery and equipment types. While this data has been made available to farmers for evaluation of individual production processes and field work technology in the past, here we incorporate it into a whole-farm inter-temporal planning model implemented using the farm-level agent-based simulation package MPMAS to allow for a comprehensive analysis of investment strategies. Technically, data can be incorporated via conventional database import or more directly through the new SPARQL interface offered by KTBL. The approach is open also for complementation with on-farm data from automatic data-capturing technology mounted on modern agricultural equipment.
Digital Support for Farm Investment Decisions: Climate Change and Economies of Size in Farm Mechanisation
Climatic change holds considerable challenges for farm management. On the one hand, climate change increases uncertainty about future trends and the inter-annual variability of farming conditions. On the other hand, economic pressure and climate mitigation efforts require farmers to be efficient economically as well as efficient in natural resource use. Strategic decisions, especially machinery investments, fix resources for a long time span and affect both the future capacity to adapt to environmental variability and the efficiency of resource use on-farm. Improving decision support tools to inform such strategic management decisions is demanded by both farmers and farm machinery suppliers. The Kuratorium für Technik und Bauwesen in der Landwirtschaft (KTBL) holds a constantly updated, comprehensive collection of farm technical coefficients on more than 5,000 fieldwork processes and more than 2,400 machinery and equipment types. While this data has been made available to farmers for evaluation of individual production processes and field work technology in the past, here we incorporate it into a whole-farm inter-temporal planning model implemented using the farm-level agent-based simulation package MPMAS to allow for a comprehensive analysis of investment strategies. Technically, data can be incorporated via conventional database import or more directly through the new SPARQL interface offered by KTBL. The approach is open also for complementation with on-farm data from automatic data-capturing technology mounted on modern agricultural equipment.
Stream and Session
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