Development of a multidimensional and customizable decision support tool for dairy culling management

The economic performance of dairy farms essentially relies on the farmer’s ability to select the most suited
cows for their production system. A major constraint lies in the time required for data encoding and analysis at
the farm level. Our solution offers a data centralization service to facilitate its access and use. The study seeks
to develop an innovative decision support tool (DST), named Win/Lose, which ranks dairy cows according to
their economic profitability by integrating various data such as milk production, veterinary costs and metabolic
disorders. The DST aims at identifying cows to keep (Win) and those to cull (Lose), thereby enriching the
farmer’s decision-making capacity. The DST calculates a profit index based on milk yield, fat content, protein,
culling weight, somatic cell count, and their respective net unit margins. The index also incorporates fertility
performance. Through predictive models utilizing the mid-infrared spectrum of milk, the DST analyzes data on
fatty acids, cheese-making properties, minerals, energy balance, infections, and methane production. This multidimensional
approach refines cow selection, offering customization according to the farmer’s priorities. This tool
enables objective selection, providing farmers with a broad range of indicators for informed decision-making on
cow culling and complementing the economic and environmental efficiency of their operations. The use of the
DST contributes to a significant improvement in the profitability and sustainability of dairy farms. By streamlining
data analysis and customizing selection criteria, this tool gives farmers the freedom to define their production
strategy, aligned with their economic and ecological objectives.