Reducing the Burden of Artificial Insemination for Dairy Cows
AutoML assisted decision support enabling farmers to make better live stock breeding decisions.
Farming dairy cows for large scale milk production relies heavily on artifical insemination. This process has a very low success rate. Multiple inseminations are stressful for cows and put a high burden on them. At the same time, failed procedures are expensive, cutting into the already slim profit margins of farmers.
Livestock breeding registries such as the Swissherdbook are already collecting a multitude of data related to milk quality and animal welfare. Making decisions with machine learning allows farmers to make judgements about the likelihood of success for an artificial insemination procedure. Data-driven decisions lead to higher success rates reducing the overall burden put on dairy cows. Ultimately, lower stress leads to healthier cows giving better milk. Additionally, with machine learning based decision support, farmers can control and forecast their operations more efficiently.
Modulos AutoML is designed to enable domain level experts to build machine learning solutions without any prior knowledge in ML. Using integrated interpretability functions, farmers additionally get insights into which factors are driving artificial insemination success. These decisions can be used to optimize breeding conditions and animal happiness.