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Project

Bridging gaps: Integration of on-farm phenotypic and genotypic data to improve monitoring and decision-support in dairy cattle - application on fertility

Sustainable food production remains one of the biggest and most timely modern-day challenges. In dairy farming, sustainability is strongly linked with reproduction performance of the cows. Unfortunately, improving cow fertility and conception have proven challenging because they depend on many physiological, genetic and environmental factors and their interactions. Better support of farmers in their decision making on which cows to inseminate and select for advanced breeding, for example by an improved insight in the chance of conception success, would nonetheless be a valuable way to enhance fertility management and increase a farm’s profitability and sustainability. This project aims to identify the factors affecting conception rate available on farm, thereby explicitly researching the variability explained by the potential discrepancy between the cows’ genetic merit and their actual performance (‘the genotype-phenotype gap, GP-gap’). To this end, a PHENGEN-ECR algorithm will be developed that predicts the expected conception rate based on a combination of (1) on-farm high-frequency sensor time series as a proxy for health and physiological status, and (2) genetic information and the GP-gap, both in perspective to and taking into account the herd environment. As this model will rely on readily available data, the improved understanding and prediction of conception rate will have the potential to increase the sustainability of dairy farming in all its aspects.

Date:2 Mar 2021 →  Today
Keywords:Fertility decision support, Genotype-phenotype gap, Precision dairy farming
Disciplines:Development of bioinformatics software, tools and databases
Project type:PhD project