GC4SHEEP working group is working to collect a breed-specific data to design predictive models that are collected on a secure federated platform.
This solution also enables the analysis of innovative tools to improve fertility by artificial insemination and increase farm profitability
Artificial Intelligence (AI) and information technologies can bring significant benefits to traditional sectors such as livestock farming. As an example, Gradiant is working on the GC4SHEEP group, which allows AI to be applied to improve the fertility of dairy sheep farms. This alliance has a double objective: to increase profitability through a transformation based on data and sharing information in fertility improvement innovations.
The dairy sheep sector associations have been collecting breed-specific data for years, becoming a a very valuable source of information but not sharing it. GC4SHEEP is working on a secure federated AI-based platform to share information for the development of predictive models with which sheep farming associations can make decisions and act more quickly.
Joaquín Lago from Gradiant points out that “new data processing technologies accompanied by AI will allow livestock farm owners to work coordinately to identify patterns and solutions in areas such as fertility in artificial insemination, taking into account factors such as genealogy, feeding or milk analysis, among others.” Explaining that “at Gradiant, we provide a technology solution to a strategic industry in Spain, representing the second European milk producer.”
Led by OVIGEN, Centre for Selection and Genetic Improvement of sheep and goats of Castilla y León, at GC4SHEEP are involvedthe three most important national associations (ASSAFE, AGRAMA and CONFELAC).
Genetic and reproductive improvement
GC4SHEEP key elements are how to develop innovative solutions to improve fertility. With Gradiant’s technologies, it is possible to extract essential data related to male jumping rhythms, making possible to know which is the most suitable rhythm to maintain the production of the best quality seminal doses.
Thanks to the information-sharing platform between breeds, key points such as stallion selection in relation to morphology studies, testicular size or semen quality can also be pooled.
Gradiant’s developments based on AI also make it possible to study data related to feed rations in ewe lambs, to define the optimal plan for the physiological development of the udder and, in the case of males, to evaluate the effect of diet on their profile as sires.
In another line, MIR (mid-infrared methodology) analysis data of milk components will be used to determine correlations with other parameters that influence fertility, as well as the body condition of the females to be inseminated, in order to evaluate reproductive outcomes.
This Operational Group has been the beneficiary of a grant for the implementation of innovation projects of general interest by operational groups of the European Innovation Partnership for Agricultural Productivity and Sustainability (AEI-Agri), in the framework of the National Rural Development Programme 2014-2022, with funds from the European Recovery Instrument (EU Next Generation). The managing authority responsible for the implementation of the corresponding aid is attributed to the Directorate-General for Rural Development, Innovation and Agri-food Training (DGDRIFA). The measure is 100
