Artificial intelligence to make cows more feed efficient and climate friendly
Innovation Fund Denmark has invested close to 15 million DKK in a new research project led by VikingGenetics. Researchers from Center for Quantitative Genetics and Genomics (QGG) participate in the project with knowledge and resources within feed efficiency and genetics.
If a professional athlete wants to be among the very best, it is a necessity to know the composition and the amount of food, he or she consumes. To ensure that cows are healthy, fertile, resilient, productive and climate friendly, it is necessary to have similar data on their feed intake.
By using Artificial Intelligence and 3D cameras, the Cattle Feed InTake (CFIT) project, launched by VikingGenetics, will measure how much feed a cow consumes. With this data, farmers can select for more feed efficient and climate friendly cows. The total budget for the project is 3 million Euros (approx. 22.5 million DKK), granted by different entities participating on it.
Today, we know the composition of the feed, but so far, the amount of feed that each cow consumes has only been possible to measure on experimental farms with expensive equipment. The research includes the development of more affordable technology. Analyses of the collected data on cows' weight, feed intake and milk production will contribute to identifying which cows have the most efficient energy intake. The overall goal is to create clear management strategies to improve dairy farming.
- The potential of this project is huge and can change the entire mindset on how to fit the cows in a modern cattle production, says head of project Jan Lassen, Senior Research Manager at VikingGenetics. - With the 3D cameras we will provide more objective monitoring of the cows, better feed efficiency per cow, improvements in daily operations and a more resource efficient production, he adds.
Sustainable milk production
VikingGenetics will use the recorded data to rank the Viking bulls to ensure that the best genes are passed on. As such, the offspring will be even more resource efficient than the previous generation. There are 1.5 billion cows worldwide, and VikingGenetics hopes that the project will strengthen the company’s market position and assure the position of the Nordic countries even more on the world map for sustainable milk production.
- Having individual feed intake records on commercial dairy farms can be a game-changer in modern dairy cattle management. It is something we have always dreamt about, says Professor Nic Friggens from the French research unit MoSAR under the French National Institute for Agriculture, Food and Environment (INRAE), one of the international partners in the project.
QGG’s contribution to the project
Center for Quantitative Genetics and Genomics (QGG) at Aarhus University in Foulum is the main research partner of the CFIT project with a total of 43 person-months for senior researchers and 110 person-months of postdoc work planned in the project. QGG research will develop the statistical models to analyze 3D camera image data to predict the feed efficiency, negative energy balance, lameness, and early warning of sick animals. In collaboration with SEGES, QGG will develop genomic evaluation models for CFIT traits, and, in collaboration with ANIS, evaluate economics of CFIT traits in the breeding goal.
At QGG, senior researchers Peter Løvendahl and Goutam Sahana are looking forward to get started.
- The project will allow large-scale recording of individual cow feed intake. This will be a game changer in dairy cattle production, going from optimization of management on herd level to optimization for the individual cow. The project will use 3D camera technology to create crucial knowledge not yet available for genetic selection and change dairy cattle management, Goutam Sahana explains, and continues, - CFIT will benefit dairy cattle production through better productivity, resource efficiency, reduced climate impact and improved animal welfare.
- Today we do not know how much an individual cow eats in a commercial production herd, he elaborates, and adds:
- QGG will develop a model to estimate the individual cow’s feed intake from 3D camera data. This is very important knowledge, because knowing the individual cow’s feed in-take allows calculating feed efficiency and farmer’s profit at cow level. We will also develop models for feed efficiency, detection of drop in feed intake, which indicates a sick animal, and lameness. This will give breeders an opportunity to select animal for these efficiency traits, which is not possible so far due to lack of large-scale individual cow level data.
QGG research will contribute in both developing genomic selection models and economic evaluation of the CFIT traits. The CFIT research questions are novel and will produce several, high quality research articles.
- The project outcomes are expected to have significant impact on the industry of dairy cattle genetic improvement and animal welfare. It is very ambitious, adds Peter Løvendahl.
Besides VikingGenetics, the project has also the participation of
- QGG and ANIS from Aarhus University, Foulum, who will calculate feed efficiency and genetics;
- The Agriculture and Food Innovation Department SEGES, responsible for the implementation of software by the farmers,
- SIMHERD A/S, who provides tools for calculating the project's economic value.
For more information, please contact
Jan Lassen, Senior Project Manager, VikingGenetics
Tel.: +45 2040 7441 Email: email@example.com
Goutam Sahana, Senior researcher, Center for Quantitative Genetics and Genomics (QGG)
Tel.: +45 8715 7501 Email: firstname.lastname@example.org