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Collecting poultry data is essential to improve production. Thatโs even more important when discussing quantitative genetics and genomics of complex traits. This research allows us to apply and develop efficient statistical learning methods for analyzing genomic data. We can integrate this and sensor-generated data into machine-learning algorithms for precision poultry farming, such as feeding behavior genetics. In this episode, I talk to Dr. Anderson Alves about his recent genomics, technology, and machine learning research to improve poultry production. We also discuss how poultry can progress toward more efficient and sustainable production in the next few years.
โI see in the future a promising opportunity to use image-based classification projections, especially the animal weight and the animal walkability.โ - Dr. Anderson Alves
๐ช๐ต๐ฎ๐ ๐๐ผ๐ ๐๐ถ๐น๐น ๐น๐ฒ๐ฎ๐ฟ๐ป:
Dr. Anderson Alves is a statistical geneticist working as a Research Associate at the University of Wisconsin-Madison. He has been leading different research projects at the Rosa Lab in partnership with Cobb Vantress for dissecting the genetic basis of feeding efficiency and feeding behavior in broilers. Dr. Alves is originally from Brazil, receiving a B.S. and an M.S. degree in Animal Science and a Ph.D. in Animal Breeding and Genetics. Dr. Alves is broadly interested in the application and development of efficient statistical learning methods for the analysis of livestock data, with a focus on the genetics and genomics of complex traits in different domestic species, such as dairy goats and sheep, beef cattle, and broiler chickens. He also integrates machine learning algorithms and other sensor-generated data in precision livestock farming projects, such as for high-throughput phenotyping, early prediction of individual performance, and real-time monitoring of mortality risk.
๐๐ถ๐๐๐ฒ๐ป ๐ผ๐ป ๐๐ฝ๐ฝ๐น๐ฒ ๐ฃ๐ผ๐ฑ๐ฐ๐ฎ๐๐๐, ๐ฆ๐ฝ๐ผ๐๐ถ๐ณ๐ ๐ผ๐ฟ ๐ฎ๐ป๐ ๐บ๐ฎ๐ท๐ผ๐ฟ ๐ฝ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ.
The Poultry Podcast Show is trusted and supported by innovative companies like:
- JBI (https://www.jbidistributors.com/animal-producers-biosecurity/)
- Protekta (https://protekta.com/product-category/poultry/)
- DSM (https://www.dsm.com/anh/species/poultry.html)
- Adisseo (http://www.adisseo.com/)
- AB Vista (http://www.abvista.com/)
By Wisenetix4.7
77 ratings
Collecting poultry data is essential to improve production. Thatโs even more important when discussing quantitative genetics and genomics of complex traits. This research allows us to apply and develop efficient statistical learning methods for analyzing genomic data. We can integrate this and sensor-generated data into machine-learning algorithms for precision poultry farming, such as feeding behavior genetics. In this episode, I talk to Dr. Anderson Alves about his recent genomics, technology, and machine learning research to improve poultry production. We also discuss how poultry can progress toward more efficient and sustainable production in the next few years.
โI see in the future a promising opportunity to use image-based classification projections, especially the animal weight and the animal walkability.โ - Dr. Anderson Alves
๐ช๐ต๐ฎ๐ ๐๐ผ๐ ๐๐ถ๐น๐น ๐น๐ฒ๐ฎ๐ฟ๐ป:
Dr. Anderson Alves is a statistical geneticist working as a Research Associate at the University of Wisconsin-Madison. He has been leading different research projects at the Rosa Lab in partnership with Cobb Vantress for dissecting the genetic basis of feeding efficiency and feeding behavior in broilers. Dr. Alves is originally from Brazil, receiving a B.S. and an M.S. degree in Animal Science and a Ph.D. in Animal Breeding and Genetics. Dr. Alves is broadly interested in the application and development of efficient statistical learning methods for the analysis of livestock data, with a focus on the genetics and genomics of complex traits in different domestic species, such as dairy goats and sheep, beef cattle, and broiler chickens. He also integrates machine learning algorithms and other sensor-generated data in precision livestock farming projects, such as for high-throughput phenotyping, early prediction of individual performance, and real-time monitoring of mortality risk.
๐๐ถ๐๐๐ฒ๐ป ๐ผ๐ป ๐๐ฝ๐ฝ๐น๐ฒ ๐ฃ๐ผ๐ฑ๐ฐ๐ฎ๐๐๐, ๐ฆ๐ฝ๐ผ๐๐ถ๐ณ๐ ๐ผ๐ฟ ๐ฎ๐ป๐ ๐บ๐ฎ๐ท๐ผ๐ฟ ๐ฝ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ.
The Poultry Podcast Show is trusted and supported by innovative companies like:
- JBI (https://www.jbidistributors.com/animal-producers-biosecurity/)
- Protekta (https://protekta.com/product-category/poultry/)
- DSM (https://www.dsm.com/anh/species/poultry.html)
- Adisseo (http://www.adisseo.com/)
- AB Vista (http://www.abvista.com/)

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