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UID:1059@biotech.technion.ac.il
DTSTART;TZID=Asia/Jerusalem:20210901T173000
DTEND;TZID=Asia/Jerusalem:20220202T164952
DTSTAMP:20220512T124718Z
URL:https://biotech.technion.ac.il/events/studying-the-relations-between-t
 he-composition-of-bovine-milk-protein-of-individual-cows-and-the-main-func
 tional-properties-essential-for-the-production-of-dairy-products-2/
SUMMARY:Studying the relations between the composition of bovine milk prote
 in of individual cows and the main functional properties essential for the
  production of dairy products
DESCRIPTION:The dairy industry is one of the largest food industries and is
  estimated with annual revenue of hundreds of billions of dollars. Cow mil
 k composition varies between individual cows\, during lactation period\, a
 nd due to physical and environmental conditions. For various dairy product
 s (such as: fluid milk\, hard and soft cheeses\, yogurts and dairy dessert
 s) different milk compositions are required depending on the properties of
  the final product and its production process. Yet\, to date\, no prescree
 ning of the milk according to the target product is being done. This proje
 ct is part of the “Food Big Data-IOT” consortium\, in a work package a
 imed at developing an AI-based tool that will allow prediction of milk fun
 ctionality from the genetics stage of cows\, by sorting cows according to 
 the suitability of their milk\, and during milking\, to enable efficient r
 outing of milk to final products of three main categories: hard cheeses\, 
 acid cheese products and milk drinks/desserts. Within this project\, we ha
 ve thus far performed comprehensive characterization of hundreds of raw mi
 lk samples\, both for the composition of the milk and for its functionalit
 y during acid-curd formation\, from individual cows and from herds\, for t
 he purpose of creating a broad database. We used the database to build a p
 rediction model using multi-parameter linear regression. The total protein
  concentration has been found to have the most significant effect in all t
 he models developed. Average casein micelle diameter\, acidity\, and lacto
 se concentration have been found to be the second most significant factors
  affecting yield\, gelation time\, and curd firmness\, respectively. In pa
 rallel\, we collaborate with the team of Prof Avi Gal in developing an AI 
 based model.
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