Predicting milk phosphorus content based on genotypic and milk infrared data rlands A cheap and accurate method for estimating milk P content of individual cows would better allow farmers to feed their cows according to their P requirements. This study aimed at predicting milk P content based on different information sources: routinely recorded milk composition traits, genotypic data and infrared spectra. Data of 1400 Dutch Holstein-Friesian cows was used. Prediction models were developed using the Partial Least Squares Regression and validated using test set validation. Prediction of milk P content based on protein content has an R2v of 41%. Prediction based on genotypes for the DGAT1 K232A polymorphism and the SNP rs29019625 (BTA1, close to SLC37A1) result in R2v of 8.7% and 4.7%, respectively. Based on the infrared spectrum the R2v for milk P content was 84%. We quantified that phosphorus efficiency can be improved with 17% when feeding cows based on the developed infrared prediction for milk P content. Key words: milk phosphorus, infrared, prediction, efficiency.

Henk Bovenhuis, Ibrahim Jibrila, Jan Dijkstra

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1, , 534, 2018
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