Predicting milk phosphorus content based on genotypic and milk infrared data

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the World Congress on Genetics Applied to Livestock Production
Subtitle of host publication Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1
PublisherWCGALP
Number of pages5
Publication statusPublished - Feb 2018
Event11th World Congress on Genetics Applied to Livestock Production - Auckland, New Zealand
Duration: 11 Feb 201816 Feb 2018

Conference

Conference11th World Congress on Genetics Applied to Livestock Production
CountryNew Zealand
CityAuckland
Period11/02/1816/02/18

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