Predicting milk phosphorus content based on genotypic and milk infrared data

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

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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phosphorus
milk
prediction
cows
cow feeding
information sources
milk composition
least squares
Holstein
protein content
genetic polymorphism
farmers
genotype
testing

Cite this

Bovenhuis, H., Jibrila, I., & Dijkstra, J. (2018). Predicting milk phosphorus content based on genotypic and milk infrared data. In Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1 [534] WCGALP.
Bovenhuis, H. ; Jibrila, I. ; Dijkstra, J. / Predicting milk phosphorus content based on genotypic and milk infrared data. Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1. WCGALP, 2018.
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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.",
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Bovenhuis, H, Jibrila, I & Dijkstra, J 2018, Predicting milk phosphorus content based on genotypic and milk infrared data. in Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1., 534, WCGALP, 11th World Congress on Genetics Applied to Livestock Production, Auckland, New Zealand, 11/02/18.

Predicting milk phosphorus content based on genotypic and milk infrared data. / Bovenhuis, H.; Jibrila, I.; Dijkstra, J.

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

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

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T1 - Predicting milk phosphorus content based on genotypic and milk infrared data

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AU - Jibrila, I.

AU - Dijkstra, J.

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N2 - 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.

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M3 - Conference paper

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Bovenhuis H, Jibrila I, Dijkstra J. Predicting milk phosphorus content based on genotypic and milk infrared data. In Proceedings of the World Congress on Genetics Applied to Livestock Production: Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1. WCGALP. 2018. 534