Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle

摘要

A group of milk components that has shown potentialto be predicted with milk spectra is milk minerals.Milk minerals are important for human health and cowhealth. Having an inexpensive and fast way to measuremilk mineral concentrations would open doors for research,herd management, and selective breeding. Thefirst aim of this study was to predict milk mineralswith infrared milk spectra. Additionally, milk mineralswere predicted with infrared-predicted fat, protein,and lactose content. The second aim was to performa genetic analysis on infrared-predicted milk minerals,to identify QTL, and estimate variance components.For training and validating a multibreed predictionmodel for individual milk minerals, 264 Danish Jerseycows and 254 Danish Holstein cows were used. Partialleast square regression prediction models were built forCa, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on80% of the cows, selected randomly. Prediction modelswere externally validated with 8 herds based on theremaining 20% of the cows. The prediction models wereapplied on a population of approximately 1,400 DanishHolstein cows with 5,600 infrared spectral records and1,700 Danish Jersey cows with 7,200 infrared spectralrecords. Cows from this population had 50k imputedgenotypes. Prediction accuracy was good for P andCa, with external R~2 ≥ 0.80 and a relative predictionerror of 5.4% for P and 6.3% for Ca. Prediction wasmoderately good for Na with an external R~2 of 0.63,and a relative error of 18.8%. Prediction accuracies ofmilk minerals based on infrared-predicted fat, protein,and lactose content were considerably lower than thosebased on the infrared milk spectra. This shows thatthe milk infrared spectrum contains valuable informationon milk minerals, which is currently not used.Heritability for infrared-predicted Ca, Na, and P variedfrom low (0.13) to moderate (0.36). Several QTL forinfrared-predicted milk minerals were observed thathave been associated with gold standard milk mineralspreviously. In conclusion, this study has shown infraredmilk spectra were good at predicting Ca, Na, and Pin milk. Infrared-predicted Ca, Na, and P had low tomoderate heritability estimates.