Principal components approach for estimating heritability of mid-infrared spectrum in bovine milk

Mid-Infrared (MIR) spectrometry can be used for prediction of milk composition. The data included 9,663 records on 1,937 cows in 1 to 12 parity recorded from April 2005 to May 2006. Each sample was scanned by MilkoScan FT6000 into 1,060 points. Principal components approach (PCA) indicated that 48 principal components (PC) described 99.02% of information. The next analysis considered PC constructed for 2,850 first lactation records of 738 cows in 7 breeds from 26 herds. PC were analyzed by multi-trait REML using the canonical transformation. Effects included were herd *test date, lactation stage, permanent environmental and animal. Heritabilities varied from 0.005% to 57.20% for different pin numbers. Spectral regions with heritability greater than 5% were located between 1 to 181; 194 to 558 and 709 to 1,060 pin numbers. PCA involving points in those regions demonstrated that only 9 PC explained 99.23% of information. MIR spectrum contains specific regions with substantial genetic information potentially useful for selecting improved milk quality directly on spectral data.