%0 Journal Article %1 Soyeurt20101722 %A Soyeurt, H. %A Misztal, I. %A Gengler, N. %D 2010 %J Journal of Dairy Science %K 2010 dairy_cattle %N 4 %P 1722 - 1728 %R http://dx.doi.org/10.3168/jds.2009-2614 %T Genetic variability of milk components based on mid-infrared spectral data %U http://www.sciencedirect.com/science/article/pii/S0022030210001463 %V 93 %X The aim of this study was to estimate the genetic parameters of the mid-infrared (MIR) milk spectrum represented by 1,060 data points per sample. The dimensionality of traits was reduced by principal components analysis. Therefore, 46 principal components describing 99.03% of the phenotypic variability were used to create 46 new traits. Variance components were estimated using canonical transformation. Heritability ranged from 0 to 0.35. Twenty-five out of 46 studied traits showed a permanent environment variance greater than genetic variance. Eight traits showed heritability greater than 0.10. Variances of original spectral traits were obtained by back transformation. Heritabilities for each spectral data points ranged from 0.003 to 0.42. In particular, 3 \MIR\ regions showing moderate to high heritability estimates were of potential genetic interest. Heritabilities for specific wave numbers, linked with common milk traits (e.g., lipids, lactose), were similar to those estimated for these traits. This research confirms the genetic variability of the \MIR\ milk spectrum and, therefore, the genetic variation of milk components. The objective of this study was to better understand the genetics of milk composition and, maybe in the future, to select animals to improve milk quality.

@article{Soyeurt20101722, abstract = {The aim of this study was to estimate the genetic parameters of the mid-infrared (MIR) milk spectrum represented by 1,060 data points per sample. The dimensionality of traits was reduced by principal components analysis. Therefore, 46 principal components describing 99.03% of the phenotypic variability were used to create 46 new traits. Variance components were estimated using canonical transformation. Heritability ranged from 0 to 0.35. Twenty-five out of 46 studied traits showed a permanent environment variance greater than genetic variance. Eight traits showed heritability greater than 0.10. Variances of original spectral traits were obtained by back transformation. Heritabilities for each spectral data points ranged from 0.003 to 0.42. In particular, 3 \{MIR\} regions showing moderate to high heritability estimates were of potential genetic interest. Heritabilities for specific wave numbers, linked with common milk traits (e.g., lipids, lactose), were similar to those estimated for these traits. This research confirms the genetic variability of the \{MIR\} milk spectrum and, therefore, the genetic variation of milk components. The objective of this study was to better understand the genetics of milk composition and, maybe in the future, to select animals to improve milk quality. }, added-at = {2016-05-15T21:36:13.000+0200}, author = {Soyeurt, H. and Misztal, I. and Gengler, N.}, biburl = {https://www.bibsonomy.org/bibtex/2aef7bd79c1da792fad9f4772a0418781/uga.abgg}, doi = {http://dx.doi.org/10.3168/jds.2009-2614}, interhash = {c46693271bff55f5f6aa32a82df9c656}, intrahash = {aef7bd79c1da792fad9f4772a0418781}, issn = {0022-0302}, journal = {Journal of Dairy Science }, keywords = {2010 dairy_cattle}, number = 4, pages = {1722 - 1728}, timestamp = {2016-05-15T21:36:13.000+0200}, title = {Genetic variability of milk components based on mid-infrared spectral data }, url = {http://www.sciencedirect.com/science/article/pii/S0022030210001463}, volume = 93, year = 2010 }