The use of multidimensional methods of analysis of the intra-breed variability of fat content in milk of dairy cattle

Abstract

The analysis included data on the origin and milk productivity of 109 first-born red steppe breed, which were descendants of five bulls-offspring (Narcissus, Topol, Tangens, Neptune, and Orpheus) and were kept in SE “Plemproductor Stepove” (Mykolaiv region, Ukraine ) during the years 2001–2014. The purpose of this study was to analyze the fat content of milk during different months of lactation (MFP1, MFP2,…, MFP10) to determine latent variables that best describe the variability of dairy cows' productivity in this herd. High correlation estimates of fat milk scores in different lactation months have been established. According to the results of the Principal Component Analysis, based on the (co)variation matrix of fat content in milk, three new variables (PC1, PC2, and PC3) were identified, which accounted for about 82% of the variability of the original data. The First Main Component (PC1) explained 53.5%, Second (PC2) – 17.7%, and Third (PC3) – 10.6% of the variability of the original data, respectively. PC1 was highly correlated with MFP4-MFP10 and, thus, it distributed the animals according to their fat content level. PC2 was highly positively correlated with MFP8-MFP10 but highly negatively correlated with M FP1-MFP3 and thus it shows the rate of increase in fat content in milk during lactation. PC3 characterizes the variability of fat content in milk during the first and second half of lactation. The Linear Discriminant Analysis found that the MFP1-MFP2 and MFP9-MFP10 scores contributed most to the discrimination among the five subpopulations. The individual identification of the offspring groups of different bulls according to the cross-check classification ranged from 44.4% (Topol) to 87.5% (Orpheus) of cows, which were correctly assigned to their own group.