Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy

Effects of different storage conditions, the farm and the stage of lactation on renneting parameters of goat milk investigated using the Formagraph method

This study evaluated the effect of storage on renneting properties of goat milk investigated using the Formagraph method. Milk samples from 169 goats in three farms (F1, F2 and F3) were analysed during an entire lactation (45, 75, 105, 135 and 165 days in milking DIM), to obtain renneting parameters, both from fresh milk and after storage with Bronopol and freezing at −20°C and −80°C. As regards fresh milk, mean values of clotting time were between 12·51 (45 DIM) and 13·29 min (105 DIM and F2), the curd firming time between 1·77 (45 DIM) and 2·15 min (F1) and curd firmness between 42·09 (165 DIM) and 49·55 mm (45 DIM). No statistical difference was recorded after storage. After regression analysis, all prediction models showed significance value at P<0·001 with the highest R2 value for clotting time, 0·710 (fresh vs. frozen milk at −20°C), and the lowest for clot firmness, 0·281 (fresh vs. frozen milk at −80°C). Results demonstrated that assessment of goat milk coagulation properties using the Formagraph method is also achievable after freezing or Bronopol addition.

Mid-infrared spectroscopy predictions as indicator traits in breeding programs for enhanced coagulation properties of milk

The aims of this study were to investigate variation of milk coagulation property (MCP) measures and their predictions obtained by mid-infrared spectroscopy (MIR), to investigate the genetic relationship between measures of MCP and MIR predictions, and to estimate the expected response from a breeding program focusing on the enhancement of MCP using MIR predictions as indicator traits. Individual milk samples were collected from 1,200 Brown Swiss cows (progeny of 50 artificial insemination sires) reared in 30 herds located in northern Italy. Rennet coagulation time (RCT, min) and curd firmness (a(30), mm) were measured using a computerized renneting meter. The MIR data were recorded over the spectral range of 4,000 to 900 cm(-1). Prediction models for RCT and a(30) based on MIR spectra were developed using partial least squares regression. A cross-validation procedure was carried out. The procedure involved the partition of available data into 2 subsets: a calibration subset and a test subset. The calibration subset was used to develop a calibration equation able to predict individual MCP phenotypes using MIR spectra. The test subset was used to validate the calibration equation and to estimate heritabilities and genetic correlations for measured MCP and their predictions obtained from MIR spectra and the calibration equation. Point estimates of heritability ranged from 0.30 to 0.34 and from 0.22 to 0.24 for RCT and a(30), respectively. Heritability estimates for MCP predictions were larger than those obtained for measured MCP. Estimated genetic correlations between measures and predictions of RCT were very high and ranged from 0.91 to 0.96. Estimates of the genetic correlation between measures and predictions of a(30) were large and ranged from 0.71 to 0.87. Predictions of MCP provided by MIR techniques can be proposed as indicator traits for the genetic enhancement of MCP. The expected response of RCT and a(30) ensured by the selection using MIR predictions as indicator traits was equal to or slightly less than the response achievable through a single measurement of these traits. Breeding strategies for the enhancement of MCP based on MIR predictions as indicator traits could be easily and immediately implemented for dairy cattle populations where routine acquisition of spectra from individual milk samples is already performed.