Mid-infrared prediction of milk titratable acidity and its genetic variability in first-parity cows

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability ... [more ▼]

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability of this trait on a large scale, mid-infrared (MIR) chemometric methods were used to predict TA. A total of 507 milk samples collected in the Walloon Region of Belgium from individual cows were analyzed using a MIR spectrometer. TA was recorded as Dornic degree. An equation to predict TA from milk MIR spectrum was developed using partial least squared regression after a first derivative pre-treatment applied to the spectra to correct the baseline drift. During the calibration process, 45 outliers were detected and removed from the calibration set. The TA mean of the final calibration set was 16.62 (standard deviation (SD) = 1.80). The coefficient of determination (R²) was 0.82 for the calibration with a standard error (SE) of 0.76. A cross-validation (cv) was performed (R²cv = 0.81 with SEcv = 0.80). This equation was then applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated by REML using single-trait random regression animal test-day model. The dataset used included 33,717 records from 9,191 Holstein first-parity cows; the TA mean was 17.05 (SD = 1.35) and TA ranged from 12.83 to 20.87. Estimated daily heritabilities ranged from 0.43 at 5th day in milk to 0.59 at 215th day in milk indicating potential of selection. Further research will study phenotypic and genetic correlations between TA and milk production traits. [less ▲]

Genetic parameters for methane indicator traits based on milk fatty acids in cows

in Journal of Dairy Science (2012, July 18)

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue ... [more ▼]

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue is the development of easily obtainable indicators, because they would also allow estimating animal genetic variability of methane emission. Recently methane indicators were proposed using gas chromatrography based milk fatty acid composition. We derived these published methane indicators using 1100 calibration samples directly from mid-infrared (MIR).For the published indicator showing the highest relationship (R2 = 0.88) with Sulfur Hexafluoride 6 methane emission data, genetic parameters for this MIR based indicator were estimated by single trait random regression test-day models from 619,272 records collected from 2007 to 2011 on 71,188 Holstein cows in their first three lactations at Walloon region of Belgium. The average daily heritability was 0.35±0.01, 0.35±0.02 and 0.32±0.02 for the first three lactations, respectively. Similarly, the lactation heritability was 0.67±0.02, 0.72±0.03 and 0.62±0.03. As expected, methane production was higher during the peak milk production depicting the normal lactation curve. The largest differences between estimated breeding values (EBV) of sires having cows in production eructing the highest and the lowest methane content was 21.80, 22.75 and 24.89 kg per lactation for the first three parities, the variances of the EBV of the sires with daughters were 10.67, 12.46, 12.18 kg2. Results were similar for other indicators. This study suggested that methane indicator traits can be predicted by MIR. Genetic parameters also indicated a rather high heritability and genetic variability exist for these published indicators and consequently a potential high genetic variability of methane eructation by dairy cows. Therefore, these first finding might open new opportunities for animal selection programs that include the reduction of methane emission. [less ▲]

Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows

in Animal (2012), 6(10), 1694-1701

Mid-infrared predictions of cheese yield from bovine milk

in Book of Abstracts of the 62nd Annual Meeting of the European Association for Animal Production (2011, August)

Economically, cheese yield (CY) is very important. Todate, empirical or theoretical formulae allow estimating the theoretical CY from milk fat and casein or protein content of milk. It would be ... [more ▼]

Economically, cheese yield (CY) is very important. Todate, empirical or theoretical formulae allow estimating the theoretical CY from milk fat and casein or protein content of milk. It would be interesting to predict CY during milk recording directly without the need to estimate milk components. Through the BlueSel project, 157 milk samples were collected in Wallonia from individual cows and analyzed using a mid-infrared (MIR) MilkoScanFT6000 spectrometer. Individual laboratory cheese yields (ILCY) were determined for each sample and expressed as g of dry coagulum/100 g of milk dry matter. An equation to predict ILCY from MIR was developed using partial least squared regression (Winisi III). A first derivative pre-treatment of spectra was used to correct the baseline drift. To improve the repeatability of the spectral data, a file which contained the spectra of samples analyzed on 5 spectrometers was used during the calibration. During calibration, 23 outliers were detected a nd removed from the calibration set. The ILCY mean of the final calibration set was 63.9% with a SD of 11.2%. The calibration (C) coefficient of determination (R²) was equal to 0.76 with a standard error (SE) of calibration of 5.5%. A full cross-validation (CV) was preformed to assess the robustness. R²cv was 0.72 with a SECV of 6.0%. The similarity between R²c and R²cv as well as between SEC and SECV permits to consider robustness of the developed equation as good. Even if it is planned to improve the equation with additional samples, this first equation will permit to study ILCY in the Walloon dairy cattle. [less ▲]

Prediction of individual methane emission by dairy cattle from mid-infrared spectra

Conference (2010, July 14)