Short communication: Predictive ability of Fourier-transform mid-infrared spectroscopy to assess CSN genotypes and detailed protein composition of buffalo milk

• Published in: Journal of dairy science Vol. 98; no. 9; pp. 6583 - 6587
• Main Authors: Bonfatti, V., Cecchinato, A., Carnier, P.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.09.2015
• Subjects: Animals; buffalo milk; Buffaloes - genetics; casein fractions; Caseins - analysis; Denmark; Genotype; Milk - chemistry; Phenotype; protein composition; spectroscopy; Spectroscopy, Fourier Transform Infrared - methods; Whey Proteins - analysis; Denmark; buffalo milk; spectroscopy; protein composition; casein fractions
• ISSN: 0022-0302; 1525-3198
• DOI: 10.3168/jds.2015-9730

The aim of this work was to test the applicability of Fourier-transform mid-infrared spectroscopy (FT-MIR) for the prediction of the contents of casein (CN) and whey protein fractions in buffalo milk. Buffalo milk samples spectra were collected using a MilkoScan FT2 (Foss, Hillerød, Denmark) over the spectral range from 5,000 to 900 wavenumber × cm−1. Contents of protein fractions, as well as CSN1S1 and CSN3 genotypes, were assessed by reversed phase HPLC. The highest coefficients of determination in cross-validation (1 − VR) were obtained for the contents (g/L of milk) of total protein and CN (1 − VR=0.92), followed by the content of β-CN, total whey protein, and αS2-CN (1 − VR of 0.87, 0.77, and 0.63, respectively). Conversely, contents of αS1-CN, γ-CN, glycosylated-κ-CN, total κ-CN, and whey protein fractions were predicted with poor accuracy (1 − VR <0.51). When protein fractions were expressed as percentages to total protein, 1 − VR values were never greater than 0.61 (β-CN). Only 56 and 70% of the observations were correctly classified by discriminant analysis in each of 2 groups of CSN1S1 and CSN3 genotypes, respectively. Results showed that FT-MIR spectroscopy is not applicable when prediction of detailed milk protein composition with high accuracy is required. Predictions may play a role as indicator traits in selective breeding, if the genetic correlation between FT-MIR predictions and measures of milk protein composition are high enough and predictions of protein fraction contents are sufficiently independent from the predicted total protein content.