Prediction of colour of European Emmental cheeses by using near infrared spectroscopy: a feasibility study

Near infrared (NIR) spectroscopy was used to predict colour of European Emmental cheese samples. Colour values (L, a and b) were measured on 20 Emmental cheese samples using a Hunter-lab D25-D-2 optical head in the system according to Hunter to determine L (brightness), a (green-red component) and b (blue-yellow component). The diffuse reflectance of the investigated cheeses was also determined by a Büchi NIR Lab N-200 spectrometer using a rotating measuring cell in the range of 1000–2500 nm. The best results for L-value (squared correlation coefficient (R ²) = 0.56, root mean square error of cross-validation (RMSECV) = 0.76, ratio of prediction deviation (RPD) = 1.89 and range error ratio (RER) = 7.91), a-value (R ² = 0.72, RMSECV = 0.15, RPD = 1.98 and RER = 7.6) and b-value (R ² = 0.82, RMSECV = 0.52, RPD = 2.56 and RER = 9.42) were obtained when the first 12 principal components (PCs) of the principal component analysis (PCA) applied on normalised NIR spectra were used. It can be concluded that NIR spectroscopy could be used to predict b-value. The a- and L-values can also be predicted from NIR technique with approximate quantitative prediction.     

Short communication: Confirmation of candidate causative variants on milk composition and cheesemaking properties in Montbéliarde cows

In a previous study, we identified candidate causative variants located in 24 functional candidate genes for milk protein and fatty acid composition in Montbéliarde, Normande, and Holstein cows. We designed these variants on the custom part of the EuroG10K BeadChip (Illumina Inc., San Diego, CA), which is routinely used for genomic selection analyses in French dairy cattle. To validate the effects of these candidate variants on milk composition and to estimate their effects on cheesemaking properties, a genome-wide association study was performed on milk protein, fatty acid and mineral composition, as well as on 9 cheesemaking traits (3 laboratory cheese yields, 5 coagulation traits, and milk pH). All the traits were predicted from midinfrared spectra in the Montbéliarde cow population of the Franche-Comté region. A total of 194 candidate variants located in 24 genes and 17 genomic regions were imputed on 19,862 cows with phenotypes and genotyped with either the BovineSNP50 (Illumina Inc.) or the EuroG10K BeadChip. We then tested the effect of each SNP in a mixed linear model including random polygenic effects estimated with a genomic relationship matrix. We confirm here the effects of candidate causative variants located in 17 functional candidate genes on both cheesemaking properties and milk composition traits. In each candidate gene, we identified the most plausible causative variant: 4 are missense in the ALPL, SLC26A4, CSN3, and SCD genes, 7 are located in 5′UTR (AGPAT6), 3′ untranslated region (GPT), or upstream (CSN1S1, CSN1S2, PAEP, DGAT1, and PICALM) regions, and 6 are located in introns of the SLC37A1, MGST1, CSN2, BRI3BP, FASN, and ANKH genes.