Mid-infrared spectrometry prediction of the cheese-making properties of raw Montbéliarde milks from herds and cheese dairy vats used for the production of Protected Designation of Origin and Protected Geographical Indication cheeses in Franche-Comté.

Franche-Comté is the primary producing region of Protected Designation of Origin cheeses in France. Normally, mid-infrared (MIR) prediction models for cheese-making property (CMP) traits are developed using individual bovine milks. However, considering the requests of all actors in the dairy sector, the present study aimed to assess the feasibility of MIR spectroscopy to develop CMP equations of Montbéliarde herd and dairy vat milks. For this purpose, 22 CMP traits were analyzed on samples collected in 2016 (half in February-March and half in May-June) from 100 commercial herds and 70 dairy vats (55 cheese dairies) located in Franche-Comté. These characteristics included 11 rennet coagulation traits and 8 lactic acidification traits measured in either soft cheese or pressed cooked cheese conditions and 3 laboratory curd yields. Models of MIR prediction for each of the 22 CMP traits were built using partial least squares regression with external validation by dividing the data set into calibration (70%) and validation (30%) sets. We confirmed that the variability of milk traits depends largely on the production scale and is higher for individual milk than for herd milk and even higher for vat milk. The best prediction models were obtained in herd milk samples for curd yields expressed in dry matter or fresh, with a coefficient of determination (R2) in external validation of 0.78 and 0.77, respectively. As with individual milk, these traits are closely related to the gross composition of the milk and therefore easier to predict by MIR spectroscopy. However, these curd yield traits were poorly predicted (R2 = 0.58) in vat milk samples due to their lower variability. In herd milk samples, prediction models of other CMP traits were poorly accurate except for the ratio of the time to obtain a standard firmness to the rennet coagulation time in soft cheese or pressed cooked cheese conditions, which showed R2 > 0.66 in external validation. Such trait is important in qualifying the behavior of milk during cheese production. Prediction models of other CMP traits for either herd or vat milk samples had poor accuracy, and further work is needed to improve their performance.

Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows.

Assessing the cheese-making properties (CMP) of milks with a rapid and cost-effective method is of particular interest for the Protected Designation of Origin cheese sector. The aims of this study were to evaluate the potential of mid-infrared (MIR) spectra to estimate coagulation and acidification properties, as well as curd yield (CY) traits of Montbéliarde cow milk. Samples from 250 cows were collected in 216 commercial herds in Franche-Comté with the objectives to maximize the genetic diversity as well as the variation in milk composition. All coagulation and CY traits showed high variability (10 to 43%). Reference analyses performed for soft (SC) and pressed cooked (PCC) cheese technology were matched with MIR spectra. Prediction models were built on 446 informative wavelengths not tainted by the water absorbance, using different approaches such as partial least squares (PLS), uninformative variable elimination PLS, random forest PLS, Bayes A, Bayes B, Bayes C, and Bayes RR. We assessed equation performances for a set of 20 CMP traits (coagulation: 5 for SC and 4 for PCC; acidification: 5 for SC and 3 for PCC; laboratory CY: 3) by comparing prediction accuracies based on cross-validation. Overall, variable selection before PLS did not significantly improve the performances of the PLS regression, the prediction differences between Bayesian methods were negligible, and PLS models always outperformed Bayesian models. This was likely a result of the prior use of informative wavelengths of the MIR spectra. The best accuracies were obtained for curd yields expressed in dry matter (CYDM) or fresh (CYFRESH) and for coagulation traits (curd firmness for PCC and SC) using the PLS regression. Prediction models of other CMP traits were moderately to poorly accurate. Whatever the prediction methodology, the best results were always obtained for CY traits, probably because these traits are closely related to milk composition. The CYDM predictions showed coefficient of determination (R2) values up to 0.92 and 0.87, and RSy,x values of 3 and 4% for PLS and Bayes regressions, respectively. Finally, we divided the data set into calibration (2/3) and validation (1/3) sets and developed prediction models in external validation using PLS regression only. In conclusion, we confirmed, in the validation set, an excellent prediction for CYDM [R2 = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CYFRESH (R2 = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R2 ≥ 0.70, RPD ≥1.8), which enable 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.

Development and evaluation of a monoclonal antibody-based inhibition ELISA for the quantification of chymosin in solution.

Chymosin is the major enzyme of natural rennet, traditionally used in cheese making for its high milk-clotting activity. For technical reasons, an accurate characterization of rennet should include its total clotting activity and also its enzymatic composition. Monoclonal antibodies specific to chymosin were obtained from mice immunized with purified bovine chymosin, and an inhibition enzyme-linked immunosorbent assay (ELISA) was developed for the quantification of chymosin in solution. No cross-reactivity was observed with other milk-clotting enzymes commonly used in cheese making. The limit of detection and limit of quantification were 125 and 400 ng/mL, respectively. The values of precision within and among runs were 7.23 and 7.39%, respectively, and satisfying recovery, from 92 to 119%, was found for spiked samples. The inhibition ELISA was successfully applied to commercial rennets, and the results were consistent with those obtained using the standard chromatographic method (IDF 110: A, 1987).

Antipeptide antibodies recognizing plasmin sensitive sites in bovine beta-casein sequence.

To investigate plasmin activity in cheese, we produced antibodies to bovine beta-casein with controlled specificity, suitable as markers of the integrity of the major bonds involved in its initial breakdown. Sixteen rabbits were immunized with synthetic substitutes for six plasmin-sensitive peptides. Antisera raised to the peptides (f20-39), (f40-56), (f94-113), (f184-202), and (f193-209) recognized beta-casein in ACP-ELISA, Western-blot, and biosensor assays. Casein in vitro hydrolysis by plasmin or chymosin reduced the detection of these determinants in ACP-ELISA, in agreement with the enzymatic sensitivity of bonds included within the binding sites, or in their neighborhood. Antiserum to (f20-39) in particular allowed the specific detection of plasmin cleavage at the bond generating gamma1-CN. Antisera to C-terminus preferentially detected the cleavage by chymosin. Immunoassays using these antibodies would allow in situ monitoring of significant proteolysis events without bias originated in the secondary degradation of the released peptides.

Characterization of the heat treatment undergone by milk using two inhibition ELISAs for quantification of native and heat denatured alpha-lactalbumin.

Dairy industries are interested to know the heat treatment undergone by milk for controlling the quality of drinking milks or to control their heating systems. The purpose of this work was to develop a specific and sensitive technique for classification of the heat treatment a milk has been submitted to, without disposing of the original raw milk. For this purpose, alpha-lactalbumin was chosen as a bioindicator of heat treatment, and monoclonal antibodies specific for its native or heat-denatured form were raised and used in two inhibition ELISAs. ELISA allowed differentiation among raw, pasteurized, ultrahigh-temperature-treated, and sterilized milks without even having to know the alpha-lactalbumin concentration of the original raw milk. However, this technique was more suitable for intense heat treatments such as UHT treatment and sterilization because of the heat stability of alpha-lactalbumin.

[Determination of plasminogen in milk by an immunoenzymatic technic]. / Dosage du plasminogène dans le lait à l'aide d'une technique immunoenzymatique.

The ELISA assay was used to measure the plasminogen in milk. The results showed that plasminogen concentration was slightly higher than the corresponding enzymatic activity, which could be explained to the fact that several active sites of the enzyme are occupied by inhibitors or caseins. This work shows also that about 75% of plasminogen is bound to caseins.