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 (CY DM ) or fresh (CY FRESH ) 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 CY DM predictions showed coefficient of determination (R 2 ) values up to 0.92 and 0.87, and RS y,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 CY DM [R 2 = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CY FRESH (R 2 = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R 2 ≥ 0.70, RPD ≥1.8), which enable quantitative prediction.

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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 (R 2 ) 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 (R 2 = 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 R 2 > 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.

We report here the cloning and functional analysis of a novel homologue of the mitochondrial carriers predominantly expressed in the central nervous system and referred to as BMCP1 (brain mitochondrial carrier protein-1). The predicted amino acid sequence of this novel mitochondrial carrier indicates a level of identity of 39, 31, or 30%, toward the mitochondrial oxoglutarate carrier, phosphate carrier, or adenine nucleotide translocator, respectively, and a level of identity of 34, 38, or 39% with the mitochondrial uncoupling proteins UCP1, UCP2, or UCP3, respectively. Northern analysis of mouse, rat, or human tissues demonstrated that mRNA of this novel gene is mainly expressed in brain, although it is 10-30-fold less expressed in other tissues. In situ hybridization analysis of brain showed it is particularly abundant in cortex, hippocampus, thalamus, amygdala, and hypothalamus. Chromosomal mapping indicates that BMCP1 is located on chromosome X of mice and at Xq24 in man. Expression of the protein in yeast strongly impaired growth rate. Analysis of respiration of total recombinant yeast or yeast spheroplasts and in particular of the relationship between respiratory rate and membrane potential of yeast spheroplasts revealed a marked uncoupling activity of respiration, suggesting that although BMCP1 sequence is more distant from the uncoupling proteins (UCPs), this protein could be a fourth member of the UCP family.

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).