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Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process
Authors:G. Bittante  C. Cipolat-GotetA. Cecchinato
Affiliation:Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro (PD), Italy
Abstract:Cheese yield (CY) is an important technological trait in the dairy industry, and the objective of this study was to estimate the genetic parameters of cheese yield in a dairy cattle population using an individual model-cheese production procedure. A total of 1,167 Brown Swiss cows belonging to 85 herds were sampled once (a maximum of 15 cows were sampled per herd on a single test day, 1 or 2 herds per week). From each cow, 1,500 mL of milk was processed according to the following steps: milk sampling and heating, culture addition, rennet addition, gelation-time recording, curd cutting, whey draining and sampling, wheel formation, pressing, salting in brine, weighing, and cheese sampling. The compositions of individual milk, whey, and curd samples were determined. Three measures of percentage cheese yield (%CY) were calculated: %CYCURD, %CYSOLIDS, and %CYWATER, which represented the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: RECFAT, RECPROTEIN, and RECSOLIDS, which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding nutrient in the milk. Energy recovery, RECENERGY, represented the energy content of the cheese versus that in the milk. For statistical analysis, a Bayesian animal model was implemented via Gibbs sampling. The effects of parity (1 to ≥4), days in milk (6 classes), and laboratory vat (15 vats) were assigned flat priors; those of herd-test-date, animal, and residual were given Gaussian prior distributions. Intra-herd heritability estimates of %CYCURD, %CYSOLIDS, and %CYWATER ranged from 0.224 to 0.267; these were larger than the estimates obtained for milk yield (0.182) and milk fat content (0.122), and similar to that for protein content (0.275). Daily cheese yields showed heritability estimates similar to those of daily milk yield. The trait %CYWATER showed a highly positive genetic correlation with %CYSOLIDS (0.87), whereas their phenotypic correlation was moderate (0.37), and the fat and protein contents of milk showed high genetic correlations with %CY traits. The heritability estimates of RECPROTEIN and RECFAT were larger (0.490 and 0.208, respectively) than those obtained for the protein and fat contents of milk, and the genetic relationships between RECPROTEIN and RECFAT with milk protein and fat content were low or moderate; RECPROTEIN and RECFAT were moderately correlated with the %CY traits and highly correlated with RECSOLIDS and RECENERGY. Both RECSOLIDS and RECENERGY were heritable (0.274 and 0.232), and showed high correlations with each other (0.96) and with the %CY traits (0.83 to 0.97). Together, these findings demonstrate the existence of economically important, genetically determined variability in cheese yield that does not depend solely upon the fat and protein contents of milk, but also relies on the ability of the coagulum to retain the highest possible proportions of the available protein, fat, and water. Exploitation of this interesting genetic variation does not seem to be feasible through direct measurement of the phenotype in cows at the population level. Instead, further research is warranted to examine possible means for indirect prediction, such as through assessing the mid-infrared spectra of milk samples.
Keywords:individual cheese yield   fat and protein recovery   whey loss   genetic parameter
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