These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Genetic and environmental relationships of different measures of individual cheese yield and curd nutrients recovery with coagulation properties of bovine milk.
    Author: Cecchinato A, Bittante G.
    Journal: J Dairy Sci; 2016 Mar; 99(3):1975-1989. PubMed ID: 26805996.
    Abstract:
    The aim of this study was to elucidate the relationships between various cheesemaking-related traits, namely the well-known traditional milk coagulation properties (MCP), the new curd firming and syneresis traits, the cheese yield, and the curd nutrient recoveries or whey losses (all measured at the individual level). Data were obtained from 1,167 Brown Swiss cows reared in 85 herds. A 2-L milk sample was collected once from each animal and assessed for 10 phenotypes related to changes in curd firmness (CF) over time, plus 7 cheesemaking traits. The CF-related traits included 4 traditional single-point lactodynamographic properties [rennet coagulation time (RCT, min); time to a CF of 20mm, min; and the CF 30 and 45 min after rennet addition (a30 and a45, respectively)], 4 parameters used to model the 360 CF data recorded over time for each milk sample [the potential asymptotic CF at infinite time (CFP, mm); the CF instant rate constant, % × min(-1); the syneresis instant rate constant, % × min(-1); and the RCT obtained from modeling individual samples], and 2 traits calculated from individual equations [the maximum CF(CFmax, mm); and the time at CFmax, min]. The cheesemaking traits included 3 cheese yield traits (weights of the fresh curd, curd solids and curd moisture as percent of the weights of the processed milk) and 4 milk nutrient recoveries in the curd (calculated as the percent ratios between a given nutrient in the curd versus that in the processed milk). Bayesian methodology-based multivariate analyses were used to estimate the phenotypic, additive genetic, herd/date, and residual relationships between the aforementioned traits, whereas statistical inferences were based on the marginal posterior distributions of the parameters of concern. The a45, CFP, and CFmax traits were genetically associated with all of the percent cheese yield traits (the additive genetic correlations varied from 0.752 to 0.855 for a45; 0.496 to 0.583 for CFP; and 0.750 to 0.801 for CFmax) and the nutrient recovery traits (additive genetic correlations varied from 0.296 to 0.901 for a45; 0.428 to 0.697 for CFP; and 0.412 to 0.941 for CFmax). Moreover, the nutrient recoveries for fat, solids, and energy exhibited large additive genetic correlations with the other coagulation and curd firming traits. In particular, recovery of protein and fat were found to be powerful instruments for understanding the relationships between milk technological properties and cheese quantity or quality. We observed only weak genetic relationships with the milk quality and MCP traits, suggesting that the highly heritable trait of protein recovery should perhaps be included as a genetic index when seeking to improve cheesemaking efficiency at the population level. In contrast, we found that fat recovery exhibited moderate genetic variation and could be improved through the CF over time traits, especially using those recorded during the late phase of the curd firming process. Moreover, our results demonstrated that the traditional MCP have limited relevance for predicting individual cheese yield. Therefore, their use for this purpose in the dairy industry and breeding programs seems questionable.
    [Abstract] [Full Text] [Related] [New Search]