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Milk coagulation properties (MCP) are important traits for profitable dairying. To improve MCP through animal breeding large quantity of routinely available data on MCP as well as existence of heritable genetic variation in these traits is required. Objectives of this study were to i) develop prediction equations for MCP through mid-infrared spectroscopy (MIRS) ii) apply equations to a spectra dataset of Holstein-Friesian cows, and iii) estimate variance components. Data for MCP and MIRS were available on 324 samples. Proportion of variation in external validation for RCT, k20, and a30 explained by equations was 0.45, 0.41 and 0.27, respectively. Heritability for MCP estimated from 9,867 spectra on 1,104 cows varied from 0.06 to 0.20; coefficient of genetic variation for MCP varied from 5.99 to 10.07, while genetic correlations between MCP and milk quality traits demonstrated positive relationships between MCP and milk composition.

Authors reviewed the genetic aspects of milk coagulation ability focusing on heritability and genetic correlation values and on the breed and milk protein loci effects on rennet coagulation time and curd firmness. The review discussed milk and cheese yield production all over the world concluding that the per capita retail demand for cheese will increase with a mean annual growth rate of 0.8%. Therefore, in the future, cheese production will continue to be one of the major livestock food products around the world. The development of new payment systems for milk considering the intrinsic value for cheese making ability, could be an important opportunity for select best individual within dairy cattle breeds and to preserve, among dairy cattle breeds, those with high milk coagulation properties. Often these genetic resources, beyond their genetic value, also exercise a positive influence on sustainability of milk production in fragile environments, such as mountain areas, preserving an important cultural value (history, traditions, arts, and literature).

Milk coagulation is the primary step in the development of most dairy products. Raw milk from individual cows and different breeds exhibit distinct coagulation capacities. This variation is largely influenced by milk protein genetic variants. The aim of the present study was to evaluate differences in coagulation properties between milk obtained from three cattle breeds/types found in Sri Lanka. A total of 90 milk samples (400mL from each individual) were collected from two Sri Lankan cattle breeds/types (Thamankaduwa White/TW and Local/“Batu” cattle) and one European cattle breed (Friesian). Collected samples were subjected to enzymatic coagulation using commercial rennet source (Chymax®, Christian Hansen Standard, Denmark) and lactic acid bacteria (LAB) coagulation using a commercial starter culture(YFL 8 12,Christian Hansen Standard, Denmark) to determine milk coagulation properties. Different properties of milk coagulum such as yield, curd firmness, syneresis and rheological properties were evaluated. The biochemical composition (lactose, protein, fat, solid-non-fat) of milk samples were determined. Capillary Zone Electrophoresis (CZE) method was used to determine milk protein genetic variants. Experimental design was Nested Completely Randomized Design with three treatments. Milk coagulation time and curd firmness after enzymatic-coagulation were not significantly different (p>0.05) among the breeds. Coagulum yield was significantly higher (p

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual&rsquo, s genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.