Milk protein fractions strongly affect the patterns of coagulation, curd firming, and syneresis

Abstract

The aim of this study was to assess the role of milk protein fractions in the coagulation, curd firming, and syneresis of bovine milk. Analyses were performed on 1,271 individual milk samples from Brown Swiss cows reared in 85 herds classified into 4 types of farming systems, from the very traditional (tied cows, feed manually distributed, summer highland pasture) to the most modern (loose cows, use of total mixed rations with or without silage). Fractions α S1 -casein (CN), α S2 -CN, β-CN, κ-CN, β-lactoglobulin (LG), and α-lactalbumin (LA) and genotypes at CSN2, CSN3, and BLG were obtained by reversed-phase HPLC. The following milk coagulation properties were measured with a lactodynamograph, with the testing time extended to 60 min: rennet coagulation time (RCT, min), curd firming time (min), and curd firmness at 30 and 45 min (mm). All the curd firmness measures recorded over time (total of 240 observations/sample) were used in a 4-parameter nonlinear model to obtain parameters of coagulation, curd firming, and syneresis: RCT estimated from the equation (min), asymptotic potential curd firmness (mm), the curd firming and syneresis instant rate constants (%/min), and the maximum curd firmness value (CF max , mm) and the time taken to reach it (min). All the aforementioned traits were analyzed with 2 linear mixed models, which tested the effects of the protein fractions expressed in different ways: in the first, quantitative model, each protein fraction was expressed as content in milk; in the second, qualitative model, each protein fraction was expressed as a percentage of total casein content. Besides proteins, additional nuisance parameters were herd (included as a random effect), daily milk production (only for the quantitative model), casein content (only for the qualitative model), dairy system, parity, days in milk, the pendulum of the lactodynamograph, and the CSN2, CSN3, and BLG genotypes. Both α S1 -CN and β-CN showed a clear and favorable effect on CF max , where the former effect was almost double the latter. Milk coagulation ability was favorably affected by κ-CN, which reduced both the RCT and RCT estimated from the equation, increased the curd firming and syneresis instant rate constants, and allowed a higher CF max to be reached. In contrast, α S2 -CN delayed gelation time and β-LG worsened curd firming, both resulting in a low CF max . The results of this study suggest that modification of the relative contents of specific protein fractions can have an enormous effect on the technological behavior of bovine milk.

Genomic Analysis of Milk Protein Fractions in Brown Swiss Cattle

“…Among the whey protein fractions, we found β-LG in amounts approximately 3.5 times that of α-LA. This result is in agreement with data from previous studies [9,19,20].…”

“…Heck et al [21] and Bobe et al [23] observed that β-LG variants affected determination of its proportion in milk, and also affected β-CN and k-CN proportions of the total milk protein. These correlations indicate that selection for lower proportions of β-LG should increase the proportion of k-CN in milk, with positive effects on milk coagulation [18,20,32]. Highly significant interactions between β-CN, κ-CN and β-LG have been reported in literature which could be explained by the existence of epistatic effects between the genes coding for these proteins [33].…”

“…The κ-CN fraction has a strong positive effect on milk coagulation, curd firming, and the syneresis process; similarly, the α S1 -CN fraction in milk has a favorable effect on curd firmness. On the other hand, the α S2 -CN fraction seems to have the opposite effect to α S1 -CN, since it delays milk gelation, and reduces the maximum curd firmness reached within 90 min as well as syneresis [20]. Sanchez et al [10] also reported positive genetic associations among α S1 -CN, α S2 -CN, and κ-CN contents and proportions, with values ranging from 0.84 to 0.98.…”

Milk Products from Minor Dairy Species: A Review

“…Yield can be predicted by applying specific formulae that have been developed by several researchers: originally, they were only based on total protein and fat content of milk, but other parameters were included with time. In particular, it has been demonstrated that the casein polymorphism connected to genotype, season, stage of lactation, and parity of the cows also make an important contribution [ 6 , 7 , 8 , 9 , 10 ]. The matter is under continuous investigation, and some physical aspects, such as the size of casein micelles and of milk fat globules, have been considered.…”

Effect of goat milk composition on cheesemaking traits and daily cheese production

“…With regard to coagulation properties of goat milk, Stocco et al (2018b) reported that high values of casein number (>82%) were associated with a general improvement of coagulation ability of goat milk, but no information is available about the effect of casein number on milk nutrient recovery in goat cheese. Some studies on bovine milk have clarified that, other than the ratio between caseins and whey proteins, the proportions among individual caseins and whey protein fractions also significantly affect both milk coagulation properties (Amalfitano et al, 2019) and cheesemaking efficiency traits (Cipolat-Gotet et al, 2018). Large breed differences in the proportions among individual protein fractions in goat milk have been demonstrated (Moatsou et al, 2008;Thomann et al, 2008), but their effects were only studied in relation to milk coagulation properties (Clark and Sherbon, 2000) and cheese yield (Damián et al, 2008).…”