Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows

This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.

Influence of Sodium and Potassium Chloride on Rennet Coagulation and Curd Firmness in Bovine Milk

One of the salting methods in cheese production implies salting the milk before coagulation used in making Domiati-type cheeses and a variety of autochthonous "Lički Škripavac" cheese. The most used sodium replacer is potassium. This study investigated the influence of different added salt concentrations (1%, 1.5%, and 2%) and NaCl to KCl ratios (100%, 50:50%, 25:75%) on the rennet coagulation and curd firmness in bovine milk. The milk coagulation parameters were determined with a computerized renneting meter, Lactodinamograph. The results showed significant interactions between the salt concentrations and NaCl to KCl ratios (p < 0.0001, α = 0.05) by prolonging the beginning of coagulation (10-20 min) and curd firming rate (1-5 min) by an increase in salt concentration for all treatments. The 50:50 treatment values (RCT, k₂₀, a₃₀, a₆₀, a_max) were closest to the control (without salt) and had the best results among all treatments in the lower (1%) and medium (1.5%) salt concentration (p > 0.0001, α = 0.05) while in the highest salt concentration (2%) the treatment effect was nonsignificant (p > 0.05). These results should help future studies make a lower sodium product appealing to consumers without losing quality.

Quality parameters of curd

The aim of this work was measurement of the curd firmness prepared by different volume of rennet solution and comparison of differences of curd firmness between these volumes. Further, it was observed the influence of different volumes of rennet up to thevolume of whey release, curd firmness, dry matter of curd and dry matter of whey. The composition of milk was determined according ISO and Czech state standard. Dry matter content (%) was determined by gravimetry, in drying oven at 102 °C to constant weight (ISO 6731:2010), the protein content (%) by Kjeldahl´s method (EN ISO 8968-1:2002), content of fat (%) by Gerber´s acidobutyrometric method (ISO 2446:2008), content of lactose by polarimetry, titratable acidity by titration Soxhlet-Henkel method, pH and calcium content in milk (g.L-1) was determined by complexometric titration with flueroxone as an indicator according to Czech state standart No 57 0530. For coagulation was used microbial rennet CHY-MAXRM 200. There were measured: curd firmness, rennet coagulation time, curd quality, volume of released whey, weight of curd, dry matter of curd and dry matter of whey. Different volumes of rennet solution had influence on curd firmness. Curd firmness (volume of rennet solution) had no significant influence on curd quality (five grade scale). Curd firmness had influence on volume of whey release (mL) out of the curd. With the increasing curd firmness s increased the volume of whey released from the curd. The volume of rennet solution had an influence on weight of curd. Curd dry matter raised with higher volume of rennet solution. Volume of added rennet solution had no statistically significant effect on the change of whey dry matter.

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n=713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000cm(-1) were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation.

Selection for milk coagulation properties predicted by Fourier transform infrared spectroscopy in the Italian Holstein-Friesian breed

Milk coagulation is based on a series of physicochemical changes at the casein micelle level, resulting in formation of a gel. Milk coagulation properties (MCP) are relevant for cheese quality and yield, important factors for the dairy industry. They are also evaluated in herd bulk milk to reward or penalize producers of Protected Designation of Origin cheeses. The economic importance of improving MCP justifies the need to account for this trait in the selection process. A pilot study was carried out to determine the feasibility of including MCP in the selection schemes of the Italian Holstein. The MCP were predicted in 1,055 individual milk samples collected in 16 herds (66 ± 24 cows per herd) located in Brescia province (northeastern Italy) by means of Fourier transform infrared (FTIR) spectroscopy. The coefficient of determination of prediction models indicated moderate predictions for milk rennet coagulation time (RCT=0.65) and curd firmness (a₃₀=0.68), and poor predictions for curd-firming time (k₂₀=0.49), whereas the range error ratio (8.9, 6.9, and 9.5 for RCT, k₂₀, and a₃₀, respectively) indicated good practical utility of the predictive models for all parameters. Milk proteins were genotyped and casein haplotypes (αS₁-, β-, αS₂-, and κ-casein) were reconstructed. Data from 51 half-sib families (19.9 ± 16.4 daughters per sire) were analyzed by an animal model to estimate (1) the genetic parameters of predicted RCT, k₂₀, and a₃₀; (2) the breeding values for these predicted clotting variables; and (3) the effect of milk protein genotypes and casein haplotypes on predicted MCP (pMCP). This is the first study to estimate both genetic parameters and breeding values of pMCP, together with the effects of milk protein genotypes and casein haplotypes, that also considered k₂₀, probably the most important parameter for the dairy industry (because it indicates the time for the beginning of curd-cutting). Heritability of predicted RCT (0.26) and k₂₀ (0.31) were close to the average heritability described in literature, whereas the heritability of a₃₀ was higher (0.52 vs. 0.27). The effects of milk proteins were statistically significant and similar to those obtained on measured MCP. In particular, haplotypes including uncommon variants showed positive (B-I-A-B) or negative (B-A(1)-A-E) effects. Based on these findings, FTIR spectroscopy-pMCP is proposed as a potential selection criterion for the Italian Holstein.

Effect of milk composition and coagulation traits on Grana Padano cheese yield under field conditions

The aim of this study was to assess the effect of chemical composition, coagulation properties, pH, and titratable acidity (TA, SH°/50 ml) of vat milk on Grana Padano cheese yield (CY) under field conditions. Twelve cheese-making sessions were carried out from February to December 2009 in a dairy cooperative of Grana Padano Consortium (Italy), for a total of 96 vats of milk processed. For each vat, samples of raw milk were collected and analysed for quality traits (fat, protein, and casein contents), pH, TA, and milk coagulation properties (MCP), measured as rennet coagulation time (RCT, min), curd-firming time (k20, min), and curd firmness (a30, mm). Cheese yield was expressed as kilograms of cheese per 100 kg milk transformed, and was measured after 2 d of drainage. Fat, protein, and casein contents were positively and strongly correlated with CY (coefficients of correlation, r = 0·72, 0·88, and 0·84, respectively; P < 0·001). Coagulation properties were moderately and significantly (P < 0·001) related to CY: milk that coagulated earlier and had stronger a30 was associated to greater CY. Cheese yield was analysed with a model that accounted for fixed effects of cheese-making day, fat and protein content, TA, and a30. Significance was found for all the effects (P < 0·05). Milk characterised by high values of a30 resulted in higher CY than milk with low values of a30, indicating that MCP could be used as indicators of cheese-making efficiency. Future research should investigate the relationships between MCP and quality of cheese, and explore the feasibility of including MCP in multiple component milk pricing system for Grana Padano cheese production.