Genetic analysis of detailed milk protein composition and coagulation properties in Simmental cattle

The objective of this study was to estimate genetic parameters for milk protein fraction contents, milk protein composition, and milk coagulation properties (MCP). Contents of α_S1-, α_S2-, β-, γ-, and κ-casein (CN), β-lactoglobulin (β-LG), and α-lactalbumin (α-LA) were measured by reversed-phase HPLC in individual milk samples of 2,167 Simmental cows. Milk protein composition was measured as percentage of each CN fraction in CN (α_S1-CN%, α_S2-CN%, β-CN%, γ-CN%, and κ-CN%) and as percentage of β-LG in whey protein (β-LG%). Rennet clotting time (RCT) and curd firmness (a₃₀) were measured by a computerized renneting meter. Heritabilities for contents of milk proteins ranged from 0.11 (α-LA) to 0.52 (κ-CN). Heritabilities for α_S1-CN%, κ-CN%, and β-CN% were similar and ranged from 0.63 to 0.69, whereas heritability of α_S2-CN%, γ-CN%, and β-LG% were 0.28, 0.18, and 0.34, respectively. Effects of CSN2-CSN3 haplotype and BLG genotype accounted for more than 80% of the genetic variance of α_S1-CN%, β-CN%, and κ-CN% and 50% of the genetic variance of β-LG%. The genetic correlations among the contents of CN fractions and between CN and whey protein fractions contents were generally low. When the data were adjusted for milk protein gene effects, the magnitude of the genetic correlations among the contents of milk protein fractions markedly increased, indicating that they undergo a common regulation. The proportion of β-CN in CN correlated negatively with κ-CN% (r = −0.44). The genetic relationships between CN and whey protein composition were trivial. Low milk pH correlated with favorable MCP. Genetically, contents and proportions of α_S1- and α_S2-CN in CN were positively correlated with RCT. The relative proportion of β-CN in CN exhibited a genetic correlation with RCT of −0.26. Both the content and the relative proportion of κ-CN in CN did not correlate with RCT. Weak curds were genetically associated with increased proportions in CN of α_S1- and α_S2-CN, decreased contents of β-CN and κ-CN, and decreased proportion of κ-CN in CN. Negligible effects on the estimated correlations between a₃₀ and κ-CN contents or proportion in CN were observed when the model accounted for milk protein gene effects. Increasing β-CN and κ-CN contents and relative proportions in CN and decreasing the content and proportions of α_S1-CN and α_S2-CN and milk pH through selective breeding exert favorable effects on MCP.     

Effects of β-κ-casein (CSN2-CSN3) haplotypes, β-lactoglobulin (BLG) genotypes, and detailed protein composition on coagulation properties of individual milk of Simmental cows

The aim of this study was to investigate the effects of CSN2-CSN3 (β-κ-casein) haplotypes, BLG (β-lactoglobulin) genotypes, content of milk protein fractions, and protein composition on coagulation properties of milk (MCP). Rennet coagulation time (RCT) and curd firmness (a₃₀) were measured using a computerized renneting meter, and the contents of major milk protein fractions were quantified by reversed-phase HPLC in individual milk samples of 2,167 Simmental cows. Cow genotypes at CSN2, CSN3, and BLG were ascertained by reversed-phase HPLC, and CSN2-CSN3 haplotype probabilities were estimated for each cow. Phenotypes for MCP were regressed on CSN2-CSN3 haplotype probabilities using linear models that also included the effects of herd-test-day, parity, days in milk, pH, somatic cell score, renneting meter sensor, sire of the cow, BLG genotype, and content of major protein fractions or, alternatively, protein composition. When the statistical model did not account for protein fraction contents or protein composition, haplotypes carrying CSN3 B were associated with shorter RCT and greater a₃₀ compared with those carrying CSN3 A. Haplotypes carrying CSN2 B had the effect of decreasing RCT and increasing a₃₀ relative to haplotype A²A. When effects of protein fractions content or protein composition were added to the model, no difference across haplotypes due to CSN3 and CSN2 alleles was observed for MCP, with the exception of the effect of CSN2 B on RCT, which remained markedly favorable. Hence, the effect of CSN3 B on MCP is related to a variation in protein composition caused by the allele-specific expression of κ-casein, rather than to a direct role of the protein variant on the coagulation process. In addition, the favorable effect exerted by CSN2 B on a₃₀ was caused by the increased β-casein content in milk. Conversely, CSN2 B is likely to exert a direct genetic effect on RCT, which does not depend upon variation of β-casein content associated with CSN2 B. Increased RCT was observed for milk yielded by BLG BB cows, even when models accounted for protein composition. Rennet clotting time was favorably affected by κ-casein content and percentage of κ-casein to total casein, whereas a₃₀ increased when contents and percentages of β-CN and κ-CN increased. Changes of milk protein composition and allele frequency at casein and whey protein genes affect variation of MCP.     

Glycosylation of κ-casein: Genetic and nongenetic variation and effects on rennet coagulation properties of milk

The aims of this study were to investigate genetic and nongenetic variation in the degree of glycosylation of κ-casein (κ-CN) and to estimate the effects of glycosylated (G-κCN) and unglycosylated (U-κCN) κ-CN contents on milk coagulation properties of Simmental cows. Measures of contents of the main casein fractions, G-κCN, and U-κCN, and assessment of genotypes at CSN2, CSN3, and BLG were obtained by reversed-phase HPLC analysis of 2,015 individual milk samples. Content of total κ-CN (κ-CNtot, g/L) was the sum of G-κCN and U-κCN, and the glycosylation degree of κ-CN (GD) was measured as the ratio of G-κCN to κ-CNtot. Rennet coagulation time (RCT) and curd firmness were measured by using a computerized renneting meter. Measures of curd firmness were adjusted for RCT before statistical analysis. Variance components of κ-CNtot, G-κCN, U-κCN, and GD were estimated by Bayesian procedures and univariate linear models that included the class effects of the herd-test-day, parity, days in milk, genotypes at milk protein genes, and animal. These class effects, those of G-κCN, U-κCN, and content of other caseins, and the linear effect of milk pH were accounted for by models investigating the influence of κ-CN glycosylation on coagulation properties. The GD ranged from 22 to 76%, indicating that variation in G-κCN depends on the variation both in κ-CNtot and in the efficiency of κ-CN glycosylation. Genotype CSN3 BB exhibited high G-κCN and U-κCN relative to that of CSN3 AA. Heritability of G-κCN, U-κCN, and GD was high and ranged from 0.46 to 0.56. A large proportion of the additive genetic variation in G-κCN and U-κCN was attributable to influence of CSN and BLG, but these genes did not affect variation in GD, and across-genotypes differences in the trait were small or trivial. Average RCT of the milk class having the highest G-κCN was, on average, 2 min (standard deviation 0.5) shorter than that of the lowest class. Conversely, U-κCN and content of other caseins were not associated with any effect on RCT, except for a slight delay in coagulation when U-κCN was very high. Curd firmness increased when the contents of both κ-CN fractions and other caseins increased. This study provides evidence that the positive association between RCT and κ-CN content is exclusively attributable to the glycosylated fraction of the protein. Because exploitable additive genetic variation in G-κCN exists, improvement of κ-CN composition through selective breeding might be an effective way to enhance milk coagulation properties.     

Effects of milk protein polymorphism and composition,casein micelle size and salt distribution on the milk coagulation properties in Norwegian Red cattle

Effects of milk protein polymorphism and composition, casein micelle size and salts distribution on the coagulation properties of milk from 99 Norwegian Red cattle (NRF) were studied. Genetic variants of α_S1-casein (CN), β-CN, κ-CN and β-lactoglobulin (LG) affected rennet coagulation properties of milk. Significant effects of κ-CN and the composite genotype α_S1-β-κ-CN were observed on acid coagulation properties. Relative concentrations of milk proteins were significantly affected by individual casein genotypes and the composite genotype of α_S1-β-κ-CN while, the relative concentration of β-LG was only affected by β-LG genotypes. The salts distribution in milk and the concentration of milk proteins affected both rennet and acid coagulation properties. Milk protein genotypes associated with better rennet coagulation, impaired the acid coagulation properties. However, α_S1-β-κ-CN BB-A¹A²-BE and BB-A²A²-BB were associated with poor rennet and acid coagulation properties. Breeding programs should focus on decreasing these genotypes in NRF cattle.     

Effects of breed and casein genetic variants on protein profile in milk from Swedish Red,Danish Holstein,and Danish Jersey cows

In selecting cows for higher milk yields and milk quality, it is important to understand how these traits are affected by the bovine genome. The major milk proteins exhibit genetic polymorphism and these genetic variants can serve as markers for milk composition, milk production traits, and technological properties of milk. The aim of this study was to investigate the relationships between casein (CN) genetic variants and detailed protein composition in Swedish and Danish dairy milk. Milk and DNA samples were collected from approximately 400 individual cows each of 3 Scandinavian dairy breeds: Swedish Red (SR), Danish Holstein (DH), and Danish Jersey (DJ). The protein profile with relative concentrations of α-lactalbumin, β-lactoglobulin, and α_S1-, α_S2-, κ-, and β-CN was determined for each milk sample using capillary zone electrophoresis. The genetic variants of the α_S1- (CSN1S1), β- (CSN2), and κ-CN (CSN3) genes for each cow were determined using TaqMan SNP genotyping assays (Applied Biosystems, Foster City, CA). Univariate statistical models were used to evaluate the effects of composite genetic variants, α_S1-β-κ-CN, on the protein profile. The 3 studied Scandinavian breeds differed from each other regarding CN genotypes, with DH and SR having similar genotype frequencies, whereas the genotype frequencies in DJ differed from the other 2 breeds. The similarities in genotype frequencies of SR and DH and differences compared with DJ were also seen in milk production traits, gross milk composition, and protein profile. Frequencies of the most common composite α_S1-β-κ-CN genotype BB/A²A²/AA were 30% in DH and 15% in SR, and cows that had this genotype gave milk with lower relative concentrations of κ- and β-CN and higher relative concentrations of α_S-CN, than the majority of the other composite genotypes in SR and DH. The effect of composite genotypes on relative concentrations of the milk proteins was not as pronounced in DJ. The present work suggests that a higher frequency of BB/A¹A²/AB, together with a decrease in BB/A²A²/AA, could have positive effects on DH and SR milk regarding, for example, the processing of cheese.     

乳蛋白多态性和盐分布对牛乳凝乳性能的影响

研究不同基因型乳蛋白对牛乳凝乳特性的影响规律。采集1 071 头荷斯坦奶牛血样,分析κ-酪蛋白（κ-casein,κ-CN）和β-乳球蛋白（β-lactoglobulin,β-LG）的基因型,在明确基因型的基础上,采集样品开展牛乳凝乳能力评价。在初步筛选的基础上,选择凝乳性能好、凝乳性能差和不凝乳样品各至少30 份,重复3 次,开展凝乳流变学特性、蛋白多态性及矿物离子分布分析。通过动态流变仪、电感应耦合等离子体质谱仪、毛细管电泳、高效液相色谱技术分析不同凝乳等级牛乳的凝乳时间,胶体钙、镁、磷含量差异,不同基因型导致蛋白多态性及含量对牛乳凝乳能力的影响。结果显示,在所有奶牛组中,β-LG的AB基因型（占比48.48%）最常见,但AA型基因（30.97%）的原料乳凝乳效果较好;κ-CN的BB基因型（12.00%）凝乳效果较好,较AA、AB等其凝乳时间更短和凝胶强度更强。凝乳性能好的样品中CN含量及胶体钙含量较高,pH值较凝乳性能差和不凝乳样品低,凝乳时间与κ-CN含量呈反比,酪蛋白和乳清蛋白组成和基因频率的变化会影响牛乳凝乳性能的变化。     

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

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.     

Invited review: Genetics and modeling of milk coagulation properties

Milk coagulation properties (MCP) are conventionally measured using computerized renneting meters, mechanical or optical devices that record curd firmness over time (CF_t). The traditional MCP are rennet coagulation time (RCT, min), curd firmness (a₃₀, mm), and curd-firming time (k₂₀, min). The milk of different ruminant species varies in terms of CF_t pattern. Milk from Holstein-Friesian and some Scandinavian cattle breeds yields higher proportions of noncoagulating samples, samples with longer RCT and lower a₃₀, and samples for which k₂₀ is not estimable, than does milk from Brown Swiss, Simmental, and other local Alpine breeds. The amount, proportion, and genetic variants (especially κ-casein) of milk protein fractions strongly influence MCP and explain variable proportions of the observed differences among breeds and among individuals of the same breed. In addition, other major genes have been shown to affect MCP. Individual repeatability of MCP is high, whereas any herd effect is low; thus, the improvement of MCP should be based principally on selection. Exploitable additive genetic variation in MCP exists and has been assessed using different breeds in various countries. Several models have been formulated that either handle noncoagulating samples or not. The heritability of MCP is similar to that of other milk quality traits and is higher than the heritability of milk yield. Rennet coagulation time and a₃₀ are highly correlated, both phenotypically and genetically. This means that the use of a₃₀ data does not add valuable information to that obtainable from RCT; both traits are genetically correlated mainly with milk acidity. Moreover, a₃₀ is correlated with casein content. The major limitations of traditional MCP can be overcome by prolonging the observation period and by using a novel CF_t modeling, which uses all available information provided by computerized renneting meters and allows the estimation of RCT, the potential asymptotic curd firmness, the curd-firming rate, and the syneresis rate. Direct measurements of RCT obtained from both mechanical and optical devices show similar heritabilities and exhibit high phenotypic and genetic correlations. Moreover, mid-infrared reflectance spectroscopy can predict MCP. The heritabilities of predicted MCP are higher than those of measured MCP, and the 2 sets of values are strongly correlated. Therefore, mid-infrared reflectance spectroscopy is a reliable and cheap method whereby MCP can be improved at the population level; this is because such spectra are already routinely acquired from the milk of cows enrolled in milk recording schemes.     

Distinct composition of bovine milk from Jersey and Holstein-Friesian cows with good,poor, or noncoagulation properties as reflected in protein genetic variants and isoforms

The objective of this study was to examine variation in overall milk, protein, and mineral composition of bovine milk in relation to rennet-induced coagulation, with the aim of elucidating the underlying causes of milk with impaired coagulation abilities. On the basis of an initial screening of 892 milk samples from 42 herds with Danish Jersey and Holstein-Friesian cows, a subset of 102 samples was selected to represent milk with good, poor, or noncoagulating properties (i.e., samples that within each breed represented the most extremes in regard to coagulation properties). Milk with good coagulation characteristics was defined as milk forming a strong coagulum based on oscillatory rheology, as indicated by high values for maximum coagulum strength (G′_max) and curd firming rate (CFR) and a short rennet coagulation time. Poorly coagulating milk formed a weak coagulum, with a low G′_max and CFR and a long rennet coagulation time. Noncoagulating milk was defined as milk that failed to form a coagulum, having G′_max and CFR values of zero at measurements taken within 1 h after addition of rennet. For both breeds, a lower content of total protein, total casein (CN) and κ-CN, and lower levels of minerals (Ca, P, Mg) were identified in poorly coagulating and noncoagulating milk in comparison with milk with good coagulation properties. Liquid chromatography/electrospray ionization-mass spectrometry revealed the presence of a great variety of genetic variants of the major milk proteins, namely, α_S1-CN (variants B and C), α_S2-CN (A), β-CN (A¹, A², B, I, and F), κ-CN (A, B, and E), α-lactalbumin (B), and β-lactoglobulin (A, B, and C). In poorly coagulating and noncoagulating milk samples of both breeds, the predominant composite genotype of α_S1-, β-, and κ-CN was BB-A²A²-AA, which confirmed a genetic contribution to impaired milk coagulation. Interestingly, subtle variations in posttranslational modification of CN were observed between the coagulation classes in both breeds. Poorly coagulating and noncoagulating milk contained a lower fraction of the least phosphorylated α_S1-CN form, α_S1-CN 8P, relative to total α_S1-CN, along with a lower fraction of glycosylated κ-CN relative to total κ-CN. Thus, apparent variation was observed in the milk and protein composition, in the genetic makeup of the major milk proteins, and in the posttranslational modification level of CN between milk samples with either good or impaired coagulation ability, whereas the composition of poorly coagulating and noncoagulating milk was similar.     

Mid-infrared spectroscopy predictions as indicator traits in breeding programs for enhanced coagulation properties of milk

The aims of this study were to investigate variation of milk coagulation property (MCP) measures and their predictions obtained by mid-infrared spectroscopy (MIR), to investigate the genetic relationship between measures of MCP and MIR predictions, and to estimate the expected response from a breeding program focusing on the enhancement of MCP using MIR predictions as indicator traits. Individual milk samples were collected from 1,200 Brown Swiss cows (progeny of 50 artificial insemination sires) reared in 30 herds located in northern Italy. Rennet coagulation time (RCT, min) and curd firmness (a₃₀, mm) were measured using a computerized renneting meter. The MIR data were recorded over the spectral range of 4,000 to 900 cm⁻¹. Prediction models for RCT and a₃₀ based on MIR spectra were developed using partial least squares regression. A cross-validation procedure was carried out. The procedure involved the partition of available data into 2 subsets: a calibration subset and a test subset. The calibration subset was used to develop a calibration equation able to predict individual MCP phenotypes using MIR spectra. The test subset was used to validate the calibration equation and to estimate heritabilities and genetic correlations for measured MCP and their predictions obtained from MIR spectra and the calibration equation. Point estimates of heritability ranged from 0.30 to 0.34 and from 0.22 to 0.24 for RCT and a₃₀, respectively. Heritability estimates for MCP predictions were larger than those obtained for measured MCP. Estimated genetic correlations between measures and predictions of RCT were very high and ranged from 0.91 to 0.96. Estimates of the genetic correlation between measures and predictions of a₃₀ were large and ranged from 0.71 to 0.87. Predictions of MCP provided by MIR techniques can be proposed as indicator traits for the genetic enhancement of MCP. The expected response of RCT and a₃₀ ensured by the selection using MIR predictions as indicator traits was equal to or slightly less than the response achievable through a single measurement of these traits. Breeding strategies for the enhancement of MCP based on MIR predictions as indicator traits could be easily and immediately implemented for dairy cattle populations where routine acquisition of spectra from individual milk samples is already performed.     

Effectiveness of mid-infrared spectroscopy for the prediction of detailed protein composition and contents of protein genetic variants of individual milk of Simmental cows

Mid-infrared (MIR) spectroscopy was used to predict the detailed protein composition of 1,517 milk samples of Simmental cows. Contents of milk protein fractions and genetic variants were quantified by reversed-phase HPLC. The most accurate predictions were those obtained for total protein, casein (CN), α_S1-CN, β-lactoglobulin (LG), glycosylated κ-CN, and whey protein content, which exhibited coefficients of determination between predicted and measured values in cross-validation (1-VR) ranging from 0.61 to 0.78. Less favorable were results for β-CN (1-VR = 0.53), α_S2-CN, and κ-CN (1-VR = 0.49). Neither the content of α-LA nor that of γ-CN was accurately predicted by MIR. Predicting the content of the most common milk protein genetic variants (κ-CN A and B; β-CN A¹, A², and B; and β-LG A and B) was unfeasible (1-VR <0.15 for the content of κ-CN genetic variants and 1-VR <0.01 for the content of β-CN variants). The best predictions were obtained for β-LG A and β-LG B contents (1-VR of 0.60 and 0.44, respectively). Results indicated that MIR is not applicable for predicting individual milk protein composition with high accuracy. However, MIR spectroscopy predictions may play a role as indicator traits in selective breeding to enhance milk protein composition. The genetic correlation between MIR spectroscopy predictions and measures of milk protein composition needs to be investigated, as it affects the suitability of MIR spectroscopy predictions as indicator traits in selective breeding.     

Genetic parameters of milk coagulation properties and their relationships with milk yield and quality traits in Italian Holstein cows

Milk coagulation properties (MCP) are an important aspect in assessing cheese-making ability. Several studies showed that favorable conditions of milk reactivity with rennet, curd formation rate, and curd strength, as well as curd syneresis, have a positive effect on the entire cheese-making process and subsequently on the ripening of cheese. Moreover, MCP were found to be heritable, but little scientific literature is available about their genetic aspects. The aims of this study were to estimate heritability of MCP and genetic correlations among MCP and milk production and quality traits. A total of 1,071 Italian Holstein cows (progeny of 54 sires) reared in 34 herds in Northern Italy were sampled from January to July 2004. Individual milk samples were collected during the morning milking and analyzed for coagulation time (RCT), curd firmness (a₃₀), pH, titratable acidity, fat, protein, and casein contents, and somatic cell count. About 10% of individual milk samples did not coagulate in 31 min, so they were removed from the analyses. Estimates of heritability for RCT and a₃₀ were 0.25 ± 0.04 and 0.15 ± 0.03, respectively. Estimates of genetic correlations between MCP traits and milk production traits were negligible except for a₃₀ with protein and casein contents (0.44 ± 0.10 and 0.53 ± 0.09, respectively). Estimates of genetic correlations between MCP traits and somatic cell score were strong and favorable, as well as those between MCP and pH and titratable acidity. Selecting for high casein content, milk acidity, and low somatic cell count might be an indirect way to improve MCP without reducing milk yield and quality traits.     

Effects of β-κ-casein (CSN2-CSN3) haplotypes and β-lactoglobulin (BLG) genotypes on milk production traits and detailed protein composition of individual milk of Simmental cows

The aim of this study was to investigate the effects of CSN2-CSN3 (β-κ-casein) haplotypes and BLG (β-lactoglobulin) genotypes on milk production traits, content of protein fractions, and detailed protein composition of individual milk of Simmental cows. Content of the major protein fractions was measured by reversed-phase HPLC in individual milk samples of 2,167 cows. Protein composition was measured as percentage of each casein (CN) fraction to total CN and as percentage of β-lactoglobulin (β-LG) to total whey protein. Genotypes at CSN2, CSN3, and BLG were ascertained by reversed-phase HPLC, and CSN2-CSN3 haplotype probabilities were estimated for each cow. Traits were analyzed by using a linear model including the fixed effects of herd-test-day, parity, days in milk, and somatic cell score class, linear regressions on haplotype probabilities, class of BLG genotype, and the random effect of the sire of the cow. Effects of haplotypes and BLG genotypes on yields were weak or trivial. Genotype BB at BLG and haplotypes carrying CSN2 B and CSN3 B were associated with increased CN content and CN number. Haplotypes including CSN3 B were associated with increased κ-CN content and percentage of κ-CN to total CN and with decreased percentages of α_S1- and γ-CN to total CN. Allele CSN2 B had the effect of increasing β-CN content and decreasing content of α_S1-CN. Haplotypes including allele CSN2 A¹ exhibited decreased β-, α_S2-, and γ-CN concentrations and increased α_S1- and κ-CN contents, whereas CSN2 I had positive effects on β-CN concentration and trivial effects on content of other protein fractions. Effects of haplotypes on CN composition were similar to those exerted on content of CN fractions. Allele BLG A was associated with increased β-LG concentration and percentage of β-LG to total whey protein and with decreased content of other milk proteins, namely β-CN and α_S1-CN. Estimated additive genetic variance for investigated traits ranged from 14 to 39% of total variance. Increasing the frequency of specific genotypes or haplotypes by selective breeding might be an effective way to change milk protein composition.     

Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000-900 cm⁻¹) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a₃₀, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm⁻¹. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm⁻¹, 3,040 to 1,700 cm⁻¹, and 4,000 to 3,470 cm⁻¹. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a₃₀, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R² = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R² = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.     

Short communication: Factors affecting coagulation properties of Mediterranean buffalo milk

The aim of this study was to investigate sources of variation of milk coagulation properties (MCP) of buffalo cows. Individual milk samples were collected from 200 animals in 5 herds located in northern Italy from January to March 2010. Rennet coagulation time (RCT, min) and curd firmness after 30 min from rennet addition (a₃₀, mm) were measured using the Formagraph instrument (Foss Electric, Hillerød, Denmark). In addition to MCP, information on milk yield, fat, protein, and casein contents, pH, and somatic cell count (SCC) was available. Sources of variation of RCT and a₃₀ were investigated using a linear model that included fixed effects of herd, days in milk (DIM), parity, fat content, casein content (only for a₃₀), and pH. The coefficient of determination was 51% for RCT and 48% for a₃₀. The most important sources of variation of MCP were the herd and pH effects, followed by DIM and fat content for RCT, and casein content for a₃₀. The relevance of acidity in explaining the variation of both RCT and a₃₀, and of casein content in explaining that of a₃₀, confirmed previous studies on dairy cows. Although future research is needed to investigate the effect of these sources of variation on cheese yield, findings from the present study suggest that casein content and acidity may be used as indicator traits to improve technological properties of buffalo milk.     

Effect of milk protein genetic polymorphisms on rennet and acid coagulation properties after standardisation of protein content

The effects of milk protein genetic polymorphisms on the rennet and acid coagulation properties of milk after protein standardisation were investigated. Skim milk samples were adjusted to a protein concentration of 6.07 ± 0.06% by ultrafiltration (UF) before evaluating rennet coagulation and acid coagulation properties. Only the β-lactoglobulin (β-LG) genotypes influenced the rennet-clotting time before standardisation for the total protein concentration by UF; however, this effect was confounded with the β-LG concentration. After UF-concentration, a similar protein concentration between the samples was achieved in the retentate, then the rennet clotting time and rennet curd firmness at 30 min were significantly influenced by both the κ-casein (κ-CN) and β-LG genotypes. κ-CN genotypes significantly influenced the acid coagulation properties of both skim milk and retentate. Variations in the concentration of milk proteins (mostly α_S2-CN-12P) explained most of the differences in the rennet and acid coagulation properties of milk after protein standardisation by UF.     

Milk coagulation ability of five dairy cattle breeds

Samples of herd milk (506) were analyzed to assess sources of variation for milk coagulation properties (MCP) for 5 different dairy cattle breeds. Data were recorded in 55 single-breed dairy herds in the Trento province, a mountain area in northeast Italy. The 5 cattle breeds were Holstein-Friesian (8 herds), Brown Swiss (16 herds), Simmental (10 herds), Rendena (13 herds), and Alpine Gray (8 herds). Herd milk samples were analyzed for the MCP traits, milk rennet coagulation time (RCT), curd-firming time, and curd firmness (a₃₀), as well as protein and fat percentages, somatic cell count, Soxhlet-Henkel acidity, and bacterial count. An ANOVA was performed to study the effect of breed, herd within breed, DIM, month of lactation, protein and fat percentages, somatic cell score, titratable acidity, and log bacterial count within breed on MCP. Breed was the most important source of variation. In particular, the Rendena breed showed the best MCP traits at 13.5 min and 27.0 mm for RCT and a₃₀, respectively. The Holstein-Friesian breed had the worst coagulation properties at 18.0 min and 17.5 mm for RCT and a₃₀, respectively. The other 3 breeds showed intermediate coagulation properties. The RCT values were better at the beginning of lactation, whereas RCT and a₃₀ values were better in September and October (14.3 min and 25.7 mm, respectively). Among the composition traits, only the titratable acidity affected MCP traits of herd milk positively.     

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 (α_S1-, β-, α_S2-, 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-A¹-A-E) effects. Based on these findings, FTIR spectroscopy-pMCP is proposed as a potential selection criterion for the Italian Holstein.     

Milk yield,quality, and coagulation properties of 6 breeds of goats: Environmental and individual variability

Goat milk and cheese production is continuously increasing and milk composition and coagulation properties (MCP) are useful tools to predict cheesemaking aptitude. The present study was planned to investigate the extension of lactodynamographic analysis up to 60 min in goat milk, to measure the farm and individual factors, and to investigate differences among 6 goat breeds. Daily milk yield (dMY) was recorded and milk samples collected from 1,272 goats reared in 35 farms. Goats were of 6 different breeds: Saanen and Camosciata delle Alpi for the Alpine type, and Murciano-Granadina, Maltese, Sarda, and Sarda Primitiva for the Mediterranean type. Milk composition (fat, protein, lactose, pH; somatic cell score; logarithmic bacterial count) and MCP [rennet coagulation time (RCT, min), curd-firming time (k₂₀, min), curd firmness at 30, 45, and 60 min after rennet addition (a₃₀, a₄₅, and a₆₀, mm)] were recorded, and daily fat and protein yield (dFPY g/d) was calculated as the sum of fat and protein concentration multiplied by the dMY. Data were analyzed using different statistical models to measure the effects of farm, parity_, stage of lactation and breed; lastly, the direct and the indirect effect of breed were quantified by comparing the variance of breed from models with or without the inclusion of linear regression of fat, protein, lactose, pH, bacterial, somatic cell counts, and dMY. Orthogonal contrasts were performed to compare least squares means. Almost all traits exhibited high variability, with coefficients of variation between 32 (for RCT) and 63% (for a₃₀). The proportion of variance regarding dMY, dFPY, and milk composition due to the farm was moderate, whereas for MCP it was low, except for a₆₀, at 69%. Parity affected both yield and quality traits of milk, with least squares means of dMY and dFPY showing an increase and RCT and curd firmness traits a decrease from the first to the last parity class. All milk quality traits, excluding fat, were affected by the stage of lactation; RCT and k₂₀ decreased rapidly and a₃₀ was higher from the first to the last part of lactation. Alpine breeds showed the highest dMY and dFPY but Mediterranean the best percentage of protein, fat, and lactose and a shorter k₂₀ and a greater a₃₀. Among the Mediterranean goats, Murciano-Granadina goats had the highest milk yield, fat, and protein contents, whereas Maltese, Sarda, and Sarda Primitiva were characterized by much more favorable technological properties in terms of k₂₀, a₃₀, and a₄₅. In conclusion, as both the farm and individual factors highly influenced milk composition and MCP traits, improvements of these traits should be based both on modifying management and individual goat factors. As expected, several differences were attributable to the breed effect, with the best milk production for the Alpines and milk quality and coagulation for the Mediterranean goats.     

Effect of CSN1S1-CSN3 (α(S1)-κ-casein) composite genotype on milk production traits and milk coagulation properties in Mediterranean water buffalo

The aim of this study was to estimate effects of CSN1S1-CSN3 (α_S1-κ-casein) composite genotypes on milk production traits and milk coagulation properties (MCP) in Mediterranean water buffalo. Genotypes at CSN1S1 and CSN3 and coagulation properties [rennet clotting time (RCT), curd firming time (K₂₀), and curd firmness (A₃₀)] were assessed by reversed-phase HPLC and computerized renneting meter analysis, respectively, using single test-day milk samples of 536 animals. Alternative protein variants of α_S1-CN and κ-CN were detected by HPLC, and identification of the corresponding genetic variants was carried out by DNA analysis. Two genetic variants were detected at CSN1S1 (A and B variants) and 2 at CSN3 (X1 and X2 variants). Statistical inference was based on a linear model including the CSN1S1-CSN3 composite genotype effect (7 genotypes), the effects of herd-test-day (8 levels), and a combined days in milk (DIM)-parity class. Composite genotype AB-X2X2 was associated with decreased test-day milk yield [?0.21 standard deviation (SD) units of the trait] relative to genotype BB-X2X2. Genotypes did not affect milk protein content, but genotype AB-X1X1 was associated with increased fat content compared with genotype BB-X2X2 (+0.28 SD units of the trait) and AB-X1X1 (+0.43 SD units of the trait). For RCT, the largest difference (+1.91 min; i.e., 0.61 SD units of the trait) was observed between genotype AA-X1X2 and AB-X1X1. Direction of genotype effects on K₂₀ was consistent with that for RCT. The maximum variation in K₂₀ due to genotype effects (between AA-X1X2 and AB-X1X1 genotypes) was almost 0.9 SD units of the trait. Magnitude of genotype effects was smaller for A₃₀ than for RCT and K₂₀, with a maximum difference of 0.5 SD units of the trait between genotype AA-X1X2 and AA-X1X1. The B allele at CSN1S1 was associated with increased RCT and K₂₀ and with weaker curds compared with allele A. Allele X2 at CSN3 exerted opposite effects on MCP relative to CSN1S1 B. Because of linkage disequilibrium, allele B at CSN1S1 and allele X2 at CSN3 tend to be associated and this likely makes their effects cancel each other. This study indicates a role for casein genes in variation of MCP of buffalo milk. Further studies are necessary to estimate the effects of casein genetic variants on variation of cheese yield.