Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording, and their relationships with milk yield and quality traits

Evidence of additive genetic variation for major milk proteins in dairy cows: A meta-analysis

In the past, there have been reports of genetic parameters for milk proteins in various dairy cattle populations. The high variability among genetic parameter estimates has been caused by this. This study aimed to use a random-effects meta-analysis model to compile published estimates of genetic parameter for major milk proteins of α-lactalbumin, β-lactoglobulin, sum of whey proteins, casein, αs1-casein, αs2-casein, β-casein, and κ-casein in dairy cows. The study used a total of 140 heritability and 256 genetic correlation estimates from 23 papers published between 2004 and 2022. The estimated range of milk protein heritability is from 0.284 (for α-lactalbumin in milk) to 0.596 (for sum of whey proteins). The genetic correlation estimates between casein and milk yield, milk fat and protein percentages were -0.461, 0.693, and 0.976, respectively (p < 0.05). The genetic correlation estimates between milk proteins expressed as a percentage of milk were significant and varied from 0.177 (between β-lactoglobulin and κ-casein) to 0.892 (between αs1-casein and αs2-casein). Moderate-to-high heritability estimates for milk proteins and their low genetic associations with milk yield and composition indicated the possibility for improving milk proteins in a genetic selection plan with negligible correlated effects on production traits in dairy cows.

Estimating the Effect of the Kappa Casein Genotype on Milk Coagulation Properties in Israeli Holstein Cows

In Israel, about 26% of produced milk is used to produce hard cheeses and 29% for soft cheeses. Milk with preferred coagulation properties requires a shorter coagulation time and yields a higher curd firmness than milk with inferior coagulation properties. Studies have shown that milk from cows with the B allele of kappa casein (κ-CN) produces more cheese than milk from those with A and E alleles. There is evidence that milk from AE or EE genotype cows is unsuitable for cheese production. In the early 1990s, the proportion of the B allele in Israeli Holstein cattle was about 17%, similar to its prevalence in the Holstein population worldwide. In recent years, however, its proportion has increased to about 40%. We analyzed milk coagulation properties as a function of the cow's κ-CN genotype, including time in minutes until the beginning of coagulation and curd firmness after 60 min-measured in volts via an optigraph device and scored on a scale of 0-4 by a laboratory technician. Cow selection was based on their sire's genotype, so that there would be sufficient genotypes that include the rare E allele. A total of 359 cows were sampled from 15 farms: 64 with genotype AA, 142 with AB, 41 with AE, 65 with BB, and 47 with BE. Data were analyzed via the general linear model procedure of SAS. We found the following: (a) There were significant differences between genotypes for optigraph-measured curd firmness. In a multi-comparison test, the BB genotype gave the highest curd firmness, and AB and BE showed a significant advantage compared to AA and AE (9.4, 8.6, 8.4, 6.9, 6.8 V, respectively). Assuming a frequency of about 55% for the A allele, about 30% of the milk delivered to dairy plants comes from AA cows. (b) There was a significant difference between the genotypes in technician-observed curd firmness, with BB scoring significantly higher than AA and AE. (c) The optigraph-measured curd firmness was significantly higher for milk from primiparous cows as compared to milk from second, third, or fourth lactation cows (8.9, 7.8, 7.9, 7.7 V, respectively). The technician-observed curd firmness was significantly higher for primiparous vs. multiparous cows. There was a clear advantage in curd firmness for genotypes that included the B allele compared to those with AA and AE genotypes. We can increase the proportion of the B allele in the population by insemination of cows using bulls with the genotypes AB and BB. This factor should therefore be included in the selection index.

Unraveling the Genomic Association for Milk Production Traits and Signatures of Selection of Cattle in a Harsh Tropical Environment

A study was designed to identify the genomic regions associated with milk production traits in a dairy cattle population reared by smallholder farmers in the harsh and challenging tropical savanna climate of Bengaluru, India. This study is a first-of-its-kind attempt to identify the selection sweeps for the dairy cattle breeds reared in such an environment. Two hundred forty lactating dairy cows reared by 68 farmers across the rural-urban transiting regions of Bengaluru were selected for this study. A genome-wide association study (GWAS) was performed to identify candidate genes for test-day milk yield, solids-not-fat (SNF), milk lactose, milk density and clinical mastitis. Furthermore, the cross-population extended haplotype homozygosity (XP-EHH) methodology was adopted to scan the dairy cattle breeds (Holstein Friesian, Jersey and Crossbred) in Bengaluru. Two SNPs, rs109340659 and rs41571523, were observed to be significantly associated with test-day milk yield. No significant SNPs were observed for the remaining production traits. The GWAS for milk lactose revealed one SNP (rs41634101) that was very close to the threshold limit, though not significant. The potential candidate genes fibrosin-like 1 (FBRSL) and calcium voltage-gated channel auxiliary subunit gamma 3 (CACN) were identified to be in close proximity to the SNP identified for test-day milk yield. These genes were observed to be associated with milk production traits based on previous reports. Furthermore, the selection signature analysis revealed a number of regions under selection for the breed-group comparisons (Crossbred-HF, Crossbred-J and HF-J). Functional analysis of these annotated genes under selection indicated pathways and mechanisms involving ubiquitination, cell signaling and immune response. These findings point towards the probable selection of dairy cows in Bengaluru for thermotolerance.

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.

Milk coagulation properties are moderately heritable in dairy cows: a meta-analysis using the random-effects model

This study aimed to conduct a meta-analysis using the random-effects model to merge published genetic parameter estimates for milk coagulation properties (MCP: comprising rennet coagulation time (RCT), curd-firming time (k20), curd firmness 30 min after rennet addition (a30), titrable acidity (TA) and milk acidity or pH) in dairy cows. Overall, 80 heritability estimates and 157 genetic correlations from 23 papers published between 1999 and 2020 were used. The heritability estimates for RCT, a30, k20, TA, and pH were 0.273, 0.303, 0.278, 0.189 and 0.276, respectively. The genetic correlation estimates between RCT-a30, RCT-pH, and RCT-TA were 0.842, 0.549 and -0.565, respectively. Genetic correlation estimates between RCT and production traits were generally low and ranged from -0.142 (between RCT and casein content) to 0.094 (between RCT and somatic cell score). Moderate and significant genetic correlations were observed between a30-pH (-0.396) and a30-TA (0.662). Also, the genetic correlation estimates between a30 and production traits were low to moderate and varied from -0.165 (between a30 and milk yield) to 0.481 (between a30 and casein content). Genetic correlation estimates between pH and production traits were low and varied from -0.190 (between pH and milk protein percentage) to 0.254 (between pH and somatic cell score). The results of this meta-analysis indicated the existence of additive genetic variation for MCP that could be used in genetic selection programs for dairy cows. Because of the moderate heritability of MCP and small genetic correlations with production traits, it could be possible to improve MCP with negligible correlated effects on production traits.

Understanding the phenotypic and genetic background of the lactose content in Sarda dairy sheep

Lactose, the principal carbohydrate found in milk, plays an important role in the physiological processes of milk production because it is related to milk volume, and it is responsible for the osmotic equilibrium between blood and milk in the mammary gland. In this study, factors affecting lactose content (LC) in sheep milk are investigated. For this purpose, 2,358 test-day records were sampled from 509 ewes (3-7 records per animal). The LC and other main milk traits were analyzed using a mixed linear model that included days in milk (DIM) class, parity, lambing month, and type of lambing as fixed effects and animal, permanent environment, and flock test day as random effects. The pedigree-based approach was used to estimate the heritability and repeatability of LC. Moreover, the genomic background of LC was investigated through a GWAS. The LC was affected by all tested factors (i.e., DIM class, parity, lambing month, and type of lambing). Low heritability (0.10 ± 0.05) and moderate repeatability (0.42 ± 0.02) were estimated for LC. High negative genetic correlations were estimated between LC and NaCl (-0.99 ± 0.01) and between LC and somatic cell count (-0.94 ± 0.05). Only 2 markers passed the chromosome-wide Bonferroni threshold. Results of the present study, although obtained on a relatively small sample, suggest the possibility to include LC in the breeding programs, particularly because of its strong relationship with NaCl and somatic cell count.

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals 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 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

New insights into the raw milk microbiota diversity from animals with a different genetic predisposition for feed efficiency and resilience to mastitis

The main objective of this study was to assess the microbiota diversity in milk samples collected from Holstein cows with different estimated breeding values for predicted feed efficiency, milk coagulation, resilience to mastitis, and consequently, to study its effects on milk quality. One hundred and twenty milk samples were collected in two seasons (summer and winter) from different commercial dairy farms in the Nord-east of Italy. For each trait, 20 animals divided into two groups of the high (10 cows) and the low (10 cows) were selected to study the microbiota profile using 16S rRNA metabarcoding sequencing. The alpha and beta diversity analysis revealed significant differences between the high and the low groups for feed efficiency and resilience to mastitis, while no significant difference was detected for milk coagulation. Moreover, remarkable differences among the taxa were detected between the two seasons, where the winter was more diverse than summer when applied the Chao1 index. Lastly, the linear discriminant analysis (LDA) effect size (LEfSe) indicated Aerococcus, Corynebacterium, Facklamia, and Psychrobacter taxa with more abundance in the high group of feed efficiency, whereas, in resilience to mastitis, only two genera of Mycoplana and Rhodococcus were more abundant in the low group. In addition, LEfSe analysis between the seasons showed significant differences in the abundance of Bacteroides, Lactobacillus, Corynebacterium, Escherichia, Citrobacter, Pantoea, Pseudomonas, and Stenotrophomonas. These findings indicate that the different genetic predisposition for feed efficiency and resilience to mastitis could affect the raw milk microbiota and, consequently, its quality. Moreover, we found more abundance of mastitis-associated bacteria in the milk of dairy cows with a higher feed efficiency index.

Genetic parameters of colostrum traits in Holstein dairy cows

The main objective of this study was to assess the genetic background of colostrum yield and quality traits after calving in Holstein dairy cows. The secondary objective was to investigate genetic and phenotypic correlations among laboratory-based and on-farm-measured colostrum traits. The study was conducted in 10 commercial dairy herds located in northern Greece. A total of 1,074 healthy Holstein cows with detailed pedigree information were examined from February 2015 to September 2016. All cows were clinically examined on the day of calving and scored for body condition. All 4 quarters were machine-milked, and a representative and composite colostrum sample was collected and examined. Colostrum total solids (TS) content was determined on-farm using a digital Brix refractometer. Colostrum fat, protein, and lactose contents were determined using an infrared milk analyzer, and energy content was calculated using National Research Council (2001) equations. Dry period length (for cows of parity ≥2), milk yield of previous 305-d lactation (for cows of parity ≥2), age at calving, parity number, season of calving, time interval between calving and first colostrum milking, and milk yield were recorded. Each trait (colostrum yield and quality traits) was analyzed with a univariate mixed model, including fixed effects of previously mentioned factors and the random animal additive genetic effect. All available pedigrees were included in the analysis, bringing the total animal number to 5,662. Estimates of (co)variance components were used to calculate heritability for each trait. Correlations among colostrum traits were estimated with bivariate analysis using the same model. Mean percentage (±SD) colostrum TS, fat, protein, and lactose contents were 25.8 ± 4.7, 6.4 ± 3.3, 17.8 ± 4.0, and 2.2 ± 0.7%, respectively; mean energy content was 1.35 ± 0.3 Mcal/kg and mean colostrum yield was 6.18 ± 3.77 kg. Heritability estimates for the above colostrum traits were 0.27, 0.21, 0.19, 0.15, 0.22, and 0.04, respectively. Several significant genetic and phenotypic correlations were derived. The genetic correlation of TS content measured on-farm with colostrum protein was practically unity, whereas the correlation with energy content was moderate (0.61). Fat content had no genetic correlation with TS content; their phenotypic correlation was positive and low. Colostrum yield was not correlated genetically with any of the other traits. In conclusion, colostrum quality traits are heritable and can be amended with genetic selection.

Genetic relationships of lactose and freezing point with minerals and coagulation traits predicted from milk mid-infrared spectra in Holstein cows

The aim of the present study was to assess the relationships of lactose percentage (LP), lactose yield (LY), and freezing point (FRP) with minerals and coagulation properties predicted from mid-infrared spectra in bovine milk. To achieve this purpose, we analyzed 54,263 test-day records of 4,297 Holstein cows to compute (co)variance components with a linear repeatability animal model. Parity, stage of lactation, season of calving, and herd-test-date were included as fixed effects in the model, and additive genetic animal, within- and across-lactation permanent environment, and residual were included as random effects. Lactose percentage was more heritable (0.405 ± 0.027) than LY (0.121 ± 0.021) and FRP (0.132 ± 0.014). Heritabilities (± standard error) of predicted milk minerals varied from 0.375 ± 0.027 for Na to 0.531 ± 0.028 for P, and those of milk coagulation properties ranged from 0.348 ± 0.052 for rennet coagulation time to 0.430 ± 0.026 for curd firming time. Lactose percentage showed favorable (negative) genetic correlations with milk somatic cell score (SCS) and FRP, and it was almost uncorrelated with casein-related minerals (Ca and P) and coagulation properties. Moreover, LP was strongly correlated with Na (-0.783 ± 0.022), a mineral known to increase in the presence of intramammary infection (IMI) and high somatic cell count. Indeed, Na is the main osmotic replacer of lactose in mastitic milk when the blood-milk barrier is altered during IMI. Being strongly associated with milk yield, LY did not favorably correlate with coagulation properties, likely because of the negative correlation of this trait with protein and casein percentages. Milk FRP presented moderate and null genetic associations with Na and SCS, respectively. Results of the present study suggest that the moderate heritability of LP and its genetic correlations with IMI-related traits (Na and SCS) could be exploited for genetic selection against mastitis. Moreover, selection for LP would not impair milk coagulation characteristics or Ca and P content, which are important for cheesemaking.

Invited review: Milk lactose-Current status and future challenges in dairy cattle

Lactose is the main carbohydrate in mammals' milk, and it is responsible for the osmotic equilibrium between blood and alveolar lumen in the mammary gland. It is the major bovine milk solid, and its synthesis and concentration in milk are affected mainly by udder health and the cow's energy balance and metabolism. Because this milk compound is related to several biological and physiological factors, information on milk lactose in the literature varies from chemical properties to heritability and genetic associations with health traits that may be exploited for breeding purposes. Moreover, lactose contributes to the energy value of milk and is an important ingredient for the food and pharmaceutical industries. Despite this, lactose has seldom been included in milk payment systems, and it has never been used as an indicator trait in selection indices. The interest in lactose has increased in recent years, and a summary of existing information about lactose in the dairy sector would be beneficial for the scientific community and the dairy industry. The present review collects and summarizes knowledge about lactose by covering and linking several aspects of this trait in bovine milk. Finally, perspectives on the use of milk lactose in dairy cattle, especially for selection purposes, are outlined.

Heritability and repeatability of milk lactose and its relationships with traditional milk traits, somatic cell score and freezing point in Holstein cows

Lactose percentage (LP) in milk is currently determined in most herd-testing schemes, and globally, it is usually routinely recorded in the framework of the official milk recording procedures. However, few studies have investigated the phenotypic and genetic variability of this component. Data used in the present paper consisted of 59 811 test-day records from 4355 Holstein cows in 266 herds. Heritabilities of LP and lactose yield (LY) were estimated through single-trait repeatability animal models, whereas genetic and phenotypic correlations of LP and LY with milk composition and production traits, somatic cell score and milk freezing point were estimated using bivariate models. Fixed effects included in the analyses were herd-test-date, season of calving, parity, stage of lactation and the interaction between parity and stage of lactation. Random effects were animal additive genetic, within and across lactation permanent environment and the residual. Lactation curves of LP and LY increased from parturition to the peak of lactation and decreased thereafter, mirroring the typical curve of milk yield. Lactose percentage was greater in first- than later-parity cows. Heritabilities of LP and LY were 0.43±0.03 and 0.14±0.02, respectively, and LP and protein percentage were the most repeatable traits. Genetic correlations (r a) of LP with somatic cell score, LY and milk freezing point were -0.22±0.08, 0.28±0.08 and -0.46±0.05, respectively. Genetic relationships of LY with milk yield (r a=0.97±0.00), fat percentage (r a=-0.71±0.06), protein percentage (r a=-0.57±0.06) and protein yield (r a=0.64±0.06) were moderate to strong. Results suggest that milk LP could be considered in breeding strategies to accelerate the gain of correlated low heritable traits. Further research is needed to evaluate the feasibility of including LP in the selection index of Italian Holstein population to address country-specific needs and market demands.

Association of candidate gene polymorphisms with milk technological traits, yield, composition, and somatic cell score in Italian Holstein-Friesian sires

Advances in DNA-based marker technology have enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to investigate 96 single nucleotide polymorphisms (SNP) located in 53 candidate genes previously reported to have effects on milk production and quality traits in a population of highly selected Holstein-Friesian bulls. A total of 423 semen samples were used to genotype the bulls through a custom oligo pool assay. Forty-five SNP in 32 genes were found to be associated with at least 1 of the tested traits. Most significant and favorable SNP trait associations were observed for polymorphisms located in CCL3 and AGPAT6 genes for fat yield (0.037 and 0.033 kg/d, respectively), DGKG gene for milk yield (0.698 kg/d), PPARGC1A, CSN1S1, and AGPAT6 genes for fat percentage (0.127, 0.113, and 0.093%, respectively), GHR gene for protein (0.064%) and casein percentage (0.053%), and TLR4 gene for fat (0.090%), protein (0.066%), and casein percentage (0.050%). Somatic cell score was favorably affected by GHR (-0.095) and POU1F1 (-0.137), and interesting SNP-trait associations were observed for polymorphisms located in CSN2, POU1F1, and AGPAT6 genes for rennet coagulation time (-0.592, -0.558, and -0.462 min, respectively), and GHR and CSN2 genes for curd firmness 30 min after rennet addition (1.264 and 1.183 mm, respectively). In addition to the influence of individual SNP, the effects of composite genotypes constructed by grouping SNP according to their individual effects on traits considered in the analysis were also examined. Favorable and significant effects on milk traits were observed for 2 composite genotypes, one including 10 SNP and the other 4 SNP. The former was associated with an increase of milk (0.075 kg/d), fat (0.097 kg/d), protein (0.083 kg/d), and casein yields (0.065 kg/d), and the latter was associated with an increase of fat (0.244%), protein (0.071%), and casein percentage (0.047%). Although further research is required to validate the identified SNP loci in other populations and breeds, our results can be considered as a preliminary foundation for further replication studies on gene-assisted selection programs.

Development and validation of a near infrared spectrophotometric method to determine total antioxidant activity of milk

In the present study a spectrophotometric method for the determination of total antioxidant activity (TAA) based on ABTS assay was developed and validated on raw milk (RM), whole UHT milk (WUM), partially skimmed UHT milk (SUM), whole pasteurised milk (WM) and partially skimmed pasteurised milk (SM). The most suitable solvent for antioxidant extraction was 80% acetone. Regardless of the type of milk, the coefficient of determination from the linearity test was greater than 0.95. The limit of detection ranged from 0.74 to 6.07μmoll^-1 Trolox equivalents. Repeatability, calculated as relative standard deviation of twenty measurements within a day, and reproducibility, calculated as relative standard deviation of sixty measurements across three days, ranged from 1.24 to 4.04% and from 2.18 to 3.52%, respectively. Preservative added to RM had negligible effects on the TAA of milk. The greatest TAA was measured for SM followed by SUM, RM, WM and WUM.

Predictive ability of mid-infrared spectroscopy for major mineral composition and coagulation traits of bovine milk by using the uninformative variable selection algorithm

Milk minerals and coagulation properties are important for both consumers and processors, and they can aid in increasing milk added value. However, large-scale monitoring of these traits is hampered by expensive and time-consuming reference analyses. The objective of the present study was to develop prediction models for major mineral contents (Ca, K, Mg, Na, and P) and milk coagulation properties (MCP: rennet coagulation time, curd-firming time, and curd firmness) using mid-infrared spectroscopy. Individual milk samples (n=923) of Holstein-Friesian, Brown Swiss, Alpine Grey, and Simmental cows were collected from single-breed herds between January and December 2014. Reference analysis for the determination of both mineral contents and MCP was undertaken with standardized methods. For each milk sample, the mid-infrared spectrum in the range from 900 to 5,000cm(-1) was stored. Prediction models were calibrated using partial least squares regression coupled with a wavenumber selection technique called uninformative variable elimination, to improve model accuracy, and validated both internally and externally. The average reduction of wavenumbers used in partial least squares regression was 80%, which was accompanied by an average increment of 20% of the explained variance in external validation. The proportion of explained variance in external validation was about 70% for P, K, Ca, and Mg, and it was lower (40%) for Na. Milk coagulation properties prediction models explained between 54% (rennet coagulation time) and 56% (curd-firming time) of the total variance in external validation. The ratio of standard deviation of each trait to the respective root mean square error of prediction, which is an indicator of the predictive ability of an equation, suggested that the developed models might be effective for screening and collection of milk minerals and coagulation properties at the population level. Although prediction equations were not accurate enough to be proposed for analytic purposes, mid-infrared spectroscopy predictions could be evaluated as phenotypic information to genetically improve milk minerals and MCP on a large scale.

Effects of dairy factory, milk casein content and titratable acidity on coagulation properties in Trentingrana dairy industry

The objective of the present study was to investigate the effect of environmental factors, milk casein content and titratable acidity on milk coagulation properties (MCP) of samples routinely collected in the Trento province (northeast Italy) under field conditions. Rennet coagulation time (RCT, min), curd-firming time (k20, min) and curd firmness (a30, mm) were determined by Formagraph on 14 971 samples from 635 herds associated to 17 dairy factories. Besides MCP, fat, protein, and casein percentages, titratable acidity (TA), and somatic cell and bacterial counts were available. A standardised index of milk aptitude to coagulate (IAC) was derived using information of RCT and a30. An analysis of variance was conducted on MCP and IAC using a fixed effects linear model. Approximately 3% of milk samples did not form a curd within the testing time (30 min) and k20 was missing for 26% of milks. The percentage of samples without information on k20 largely differed among dairy factories (1·7–20·9%). Significant differences were estimated between the best and the worst dairy factory for RCT (−2 min), k20 (−1·2 min), a30 (+3·4 mm) and IAC (+2·6 points). Milk casein content and TA were important factors in explaining the variation of MCP and IAC, supporting the central role of these two traits on technological properties. The Trento province is heterogeneous in terms of dairy systems and this could explain the differences among dairy factories.

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions.

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.

Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle

Background

Recently, selection for milk technological traits was initiated in the Italian dairy cattle industry based on direct measures of milk coagulation properties (MCP) such as rennet coagulation time (RCT) and curd firmness 30 min after rennet addition (a₃₀) and on some traditional milk quality traits that are used as predictors, such as somatic cell score (SCS) and casein percentage (CAS). The aim of this study was to shed light on the causal relationships between traditional milk quality traits and MCP. Different structural equation models that included causal effects of SCS and CAS on RCT and a₃₀ and of RCT on a₃₀ were implemented in a Bayesian framework.

Results

Our results indicate a non-zero magnitude of the causal relationships between the traits studied. Causal effects of SCS and CAS on RCT and a₃₀ were observed, which suggests that the relationship between milk coagulation ability and traditional milk quality traits depends more on phenotypic causal pathways than directly on common genetic influence. While RCT does not seem to be largely controlled by SCS and CAS, some of the variation in a₃₀ depends on the phenotypes of these traits. However, a₃₀ depends heavily on coagulation time. Our results also indicate that, when direct effects of SCS, CAS and RCT are considered simultaneously, most of the overall genetic variability of a₃₀ is mediated by other traits.

Conclusions

This study suggests that selection for RCT and a₃₀ should not be performed on correlated traits such as SCS or CAS but on direct measures because the ability of milk to coagulate is improved through the causal effect that the former play on the latter, rather than from a common source of genetic variation. Breaking the causal link (e.g. standardizing SCS or CAS before the milk is processed into cheese) would reduce the impact of the improvement due to selective breeding. Since a₃₀ depends heavily on RCT, the relative emphasis that is put on this trait should be reconsidered and weighted for the fact that the pure measure of a₃₀ almost double-counts RCT.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0123-7) contains supplementary material, which is available to authorized users.

Effect of microparticulated whey proteins on milk coagulation properties

The enhancement of milk coagulation properties (MCP) and the reuse of whey produced by the dairy industry are of great interest to improve the efficiency of the cheese-making process. Native whey proteins (WP) can be aggregated and denatured to obtain colloidal microparticulated WP (MWP). The objective of this study was to assess the effect of MWP on MCP; namely, rennet coagulation time (RCT), curd-firming time, and curd firmness 30 min after rennet addition. Six concentrations of MWP (vol/vol; 1.5, 3.0, 4.5, 6.0, 7.5, and 9.0%) were added to 3 bulk milk samples (collected and analyzed during 3 d), and a sample without MWP was used as control. Within each day of analysis, 6 replicates of MCP for each treatment were obtained, changing the position of the treatment in the rack. For control samples, 2 replicates per day were performed. In addition to MCP, WP fractions were measured on each treatment during the 3 d of analysis. Milk coagulation properties were measured on 144 samples by using a Formagraph (Foss Electric, Hillerød, Denmark). Increasing the amount of MWP added to milk led to a longer RCT. In particular, significant differences were found between RCT of the control samples (13.5 min) and RCT of samples with 3.0% (14.6 min) or more MWP. A similar trend was observed for curd-firming time, which was shortest in the control samples and longest in samples with 9.0% MWP (21.4 min). No significant differences were detected for curd firmness at 30 min across concentrations of MWP. Adjustments in cheese processing should be made when recycling MWP, in particular during the coagulation process, by prolonging the time of rennet activity before cutting the curd.