Milk Coagulation Traits Research Articles

Low Effectiveness of Mid-Infrared Spectroscopy Prediction Models of Mediterranean Italian Buffalo Bulk Milk Coagulation Traits.

This study evaluated the potential use of mid-infrared spectroscopy to predict milk coagulation traits in bulk milk from Mediterranean Italian buffaloes. A total of 1736 bulk milk samples from 55 farms in central Italy were collected during the official milk quality testing system. The prediction models were developed based on modified partial least-squares regression with 75% of the samples and validated with the remaining samples. All bulk milk samples coagulated between 7.37 and 29.45 min. Average values for milk coagulation traits in the calibration set were 17.71 min, 3.29 min, and 38.83 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. The validation set included samples with similar mean and standard deviation for each trait. The prediction models showed the greatest coefficient of determination of external validation (0.57) and the ratio of prediction to deviation (1.52) for curd firmness. Similar fitting statistics of the prediction models were obtained for rennet coagulation time and curd firming time. In conclusion, the prediction models for all three coagulation traits were below the threshold to consider the prediction models adequate even for rough screening of the samples.

Milk quality of Italian Mediterranean buffalo as affected by temperature-humidity index during late spring and summer

A total of 18 Italian Mediterranean buffalo cows were subjected to fortnightly milk sampling from May to July 2022. Air temperature and relative humidity were monitored throughout the trial. Temperature-humidity index (THI) was calculated and ranged from 69 to 79, so that 3 classes were set to study the effect of different THI on milk quality: THI less than 72 (THI<72), THI ranging from 72 to 76 (THI72-76), and THI over 76 (THI>76). Individual milk samples from buffalo cows were analyzed for milk composition and coagulation traits, fatty acid and amino acid composition, and enzymatic and mineral profiles. The THI>76 class registered higher lactose content and poorer milk clot characteristics in comparison with THI<72. Exposure to a THI over 76 resulted in increased SFA and short-chain fatty acid contents in milk, as well as in the highest atherogenic and thrombogenic index values and the lowest essential amino acid content. Moreover, the lowest values of calcium, copper, and selenium contents were found in the milk of buffalo cows exposed to a THI over 72. Results confirm that Italian Mediterranean buffalo express a good level of thermo-tolerance, even though exposure to a daily THI over 76 has a deleterious effect on some nutritional and technological properties of milk.

Variability of genes involved in lipid metabolism and their effect on milk yield, composition and coagulation traits in Sarda sheep

Variability of genes involved in lipid metabolism and their effect on milk yield, composition and coagulation traits in Sarda sheep

Effect of total and differential somatic cell count on yield, composition and predicted coagulation properties from individual dairy cows

This study aimed to investigate the effect of interaction between total (SCC) and differential somatic cell count (DSCC) on milk yield, composition and coagulation traits from individual dairy cows. A total of 159 224 test‐day records (daily milk yield, composition and coagulation traits) have been collected during a period of 14 months from 12 849 Holstein‐Friesian and 9275 Simmental cows farmed in 223 herds. The interaction between somatic cell traits was highly significant for almost all the evaluated traits. This study showed that the combined use of SCC and DSCC can be employed for assessing the performances of dairy cows and for monitoring the improvement of milk quality.

Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle

Cheese-making traits in dairy cattle are important to the dairy industry but are difficult to measure at the individual level because there are limitations on collecting phenotypic information. Mid-infrared spectroscopy has its advantages, but it can only be used during monthly milk recordings. Recently, in-line devices for real-time analysis of milk quality have been developed. The AfiLab recording system (Afimilk) offers significant benefits as phenotypes can be collected from each cow at each milking session. The objective of this study was to assess the potential of integrating AfiLab real-time milk analyzer measures with the stacking ensemble learning technique using heterogeneous base learners for the in-line daily monitoring of cheese-making traits in Holstein cattle with a view to developing a precision livestock farming system for monitoring the technological quality of milk. Data and samples for wet-laboratory analyses were collected from 499 Holstein cows belonging to 2 farms where the AfiLab system was installed. The traits of concern were 9 milk coagulation traits [3 milk coagulation properties (MCP), and 6 curd firming traits (CFt)], and 7 cheese-making traits [3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits]. The near-infrared AfiLab spectral data and on-farm information (days in milk and parity) were used to assess the predictive ability of different statistical methods [elastic net (EN), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), and artificial neural network (ANN)] across different cross-validation scenarios. These statistical methods were considered the base learners, which were then combined in a stacking ensemble learning. Results indicate that including information on the cows (days in milk and parity) in the AfiLab infrared prediction increased its accuracy by 10.3% for traditional MCP, 13.8% for curd firming, 9.8% for CY, and 11.2% for REC traits compared with those obtained from near-infrared AfiLab alone. The statistical approaches exhibited high prediction accuracies (R2) averaged across the cross-validation scenarios for traditional MCP (0.58 for ANN, 0.55 for EN and GBM, 0.52 for XGBoost, and 0.62 for stacking ensemble), CFt (0.55 for ANN, 0.54 for EN and GBM, 0.53 for XGBoost, and 0.61 for stacking ensemble), and similar R2 averages for CY and REC (0.55 for ANN, 0.54 for EN and GBM, 0.53 for XGBoost, and 0.61 for stacking ensemble). The ANN approach was more accurate than the other base learners (EN, GBM, and XGBoost) and improved accuracy across cross-validation scenarios on average by 7% for traditional MCP, 5% for CFt, 8% for CY, and 7% for REC. The stacking ensemble method improved prediction accuracy by 3% to 31% for traditional MCP, 2% to 26% for CFt, 1% to 38% for CY traits, and 2% to 27% for REC traits compared with the base learners. The prediction accuracies of the different approaches evaluated tended to decrease from the 10-fold cross-validation to the independent validation scenario, although there was a smaller reduction in prediction accuracy with the stacking ensemble learning technique across all the cross-validation scenarios. Our results show that combining in-line on-farm information with stacking ensemble machine learning represents an effective alternative for obtaining robust daily predictions of milk cheese-making traits.

Novel Genes Associated with Dairy Traits in Sarda Sheep.

Simple SummaryIn a population of 1112 individuals of Sarda sheep, we investigated the polymorphism of 45 single nucleotide polymorphisms (SNPs) in 15 different genes that have been previously investigated because of their relation to metabolism and innate immunity. For SNPs with a sufficient allele frequency, we also tested their influence on a wide panel of dairy traits. The genotyping evidenced some new genetic patterns, and seven SNPs had significant influences on the milk yield, composition and coagulation traits. The results may represent a starting point to acquire new knowledge in the field of dairy sheep sector and to improve the breeding schemes for the Sarda sheep breed.The aim of the present research was to analyze the variability of 45 SNPs from different genes involved in metabolism and innate immunity to perform an association analysis with the milk yield, composition and milk coagulation traits. A population of 1112 Sarda breed sheep was sampled. Genotyping was generated by a TaqMan Open ArrayTM. Thirty out of the 45 SNPs were polymorphic, and 12 displayed a minor allele frequency higher than 0.05. An association analysis showed that the variability at genes PRKAG3 and CD14 was significantly associated with the daily milk yield. The variability at PRKAG3 was also associated with the protein and casein content, somatic cell score and bacterial score. The variation at the PRKAA2 gene was associated with the milk lactose concentration. The SNPs at CD14 were also associated with the traditional milk coagulation properties, while the SNPs at GHR and GHRHR were associated with kSR, a derived coagulation parameter related to the rate of syneresis. The information provided here is new and increases our knowledge of genotype–phenotype interactions in sheep. Our findings might be useful in appropriate breeding schemes to be set up for the Sarda sheep breed, but these should be confirmed by further studies, possibly performed on independent populations.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.

Breed of goat affects the prediction accuracy of milk coagulation properties using Fourier-transform infrared spectroscopy

The prediction of traditional goat milk coagulation properties (MCP) and curd firmness over time (CFt) parameters via Fourier-transform infrared (FTIR) spectroscopy can be of significant economic interest to the dairy industry and can contribute to the breeding objectives for the genetic improvement of dairy goat breeds. Therefore, the aims of this study were to (1) explore the variability of milk FTIR spectra from 4 goat breeds (Camosciata delle Alpi, Murciano-Granadina, Maltese, and Sarda), and to assess the possible discriminant power of milk FTIR spectra among breeds, (2) assess the viability to predict coagulation traits by using milk FTIR spectra, and (3) quantify the effect of the breed on the prediction accuracy of MCP and CFt parameters. In total, 611 individual goat milk samples were used. Analysis of variance of measured MCP and CFt parameters was carried out using a mixed model including the farm and pendulum as random factors, and breed, parity, and days in milk as fixed factors. Milk spectra for each goat were collected over the spectral range from wavenumber 5,011 to 925 × cm-1. Discriminant analysis of principal components was used to assess the ability of FTIR spectra to identify breed of origin. A Bayesian model was used to calibrate equations for each coagulation trait. The accuracy of the model and the prediction equation was assessed by cross-validation (CRV; 80% training and 20% testing set) and stratified CRV (SCV; 3 breeds in the training set, one breed in the testing set) procedures. Prediction accuracy was assessed by using coefficient of determination of validation (R2VAL), the root mean square error of validation (RMSEVAL), and the ratio performance deviation. Moreover, measured and FTIR predicted traits were compared in the SCV procedure by assessing their least squares means for the breed effect, Pearson correlations, and variance heteroscedasticity. Results showed the feasibility of using FTIR spectra and multivariate analyses to correctly assign milk samples to their breeds of origin. The R2VAL values obtained with the CRV procedure were moderate to high for the majority of coagulation traits, with RMSEVAL and ratio performance deviation values increasing as the coagulation process progresses from rennet addition. Prediction accuracy obtained with the SCV were strongly influenced by the breed, presenting general low values restricting a practical application. In addition, the low Pearson correlation coefficients of Sarda breed for all the traits analyzed, and the heteroscedastic variances of Camosciata delle Alpi, Murciano-Granadina, and Maltese breeds, further indicated that it is fundamental to consider the differences existing among breeds for the prediction of milk coagulation traits.

Protein profile of cow milk from multibreed herds and its relationship with milk coagulation properties

The aims of this study were to estimate the effect of cow breed on milk protein profile, and to assess the relationship between protein profile and milk coagulation properties (MCP) predicted with mid-infrared spectroscopy (MIRS). The dataset included 173,841 test-day observations of 12,533 specialised (Holstein-Friesian [HF] and Brown Swiss [BS]) and dual-purpose cows (Simmental [SI] and Alpine Grey) sampled in 488 multi-breed herds. Fixed effects considered in the mixed model were breed, month of sampling, parity class, stage of lactation, and first-order interactions and random effects were cow nested within breed, herd and the residual. BS had the greatest casein (CN) fractions content and SI the greatest whey fractions content. A lesser clear pattern was observed when considering the proportion of protein fractions. Longer rennet coagulation, longer curd-firming time and firmer curd were observed for Alpine Grey, HF and BS, respectively. Regarding the index of milk aptitude to coagulate (IAC), BS and SI had the greatest value and HF and Alpine Grey (AG) the lowest one. Weak relationships were estimated between protein fractions and MCP. For whey proteins, all the analysed traits were optimised at β-lactoglobulin (β-LG) concentrations next to the maximum of the physiological range and at α-lactalbumin (α-LA) concentrations at the minimum level. For CNs, all the analysed traits were optimised at α-CN and β-CN concentrations closer to the minimum level and at κ-CN concentration at intermediate levels. Results highlighted the lower efficiency of HF milk for cheese manufacturing compared to the other breeds. Highlights Breed, month of sampling, parity order, stage of lactation and their interactions were important to explain the variability of milk protein fractions and coagulation traits. Brown Swiss (BS) had the greatest casein (CN) fractions content and Simmental (SI) the greatest whey fractions content. Longer rennet coagulation was observed for Alpine Grey, whereas firmer curd was observed for BS. Coagulation properties were optimised in milk with low concentration of α-CN and β-CN and for intermediate levels of κ-casein.

On the Effect of the Temperature-Humidity Index on Buffalo Bulk Milk Composition and Coagulation Traits.

Little is known about the effects of high levels of environmental temperature and humidity on milk yield and quality in buffaloes since this species is known to be more heat tolerant than cattle. However, the distribution of sweat glands and the dark skin color can negatively affect heat tolerance. Moreover, due to increased global temperatures, concerns regarding heat stress and thermoregulation in dairy animals, including buffaloes, have been extended to the northern hemisphere. In this study, the effects of both the temperature-humidity index (THI) and the maximum daily temperature-humidity index (MTHI) were estimated on bulk milk traits, namely fat, protein, lactose, urea content, pH levels, somatic cell score, coagulation properties, and bacteria count. The dataset consisted of repeated data from 99 Mediterranean water buffalo farms, and mixed models were used for the analyses. Supporting the negative correlations observed, bulk milk fat, protein, and lactose content were significantly lower when THI and MTHI were higher. Similarly, milk pH was lower when THI and MTHI were high; however, high levels of THI or MTHI seemed to not be markedly associated with the milk's coagulation ability. According to both analysis of variance and correlations, the somatic cell score was not significantly affected by the THI and MTHI. This is the first study based on a large dataset that evaluates the impact of high temperature and humidity in Italian buffalo milk and that provides correlations with traits of interest for the dairy industry, i.e., milk acidity and coagulation ability. In general, findings show that the effects of elevated THI and heat stress on bulk milk quality in buffalo is less evident than in cattle. These preliminary results intend to open debate on the issue of heat stress in dairy buffaloes that are reared in temperate regions. Further studies should focus on individual milk and performance and should investigate the relationship between high THI and buffalo fertility, behavior, and welfare.

Test positivity for Maedi–Visna virus and Mycobacterium avium ssp. paratuberculosis in Sarda ewes: Effects on milk composition and coagulation traits and heritability estimates for susceptibility

Maedi-Visna virus (MVV) and Mycobacterium avium ssp. paratuberculosis (MAP) are two pathogens that cause chronic, production-limiting diseases in dairy sheep. Although they are present worldwide, there are no detailed reports on their actual effects on milk traits in the literature. This study was designed to investigate the effects of test positivity to MVV and MAP on ovine milk yield, composition and coagulation properties, and curd-firming over time (CFt) variables in clinically healthy animals at the field level. The additive genetic variation and heritabilities of MVV and MAP positivity were also estimated. Milk samples were collected from 1,079 Sarda sheep kept on 23 farms, and pedigree information was obtained from the flock book. Milk yield was also recorded on the sampling date. Positivity for MVV and MAP was determined from milk samples using indirect ELISA test kits. Milk composition traits were measured by spectroscopy, milk coagulation properties were measured with a Formagraph (Foss Italia, Padua, Italy), and CFt traits were calculated using the data from the Formagraph diagram. The effects of MVV and MAP positivity on milk traits were determined through a set of mixed linear models, which took into account various sources of variation, such as days in milk, parity, and flock effects, and included the effects (positive or negative) of the 2 pathogens. A Bayesian threshold sire model with sire relationship was used to estimate genetic variation and heritability. The overall animal prevalence of MVV-positive ewes was 43.6%; on only 1 farm of the 23 tested were all sampled ewes negative. An overall animal prevalence of 10.6% was recorded for MAP, with 4 farms at 0%. Positivity for MVV significantly affected the logarithmic score of the bacterial count, curd firmness after 30 min and 45 min, and the curd-firming instant rate constant. We found significant effects of MAP infection on milk composition, pH, and rennet coagulation time. The mean of the posterior distributions of heritability estimates on the liability scale was 0.15 for MAP and 0.07 for MVV. Our results demonstrate that only a few traits are negatively affected by MVV and MAP positivity, and that there is exploitable genetic variation in MVV and MAP susceptibility in dairy sheep.

Association Analysis between SPP1, POFUT1 and PRLR Gene Variation and Milk Yield, Composition and Coagulation Traits in Sarda Sheep.

Simple SummaryThe purpose of our research was to analyze the association between the three candidate genes secreted phosphoprotein 1 (SPP1), protein O-fucosyltransferase 1 (POFUT1) and prolactin receptor (PRLR) with milk production, quality and coagulation properties in 380 Sarda dairy sheep. Results revealed an association between SPP1 and somatic cells count, in line with the function of this gene and with its genomic position. We revealed an association of POFUT1 variation with milk coagulation properties, and PRLR with quality. This information can be useful for future breeding schemes in sheep.Many studies focus on the identification of genomic regions that undergo selective processes, where evidence of selection is revealed and positional candidate genes are identified. The aim of the research was to evaluate the association between positional candidate genes, namely secreted phosphoprotein 1 (SPP1, sheep chromosome Ovis aries OAR6, 36.651–36.658 Mb), protein O-fucosyltransferase 1 (POFUT1, OAR13, 61.006–61.027 Mb) and prolactin receptor (PRLR, OAR16, 38.969–39.028 Mb) with milk yield, composition and coagulation traits. Eight single nucleotide polymorphisms (SNPs) mapping to the three genes were genotyped in 380 Sarda dairy sheep. Statistical analysis revealed an association between SNP rs161844011 at SPP1 (chromosome position Oar_v3 OAR6:36651870, gene region exon 7) and somatic cell score, while POFUT1 SNP rs424501869 (OAR13:61007495, intron 1) was associated with curd firmness both 45 and 60 min after rennet addition (p = 0.015 and p = 0.007, respectively). SNP rs400874750 at PRLR gene (OAR16:39004070, intron 2) had a significant association with lactose content (p = 0.020), somatic cell score (p = 0.038), rennet coagulation time (p = 0.018) and curd firming time (p = 0.047). The outcome of this research confirmed predictions based on genomic studies, producing new information regarding the SPP1, POFUT1 and PRLR genes, which may be useful for future breeding schemes.

Effects of animal versus vegetal rennet on milk coagulation traits in Mediterranean buffalo bulk milk

Given consumer interest in Mozzarella di latte di Bufala and other cheeses, and the growing interest of the cheese industry in offering products adequate for lactovegetarian consumers, this study aimed to compare clotting capacity of vegetal and animal rennet in buffalo milk. Milk coagulation properties of 1,261 buffalo bulk milk samples collected during milk quality testing were assessed by lactodynamography using commercial animal (75% chymosin and 25% bovine pepsin) and vegetal (Cynara cardunculus) rennets. Chemical composition of milk samples was predicted by MilkoScan (Foss Analytics, Hillerød, Denmark) calibrated with specific buffalo standards. Rennet effect (animal versus vegetal) was statistically analyzed with a paired t-test. Fat, protein, and lactose contents of milk samples were 7.94%, 4.52%, and 4.80%, respectively. A similar variability of milk coagulation properties was observed with both rennets, with the exception of greater variability of curd firmness at 30 min after the addition of vegetal rennet compared with animal rennet (73 and 26%, respectively). On average, when using plant rennet, milk started to coagulate and reached the 20-mm coagulum 12 ± 0.22 min and 1.9 ± 0.20 min, respectively, later than with animal rennet. Thirty minutes after rennet addition, curds were almost twice as firm in animal as in vegetal rennet (difference of 23.92 ± 0.66 mm). However, curd firmness at 60 min was only 1.21 ± 0.39 mm thicker with vegetal than with animal rennet. Moreover, when using animal rennet, 99.52% of samples started coagulating within the first 30 min of analysis, whereas only 70.42% did so when using vegetal rennet. We conclude that vegetal rennet has the capacity to coagulate buffalo milk, achieving a similar curd firmness to that of animal rennet at 60 min. Further studies are needed to evaluate the sensory characteristics and consumer acceptability of Mozzarella di latte di Bufala processed with vegetal rennet.

Effects of Chickpea in Substitution of Soybean Meal on Milk Production, Blood Profile and Reproductive Response of Primiparous Buffaloes in Early Lactation.

Simple SummaryCurrently, the protein needs of lactating buffaloes are mainly covered by soybean derivatives produced predominantly overseas. In order to promote the use of locally produced protein sources, in this study we tested the effects of total replacement of soybean meal by using chickpea meal, a protein-rich legume well adapted to and traditionally grown in the Mediterranean area. We evaluated the effects of these two alternative protein sources on blood profile, reproductive response and milk traits in primiparous buffaloes in early lactation. Based on our findings, chickpea meal does not impair the productive and reproductive performances of primiparous dairy buffaloes. In addition, chickpeas may represent a good alternative protein source for organic farms as it is not at risk of contamination by genetically modified cultivars.This study aimed to evaluate the effects of the use of chickpea meal in substitution of soybean meal on plasma metabolites, reproductive response, milk yield and composition and milk coagulation traits of primiparous buffaloes in early lactation. Eighteen primiparous buffaloes were blocked by age, body weight and days in milk and equally allotted to two experimental groups from 10 to 100 days of lactation. The experimental diets consisted of the same forage integrated with two different isonitrogenous and isoenergetic concentrates containing either 210 g/kg of soybean meal or 371 g/kg chickpea. The use of chickpea meal had no negative effects on dry matter intake (p = 0.69), body condition score (p = 0.33) and milk yield (p = 0.15). Neither milk composition nor blood metabolites were influenced by dietary treatments (p > 0.05), but an increment of urea concentrations in milk (p < 0.05) and blood plasma (p < 0.001) were observed in buffaloes fed chickpeas. Moreover, no effect (p > 0.05) of the dietary treatment was highlighted on milk coagulation traits as well as buffalo reproductive responses. We concluded that soybean meal can be replaced by chickpea meal in the diet for primiparous dairy buffaloes in the early lactation period without impairing their productive and reproductive performance.

Milk coagulation traits and cheese yields of purebred Holsteins and 4 generations of 3-breed rotational crossbred cows from Viking Red, Montbéliarde, and Holstein bulls

Crossbreeding is a strategy to counter the declining fertility, resilience, and longevity of purebred Holstein (Ho) cows. However, little is known of the effects of long-term systematic rotational crossbreeding on milk technological properties and cheese yield (CY). In this study, we compared the individual milk composition, milk coagulation properties (MCP), and CY of 468 purebred Ho and 648 crossbred (CR) cows obtained from two 3-breed rotational crossbreeding systems using Viking Red (VR), Montbéliarde (Mo), and Ho sires over 4 generations. Individual milk samples were collected once from 1,116 primiparous and multiparous cows kept in 2 dairy herds, raised for the production of Grana Padano (high milk yield, total mixed ration based on corn silage) and Parmigiano Reggiano (moderate milk yield, only dry feeds) cheeses. In both herds, a 3-breed rotational mating system was used in which Ho cows were first inseminated with VR, whereas Mo and Ho semen was used in the subsequent generations. In one herd, the sequence Mo-VR-Ho was also used. Individual milk samples were analyzed for milk composition, single-point MCP, and parameters for modeling curd firming over time, whereas CY and milk nutrient recovery in the curd were assessed through a laboratory cheese-making procedure. Compared with Ho, CR cows produced 5.8% less milk, which had comparable fat but greater protein and casein contents and lower lactose contents and somatic cell scores. Milk from CR cows tended to reach a curd firmness of 20 mm more quickly and exhibited greater curd firmness at 45 and 60 min from rennet addition. Holstein and CR cows yielded milk with similar CY and recovery in the curd traits. The milk fat content, somatic cell scores, curd firmness traits, and CY of CR cows relative to the Ho cows differed in the 2 herds, and the favorable effects on the CR cows were more evident in the herd with the greatest milk yield and the worst MCP traits. Crossbred cows of the 4 generations performed similarly, with the exception of the better MCP of the milk from first-generation CR cows. The 2 rotational systems using different sire-breed sequences also performed similarly. In summary, both rotational crossbreeding programs exhibited some advantage over the Ho purebred breeding system in terms of milk composition and MCP but not CY. Future research is needed to investigate the interactions between crossbreeding schemes and dairy systems.

Effects of somatic cell score on milk yield and mid-infrared predicted composition and technological traits of Brown Swiss, Holstein Friesian, and Simmental cattle breeds

High milk somatic cell count (SCC) influences milk production and quality; however, very little is known about the effect of low SCC on milk quality, especially in terms of mineral content and coagulation properties. Thus, the present study aimed to investigate the effects of somatic cell score (SCS), calculated as log2(SCC/100) + 3, on milk yield, composition (fat, crude protein, casein, lactose, milk urea nitrogen, protein fractions, and mineral contents), and coagulation properties of Brown Swiss, Holstein Friesian, and Simmental cows from multibreed herds. Milk composition and coagulation traits were predicted using mid-infrared spectroscopy. The data set comprised 95,591 observations of 6,940 cows in 313 multibreed herds, collected from January 2011 to December 2017. Observations were divided into 8 classes based on SCS. Statistical analysis was performed using a linear mixed model, which included breed, parity, stage of lactation, SCS class, and their interactions as fixed effects, and herd test day, cow, and residual as random effects. The probability that cows experienced SCS > 4.00 at 30 ± 5, 60 ± 5, or 90 ± 5 d after the observation test day was calculated for each SCS class, and odds ratios to the reference class (-1.00 < SCS ≤ 0.00) were reported. Results showed that the relationship between SCS and milk traits followed a third-order polynomial regression. The average loss of milk, fat, and crude protein yields were 0.43, 0.01, and 0.01 kg/d, respectively, for each SCS unit higher than 1.00. Very low SCS (<-1.00) had detrimental effects on milk yield and quality traits similar to or even stronger than high SCS (>4.00). Moreover, cows with SCS lower than -1.00 on a test day were about 7 times more likely to present high SCS within the following 90 ± 5 d than cows with SCS between -1.00 and 0.00. Breeds responded similarly to the increase of SCS, but the overall loss of fat and crude protein yields, and several minerals among Holstein Friesian were lower with increasing SCS. The best milk yield and quality were observed between SCS 0.00 and 1.00, but milk quality of Holstein Friesians started to decrease at lower SCS compared with milk quality of Brown Swiss and Simmental cows. Results suggest a breed-dependent optimum of SCS, and highlighted that very low SCS can be an indicator of udder health problems and, thus, may be used for early detection of mastitis.

Short communication: Prediction of milk coagulation and acidity traits in Mediterranean buffalo milk using Fourier-transform mid-infrared spectroscopy

Milk coagulation and acidity traits are important factors to inform the cheesemaking process. Those traits have been deeply studied in bovine milk, whereas scarce information is available for buffalo milk. However, the dairy industry is interested in a method to determine milk coagulation and acidity features quickly and in a cost-effective manner, which could be provided by Fourier-transform mid-infrared (FT-MIR) spectroscopy. The aim of this study was to evaluate the potential of FT-MIR to predict coagulation and acidity traits of Mediterranean buffalo milk. A total of 654 records from 36 herds located in central Italy with information on milk yield, somatic cell score, milk chemical composition, milk acidity [pH, titratable acidity (TA)], and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness) were available for statistical analysis. Reference measures of milk acidity and coagulation properties were matched with milk spectral information, and FT-MIR prediction models were built using partial least squares regression. The data set was divided into a calibration set (75%) and a validation set (25%). The capacity of FT-MIR spectroscopy to correctly classify milk samples based on their renneting ability was evaluated by a canonical discriminant analysis. Average values for milk coagulation traits were 13.32 min, 3.24 min, and 39.27 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. Milk acidity traits averaged 6.66 (pH) and 7.22 Soxhlet-Henkel degrees/100 mL (TA). All milk coagulation and acidity traits, except for pH, had high variability (17 to 46%). Prediction models of coagulation traits were moderately to scarcely accurate, whereas the coefficients of determination of external validation were 0.76 and 0.66 for pH and TA, respectively. Canonical discriminant analysis indicated that information on milk coagulating ability is present in the MIR spectra, and the model correctly classified as noncoagulating the 91.57 and 67.86% of milk samples in the calibration and validation sets, respectively. In conclusion, our results can be relevant to the dairy industry to classify buffalo milk samples before processing.

Comparison between automatic and conventional milking systems for milk coagulation properties and fatty acid composition in commercial dairy herds

The aim of this study was to investigate the effect of milking dairy cows using conventional milking parlour (CMP) and automatic milking system (AMS) on milk coagulation properties and fatty acid (FA) composition. Milk coagulation traits were rennet coagulation time, curd-firming time and curd firmness. Data consisted of 10,476 individual milk samples collected from 918 Holstein–Friesian cows in 8 herds: four herds milked cows using a CMP and four using an AMS. A linear mixed model was used to investigate sources of variation for milk yield, traditional quality traits, coagulation properties and FA profile. On average, cows from AMS produced 1 kg/d more milk than cows from CMP. Rennet coagulation time was slightly longer (+1.2 min) and free FA content was greater (+0.16 mmol/100 g milk fat) in milk from cows milked in AMS than CMP. Overall, the milking system did not affect the FA concentration of milk. Results of the present study suggest that AMS can be adopted without detrimental effects on milk features.

Plasmin–plasminogen system and milk coagulation properties of two Greek dairy sheep breeds

The enzymatic activities of plasmin (PL), plasminogen-derived (PG) and plasminogen activator (PA) and their correlation with the milk coagulation properties and major milk components were studied in two Greek sheep breeds during their whole lactation. Individual milk samples were collected at 3-week intervals from 14 Karagouniko and 14 Chios sheep breed. The enzymatic activities of PL, PG and PA were measured by colorimetric assay. The milk coagulation properties (rCT rennet clotting time, K20 curd firming time, A30 final curd consistency) were determined with a Formagraph. The results showed that PL, PG and PA activities and rennet clotting time (rCT) did not differ between the two breeds. However, K20 and A30 differed significantly between Karagouniko and Chios milk. The stage of lactation (early, mid or late) significantly affected PL, PG and PA activities. PL and PA activity levels were lower during late lactation (after the 150 days of the lactation period) compared to the corresponding levels during early and mid lactation, while a significant reduction of PG activity was observed from mid to late lactation stage. Lactation stage also significantly affected milk coagulation traits: A decrease in rCT occurred at mid lactation (from 100 to 150 days) while K20 increased from the early to the mid stage of lactation. The activities of PL and PA were significantly affected by the health status of the udder; milk with >300,000 SCC had 51% higher activity of PL and 86% higher activity of PA than milk containing <300,000 SCC. PG activity was 12% lower in milk with low SCC in comparison with milk with high SCC, but the results were not statistically significant. The coagulation properties of milk were not affected by SCC. A weak significant correlation exists between plasmin, PL+PG and K20.

Short communication: Genetic correlation and heritability of milk coagulation traits within and across lactations in Holstein cows using multiple-lactation random regression animal models

Genetic parameters of milk rennet coagulation time (RCT) and curd firmness (a30) among the first 3 lactations in Holstein cows were estimated. The data set included 39,960 test-day records from 5,216 Estonian Holstein cows (the progeny of 306 sires), which were recorded from April 2005 to May 2010 in 98 herds across the country. A multiple-lactation random regression animal model was used. Individual milk samples from each cow were collected during routine milk recording. These samples were analyzed for milk composition and coagulation traits with intervals of 2 to 3 mo in each lactation (7 to 305 DIM) and from first to third lactation. Mean heritabilities were 0.36, 0.32, and 0.28 for log-transformed RCT [ln(RCT)] and 0.47, 0.40, and 0.62 for a30 for parities 1, 2, and 3, respectively. Mean repeatabilities for ln(RCT) were 0.53, 0.55, and 0.56, but 0.59, 0.61, and 0.68 for a30 for parities 1, 2 and 3, respectively. Mean genetic correlations between ln(RCT) and a30 were −0.19, −0.14, and 0.02 for parities 1, 2, and 3, respectively. Mean genetic correlations were 0.91, 0.79, and 0.99 for ln(RCT), and 0.95, 0.94, and 0.94 for a30 between parities 1 and 2, 1 and 3, and 2 and 3, respectively. Due to these high genetic correlations, we concluded that for a proper genetic evaluation of milk coagulation properties it is sufficient to record RCT and a30 only in the first lactation.