Prolonged observation and modelling of milk coagulation, curd firming, and syneresis

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

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

Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle

In recent years, increasing attention has been focused on the genetic evaluation of protein fractions in cow milk with the aim of improving milk quality and technological characteristics. In this context, advances in high-throughput phenotyping by Fourier transform infrared (FTIR) spectroscopy offer the opportunity for large-scale, efficient measurement of novel traits that can be exploited in breeding programs as indicator traits. We took milk samples from 2,558 Holstein cows belonging to 38 herds in northern Italy, operating under different production systems. Fourier transform infrared spectra were collected on the same day as milk sampling and stored for subsequent analysis. Two sets of data (i.e., phenotypes and FTIR spectra) collected in 2 different years (2013 and 2019-2020) were compiled. The following traits were assessed using HPLC: true protein, major casein fractions [α_S1-casein (CN), α_S2-CN, β-CN, κ-CN, and glycosylated-κ-CN], and major whey proteins (β-lactoglobulin and α-lactalbumin), all of which were measured both in grams per liter (g/L) and proportion of total nitrogen (% N). The FTIR predictions were calculated using the gradient boosting machine technique and tested by 3 different cross-validation (CRV) methods. We used the following CRV scenarios: (1) random 10-fold, which randomly split the whole into 10-folds of equal size (9-folds for training and 1-fold for validation); (2) herd/date-out CRV, which assigned 80% of herd/date as the training set with independence of 20% of herd/date assigned as the validation set; (3) forward/backward CRV, which split the data set in training and validation set according with the year of milk sampling (FTIR and gold standard data assessed in 2013 or 2019-2020) using the "old" and "new" databases for training and validation, and vice-versa with independence among them; (4) the CRV for genetic parameters (CRV-gen), where animals without pedigree as assigned as a fixed training population and animals with pedigree information was split in 5-folds, in which 1-fold was assigned to the fixed training population, and 4-folds were assigned to the validation set (independent from the training set). The results (i.e., measures and predictions) of CRV-gen were used to infer the genetic parameters for gold standard laboratory measurements (i.e., proteins assessed with HPLC) and FTIR-based predictions considering the CRV-gen scenario from a bi-trait animal model using single-step genomic BLUP. We found that the prediction accuracies of the gradient boosting machine equations differed according to the way in which the proteins were expressed, achieving higher accuracy when expressed in g/L than when expressed as % N in all CRV scenarios. Concerning the reproducibility of the equations over the different years, the results showed no relevant differences in predictive ability between using "old" data as the training set and "new" data as the validation set and vice-versa. Comparing the additive genetic variance estimates for milk protein fractions between the FTIR predicted and HPLC measures, we found reductions of -19.7% for milk protein fractions expressed in g/L, and -21.19% expressed as % N. Although we found reductions in the heritability estimates, they were small, with values ranging from -1.9 to -7.25% for g/L, and -1.6 to -7.9% for % N. The posterior distributions of the additive genetic correlations (r_a) between the FTIR predictions and the laboratory measurements were generally high (>0.8), even when the milk protein fractions were expressed as % N. Our results show the potential of using FTIR predictions in breeding programs as indicator traits for the selection of animals to enhance milk protein fraction contents. We expect acceptable responses to selection due to the high genetic correlations between HPLC measurements and FTIR predictions.

A Study of Milk Composition and Coagulation Properties of Holstein-Friesian, Jersey, and Their Cross Milked Once or Twice a Day

The objective of the study was to explore the effect of breed on the composition and coagulation properties (rennet coagulation time (min), curd firming rate (min), and curd firmness (mm)) of milk from cows milked once a day or twice a day in the morning and afternoon, using a Formagraph. Thirty cows (11 Holstein-Friesian, 8 Holstein-Friesian × Jersey cross, and 11 Jersey) from a once-a-day milking herd and thirty cows (16 Holstein-Friesian, 10 Holstein-Friesian × Jersey cross, and 4 Jersey) from a twice-a-day milking herd were sampled in late lactation. The milk composition and coagulation properties were analysed for each milk sample. Jersey cows had better milk coagulation properties at each milking frequency-milking time compared to Holstein-Friesian cows. Curd firmness 30 min after the addition of rennet was positively (p < 0.05) correlated with the protein concentration. However, the correlations were inconsistent between milking frequencies and milking times, resulting in poor prediction of the changes in cheese-making potential. This study indicated that milk composition and coagulation properties were affected by breed and milking frequency. The effect of the breed could be due to the variation in the composition of the milk, but firm recommendations were hampered by a low number of samples. Further research with larger cow numbers is justified.

Quarter-level analyses of the associations among subclinical intramammary infection and milk quality, udder health, and cheesemaking traits in Holstein cows

In this study, we investigated associations among subclinical intra-mammary infection (IMI) and quarter-level milk composition, udder health indicators, and cheesemaking traits. The dataset included records from 450 Holstein cows belonging to three dairy herds. After an initial screening (T0) to identify animals infected by Streptococcus agalactiae, Streptococcus uberis, Staphylococcus aureus, and Prototheca spp., 613 quarter milk samples for 2 different sampling times (T1 and T2, 1 mo after T1) were used for analysis. Milk traits were analyzed using a hierarchical linear mixed model including the effects of days in milk, parity and herd, and bacteriological and inflammatory category [culture negative with somatic cell count (SCC) <200,000 cells/mL; culture negative with SCC ≥200,000 cells/mL; or culture positive]. All udder health indicators were associated with increased SCC and IMI at both sampling times. The largest effects were detected at T2 for milk lactose (-7% and -5%) and milk conductivity (+9% and +8%). In contrast, the increase in differential SCC (DSCC) in samples with elevated SCC was larger at T1 (+17%). Culture-negative samples with SCC ≥200,000 cells/mL had the highest SCC and greatest numbers of polymorphonuclear-neutrophils-lymphocytes and macrophages at both T1 and T2. Regarding milk cheesemaking ability, samples with elevated SCC showed the worst pattern of curd firmness at T1 and T2. At T2, increased SCC and IMI induced large decreases in recoveries of nutrients into the curd, in particular recovered protein (-14% and -16%) and recovered fat (-12% and -14%). Different behaviors were observed between Strep. agalactiae and Prototheca spp., especially at T2. In particular, samples that were positive for Strep. agalactiae had higher proportions of DSCC (+19%) compared with negative samples with low SCC, whereas samples that were positive for Prototheca spp. had lower DSCC (-11%). Intramammary infection with Prototheca spp. increased milk pH compared with culture-negative samples (+3%) and negative samples that had increased SCC (+2%). The greatest impairment in curd firmness at 30 min from rennet addition was observed for samples that were positive for Prototheca spp. (-99% compared with negative samples, and -98% compared with negative samples with high SCC). These results suggest that IMI caused by Prototheca spp. have detrimental effects on milk technological traits that deserve further investigation of the mechanisms underlying animals' responses to infection.

Composition and aptitude for cheese-making of milk from cows, buffaloes, goats, sheep, dromedary camels, and donkeys

Bovines account for about 83% of the milk and dairy products consumed by humans worldwide, the rest represented by bubaline, caprine, ovine, camelid, and equine species, which are particularly important in areas of extensive pastoralism. Although milk is increasingly used for cheese production, the cheese-making efficiency of milk from the different species is not well known. This study compares the cheese-making ability of milk sampled from lactating females of the 6 dairy species in terms of milk composition, coagulation properties (using lactodynamography), curd-firming modeling, nutrients recovered in the curd, and cheese yield (through laboratory model-cheese production). Equine (donkey) milk had the lowest fat and protein content and did not coagulate after rennet addition. Buffalo and ewe milk yielded more fresh cheese (25.5 and 22.9%, respectively) than cow, goat, and dromedary milk (15.4, 11.9, and 13.8%, respectively). This was due to the greater fat and protein contents of the former species with respect to the latter, but also to the greater recovery of fat in the curd of bubaline (88.2%) than in the curd of camelid milk (55.0%) and consequent differences in the recoveries of milk total solids and energy in the curd; protein recovery, however, was much more similar across species (from 74.7% in dromedaries to 83.7% in bovine milk). Compared with bovine milk, the milk from the other Artiodactyla species coagulated more rapidly, reached curd firmness more quickly (especially ovine milk), had a more pronounced syneresis (especially caprine milk), had a greater potential asymptotical curd firmness (except dromedary and goat milk), and reached earlier maximum curd firmness (especially caprine and ovine milk). The maximum measured curd firmness was greater for bubaline and ovine milk, intermediate for bovine and caprine milk, and lower for camelid milk. The milk of all ruminant species can be used to make cheese, but, to improve efficiency, cheese-making procedures need to be optimized to take into account the large differences in their coagulation, curd-firming, and syneresis properties.

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k₂₀), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCT_eq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CF_max), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CF_max (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCT_eq (0.53 and 0.41), t_max (0.38 and 0.48). Log MAC count was correlated with k₂₀ (+0.34), and log PMN-LYM count was correlated with CF_max (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

The mineral profile affects the coagulation pattern and cheese-making efficiency of bovine milk

Natural variations in milk minerals, their relationships, and their associations with the coagulation process and cheese-making traits present an opportunity for the differentiation of milk destined for high-quality natural products, such as traditional specialties or Protected Designation of Origin (PDO) cheeses. The aim of this study was to quantify the effects of the native contents of Ca, P, Na, K, and Mg on 18 traits describing traditional milk coagulation properties (MCP), curd firming over time (CF_t) equation parameters, cheese yield (CY) measures, and nutrient recoveries in the curd (REC) using models that either included or omitted the simultaneous effects of milk fat and casein contents. The results showed that, by including milk fat and casein and the minerals in the statistical model, we were able to determine the specific effects of each mineral on coagulation and cheese-making efficiency. In general, about two-thirds of the apparent effects of the minerals on MCP and the CF_t equation parameters are actually mediated by their association with milk composition, especially casein content, whereas only one-third of the effects are direct and independent of milk composition. In the case of cheese-making traits, the effects of the minerals were mediated only negligibly by their association with milk composition. High Ca content had a positive effect on the coagulation pattern and cheese-making traits, favoring water retention in the curd in particular. Phosphorus positively affected the cheese-making traits in that it was associated with an increase in CY in terms of curd solids, and in all the nutrient recovery traits. However, a very high P content in milk was associated with lower fat recovery in the curd. The variation in the Na content in milk only mildly affected coagulation, whereas with regard to cheese-making, protein recovery was negatively associated with high concentrations of this mineral. Potassium seemed not to be actively involved in coagulation and the cheese-making process. Magnesium content tended to slow coagulation and reduce CY measures. Further studies on the relationships of minerals with casein and protein fractions could deepen our knowledge of the role of all minerals in coagulation and the cheese-making process.

Lower critical concentration temperature as thermodynamic origin of syneresis: Case of kappa-carrageenan solution

Polysaccharide ubiquity is trimmed for applications of low syneresis impact. This syneresis may be crucial for specific applications that are very sensitive to gel dimension stability, namely, 3D scaffolds for cell culture for disease diagnosis and tissue engineering. We hypothesized that the syneresis origin results from the kappa-carrageenan (kC) polysaccharide thermodynamic instability, and we demonstrated this by measuring the critical (coil-to-coil contact) concentration as a function of temperature. The impact of 5 mM, 10 mM and 15 mM KCl salt on the critical concentration of the solution and the lower critical concentration temperature (LCCT) were particularly investigated. For the kC polysaccharide, the gelation temperature (T_g) falls at temperatures below the LCCT, which explains the shrinking or syneresis reaction of the polysaccharide gels. The gap between T_g and LCCT would be the thermomotive force of the syneresis of many colloidal gels.

Coagulation process in Manchega sheep milk from Spain: A path analysis approach

Characteristics of sheep milk are of great interest for the dairy industry, as almost the totality of production is intended for cheesemaking. However, the existing relationships between these variables are complex. This study assessed composition, hygienic quality, coagulation properties, and curd yield of 1,200 individual Manchega sheep milk samples. The aim was to compare the effect of composition and hygienic quality on coagulation and curdling, and to evaluate the relationship between curd yields and the coagulation process and the effect of other features by using path analysis methodologies. Outcomes proved path analysis to be a useful and effective tool to assess these relationships through direct and indirect paths within the same model. Results showed that the factors that had a direct influence on milk coagulation were lactose concentration, casein content, and initial pH of milk. Contrastingly, somatic cells did not seem to have any effect (direct or indirect) on the coagulation process. Factors that directly affected curd yield were fat content, lactose concentration, casein content, and curd moisture. However, technological parameters showed little effect over curd yield.

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 (CF_t) 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 CF_t parameters. In total, 611 individual goat milk samples were used. Analysis of variance of measured MCP and CF_t 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 (R²_VAL), the root mean square error of validation (RMSE_VAL), 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 R²_VAL values obtained with the CRV procedure were moderate to high for the majority of coagulation traits, with RMSE_VAL 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.

Estimation of genetic parameters for cheese-making traits in Spanish Churra sheep

The global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, -0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and -0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.

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 (CF_t) 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 CF_t 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

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.

Coagulation Traits of Sheep and Goat Milk

Milk production from sheep and goat species is continuously growing worldwide, and its main use is for cheesemaking. Given that the final quality of cheese is linked to the traits of raw milk cheese yield at dairy plants, it is often calculated by using predictive formulas based on fat and protein content. Predictive formulas have been studied for bovine milk and are very effective but not appropriate for sheep and goat milk. Several methods, which simulate the actual coagulation processes, are available at the laboratories. This article reviews the available literature about rennet coagulation and cheese yield traits from sheep and goat milk and the methods used at the laboratory level. In general, if compared to cow milk, sheep and goat milk are characterized by shorter rennet coagulation times and a very limited amount of non-coagulating samples. Curd firmness of sheep milk is almost independent from the rennet coagulation time, and some coagulation traits can be predicted by infrared spectra. In addition, coagulation traits are characterized by appropriate values of heritability to be considered in selective breeding plans. With regard to goat milk, rennet coagulation time and cheese yield are strongly influenced by the breed effect.

Association between the GHR, GHRHR and IGF1 gene polymorphisms and milk coagulation properties in Sarda sheep

We investigated whether variation of the sheep Growth Hormone Receptor (GHR), Growth Hormone Releasing Hormone Receptor (GHRHR) and Insulin-Like Growth Factor 1 (IGF1) genes were associated with milk coagulation properties (MCP) in sheep. The GHR, GHRHR and IGF1 genes are part of the GH system, which is known to modulate metabolism, growth and reproduction as well as mammogenesis and galactopoiesis in dairy species. A total of 380 dairy Sarda sheep were genotyped for 36 SNPs mapping to these three genes. Traditional MCP were measured as rennet coagulation time (RCT), curd-firming time (k20) and curd firmness at 30 m (a30). Modeling of curd firming over time (CFt) was based on a 60 m lactodynamographic test, generating a total of 240 records of curd firmness (mm) for each milk sample. The model parameters obtained included: the rennet coagulation time as a result of modeling all data available (RCTeq, min); the asymptotic potential value of curd firmness (CFP, mm) at an infinite time; the CF instant rate constant (kCF, %/min); the syneresis instant rate constant (kSR, %/min); the maximum value of CF (CFmax, mm) and the time at achievement of CFmax (tmax, min). Statistical analysis revealed that variation of the GHR gene was significantly associated with RCT, kSR and CFP (P < 0.05). No other significant associations were detected. These findings may be useful for the dairy industry, as well as for selection programs.

Effects of Summer Transhumance of Dairy Cows to Alpine Pastures on Body Condition, Milk Yield and Composition, and Cheese Making Efficiency

Simple Summary

Summer transhumance of dairy cows is a seasonal pastoral system practiced in many European countries from ancient times. This practice provides additional forage supply for mountain dairy farms and plays a role in the preservation of landscape, biodiversity, and natural habitats and conservation of local traditional dairy products, but it may affect cows’ physiological and nutritional status. This study aimed to investigate the effects of transhumance of Brown Swiss cows to summer pastures on the yield, composition, and coagulation properties of milk, and on cheese yield. For this study, twelve multiparous cows from a mountain lowland permanent farm were divided into two groups of six cows: One group stayed at the permanent farm while the other moved to the alpine pasture (1860 m above sea level). Cows at the alpine pasture had reduced milk yield and body condition, and greater fat and lower protein contents in milk compared to cows at the permanent farm. Conversely, neither milk coagulation properties nor cheese yield were affected by summer transhumance. In conclusion, summer transhumance did not affect the cheese making efficiency of milk compared to permanent farm, but the negative effect on milk yield depressed daily cheese yield, which was 2 kg/d lower in cows moved to Alpine pasture.

Abstract

Summer transhumance to alpine pastures (ALP) is widespread in dairy systems of alpine regions. This study aimed to investigate the effects of transhumance of Brown Swiss cows to ALP on the yield, composition, and coagulation properties of milk (MCP), and on cheese yield (CY). The study involved 12 multiparous cows kept at a mountain lowland permanent farm (PF), which were divided into two equal groups: One remained at the PF, the other was moved to the ALP (1860 m above sea level) from July to September. Every month (June to October), daily milk yield (MY) and body condition score (BCS) were recorded, and individual milk samples (n = 60, 2000 mL each) were collected to assess milk composition, MCP, and CY. Compared with PF, ALP cows had a reduced MY and BCS, which was maintained on return to the PF, greater fat and lower protein contents of milk. Neither MCP nor CY were affected by summer transhumance. In conclusion, summer transhumance did not affect the cheese making efficiency of milk but depressed MY and consequently daily cheese yield, which was nearly 2 kg/d lower for the ALP than the PF cows and was only partially recovered after returning to the PF in autumn.

Genetic variation in serum protein pattern and blood β-hydroxybutyrate and their relationships with udder health traits, protein profile, and cheese-making properties in Holstein cows

The aim of this study was to investigate in Holstein cows the genetic basis of blood serum metabolites [i.e., total protein, albumin, globulin, albumin:globulin ratio (A:G), and blood β-hydroxybutyrate (BHB)], a set of milk phenotypes related to udder health, milk quality technological characteristics, and genetic relationships among them. Samples of milk were collected from 498 Holstein cows belonging to 28 herds. All animal welfare and milk phenotypes were assessed using standard analytical methodology. A set of Bayesian univariate and bivariate animal models was implemented via Gibbs sampling, and statistical inference was based on the marginal posterior distributions of parameters of concern. We observed a small additive genetic influence for serum albumin concentrations, moderate heritability (≥0.20) for total proteins, globulins, and A:G, and high heritability (0.37) for blood BHB. Udder health traits (somatic cell score, milk lactose, and milk pH) showed low or moderate heritabilities (0.15-0.20), whereas variations in milk protein fraction concentrations were confirmed as mostly under genetic control (heritability: 0.21-0.71). The moderate and high heritabilities observed for milk coagulation properties and curd firming modeling parameters provided confirmation that genetic background exerts a strong influence on the cheese-making ability of milk, largely due to genetic polymorphisms in the major milk protein genes. Blood BHB showed strong negative genetic correlations with globulins (-0.619) but positive correlations with serum albumin (0.629) and A:G (0.717), which suggests that alterations in the serum protein pattern and BHB blood levels are likely to be genetically related. Strong relationships were found between albumin and fat percentages (-0.894), between globulin and α_S2-CN (-0.610), and, to a lesser extent, between serum protein pattern and milk technological characteristics. Genetic relationships between blood BHB and traits related to udder health and milk quality and technological characteristics were mostly weak. This study provides evidence that there is exploitable additive genetic variation for traits related to animal health and welfare and throws light on the shared genetic basis of these traits and the phenotypes related to the quality and cheese-making ability of milk.

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.

Inferring individual cow effects, dairy system effects and feeding effects on latent variables underlying milk protein composition and cheese-making traits in dairy cattle

We examined the latent structure of 26 cheese related phenotypes in dairy cattle. Traits related to milk yield and quality (8 traits), milk protein fractions (8 traits), coagulation and curd firmness indicators (CF, 5 traits) and cheese-making phenotypes (cheese yields (%CY) and nutrient recoveries in the curd (REC), 5 traits) were analysed through multivariate factor analysis (MFA) using a varimax rotation. All phenotypes were measured in 1264 Brown Swiss cows. Ten mutual orthogonal, latent variables (factors; Fs) were obtained explaining 74% of the original variability. These Fs captured basic concepts of the cheese-making process. More precisely, the first 4 Fs, sorted by variance explained, were able to capture the underlying structure of the CY percentage (F1: %CY), the CF process with time (F2: CFt), the milk and solids yield (F3: Yield) and the presence of nitrogen (N) in the cheese (F4: Cheese N). Moreover, 4 Fs (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN and F9: as1-CN-Ph) were related to the basic milk caseins and 1 factor was associated with the α-LA whey protein (F10: α-LA). A factor describing udder health status (F6: Udder health), mainly loaded on lactose, other nitrogen compounds in the milk and SCS, was also obtained. Further, we inferred the effects of some potential sources of variation (e.g. stage of lactation and parity) including feeding and management systems. Stage of lactation had a significant effect for 7 of the 10 Fs, followed by parity of the cow (3 Fs), dairy system and feeding (3 Fs). Our work demonstrates the usefulness of MFA in reducing a large number of variables to a few latent factors with biological meaning and representing groups of traits that describe a complex process like cheese-making. Such an approach would be a valuable tool for studying the influence of different production environments and individual animal factors on protein composition and cheese-making related traits.

A new study of the kinetics of curd production in the process of cheese manufacture

We studied the role played by temperature and rennet concentration in the coagulation process for cheese manufacture and the evaluation of their kinetics. We concluded that temperature is the main factor that determines the kinetics. The rennet concentration was unimportant probably due to the fast action of the enzyme chymosin. The Dynamic light scattering technique allowed measuring the aggregate's size and their formation kinetics. The volume fraction of solids was determined from viscosity measurements, showing profiles that are in agreement with the size profiles. The results indicate that the formation of the aggregates for rennet cheese is strongly dependent on temperature and rennet concentration. The results revealed that at 35·5 °C the volume fraction of solids has the maximum slope, indicating that at this temperature the curd is formed rapidly. The optimal temperature throughout the process was established. Second-order kinetics were obtained for the process. We observed a quadratic dependence between the rennet volume and the volume fraction of solids (curd), thereby indicating that the kinetics of the curd production should be of order two.

Genome-wide association and pathway-based analysis using latent variables related to milk protein composition and cheesemaking traits in dairy cattle

The aim of this study was to perform genome-wide associations (GWAS) and gene-set enrichment analyses with protein composition and cheesemaking-related latent variables (factors; F) in a cohort of 1,011 Italian Brown Swiss cows. Factor analysis was applied to identify latent structures of 26 phenotypes related to bovine milk quantity and quality, protein fractions [α_S1-, α_S2-, β-, and κ-casein (CN), β-lactoglobulin, and α-lactalbumin (α-LA)], coagulation and curd firming at time t (CF_t) measures, and cheese properties [cheese yield (%CY) and nutrients recovery in the curd] of individual cows. Ten orthogonal F were extracted, explaining 74% of the original variability. Factor 1_%CY underlined the %CY characteristics, F2_CFt was related to the CF_t process parameters, F3_Yield was considered as descriptor of milk and solids yield, whereas F4_{Cheese N} underscored the presence of nitrogenous compounds (N) into the cheese. Four more F were related to the milk caseins (F5_αS1-β-CN, F7_β-κ-CN, F8_αS2-CN, and F9_αS1-CN-Ph) and 1 F was linked to the whey protein (F10_α-LA); 1 F underlined the udder health status (F6_{Udder health}). All cows were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc., San Diego, CA). Single marker regression GWAS were fitted. Gene-set enrichment analysis was run on GWAS results, using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases, to reveal ontologies or pathways associated with the F. All F but F3_Yield showed significance in GWAS. Signals in 10 Bos taurus autosomes (BTA) were detected. High peaks on BTA6 (∼87 Mbp) were found for F6_β-κ-CN, F5_αS1-β-CN, and at the tail of BTA11 (∼104 Mbp) for F4_{Cheese N}. Gene-set enrichment analyses showed significant results (false discovery rate at 5%) for F8_αS2-CN, F1_%CY, F4_{Cheese N}, and F10_α-LA. For F8_αS2-CN, 33 Gene Ontology terms and 3 Kyoto Encyclopedia of Genes and Genomes categories were enriched, including terms related to ion transport and homeostasis, neuron function or part, and GnRH signaling pathway. Our results support the feasibility of factor analysis as a dimension reduction technique in genomic studies and evidenced a potential key role of α_S2-CN in milk quality and composition.

From cow to cheese: genetic parameters of the flavour fingerprint of cheese investigated by direct-injection mass spectrometry (PTR-ToF-MS)

BACKGROUND

Volatile organic compounds determine important quality traits in cheese. The aim of this work was to infer genetic parameters of the profile of volatile compounds in cheese as revealed by direct-injection mass spectrometry of the headspace gas from model cheeses that were produced from milk samples from individual cows.

METHODS

A total of 1075 model cheeses were produced using raw whole-milk samples that were collected from individual Brown Swiss cows. Single spectrometry peaks and a combination of these peaks obtained by principal component analysis (PCA) were analysed. Using a Bayesian approach, we estimated genetic parameters for 240 individual spectrometry peaks and for the first ten principal components (PC) extracted from them.

RESULTS

Our results show that there is some genetic variability in the volatile compound fingerprint of these model cheeses. Most peaks were characterized by a substantial heritability and for about one quarter of the peaks, heritability (up to 21.6%) was higher than that of the best PC. Intra-herd heritability of the PC ranged from 3.6 to 10.2% and was similar to heritabilities estimated for milk fat, specific fatty acids, somatic cell count and some coagulation parameters in the same population. We also calculated phenotypic correlations between PC (around zero as expected), the corresponding genetic correlations (from -0.79 to 0.86) and correlations between herds and sampling-processing dates (from -0.88 to 0.66), which confirmed that there is a relationship between cheese flavour and the dairy system in which cows are reared.

CONCLUSIONS

This work reveals the existence of a link between the cow's genetic background and the profile of volatile compounds in cheese. Analysis of the relationships between the volatile organic compound (VOC) content and the sensory characteristics of cheese as perceived by the consumer, and of the genetic basis of these relationships could generate new knowledge that would open up the possibility of controlling and improving the sensory properties of cheese through genetic selection of cows. More detailed investigations are necessary to connect VOC with the sensory properties of cheese and gain a better understanding of the significance of these new phenotypes.

Breed of cow and herd productivity affect milk composition and modeling of coagulation, curd firming, and syneresis

Milk coagulation properties (MCP) have been widely investigated in the past using milk collected from different cattle breeds and herds. However, to our knowledge, no previous studies have assessed MCP in individual milk samples from several multi-breed herds characterized by either high or low milk productivity, thereby allowing the effects of herd and cow breed to be evaluated independently. Multi-breed herds (n=41) were classified into 2 categories based on milk productivity (high vs. low), defined according to the average milk net energy yielded daily by lactating cows. Milk samples were taken from 1,508 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, Jersey) and 3 dual-purpose (Simmental, Rendena, Alpine Grey) breeds, and analyzed in duplicate (3,016 tests) using 2 lactodynamographs to obtain 240 curd firming (CF) measurements over 60min (1 every 15 s) for each duplicate. The 5 traditional single-point MCP (RCT, k₂₀, a₃₀, a₄₅, and a₆₀) were yielded directly by the instrument from the available CF measures. All 240 CF measures of each replicate were also used to estimate 4 individual equation parameters: RCT estimated according to curd firm change over time modeling (RCT_eq), asymptotic potential curd firmness (CF_P), curd firming instant rate constant (k_CF), and syneresis instant rate constant (k_SR) and 2 derived traits: maximum curd firmness achieved within 45min (CF_max) and time at achievement of CF_max (t_max) by curvilinear regression using a nonlinear procedure. Results showed that the effect of herd-date on traditional and modeled MCP was modest, ranging from 6.1% of total variance for k₂₀ to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for t_max to 82.5% for RCT_eq. The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a₆₀, k_SR, k_CF, and t_max: 57 to 71%). Reproducibility, taking into account the effect of instrument, was equal to or slightly lower than repeatability. Milk samples collected in farms characterized by high productivity exhibited delayed coagulation (RCT_eq: 18.6 vs. 16.3min) but greater potential curd firmness (CF_P: 76.8 vs. 71.9mm) compared with milk samples collected from low-productivity herds. Parity and days in milk influenced almost all MCP. Large differences in all MCP traits were observed among breeds, both between specialized and dual-purpose breeds and within these 2 groups of breeds, even after adjusting for milk quality and yield. Milk quality and MCP of samples from Jersey cows, and coagulation time of samples from Rendena cows were better than in milk from Holstein-Friesian cows, and intermediate results were found with the other breeds of Alpine origin. The results of this study, taking into account the intrinsic limitation of this technique, show that the effects of breed on traditional and modeled MCP are much greater than the effects of herd productivity class, parity, and DIM. Moreover, the variance in individual animals is much greater than the variance in individual herds within herd productivity class. It seems that improvement in MCP depends more on genetics (e.g., breed, selection) than on environmental and management factors.

Variation of milk coagulation properties, cheese yield, and nutrients recovery in curd of cows of different breeds before, during and after transhumance to highland summer pastures

This paper aimed at evaluating the effect of summer transhumance to mountain pastures of dairy cows of different breeds on cheese-making ability of milk. Data were from 649 dairy cows of specialized (Holstein Friesian and Brown Swiss) dual purpose (Simmental) and local (mostly Rendena and Alpine Grey) breeds. The Fourier-Transform Infra-Red Spectra (FTIRS) of their milk samples were collected before and after transhumance in 109 permanent dairy farms, and during transhumance in 14 summer farms (with multi-breeds herds) of the Trento Province, north-eastern Italy. A variety of 18 traits describing milk coagulation, curd firming, cheese yield and nutrients recovery in curd/loss in whey were predicted on the basis of FTIRS collected at the individual cow level. Moving the cows to summer farms improved curd firming traits but reduced cheese yields because of an increase of water and fat lost in the whey. During summer grazing, most of cheese-making traits improved, often non-linearly. The milk from summer farms supplementing cows with more concentrates showed better curd firming and cheese yield, because of lower fat lost in the whey. The breed of cows affected almost all the traits with a worst cheese-making ability for milk samples of Holsteins through all the trial, and interacted with concentrate supplementation because increasing compound feed tended to improve cheese-making traits for all breed, with the exception of local breeds for coagulation time and of Brown Swiss for curd firming time. In general, summer transhumance caused a favourable effect on cheese-making aptitude of milk, even though with some difference according to parity, initial days in milk, breed and concentrate supplementation of cows.

Cheesemaking in highland pastures: Milk technological properties, cream, cheese and ricotta yields, milk nutrients recovery, and products composition

Summer transhumance of dairy cows to high Alpine pastures is still practiced in many mountainous areas. It is important for many permanent dairy farms because the use of highland pastures increases milk production and high-priced typical local dairy products often boost farm income. As traditional cheese- and ricotta-making procedures in Alpine pastures are central to this dairy system, the objective of this study was to characterize the quality and efficiency of products and their relationships with the quality and availability of grass during the grazing season. The milk from 148 cows from 12 permanent farms reared on a temporary farm located in Alpine pastures was processed every 2wk during the summer (7 cheesemakings from late June to early September). During each processing, 11 dairy products (4 types of milk, 2 by-products, 3 fresh products, and 2 ripened cheeses) were sampled and analyzed. In addition, 8 samples of fresh forage from the pasture used by the cows were collected and analyzed. At the beginning of the pasture season the cows were at 233±90d in milk, 2.4±1.7 parities, and produced 23.6±5.7kg/d of milk. The milk yield decreased with the move from permanent to temporary farms and during the entire summer transhumance, but partly recovered after the cows returned to the permanent farms. Similar trends were observed for the daily yields of fat, protein, casein, lactose, and energy, as we found no large variations in the quality of the milk, with the exception of the first period of Alpine pasture. The somatic cell counts of milk increased during transhumance, but this resulted from a concentration of cells in a lower quantity of milk rather than an increase in the total number of cells ejected daily from the udder. We noted a quadratic trend in availability of forage (fresh and dry matter weight per hectare), with a maximum in late July. The quality of forage also varied during the summer with a worsening of chemical composition. The evening milk (before and after natural creaming), the whole morning milk, and the mixed vat milk had different chemical compositions, traditional coagulation properties, and curd-firming modeling parameters. These variations over the pasture season were similar to the residual variations with respect to chemical composition, and much lower with respect to coagulation and curd-firming traits. Much larger variations were noted in cream, cheese, and ricotta yields, as well as in nutrient recoveries in curd during the pasture season. The protein content of forage was correlated with some of the coagulation and curd-firming traits, the ether extract of forage was positively correlated with milk fat content and cheese yields, and fiber fractions of forage were unfavorably correlated with some of the chemical and technological traits. Traditional cheese- and ricotta-making procedures showed average cream, cheese, and ricotta yields of 6.3, 14.2, and 4.9%, respectively, and an overall recovery of almost 100% of milk fat, 88% of milk protein, and 60% of total milk solids.

The nonlinear effect of somatic cell count on milk composition, coagulation properties, curd firmness modeling, cheese yield, and curd nutrient recovery

The aim of this study was to investigate the relationships between somatic cell count (SCC) in milk and several milk technological traits at the individual cow level. In particular, we determined the effects of very low to very high SCC on traits related to (1) milk yield and composition; (2) coagulation properties, including the traditional milk coagulation properties (MCP) and the new curd firming model parameters; and (3) cheese yield and recovery of milk nutrients in the curd (or loss in the whey). Milk samples from 1,271 Brown Swiss cows from 85 herds were used. Nine coagulation traits were measured: 3 traditional MCP [rennet coagulation time (RCT, min), curd firming rate (k20, min), and curd firmness after 30 min (a30, mm)] and 6 new curd firming and syneresis traits [potential asymptotic curd firmness at infinite time (CFP, mm), curd firming instant rate constant (kCF, % × min(-1)), syneresis instant rate constant (kSR, % × min(-1)), rennet coagulation time estimated using the equation (RCTeq, min), maximum curd firmness achieved within 45 min (CFmax, mm), and time at achievement of CFmax (tmax, min)]. The observed cheese-making traits included 3 cheese yield traits (%CYCURD, %CYSOLIDS, and %CYWATER, which represented the weights of curd, total solids, and water, respectively, as a percentage of the weight of the processed milk) and 4 nutrient recoveries in the curd (RECFAT, RECPROTEIN, RECSOLIDS, and RECENERGY, which each represented the percentage ratio between the nutrient in the curd and milk). Data were analyzed using a linear mixed model with the fixed effects of days in milk, parity, and somatic cell score (SCS), and the random effect of herd-date. Somatic cell score had strong influences on casein number and lactose, and also affected pH; these were traits characterized by a quadratic pattern of the data. The results also showed a negative linear relationship between SCS and milk yield. Somatic cell score influenced almost all of the tested coagulation traits (both traditional and modeled), with the exceptions of k20, CFP, and kSR. Gelation was delayed when the SCS decreased (slightly) and when it increased (strongly) with respect to a value of 2, as confirmed by the quadratic patterns observed for both RCT and RCTeq. The SCS effect on a30 showed a quadratic pattern almost opposite to that observed for RCT. With respect to the CFt parameters, kCF decreased linearly as SCS increased, resulting in a linear decrease of CFmax and a quadratic pattern for tmax. Milk SCS attained significance for %CYCURD, %CYWATER, and RECPROTEIN. As the SCS increased beyond 3, we observed a progressive quadratic decrease of the water retained in the curd (%CYWATER), which caused a parallel decrease in %CYCURD. With respect to RECPROTEIN, the negative effect of SCS was almost linear. Recovery of fat and (consequently) RECENERGY was characterized by a more evident quadratic trend, with the most favorable values associated with an intermediate SCS. Together, our results confirmed that high SCS has a negative effect on milk composition and technological traits, highlighting the nonlinear trends of some traits across the different classes of SCS. Moreover, we report that a very low SCS has a negative effect on some technological traits of milk.

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict "difficult-to-predict" dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and protein recovery, using Fourier-transform infrared (FTIR) spectral data. Our main hypothesis was that Bayesian models that can estimate shrinkage and perform variable selection may improve our ability to predict FA traits and technological traits above and beyond what can be achieved using the current calibration models (e.g., partial least squares, PLS). To this end, we assessed a series of Bayesian methods and compared their prediction performance with that of PLS. The comparison between models was done using the same sets of data (i.e., same samples, same variability, same spectral treatment) for each trait. Data consisted of 1,264 individual milk samples collected from Brown Swiss cows for which gas chromatographic FA composition, milk coagulation properties, and cheese-yield traits were available. For each sample, 2 spectra in the infrared region from 5,011 to 925 cm(-1) were available and averaged before data analysis. Three Bayesian models: Bayesian ridge regression (Bayes RR), Bayes A, and Bayes B, and 2 reference models: PLS and modified PLS (MPLS) procedures, were used to calibrate equations for each of the traits. The Bayesian models used were implemented in the R package BGLR (http://cran.r-project.org/web/packages/BGLR/index.html), whereas the PLS and MPLS were those implemented in the WinISI II software (Infrasoft International LLC, State College, PA). Prediction accuracy was estimated for each trait and model using 25 replicates of a training-testing validation procedure. Compared with PLS, which is currently the most widely used calibration method, MPLS and the 3 Bayesian methods showed significantly greater prediction accuracy. Accuracy increased in moving from calibration to external validation methods, and in moving from PLS and MPLS to Bayesian methods, particularly Bayes A and Bayes B. The maximum R(2) value of validation was obtained with Bayes B and Bayes A. For the FA, C10:0 (% of each FA on total FA basis) had the highest R(2) (0.75, achieved with Bayes A and Bayes B), and among the technological traits, fresh cheese yield R(2) of 0.82 (achieved with Bayes B). These 2 methods have proven to be useful instruments in shrinking and selecting very informative wavelengths and inferring the structure and functions of the analyzed traits. We conclude that Bayesian models are powerful tools for deriving calibration equations, and, importantly, these equations can be easily developed using existing open-source software. As part of our study, we provide scripts based on the open source R software BGLR, which can be used to train customized prediction equations for other traits or populations.