Reproducibility and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy

Alpine grazing management, breed and diet effects on coagulation properties, composition, and microbiota of dairy cow milk by commercial mountain based herds

Cow milk microbiota has received increased attention in recent years, not only because of its importance for human health but also because of its effect on the quality and technological properties of milk. Several studies, therefore, have investigated the effect of various production factors on the microbial composition of milk. However, most of the previous studies considered a limited number of animals from experimental or single farm, which could have biased the results. Therefore, this study aimed to understand the effect of different alpine production systems on the compositional and microbiological quality of milk, considering commercial herds with different feeding intensities and cattle breeds. The results obtained in this work indicated that the month/season of sampling (July for summer or February for winter) more than farm, breed and cow diet exerted significant effects on cow milk parameters and microbiota. In particular, significant differences were observed for urea content in milk between sampling seasons. Differences in milk fat were mainly related to breed specific effects. From a microbiological point of view, statistically significant differences were found in presumptive lactic acid bacteria counts. Based on a culture-independent method, milk obtained in February harbored the highest number of Firmicutes (e.g., Lactobacillus) and the lowest number of Actinobacteria (e.g., Corynebacterium). Moreover, bacterial richness and diversity were higher in July/summer during alpine pasture season indicating a significant effect of pasture feed on the growth of bacterial communities. The results of this study highlighted the effect of month/season mainly related to differences in feeding management (e.g., access to pasture during vegetation period, concentrates supplementation) on composition and microbiota in milk.

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

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

Phenotypic and genetic characterization of the occurrence of noncoagulating milk in dairy sheep

Milk coagulation ability is of central importance for the sheep dairy industry because almost all sheep milk is destined for cheese processing. The occurrence of milk with impaired coagulation properties is an obstacle to cheese processing and, in turn, to the profitability of the dairy companies. In this work, we investigated the causes of noncoagulation of sheep milk; specifically, we studied the effect of milk physicochemical properties on milk coagulation status [coagulating and noncoagulating (NC) milk samples, which do or do not coagulate within 30 min, respectively], and whether mid-infrared spectroscopy (MIR) could be used to assess variability in coagulation status. We also investigated the genetic background of milk coagulation ability. Individual milk samples were collected from 996 Sarda ewes farmed in 47 flocks located in Sardinia (Italy). Considered traits were daily milk yield, milk composition traits, and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness), and MIR spectra were acquired. About 9% of samples did not coagulate within 30 min. A logistic regression approach was used to test the effect of milk-related traits on milk coagulation status. A principal component (PC) analysis was carried out on the milk MIR spectra, and PC scores were then used as covariates in a logistic regression model to assess their relationship with milk coagulation status. Results of the present work demonstrated that the probability of having NC samples increases as milk contents of proteins and chlorides and somatic cell score increase. The analysis of PC extracted from milk spectra that influenced coagulation status highlighted key regions associated with lactose and protein concentrations, and others not associated with routinely collected milk composition traits. These results suggest that the occurrence of NC is mostly related to damage of the epithelium secretory mammary cells, which occurs with the advancement of a lactation or due to unhealthy mammary gland status. Genetic analysis of milk coagulation status and of the extracted PC confirmed the genetic background of the milk coagulability of sheep milk.

Feeding cows with hay, silage, or fresh herbage on pasture or indoors affects sensory properties and chemical composition of milk and cheese

In European countries, silage-free feeding is an ancient tradition and has a particularly positive reputation among consumers. In the present study, we compared grass-based forages from the same plot conserved as hay or silage or fed fresh either on pasture or indoors, and we evaluated the differences in sensory properties of milk and uncooked pressed cheese. All herbage from the first cut of a grassland dominated by perennial ryegrass was harvested on the same day and preserved either as hay or silage. The first regrowth of the same plot was used for strip grazing or green feeding indoors. Balanced by breed, 24 Montbéliarde and 24 Holstein cows were allocated to the 4 treatments. Apart from the forages, the late-lactation cows received 3 kg/d of dry matter from concentrate. After 2 wk of dietary adaptation, the bulk milk of 3 subgroups, each with 4 cows, was collected. Part of the milk was pasteurized, and part was left raw and partly transformed to small-sized Cantal-type cheese ripened for 9 wk. Milk and cheese underwent descriptive sensory analysis by a trained sensory panel, as well as analyses of physicochemical traits. Volatile organic compounds of the cheeses were also analyzed. Raw and pasteurized milk from hay-fed cows had less intense odors of cooked milk, cream, and barnyard than milk from grazing cows, whereby the effect of pasteurization did not differ between herbage utilization methods. Cheeses obtained from cows fed fresh herbage (grazing and indoors) were clearly yellower than cheeses from silage- and hay-fed cows, which coincided with the color intensity perceived by the panelists. Moreover, cheeses from cows fed fresh herbage had more intense barnyard and dry fruit flavors, were perceived as creamier and having less lactic odor, and exhibited more fat exudation than those from cows fed conserved herbage. Only a few differences were observed in milk and cheeses from hay-fed compared with silage-fed cows, and those differences were far less pronounced than those of milk and cheeses from cows fed fresh herbage. In conclusion, the present study did not substantiate assumptions of clear sensory differences of milk and uncooked pressed cheese from hay-fed compared with silage-fed cows. For the first time, this study reports that the global flavor intensity of cheeses from indoor green-fed cows is similar to that of cheeses derived from cows fed conserved forages, whereas cheeses from grazing cows have the greatest global flavor intensity.

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.

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

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

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

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