Derivation of multivariate indices of milk composition, coagulation properties, and curd yield in Manchega dairy sheep

Exploring Interrelationships between Colour, Composition, and Coagulation Traits of Milk from Cows, Goats, and Sheep

This study explores the interrelationships between the composition, coagulation, and colour of sheep, goat, and cow milk to identify their similarities and differences and to assess whether the relationships between the variables are common to all species or whether they emerge from species-specific relationships. For this purpose, 2400 individual milk samples were analysed. The differences and similarities between the species were determined using discriminant analysis and cluster analysis. The results show a clear differentiation between species. Sheep milk stands out for its cheesemaking capacity and shows similarities with goat milk in composition and coagulation. Nonetheless, colorimetry highlights a greater similarity between sheep and cow milk. Composition and colorimetry were more discriminating than coagulation, and the variables that differed the most were fat, protein, curd yield, lightness, and red-green balance. Using canonical correlation, the interrelationships between the different sets of variables were explored, revealing patterns of common variation and species-specific relationships. Colorimetric variables were closely related to milk solids in all species, while in sheep milk, an inverse relationship with lactose was also identified. Furthermore, a strong relationship was revealed for all species between colour and curd yield. This could be modelled and applied to estimate the technological value of milk, proving colorimetry as a useful tool for the dairy industry.

Characteristics of Red Deer (Cervus elaphus) Milk: Lactational Changes in Composition and Processing Impacts on Structural and Gelation Properties

In an increasingly diversified global market, milk of minor dairy species has gained interest as a novel and premium source of nutrition. Relative to the major dairy species, much is lacking in our understanding of red deer (Cervus elaphus) milk. In this study, we characterized the compositions (macronutrients, minerals, fatty acids, and proteins) of red deer milk and their variations throughout lactation. We also investigated the structures, physical properties, and gelation (acid- and rennet-induced) properties of deer milk and how they are impacted by typical processing treatments (e.g., homogenization and pasteurization). We identified unique features in the composition of deer milk, including being richer in protein, fat, calcium, zinc, iodine, branched-chain fatty acids, and α-linolenic acid than other ruminant milks. Different deer milk components displayed diverse variation patterns over the lactation cycle, many of which were different from those demonstrated in other ruminant species. Other physicochemical features of deer milk were identified, such as its markedly larger fat globules. Processing treatments were demonstrated to alter the structural and gelation properties of deer milk. Most of the gelation properties of deer milk resembled that of bovine milk more than ovine and caprine milks. This study furthers our understanding of red deer milk and will aid in its processing and applications in novel products.

Acid and rennet gelation properties of sheep, goat, and cow milks: Effects of processing and seasonal variation

Gelation is an important functional property of milk that enables the manufacture of various dairy products. This study investigated the acid (with glucono-δ-lactone) and rennet gelation properties of differently processed sheep, goat, and cow milks using small-amplitude oscillatory rheological tests. The impacts of ruminant species, milk processing (homogenization and heat treatments), seasonality, and their interactions were studied. Acid gelation properties were improved (higher gelation pH, shorter gelation time, and higher storage modulus (G') by intense heat treatment (95°C for 5 min) to comparable extents for sheep and cow milks, both better than those for goat milk. Goat milk produced weak acid gels with low G' (<100 Pa) despite improvements induced by heat treatments. Seasonality had a marked impact on the acid gelation properties of sheep milk. The acid gels of late-season sheep milk had a lower gelation pH, no maximum in tan δ following gel formation, and 70% lower G' values than those from other seasons. We propose the potential key role of a critical acid gelation pH that induces structural rearrangements in determining the viscoelastic properties of the final gels. For rennet-induced gelation, compared with cow milk, the processing treatments of the goat and sheep milks had much smaller impacts on their gelation properties. Intense heat treatment (95°C for 5 min) prolonged the rennet gelation time of homogenized cow milk by 8.6 min (74% increase) and reduced the G' of the rennet gels by 81 Pa (85% decrease). For sheep and goat milks, the same treatment altered the rennet gelation time by only less than 3 min and the G' of the rennet gels by less than 14 Pa. This difference may have been caused by the different physicochemical properties of the milks, such as differences in their colloidal stability, proportion of serum-phase caseins, and ionic calcium concentration. The seasonal variations in the gelation properties (both acid and rennet induced) of goat milk could be explained by the minor variation in its protein and fat contents. This study provides new perspectives and understandings of milk gelation by demonstrating the interactive effects among ruminant species, processing, and seasonality.

Efficiency of Manchega Sheep Milk Intended for Cheesemaking and Determination of Factors Causing Inefficiency

Understanding the factors that determine and regulate cheese yield would allow, through deterministic parametric efficiency models, the determination of the most appropriate milk characteristics for the industry, and the estimation of a technological value for these characteristics. The present study aims to evaluate coagulation performance of Manchega sheep milk intended for cheesemaking and explores two models to determine milk technological efficiency. For this purpose, 1200 Manchega sheep milk samples were collected, and analyses were performed for composition, milk coagulation properties (MCP), somatic cell count (SCC), and milk color values. A first model was built based on curd yield (CE) and a second one based on dry curd yield (DCE). GLM and MANCOVA analyses were used to identify the factors that determine curd yield efficiency, which mainly depended on pH, casein, and lactose content and, to a lesser extent, on the speed of coagulation and curd firmness. When comparing both models, differences were linked to the water retention capacity of the curd. Based on this, the DCE model was considered much more accurate for prediction of coagulation efficiency in a wider variety of cheeses, as it does not seem to be affected by moisture loss.

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.

Seasonal Variations in the Composition and Physicochemical Characteristics of Sheep and Goat Milks

There has been growing consumer interest in sheep and goat milk products as alternatives to cow milk products. The physicochemical characteristics of milk vary not only between ruminant species, but also during different seasons; they determine the nutritional quality and processing properties of the milk. In this study, we characterized sheep and goat milks from New Zealand over the seasons for their composition (macronutrients, macro- and micro-minerals, fatty acids, and proteins) and physicochemical properties (e.g., ionic calcium, fat globule size, casein micelle size, viscosity, and melting behavior of milk fat). Heat-induced (95 °C for 5 min) protein interactions and changes in the physical properties of the milks were also investigated. The compositional and structural features of sheep and goat milks were identified and compared with those reported for cow milk. Seasonal variations in the milk characteristics were more pronounced for sheep milk than goat milk and were probably affected by the production systems. Sheep milk, particularly in the late season, had the largest heat-induced increases in casein micelle size and viscosity, probably arising from the greater casein–whey protein and casein–casein interactions during heat treatment. This study provides comprehensive information on the properties of sheep and goat milks and highlights the interaction effects between species, season, and processing.

Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed

Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.