Variation In Milk Composition Research Articles

Evaluating Source Complexity in Blended Milk Cheese: Integrated Strontium Isotope and Multi-Elemental Approach to PDO Graviera Naxos.

Graviera Naxos, a renowned cheese with Protected Designation of Origin status, is crafted from a blend of cow, goat, and sheep milk. This study focused on assessing the Sr isotopic and multi-elemental composition of both the processed cheese and its ingredients, as well as the environmental context of Naxos Island, including samples of milk, water, soil, and feed. The objective was to delineate the geochemical signature of Graviera Naxos cheese and to explore the utility of Sr isotopes as indicators of geographic origin. The 87Sr/86Sr values for Graviera Naxos samples ranged from 0.70891 to 0.70952, indicating a relatively narrow range. However, the Sr isotopic signature of milk, heavily influenced by the feed, which originates from geologically distinct areas, does not always accurately reflect the local breeding environment. Multi-elemental analysis revealed variations in milk composition based on type and season; yet, no notable differences were found between raw and pasteurized milk. A mixing model evaluating the contributions of milk, sea salt, and rennet to the cheese's Sr isotopic signature suggested a significant average contribution of 73.1% from sea salt. This study highlights the complexities of linking dairy products with their geographical origins and emphasizes the need for sophisticated geochemical authentication methods.

Variations in Composition, Antioxidant Profile, and Physical Traits of Goat Milk within the Semi-Intensive Production System in Mountainous Areas during the Post-Weaning to End-of-Lactation Period.

Dairy products from mountain-origin milk are known for their superior composition and quality. This study aimed to examine changes in composition, nutritional quality, and antioxidant properties of milk from semi-intensively managed goats in mountainous regions during the post-weaning to end-of-lactation period. Bulk tank milk samples from 10 farms were collected bi-weekly in the period from March to September. The farms were situated in regions with an average altitude of 772.20 m above sea level. The results revealed significant variations in milk composition, with fluctuations in fat, protein, lactose, and total solids. Milk yield per doe showed seasonal differences, with the highest yield in April and the lowest in September. Fatty acid composition exhibited changes throughout the sampling period, with variations in polyunsaturated fatty acids. Nutritional indices, such as the atherogenicity index and thrombogenicity index, remained within the recommended values. Antioxidant properties, including total phenolic content, DPPH, FRAP, and ABTS, showed significant differences, with higher values toward the end of the study. Milk pH, electrical conductivity, brix value, and refractive index also exhibited variations, while density and freezing point remained relatively stable. The study provided valuable information that can be used to develop breeding and feeding plans to achieve uniform milk quality in mountainous regions.

Variations in fatty acids, micronutrients and metabolites in discrete milk lines of Danish dairy milk

Highlighting factors driving natural variation in milk composition among different dairy milk lines is important not only to secure uniform products but also for possible exploitation of the inherent variation. The composition of milk is related to genetic and environmental differences, causing variation in the milk delivered to the dairies. This study investigated compositional variations related to management systems, feeding strategies and seasonal periods. Milk samples from 15 Danish dairies, representing 34 unique milk lines, were collected monthly for two years. The study revealed significant compositional differences in fatty acids, micronutrients and metabolites relative to management systems. This is possibly related to differences in feeding and management practices, e.g., periods of outdoor grazing. Data expressed a higher degree of variation in milk samples representing biodynamic and organic milk lines with extensive grass feeding in comparison with conventional and organic milk lines reflecting more common Danish feeding practices.

Macroelement Seasonal Variations in Latvian Organic Milk

Abstract Consumer perception of organic milk is associated with the assumption that organic milk differs from conventionally produced milk. The aim of the present study was to analyse calcium, magnesium, and phosphorus concentration in organic milk in the context of the season. The study was conducted from November 2019 to the end of October 2020. Over a year, raw bulk milk samples were collected and analysed. The milk for the study was supplied by two organic farms located in Latvia. Cows received a total mixed ration consisting of high moisture maize silage, grass silage, etc. The chemical composition of the total mixed rations was analysed, as well as fat, protein, lactose, milk solids non-fat, and total solids, calcium, phosphorus, and magnesium content in organic milk were determined. Seasonal variation in milk composition was observed. The average calcium concentration in our study was 107.96 ± 9.61 mg·100 g−1 with a lower average concentration 97 mg·100 g−1 in organic milk in March. The concentration of calcium, phosphorus, and magnesium was higher in organic milk during the spring–summer season. The sale of organic milk is growing in Latvia, and the presence of a favourable level of calcium in organic milk during the whole year should be reached, providing calcium concentration in cow’s milk around 120 mg·100 g−1 throughout the lactation period. Milk and milk products are an important part of daily nutrition, recommended to every consumer due to their wholesomeness and calcium concentration. Evaluating the bone health data of the Latvian population, 100 ml of milk consumption should provide at least 15% of the recommended daily intake of calcium.

Technological solutions and adaptive processing tools to mitigate the impact of seasonal variations in milk composition on Cheddar cheese production—A review

Variability in milk composition and physicochemical properties impact both manufacturing process performance and the end‐use functionality of cheese. Such variability may be attributed to seasonal calving patterns, production systems, breed, weather patterns, and feed type and significantly impacts concentrations of macro‐ and microconstituents and ultimately cheese composition and quality. This article reviews technological approaches (e.g., milk standardisation protocols and calcium addition), and predictive strategies (e.g., predictive models for coagulation and curd cutting time, in‐line sensors), used to mitigate the effects of seasonal changes in milk composition and their impact on process efficacy and functionality in Cheddar cheese manufacturing.

Using detailed milk protein composition to explain variations in rennet gelation properties

Individual milk samples were used to investigate how much of the variation in rennet gelation properties that can be explained by variation in milk composition by linear regression using the ordinary least squares method so as to optimise cheese milk. Natural variation in casein (CN) content was shown to have a large effect on gel strength but did not affect gel formation kinetics. Ionic calcium concentration was more important for initial gel formation whereas total calcium content is a better predictor for the developed gel structure. Of the individual milk proteins, κ-CN had the largest effect on gelation explaining up to 20% of the variation in gel forming kinetics and gel strength, while post-translational modifications of κ-CN did not explain more variation than total κ-CN. However, the relative concentration of glycosylated κ-CN seems to be more important for gel-build-up kinetics and un-glycosylated κ-CN for the gel-structure.

Enhancing dairy productivity through best bet feeding interventions under smallholders in the central highlands of Ethiopia

Dairy cattle production is an integral part of smallholder farming systems in the central highlands of Ethiopia, but it is characterized by low milk productivity mainly due to nutritional constraints. This study assessed the comparative advantage of using improved forage-based feeding system over the traditional feeding practices on feed intake, milk yield and quality, and cost benefit analysis of crossbred dairy cows under smallholder farmers. The study was conducted at Welmera and Ejere districts on 12 farmers and two cows per farmer, and two dietary treatments were assigned to each cow randomly, and the study lasted 8 weeks. The treatments were: 1) intervention diet composed of oats-vetch mixture hay with concentrate supplementation at the rate of 0.5 kg/l of milk and 2) basal diet following farmers’ current feeding practices: crop residues and native hay, commonly soaked with local brewery residue (“Atela”) and water. The results showed that there was no difference in total dry matter intake between the two diets. However, the basal feed intake was higher in the traditional feeding practice by 11% whereas the concentrate intake was higher in the intervention diet by 25%. Crude protein intake was significantly higher (P<0.05) in the intervention group by 23%. As a result, milk yield was increased by 36% under oat-vetch mixed fodder-based feeding system as compared to the traditional feeding practice. Consequently, the amount of feed required per unit of milk was lower in the intervention group, indicating higher feed conversion efficiency as compared to the traditional feeding practice. On the other hand, there was no significant variation in milk composition between the two groups. Partial budget analysis indicated that the benefit from the intervention diet (95 birr/cow/day) was greater by 266% than that obtained from the traditional practice (45 birr/cow/day). Utilization of improved forage varieties was proven to play significant role in supplying good quality and abundant feed resource that increased milk yield and also fetch additional economic return for smallholder farmers compared to the existing traditional practice. In general, this study demonstrates that adoption of improved forage production and feeding practices along with sufficient training on balanced ration formulation has been observed to increase dairy productivity and food security through provision of sustainable livelihood opportunity for smallholder farmers.

Evaporative cooling in late gestation heat-stressed transition Murrah buffaloes improves milk production through hormone-metabolite interaction

ABSTRACT Animals adapt to stress by hormone-metabolite interaction. This is necessary to protect animal health status and subsequent milk production. To investigate this, sixteen healthy late-gestation dry Murrah buffaloes were selected and divided into two groups of eight animals each. One group of buffaloes (Cooled/CL) was managed under fan and mist cooling system during dry period. Another group (Non-cooled/NCL) remained without the provision of cooling during dry period. After parturition, all the animals were managed under evaporative cooling. Milk yield was significantly (p<0.05) higher in CL (10.25±0.23 kg/day) relative to NCL (8.92±0.17 kg/day) buffaloes without any significant variation in milk composition. The average dry matter intake was significantly (p<0.05) higher in CL as compared to NCL group. The non-esterified fatty acids were significantly (p<0.05) higher in CL relative to NCL buffaloes. Significantly (p<0.05) higher glucose level was found on the day of calving in CL as compared to NCL buffaloes. The level of insulin was higher in NCL buffaloes as compared to CL buffaloes. The growth hormone was higher in CL relative to NCL buffaloes. Evaporative cooling in late gestation therefore proves to be a potential tool to alleviate the adverse effect of thermal stress thus affecting subsequent milk production.

Effect of Production Systems on Milk Yield and Calf Performance in North Kordofan State, Sudan

This study was conducted in two locations, Kazgail and Um arada, Sheikan locality, North Kordofan State, Sudan. Objective of the study to evaluate the effects of production system on milk production and quality and calf performance. Thirty (30) dairy cattle were employed in this experiment. Cows were weighed and divided into two groups each with Fifteen (15 cow) in complete randomized design. Group A was located in Kazgail village and considered as close production system and group B in Um arada village as open production system. Data were analyzed by using T test for analysis of variance procedures and least significant difference (LSD) for mean separation. The results revealed that production system significantly (p&lt;0.001) affected milk production, where group A had maintained higher milk yield compared with group B. the respectively milk yield were 153.60 and 65.57 Lb for Group A and B respectively. Results showed significant differences (p&lt;0.05) between systems for the milk quality during first and second month of lactation period on fat content (4.67 vs 4.87% ) for A and B groups respectively and lactose content (4.61 vs 4.77%) for A and B groups respectively. Results revealed that calves birth weight significantly (p&lt;0.05) affected by production system. The mean birth weights were (35.58 vs 31.98 kg) for A and B groups respectively. The study demonstrated that production system had no significant effect on weaning weight. Results showed that production system significantly (p&lt;0.05) affect daily body weight gain. In conclusion, dairy cattle in different production system; showed variable milk production during lactation period and variation in milk composition during three month.

Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage.

Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.

Variations in the biochemical and functional properties of commercial low-moisture part-skim mozzarella during 3 months of storage at 4 °C

The combined effects of seasonal variation in milk composition and changes to cheese recipe (e.g., type and dosage of starter culture or coagulant) on the composition and functionality of low-moisture part-skim mozzarella were examined. Cheese blocks were sampled from 50 random vats at a commercial plant on 17 different days over a 13-month period, stored at 4 °C and assayed after 14, 56 or 84 d for composition, insoluble Ca, primary proteolysis, texture profile analysis, heat-induced changes in viscoelastic behaviour, extensibility and flow. Differences in the functional quality between cheeses obtained on different sampling occasions were evident after each storage time. Principal component analysis in conjunction with a multiple linear regression model revealed that the variability in functional performance was related to differences in storage time and cheese composition (e.g., dry matter, fat-in-dry matter, protein, salt-in-moisture, or total Ca content), and to interactive effects between storage time, protein and salt-in-moisture.

111. Accounting for individual cow variation in milk composition and dry matter intakes when allocating concentrates on a feed-to-yield basis

111. Accounting for individual cow variation in milk composition and dry matter intakes when allocating concentrates on a feed-to-yield basis

The milk fingerprint of Sardinian dairy sheep: quality and yield of milk used for Pecorino Romano P.D.O. cheese production on population-based 5-year survey

The Pecorino Romano P.D.O. is the main sheep cheese produced in Italy and the first one among the sheep cheeses, in terms of quality and value, exported from the European Union. About half of the sheep milk produced in Italy is processed into this type of cheese by 36 dairies belonging to the Pecorino Romano Consortium. Eight million records of biweekly analyses of milk collected within a 5-year period from farms delivering their milk to the aforementioned consortium were analysed in this work. Monthly evolution curves were plotted for fat, protein, lactose, pH, NaCl, SCC, bacterial load and principal fatty acids (FAs). Due to the seasonal production systems of Sardinian sheep, monthly evolution of milk fat and protein contents and cheese yield are directly linked to the lactation curve pattern and the pastures quantity and quality. Also, the FA profile of milk is affected by grass availability and quality in both early and mid-lactation, whereas it is influenced by the energy balance of ewes in late lactation. Cheese yield equation was computed based on fat and protein contents and considering the variability among dairies in technological processes used in transforming Sarda sheep milk to Pecorino Romano P.D.O. These data could be a relevant basis to set-up future grids of milk payments based on quality standards. Moreover, they could be useful to formulate administrative policies on the dairy sector with the prospective to improve milk quality of Sardinian sheep destined to the Pecorino Romano production. Highlights The yield of Pecorino Romano P.D.O. (PR) is linked to fat and protein content of milk and it depends on the industrial processes adopted by each dairy Monthly variation of milk composition is of high interest for the PR producers to program the output of their milk-processing plans The content and monthly evolutions of principal fatty acids are important to determine the nutritional and technological properties of PR

Variation in Milk Composition of Dairy Goats due to N-3 Unsaturated Fatty Acids Supplementation

The objective of this research was to determine the effect of addition of n-3 unsaturated fatty acids (α-linoleic, eicosapentaenoic and docosahexaenoic) in dairy goats’ ration on milk composition (fat and protein content). Also, the persistence of the effect after supplementation was analysed. The research was conducted on dairy goats (Alpine and Saanen) bred at an indoor farm. Regarding the experimental period, the milk sampling at milking (morning and evening) was performed in the period before supplementation (BS), during supplementation (S), and after supplementation (AS). According to the added supplement, animals were randomly allocated into a group (G-4) with no added supplement and three test groups (G-1; G-2; G-3) where a supplement containing n-3 unsaturated fatty acid was added over a period of five days. The results of this research indicate that the addition of PUFA in goats’ ration changes the milk composition. The supplementation of α-linoleic resulted in increase of both milk fat and protein content. Furthermore, the addition of eicosapentaenoic and docosahexaenoic resulted in decrease of fat but increase of protein content in milk. The observed trends also persisted after the supplementation period.

Longitudinal retrospective study on the effect of season on milk production and composition in Rio Grande do Sul, Brazil

This longitudinal retrospective study evaluated production and composition of milk from dairy cows according to season on a rural property in Palmeira das Missões, Rio Grande do Sul, Brazil, between January 2009 and December 2016. Milk yield per hectare per month was the primary variable measured, along with chemical composition (total dry extract, defatted dry extract, fat, protein, and lactose), somatic cell count, and total bacterial count of milk. Production in summer (513.53 kg/ha/month) did not differ (p &gt; 0.05) from that in fall (504.69 kg/ha/month) or spring (564.63 kg/ha/month), but production in winter (639.20 kg/ha/month) was significantly higher than in summer (p &lt; 0.0057). The real price of milk did not differ (p &gt; 0.05) among seasons. The total dry extract content differed (p &lt; 0.0059) between seasons. However, the cooler fall and winter seasons favored the production of total solids. The defatted dry extract content was higher (p &lt; 0.0001) in winter (8.65%), compared to the other seasons of the year. Fat content did not differ (p &gt; 0.05) among seasons. Protein content differed (p &lt; 0.0200) between summer (3.01%) and winter (3.16%), but both seasons did not differ (p &gt; 0.05) from fall (3.13%) or spring (3.05%). Winter lactose levels (4.52%) were higher (p &lt; 0.0011) than during other seasons. The somatic cell count did not differ (p &gt; 0.05) among seasons, demonstrating that the evaluated herd possesses standard mammary gland health. The total bacterial count did not differ (p &gt; 0.05) among the seasons, demonstrating that the hygiene of the facilities remains constant. As expected, the temperature and humidity index varied (p &lt; 0.0001) with the seasons, and the deleterious effects were more pronounced in summer and spring, as they are the hottest seasons in humid subtropical environments. The results emphasize that the organized management of milk production reduces the variation in milk composition, making it easier to maintain a consistent high milk quality and also generating extra revenue.

Variation in Milk Composition and Fatty Acid Profile during the Lactation of Araucana Creole Ewes in a Pasture-Based System.

Simple SummaryThe Araucana creole sheep is a local Chilean genetic resource and represents an important economic resource for the Mapuche ethnic group, who mainly use it for meat and wool production. In recent years, an interesting gourmet market has emerged for milk products derived from sheep’s milk. These products are highly valued because they come from sheep fed in systems based on pastures that are considered healthier than the diet of sheep fed indoors. Therefore, it is important to know the production and composition of Araucana creole ewe’s milk, which has not been studied. This information may provide an alternative for the diversification of sheep production by small farmers, contributing to the agricultural and cultural diversity of southern Chile.Araucana creole sheep are a local animal genetic resource adapted to environmental conditions in rural production systems in southern Chile. The aim of the present study was to analyze the milk yield and composition of Araucana creole ewe’s milk from ewes maintained in a traditional grazing system of natural pastures. Twenty healthy single-bearing Araucana creole ewes were selected immediately after lambing (body condition score (BCS) of 2.8 ± 0.2, ewe weight (EW) of 62 ± 3.5 kg, and age of 3.8 ± 0.7 years). BCS, EW, and lamb weights were determined. Milk samples were obtained using the oxytocin technique at 10 days postpartum and then twice a month during the lactation stage (90 days). Protein, fat, lactose, total solids (TS), solid non-fat (SNF), urea contents, and fatty acid (FA) composition were analyzed. The Araucana ewe’s milk yield was lower than that of other dairy sheep but was higher than that of meat breeds. The milk fat had a higher content of oleic acid in the early lactation period, which decreased slowly according to the progress of lactation. The increase in oleic acid improved the milk health indexes during this period and thus provided a healthier milk product for human consumption than later in lactation. During lactation, higher conjugated linoleic acid (CLA) levels were obtained only at day 60. Our research suggests that Araucana creole sheep can provide high-quality milk during early lactation, which is rich in oleic acid and represents an alternative for the production of dairy products, improving the profitability of the productive systems of small-holder farmers in Chile.

The Effect of Calcium, Citrate, and Urea on the Stability of Ultra-High Temperature Treated Milk: A Full Factorial Designed Study.

The composition of raw milk is important for the stability of dairy products with a long shelf-life. Based on known historical changes in raw milk composition, the aim of this study was to get a better understanding of how possible future variations in milk composition may affect the stability of dairy products. The effects of elevated calcium, citrate, and urea levels on the stability of ultra-high temperature (UHT) treated milk stored for 52 weeks at 4, 20, 30, and 37 °C were investigated by a two-level full factorial designed study with fat separation, fat adhesion, sedimentation, color, pH, ethanol stability, and heat coagulation time as response variables. The results showed that elevated level of calcium lowered the pH, resulting in sedimentation and significantly decreased stability. Elevated level of citrate was associated with color, but the stability was not improved compared to the reference UHT milk. Elevated levels of urea or interaction terms had little effect on the stability of UHT milk. Storage conditions significantly affected the stability. In conclusion, to continue produce dairy products with high stability, the dairy industry should make sure the calcium content of raw milk is not too high and that storage of the final product is appropriate.

Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows

Assessing the cheese-making properties (CMP) of milks with a rapid and cost-effective method is of particular interest for the Protected Designation of Origin cheese sector. The aims of this study were to evaluate the potential of mid-infrared (MIR) spectra to estimate coagulation and acidification properties, as well as curd yield (CY) traits of Montbéliarde cow milk. Samples from 250 cows were collected in 216 commercial herds in Franche-Comté with the objectives to maximize the genetic diversity as well as the variation in milk composition. All coagulation and CY traits showed high variability (10 to 43%). Reference analyses performed for soft (SC) and pressed cooked (PCC) cheese technology were matched with MIR spectra. Prediction models were built on 446 informative wavelengths not tainted by the water absorbance, using different approaches such as partial least squares (PLS), uninformative variable elimination PLS, random forest PLS, Bayes A, Bayes B, Bayes C, and Bayes RR. We assessed equation performances for a set of 20 CMP traits (coagulation: 5 for SC and 4 for PCC; acidification: 5 for SC and 3 for PCC; laboratory CY: 3) by comparing prediction accuracies based on cross-validation. Overall, variable selection before PLS did not significantly improve the performances of the PLS regression, the prediction differences between Bayesian methods were negligible, and PLS models always outperformed Bayesian models. This was likely a result of the prior use of informative wavelengths of the MIR spectra. The best accuracies were obtained for curd yields expressed in dry matter (CYDM) or fresh (CYFRESH) and for coagulation traits (curd firmness for PCC and SC) using the PLS regression. Prediction models of other CMP traits were moderately to poorly accurate. Whatever the prediction methodology, the best results were always obtained for CY traits, probably because these traits are closely related to milk composition. The CYDM predictions showed coefficient of determination (R2) values up to 0.92 and 0.87, and RSy,x values of 3 and 4% for PLS and Bayes regressions, respectively. Finally, we divided the data set into calibration (2/3) and validation (1/3) sets and developed prediction models in external validation using PLS regression only. In conclusion, we confirmed, in the validation set, an excellent prediction for CYDM [R2 = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CYFRESH (R2 = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R2 ≥ 0.70, RPD ≥1.8), which enable quantitative prediction.

Causes and short-term consequences of variation in milk composition in wild sheep.

Ecologists seek to understand the fitness consequences of variation in physiological markers, under the hypothesis that physiological state is linked to variability in individual condition and life history. Thus, ecologists are often interested in estimating correlations between entire suites of correlated traits, or biomarkers, but sample size limitations often do not allow us to do this properly when large numbers of traits or biomarkers are considered. Latent variables are a powerful tool to overcome this complexity. Recent statistical advances have enabled a new class of multivariate models-multivariate hierarchical modelling (MHM) with latent variables-which allow to statistically estimate unstructured covariances/correlations among traits with reduced constraints on the number of degrees of freedom to account in the model. It is thus possible to highlight correlated structures in potentially very large numbers of traits. Here, we apply MHM to evaluate the relative importance of individual differences and environmental effects on milk composition and identify the drivers of this variation. We ask whether variation in bighorn sheep milk affects offspring fitness. We evaluate whether mothers show repeatable individual differences in the concentrations of 11 markers of milk composition, and we investigate the relative importance of annual variability, maternal identity and morphological traits in structuring milk composition. We then use variance estimates to investigate how a subset of repeatable milk markers influence lamb summer survival. Repeatability of milk markers ranged from 0.05 to 0.64 after accounting for year-to-year variations. Milk composition was weakly but significantly associated with maternal mass in June and September, summer mass gain and winter mass loss. Variation explained by year-to-year fluctuations ranged from 0.07 to 0.91 suggesting a strong influence of environmental variability on milk composition. Milk composition did not affect lamb survival to weaning. Using joint models in ecological, physiological or behavioural contexts has the major advantage of decomposing a (co)variance/correlation matrix while being estimated with fewer parameters than in a "traditional" mixed-effects model. The joint models presented here complement a growing list of tools to analyse correlations at different hierarchical levels separately and may thus represent a partial solution to the conundrum of physiological complexity.

Variation among populations in the immune protein composition of mother's milk reflects subsistence pattern.

Lay SummaryAdaptive immune proteins in mothers’ milk are more variable than innate immune proteins across populations and subsistence strategies. These results suggest that the immune defenses in milk are shaped by a mother’s environment throughout her life.Background and objectivesMother’s milk contains immune proteins that play critical roles in protecting the infant from infection and priming the infant’s developing immune system during early life. The composition of these molecules in milk, particularly the acquired immune proteins, is thought to reflect a mother’s immunological exposures throughout her life. In this study, we examine the composition of innate and acquired immune proteins in milk across seven populations with diverse disease and cultural ecologies.MethodologyMilk samples (n = 164) were collected in Argentina, Bolivia, Nepal, Namibia, Philippines, Poland and the USA. Populations were classified as having one of four subsistence patterns: urban-industrialism, rural-shop, horticulturalist-forager or agro-pastoralism. Milk innate (lactalbumin, lactoferrin and lysozyme) and acquired (Secretory IgA, IgG and IgM) protein concentrations were determined using triple-quadrupole mass spectrometry.ResultsBoth innate and acquired immune protein composition in milk varied among populations, though the acquired immune protein composition of milk differed more among populations. Populations living in closer geographic proximity or having similar subsistence strategies (e.g. agro-pastoralists from Nepal and Namibia) had more similar milk immune protein compositions. Agro-pastoralists had different milk innate immune protein composition from horticulturalist-foragers and urban-industrialists. Acquired immune protein composition differed among all subsistence strategies except horticulturist-foragers and rural-shop.Conclusions and implicationsOur results reveal fundamental variation in milk composition that has not been previously explored in human milk research. Further study is needed to understand what specific aspects of the local environment influence milk composition and the effects this variation may have on infant health outcomes.