Age-specific composition of milk microbiota in Tibetan sheep and goats.

This study investigates the dynamic changes in milk nutritional composition and microbial communities in Tibetan sheep and goats during the first 56 days of lactation. Milk samples were systematically collected at five time points (D0, D7, D14, D28, D56) post-delivery. In Tibetan sheep, milk fat, protein, and casein contents were highest on D0, gradually decreased, and stabilized after D14, while lactose and galactose levels showed the opposite trend. Goat milk exhibited similar initial peaks, with significant changes particularly between D0, D7, D14, and D56. 16S rRNA gene sequencing revealed increasing microbial diversity in both species over the lactation period. Principal coordinates analysis identified distinct microbial clusters corresponding to early (D0-D7), transitional (D14-D28), and mature (D56) stages. Core phyla, including Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria, dominated the milk microbiota, with significant temporal shifts. Core microbes like Lactobacillus, Leuconostoc, and Streptococcus were common in both species, with species-specific taxa observed (e.g., Pediococcus in sheep, Shewanella in goats). Furthermore, we observed a highly shared core microbiota in sheep and goat milk, including Lactobacillus, Leuconostoc, and Streptococcus. Spearman correlation analysis highlighted significant relationships between specific microbial genera and milk nutrients. For instance, Lactobacillus positively correlated with total solids, non-fat milk solids, protein, and casein, while Mannheimia negatively correlated with protein content. This study underscores the complex interplay between milk composition and microbial dynamics in Tibetan sheep and goats, informing strategies for livestock management and nutritional enhancement. KEY POINTS: • The milk can be classified into three types based on the microbiota composition • The changes of milk microbiota are closely related to the variations in nutrition • Filter out microbiota with species specificity and age specificity in the milk.

Mammary fat globules as a source of mRNA to model alterations in the expression of some milk component genes during lactation in bovines.

BACKGROUND: The milk's nutritional value is determined by its constituents, including fat, protein, carbohydrates, and minerals. The mammary gland's ability to produce milk is controlled by a complex network of genes. Thereby, the fat, protein, and lactose synthesis must be boost in milk to increase milk production efficiency. This can be accomplished by fusing genetic advancements with proper management practices. Therefore, this study aimed to investigate the association between the Lipoprotein lipase (LPL), kappa casein CSN3, and Glucose transporter 1 (GLUT1) genes expression levels and such milk components as fat, protein, and lactose in different dairy breeds during different stages of lactation. METHODS: To achieve such a purpose, 94 milk samples were collected (72 samples from 36 multiparous black-white and red-white Holstein-Friesian (HF) cows and 22 milk samples from 11 Egyptian buffaloes) during the early and peak lactation stages. The milk samples were utilized for milk analysis and genes expressions analyses using non- invasive approach in obtaining milk fat globules (MFGs) as a source of Ribonucleic acid (RNA). RESULTS: LPL and CSN3 genes expressions levels were found to be significantly higher in Egyptian buffalo than Holstein-Friesian (HF) cows as well as fat and protein percentages. On the other hand, GLUT1 gene expression level was shown to be significantly higher during peak lactation than early lactation. Moreover, lactose % showed a significant difference in peak lactation phase compared to early lactation phase. Also, fat and protein percentages were significantly higher in early lactation period than peak lactation period but lactose% showed the opposite pattern of Egyptian buffalo. CONCLUSION: Total RNA can be successfully obtained from MFGs. The results suggest that these genes play a role in glucose absorption and lactose synthesis in bovine mammary epithelial cells during lactation. Also, these results provide light on the differential expression of these genes among distinct Holstein-Friesian cow breeds and Egyptian buffalo subspecies throughout various lactation phases.

Selection of a suitable animal model to evaluate secretion of drugs in the human milk: a systematic approach.

Lack of data on drug secretion in human milk is a concern for safe use of drugs during postpartum.Clinical studies are often difficult to perform; despite substantial improvements in computational methodologies such as physiologically based pharmacokinetic modelling, there is limited clinical data to validate such models for many drugs.Various factors that are likely to impact milk to plasma ratio were identified. A literature search was performed to gather available data on milk composition, total volume of milk produced per day, milk pH, haematocrit, and renal blood flow and glomerular filtration rate in various animal models.BLAST nucleotide and protein tools were used to evaluate the similarities between humans and animals in the expression and predominance of selected drug transporters, metabolic enzymes, and blood proteins.A multistep analysis of all the potential variables affecting drug secretion was considered to identify most appropriate animal model. The practicality of using the animal in a lab setting was also considered.Donkeys and goats were identified as the most suitable animals for studying drug secretion in milk and future studies should be performed in goats and donkeys to validate the preliminary observations.

Application of a short-wave pocket-sized near-infrared spectrophotometer to predict milk quality traits.

Portable handheld devices based on near-infrared (NIR) technology have improved and are gaining popularity, even if their implementation in milk has been barely evaluated. Thus, the aim of the present study was to assess the feasibility of using short-wave pocket-sized NIR devices to predict milk quality. A total of 331 individual milk samples from different cow breeds and herds were collected in 2 consecutive days for chemical determination and spectral collection by using 2 pocket-sized NIR spectrophotometers working in the range of 740 to 1,070 nm. The reference data were matched with the corresponding spectrum and modified partial least squares regression models were developed. A 5-fold cross-validation was applied to evaluate individual device performance and an external validation with 25% of the dataset as the validation set was applied for the final models. Results revealed that both devices' absorbance was highly correlated but greater for instrument A than B. Thus, the final models were built by averaging the spectra from both devices for each sample. The fat content prediction model was adequate for quality control with a coefficient of determination (R2ExV) and a residual predictive deviation (RPDExV) in external validation of 0.93 and 3.73, respectively. Protein and casein content as well as fat-to-protein ratio prediction models might be used for a rough screening (R2ExV >0.70; RPDExV >1.73). However, poor prediction models were obtained for all the other traits with an R2ExV between 0.43 (urea) and 0.03 (SCC), and a RPDExV between 1.18 (urea) and 0.22 (SCC). In conclusion, short-wave portable handheld NIR devices accurately predicted milk fat content, and protein, casein, and fat-to-protein ratio might be applied for rough screening. It seems that there is not enough information in this NIR region to develop adequate prediction models for lactose, SCC, urea, and freezing point.

Replacing the forage portion of the ration with triticale hay improves the performance of Holstein dairy cows.

The aim of the present study was to assess the effect of replacing the forage portion (alfalfa, corn silage, and barley straw) in the diet of lactating Holstein cows with triticale hay (TH, × Triticosecale L.) on DMI, digestibility, ruminal fermentation variables, estimated microbial-N synthesis (EMNS), and milk production and composition. Eight Holstein cows were used in a replicated Latin square design (two 4 × 4 squares) with four 28-d periods and 4 treatments, including a TH-free diet (control), and diets replacing 33%, 66%, and 100% of the forage portion with TH. Cows were fed ad libitum with 10% carryover during the experimental periods. Intakes and in vivo digestibilities of dry matter, organic matter, crude protein, and ash-free neutral detergent fiber, rumen pH, ammonia-N, total and individual short-chain fatty acids, protozoa, and bacteria populations were evaluated using specific methods. Moreover, in vitro total gas and methane release and in vivo urinary purine derivatives, EMNS, milk production, and composition were measured. The results showed that TH diets lowered DMI, compared with the control. Apparent digestibilities of DM, OM, CP, and NDF increased with dietary TH inclusion. The addition of TH instead of the diet forage portion increased in vivo rumen pH; acetic, propionic, valeric, and isovaleric acids concentrations; cellulolytic bacteria number; and in vitro gas production. In vivo rumen ammonia-N, short-chain fatty acids, butyric acid, in vivo and in vitro total protozoa and Entodiniinae numbers, and in vitro methane production decreased with increasing dietary levels of TH instead of the forage portion. The dietary addition of TH did not affect milk yield, protein, and lactose, but increased fat-corrected milk, milk fat, fat-corrected milk:DMI ratio, and milk yield:DMI ratio. Milk urea N decreased, but urinary purine derivatives excretion and EMNS increased with increasing levels of TH in the diet. For variables with significant changes, except for isovaleric acid, there was a linear response of animals to increasing levels of TH in the diet. Results suggest that TH, which is grown with less water compared with alfalfa, corn forage, and straw, is a potential alternative to those forages by increasing milk production efficiency, milk fat, and decreasing methane emission.

l-Arginine supplementation for pregnant and lactating sows may improve the performance of piglets: A systematic review.

The objective was to conduct a systematic review to clarify the effects of l-arginine supplementation in pregnant and lactating sows on plasma hormone levels, milk production and composition, the body condition of sows and piglet performance. In April 2023, an online search and a systematic search were performed in the following databases: Embase, Scopus, SciELO, Web of Science, PubMed and Science Direct. The combinations of keywords used were sow and arginine and lactation; sow and arginine and lactating; sow and arginine and gestation; sow and arginine and gestating; sow and arginine and pregnancy; sow and arginine and reproduction; piglet and arginine; and sow and arginine and mammary gland. In total, 21 scientific articles with original data were selected according to preestablished criteria. Among the 21 articles, seven (33%) reported measurements of some plasma hormones, and among these, six reported an increase in the levels of at least one hormone, namely, estradiol, insulin-like growth factor 1 (IGF-1), insulin, follicle stimulating hormone, growth hormone or prolactin, with l-arginine supplementation. The parameters of milk were evaluated in 11 studies (52%), one reported an increase in protein content, and one reported an increase in IGF-1 content in milk with supplementation of this amino acid. Of the 14 studies that evaluated the performance parameters of piglets, only four reported improvements in some parameters of piglets from sows that received supplementation. Dietary supplementation of arginine for sows in the final third of gestation and/or lactation may alter the plasma levels of some hormones, which may reflect in greater development of the mammary gland tissue and, consequently, promote benefits on the performance of piglets. However, more studies are needed to evaluate the real impact of this amino acid supplementation on the physiology of the sows, in general, and the performance of suckling piglets.

Lactation traits and reproductive performances of Sahraoui female camel in two breeding systems at Algerian Sahara.

The main objective of this study is to determine the impact of the camel livestock system on individual and herd performances of milk production, lactation curve, fats, and protein concentrations. For this purpose, 13 she-camels of Sahraoui breed from the south eastern Algeria and belonging and semi-intensive system (N = 6) and intensive system (N = 7) were studied. Recording and sampling of milk were carried out at regular intervals during a full lactation. The lactation curve was estimated using Wood's gamma function and the t-test of independent groups was carried out to compare lactation performances, lactation curve, and reproductive parameters. The overall average daily milk (DMY), fat (DFY), and protein (DPY) yield were 6.77 ± 0.82 kg/day, 4.15 ± 0.91%, and 4.49 ± 0.20%, respectively. The mean of total milk yield (TMY) was 2696.39 ± 343.86 kg during a mean lactation length (LL) of 398.38 ± 20.65 days. The peak of milk production (6.79 ± 0.68 kg) was reached at 93.9 ± 55.8 days after calving. The open day (DO) and inter-calving interval (ICI) recorded in this study were 348.38 ± 30.33 and 723.38 ± 30.33 days, respectively. There is no significant difference (p > 0.05) between intensive and semi-intensive breeding systems for TMY (2795.39 ± 261.88 kg vs. 2580.89 ± 414.43 kg), DMY (6.96 ± 0.66 kg vs. 6.55 ± 1.00 kg), and LL (402.14 ± 21.18 days vs. 394 ± 21.03 days). However, the total amount of fat was significantly higher in intensive system (182.02 ± 33.91 kg) and the DPY content was significantly higher in semi-intensive system (4.60 ± 0.13%). The parameters α, ß, and γ of lactation, fat, and protein curves between the two systems showed a highly significant difference (p < 0.01) for the parameters (α and ß) for the milk production curve, significant (p < 0.05) for the time to reach peak yield, and no significance for the other parameters. The corresponding values of the coefficient of determination (R2) were 0.62, 0.35 for milk yield (p > 0.05), 0.12, 0.13 (p > 0.05) for fat, and 0.03, 0.11 (p < 0.05) for protein, in the intensive and semi-intensive systems, respectively. In addition, DO and ICI were not significantly different between the livestock systems, but were higher in the intensive system than the semi-intensive system (337.17 ± 26.26 vs. 712.17 ± 26.26, respectively). The study concluded that the intensive system had a higher milk performance with a more efficient lactation curve. The incomplete gamma model (Wood) used in this study was inappropriate for estimating milk yield, but acceptable for fat and protein.

Nutritional factors affecting camel (Camelus dromedarius) milk composition.

Saharan population in Algeria still depending on bovine milk, which suffers from serious constraints undermining its sustainability. Camelus dromedarius milk has experienced growing demand following the emerging market requirements for livestock production and dairy farming over the past decade. The present work aimed at analysing the effect of nutritional regime on milk quality. The differences in pH, Acidity D°, Ash and Fats were significant. The pH was negatively influenced by the intensification conditions such as the much higher use of concentrates. The major constituents of milk were strongly and positively correlated with barley, wheat bran, TN/Kg.DM (Total Nitrogen/ Kg. Dry Matter), Kg.DM, Concentrates and daily watering. The results showed that a good energy-protein balance around 73 g PDI/UFL (Protein Digestible in the Intestine/Energetic Forage Unit for milk production) was beneficial for a better milk protein ratio. The use of corn, soybeans, palm dates and VM-premix (Vitamin Mineral) supplementation were also favourable to the synthesis of fats. Crude fiber and cell walls were better valued in the synthesis of fats with the availability of concentrates and the increasing of TN /Kg.DM and VM-premix rate in dietary regime. The vitamin C content elevate following high ratio of UFL /Kg.DM and PDI/UFL. For thus, the influence of nutritional status can lead to major improvements that need also more advanced and detailed studies.

Dairy goat performance in two grazing regimes: silvopastoral rangeland or abandoned agricultural land, and two supplementation treatments in central Mexico.

Twenty Saanen third parturition dairy goats were used in an on-farm 2 × 2 factorial arrangement that ran for 12 weeks, with two grazing regimes and two concentrate types. The grazing regimes evaluated were an extensive silvopastoral native rangeland (SPR) and grazing in an abandoned agricultural land (AAL). Grazing happened between 9:00 and 17:00 h. The two types of concentrate supplement were a high protein concentrate (HP = 180 g CP/kg DM and 13 MJ ME/kg DM) or high energy concentrate (HE = 110  g CP/kg DM and 14.3 MJ ME/kg DM). Goats were milked once a day, providing 250 g of concentrate supplement per goat and day. Animal variables were fat and protein corrected milk yield recorded every day, and milk composition determined for two consecutive days at the end of each experimental week. Flora in the experimental paddocks was characerised and sampled, including grasses, shrubs, trees, legumes and cacti. The data was analysed with the R software using a mixed model with day nested in period as random effect and goat as repeated measure. The SPR had greater (P = 0.002) fat and protein corrected milk yield than AAL, with no differences between concentrate type and no interaction (P > 0.05). There was an interaction (P < 0.01) between grazing regime and concentrate type for fat content in milk, where a reduction in fat content was notorious in the SPR regime. Protein content of milk was greater (P < 0.01) in SPR with no significant effects of concentrate type or the interaction. The number of plant species in SPR was greater. The native silvopastoral system supplemented with the high energy concentrate was the strategy with higher milk yield, and protein and milk fat content, although the interaction between grazing regime and supplement was significant only for milk fat content.

Specific Milk Composition of miR-30b Transgenic Mice Associated with Early Duodenum Maturation in Offspring with Lasting Consequences for Growth.

BACKGROUND: Milk composition is complex and includes numerous components essential for offspring growth and development. In addition to the high abundance of miR-30b microRNA, milk produced by the transgenic mouse model of miR-30b-mammary deregulation displays a significantly altered fatty acid profile. Moreover, wild-type adopted pups fed miR-30b milk present an early growth defect. OBJECTIVE: This study aimed to investigate the consequences of miR-30b milk feeding on the duodenal development of wild-type neonates, a prime target of suckled milk, along with comprehensive milk phenotyping. METHODS: The duodenums of wild-type pups fed miR-30b milk were extensively characterized at postnatal day (PND)-5, PND-6, and PND-15 using histological, transcriptomic, proteomic, and duodenal permeability analyses and compared with those of pups fed wild-type milk. Milk of miR-30b foster dams collected at mid-lactation was extensively analyzed using proteomic, metabolomic, and lipidomic approaches and hormonal immunoassays. RESULTS: At PND-5, wild-type pups fed miR-30b milk showed maturation of their duodenum with 1.5-fold (P < 0.05) and 1.3-fold (P < 0.10) increased expression of Claudin-3 and Claudin-4, respectively, and changes in 8 duodenal proteins (P < 0.10), with an earlier reduction in paracellular and transcellular permeability (183 ng/mL fluorescein sulfonic acid [FSA] and 12 ng/mL horseradish peroxidase [HRP], respectively, compared with 5700 ng/mL FSA and 90 ng/mL HRP in wild-type; P < 0.001). Compared with wild-type milk, miR-30b milk displayed an increase in total lipid (219 g/L compared with 151 g/L; P < 0.05), ceramide (17.6 µM compared with 6.9 µM; P < 0.05), and sphingomyelin concentrations (163.7 µM compared with 76.3 µM; P < 0.05); overexpression of 9 proteins involved in the gut barrier (P < 0.1); and higher insulin and leptin concentrations (1.88 ng/mL and 2.04 ng/mL, respectively, compared with 0.79 ng/mL and 1.06 ng/mL; P < 0.01). CONCLUSIONS: miR-30b milk displays significant changes in bioactive components associated with neonatal duodenal integrity and maturation, which could be involved in the earlier intestinal closure phenotype of the wild-type pups associated with a lower growth rate.

Human milk: From complex tailored nutrition to bioactive impact on child cognition and behavior.

Human milk is a highly complex liquid food tailor-made to match an infant's needs. Beyond documented positive effects of breastfeeding on infant and maternal health, there is increasing evidence that milk constituents also impact child neurodevelopment. Non-nutrient milk bioactives would contribute to the (long-term) development of child cognition and behavior, a process termed 'Lactocrine Programming'. In this review we discuss the current state of the field on human milk composition and its links with child cognitive and behavioral development. To promote state-of-the-art methodologies and designs that facilitate data pooling and meta-analytic endeavors, we present detailed recommendations and best practices for future studies. Finally, we determine important scientific gaps that need to be filled to advance the field, and discuss innovative directions for future research. Unveiling the mechanisms underlying the links between human milk and child cognition and behavior will deepen our understanding of the broad functions of this complex liquid food, as well as provide necessary information for designing future interventions.

Dairy products and constituents: a review of their effects on obesity and related metabolic diseases.

Obesity has become a global public health problem that seriously affects the quality of life. As an important part of human diet, dairy products contain a large number of nutrients that are essential for maintaining human health, such as proteins, peptides, lipids, vitamins, and minerals. A growing number of epidemiological investigations provide strong evidence on dairy interventions for weight loss in overweight/obese populations. Therefore, this paper outlines the relationship between the consumption of different dairy products and obesity and related metabolic diseases. In addition, we dive into the mechanisms related to the regulation of glucose and lipid metabolism by functional components in dairy products and the interaction with gut microbes. Lastly, the role of dairy products on obesity of children and adolescents is revisited. We conclude that whole dairy products exert more beneficial effect than single milk constituent on alleviating obesity and that dairy matrix has important implications for metabolic health.

Urea molasses mineral block under various feeding systems improved nutrient digestibility, productive performance and blood biochemical profile of Yaks.

BACKGROUND: The study aimed to investigate the effect of urea molasses mineral blocks (UMMB) on nutrient digestibility, productive performance and blood biochemical profile of indigenous yaks under various feeding systems. A total of sixteen yaks were randomly divided into four groups (n = 4 animal per group) and offered the, following feeding systems: (A) stall feeding, (B), urea molasses mineral block (UMMB) + stall feeding, (C) yard feeding and (D) UMMB + yard feeding. Trial lasted for 40 days. RESULTS: Results showed that nutrients intake (g) and nutrient digestibility (%) of dry matter (DM), organic matter (OM), crude protein (CP), ether extract (EE) and crude fiber (CF) were significantly higher (p < 0.05) in stall and yard feeding groups with UMMB licking. Blood zinc, cobalt, hemoglobin (Hb), red blood cell (RBC), glucose and serum glutamate private transaminase (SGPT) significantly (p < 0.05) increased in stall and yard feeding with UMMB licking. Milk yield, Ca and monounsaturated fatty acid except milk composition improved significantly (p < 0.05) in stall and yard feeding groups with UMMB licking. CONCLUSION: It was concluded that feeding of UMMB improved utilization of low-quality roughages and best results were obtained from stall and yard feedings with UMMB licking as compared to other groups.

Potential role of rumen bacteria in modulating milk production and composition of admixed dairy cows.

Cattle milk is an important food for the growing calf and humans because of its concentrated macro and micro nutrients. However, the quantity and quality of milk nutrients vary depending on several factors. This study evaluated the effect of dietary modification on rumen bacteria as well as the potential role of rumen bacteria in modifying milk production and composition profile. Using a 16S rRNA metagenomic approach, the study characterized the rumen bacterial community composition in four dairy cows and their milk production and composition. The results indicated that Bacteroidetes and Firmicutes were the dominant bacteria, totaling ∼83.7% of the rumen bacteria. An increase in concentrate proportion in diet led to an increase in the abundance of Bacteroidetes (P ≤ 0.05) and Proteobacteria while Firmicutes and Fibrobacter decreased. Milk production and composition were highly correlated with the abundance of various rumen bacterial members. Lentispaerae (P = 0.010), and Synergistetes (P = 0.011) exhibited a positive and significant correlation while Tenericutes (P = 0.009) showed a negative correlation with milk protein. Fusobacteria (P = 0.016) showed a negative correlation with milk lactose. Similarly, several genera showed correlations with milk parameters. The correlation between microbes with milk parameters implies that the bacterial community possesses the potential to influence milk production and composition.

Genetic analysis of milk and milk composition traits in Murrah buffaloes using Bayesian inference.

Accurate and unbiased assessment of genetic parameters of milk and milk composition traits play an important role in formulating breeding program for genetic improvement of Murrah buffaloes. In this study, data spread over 28 years were utilized to estimate genetic parameters of traits viz., 305 d milk yield (305MY), 305 d fat yield (305FY), 305 d solid not fat yield (305SNFY), milk fat percentage (fat%) and solid not fat percentage (SNF) percentage (SNF%) in Murrah buffaloes kept at ICAR-National Dairy Research Institute, Karnal. Bayesian multiple-trait analysis was done using animal model and Gibbs sampling to estimate (co)variance components. Posterior means of heritability and posterior standard deviation for 305MY, 305FY, 305SNFY, fat% and SNF% were 0.18 ± 0.05, 0.17 ± 0.05, 0.18 ± 0.05, 0.07 ± 0.03 and 0.15 ± 0.06 and posterior means of repeatability estimates along with posterior standard deviation for corresponding traits were 0.33 ± 0.04, 0.32 ± 0.04, 0.33 ± 0.04, 0.14 ± 0.02 and 0.30 ± 0.04, respectively. Estimates of genetic correlation varied from -0.080 (305MY and fat %) to 0.999 (305MY and 305SNFY). Permanent environmental correlations varied from -0.060 (305MY and SNF%) to 0.999 (305FY and 305SNFY). This study indicated that all considered traits except fat% have ample genetic variability which can be exploited for selection and genetic improvement of Murrah buffaloes.

Association of new SNPs at DGAT1 gene with milk quality in Egyptian Zaraibi goat breed.

This study aimed to detect putative genomic loci in candidate genes associated with milk composition in Egyptian Zaraibi goats. A total number of 50 samples were tested to detect polymorphism in exons 15 and 16 of the diacylglycerol acyltransferase 1 (DGAT1) gene. The PCR products were sequenced and aligned. Sequence analysis showed three new genotypes in the studied samples: T1C1 (T12C SNP), T2C2 (T84C), and AG (G219A), then three groups were created: the first group was BB with C1T1 and AG genotypes, the second was DD which contains C2T2 and AG genotypes, and the third was AG with only AG genotype. GLM showed that the DD group with C84T and G219A SNPs had significantly the highest fat percent. Meanwhile, the BB group with C84T and G219A SNPs recorded significantly the highest total solids levels. On the other hand, the AG group which has G219A SNP showed a non-significant effect on milk components. Those new SNPs were submitted to GenBank and approved to be published. Moreover, translation of those sequences showed that the G219A SNP causes a substitution of Glycine to Serine in exon 16 at position 106. This SNP (G106S) was predicted to be tolerated by SIFT with a score of 0.48.

Genetic variation in the OPN gene affects milk composition in Chinese Holstein cows.

The aim of this study was to investigate the association between genotypes and haplotypes of OPN, and milk composition in dairy cows. A total of 317 Chinese Holstein cows were genotyped via DNA sequencing in this study. Three single nucleotide polymorphisms (SNPs), g.2916G > A, g.58675C > T and g.58899C > A, and eight haplotypes were identified. Of the eight possible haplotypes, four haplotypes i.e., Hap2 (ACC; 55.30%), Hap6 (GCC, 15.6%), Hap1 (ACA, 13.6%) and Hap4 (ATC, 5.70%), were considered to be major with a cumulative estimated frequency of >90%. Single markers (g.2916G > A and g.58899C > A) and Haplotype Hap6/4 were found to be associated with an increase in butter-fat percentage (p < 0.05). Taken together, our results provided evidence that polymorphisms in OPN are associated with milk composition, and could potentially be used for marker-assisted selection in Chinese Holstein cows.

Heritabilities and genetic and phenotypic correlations for milk production and fertility traits of spring-calved once-daily or twice-daily milking cows in New Zealand.

The objectives of this study were to estimate the genetic and phenotypic correlations and heritabilities for milk production and fertility traits in spring-calved once-daily (OAD) milking cows for the whole season in New Zealand and compare those estimates with twice-daily (TAD) milking cows. Data used in the study consisted of 69,252 first parity cows from the calving seasons 2015-2016 to 2017-2018 in 113 OAD and 531 TAD milking herds. Heritability estimates for production and fertility traits were obtained through single-trait animal models, and estimates of genetic and phenotypic correlations were obtained through bivariate animal models. Heritability estimates of production traits varied from 0.26 to 0.61 in OAD and from 0.13 to 0.63 in TAD. Heritability estimates for fertility traits were low in both OAD and TAD milking cow populations, and estimates were consistent (OAD: 0.01 to 0.10 and TAD: 0.01 to 0.08) across milking regimens. Estimates of phenotypic and genetic correlations among production traits were consistent across populations. In both populations, phenotypic correlations between milk production and fertility traits were close to zero, and most of the genetic correlations were antagonistic. In OAD milking cows, genetic correlations of milk and lactose yields with the start of mating to conception, 6-wk in-calf, not-in-calf, and 6-wk calving rate were close to zero. Interval from first service to conception was negatively genetically correlated with milk and lactose yields in OAD milking cows. Protein percentage was positively genetically correlated with 3-wk and 6-wk submission, 3-wk in-calf, 6-wk in-calf, first service to conception, 3-wk calving, and 6-wk calving rate in the TAD milking cow population, but these correlations were low in the OAD milking cow population. Further studies are needed to understand the relationship of protein percentage and fertility traits in the OAD milking system. The phenotypic correlations between fertility traits were similar in OAD and TAD milking populations. Genetic correlations between fertility traits were strong (≥0.70) in cows milked TAD, but genetic correlations varied from weak to strong in cows milked OAD. Further research is required to evaluate the interaction between genotype by milking regimen for fertility traits in terms of sire selection in the OAD milking cow population.

Invited review: Corrected milk: Reconsideration of common equations and milk energy estimates.

Corrected milk equations were developed in attempts to bring milk weights to a standardized basis for comparison by expressing the weight and composition of milk as corrected to the energy content of milk of a specific composition. Expressed as milk weights familiar on farm and in commerce, this approach integrates energy contributions of the dissimilar components to make the mass units more comparable. Such values are applied in evaluating feed efficiency, lactation performance, and global milk production, as functional units for lifecycle assessments, and in translation of research results. Corrected milk equations are derived from equations relating milk gross energy to milk composition. First, a milk energy equation is used to calculate the energy value of the milk composition to correct to (e.g., 0.695 Mcal/kg for milk with 3.5% fat, 3.05% true protein, and 4.85% lactose). That energy value is divided into the energy equation to give the corrected milk equation. Confusion has arisen, as different equations purport to correct to the same milk composition; their differences are based on uses of different energy equations or divisors. Accuracy of corrected milk equations depends on the accuracy of the energy equations used to create them. Energy equations have evolved over time as different milk component analyses have become more available. Inclusion of multiple milk components more accurately predicts milk energy content than does fat content alone. Omission of components from an equation requires the assumption that their content in milk is constant or highly correlated with an included component. Neither of these assumptions is true. Milk energy equations evaluated on a small data set of measured milk values have demonstrated that equations that incorporate protein, fat, and lactose contents multiplied by the gross energy of each component more closely predict milk energy than equations containing fewer components or regression-derived equations. This provides a tentative recommendation for using energy equations that include the 3 main milk components and their gross energy multipliers for predicting milk energy and deriving corrected milk equations. Accuracy of energy equations is affected by the accuracy of gross energy values of individual components and variability of milk composition. Lactose has consistent reported gross energy values. In contrast, gross energy of milk fat and protein vary as their compositional profiles change. Future refinements could assess accuracy of milk fat and protein gross energy and whether that appreciably improves milk energy predictions. Fat gross energy has potential to be calculated using the milk fatty acid profile, although the influence on gross energy may be small. For research, direct reporting of milk energy values, rather than corrected milk, provides the most explicit, least manipulated form of the data. However, provision of corrected milk values in addition to information on components can serve to translate the energy information to a form familiar to and widely used in the field. When reporting corrected milk data, the corrected milk equation, citation for the energy equation used, and composition and energy contents of the corrected milk must be described to make clear what the values represent.

Diagnostic milk biomarkers for predicting the metabolic health status of dairy cattle during early lactation.

Data on metabolic profiles of blood sampled at d 3, 6, 9, and 21 in lactation from 117 lactations (99 cows) were used for unsupervised k-means clustering. Blood metabolic parameters included ß-hydroxybutyrate (BHB), nonesterified fatty acids, glucose, insulin-like growth factor-1 (IGF-1) and insulin. Clustering relied on the average and range of the 5 blood parameters of all 4 sampling days. The clusters were labeled as imbalanced (n = 42) and balanced (n = 72) metabolic status based on the values of the blood parameters. Various random forest models were built to predict the metabolic cluster of cows during early lactation from the milk composition. All the models were evaluated using a leave-group-out cross-validation, meaning data from a single cow were always present in either train or test data to avoid any data leakage. Features were either milk fatty acids (MFA) determined by gas chromatography (MFA [GC]) or features that could be determined during a routine dairy herd improvement (DHI) analysis, such as concentration of fat, protein, lactose, fat/protein ratio, urea, and somatic cell count (determined and reported routinely in DHI registrations), either or not in combination with MFA and BHB determined by mid-infrared (MIR), denoted as MFA [MIR] and BHB [MIR], respectively, which are routinely analyzed but not routinely reported in DHI registrations yet. Models solely based on fat, protein, lactose, fat/protein ratio, urea and somatic cell count (i.e., DHI model) were characterized by the lowest predictive performance [area under the receiver operating characteristic curve (AUCROC) = 0.69]. The combination of the features of the DHI model with BHB [MIR] and MFA [MIR] powerfully increased the predictive performance (AUCROC = 0.81). The model based on the detailed MFA profile determined by GC analysis did not outperform (AUCROC = 0.81) the model using the DHI-features in combination with BHB [MIR] and MFA [MIR]. Predictions solely based on samples at d 3 were characterized by lower performance (AUCROC DHI + BHB [MIR] + MFA [MIR] model at d 3: 0.75; AUCROC MFA [GC] model at d 3: 0.73). High predictive performance was found using samples from d 9 and 21. To conclude, overall, the DHI + BHB [MIR] + MFA [MIR] model allowed to predict metabolic status during early lactation. Accordingly, these parameters show potential for routine prediction of metabolic status.