The study set out to disentangle the genetic and non-genetic factors that shape milk composition and cow metabolism under real field conditions. The researchers analysed 230 Czech Holstein and 289 Czech Simmental cows, sired by 122 bulls and housed on five farms operating free-stall systems. Milk samples were collected during routine performance testing, meaning the animals were handled exactly as they would be in ordinary commercial practice. Roughly half of the cows were sampled twice within the same lactation, allowing the team to build a dataset of 814 individual test-day records spanning the first through sixth lactations and covering days 1 to 305 of milk production.

The analytical toolkit was deliberately broad. In an accredited laboratory of the Czech–Moravian Breeders Association, the team used Fourier transform mid-infrared spectroscopy to measure fat, crude protein, lactose, urea, citric acid, acetone, β-hydroxybutyric acid (BHB), somatic cell counts, and a panel of fatty acids in every sample. DNA was extracted non-invasively from the milk itself, and the cows were genotyped for polymorphisms in five candidate genes central to milk fat synthesis: AGPAT6, SCD1, FASN, LEP, and DGAT1. These genes encode enzymes and regulators of lipid metabolism and have repeatedly been implicated in previous studies as potential markers for milk fat content, fatty acid composition, and susceptibility to metabolic disease.

Statistically, the researchers applied a linear mixed model with repeated measurements, treating gene variant, farm, parity, lactation stage, and breed as fixed effects while accounting for the sire and the permanent environment of each cow as random effects. Two-way interactions among genotype, farm, lactation stage, and parity were also tested. Post hoc comparisons were performed with Scheffé’s test, and Pearson correlations quantified the relationships among milk components. This design allowed the team to ask, with unusual resolution for a field study, which factors truly matter when the messy realities of commercial dairying are taken into account.

The verdict was unambiguous: farm and lactation stage were the most significant factors influencing nearly every milk parameter measured, along with their interaction. The effects of parity and breed were much weaker, a result the authors attribute in part to the partial overlap between breed and farm, since most of the participating herds kept only one breed. Notably, the significance of parity increased once lactation stage was included in the model, suggesting that properly adjusting for the physiological trajectory of lactation reveals genuine differences between first, second, and later calvings that would otherwise be masked by lactation-related variability.

The candidate genes, by contrast, largely failed to leave their mark. The impact of the five polymorphisms on milk parameters and the fatty acid profile was very low, as were the interactions between gene and farm, gene and lactation stage, and parity and lactation stage. This stands in tension with earlier work reporting significant associations between FASN, SCD1, and DGAT1 variants and milk fat traits or fatty acid composition. One caveat concerns the rare FASN genotype, the AA variant, which was detected in only two animals, potentially reducing the statistical power to detect effects for that allele. The authors also note that four of the five loci deviated significantly from Hardy–Weinberg equilibrium, a pattern consistent with the selection pressure and non-random mating that characterise managed livestock populations.

The metabolic story centred on BHB, a ketone body produced when cows mobilise body fat during the negative energy balance of early lactation. BHB levels in milk were significantly influenced by farm in all models, and by parity in the models including AGPAT6, SCD1, and DGAT1, with concentrations rising from 0.046 millimoles per litre in first lactation to 0.062 in second. Intriguingly, lactation stage itself did not significantly affect BHB in any model, unlike its pervasive effect on other components. BHB correlated strongly and positively with acetone, a relationship reflecting shared ketone metabolism, and correlated significantly with the fat-to-protein ratio, confirming earlier reports linking this ratio to energy status.

Yet the study delivers a sobering message about individual-level diagnosis. Although the association between BHB and the fat-to-protein ratio was statistically significant, the authors conclude that predicting ketosis in individual cows from this ratio does not appear reliable. Previous work has shown that while the fat-to-protein ratio can indicate negative energy balance at the herd level, no threshold provides acceptable sensitivity and specificity for identifying hyperketonaemia in a single animal. Instead, the researchers propose that milk BHB itself, which is routinely assessed during standard milk performance testing, may serve as a practical field predictor of clinical or subclinical ketosis, particularly as automatic in-line milk composition recording becomes more widespread.

Other correlations painted a coherent picture of high-producing cows under metabolic strain. Daily milk yield correlated negatively with most milk components, while urea content and milk yield were significantly positively correlated, hinting at higher metabolic intensity in the most productive animals. Lactose content showed a significant negative correlation with the somatic cell score, reinforcing its role as an indicator of udder health, and a weak but significant positive correlation emerged between the somatic cell score and BHB. Milk urea, the authors caution, should be interpreted as a herd-level tool for evaluating protein nutrition rather than as an individual diagnostic, since it is influenced by a wide variety of factors including health status.

The study’s limitations are acknowledged by the authors themselves: the animals came from a limited number of farms, and some genotypes were represented by very few animals. Even so, the central conclusion is robust and actionable. In the contest between genes and environment for control of milk composition, the environment wins decisively under field conditions, with feeding regimes, housing, milking management, and the natural arc of the lactation curve overwhelming the modest contributions of individual lipogenic gene variants. For dairy producers, the practical takeaway is that routine milk recording, especially when it includes BHB measurement, offers a powerful and increasingly automated window into herd metabolism, one that may ultimately catch ketotic cows earlier than any single genetic marker or ratio ever could.

Subject of Research: Genetic and non-genetic factors affecting milk composition and metabolic status in dairy cows

Article Title: Genetic and non-genetic factors influencing milk composition and cow metabolism

Article References: Čítek, J., Samková, E., Brzáková, M., Hanuš, O., Večerek, L., Jozová, E., Hasoňová, L., Baldíková, E., Iliyasu, S. M., & Rost, M. (2026). Genetic and non-genetic factors influencing milk composition and cow metabolism. Archives Animal Breeding, 69(4), 541-552. https://doi.org/10.5194/aab-69-541-2026

Image Credits: AI Generated

DOI: 10.5194/aab-69-541-2026

Keywords: dairy cattle, milk composition, ketosis, beta-hydroxybutyrate, lipogenic genes, fatty acids, lactation stage, fat-to-protein ratio, animal genetics, metabolic health, FT-MIR spectroscopy, Holstein

The research, published in Food Science of Animal Resources, followed 400 lactating Holstein cows across three commercial dairy farms in Jeju City over 47 months, from January 2021 to November 2024. During this period the farms progressively replaced their conventional concentrate feeds with commercially manufactured methane-mitigating concentrates, allowing the researchers to compare milk records before and after the transition under genuine production conditions. Two products were involved: one containing a yeast-based additive, garlic-derived diallyl disulfide, and condensed tannins, and another built around a commercial essential-oil blend marketed as Agolin. The full composition of the additives is proprietary, a common feature of the emerging methane-mitigation market that itself complicates independent scientific evaluation. All cows received a total mixed ration formulated to Korean feeding standards, delivered twice daily, with free access to water and minerals.

The headline result is straightforward: milk volume survived the transition intact. Across all statistical models, including multifactorial general linear models and linear mixed-effects models that treated individual cows as random effects, methane-mitigating feeding showed no significant effect on daily milk yield. For dairy farmers weighing whether to adopt climate-friendly rations, this is the single most commercially consequential finding, because any drop in milk output would translate directly into lost revenue and would likely doom adoption regardless of environmental benefits. The result also aligns with earlier experimental work showing that additives such as 3-nitrooxypropanol, which can cut enteric methane by 24 to 40 percent, and the red seaweed Asparagopsis, which has suppressed methane by more than 80 percent in controlled trials, generally leave production untouched.

Beneath the calm surface of total yield, however, the milk itself changed. Cows receiving the methane-mitigating concentrate showed significantly lower concentrations of milk protein, solid non-fat, and milk urea nitrogen, along with a modest but statistically consistent increase in somatic cell count, an indicator of udder health and immune activity. Milk urea nitrogen is a window into nitrogen metabolism: when rumen microbes capture dietary nitrogen inefficiently, excess ammonia is converted to urea and appears in blood and milk. Lower MUN in the methane-mitigating group therefore hints that the additives altered rumen fermentation in ways that shifted how the animals handled nitrogen, a plausible consequence of additives that redirect hydrogen away from methanogenic archaea and thereby reshape the entire microbial economy of the rumen.

The somatic cell count finding deserves careful handling. The increase was moderate and does not indicate clinical mastitis, and the authors explicitly caution against causal interpretation. Still, the signal appeared across all three farms, reaching statistical significance everywhere, which lends it weight. One mechanistic explanation involves the gut-immune axis: dietary components that alter rumen fermentation can shift ruminal pH and microbial turnover, promoting the release of lipopolysaccharides, molecular fragments of bacterial membranes that act as inflammatory triggers and can elevate somatic cell counts even in the absence of infection. Previous trials with 3-nitrooxypropanol and Asparagopsis have reported similarly inconsistent somatic cell outcomes, suggesting this may be a recurring, if subtle, trade-off in methane-mitigation feeding.

Perhaps the most striking feature of the study is how context-dependent the responses proved to be. Milk fat fell significantly on Farm A but not on the other two. Milk protein dropped on Farm C alone. Solid non-fat declined on Farms B and C but not on A. Interactions between feed type and farm, parity, and month were significant for nearly every compositional trait, meaning the effect of the same additive family depended on where the cow lived, how many lactations she had completed, and what time of year it was. Farm-level differences in forage quality, hygiene protocols, microclimate, and baseline nutrition likely explain much of this heterogeneity, and the authors argue that any policy or implementation framework must account for it.

Parity emerged as a particularly powerful moderator. Milk yield climbed steadily from the first through the fifth lactation before plateauing and declining, while protein, solid non-fat, and MUN drifted downward with age, consistent with the cumulative metabolic stress and reduced hepatic and mammary efficiency of older cows. Against this backdrop, the methane-mitigating feed produced parity-specific effects: milk yield rose significantly in sixth-parity cows but fell in third and fourth parity animals, solid non-fat declined consistently across parities three through six, and somatic cell counts rose in several mid-life parities. MUN was lower across all parities, though significance faded after the second. These patterns suggest that younger, more metabolically resilient cows absorb dietary perturbation more easily, while older animals, already operating closer to their physiological limits, respond more visibly.

Seasonality added another layer of complexity. Milk protein and solid non-fat dipped during the hot summer months of June through August, a classic heat-stress signature reflecting reduced feed intake and impaired rumen function. Yet the methane-mitigating group’s solid non-fat decline progressed gradually from summer into winter rather than showing a sharp heat-driven drop, and MUN differences persisted across most months with only scattered exceptions. The monthly patterns therefore do not map neatly onto thermal stress alone, implying that individual cow variability, forage quality, and intake dynamics modulate how the feed expresses itself through the calendar. Notably, somatic cell counts remained stable across months, suggesting mammary health in these herds was governed more by parity structure and farm hygiene than by climate.

To distill these tangled effects, the team ran stepwise regression guided by the Schwarz Bayesian Criterion, testing whether methane-mitigating feeding independently explained variation in each trait once farm, parity, and month were considered. The answer was nuanced. Feed group was not retained for milk yield, fat, or protein, indicating those traits are governed by structural factors. But it was retained with strong statistical support for solid non-fat, MUN, and log-transformed somatic cell count, and its inclusion improved model fit, most notably for MUN. The overall explanatory power of the models was modest, with adjusted R-squared values between roughly 0.07 and 0.20, which the authors attribute to the enormous unmeasured variability inherent in field data, from genetics and individual intake to rumen microbial communities.

The study carries an important caveat that tempers its climate message: no methane was actually measured. The feeds were formulated with mitigation in mind, but the research assessed downstream consequences on milk, not upstream effects on emissions. The authors are explicit that the results should not be read as proof of methane reduction. What the study does establish is feasibility and safety at scale: commercially available methane-mitigating concentrates can be deployed across real farms for years without sacrificing milk volume, while producing detectable, context-sensitive shifts in nitrogen-related milk traits and a modest rise in somatic cell counts. The next generation of research, the authors argue, must pair direct methane measurement with rumen fermentation analysis, inflammatory marker monitoring, and cow-level physiological profiling. Until then, the Jeju experiment stands as a rare and valuable bridge between the optimistic world of controlled methane trials and the messy, variable reality of the commercial dairy farm, where the climate solution ultimately has to work.

Subject of Research: Field evaluation of methane-mitigating concentrate feed effects on milk production, composition, and udder health in commercial Holstein dairy cows

Article Title: Impact of methane-mitigating concentrate feed on milk production, composition, and udder health in Holstein cows

Article References: Lee, S., Ko, K., Kim, G., Park, J.-E., & Ryu, Y. (2026). Impact of methane-mitigating concentrate feed on milk production, composition, and udder health in Holstein cows. Food Science of Animal Resources, 46(1), Article 49. https://doi.org/10.1007/s44463-025-00033-w

Image Credits: AI Generated

DOI: 10.1007/s44463-025-00033-w

Keywords: methane mitigation, dairy cows, Holstein, milk composition, milk urea nitrogen, somatic cell count, enteric fermentation, feed additives, greenhouse gas emissions, udder health, commercial dairy farms, sustainable dairy production

The research, led by Camila S. da Silva of Embrapa Mid-North together with colleagues at Embrapa Dairy Cattle in Minas Gerais, Michigan State University, and the Federal University of Minas Gerais, was conducted at the Multi-User Laboratory of Livestock Bioefficiency and Sustainability in Coronel Pacheco, a humid subtropical site in the heart of Brazilian dairy country. The heifers entered the trial at roughly two and a half years of age with an average body weight of 563 kilograms. None were inseminated during the study, a deliberate design choice that removed pregnancy as a confounding factor and allowed the researchers to isolate how lactation itself reshapes the animal’s energy economy. The cows were housed in a free-stall barn equipped with electronic feed bins and automated weighing platforms, so that every kilogram of feed consumed and every fluctuation in body weight was captured in real time.

The animals received a total mixed ration based on corn silage, chopped hay, soybean meal, ground corn, urea, and minerals, reformulated at each of three lactation stages so that the roughage-to-concentrate ratio shifted from 62:38 in early lactation to 81:19 by late lactation. The diet supplied on average 18.41 megajoules of gross energy per kilogram of dry matter. Measuring what happened to that energy required an unusually demanding experimental battery: six total-tract digestibility trials, in which feces were collected completely over five consecutive days and urine was sampled by spot collections; and respirometry sessions in open-circuit respiration chambers, where cows spent 22-hour periods under thermoneutral conditions while oxygen consumption, carbon dioxide production, and methane output were quantified. From these measurements the team calculated digestible energy intake, metabolizable energy intake, heat production, and ultimately the full energy balance of each cow.

The headline finding is that these animals are, metabolically speaking, unusually comfortable dairy cows. Milk yield averaged 16.1 kilograms per day, with fat-corrected yield at 18.4 kilograms, moderate figures by Holstein standards but achieved with striking stability. Dry matter intake held nearly flat across the lactation, drifting only from 15.7 kilograms per day in early lactation to 14.7 in late lactation. Digestible and metabolizable energy intakes likewise barely moved, hovering near 180 and 150 megajoules per day respectively. In contrast to the dramatic metabolic rollercoaster familiar from high-producing Holsteins, the F1 crossbreds simply never fell into a deep or prolonged energy deficit. Their energy balance dipped to only about −12.9 megajoules per day in the earliest stage and turned positive, reaching +8.8 megajoules per day, once cows reached mid-lactation.

That short negative phase is arguably the study’s most consequential result. In purebred Holsteins selected for extreme yields, the weeks after calving typically bring a punishing gap between the energy poured into milk and the energy the cow can physically consume, forcing the animal to mobilize body reserves and predisposing her to ketosis, impaired fertility, and other transition disorders. The F1 cows in this study resolved their negative balance within roughly two to three weeks postpartum. The authors attribute this resilience to the combination of moderate milk output, stable intake, and a genetic predisposition toward fat storage inherited partly from the zebu side. Bos indicus cattle and their crosses deposit proportionally more subcutaneous fat, whereas Holsteins accumulate visceral fat and channel nutrients preferentially into the mammary gland, leaving pure Holsteins metabolically far more vulnerable in early lactation.

Body condition data reinforced this picture. The cows averaged a body condition score of 3.7 on the five-point scale just two weeks after calving, climbed to 4.2 by fifteen weeks, and settled at 4.4 by week twenty-eight—a whole-lactation average of 4.1. Body weight rose steadily from around 592 kilograms in early lactation to 695 kilograms in late lactation, with the animals reaching about 726 kilograms at forty-two weeks in milk. Because the heifers had calved at roughly 78 percent of their hypothetical mature weight at thirty months, the researchers conclude that these animals grew faster than the average Brazilian Girolando herd, likely reflecting the standardized genetics and intensive rearing nutrition applied from calfhood onward. Still growing while lactating, they were effectively funding two demanding biological projects simultaneously without apparent metabolic strain.

The partitioning of dietary energy reveals where the calories went. Heat production was the single largest expenditure, consuming 34.1 percent of gross energy intake, with cows losing between 96.1 and 89.0 megajoules per day as heat across the three stages. Fecal energy losses came a close second at 33.2 percent, a figure that reflects the substantial roughage content of the rations, while urinary losses remained a minor and remarkably constant 3.4 megajoules per day. Energy retained in milk accounted for 20 percent of gross intake, declining from 61.2 megajoules per day in early lactation to 46.0 in late lactation as milk yield fell. Notably, and counter to what has been reported for Holsteins, both heat and methane losses declined rather than rose from early to late lactation in these crossbreds, most likely because energy intake itself tapered alongside the falling concentrate proportion of the diet.

The methane numbers carry implications well beyond cattle nutrition. Enteric methane represented 7.6 percent of gross energy intake—a methane conversion factor about one percentage point above the 6.5 percent default that the Intergovernmental Panel on Climate Change assigns to cattle and buffalo. In absolute terms, methane energy losses fell from 22.8 megajoules per day in early lactation to 18.6 in late lactation. The authors urge caution in generalizing the figure, since fiber fractions and feeding level strongly influence rumen passage rate and thus methanogenesis, and their diets contained only about half the concentrate of some comparison studies. Indeed, crossbred cows in comparable trials lost more energy as methane than Holsteins or Jerseys on high-concentrate rations. Still, with livestock methane under intensifying scrutiny as a greenhouse gas, the data identify a concrete research target: understanding and mitigating methane conversion in F1 and other Girolando compositions under tropical feeding systems.

Milk composition adds another dimension to the crossbred’s commercial case. The cows produced milk with an average fat content of 4.66 percent and protein of 3.57 percent, sitting at the upper end of published ranges for Girolando animals and above the breed averages of roughly 3.9 and 3.3 percent. Since pure Holsteins typically produce a larger but skimmer volume, the solids-rich F1 milk can counterbalance the yield gap, particularly attractive for producers diversifying into cheese and other dairy products. Feed efficiency told a similar intermediate story: cows converted each kilogram of dry matter into 1.16 kilograms of milk in early lactation, declining to 0.93 by late lactation, with an overall lactation figure near 1.05—better than Gyr, below elite Holstein, and potentially convergent with both when nutrient availability is not limiting.

Taken together, the study delivers a persuasive argument that F1 Holstein × Gyr cows are a viable and physiologically sustainable option for confined tropical milk production, combining heat tolerance and intake stability with acceptable yields and unusually gentle metabolic transitions. The authors are careful to note the caveats: the favorable energy balance reflects not only genotype but also excellent nutrition and a comparatively late age at first calving, and the pronounced tendency toward over-conditioning in mid-to-late lactation demands careful dietary energy control before subsequent calvings. They also emphasize that comparable measurements under grazing conditions—where most tropical F1 cows actually live—are essential next steps. But as a metabolic portrait of the cow that milks Brazil, the data finally fill in the energy ledger, showing precisely how a hybrid animal manages to give milk, gain weight, stay cool, and recover from calving faster than either of its parent breeds could alone.

Subject of Research: Energy metabolism and partitioning in primiparous F1 Holstein × Gyr dairy cows throughout lactation

Article Title: Unveiling the energy metabolism of primiparous F1 Holstein × Gyr cows throughout lactation

Article References: da Silva, C. S., Rodrigues, J. P. P., Sacramento, J. P., Coelho, S. G., & Campos, M. M. (2026). Unveiling the energy metabolism of primiparous F1 Holstein × Gyr cows throughout lactation. Discover Agriculture, 4(1), Article 296. https://doi.org/10.1007/s44279-026-00774-2

Image Credits: AI Generated

DOI: 10.1007/s44279-026-00774-2

Keywords: dairy cattle, Holstein, Gyr, Girolando, energy metabolism, lactation, tropical agriculture, methane emissions, body condition, feed efficiency, crossbreeding, respirometry