A multi-lactation genetic analysis of South African Holstein dairy cattle has demonstrated that lactation persistency behaves as a distinctly different genetic trait depending on whether herds are managed on pasture or fed total mixed rations. Published in Genetics Selection Evolution, the study investigated milk production records to examine how environmental differences influence the expression of breeding merit. While the general production level of cows demonstrated consistent genetic merit across both management systems, persistency showed substantial genotype-by-environment interaction. The authors concluded that national genetic evaluations must treat persistency across distinct management environments as separate traits to prevent misranking of breeding sires.<\/p>\n
Dairy farming across South Africa takes place in varied environments encompassing thirteen distinct climatic zones according to the K\u00f6ppen-Geiger classification system. Commercial dairy production in the country is broadly separated into total mixed ration systems, which are typically concentrated in more arid or semi-arid zones, and pasture-based grazing systems, which are situated primarily in regions with higher average annual rainfall. Previous investigations evaluating genotype-by-environment interactions using traditional 305-day cumulative lactation records had failed to identify significant interactions for milk yield. However, researchers noted that summarizing an entire lactation into a single cumulative measurement inherently obscures the trajectory of the lactation curve, preventing geneticists from distinguishing between a cow’s general production level and her persistency throughout lactation.<\/p>\n
To overcome the limitations of cumulative lactation metrics, the research team implemented an alternative random regression animal model using individual test-day records collected between 1988 and 2016. The dataset, provided by the South African Holstein Cattle Breeders\u2019 Society, comprised 2,310,430 test-day records prior to strict quality control edits. Cows were required to have valid calving dates, known sires, and milk recording in their first three lactations. To accurately capture lactation persistency, lactations required at least seven test-day records spanning between 6 and 300 days in milk, with the first test occurring within the initial 65 days in milk. Lactations with testing intervals of 100 days or longer were discarded, allowing no more than one interval between 70 and 100 days per lactation.<\/p>\n
Following quality control filtering, the final analytical dataset consisted of 74 herds encompassing 571,236 test-day records under total mixed ration management, and 22 herds with 215,592 test-day records under pasture management. A total of 1,221 sires were represented in the data, with 53 percent originating from North American lineages across both management types. A shared cohort of 711 sires had recorded progeny in both production systems, including 454 sires that had at least five recorded daughters in first lactation within each system, and 168 highly influential sires having at least twenty daughters per system. The complete pedigree dataset included 123,082 animals spanning approximately 15 ancestral generations, forming the relationship matrix used in the mixed model equations.<\/p>\n
The statistical framework employed restricted maximum likelihood methods implemented in the Wombat software package. The researchers fitted a multi-lactation random regression model that separately analyzed milk, fat, and protein production across the first three lactations while accounting for both additive genetic and permanent environmental random effects. Fixed effects included contemporary groups defined by herd, test date, and milking frequency, alongside nested effects combining herd, calving year, calving season, and lactation. The modeling of days in milk utilized natural cubic splines with six knots at days 6, 20, 50, 135, 245, and 300, which provided a statistically superior fit compared to Legendre polynomials of orders four through six based on Bayesian Information Criterion evaluations.<\/p>\n
The random regression model dissociated the additive genetic effect into two orthogonal components per lactation: an intercept representing the general genetic production level across the centered lactation trajectory, and a linear slope representing genetic persistency from day 6 to day 300 in milk. Because test-day records from total mixed ration and pasture herds were treated as genetically distinct traits in a twelve-component additive genetic covariance matrix, the analysis directly estimated the genetic correlations between environments for both production level and persistency across all three lactations, as well as the resulting changes in sire breeding value ranks.<\/p>\n
The variance component analysis revealed striking contrasts between the two production regimes. Across all three lactations, the additive genetic variance for total milk production was substantially higher in total mixed ration herds than in pasture herds, diverging increasingly toward the end of lactation. By the end of the first and second lactations, genetic variance in the total mixed ration environment was 42 percent and 50 percent higher, respectively, than in pasture herds. The authors explained that environmental variances indicate total mixed rations offer a more optimal production system than pasture, in which animals are better able to express their full genetic merit.<\/p>\n
Conversely, heritability estimates for total milk yield across all lactations were consistently higher in pasture herds than in total mixed ration herds. In the first lactation, pasture heritability averaged 0.27 compared to 0.18 for total mixed ration cows, with similar patterns appearing in second lactation (0.24 versus 0.15) and third lactation (0.24 versus 0.14). This divergence occurred because permanent environmental variance ratios were considerably higher in total mixed ration herds. The authors attributed this pattern to individualized nutritional management, wherein cows in total mixed ration herds are fed concentrates corresponding to their daily yield during early lactation, confounding permanent environmental effects with underlying additive genetics.<\/p>\n
The estimated genetic correlations between the two production systems demonstrated a marked divergence between production volume and lactation persistency. For general genetic production level, correlations between total mixed ration and pasture systems remained exceptionally high across all three lactations, ranging between 0.83 and 0.93. These strong correlations demonstrate that the genes governing overall milk volume function similarly across different feeding environments. In stark contrast, genetic correlations for the linear persistency slope between pasture and total mixed ration systems were moderate to weak, ranging from 0.40 to 0.60 across lactations, with values of 0.55, 0.54, and 0.48 for milk in lactations one through three.<\/p>\n
Because the genetic correlations for persistency fell significantly below the conventional biological threshold of 0.80, the findings confirm that persistency is governed by different genetic mechanisms across management systems. Consequently, significant reranking of breeding sires occurred. When evaluating the top 30 percent of sires for persistency in pasture systems, only 24 percent remained in the top 30 percent when evaluated in total mixed ration systems for first-lactation milk yield. By comparison, 95 percent of top sires for production level remained superior across both systems. The authors concluded that dairy breeding programs should implement multi-trait evaluations that publish separate estimated breeding values for persistency across individual production systems.<\/p>\n
Examining the separate heritability estimates for the model\u2019s two underlying components revealed distinctive developmental trajectories between production level and persistency. In the first lactation, heritability for general production level reached 0.20 for milk, 0.17 for protein, and 0.10 for fat in the total mixed ration system, compared to higher pasture values of 0.28, 0.22, and 0.17, respectively. In contrast, first-lactation persistency heritabilities were considerably lower, spanning 0.04 to 0.07 in total mixed rations and 0.06 to 0.11 on pasture. However, as cows matured into second and third lactations, persistency heritabilities rose markedly to between 0.08 and 0.18 under total mixed rations and 0.10 to 0.21 on pasture. This increase was driven by a substantial surge in additive genetic variance for persistency, which climbed by more than 200 to 400 percent in later lactations, indicating that genetic differences in sustaining milk yield become much more pronounced as cows age.<\/p>\n
The model also demonstrated that general production level and lactation persistency are genetically independent traits. Genetic correlations between the two components within each feeding environment ranged from negative 0.52 to 0.06, while cross-environment correlations between production level and persistency ranged from negative 0.47 to 0.09, frequently remaining indistinguishable from zero. This genetic independence allows dairy producers to select for lactation persistency without compromising overall milk volume. When evaluating total breeding value, which combines both components, sire rank correlations between systems dropped to 0.78 in first lactation, 0.64 in second, and 0.51 in third for milk. Consequently, the genotype-by-environment interaction in persistency caused notable sire reranking for overall production, with only 83 percent of sires superior on pasture maintaining superior status in total mixed rations.<\/p>\n
Cross-lactation comparisons further highlighted complex dynamics between environments. Persistency during first lactation in total mixed ration herds showed moderate genetic correlations with pasture persistency in later lactations, registering 0.44 to 0.46 for milk and exceeding 0.60 for fat and protein. By contrast, first-lactation pasture persistency exhibited weak correlations of negative 0.19 to 0.07 with subsequent pasture lactations.<\/p>\n
These biological differences carry direct practical implications for commercial breeding strategies and national genetic evaluations. The researchers emphasized that joint multi-trait evaluations analyzing both management systems together offer major advantages over isolated single-system models. By incorporating the non-zero genetic covariance across environments, multi-trait models utilize baseline merit across shared sires, substantially increasing breeding value reliability when daughter distributions are unbalanced between systems. Furthermore, because pasture herds require cows capable of producing across 2.5 seasons in extensive environments, selection indices on pasture should emphasize persistency and resilience, whereas intensive herds benefit primarily through favorable responses in animal health.<\/p>\n
Subject of Research: Genotype-by-environment interactions in dairy cattle breeding under different management systems<\/p>\n
Article Title: Genotype by environment interaction under two production systems utilizing a random regression model for milk production traits in multiparous South African Holstein dairy cattle<\/p>\n
Article References: Van Niekerk, M., Neser, F. W. C., Van Wyk, J. B., & Ducrocq, V. (2026). Genotype by environment interaction under two production systems utilizing a random regression model for milk production traits in multiparous South African Holstein dairy cattle. Genetics Selection Evolution, 58(1), Article 78. https:\/\/doi.org\/10.1186\/s12711-026-01098-x<\/a><\/p>\n Image Credits: AI Generated<\/p>\n