Productive and reproductive trends in primiparous Holstein cows: longitudinal and multivariate analysis in an Argentine grazing system (1994–2023)
DOI:
https://doi.org/10.30972/vet.3719154Keywords:
genotype, environment interaction, milk yield, calving interval, grazing systems, multivariate analysisAbstract
The Holstein breed constitutes the predominant genetic base in intensive and pasture-based dairy systems worldwide. The objective of this study was to characterize productive trends and calving interval in primiparous Holstein cows managed in an Argentine grazing system from 1994 to 2023; to evaluate the joint structure of these traits through multivariate analysis; and to detect potential structural changes associated with modifications on the production system, interpreting the results within the conceptual framework of genotype × environment interaction. Retrospective data from 93 primiparous Holstein cows of the American–Canadian biotype, calved in autumn between 1994 and 2023, were analyzed. The animals belonged to a Holstein dairy farm located in Casilda, Santa Fe province, Argentina. Milk production (MP305) and butterfat production (BP305) adjusted to 305 days showed a sustained increase over the study period, accompanied by a moderate increase in interindividual variability. Days in milk (DIM) increased progressively, although to a lesser extent, whereas calving interval (CI) did not show significant changes in linear models. Correlation analysis revealed a strong association between MP305 and BP305 (r = 0.881; p<0.001). DIM was moderately correlated with productive traits and strongly associated with CI (p<0.001). Principal component analysis explained 89.8% of the total variance: PC1 (58.8%) was primarily associated with productive variables (MP305, BP305, DIM), whereas PC2 (31.0%) was mainly associated with CI. The findings indicate that optimization of the grazing environment may represent a key factor for improving performance in primiparous Holstein cows. Furthermore, longitudinal and multivariate approaches provide useful tools for identifying system-level factors influencing phenotypic expression.
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