Influence of stud farm, birth month and birth year on body weight of thoroughbred foals raised on pasture in Argentina: A 10-year longitudinal study.

This 10-year study of 2,408 Thoroughbred foals raised on pasture in Argentina found that where a foal is raised (stud farm) and when it is born (birth month) meaningfully influence its body weight at 18 months. The farm effect was largest, with a roughly 26 kg gap between the lightest and heaviest farms, highlighting the impact of farm-specific management and environmental conditions.

What the researchers asked and why it matters

• Question: How do stud farm, birth month, and birth year influence the body weight of Thoroughbred foals raised under pastoral (pasture-based) management?
• Rationale: Growth during the first 18 months affects future athletic performance and economic value; in pasture systems, environmental and management differences may strongly shape growth trajectories.
• Relevance: Identifying which extrinsic factors most affect weight can guide targeted management to produce more consistent, optimal growth in foals.

Study design and data

• Population: 2,408 Thoroughbred foals (51% females, 49% males) from seven stud farms in Argentina’s Pampas region.
• Period: 10 consecutive years (2009–2018), enabling evaluation of inter-annual variability.
• Measurements: Body weight recorded from 5 to 19 months of age under pasture-based management.
• Standardization of outcome: The Brody growth model was fitted to each foal’s longitudinal weights to estimate a comparable 18-month body weight for every individual, minimizing bias from different weighing ages and schedules.
• Statistical analysis: A linear model (ANOVA framework) tested main effects of stud farm, birth month, and birth year, plus their interactions, on the estimated 18-month weight.

Key results

• Overall growth outcome: Mean estimated weight at 18 months was 452.38 kg with a standard deviation of 29.83 kg.
• Stud farm effect:
  • Largest contributor to variation among the tested factors.
  • Range across farms: approximately 26.4 kg difference between the lightest (444.5 kg) and heaviest (470.9 kg) farms at 18 months (~5.8% of the mean).
  • Implication: Management practices and local environmental conditions at the farm level substantially shape growth outcomes.
• Birth month effect:
  • Reported as statistically significant (exact p-value not provided in the abstract).
  • Implication: Seasonality at and after birth—such as forage availability/quality, temperature, rainfall, and parasite pressure—likely alters early-life growth windows with lasting effects detectable at 18 months.
• Birth year and interactions:
  • These were evaluated in the model; detailed significance levels are not provided in the abstract.
  • Year-to-year climatic variability (e.g., droughts, El Niño/La Niña) and management adjustments could contribute to between-cohort differences.

How to interpret the findings

• The prominence of the stud farm effect suggests that farm-specific factors—pasture management, supplementation strategies, stocking density, parasite control, weaning practices, and health protocols—can cumulatively shift 18-month body weight by a meaningful margin.
• The birth month effect, even after standardizing weight to the same age via the Brody model, indicates that early-life seasonal conditions imprint on growth trajectories in ways that are not fully “corrected” by age-standardization.
• Because the outcome was harmonized to 18 months, differences are less likely to be artifacts of weighing at different ages and more likely to reflect genuine differences in growth opportunity and management.

About the methods (Brody model and ANOVA)

• Brody growth model:
  • A commonly used sigmoidal growth function estimating asymptotic growth parameters and providing fitted weights at specific ages.
  • Strength: Uses each foal’s repeated measures to derive a robust 18-month estimate despite irregular measurement timing.
  • Assumption: The chosen model appropriately captures equine growth patterns in this age window; model misspecification could bias estimates.
• ANOVA (linear model) on estimated 18-month weight:
  • Treats farm, birth month, and birth year as fixed effects to partition variance in the standardized outcome.
  • Strength: Clear decomposition of variation attributable to each extrinsic factor and their interactions.
  • Consideration: Without random effects for farm or pedigree, estimates reflect observed farms and may not generalize to all farms; genetic clustering is not explicitly modeled.

Practical implications for breeders and managers

• Prioritize farm-level management:
  • Pasture planning: Match forage supply to foal and lactating mare demand; overseeding, fertilization, rotational grazing.
  • Nutritional buffering: Seasonal creep feed or targeted supplementation during pasture troughs (e.g., winter) to protect early growth.
  • Parasite control: Strategic deworming based on fecal egg counts aligned with seasonal risk.
  • Water, shade, and heat mitigation: Reduce heat stress during peak months to maintain intake and growth.
  • Weaning and grouping: Age-appropriate, low-stress weaning; minimize competition via appropriate stocking density and group composition.
• Use birth month strategically:
  • Align foaling with periods of improving pasture quality when feasible, or plan supplemental nutrition if foaling occurs before pasture peaks.
  • Monitor cohorts born in less favorable months more closely and intervene early to prevent cumulative growth deficits.
• Benchmarking and targets:
  • Use the reported mean (≈452 kg at 18 months) and between-farm spread (~26 kg) as reference points for auditing farm performance.
  • Track farm-specific 18-month weights annually to evaluate management changes and close gaps to top-performing farms.

What the study does not address directly

• Causality: As an observational analysis, it cannot definitively ascribe farm differences to specific practices without controlled interventions.
• Genetics and pedigree: Sire, dam, and familial effects are not explicitly modeled and could confound farm differences if breeding stock quality varies by farm.
• Sex differences: Although the cohort was ~50/50 female/male, the abstract does not report whether sex was included as a covariate; sex-related growth dimorphism might influence results if unevenly distributed across farms or months.
• Other growth dimensions: Body condition, height/withers growth, and musculoskeletal development are not captured by weight alone.
• Downstream outcomes: The analysis does not link 18-month weight to sale price, training soundness, or racing performance.

Limitations and potential sources of bias

• Farm sample: Only seven farms from one region; findings may not generalize to all pastoral systems or climates.
• Measurement variation: Potential differences in scales, weigh timing (e.g., post-feeding), and handling could add noise, though large sample size helps mitigate random error.
• Model choice: While appropriate for growth, the Brody model may fit some individuals better than others; sensitivity to alternative growth models (e.g., Gompertz, von Bertalanffy) is not reported.
• Unmeasured management variables: Supplementation protocols, disease events, and microclimate were not individually quantified in the abstract.

Recommendations for future research

• Augment models with:
  • Pedigree or genomic information to partition genetic vs. environmental variance.
  • Sex, dam age/parity, colostrum quality, and health events as covariates.
  • Objective pasture and climate metrics (forage biomass/quality, temperature-humidity index, rainfall).
• Explore interactions:
  • Farm-by-birth-month and farm-by-year interactions to detect season- or climate-specific management resilience.
  • Dose-response of supplementation or stocking density across seasons.
• Link growth to outcomes:
  • Prospective analyses associating early growth patterns with orthopedic health, sale prices, and performance metrics.
  • Economic evaluations to quantify return on investment for targeted management interventions.

Bottom line

• In pasture-based Thoroughbred systems, farm-specific management and seasonal timing of birth exert strong, lasting influences on 18-month body weight.
• Standardizing to an 18-month weight via growth modeling underscores that these are not mere timing artifacts but meaningful differences that farms can address through tailored management.