How genotype-environment interaction is reshaping dairy farming in tropical climates
In the heart of Sri Lanka's tropical lowlands, a quiet revolution is unfolding in dairy farming. Imagine a Jersey cow, bred for generations in temperate Australia, now standing in the sweltering heat of Sri Lanka, where the average temperature hovers around 27 degrees Celsius and humidity reaches 80%. This isn't just a change of scenery—it's an environmental shock that rewrites the very expression of her genetic potential for milk production 1 .
For decades, Sri Lanka has struggled with milk self-sufficiency, importing approximately 100,000 metric tonnes of milk products as recently as 2016. To address this, the government initiated programs to import temperate dairy cattle, primarily Jersey and Jersey-Friesian crosses from Australia 1 . But a critical question emerged: would these animals, selectively bred for performance in temperate climates, maintain their genetic advantages in Sri Lanka's challenging tropical environment?
This article explores how scientists are decoding the genetic parameters of first lactation Jersey cows in Sri Lanka—research that could hold the key to developing a truly adapted dairy breed capable of thriving in tropical conditions while supporting the nation's dairy independence.
Heritability represents the proportion of observable differences in a trait (like milk yield) that can be attributed to genetic differences rather than environmental factors. Measured on a scale from 0 to 1, higher values indicate that genetics play a stronger role in determining the trait 1 7 .
This concept explains how the same genetics can express differently across various environments. A high-producing cow in Australia may perform poorly in Sri Lanka not because her genes changed, but because environmental stressors like heat, humidity, and different feed resources alter how those genes are expressed 1 .
The following table illustrates how heritability estimates for milk yield vary across different environments:
| Location | Breed | Heritability Estimate | Environmental Context |
|---|---|---|---|
| Sri Lanka 1 | Jersey | 0.08 ± 0.03 | Tropical low-country |
| Sri Lanka 1 | Jersey-Friesian | 0.02 ± 0.01 | Tropical low-country |
| Zimbabwe 7 | Jersey | 0.30 | Tropical savannah |
| Florida 2 | Jersey | 0.27-0.43 | Subtropical |
The weak correlation between Australian bull breeding values and their actual performance in Sri Lanka (0.39 for Jerseys and -0.35 for Jersey-Friesians) clearly demonstrates this phenomenon 1 . Essentially, sire differences expressed in Australia weren't reliably reproduced in Sri Lanka's tropical conditions.
In a meticulously designed study conducted from 2015 to 2018, researchers tracked first lactation performance of imported Jersey and Jersey-Friesian cows in an intensively managed commercial farm in Sri Lanka's low-country region 1 .
They gathered 904,437 daily milk records from 2,434 Jersey and Jersey-Friesian crossbred cows during their first lactation, using automated monitoring systems in a DeLaval milking parlor 1 .
Scientists defined multiple traits for analysis, including predicted 305-day milk yield (using Wood's model and multiple trait prediction methods), realized 305-day milk yield (actual cumulative yield), and daily milk yields as a longitudinal trait 1 .
Researchers employed univariate animal models for 305-day yield traits and random regression models using second-order Legendre polynomials for daily milk yields, accounting for heterogeneous residual variances across lactation stages 1 .
The team implemented rigorous editing procedures, removing records beyond 350 days postpartum, outliers exceeding four standard deviations, and ensuring minimum data density for reliable parameter estimation 1 .
The analysis yielded surprising results that challenged conventional dairy breeding wisdom:
The heritability of predicted 305-day milk yield in first lactation was significantly low—0.08 for Jersey cows and just 0.02 for Jersey-Friesian crosses. These values are substantially lower than typical estimates from temperate regions or even other tropical areas like Zimbabwe 1 7 .
When examining daily milk yields throughout the lactation, heritability estimates varied considerably, ranging from as low as 0.002 to 0.19 depending on the day of milk, revealing how genetic influences on production change throughout the lactation cycle 1 .
The correlation between Australian bull breeding values and their actual performance in Sri Lanka was moderate for Jerseys (0.39) and negative for Jersey-Friesian crosses (-0.35), indicating that selection based on Australian genetic evaluations would be inefficient for the Sri Lankan context 1 .
| Lactation | Jersey Heritability | Jersey-Friesian Heritability | Sample Size (Cows) |
|---|---|---|---|
| First 1 | 0.08 ± 0.03 | 0.02 ± 0.01 | 2,372 |
| Second 1 | Similar to first lactation | Similar to first lactation | 1,905 |
Modern genetic research on dairy cattle relies on sophisticated methodological tools that enable precise parameter estimation:
These statistical models fit polynomial curves to daily milk records, allowing researchers to estimate how genetic influences change throughout the lactation trajectory 1 .
Advanced milking systems that automatically record yield data at each milking session, generating extensive daily milk records 1 .
Mathematical functions used in random regression models to describe the shape of lactation curves and how genetic parameters fluctuate 1 .
The revelation that imported genetics perform differently in Sri Lanka's tropical environment has transformative implications for the country's dairy development strategy.
The low heritability estimates and weak correlation with international breeding values underscore the critical need for within-country genetic evaluation programs 1 .
This research highlights the potential of advanced monitoring technologies in genetic improvement. Automated milking parlours can generate the dense phenotypic data needed for accurate genetic parameter estimation 1 .
The findings suggest opportunities for strategic crossbreeding that incorporates thermotolerant genetics from indigenous cattle populations 3 .
Rather than continuing to depend on imported semen and live animals based on temperate performance metrics, Sri Lanka would benefit more from developing localized breeding values that account for genotype-environment interactions 1 .
The investigation into genetic parameters of first lactation Jersey cows in Sri Lanka represents more than academic interest—it's a practical roadmap for developing a sustainable dairy industry in tropical environments. The key insight is unmistakable: successful genetic improvement must account for the complex interplay between genetics and environment.
As Sri Lanka works toward milk self-sufficiency, the foundation for progress will likely involve establishing robust within-country genetic evaluation systems, potentially incorporating thermotolerant traits from indigenous cattle, and leveraging technology for precise data collection.
The journey of the humble Jersey cow in Sri Lanka's heat ultimately illuminates a broader truth: in animal breeding, context matters just as much as genetics. By respecting this principle, tropical nations can develop dairy industries that are both productive and sustainable, turning genetic challenges into opportunities for innovation.