BREEDER’S BLOG

“Heritability Scores in Breeding: Practical Benefits, Realities and Misconceptions “

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Practical Benefits of using Heritability Scores

Heritability scores offer significant benefits in plant breeding, helping breeders make informed decisions, yet breeding misconceptions often lead to missed opportunities and errors. This post explores the true value of heritability, clears up common misunderstandings, and provides practical insights to refine your selection strategies and maximize genetic progress.

Check out the infographic below to see the top five benefits of using heritability in plant breeding


Five Common Misconceptions About Heritability in Breeding

We have seen previously that breeders can benefit from calculating and using  heritability values when deciding their breeding strategy. However,  they misunderstand the concept of heritabilityin some cases, leading to inefficient selection strategies. Here, we debunk five common misconceptions about heritability and its application in breeding programs.

Heritability is not an absolute value; it varies depending on the population, environment, and management conditions. A trait with high heritability in one environment may show lower heritability in another due to different environmental influences or less efficient phenotyping protocols. 

For example, if breeders evaluate resistance  to a disease caused by natural conditions, they run the risk of characterising sensitive genotypes as resistant if the infection rate is low. But if they inoculate the plants artificially with the pathogen of interest, they ensure higher infection rates and less errors in classifying the plants as sensitive or resistant.

The heritability of a trait can change depending on the environment, the population and the management conditions. 

We often consider traits with low heritability difficult to improve, leading to disregard them in selection programs. But, as we mentioned before, heritability is not a static value; breeders can improve it by integrating different strategies in their programmes, like using standardized phenotyping protocols, experimental designs to reduce the effect of the environment  and larger population sizes.

A good example of improving heritability is to use molecular markers for selecting the plants with the desirable genotype. Marker-assisted selection (MAS) targets specific genomic regions associated with the desired characteristics. So, it turns out to be more reliable than standardized phenotyping protocols because changes in the environmental do not affect the gnetic markers, ensuring consistent and accurate selection across different conditions.

Many breeders assume that if a trait has high heritability, improving it will be an easy and rapid task. However, heritability only reflects the proportion of trait variation due to genetic factors in a specific population and environment. If selection intensity is low or genetic variation is limited, progress may still be slow. High heritability does not replace the need for strategic selection and population management.

Consider plant height in wheat, which often has high heritability (e.g., 80%). A breeder aiming to develop shorter wheat varieties for lodging resistance might assume that selection will quickly reduce plant height. However, despite the high heritability, genetic progress could be slow if:

  • Limited Genetic Variation: If the breeding population already consists of mostly short plants, there may not be enough genetic variation to make further improvements.
  • Low Selection Intensity: If breeders apply only mild selection pressure (e.g., keeping many taller plants in the breeding pool), genetic gain per cycle will be minimal.
  • Environmental Factors: Even with high heritability, soil fertility or water availability can still influence plant height, requiring multi-environment trials to ensure stable selection.

This example highlights why high heritability alone does not guarantee rapid progress—effective selection strategies and sufficient genetic diversity are essential for achieving breeding goals.

Heritability is a population-level statistic and does not predict the genetic potential of a single individual. It describes the proportion of observed variation that is genetic within a given population, not the likelihood that an individual will pass on a trait. Breeders should interpret heritability in the context of population-wide selection rather than as a measure of individual performance.

Consider fruit weight in tomato, which often has moderate to high heritability (e.g., 60–70%). A breeder might assume that selecting a single plant with large fruits will ensure that its offspring also produce large fruits. However, this is a misunderstanding of heritability:

  • Population-Level Measure: A heritability of 70% means that 70% of the variation in fruit weight within the tested population is due to genetic factors, not that a specific plant will reliably pass on its large fruit size to its progeny.
  • Influence of Other Factors: Environmental conditions (soil nutrients, water availability, temperature) and random genetic recombination also affect fruit size, meaning offspring from the selected plant may not consistently produce large fruits.
  • Breeding Program Perspective: Effective selection should be based on replicated trials, statistical analysis (e.g., BLUP), and multi-generation selection, rather than choosing a single standout plant.

This example highlights why breeders should be interprete heritability at the population level, guiding selection strategies rather than predicting individual plant performance.

A common misconception is that a high heritability value indicates the presence of a major-effect QTL (quantitative trait locus) controlling the trait. However, heritability simply quantifies how much of the observed variation in a trait is due to genetic factors within a specific population and environment—it does not reveal the number or effect size of the underlying genes. A trait controlled by a single major QTL can have low heritability if there is little variation in the population being studied. 

For example, eye color in a population where most individuals have the same color will show low heritability, despite being largely determined by a few genes. Conversely, highly polygenic traits, such as grain yield in wheat, can exhibit high heritability if the experiment is well-designed, with proper replication and minimal environmental noise. However, the same trait can show low heritability if poor agronomic management introduces excessive environmental variability, masking genetic differences. This highlights the importance of experimental design and population structure in interpreting heritability rather than assuming it reflects the genetic architecture of a trait.

Check out the infographic below to see the top five misconceptions about heritability in plant breeding

Final Thoughts

Understanding heritability correctly is crucial for maximizing genetic gains in breeding programs. By avoiding these misconceptions, breeders can make more informed decisions, optimize selection strategies, and improve the efficiency of their breeding efforts.

At AgroSynapsis, we help breeders apply statistical tools and molecular techniques to enhance trait selection. If you’re interested in optimizing your breeding program, contact us to learn more about our heritability analysis services!