Blueberry consumption is rising worldwide, with demand not only for flavor but also for fruits that remain firm during storage and transport. Texture—how a berry feels when eaten—affects consumer appeal and postharvest quality, yet traditional evaluations are laborious and limited.
New tools for measuring multiple firmness traits now offer breeders deeper insights, making it crucial to understand the genetic basis of blueberry texture to improve both quality and longevity.
Figure 1. Genomic prediction of texture-related traits in blueberry. (a) Scenarios of cross-validation tested in Northern (NHB) and Southern (SHB) highbush blueberries from Oregon and Florida States, respectively; (b) Genomic heritability for 17 texture traits evaluated in NHB and SHB; (c) Predictive ability measured as the Person’s correlation between predicted and observed phenotypic values for inter and intra-population validation scenarios.
Genetic analysis and methodology
A study published on August 21, 2024, in Horticulture Research (DOI: 10.1093/hr/uhae233) brought together researchers from the University of Florida, NC State University, USDA-ARS, and global partners.
They analyzed 2,289 northern (NHB) and southern (SHB) highbush blueberry genotypes with advanced genotyping and texture profiling to uncover key traits and genetic markers. Their work combined mapping of candidate genes with predictive genomic modeling to support future breeding strategies.
Key traits and genetic markers
Seventeen texture-related traits—including stiffness, puncture force, and burst strain—were measured across large breeding populations. Results highlighted clear textural differences between NHB and SHB, with parameters such as YM20_BuStr and burst strain being particularly discriminant.
Genome-wide association studies identified over 100 regions linked to texture, including hotspots on chromosomes 5 and 7, with candidate genes like XTH, PME, and PEL pointing to roles in cell wall composition and fruit softening.
Implications for breeding
Heritability estimates were generally low to moderate, reflecting a polygenic basis, yet genomic prediction models achieved moderate accuracy, especially in SHB lines.
Importantly, evaluating just 10 berries per genotype proved efficient and reliable. According to lead author Dr. Patricio R. Munoz, integrating texture profiling with genomic tools offers breeders a powerful approach to select for firmness and storability earlier in the cycle.
These findings not only accelerate blueberry improvement but also provide a roadmap for addressing texture challenges in other fruit crops.
Source: academic.oup.com
