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Understanding the genetic basis of blueberry postharvest traits to define better breeding strategies.

Authors :
Casorzo, Gonzalo
Ferrão, Luis Felipe
Adunola, Paul
Flores, Estefania Tavares
Azevedo, Camila
Amadeu, Rodrigo
Munoz, Patricio R
Source :
G3: Genes | Genomes | Genetics. Sep2024, Vol. 14 Issue 9, p1-12. 12p.
Publication Year :
2024

Abstract

Blueberry (Vaccinium spp.) is among the most-consumed soft fruit and has been recognized as an important source of health-promoting compounds. Highly perishable and susceptible to rapid spoilage due to fruit softening and decay during postharvest storage, modern breeding programs are looking to maximize the quality and extend the market life of fresh blueberries. However, it is uncertain how genetically controlled postharvest quality traits are in blueberries. This study aimed to investigate the prediction ability and the genetic basis of the main fruit quality traits affected during blueberry postharvest to create breeding strategies for developing cultivars with an extended shelf life. To achieve this goal, we carried out target genotyping in a breeding population of 588 individuals and evaluated several fruit quality traits after 1 day, 1 week, 3 weeks, and 7 weeks of postharvest storage at 1°C. Using longitudinal genome-based methods, we estimated genetic parameters and predicted unobserved phenotypes. Our results showed large diversity, moderate heritability, and consistent predictive accuracies along the postharvest storage for most of the traits. Regarding the fruit quality, firmness showed the largest variation during postharvest storage, with a surprising number of genotypes maintaining or increasing their firmness, even after 7 weeks of cold storage. Our results suggest that we can effectively improve the blueberry postharvest quality through breeding and use genomic prediction to maximize the genetic gains in the long term. We also emphasize the potential of using longitudinal genomic prediction models to predict the fruit quality at extended postharvest periods by integrating known phenotypic data from harvest. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21601836
Volume :
14
Issue :
9
Database :
Academic Search Index
Journal :
G3: Genes | Genomes | Genetics
Publication Type :
Academic Journal
Accession number :
179691265
Full Text :
https://doi.org/10.1093/g3journal/jkae163