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.

Details

Title
Understanding the genetic basis of blueberry postharvest traits to define better breeding strategies
Author
Casorzo, Gonzalo 1   VIAFID ORCID Logo  ; Luis Felipe Ferrão 1   VIAFID ORCID Logo  ; Adunola, Paul 1 ; Estefania Tavares Flores 1 ; Azevedo, Camila 2 ; Amadeu, Rodrigo 1 ; Munoz, Patricio R 1   VIAFID ORCID Logo 

 Horticultural Sciences Department, University of Florida , Gainesville, FL 32608 , USA 
 Department of Statistics, Federal University of Viçosa , Viçosa 36570 , Brazil 
Publication year
2024
Publication date
Sep 2024
Publisher
Oxford University Press
e-ISSN
21601836
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3169700125
Copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.