Development of a Novel Phenotypic Roadmap to Improve Blueberry Quality and Storability.

Abstract

Improved fruit quality and prolonged storage capability are key breeding traits for blueberry ( Vaccinium spp.) fruit. Until now, breeding selection was mostly oriented on the amelioration of agronomic traits, such as flowering time, chilling requirement, or plant structure. Up until now, however, the storage effect on fruit quality has not been extensively studied, mostly because objective and handy phenotyping tools to evaluate quality traits were not available. In this study we are proposing a novel phenotyping protocol to support breeding selection and quality control within the entire blueberry production chain. Volatile organic compounds (VOCs) and texture traits, were measured by Proton Transfer Reaction- Time of Flight- Mass Spectrometry (PTR-ToF-MS) and a texture analyzer respectively, taking into consideration the influence of prolonged storage. The exploitation of the genetic variability existing within the investigated blueberry germplasm collection (including both southern and northern highbush, hybrids, and rabbiteyes) allowed the identification of the best performing cultivars, based on texture and VOCs variability, to be used as superior parental lines for future breeding programs. The comprehensive characterization of blueberry aroma allowed the identification of a wide array of spectrometric features, mostly related to aldehydes, alcohols, terpenoids, and esters, that can be used as putative biomarkers to rapidly evaluate the blueberry aroma variations related to genetic differences and storability. In addition, this study revealed a lack of straightforward relationship between harvest and postharvest quality features, that might be genotype-dependent.

Plant phenotyping relevance

ブルーベリー果実の品質・貯蔵性を評価する新規フェノタイピングプロトコルを提案し、PTR-ToF-MSとテクスチャ解析を育種選抜・品質管理に適用しているため、表現型取得法が中心的です。

Code and data availability

The article describes texture and PTR-ToF-MS VOC phenotyping of 46 blueberry cultivars plus SSR-based genetic analysis, but no public phenotype dataset, image/sensor inputs, author code repository, or trained model is deposited or linked. R packages (Adegenet, Poppr, mixOmics, etc.) are generic libraries, and the SSR/m

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