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Towards smart and sustainable development of modern berry cultivars in Europe

Senger, Elisa, Osorio, Sonia, Olbricht, Klaus, Shaw, Paul, Denoyes, Beatrice, Davik, Jahn, Predieri, Stefano, Karhu, Saila, Raubach, Sebastian, Lippi, Nico, and others. (2022) Towards smart and sustainable development of modern berry cultivars in Europe. The Plant Journal, . ISSN 0960-7412. (doi:10.1111/tpj.15876) (KAR id:96191)

Abstract

Fresh berries are a popular and important component of the human diet. The demand for high-quality berries and sustainable production methods is increasing globally, challenging breeders to develop modern berry cultivars that fulfill all desired characteristics. Since 1994, research projects have characterized genetic resources, developed modern tools for high-throughput screening, and published data in publicly available repositories. However, the key findings of different disciplines are rarely linked together, and only a limited range of traits and genotypes has been investigated. The Horizon2020 project BreedingValue will address these challenges by studying a broader panel of strawberry, raspberry and blueberry genotypes in detail, in order to recover the lost genetic diversity that has limited the aroma and flavor intensity of recent cultivars. We will combine metabolic analysis with sensory panel tests and surveys to identify the key components of taste, flavor and aroma in berries across Europe, leading to a high-resolution map of quality requirements for future berry cultivars. Traits linked to berry yields and the effect of environmental stress will be investigated using modern image analysis methods and modeling. We will also use genetic analysis to determine the genetic basis of complex traits for the development and optimization of modern breeding technologies, such as molecular marker arrays, genomic selection and genome-wide association studies. Finally, the results, raw data and metadata will be made publicly available on the open platform Germinate in order to meet FAIR data principles and provide the basis for sustainable research in the future.

Item Type: Article
DOI/Identification number: 10.1111/tpj.15876
Uncontrolled keywords: berry breeding, trait/genotype association, genomics, metabolomics, image analysis, consumer preference, plant genetic resources, BreedingValue project
Subjects: Q Science
Q Science > QK Botany
S Agriculture
Divisions: Divisions > Division of Natural Sciences > Biosciences
Depositing User: Helen Cockerton
Date Deposited: 12 Aug 2022 16:48 UTC
Last Modified: 15 Aug 2022 09:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/96191 (The current URI for this page, for reference purposes)

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