High-throughput phenotyping for breeding targets - Current status and future directions of strawberry trait automation

James, Katherine Margaret Frances, Sargent, Daniel James, Whitehouse, Adam and Cielniak, Grzegorz (2022) High-throughput phenotyping for breeding targets - Current status and future directions of strawberry trait automation. Plants, People, Planet, 4 (5). pp. 432-443. ISSN 2572-2611

Full content URL: https://doi.org/10.1002/ppp3.10275

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High-throughput phenotyping for breeding targets—Currentstatus and future directions of strawberry trait automation
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Abstract

Automated image-based phenotyping has become widely accepted in crop phenotyping, particularly in cereal crops, yet few traits used by breeders in the strawberry industry have been automated. Early phenotypic assessment remains largely qualitative in this area since the manual phenotyping process is laborious and domain experts are constrained by time. Precision agriculture, facilitated by robotic technologies, is increasing in the strawberry industry, and the development of quantitative automated phenotyping methods is essential to ensure that breeding programs remain economically competitive. In this review, we investigate the external morphological traits relevant to the breeding of strawberries that have been automated and assess the potential for automation of traits that are still evaluated manually, highlighting challenges and limitations of the approaches used, particularly when applying high-throughput strawberry phenotyping in real-world environmental conditions.

Keywords:high-throughput phenotyping, strawberry breeding, computer vision, automation potential, trait automation
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
D Veterinary Sciences, Agriculture and related subjects > D470 Agricultural Technology
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
ID Code:49681
Deposited On:06 Sep 2022 14:50

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