Breeder friendly phenotyping

Matthew Reynolds, Scott Chapman, Leonardo Crespo-Herrera, Gemma Molero, Suchismita Mondal, Diego N.L. Pequeno, Francisco Pinto, Francisco J. Pinera-Chavez, Jesse Poland, Carolina Rivera-Amado, Carolina Saint Pierre, Sivakumar Sukumaran

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the ‘breeder friendliness’ of phenotyping within three main domains: (i) the ‘minimum data set’, where being ‘handy’ or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or ‘precision’ phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.
Original languageEnglish (US)
JournalPlant Science
StatePublished - Jun 1 2020
Externally publishedYes

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Generated from Scopus record by KAUST IRTS on 2022-09-13


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