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Closing the gap between phenotyping and genotyping: review of advanced, image-based phenotyping technologies in forestry Bian, Liming; Zhang, Huichun; Ge, Yufeng; Čepl, Jaroslav; Stejskal, Jan; El-Kassaby, Yousry A.

Abstract

Key message The lack of efficient phenotyping capacities has been recognized as a bottleneck in forestry phenotyping and breeding. Modern phenotyping technologies use systems equipped with various imaging sensors to automatically collect high volume phenotypic data that can be used to assess trees' various attributes. Context Efficient phenotyping has the potential to spark a new Green Revolution, and it would provide an opportunity to acquire growth parameters and dissect the genetic bases of quantitative traits. Phenotyping platforms aim to link information from several sources to derive knowledge about trees' attributes. Aims Various tree phenotyping techniques were reviewed and analyzed along with their different applications. Methods This article presents the definition and characteristics of forest tree phenotyping and reviews newly developed imaging-based practices in forest tree phenotyping. Results This review addressed a wide range of forest trees phenotyping applications, including a survey of actual inter- and intra-specific variability, evaluating genotypes and species response to biotic and abiotic stresses, and phenological measurements. Conclusion With the support of advanced phenotyping platforms, the efficiency of traits phenotyping in forest tree breeding programs is accelerated.

Item Metadata

Title
Closing the gap between phenotyping and genotyping: review of advanced, image-based phenotyping technologies in forestry
Creator
Bian, Liming; Zhang, Huichun; Ge, Yufeng; Čepl, Jaroslav; Stejskal, Jan; El-Kassaby, Yousry A.
Publisher
Springer Paris
Date Issued
2022-05-09
Description
Key message The lack of efficient phenotyping capacities has been recognized as a bottleneck in forestry phenotyping and breeding. Modern phenotyping technologies use systems equipped with various imaging sensors to automatically collect high volume phenotypic data that can be used to assess trees' various attributes. Context Efficient phenotyping has the potential to spark a new Green Revolution, and it would provide an opportunity to acquire growth parameters and dissect the genetic bases of quantitative traits. Phenotyping platforms aim to link information from several sources to derive knowledge about trees' attributes. Aims Various tree phenotyping techniques were reviewed and analyzed along with their different applications. Methods This article presents the definition and characteristics of forest tree phenotyping and reviews newly developed imaging-based practices in forest tree phenotyping. Results This review addressed a wide range of forest trees phenotyping applications, including a survey of actual inter- and intra-specific variability, evaluating genotypes and species response to biotic and abiotic stresses, and phenological measurements. Conclusion With the support of advanced phenotyping platforms, the efficiency of traits phenotyping in forest tree breeding programs is accelerated.
Subject
Forest tree; Phenotyping; Platforms; Sensor; Stress tolerance; Deep learning; Phenological measurement
Genre
Article
Type
Text
Language
eng
Date Available
2022-07-13
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0416252
URI
http://hdl.handle.net/2429/82127
Affiliation
Forestry, Faculty of; Non UBC; Forest and Conservation Sciences, Department of
Citation
Annals of Forest Science. 2022 May 09;79(1):22
Publisher DOI
10.1186/s13595-022-01143-x
Peer Review Status
Reviewed
Scholarly Level
Faculty; Researcher
Copyright Holder
The Author(s)
Rights URI
http://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 International (CC BY 4.0)