Closing the gap between phenotyping and genotyping: review of advanced, image-based phenotyping technologies in forestry

Abstract

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.

Plant phenotyping relevance

森林樹木の画像ベース表現型技術とフェノタイピングプラットフォームを体系的にレビューしており、方法論が中心である。

Code and data availability

This is a review article on image-based forest tree phenotyping. The supplied blocks contain no paper-specific phenotype datasets, image/sensor data, analysis code, or trained models with public availability statements; figures are illustrative and cited works are third-party.

No evidence-backed public reproduction asset is currently recorded.