Development and Application of Image-Based High-Throughput Phenotyping Methodology for Salt Tolerance in Lentils

Abstract

Soil salinity is a major abiotic stress in Australian lentil-producing areas. It is therefore imperative to identify genetic variation for salt tolerance in order to develop lentil varieties suitable for saline soils. Conventional screening methods include the manual assessment of stress symptoms, which can be very laborious, time-consuming, and error-prone. Recent advances in image-based high-throughput phenotyping (HTP) technologies have provided unparalleled opportunities to screen plants for a range of stresses, such as salt toxicity. The current study describes the development and application of an HTP method for salt toxicity screening in lentils. In a pilot study, six lentil genotypes were evaluated to determine the optimal salt level and the growth stage for distinguishing lentil genotypes using red–green–blue (RGB) images on a LemnaTec Scanalyzer 3D phenomics platform. The optimized protocol was then applied to screen 276 accessions that were also assessed earlier in a conventional phenotypic screen. Detailed phenotypic trait assessments, including plant growth and green/non-green color pixels, were made and correlated to the conventional screen (r = 0.55; p < 0.0001). These findings demonstrated the improved efficacy of an image-based phenotyping approach that is high-throughput, efficient, and better suited to modern breeding programs.

Plant phenotyping relevance

レンティルの塩害スクリーニング向け画像ベースHTP法を開発し、最適化・従来法との相関検証・大規模適用まで行っており、表現型取得法が研究の中心です。

Code and data availability

The paper describes image-based salt-tolerance phenotyping of lentils on a LemnaTec Scanalyzer 3D, but no public phenotype dataset, image repository, analysis code, or model deposit is stated. The only supplementary link contains figures/tables (scoring scale, post-hoc comparisons), not raw data or code. R, ggpubr, ASR

No evidence-backed public reproduction asset is currently recorded.