Step-wise selection using high throughput phenotyping platform (HTTP) and stress tolerance indices as an approach for improving drought tolerance in groundnut (Arachis hypogaea L.)

Abstract

Abstract Drought stress is a major production constraint of groundnut in Africa and Asia where it is largely grown as rainfed crop. The experiments aim to design an early testing approach for drought tolerance in the groundnut breeding pipeline to ensure sustainable production. A population of 600 multi parent advanced generation inter-cross (MAGIC) lines (MLs) (F 8/9 generation) and 100 advance breeding lines (ABLs) were studied in LeasyScan, a high throughput phenotyping platform (HTPP) to assess early canopy growth, and under a managed stress environment (MSE). MSE ensures uniform water application in well-watered and water-stressed plots, while intermittent drought is imposed in water-stressed plots from 1000 0 cumulative thermal time (CTT) during pod-filling stage. Digital biomass, leaf area 3D and plant height measured under HTPP recorded high heritability along with high genetic gain and were identified for use as selection criteria for early canopy vigour. The second selection criteria is Mean Score Index (MSI) (1 to 10 scale), which accounts for both resilience and productivity capacity indices (RCI and PCI), with the MSI ranging from 1.4 to 8.4. Based on results, a two-step selection approach is proposed for selection of traits required for adaption under drought stress. The approach involves HTPP (LeasyScan) to select early canopy vigour followed by selection based on MSI under MSE. MSE is field based and expensive, hence screening of a large number of selection candidates under HTTP helps to select a relatively small subset of early vigour lines for screening under MSE for agronomic performance.

Plant phenotyping relevance

LeasyScan高スループット表現型解析プラットフォームを用いたデジタルバイオマス、葉面積、草丈の取得と、圃場ストレス評価を組み合わせた選抜ワークフローが研究の中心であり、単なる作物試験のルーチン測定ではない。

Code and data availability

The paper's phenotype datasets (LeasyScan canopy traits and MSE yield data) are not publicly deposited; the authors state data are available only on request. The LeasyScan/Phenospex URLs refer to the phenotyping platform/facility, not to this paper's measurements, and no author analysis code or trained models are made

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