Isolating higher yielding and more stable rice genotypes in stress environments: fine-tuning a selection method using production and resilience score indices

Highlights

● Score index methods readily discriminate genotypes adapted to a target environment.

● New quantitative method evaluated productivity and resilience of rice genotypes.

● Method identified A genotypes (high productivity and resilience) of Fernandez (1992).

● Method identified genotypes better adapted to reduced soil water conditions.

● Method can enhance rice sustainability (high productivity, low water use).

Abstract

In Asia, the rice crop sustains millions of people. However, growing demand for this crop needs to be met while simultaneously reducing its water consumption to cope with the effects of climate change. Lowland cropping systems are the most common and productive but have particularly high water requirements. High-yielding rice genotypes adapted to drier environments (such as rainfed or aerobic rice ecosystems) are needed to increase the water use efficiency of cropping. Identifying these genotypes requires fast and more accurate selection methods. It is hypothesized that applying a new quantitative selection method (the score index selection method), can usefully compare rice yield responses over different years and stress intensities to select genotypes more rapidly and efficiently. Applying the score index to previously published rice yield data for 39 genotypes grown in no-stress and two stress environments, identified three genotypes (ARB 8, IR55419-04 and ARB 7) with higher and stable yield under moderate to severe stress conditions. These genotypes are postulated to be better adapted to stress environment such as upland and aerobic environments. Importantly, the score index selection method offers improved precision than the conventional breeding selection method in identifying genotypes that are well-suited to a range of stress levels within the target environment.

Graphical abstract

Keywords

Aerobic rice / breeding selection / drought resilience / production capacity index / resilience capacity index / stress score index / upland

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Supplementary materials

The online version of this article at https://doi.org/10.15302/J-FASE-2023521 contains supplementary materials (Sections A–C; Figs. S1–S2; Tables S1–S3).

Acknowledgements

This research was supported by a FONDECYT—World Bank fund for the project 017-2020 and a Newton Fund Impact Scheme ID 630222342 under the Newton-Paulet Fund partnership. Bethsy Nieuwenhuizen is thanked for her pertinent comments on a draft version of this paper.

Compliance with ethics guidelines

Arnauld Thiry, William J. Davies, and Ian C. Dodd declare that they have no conflicts of interest or financial conflicts to disclose. This article does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

The Author(s) 2023. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)