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A novel genotypic selection methodology to create a breeding population for developing drought-tolerant cultivars in tree crops.

Authors :
Samarasinghe CRK
Kumarathunge DP
Meegahakumbura MK
Source :
MethodsX [MethodsX] 2023 May 10; Vol. 10, pp. 102217. Date of Electronic Publication: 2023 May 10 (Print Publication: 2023).
Publication Year :
2023

Abstract

With the adverse effects of climate change, selecting the best tolerant varieties to drought stress is highly necessary to sustain the yield and productivity of agricultural crops including tree crops. However, classical drought tolerance selection studies of tree crops have several limitations due to their relatively long lifespan. In this study, we propose a method to identify stable high-yielding trees under changing soil moisture conditions using yield data of existing elite tree populations. We develop this method using the data from a tropical tree palm, Coconut ( Cocos nucifera L.) as a model crop. Our selection method considers individual palms as different genotypes. The method considered both mean trait values and their stability across different environments therefore, it can be effectively used to identify elite genotypes of tree crops for drought tolerance.•We propose an analysis framework to identify stable, high-yielding individuals of tree crops under limited soil moisture conditions using the data of existing tree populations.•Individual trees that produce stable and higher yields under soil moisture stress were identified based on mean yield and regression-based coefficient over different environments characterized by inter-annual rainfall variability.•Individual trees selected by this method can be used as parental populations in breeding programs that focus on developing drought-tolerant varieties.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2023 The Author(s).)

Details

Language :
English
ISSN :
2215-0161
Volume :
10
Database :
MEDLINE
Journal :
MethodsX
Publication Type :
Academic Journal
Accession number :
37251653
Full Text :
https://doi.org/10.1016/j.mex.2023.102217