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More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop

KEY MESSAGE: Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. ABSTRACT: Identifying target traits for breeding stable...

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Autores principales: Wang, Tien-Cheng, Casadebaig, Pierre, Chen, Tsu-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006026/
https://www.ncbi.nlm.nih.gov/pubmed/36897399
http://dx.doi.org/10.1007/s00122-023-04264-7
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author Wang, Tien-Cheng
Casadebaig, Pierre
Chen, Tsu-Wei
author_facet Wang, Tien-Cheng
Casadebaig, Pierre
Chen, Tsu-Wei
author_sort Wang, Tien-Cheng
collection PubMed
description KEY MESSAGE: Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. ABSTRACT: Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (P(i)) was least affected among 11 SI. P(i) was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or P(i). For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in P(i); while light extinction coefficient and radiation use efficiency were more correlated with P(i) than with yield. The high number of genotypes and environments required for studying P(i) highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-023-04264-7.
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spelling pubmed-100060262023-03-12 More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop Wang, Tien-Cheng Casadebaig, Pierre Chen, Tsu-Wei Theor Appl Genet Original Article KEY MESSAGE: Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. ABSTRACT: Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (P(i)) was least affected among 11 SI. P(i) was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or P(i). For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in P(i); while light extinction coefficient and radiation use efficiency were more correlated with P(i) than with yield. The high number of genotypes and environments required for studying P(i) highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-023-04264-7. Springer Berlin Heidelberg 2023-03-10 2023 /pmc/articles/PMC10006026/ /pubmed/36897399 http://dx.doi.org/10.1007/s00122-023-04264-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Wang, Tien-Cheng
Casadebaig, Pierre
Chen, Tsu-Wei
More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title_full More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title_fullStr More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title_full_unstemmed More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title_short More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
title_sort more than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006026/
https://www.ncbi.nlm.nih.gov/pubmed/36897399
http://dx.doi.org/10.1007/s00122-023-04264-7
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