Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 34 |
| Fachzeitschrift | Theoretical and applied genetics |
| Jahrgang | 136 |
| Ausgabenummer | 3 |
| Publikationsstatus | Veröffentlicht - März 2023 |
Abstract
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 (Pi) was least affected among 11 SI. Pi 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 Pi. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in Pi; while light extinction coefficient and radiation use efficiency were more correlated with Pi than with yield. The high number of genotypes and environments required for studying Pi highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.
ASJC Scopus Sachgebiete
- Biochemie, Genetik und Molekularbiologie (insg.)
- Biotechnologie
- Agrar- und Biowissenschaften (insg.)
- Agronomie und Nutzpflanzenwissenschaften
- Biochemie, Genetik und Molekularbiologie (insg.)
- Genetik
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in: Theoretical and applied genetics, Jahrgang 136, Nr. 3, 34, 03.2023.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters
T2 - a computational study on wheat crop
AU - Wang, Tien Cheng
AU - Casadebaig, Pierre
AU - Chen, Tsu Wei
N1 - Funding Information: The authors gratefully acknowledge the technical support by Dr. Katrin Leinweber for her help in developing the R package toolStability and setting up with GitHub. We also thank Magnus Alder form Leibniz Universität Hannover for maintaining the server for simulation. The study was funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under project number 419973621).
PY - 2023/3
Y1 - 2023/3
N2 - 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 (Pi) was least affected among 11 SI. Pi 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 Pi. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in Pi; while light extinction coefficient and radiation use efficiency were more correlated with Pi than with yield. The high number of genotypes and environments required for studying Pi highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.
AB - 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 (Pi) was least affected among 11 SI. Pi 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 Pi. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in Pi; while light extinction coefficient and radiation use efficiency were more correlated with Pi than with yield. The high number of genotypes and environments required for studying Pi highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.
UR - http://www.scopus.com/inward/record.url?scp=85149942569&partnerID=8YFLogxK
U2 - 10.1007/s00122-023-04264-7
DO - 10.1007/s00122-023-04264-7
M3 - Article
C2 - 36897399
AN - SCOPUS:85149942569
VL - 136
JO - Theoretical and applied genetics
JF - Theoretical and applied genetics
SN - 0040-5752
IS - 3
M1 - 34
ER -