### Abstract

Premise of the Study Access to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype-by-environment interactions (GEI) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and disease resistance. The stability of genotypes across a range of environments can be analyzed using GEI analysis. GEI analysis includes univariate and multivariate analyses with both parametric and non-parametric models. Methods and Results The program STABILITYSOFT is online software based on JavaScript and R to calculate several univariate parametric and non-parametric statistics for various crop traits. These statistics include Plaisted and Peterson's mean variance component (theta(i)), Plaisted's GE variance component (theta((i))), Wricke's ecovalence stability index (W-i(2)), regression coefficient (b(i)), deviation from regression (S-di(2)), Shukla's stability variance (sigma(2)(i)), environmental coefficient of variance (CVi), Nassar and Huhn's statistics (S-(1), S-(2)), Huhn's equation (S-(3) and S-(6)), Thennarasu's non-parametric statistics (NP(i)), and Kang's rank-sum. These statistics are important in the identification of stable genotypes; hence, this program can compare and select genotypes across multiple environment trials for a given data set. This program supports both the repeated data across environments and matrix data types. The accuracy of the results obtained from this software was tested on several crop plants. Conclusions This new software provides a user-friendly interface to estimate stability statistics accurately for plant scientists, agronomists, and breeders who deal with large volumes of quantitative data. This software can also show ranking patterns of genotypes and describe associations among different statistics with yield performance through a heat map plot. The software is available at .

Original language | English |
---|---|

Article number | 1211 |

Number of pages | 6 |

Journal | Applications in Plant Sciences |

Volume | 7 |

Issue number | 1 |

DOIs | |

Publication status | Published - Jan 2019 |

### Cite this

*Applications in Plant Sciences*,

*7*(1), [1211]. https://doi.org/10.1002/aps3.1211

}

*Applications in Plant Sciences*, vol. 7, no. 1, 1211. https://doi.org/10.1002/aps3.1211

**STABILITYSOFT : A new online program to calculate parametric and non-parametric stability statistics for crop traits.** / Pour-Aboughadareh, Alireza; Yousefian, Mohsen; Moradkhani, Hoda; Poczai, Peter; Siddique, Kadambot H. M.

Research output: Contribution to journal › Editorial

TY - JOUR

T1 - STABILITYSOFT

T2 - A new online program to calculate parametric and non-parametric stability statistics for crop traits

AU - Pour-Aboughadareh, Alireza

AU - Yousefian, Mohsen

AU - Moradkhani, Hoda

AU - Poczai, Peter

AU - Siddique, Kadambot H. M.

PY - 2019/1

Y1 - 2019/1

N2 - Premise of the Study Access to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype-by-environment interactions (GEI) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and disease resistance. The stability of genotypes across a range of environments can be analyzed using GEI analysis. GEI analysis includes univariate and multivariate analyses with both parametric and non-parametric models. Methods and Results The program STABILITYSOFT is online software based on JavaScript and R to calculate several univariate parametric and non-parametric statistics for various crop traits. These statistics include Plaisted and Peterson's mean variance component (theta(i)), Plaisted's GE variance component (theta((i))), Wricke's ecovalence stability index (W-i(2)), regression coefficient (b(i)), deviation from regression (S-di(2)), Shukla's stability variance (sigma(2)(i)), environmental coefficient of variance (CVi), Nassar and Huhn's statistics (S-(1), S-(2)), Huhn's equation (S-(3) and S-(6)), Thennarasu's non-parametric statistics (NP(i)), and Kang's rank-sum. These statistics are important in the identification of stable genotypes; hence, this program can compare and select genotypes across multiple environment trials for a given data set. This program supports both the repeated data across environments and matrix data types. The accuracy of the results obtained from this software was tested on several crop plants. Conclusions This new software provides a user-friendly interface to estimate stability statistics accurately for plant scientists, agronomists, and breeders who deal with large volumes of quantitative data. This software can also show ranking patterns of genotypes and describe associations among different statistics with yield performance through a heat map plot. The software is available at .

AB - Premise of the Study Access to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype-by-environment interactions (GEI) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and disease resistance. The stability of genotypes across a range of environments can be analyzed using GEI analysis. GEI analysis includes univariate and multivariate analyses with both parametric and non-parametric models. Methods and Results The program STABILITYSOFT is online software based on JavaScript and R to calculate several univariate parametric and non-parametric statistics for various crop traits. These statistics include Plaisted and Peterson's mean variance component (theta(i)), Plaisted's GE variance component (theta((i))), Wricke's ecovalence stability index (W-i(2)), regression coefficient (b(i)), deviation from regression (S-di(2)), Shukla's stability variance (sigma(2)(i)), environmental coefficient of variance (CVi), Nassar and Huhn's statistics (S-(1), S-(2)), Huhn's equation (S-(3) and S-(6)), Thennarasu's non-parametric statistics (NP(i)), and Kang's rank-sum. These statistics are important in the identification of stable genotypes; hence, this program can compare and select genotypes across multiple environment trials for a given data set. This program supports both the repeated data across environments and matrix data types. The accuracy of the results obtained from this software was tested on several crop plants. Conclusions This new software provides a user-friendly interface to estimate stability statistics accurately for plant scientists, agronomists, and breeders who deal with large volumes of quantitative data. This software can also show ranking patterns of genotypes and describe associations among different statistics with yield performance through a heat map plot. The software is available at .

KW - adaptability

KW - phenotypic stability

KW - quantitative traits

KW - ranking method

KW - STABILITYSOFT

KW - X ENVIRONMENT INTERACTION

KW - RANK-SUM METHOD

KW - YIELD STABILITY

KW - PHENOTYPIC STABILITY

KW - GENOTYPE

KW - PERFORMANCE

KW - ADAPTATION

KW - TESTS

U2 - 10.1002/aps3.1211

DO - 10.1002/aps3.1211

M3 - Editorial

VL - 7

JO - Applications in Plant Sciences

JF - Applications in Plant Sciences

SN - 2168-0450

IS - 1

M1 - 1211

ER -