Article citationsMore>>

Dia, M., Wehner, T.C., Hassell, R., Price, D.S., Boyhan, G.E., Olson, S., King, S., Davis, A.R., Tolla, G.E., Bernier, J., Juarez, B., Sari, N., Solmaz, I. and Aras V.(2012) Mega-Environment Identification for Watermelon Yield Testing in the USProceedings of the Xth EUCARPIA Meeting on Genetics and Breeding of Cucurbitaceae, Antalya, Turkey, 15-18 October 2012, 385-390.

has been cited by the following article:

• TITLE: RGxE: An R Program for Genotype x Environment Interaction Analysis

  AUTHORS: Mahendra Dia, Todd C. Wehner, Consuelo Arellano

  KEYWORDS: Genotype x Environment Interaction, R Programming Language, RGxE, Univariate, Multivariate

  JOURNAL NAME: American Journal of Plant Sciences, Vol.8 No.7, June 26, 2017

  ABSTRACT: Genotype x environmental interaction (GxE) can lead to differences in performance of genotypes over environments. GxE analysis can be used to analyze the stability of genotypes and the value of test locations. We developed an Rlanguage program (RGxE) that computes univariate stability statistics, descriptive statistics, pooled ANOVA, genotype F ratio across location and environment, cluster analysis for location, and location correlation with average location performance. Univariate stability statistics calculated are regression slope (bi), deviation from regression (S2d), Shukla’s variance (σi2), S square Wricke’s ecovalence (Wi), and Kang’s yield stability (YSi). RGxE is free and intended for use by scientists studying performance of polygenic or quantitative traits over multiple environments. In the present paper we provide the RGxE program and its components along with an example input data and outputs. Additionally, the RGxE program along with associated files is also available on GitHub at https://github.com/mahendra1/RGxE, http://cucurbitbreeding.com/todd-wehner/publications/software-sas-r-project/ and http://cuke.hort.ncsu.edu/cucurbit/wehner/software.html.