Analysis of Genotype × Environment Interaction (G×E) Using SAS Programming

By Mahendra Dia, Todd C. Wehner, C. Arellano. 2016

73 citations recorded by the source corpus.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/2197c86266156f463c8eebdc90d6c2c7ac5dfa6a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. R. Mohammadi
2. M. Rafii
3. Y. Oladosu
4. A. Mehraban
5. A. Ramli
6. Kadambot H. M. Siddique

In Plant Science

1. N. Abdullah
2. R. Mohammadi
3. M. Rafii
4. Y. Oladosu
5. G. Miah
6. A. Mehraban
7. A. Ramli
8. Ghazali Hussin

Citations in the corpus

• Integrating different stability models to investigate genotype × environment interactions and identify stable and high-yielding barley genotypes (2019, background): “…(1988) rank-sum, S(i) Huehn’s (1979) and Nassar and Huehn’s (1987) non-parametric measures, NP(i) Thennarasu’s non-parametric (1995) measures quantitative traits including grain yield, reproductive fitness, longevity, and seed weight as well as both biotic and abiotic resistance (Dia et al. 2016).”
• Genotype × Environment interaction and stability analyses of yield and yield components of established and mutant rice genotypes tested in multiple locations in Malaysia* (2017, methodology): “The SASGxE code was developed by Dia et al. (2015) which is freely available at http://cuke.hort.ncsu.edu/ cucurbit/wehner/software.html.”