Interpretation of genotype × environment interaction for winter wheat yield in Ontario

By Weikai Yan, L. A. Hunt. 2001

396 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Plant Science

View Paper: https://www.semanticscholar.org/paper/e7c2331dd228a7b601ba19737a61e7e160b0e59b

How researchers see this paper

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

In Agronomy and Crop Science

1. Istvan Rajcan
2. Weikai Yan
3. E. Farshadfar
4. R. Mohammadi
5. R. Papa
6. Monica Rodriguez
7. G. Attene
8. D. Rau

In Plant Science

1. Weikai Yan
2. R. Mohammadi
3. P. Cornelius
4. Jose Crossa
5. Baoluo Ma
6. Manjit S. Kang
7. E. Farshadfar
8. M. Kang

Citations in the corpus

• Performance of yield and stability of advanced wheat genotypes under heat stress environments of the Indo-Gangetic plains (2007, background): “Considering that the fi rst component of the SRG analysis accounted for the noncrossover G×E interaction variability and that the second components is due to the crossover G×E variance ( Yan and Hunt, 2001 ), the ideal genotype is the one with the highest values for the fi component and a value clos”
• Biplot Analysis of Genotype by Environment Interaction for Barley Yield in Iran (2006, background): “The termGE interaction commonly refers to yield variation that cannot be explained by G or E alone (Yan and Hunt, 2001).”
• Genotype by environment interactions in barley (Hordeum vulgare L.): different responses of landraces, recombinant inbred lines and varieties to Mediterranean environment (2008, methodology): “Additionally, the phenology (later booting and maturity stages) of these genotypes, even if not strongly correlated to GEI as other covariables, may have been important for the specific adaptation to these environment conditions (Voltas et al. 1999b; Yan and Hunt 2001 ), possibly allowing a higher ”
• Biplot analysis of multi-environment trial data. (2020, background): “In addition, it facilitates interpretation of GE as genotypic factor by environmental factor interactions (Yan and Hunt, 2001).”
• Genetic improvement effects on yield stability in durum wheat genotypes grown in Italy (2010, methodology): “Furthermore, using the AMMI model, information on external environmental or genotypic covariates can be associated with IPCA scores (Vargas et al., 1999; Yan and Hunt, 2001) to elucidate genotypic and environmental causes of GE interaction.”
• Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application (2017, methodology): “The linear model used in GGE analysis is as follows (Yan and Hunt 2001):”
• Yield stability and relationships among stability parameters in faba bean (Vicia faba L.) genotypes (2015, background): “[46] W.”
• GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data (2007, methodology): “When supplemental information (e.g., data on environmental or genotypic covariates) is available, a fourth aspect, which is to understand the causes of G and GE, can be included (Yan and Hunt, 2001; Yan and Kang, 2003; Yan and Tinker , 2005b, 2006).”
• AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.) (2011, background): “Thus, these scores presented a disproportionate genotype response (Yan and Hunt, 2001; Mohammadi et al., 2007), which was the major source of variation for any crossover (qualitative) interaction.”
• Biplot Analysis of Test Sites and Trait Relations of Soybean in Ontario. (2002, methodology): “For each entry at each test site, the average yieldmet for yearly METs (Yan and Hunt, 2001), but not for and average values of other traits were computed in accor-all datasets.”
• GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. (2012, methodology): “…for the analysis of GE interactions (Butron et al., 2004; Fan et al., 2007; Laffont et al., 2007; Yan and Kang, 2003; Samonte et al., 2005) and had been exploited in the variety evaluation of wheat (Yan and Hunt 2001; Yan et al., 2000), Maize (Fan et al., 2007) and soybean (Yan and Rajcan, 2002).”