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Image Search Results


The polygon view of “Which-won-where” model of GGE biplot representing the performance of wheat genotypes and their interactions with environment. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Journal: Scientific Reports

Article Title: Exploring the genotype-environment interaction of bread wheat in ambient and high-temperature planting conditions: a rigorous investigation

doi: 10.1038/s41598-024-53052-w

Figure Lengend Snippet: The polygon view of “Which-won-where” model of GGE biplot representing the performance of wheat genotypes and their interactions with environment. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Article Snippet: The “metan” package of R studio was practical for AMMI analysis, while the GGE Biplot GUI package was working for GGE biplot based analysis.

Techniques:

“Ranking of genotypes” model of biplot assess other wheat genotypes against the ideal genotype conferring genotype interaction and genotype x environment interactions. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Journal: Scientific Reports

Article Title: Exploring the genotype-environment interaction of bread wheat in ambient and high-temperature planting conditions: a rigorous investigation

doi: 10.1038/s41598-024-53052-w

Figure Lengend Snippet: “Ranking of genotypes” model of biplot assess other wheat genotypes against the ideal genotype conferring genotype interaction and genotype x environment interactions. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Article Snippet: The “metan” package of R studio was practical for AMMI analysis, while the GGE Biplot GUI package was working for GGE biplot based analysis.

Techniques:

The “Discrimitiveness vs. Representativeness” model of biplot evaluate the wheat genotypes against the ideal genotypes, conferring genotype interaction and genotype x environment interactions. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Journal: Scientific Reports

Article Title: Exploring the genotype-environment interaction of bread wheat in ambient and high-temperature planting conditions: a rigorous investigation

doi: 10.1038/s41598-024-53052-w

Figure Lengend Snippet: The “Discrimitiveness vs. Representativeness” model of biplot evaluate the wheat genotypes against the ideal genotypes, conferring genotype interaction and genotype x environment interactions. ( a ) grain yield under normal sown environment, ( b ) grain filling rate under normal sown environment, ( c ) grain yield under heat stress environment ( d ) grain filling rate under heat stress environment.

Article Snippet: The “metan” package of R studio was practical for AMMI analysis, while the GGE Biplot GUI package was working for GGE biplot based analysis.

Techniques:

The four-quadrant diagram of economic resistance and recoverability (a) and biplot of economic resilience (b).

Journal: PLOS ONE

Article Title: Measurement of economic resilience under the COVID-19 based on nighttime light remote sensing: Case of Hubei province

doi: 10.1371/journal.pone.0307613

Figure Lengend Snippet: The four-quadrant diagram of economic resistance and recoverability (a) and biplot of economic resilience (b).

Article Snippet: Furthermore, GGE biplot in R studio [ ] was utilized to graphically rank the economic resilience of cities in the second and third quadrants, taking into account their overall performance in terms of resistance and recoverability during the COVID-19 pandemic ( ).

Techniques: