Gge Biplot Full Fixed Version
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# Gge Biplot Full Version: A Powerful Tool for Genotype by Environment Interaction Studies
If you are a researcher who conducts and analyzes crop variety trials, you may have encountered the challenge of dealing with genotype by environment interaction (GEI). GEI occurs when different genotypes perform differently across different environments, making it difficult to identify the best genotypes for each environment or across environments. GEI also complicates the interpretation of the results and the presentation of the data.
One way to overcome this challenge is to use Gge Biplot Full Version, a user-friendly software designed for conducting biplot analysis of research data. Biplot analysis is a graphical method that can simultaneously display genotypes and environments on a two-dimensional plane, revealing the relationships among them and facilitating visual evaluation. Gge Biplot Full Version can generate perfect biplots of all possible centering and scaling models, and provide tools to interpret the biplot in all possible perspectives, many of them novel and unique.
## What is Gge Biplot Full Version?
Gge Biplot Full Version is a software developed by Dr. Weikai Yan, a research scientist at Agriculture and Agri-Food Canada. It is based on the singular value decomposition (SVD) of environment-centered data, which partitions the total variation into genotype main effects (G), environment main effects (E), and GEI effects (GxE). The software can then plot the first two principal components (PCs) of the SVD, which account for most of the variation in the data. The resulting biplot is called a GGE biplot, where GGE stands for genotype main effects plus GEI effects.
Gge Biplot Full Version can handle data from various types of experiments, such as randomized complete block design (RCBD), alpha design, augmented design, lattice design, split-plot design, strip-plot design, and multi-location trials. It can also handle data with missing values, unbalanced replications, covariates, and transformations. It can perform various statistical analyses, such as analysis of variance (ANOVA), stability analysis, correlation analysis, regression analysis, cluster analysis, discriminant analysis, and principal component analysis (PCA).
## How to use Gge Biplot Full Version?
To use Gge Biplot Full Version, you need to have your data in a two-way table format, where rows represent genotypes and columns represent environments. You also need to have a license key to activate the software. Once you have installed and activated the software, you can follow these steps to create a GGE biplot:
1. Open the software and click on File > Open Data File to load your data file.
2. Click on Analysis > GGE Biplot Analysis to open the GGE biplot analysis window.
3. Select the centering and scaling model that suits your objective. For example, if you want to compare genotypes across environments, you can choose "Double Standardization". If you want to compare environments across genotypes, you can choose "Environment Focused Scaling".
4. Click on OK to generate the GGE biplot.
5. You can then use various tools in the software to interpret the biplot. For example, you can use "Which-Won-Where" to identify the winning genotypes for each environment or mega-environment. You can use "Average Environment Coordination" (AEC) to evaluate genotype stability and adaptability. You can use "Genotype Ranking" to rank genotypes based on their mean performance or stability indices. You can also use "Environment Evaluation" to assess environment representativeness and discriminating ability.
## What are the benefits of Gge Biplot Full Version?
Gge Biplot Full Version has many benefits for researchers who deal with GEI data. Some of them are:
- It can simplify complex data into a two-dimensional graph that is easy to understand and communicate.
- It can reveal patterns and relationships that are hidden or difficult to detect in numerical tables or charts.
- It can provide multiple perspectives and insights that are not available from other methods or software.
- It can help researchers make informed decisions about genotype selection, breeding strategy, trial design, and resource allocation.
## Conclusion
Gge Biplot Full Version is a powerful tool for genotype by environment interaction studies. It can help researchers analyze and interpret their data in a graphical way that is informative and intuitive. It can also help researchers improve their research efficiency and effectiveness.
If you want to learn more about Gge Biplot Full Version or download a free trial version, you can visit its official website at http://g
## What are the applications of Gge Biplot Full Version?
Gge Biplot Full Version can be applied to various types of data that can be presented in a two-way table, such as crop variety trials, sensory evaluation, quality control, market research, and social science. However, one of the most common and important applications of Gge Biplot Full Version is to analyze genotype by environment interaction (GEI) data from multi-environment trials (METs).
METs are experiments that evaluate the performance of different genotypes across different environments, such as locations, seasons, years, or management practices. METs are essential for plant breeding and crop improvement, as they can help identify superior genotypes that are adapted to specific or broad environments, and provide information for genotype selection and recommendation.
However, METs also pose challenges for data analysis and interpretation, as different genotypes may perform differently across different environments due to GEI. GEI can complicate the ranking of genotypes and the identification of the best genotypes for each environment or across environments. GEI can also affect the representativeness and discriminating ability of the test environments.
Gge Biplot Full Version can help overcome these challenges by providing a graphical method that can simultaneously display genotypes and environments on a two-dimensional plane, revealing the relationships among them and facilitating visual evaluation. Gge Biplot Full Version can help researchers answer questions such as:
- Which genotypes are the best performers in each environment or across environments?
- Which genotypes are the most stable or adaptable across environments?
- Which environments are the most representative or discriminating for testing genotypes?
- How are the genotypes and environments correlated or clustered?
- How much variation is explained by genotype main effects, environment main effects, and GEI effects?
## Examples of Gge Biplot Full Version
To illustrate the use and interpretation of Gge Biplot Full Version, here are some examples from recent studies that applied Gge Biplot Full Version to analyze GEI data from METs.
### Example 1: Yield performance and stability of Bambara groundnut genotypes
Bambara groundnut [Vigna subterranea L. (Verdc.)] is an under-researched legume crop that is important for food security and nutrition in Africa. Khan et al. (2021) evaluated the yield performance and stability of 30 Bambara groundnut genotypes in four different Malaysian environments using Gge Biplot Full Version. They used a randomized complete block design with three replications in each environment, and measured yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare.
They performed a pooled analysis of variance and found highly significant variations among genotypes, environments, and GEI for all traits. They then generated a GGE biplot using double standardization as the centering and scaling model. The GGE biplot explained 94.97% and 3.11% of the variation in GEI for yield per hectare by the first two principal components (PCs), respectively.
The GGE biplot revealed that the three winning genotypes G1, G3, and G5 appeared across environments, while AMMI model exposed genotypes G18, G14, G7, G3, G1, and G5 as best performers. Based on ideal genotype ranking, genotype G1 was the best performer, with a high mean yield and high stability in the tested environment. According to the AEC line, genotypes G1 and G3 were extremely stable, while genotypes G2 and G4 were low stable, with a high average yielding per hectare.
The GGE biplot also showed that season and location were the most significant causes of yield heterogeneity, accounting for 31.13% and 14.02% of overall variation, respectively. The biplot also classified the environments into three groups: E1 (main season at Serdang), E2 (off-season at Serdang), E3 (main season at Bagan Datuk), and E4 (off-season at Bagan Datuk). The biplot also indicated that E1 was the most representative and discriminating environment for testing Bambara groundnut genotypes.
The authors concluded that breeding could improve yield production, and that the genotypes discovered could be recommended for commercial cultivation.
### Example 2: Genotype by environment interaction of wheat cultivars
Wheat (Triticum aestivum L.) is one of the most important cereal crops in the world. Alake et al. (2019) determined the yield stability of 24 wheat cultivars using Gge Biplot Full Version. They conducted a multi-environment trial in six locations across Nigeria using an alpha lattice design with three replications in each location. They measured grain yield (t ha−1) as the main trait of interest.
They performed an ANOVA and found significant differences among cultivars, locations
### Example 3: Genotype by environment interaction of maize hybrids
Maize (Zea mays L.) is a major staple crop in many countries. Oyekunle et al. (2017) analyzed the genotype by environment interaction of 15 maize hybrids in 12 environments across Nigeria using Gge Biplot Full Version. They used an alpha lattice design with three replications in each environment, and measured grain yield (t ha−1) and other agronomic traits.
They performed a combined ANOVA and found significant differences among hybrids, environments, and GEI for grain yield and other traits. They then generated a GGE biplot using environment-focused scaling as the centering and scaling model. The GGE biplot explained 64.6% and 10.8% of the variation in GEI for grain yield by the first two PCs, respectively.
The GGE biplot showed that the hybrids H1, H2, H3, H4, H5, H6, H7, H8, and H9 were high yielding and stable across environments, while the hybrids H10, H11, H12, H13, H14, and H15 were low yielding and unstable. The biplot also identified three mega-environments: E1 (Ikenne), E2 (Ibadan), and E3 (the rest of the environments). The biplot also indicated that E1 was the most representative and discriminating environment for testing maize hybrids.
The authors concluded that the GGE biplot was a useful tool for identifying superior and stable maize hybrids and evaluating test environments.
## Conclusion
Gge Biplot Full Version is a powerful tool for analyzing genotype by environment interaction data from multi-environment trials. It can help researchers simplify complex data into a two-dimensional graph that reveals patterns and relationships among genotypes and environments. It can also help researchers make informed decisions about genotype selection, breeding strategy, trial design, and resource allocation.
Gge Biplot Full Version is user-friendly software that can handle various types of data and experiments. It can also perform various statistical analyses and provide tools to interpret the biplot in all possible perspectives. It is a valuable tool for researchers who conduct and analyze crop variety trials or other data that can be presented in a two-way table.
If you want to learn more about Gge Biplot Full Version or download a free trial version, you can visit its official website at http://ggebiplot.com/.
In summary, Gge Biplot Full Version is a software that can help researchers analyze and interpret genotype by environment interaction data from multi-environment trials. It can generate biplots that display genotypes and environments on a two-dimensional plane, revealing their relationships and facilitating visual evaluation. It can also provide tools to answer questions such as which genotypes are the best performers, which environments are the most representative, and how much variation is explained by different sources. Gge Biplot Full Version can handle various types of data and experiments, and perform various statistical analyses. It is a useful tool for researchers who deal with complex data that can be presented in a two-way table. 4aad9cdaf3