📤 Data Upload & Preview

📁 Upload your Excel/CSV file

📝 Supported: .xlsx, .xls, .csv

🌍 Per-Environment Analysis

Environment-wise Descriptive Statistics

💡 Interpretation

Per-environment descriptive statistics reveal how trait expression varies across locations/seasons. Large CV differences between environments signal strong environmental effects.

Trait Distribution per Environment

💡 Interpretation

Boxplots and violin plots show the spread of trait values within each environment. Outlier genotypes can be spotted as individual points beyond the whiskers.

ANOVA Results by Environment

💡 Interpretation

Within-environment ANOVA tests whether genotypic differences are significant in each location. Significant p-values (< 0.05) justify genotype comparisons within that environment.

Genotype Means per Environment

💡 Interpretation

Genotype mean performance in each environment. Use for identifying top performers in specific target environments.

Genotype Rank Across Environments

💡 Interpretation

Rank changes across environments reveal G×E interaction. Consistent ranks indicate stable genotypes; large rank changes indicate strong G×E.

Environment-to-Environment Correlation

💡 Interpretation

High correlation between environments means they discriminate genotypes similarly. Low or negative correlation suggests mega-environment differentiation.

BLUEs within Each Environment

💡 Interpretation

Within-environment BLUEs remove block/rep noise. Use these adjusted means for environment-specific selection decisions.

📊 Descriptive Statistics

💡 Interpretation

CV > 20% indicates high variability. Check skewness and kurtosis for normality.

🧮 Analysis of Variance (ANOVA)

ANOVA Table

💡 Interpretation

P < 0.05 indicates significant differences. Check residual plots for model assumptions.

📈 Mixed Models & BLUEs

💡 Interpretation

Parallel lines = no G×E; crossing lines = interaction present.

🧬 Heritability Analysis

Variance Components

Heritability Estimates

💡 Interpretation

H² > 0.6 = high heritability, suitable for direct selection.

🔗 Trait Correlations

💡 Interpretation

Values near ±1 = strong relationships. Use for indirect selection strategies.

🌐 Genotype Clustering

💡 Interpretation

Groups similar genotypes. Use for identifying genetic groups and breeding strategies.

📐 Principal Component Analysis

💡 Interpretation

First PCs explain most variation. Loadings show trait contributions.

⚖️ Genotype Stability Analysis

💡 Interpretation

Low Ecovalence (Wi²) + high yield = stable high-performer.

🎨 Plot Customization

Adjust Plot Dimensions

Select Color Scheme

💡 Instructions

Adjust height/width and color scheme, then click Apply.