Evaluation of the yield and quality stability of chilli genotypes by employing AMMI, GGE and MTSI techniques

Technical Summary: Evaluation of the Yield and Quality Stability of Chilli Genotypes by Employing AMMI, GGE and MTSI Techniques

Problem Statement
Chilli (Capsicum annuum L.) is a vital solanaceous crop with significant economic value for food, medicinal, and industrial applications. However, its productivity is severely compromised by extreme sensitivity to diverse agro-climatic conditions. Genotype × Environment (GEI) interactions frequently alter the ranking of lines across locations and seasons, creating challenges in identifying resilient, widely adapted genotypes. Traditional selection methods often fail to simultaneously account for mean performance and stability across multiple traits and environments. Consequently, there is a critical need for advanced statistical frameworks to dissect GEI, assess buffering ability, and select genotypes that maintain high yield and quality (specifically oleoresin and Total Soluble Solids) under the variable conditions of the North-Western Himalayas.

Methodology
The study evaluated 28 chilli genotypes, comprising 21 F1 hybrids and 7 parental lines (including one check variety, DKC-8), across three diverse environments in Himachal Pradesh, India: Nauni (E1), Dhaula Kuan (E2), and Bajaura (E3). These locations represented varying elevations (468–1300 m), soil textures, and climatic conditions (sub-tropical to sub-humid temperate). The experiment was conducted using a Randomized Complete Block Design (RCBD) with three replications.

Nine traits were recorded: days to 50% flowering, plant spread, primary branches per plant, fruit length, fruit width, red ripe fruit yield per plant, 1000-seed weight, oleoresin content, and Total Soluble Solids (TSS).

To analyze stability and performance, the study employed a comprehensive suite of multivariate statistical techniques:

1. Pooled ANOVA: To assess the significance of genotypic, environmental, and GEI effects.
2. AMMI (Additive Main Effects and Multiplicative Interaction): To partition GEI variance into principal component axes (IPCA) and visualize interactions via biplots (AMMI1 and AMMI2).
3. GGE Biplot: To visualize "which-won-where" patterns, identify mega-environments, and rank genotypes based on mean performance and stability relative to an ideal genotype.
4. Stability Indices: Calculation of AMMI-based indices (ASV, ASI, ASTAB, MASI, MASV) and the Genotype Selection Index (GSI).
5. WAASB and MTSI: Utilization of the Weighted Average of Absolute Scores (WAASB) derived from BLUPs and the Multi-Trait Stability Index (MTSI) to integrate mean performance with stability across multiple traits simultaneously.

Key Results

• Significance of Interactions: Pooled ANOVA revealed highly significant genotypic and environmental effects for all traits. GEI was significant for five key traits: plant spread, fruit yield, 1000-seed weight, oleoresin, and TSS, confirming the necessity for stability analysis.
• AMMI Analysis: The AMMI model indicated that genotype effects contributed the largest proportion (80%) to the variation in fruit yield, followed by GEI (6.03%) and environment (5.06%). AMMI1 and AMMI2 biplots identified genotypes with broad adaptability (low IPCA scores) versus those with specific adaptation. Genotypes NHPCH1 (G8), NHPCH20 (G27), NHPCH16 (G23), NHPCH21 (G28), and NHPCH4 (G11) emerged as top performers.
• GGE Biplot: The "which-won-where" analysis clustered environments into sectors, identifying specific winning genotypes for each location. For fruit yield, G8 (NHPCH1) was the winner in Dhaula Kuan and Bajaura, while G11 (NHPCH4) excelled in Nauni. The ranking view identified G7, G28, G22, G27, and G6 as the most stable and high-performing genotypes for flowering time, while G11, G8, G23, G13, and G27 were top-ranked for yield.
• Stability Indices: Based on AMMI-derived indices (ASV, MASV) and GSI, genotypes G23 and G27 were consistently ranked as the most stable for fruit yield.
• WAASB and MTSI: The MTSI analysis, using a 15% selection intensity, successfully identified superior genotypes that balanced high productivity with stability. The top-ranked genotypes were G27 (NHPCH20), G7 (DKC-8), G5 (Punjab Guchhedar), and G28 (NHPCH21).
  • Selection Gains: The MTSI approach achieved desired selection differentials (SD%) for 7 out of 9 traits (77% success rate), including plant spread, fruit width, number of primary branches per plant (NPBP), fruit yield per plant (FYPP), 1000-seed weight, oleoresin, and TSS.
  • Trait Clustering: Factor analysis grouped the nine traits into three components: FA1 (yield-related), FA2 (quality-related: TSS and oleoresin), and FA3 (phenology).
  • Specific Highlights: NHPCH20 (G27) was ranked superior for oleoresin content, while Punjab Guchhedar (G5) was identified as superior for TSS.

Significance and Claims
The paper asserts that the comparative application of AMMI, GGE biplot, WAASB, and MTSI provides a more robust framework for understanding GEI and stability in chilli breeding than any single model alone.

• Methodological Integration: The study demonstrates that while AMMI effectively structures GEI and GGE visualizes performance patterns, the MTSI approach offers a decisive advantage by integrating mean performance and stability across multiple agronomic and quality traits into a single selection criterion.
• Breeding Recommendations: The identified genotypes, particularly NHPCH20 (G27) and NHPCH16 (G23), are presented as promising candidates for regional cultivation in the North-Western Himalayas. These lines exhibit the desired combination of high yield, stability, and superior quality traits (oleoresin and TSS).
• Environmental Insight: The study highlights Nauni and Dhaula Kuan as the most descriptive environments for evaluating yield stability, while Bajaura showed lower average yields.
• Practical Application: The selected genotypes are proposed as valuable genetic resources for future varietal development and as parental lines to breed broadly adapted, high-yielding, and resilient chilli cultivars capable of withstanding changing climatic conditions.

The authors conclude that these resilient genotypes can be considered for commercial cultivation and future validation, offering a solution to the trade-off between high yield and stability in heterogeneous environments.