Vol. 8 No. 07 (2026): Volume 08 Issue 07

This study developed a multivariate framework for comparing leaf-pigment profiles among the strawberry cultivars Kingsberry, Murano, and Brina and six breeding hybrids. Because the originally supplied absorbance values produced biologically implausible negative pigment estimates, a three-replicate model dataset was constructed using the Lichtenthaler equations for 100% acetone and quantitative ranges reported for strawberry leaves. The modeled ranges were 1.00-1.55 mg g⁻¹ FW for chlorophyll a, 0.52-0.68 mg g⁻¹ FW for chlorophyll b, 1.52-2.23 mg g⁻¹ FW for total chlorophyll, and 0.30-0.50 mg g⁻¹ FW for total carotenoids. One-way ANOVA indicated a strong modeled genotype effect on all major pigment traits (P < 0.001; η² = 0.947-0.986). Hybrid 4 exhibited the highest modeled total chlorophyll (2.23 ± 0.03 mg g⁻¹ FW) and carotenoid content (0.50 ± 0.01 mg g⁻¹ FW), whereas Hybrid 2, Hybrid 5, and Murano formed an intermediate-to-high pigment group. The first two principal components explained 99.69% of the total variation: PC1 represented overall pigment accumulation, whereas PC2 primarily reflected variation in the chlorophyll a/b ratio. Ward clustering separated the genotypes into high-, intermediate-, and relatively low-pigment groups. These findings illustrate how integrated univariate and multivariate methods can support the preliminary screening of breeding material. However, the numerical values are literature-constrained model data and must not be interpreted as original experimental observations.

Chilli (Capsicum annuum L.) is among the most economically important vegetable and spice crops cultivated worldwide due to its nutritional, medicinal, and commercial significance. Continuous improvement of chilli cultivars is essential to meet the increasing demand for higher yield, superior fruit quality, resistance to biotic and abiotic stresses, and enhanced adaptability to diverse agro-climatic conditions. Conventional breeding approaches relying primarily on biparental populations have significantly contributed to cultivar development; however, they frequently suffer from limited genetic variability and restricted recombination events. Multi-parent derived populations have emerged as an advanced breeding strategy capable of integrating favorable alleles from multiple elite parental lines while generating broader genetic diversity and increased recombination frequencies. Such populations provide superior opportunities for dissecting quantitative genetic variation and accelerating genetic gain. This review synthesizes current theoretical and practical knowledge regarding the genetic architecture governing economically important traits in chilli and critically evaluates breeding efficiency within multi-parent derived populations. An integrated methodological framework incorporating quantitative genetic principles, population development strategies, breeding value estimation, trait evaluation, and selection indices is proposed to optimize crop improvement programs. The review further discusses the role of additive and non-additive genetic effects, transgressive segregation, heterosis, recombination, genotype evaluation, and selection efficiency in improving breeding outcomes. Comparative analyses of existing breeding strategies indicate that multi-parent populations possess considerable advantages over traditional biparental approaches in terms of allele accumulation, selection precision, and long-term breeding progress. Nevertheless, practical challenges including population management, resource requirements, and statistical complexity remain important considerations. The integrated framework presented herein provides a comprehensive conceptual foundation for future chilli breeding programs focused on sustainable genetic improvement, enhanced breeding efficiency, and resilient cultivar development.