Agronomic characterization of biquinho vermelha and bode amarela peppers by principal component analysis

Authors

Keywords:

Multivariate analysis, Capsicum chinense, genetical enhancement

Abstract

Peppers are part of brazilian cultural richness and a valuable patrimony of Brazil's biodiversity. They have been domesticated over the years and, currently, there are several varieties of pepper, each with its own characteristics. Due to the benefits brought by peppers, their agronomic characterization is important as it can serve as a basis for the development of new cultivars. Thus, the present work aimed to characterize and compare the biquinho vermelha and bode amarela peppers in terms of some of their agronomic characteristics, using principal component analysis. The variables analyzed in the commercial maturity of the plants were: height, height of the first bifurcation, transversal and longitudinal diameter of the plant top, crown compactness, number of fruits, number of leaves, SPAD index, fruit diameter, fruit length, fresh weight of part aerial, pot coverage, leaf length, leaf width, number of lateral branches, length of lateral branches and days after transplanting for flowering (DAT). Using Kaiser's criterion, four principal components were selected in the analysis, which captured approximately 92% of the data variability. The biquinho vermelha pepper was characterized by higher values for number of fruits, fruit diameter, fruit length, fresh weight of aerial part, pot coverage, leaf length and leaf width. The bode amarela pepper was characterized by higher values of plant height, height of the first fork, crown compactness, number of leaves and DAT. There was no difference between the peppers regarding the other agronomic variables analyzed. 

References

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Published

04-11-2024

How to Cite

Bandini de Carvalho, B., Romanini Morales, B., de Fátima Martins França, C., César Sala, F., Rodrigues Liska, G., & Rodrigues, J. (2024). Agronomic characterization of biquinho vermelha and bode amarela peppers by principal component analysis. Sigmae, 13(4), 32–40. Retrieved from https://publicacoes.unifal-mg.edu.br/revistas/index.php/sigmae/article/view/2505

Issue

Section

Applied Statistics