Application of multivariate and univariate data analysis to evaluate the response of chili ( <i>Capsicum annuum</i> L.) to various plant growth regulators

Chili peppers ( Capsicum annuum L.) are a strategic horticultural commodity in Indonesia that greatly influences consumption patterns. This commodity also affects market dynamics. One effective approach to increasing productivity is through the application of plant growth regulators (PGRs). This study evaluated the effects of two types of PGR: Atonik, which contains nitrophenol compounds (sodium para-nitrophenolate, sodium ortho-nitrophenolate, and sodium 5-nitroguaiaolate), and Agrogibb, which contains gibberellic acid (GA₃), as well as a combination of the two. This experiment used TM999 curly red chili peppers. This experiment was designed to assess growth parameters and crop yield. Data analysis was performed using univariate and multivariate approaches. Multivariate analysis (PCA) showed a clear separation between treatments. Univariate analysis (ANOVA and Tukey's post hoc test) confirmed that the 60 mg/L Agrogibb treatment provided a significant increase in growth in several parameters observed. The results of the univariate and multivariate tests reinforced each other, showing that Agrogibb had a better and more dominant effect on chili plants. Correlation analysis revealed a strong positive relationship between vegetative traits, such as plant height, number of leaves, and branch development. These parameters can serve as reliable predictors in determining chili crop yield performance. This approach demonstrates the potential of statistical integration in optimizing agricultural productivity and supporting chili production development in Indonesia.

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