Integration of univariate and multivariate analysis in evaluating irrigation efficiency and nitrogen fertilization in upland rice cultivation

Upland rice ( Oryza sativa L.) has emerged as a potential solution for global warming condition to its ability to grow on dry land. However, the productivity of upland rice is generally lower than that of irrigated rice, necessitating efforts to improve yields through proper agronomic management. The integration of univariate and multivariate analysis provides a robust framework for evaluating plant performance. This study aims to investigate the effects of irrigation intensity and nitrogen fertilization rates on upland rice using integrated univariate and multivariate data analysis. The experiment used a completely randomized block design (CRBD) with combination from two factors using Situ Bagendit variety. The treatments consisted of four levels of irrigation intensity (433, 477, 560, and 610 ml/polybag) and four nitrogen fertilizer doses (0, 100, 200, and 300 kg Urea/ha). The N4P1 treatment (300 kg N/ha with daily irrigation of 433 ml/polybag) provided the most optimal results for most of the upland rice yield parameters. The number of panicles and the number of grains per plant, are the main factors determining the productivity of milled dry grain. Univariate and multivariate tests confirm that the combination of nitrogen availability and adequate irrigation is a key factor in optimizing upland rice yields.

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