A Study of the Effect of Site, Variety, and Fertilizer Application on Growth and Yield Component of Rice
Multivariate Analysis of Variance Approach
Abstract
The study aimed to evaluate the effects of site, variety, and fertilizer application on crop yield through a multivariate analysis of variance (MANOVA). The experiment was conducted across multiple sites with different soil types and environmental conditions. Four distinct crop varieties were selected, and three different fertilizer treatments were applied. Data on various agronomic traits, including plant height, tillering height, and yield, were collected to assess the interactions between the factors. The multivariate analysis of variance result indicates significant finding across various effects and interactions related to site, variety, fertilizer and their combinations. The intercepts terms for all test (pillai’s trace, wilks lambda, Hotelling trace and Roy’s largest root) were highly significant (p < 0.001), confirming that the combined dependent variables differ significantly from zero for the main effects, site and variety showed strong significant in all test statistics with p-value less than 0.001, indicating that both environmental factor(site) and genetic difference(variety) significantly influence the growth and yield of rice. These results highlight the primary importance of site and variety in influencing rice growth with a weaker but notable influence of fertilizer and some potential for variety specific fertilizer responses. The finding emphasizes the importance of selecting appropriate rice varieties and optimizing environmental conditions to achieve better rice productivity. The results highlight the robustness of MANOVA as a tool for agricultural research, especially in evaluating interrelated agronomic traits. The study contributes to the optimization of rice production strategies through multivariate modeling that accounts for environmental and varietal complexity.
Keywords:
Site, Variety, Fertilizer, MANOVADownloads
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Copyright (c) 2025 Alfa, M. B., A. Usman, K. Salisu, A. Gambo (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.