STATISTICAL MODELING OF MAIZE YIELD VARIABILITY UNDER DIFFERENT SOIL FERTILITY AND TILLAGE CONDITIONS
DOI:
https://doi.org/10.69980/thyp4v61Keywords:
Maize yield variability, Organic matter management, Soil fertility, Statistical modeling, Tillage practicesAbstract
Soil fertility, tillage, and organic matter management are all factors that affect maize productivity and thus yield. This study aimed to evaluate maize yield variability under different soil fertility and tillage conditions using statistical modeling techniques. Thirty-six experimental observations were used for a quantitative analytical approach: three tillage practices and three organic matter treatments. Treatment differences and relationships between soil characteristics and the maize yield were assessed through descriptive statistics, two-way analysis of variance (ANOVA), Pearson correlation analysis and multiple linear regression. Results showed differences in maize productivity among management treatments, traditional rotary tillage yielding the highest and the lowest yield was from no-till and earthworm bio-till. ANOVA, however, showed that neither tillage nor organic matter treatments nor the combination of tillage and organic matter were significant. Correlation analysis revealed that there was weak non-significant relationship between maize yield and soil fertility indicators. Multiple linear regression indicated a significant positive relationship between traditional rotary tillage and maize yield when compared with earthworm bio-tillage, but the model had not been satisfactory in explaining the phenomena. The results here suggest that the relationship between agriculture management practices and soil properties is complicated and that all these influence maize yield variability. The study highlights the need for integrated soil management and advises for deeper, multi-season studies with a greater statistical weight to promote a better predictive modeling and the sustainable production of maize in different agricultural environments.
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