S U M M A R YSimple linear correlations, stepwise multiple regressions and path-coefficient analyses were used to determine the relation between grain yield of maize (Zea mays L.) and weather factors in a three year study involving several planting dates within each year. Maximum and minimum relative humidity, which demonstrated negative relationships with yield, were the most reliable factors, both directly and indirectly, for predicting yield. Temperature (including accumulated heat units), sunshine hours and total and effective rainfall generally snowed negligible direct effects on yield. Potential evaporation, which showed positive correlation, had a negative direct influence on grain yield. We conclude that, whenever possible, path analysis should be used as well as correlation and regression analyses in explaining the complex multiple interactions of yield and weather factors in crop production.
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