To test for the statistical significance of the influence of different management strategies on corn yield, nitrogen uptake, and nitrate leaching under different climate scenarios, we used a Kruskal-Wallis rank sum test, also known as non-parametric analysis of variance (ANOVA). This test is designed to test for differences between two or more groups and does not assume a normal distribution of the residuals, which is more appropriate for skewed distributions that we obtained for the rainfed treatments. Pairwise comparison between different treatments were done using Dunn’s multi comparison test at the 95% confidence level. For analyzing the differences in water use efficiency between calendar and precision irrigation treatments, Wilcoxon rank sum test was used at the 95% significance level.
To test for the statistical significance of the influence of different management strategies on corn yield, nitrogen uptake, and nitrate leaching under different climate scenarios, we used a Kruskal-Wallis rank sum test, also known as non-parametric analysis of variance (ANOVA). This test is designed to test for differences between two or more groups and does not assume a normal distribution of the residuals, which is more appropriate for skewed distributions that we obtained for the rainfed treatments. Pairwise comparison between different treatments were done using Dunn’s multi comparison test at the 95% confidence level. For analyzing the differences in water use efficiency between calendar and precision irrigation treatments, Wilcoxon rank sum test was used at the 95% significance level.