In this paper, the development of novel MINITAB macros are presented, performing certain operations: (i) a curve-fitting examining 14 algorithms, (ii) comparing experimental designs, (iii) analyzing multi-observation Latin square designs,(iv) orthogonal contrasts, (v) performing multivariate path analysis, (vi, vii) analyzing stability analysis of genotypes. Twenty of recently-bred maize genotypes were examined under 2 drought environments along with the control in the field, and grain yield (YLD), seeds per ear (SPE), and ear length (EL) were scored. In the results, the relative efficiencies (RE) showed that LS design has a lower RE than its lower-level designs. The orthogonal comparison indicated a significant difference between two groups of maize genotypes (9 vs 11). Accordingly, our macro unraveled a specific kind of the exponential curves with the highest R-sq(adj) index (91.54%). Path coefficients analysis showed the effects of EL and SPE traits on grain yield. The stability analysis introduced genotype BARAKAT-74, GARZA, and DKC-6101, BOLSON as the most stable genotypes under drought. Finally, the AMMI2 model was the best model and introduced the stable, high-yielding and moderate-tolerant maize genotypes. The macros presented here could be utilized in various areas of biological sciences, especially plant breeding, to perform advanced statistical and experimental design analyses.
