Application of a Rank-Based Method for Improved Cultivar Selection in Soft Red Winter Wheat

Abstract

Lackermann, K. V., and Esker, P. D. 2011. Application of a rank-based method for improved cultivar selection in soft red winter wheat. Plant Dis. 95:1407-1413.Both grain yield and disease performance are important factors to consider for winter wheat {Triticum aestivum) cultivar selection. However, disease severity and yield data are often presented separately, making it difficult to compare values across multiple environments. The objective of this study was to use a rank-based method to compare cultivars based on yield and disease performance combined across multiple environments. Thirty-six wheat cultivars were planted at each of four Wisconsin locations (Arlington, Chilton, Janesville, and Lancaster) in 2009 and 2010. Plots were assessed four times during the growing season for powdery mildew, Septoria/Stagonospora leaf blotch, and leaf rust. Incidence and severity of Fusarium head blight were assessed at Zadoks growth stage 85 (soft dough). Within each location-year. cultivars were ranked for severity of each disease and for grain yield. One-way analysis of variance was performed to calculate an overall rank value that incorporated data for all four diseases and yield across the eight location-years. There was an effect of cultivar on overall rank {P < 0.0001). Powdery mildew rank was strongly correlated with overall rank (Spearman's rho = 0.485, P = 0.005), as was yield rank (Spearman's rho = 0.674, P < 0.0001). Cultivars described as "best" or "worst" cultivars were generally more consistent in their rankings across different treasures. The use of a rank-based method provides an approach that will allow growers to base cultivar selection on multiple performance measures across multiple environments.

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“…Microsoft Office Excel 2010 and Origin 9.1 were used for experimental data analyses. One‐way analysis of variance (ANOVA) and correlation analysis were performed on the experimental data using the SPSS Statistics 22.0 package, and significant comparisons were calculated based on least significant difference (LSD) tests.…”