Mixed Modeling of Yield Components and Brown Rust Resistance in Sugarcane Families

Sugarcane ( Saccharum spp.) is a complex autopolyploid with high potential for biomass production that can be converted into sugar and ethanol. Genetic improvement is extremely important to generate more productive and resistant cultivars. Populations of improved sugarcane are generally evaluated for several traits simultaneously and in multi‐environment trials. In this study, we evaluated two full‐sib families of sugarcane (SR1 and SR2) at two locations and 3 yr for stalk diameter, stalk height, stalk number, stalk weight, soluble solid content (Brix), sucrose content of cane, sucrose content of juice, fiber, cane yield, sucrose yield, and resistance to brown rust ( Puccinia melanocephala ). Using a mixed model approach, we included appropriate variance–covariance (VCOV) structures for modeling heterogeneity and correlation of genetic effects and non‐genetic residual effects. The genotypic correlations between traits were calculated across the adjusted means as the standard Pearson product‐moment coefficient. Through the VCOV structures estimated for each trait, in general, the heritabilities ranged from 0.78 to 0.94. Additionally, we detected 17 and 12 significant genotypic correlations between the evaluated traits for SR1 and SR2, respectively. The analysis of the severity data for brown rust revealed that 66 and 32% of the full‐sib genotypes in SR1 and SR2, respectively, had at least 90% probability of being resistant. A linear mixed model is efficient in production data analysis of sugarcane. In general, the broad‐sense heritability of the traits were high, ranging from 0.78 to 0.94. A generalized linear mixed model can be applied in brown rust analysis of sugarcane. Multi‐environment trials were applied to the genetic improvement of sugarcane.