Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models

ABSTRACT The mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass ( Cenchrus purpureus (Schumach.) Morrone ) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.摘要 混合模型方法（mixed-model methodology）是针对受环境影响显著的性状筛选基因型的可选方案。此外，该方法可用于估算重复系数，并预测选择过程中为提升可靠性所需的评价次数。本研究旨在明确可靠筛选流程所需的最少评价次数，并借助该方法估算象草（Cenchrus purpureus (Schumach.) Morrone）半同胞家系间及家系内遗传增益预测所需的方差组分。本研究以象草活性种质库的基因型为材料构建半同胞家系，实验采用随机区组设计，共设置9个半同胞家系、3次重复，每小区定植8株植株，共评价216份象草基因型（单株）。采用Selegen软件完成偏差分析、遗传参数估算、家系间与家系内遗传增益预测，并计算得到重复系数。结果表明，供试家系内存在可用于筛选的遗传变异；株高、分蘖数的可靠性值均高于60%，干物质产量的可靠性值高于80%，这意味着仅需2次评价即可筛选出可靠性优异的优良基因型。本研究共鉴定并筛选出16份具备高产潜力的基因型，可作为生物能源生产用象草育种项目的亲本材料。