Rossi D A, Daher R F, Barbé T C, Lima R S N, Costa A F, Ribeiro L P, Teodoro P E, Bhering L L
Faculdade Venda Nova do Imigrante, Venda Nova do Imigrante, ES, Brasil.
Laboratório de Melhoramento Genético Vegetal, , , Brasil.
Genet Mol Res. 2017 Sep 27;16(3):gmr-16-03-gmr.16039803. doi: 10.4238/gmr16039803.
Elephant grass is a perennial tropical grass with great potential for energy generation from biomass. The objective of this study was to estimate the genetic diversity among elephant grass accessions based on morpho-agronomic and biomass quality traits and to identify promising genotypes for obtaining hybrids with high energetic biomass production capacity. The experiment was installed at experimental area of the State Agricultural College Antônio Sarlo, in Campos dos Goytacazes. Fifty-two elephant grass genotypes were evaluated in a randomized block design with two replicates. Components of variance and the genotypic means were obtained using a Bayesian multi-trait model. We considered 350,000 iterations in the Gibbs sampler algorithm for each parameter adopted, with a warm-up period (burn-in) of 50,000 Iterations. For obtaining an uncorrelated sample, we considered five iterations (thinning) as a spacing between sampled points, which resulted in a final sample size 60,000. Subsequently, the Mahalanobis distance between each pair of genotypes was estimated. Estimates of genotypic variance indicated a favorable condition for gains in all traits. Elephant grass accessions presented greater variability for biomass quality traits, for which three groups were formed, while for the agronomic traits, two groups were formed. Crosses between Mercker Pinda México x Mercker 86-México, Mercker Pinda México x Turrialba, and Mercker 86-México x Taiwan A-25 can be carried out for obtaining elephant grass hybrids for energy purposes.
象草是一种多年生热带草本植物,具有通过生物质发电的巨大潜力。本研究的目的是基于形态农艺和生物质质量性状评估象草种质间的遗传多样性,并鉴定出有潜力的基因型,以获得具有高能量生物质生产能力的杂交种。试验在坎波斯-多斯戈伊塔卡泽斯的安东尼奥·萨洛州立农业学院试验区进行。采用随机区组设计,对52个象草基因型进行了两次重复评估。使用贝叶斯多性状模型获得方差分量和基因型均值。对于采用的每个参数,在吉布斯采样器算法中考虑了350,000次迭代,预热期(预烧)为50,000次迭代。为了获得不相关的样本,我们将五次迭代(间隔抽样)作为采样点之间的间隔,最终样本量为60,000。随后,估计了每对基因型之间的马氏距离。基因型方差估计表明所有性状都有有利于增益的条件。象草种质在生物质质量性状上表现出更大的变异性,据此形成了三组,而在农艺性状上形成了两组。为了获得用于能源目的的象草杂交种,可以进行默克品达墨西哥×默克86 - 墨西哥、默克品达墨西哥×图里亚尔巴以及默克86 - 墨西哥×台湾A - 25之间的杂交。