Genetic diversity based on multivariate techniques in elephant grass genotypes for bioenergy.

The use of biomass for energy production constitutes a promising strategy that warrants the search for new sources of biomass. Elephant grass has been gaining notoriety due to its high dry matter yield and rapid growth. The present study was carried out to quantify the genetic divergence of nine elephant grass half-sib families in order to identify genotypes with greater genetic divergence and productive potential for hybridization, using the hierarchical clustering methodology based on principal components. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was laid out in a randomized-block design with nine half-sib families, three replicates, and eight plants per plot. A total of 216 genotypes of elephant grass were evaluated. Principal component (PC), biplot, and hierarchical clustering analyses for diversity estimation were conducted using R software. The first two PCs of biplot analysis accounted for 64% of the cumulative variation. Dry matter yield was the most important trait for genotype discrimination (0.89), followed by plant height (0.67) and stem diameter (0.61) in PC1. In this analysis, the distances between accessions were considered and there were no family links, which indicates the existence of wide variability within the evaluated families, since genotypes belonging to the same family were not grouped together, but rather distributed into different groups. Crosses between genotypes of group three and genotypes of groups one and two are recommended for the development of high-yielding genotypes when aiming at energy production.

Selecting elephant grass families and progenies to produce bioenergy through mixed models (REML/BLUP).

Brazil has great potential to produce bioenergy since it is located in a tropical region that receives high incidence of solar energy and presents favorable climatic conditions for such purpose. However, the use of bioenergy in the country is below its productivity potential. The aim of the current study was to select full-sib progenies and families of elephant grass (Pennisetum purpureum S.) to optimize phenotypes relevant to bioenergy production through mixed models (REML/BLUP). The circulating diallel-based crossing of ten elephant grass genotypes was performed. An experimental design using the randomized block methodology, with three repetitions, was set to assess both the hybrids and the parents. Each plot comprised 14-m rows, 1.40 m spacing between rows, and 1.40 m spacing between plants. The number of tillers, plant height, culm diameter, fresh biomass production, dry biomass rate, and the dry biomass production were assessed. Genetic-statistical analyses were performed through mixed models (REML/BLUP). The genetic variance in the assessed families was explained through additive genetic effects and dominance genetic effects; the dominance variance was prevalent. Families such as Capim Cana D'África x Guaçu/I.Z.2, Cameroon x Cuba-115, CPAC x Cuba-115, Cameroon x Guaçu/I.Z.2, and IAC-Campinas x CPAC showed the highest dry biomass production. The family derived from the crossing between Cana D'África and Guaçu/I.Z.2 showed the largest number of potential individuals for traits such as plant height, culm diameter, fresh biomass production, dry biomass production, and dry biomass rate. The individual 5 in the family Cana D'África x Guaçu/I.Z.2, planted in blocks 1 and 2, showed the highest dry biomass production.