Multivariate analysis in the selection of elephant grass genotypes for biomass production

Lilia M. Gravina, Tâmara Rebecca A. de Oliveira, Rogério F. Daher, Geraldo A. Gravina, Ana Kessia F. Vidal, Wanessa F. Stida, Derivaldo P. Cruz, Q.S.S. de Sant’Anna, Camila, Richardson S. Rocha, Antonio V. Pereira and Gustavo Hugo F. de Oliveira

Renewable Energy, 2020, vol. 160, issue C, 1265-1268

Abstract: The elephant grass has proved to be a great option for biomass production because it causes less damage to the environment, yet there is not a lot of information about its use as a renewable energy source. The objective of this study was to use multivariate analysis to check elephant grass genotypes for biomass production. Between 2016 and 2018, comprising four semiannual cutting, 12 entries were evaluated, and the Active Germplasm Bank of Elephant grass of North Fluminense State University Darcy Ribeiro presented better performances for dry matter yield. The experimental design was a randomized complete block design with three replications. ANOVA and biplot graphs were drawn for variables plant height, number of tillers, stem diameter, leaf blade length, leaf blade width, dry weight and percentage of dry matter. The variance analysis showed the existence of genetic variability between elephant grass genotypes and two first principal components, a biplot analysis of the genotype and the characteristics explained 70.07% of the total variation. The dry weight per linear meter and yield per hectare were the variables with greater discriminatory powers, thus being suitable for selecting elephant grass genotypes. The dry matter yield was positively correlated with dry weight and stem diameter. Genotypes 7, 11 and 12 presented the highest overall mean and were also the most stable.

Keywords: Biplot; Genotype x characteristics correlation; Pennisetum purpureum (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:160:y:2020:i:c:p:1265-1268

DOI: 10.1016/j.renene.2020.06.094

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