Genetic diversity of elephant grass ( Cenchrus purpureus [Schumach.] Morrone) for energetic production based on quantitative and multi-category traits
Elephant grass (Cenchrus purpureus (Schumach.) Morrone) has been used as an alternative source of energy. It is widely cultivated in Brazil, however it needs genotypes adapted to different ecosystems of the country. The knowledge of genetic diversity allows the identification of genotypes that can b...
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Veröffentlicht in: | Chilean journal of agricultural research 2017-01, Vol.77 (1), p.48-56 |
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Sprache: | eng |
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Zusammenfassung: | Elephant grass (Cenchrus purpureus (Schumach.) Morrone) has been used
as an alternative source of energy. It is widely cultivated in Brazil,
however it needs genotypes adapted to different ecosystems of the
country. The knowledge of genetic diversity allows the identification
of genotypes that can be used in breeding programs. Thus, this study
aimed to evaluate the diversity among 85 genotypes of elephant grass by
Tocher's clustering method and by the unweighted pair group
method with arithmetic averages (UPGMA), using quantitative and
multi-category traits in 2 yr of evaluations. The experiment was
implemented in the State Center for Research on Bioenergy and Waste Use
at Pesagro-Rio, located in Campos dos Goytacazes, Río de Janeiro,
Brazil. Eighty-five elephant grass genotypes donated by the Active
Elephant Grass Germplasm Bank of Embrapa Dairy Cattle, in Coronel
Pacheco, Minas Gerais, Brazil, were included in the experiment. The
experimental design was arranged as randomized blocks, with two
replicates. Based on the quantitative traits, the 85 genotypes analyzed
belonged to 17 groups according to Tocher's optimization method
and to 13 groups when analyzed by UPGMA. For the qualitative traits,
however, the genotypes formed 10 groups for both methods. Therefore,
the multivariate technique indicated genetic divergences among the
genotypes and allowed the formation of similarity groups by
Tocher's optimization and UPGMA methods for both the quantitative
and qualitative traits. |
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ISSN: | 0718-5820 0718-5839 0718-5839 |
DOI: | 10.4067/S0718-58392017000100006 |