期刊论文详细信息
Pesquisa Agropecuária Brasileira
Selection of the most informative morphoagronomic descriptors for cassava germplasm
Eder Jorge De Oliveira1  Osvaldo Sebastião De Oliveira Filho1  Vanderlei Da Silva Santos1 
关键词: Manihot esculenta;    descriptor selection;    genetic resources;    multiple correspondence analysis;    Manihot esculenta;    seleção de descritor;    recursos genéticos;    análise de correspondência múltipla;   
DOI  :  10.1590/S0100-204X2014001100008
来源: SciELO
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【 摘 要 】

The objective of this work was to select the most informative morphoagronomic descriptors for cassava (Manihot esculenta) germplasm and to evaluate the ability of different methods to select the descriptors. Ninety-five accessions were characterized using 51 morphoagronomic descriptors. Data were subjected to a multiple correspondence analysis (MCA), whose information was used in the following four methods of descriptor selection: reverse order of the descriptor for the pth factorial axis of the MCA (Jolliffe); sequential, multiple correspondence analysis (SMCA); mean of the contribution orders of the descriptor in the first three factorial axes (C3PA); and C3PA method weighted by the respective eigenvalues of the full analysis (C3PAWeig). The correlations between the dissimilarity matrix with all descriptors and the most informative descriptors were high and significant (0.75, 0.77, 0.83, and 0.84 for C3PAWeig, C3PA, SMCA, and Jolliffe, respectively). The less informative descriptors were discarded, considering those common among the selection methods and relevant for the breeding interests. Therefore, 32 morphoagronomic descriptors with correlation between the dissimilarity matrices (r=0.81) were selected, due to their high capacity to discriminate cassava germplasm and to their ability to maintain some preliminary agronomic traits, useful for the initial characterization of the germplasm.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

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