Correlations and track analysis for morphoagronomic descriptors in pedigree and parental lines of castor bean

• Autor(a) principal: Silva,Adielle Rodrigues da
• Data de Publicação: 2017
• Outros Autores: Silva,Simone Alves, Almeida,Vanessa de Oliveira, Araújo,Gilmara de Melo, Ledo,Carlos Alberto da Silva
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Ciência Rural
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000400205
• topic: Ricinus communis L. selection; productivity

ABSTRACT: As castor bean (Ricinus communis L.) reveals immense adaptability to various ecological conditions and due to its socioeconomic significance, new studies have emerged primarily to develop more productive cultivars to suit different regions in Brazil. This study aimed to confirmthe correlations and direct and indirect effects of the morphoagronomic descriptors on castor bean productivity, employing correlation studies and track analysis. Between 2014 and 2015, experiments utilizing the randomized block design were performed, with four replications, which included 208 treatments involving pedigree and parental lines of castor bean, drawn from the germplasm bank of the Universidade Federal do Recôncavo da Bahia. Variables in the correlation analysis included primary racemic insertion, stem diameter, number of stem internodes, plant flowering, plant height, racemic length, number of fruits per raceme, fruit weight per raceme, seed yield per fruit and productivity. Correlations among the variables analyzed were imposed, via track analysis, on the direct and indirect influences of the morphoagronomic descriptors on productivity. The most direct and positively influential descriptors included fruit weight per raceme and number of seeds per raceme; the most direct albeit negatively influential descriptors are the number of internodes on the stem and flowering. Therefore, lines with less number of internodes and requiring fewer days to bloom are more highly productive. These descriptors can thus effectively identify the productive lines.