Biometric analysis of cassava clones

In the last ten years cassava roots represented the fourth most produced commodity in Brazil. Given its commercial importance, higher yields are constantly sought in breeding programs. This study was aimed at conducting a biometric analysis of cassava clones based on the estimation/predi...

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Bibliographic Details
Main Authors: Ísis Fernanda de Almeida, Adriana Madeira Santos Jesus, Ramon Vinicius de Almeida, Bianca Stefáni Arantes Leite, Mayara Cardoso do Prado
Format: Article
Language:Portuguese
Published: Universidade Federal Rural da Amazônia (UFRA) 2018-12-01
Series:Revista de Ciências Agrárias
Subjects:
Online Access:https://ajaes.ufra.edu.br/index.php/ajaes/article/view/2950/1567
Description
Summary:In the last ten years cassava roots represented the fourth most produced commodity in Brazil. Given its commercial importance, higher yields are constantly sought in breeding programs. This study was aimed at conducting a biometric analysis of cassava clones based on the estimation/prediction of genetic parameters and correlated genetic gain using mixed models and path analysis, respectively. Forty-eight clones were evaluated in a randomized block design with two replicates. The experiment was carried out in northern Minas Gerais in 2010. The agronomic characteristics evaluated were plant height (PH), fresh weight of aerial parts (FWAP), fresh root weight (FRW), fresh weight of commercial roots (FWCR), root length (RL), and root diameter (RD). These traits were evaluated at six and twelve months after planting. All traits examined were significantly affected by genotype. FWAP, RL and RD changed according the time of harvesting and RL was superior at six months. Accuracy was highest for PH (0.90) and lowest for FRW and FWCR (0.64). UFLA 42 was the most commercially productive. The trait RL exhibited the highest gain via correlated response to FWCR at twelve months after planting. At six months after planting, no traits were suitable for indirect selection. The traits PH and FWAP had little relevance as secondary components in path analysis.
ISSN:2177-8760
2177-8760