Phenotypic diversity of starch pasting properties in cassava for food industry

ABSTRACT. The aim of this study was to evaluate the phenotypic variation and diversity of cassava for breeding purposes based on the pasting properties of starch, for food applications. The viscosities of the starches, extracted from 1031 accessions, were obtained using a Rapid Visco Analyzer. The best linear unbiased predictors were calculated for five critical points of the viscograms, which were then used to cluster the accessions based on the discriminant analysis of principal components. The wide phenotypic variation identified from the viscograms reveals the high potential for selection gains, especially for pasting temperature and setback. Certain strong correlations indicate that selection based on a specific viscogram trait can be used for indirect selection (e.g., the correlation between peak viscosity and breakdown [0.85]). The lowest Bayesian information criterion identified five different groups. Groups 3 and 4 exhibited high pasting temperatures, while Groups 3 and 5 exhibited low setbacks. Group 3 also exhibited low viscosity and breakdown. However, we focused on selecting cassava accessions with a high pasting temperature and low setback, as these are the most important traits for industrial applications. The predicted genetic gains from the selection of the top 15 cassava accessions for increasing pasting temperature and decreasing setback were 4.40% and 53.17%, respectively. The increased pasting temperature (~72.89°C) and high amplitude of setback (~600 cP) due to selection can guide the utilization of the cassava germplasm for breeding and provide a basis for further studies to develop varieties with added value, especially in the food industry.

Bibliographic Details

Main Authors:	Santos,Cristiano Silva dos, Sousa,Massaine Bandeira e, Brito,Ana Carla, Oliveira,Luciana Alves de, Carvalho,Carlos Wanderlei Piler, Oliveira,Eder Jorge de
Format:	Digital revista
Language:	English
Published:	Editora da Universidade Estadual de Maringá - EDUEM 2023
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-86212023000103004
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