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Change in physicochemical traits of cassava roots and starches associated with genotypes and environmental factors
Author(s) -
Gu Bi,
Yao Qingqun,
Li Kaimian,
Chen Songbi
Publication year - 2013
Publication title -
starch ‐ stärke
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.62
H-Index - 82
eISSN - 1521-379X
pISSN - 0038-9056
DOI - 10.1002/star.201200028
Subject(s) - cultivar , starch , biology , trait , genotype , gene–environment interaction , dry matter , agronomy , food science , gene , biochemistry , computer science , programming language
Cassava South China genotype cultivars were released by Chinese Academy of Tropical Agricultural Sciences and their physicochemical traits had been described. However, the physicochemical traits of these cultivars affected by environmental factors were poorly understood. This study aimed to investigate the effects of interrelationship between genotypes and environments (G and E) on physicochemical traits of cassava roots and starches. Fourteen quantitative characteristics were assessed in seven genotypes grown in eight locations in China. The influences due to G and E upon the physicochemical traits of cassava roots and starches were evaluated using the general linear models procedure. The results indicated that the examined traits could be significantly affected by the factors of G and E, and the different contribution of G and E to total variation was evidenced. A most important economic trait dry matter content, ranging from 18.3 to 31.9% during seven genotypes, was negatively correlated to rainfall in cassava growing environments, but insignificantly correlated to temperature. Average starch granule sizes ranged between 9.5 and 12.7 µm. Granules were mainly truncated in shape and similar across all cultivars, and were insignificantly affected by rainfall and temperature. Significant correlations were observed among starch properties including paste clarity and viscosity, which was positively correlated to granule surface area. Principal component analysis demonstrated that SC8 is the best genotype suited for industrial applications and all cassava genotypes responded differently in various environmental climate conditions for the examined traits.