Correlation between physicochemical properties of japonica and indica rice starches

• Published in: Food science & technology Vol. 66; pp. 530 - 537
• Main Authors: Jang, Eun-Hee, Lee, Su-Jin, Hong, Joo-Yeon, Chung, Hyun-Jung, Lee, Young-Tack, Kang, Bo-Sik, Lim, Seung-Taik
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2016
• Subjects: Amylose content; Pasting properties; Rice starches; Textural properties; Thermal properties; Thermal properties; Amylose content; Pasting properties; Textural properties; Rice starches
• ISSN: 0023-6438; 1096-1127
• DOI: 10.1016/j.lwt.2015.11.001

Rice starches isolated from different cultivars were compared in their physicochemical properties including granule size, amylose content, protein content, thermal property, pasting viscosity, and gel texture, and the relationships among those properties were determined using Pearson correlation analysis. The starch containing the greatest amount of amylose which had been isolated from a japonica cultivar Goami 3 showed the highest gelatinization temperature and the greatest gel hardness among twelve rice starches tested. The indica starches which contained the higher amylose and protein contents and the larger granules than japonica starches showed the higher gelatinization and pasting temperatures with the lower pasting viscosity. Amylose content was positively correlated to pasting temperature (r = 0.878, p ≤ 0.01), but negatively correlated to peak viscosity (r = −0.910, p ≤ 0.001) and breakdown (r = −0.905, p ≤ 0.001). Cohesiveness of starch gel was positively related to amylose content (r = 0.780, p ≤ 0.05), protein content (r = 0.933, p ≤ 0.001) and mean granule size (r = 0.791, p ≤ 0.05). •Physicochemical properties of starches varied from different rice varieties.•Amylose content was the major factor affecting the pasting properties of rice starch.•The higher amylose and mean granule size in starch increased the melting temperature.•Gel cohesiveness had high and positive correlation with protein content (r = 0.933).•Relationships amongst variables were examined by principal component analysis.