Using a series of rice varieties having different amylose content as a model to study the factor affecting gelling properties of starch

• Main Authors: Chi-Ruei Wu, 吳啟瑞
• Other Authors: 呂廷璋
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/82418142647221955349

碩士 === 國立臺灣大學 === 食品科技研究所 === 94 === Abstract To understand the roles of starch molecules, amylose and amylopectin, plays in gel-forming properties, starch samples with wide range of amylose content from 18 rice cultivars of were selected to study the relationship between molecular structural characters and their gel texture, pasting properties, and viscoelastic properties measured by using texture profile analysis (TPA), rapid visco-analysis (RVA), and dynamic rheolometry (DR). In order to increase sample population for statistical analysis, other 26 starch samples from rice mutant were also included in this study. Chain-length distribution values of starch molecules were used as independent parameters for multivariate stepwise regression analysis to elucidate the correlation between the textural properties mentioned. High-performance size-exclusion chromatographic peaks of debranched starch were designated as F1, F2 and F2 according its eluting order. The results showed that apparent amylose content of starch samples from rice cultivars (ranged from 0.30% to 29.37%) as well as samples from mutants (1.48% to 28.48%) had covered a wide range and had no significant difference in mass ratio of all three fractions and in chain-length of F2 and F3 fractions, but found significant difference in chain-length of F1 (represents the amylose and extra-long chains of amylopectin). The mutants had longer F1 chain-length than selected cultivars. Function of multiple regression analysis could be used to predict TPA hardness using starch molecular structural parameters. Mass ratio of F1 and chain-length of F1explained most of the variance attributed to the models (55.8%, 18.8% ), but chain-length of F2、mass ratio of F2、apparent amylose content had little effect on the amount of variance attributed to the models (5.5%, 4.3%, 1.9%, respectively). The full multiple regression models explained 86.3% of the variation in TPA hardness. After adding dynamic rheologic parameters, storage modular force at 25℃, as extra predictor into the multiple regression model, it will increase most of the variance (from 55.8% to 84.3%) and full variance (from 86.3% to 92.9%). The results implied that the stiffness of swollen starch granules in the starch gel at early stage of gel-forming contributed more than those leached molecules for hardness attributes of starch gel.