纹理(宇宙学)
钥匙(锁)
农业工程
环境科学
计算机科学
人工智能
工程类
计算机安全
图像(数学)
作者
Qingyun Lyu,Xing Wang,Yong-Jian Dang,Lihua Zhu,Lei Chen,Xuedong Wang,Wenping Ding
出处
期刊:Foods
[MDPI AG]
日期:2024-02-19
卷期号:13 (4): 621-621
标识
DOI:10.3390/foods13040621
摘要
This study aimed to find a unique method to assess the textural properties of Niangao (glutinous rice cakes), to determine the relationship between the textural properties of rice cakes and the indicators of glutinous rice, and to identify the key indicators that significantly affect the textural properties of Niangao. The study encompassed the analysis of the chemical composition and pasting characteristics of 22 glutinous rice varieties, revealing the substantial impact of variety on lipid content, straight-chain starch content, and pasting performance. Subsequently, the textural features of the resulting Niangao were subjected to principal component analysis (PCA) to derive a mathematical method for evaluating their textural attributes, with the obtained scores employed in hierarchical cluster analysis (HCA) to identify 12 key textural characteristics. Further analysis using stepwise linear regression (SLR) demonstrated that the regression model incorporating final and peak viscosities of the glutinous rice significantly predicted the composite score of the Niangao’s textural properties. This highlights the importance of final and peak viscosities as key indicators for assessing the textural quality of Niangao.
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