文献类型： 外文期刊

作者： Ma, Chen ¹ ; Zhang, Yi ¹ ; Yue, Ruixue ¹ ; Zhang, Wenting ¹ ; Sun, Jian ¹ ; Ma, Zhimin ² ; Niu, Fuxiang ¹ ; Zhu, Hong ¹ ; Liu, Yunfeng ³ ;

作者机构： 1.Xuzhou Inst Agr Sci Jiangsu Xuhuai Dist, Xuzhou, Peoples R China

2.Hebei Acad Agr & Forestry Sci, Inst Cereal & Oil Crops, Shijiazhuang, Peoples R China

3.Hebei Zhongshu Agr Technol Grp Co Ltd, Qinhuangdao, Peoples R China

关键词： sweet potato starch; principal component analysis; analytic hierarchy process; quality evaluation system; evaluation model

期刊名称：FRONTIERS IN NUTRITION （ 影响因子：6.59； 五年影响因子：6.873 ）

ISSN： 2296-861X

年卷期： 2022 年 9 卷

页码：

收录情况： SCI

摘要： BackgroundThe quality of starch greatly affects the quality of processed products. There are many indexes for quality evaluation of starch. Currently, amylose content is considered the chief index in the quality evaluation of sweet potato starch, which is entirely based on tradition (experience) method. The existing evaluation standards lack quality evaluation standards for sweet potato starch. PurposeTo screen reasonable evaluation indexes of sweet potato starch, and establish a scientific and systematic evaluation system of sweet potato starch. MethodsTwenty-two components and quality indexes of sweet potato starch were measured. The evaluation indexes of sweet potato starch were screened based on a statistical description, correlation analysis, and principal component analysis (PCA), and a quality evaluation model of sweet potato starch for brewing was established based on analytic hierarchy process. The calculated values of the model were verified by linear fitting with standardized sensory evaluation values. ResultsThe coefficient of variation of total starch content (%), amylose content (%), amylopectin content (%), L* value, Delta E, water absorption capacity (g/g), and pasting temperature was less than 6%, while the coefficient of variation of other indexes was larger. In addition, there were different degrees of correlation among the indexes. PCA was used to identify interrelated variables, and the first six principal components together account for 82.26% of the total variability. Then, seven core indexes - setback (cp), rate of regression (%), ratio of amylose to amylopectin (%), gel strength (kgf/cm(2)), a* value, ash content (%), and solubility (%) - were selected from the six principal components according to the load value of the rotation matrix. These seven core indexes replaced the original 22 indexes to simplify the evaluation of sweet potato starch. The quality evaluation model of sweet potato starch was Y = 0.034X(2) + 0.321X(6) + 0.141X(8) + 0.08X(17) + 0.023X(19) + 0.08X(21) + 0.321X(22). ConclusionThe comprehensive evaluation system of sweet potato starch can accurately predict the quality of sweet potato starch. The development of such a system is of great significance to the post-harvest processing of high-starch sweet potato and the breeding of high-quality and high-starch sweet potato varieties.