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基于模糊数学感官评价法沙棘饼干烘焙工艺优化
引用本文:崔立柱,付依依,刘士伟,王永霞,谭志超,段盛林.基于模糊数学感官评价法沙棘饼干烘焙工艺优化[J].食品工业科技,2021,42(15):163-169.
作者姓名:崔立柱  付依依  刘士伟  王永霞  谭志超  段盛林
作者单位:1.中国食品发酵工业研究院有限公司,北京 1000152.河北工程大学生命科学与食品工程学院,河北邯郸 0560383.张北宝得康食品有限公司,河北张家口 076450
基金项目:河北省重点研发计划项目(19223002D)
摘    要:为提高沙棘饼干的品质,运用模糊数学感官评价法,以感官得分为评价指标,研究烘焙时间、上下火温度对其感官指标的影响,通过响应面法对其烘焙条件进行优化。利用电子舌、电子鼻对沙棘饼干的品质进行分析对比分析。结果表明,沙棘饼干最佳烘焙条件为:上火温度175 ℃、下火温度167.5 ℃、烘焙时间13 min。在此条件下,沙棘饼干的感官评分为77.89。电子感官结果表明,电子舌对沙棘饼干与市售饼干分析显示其差异主要存在于酸味、甜味、咸味、鲜味上,差异显著,说明电子舌分析结果可以区分不同样品饼干。电子鼻分析显示其差异主要存在于PA/2(食品鲜度传感器)、P30/1(酸败气味传感器),主成分分析累计方差贡献率达到99.40%,说明电子鼻能准确区分沙棘饼干于市售样品。

关 键 词:沙棘    饼干    模糊数学感官评价    电子感官评价
收稿时间:2020-10-12

Optimization for Baking Process of Sea-Buckthorn Biscuits Based on Sensory Evaluation of Fuzzy Mathematics
CUI Lizhu,FU Yiyi,LIU Shiwei,WANG Yongxia,TAN Zhichao,DUAN Shenglin.Optimization for Baking Process of Sea-Buckthorn Biscuits Based on Sensory Evaluation of Fuzzy Mathematics[J].Science and Technology of Food Industry,2021,42(15):163-169.
Authors:CUI Lizhu  FU Yiyi  LIU Shiwei  WANG Yongxia  TAN Zhichao  DUAN Shenglin
Affiliation:1.China National Research Institute of Food & Fermentation Industries Co., Ltd., Beijing 100015, China2.Hebei University of Engineering, Handan 056038, China3.Zhangbei Baodekang Food Co., Ltd., Zhangjiakou 076450, China
Abstract:To improve the quality of sea-buckthorn biscuits, the effect of baking time, surface and bottom heating temperature on the quality of sea-buckthorn biscuits by using the sensory score as a evaluation index based on the sensory evaluation method of fuzzy mathematics. The baking conditions were optimized by response surface methodology (RSM). The quality of sea-buckthorn biscuit was analyzed by electronic tongue and electronic nose. The results showed that, the optimal baking conditions of sea-buckthorn biscuits were as follows: surface temperature 175 ℃, bottom temperature 167.5 ℃, and baking time 13 min. In this condition, the sensory scores of sea-buckthorn biscuits was 77.89. The analysis of the taste of Sea-buckthorn biscuits by electronic tongue showed that the difference mainly existed in the sour, sweet, salty and umami taste, significant difference results, which indicated that the results of electronic tongue analysis could completely distinguish different samples. The results of electronic nose showed that the main differences were PA/2 (Umami sensor) and P30/1 (Rancidity odor sensor), the cumulative variance contribution rate of principal component analysis was 99.40%, which indicated that the electronic nose could distinguish different Sea-buckthorn biscuits and commercial samples accurately.
Keywords:
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