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

doi:10.13386/j.issn1002-0306.2020100038

Volume 42 Issue 15

Jul. 2021

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Science and Technology of Food Industry > 2021 > 42(15): 163-169. > DOI: 10.13386/j.issn1002-0306.2020100038

CUI Lizhu, FU Yiyi, LIU Shiwei, et al. 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. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020100038.

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Optimization for Baking Process of Sea-Buckthorn Biscuits Based on Sensory Evaluation of Fuzzy Mathematics

1.
China National Research Institute of Food & Fermentation Industries Co., Ltd., Beijing 100015, China
2.
Hebei University of Engineering, Handan 056038, China
3.
Zhangbei Baodekang Food Co., Ltd., Zhangjiakou 076450, China

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Received Date: October 11, 2020
Available Online: June 02, 2021

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Abstract

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.
- Sea-buckthorn,
- biscuits,
- fuzzy mathematics sensory evaluation,
- electronic sensory evaluation

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References (22)

References

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