电子鼻
质量评定
主成分分析
食品科学
调料品
感官分析
气味
电子舌
仿形(计算机编程)
芳香
模式识别(心理学)
原材料
食品质量
环境科学
嗅觉测定
人工智能
传感器阵列
食品加工
食品
品味
己醛
计算机科学
作者
Kornkanok Chujan,Varanya Somaudon,Teerakiat Kerdcharoen
标识
DOI:10.1109/icpei66116.2025.11282680
摘要
Seasonings such as fish sauce, seasoning sauce, soy sauce, and oyster sauce are essential for augmenting taste and fragrance in culinary practices. Their sensory attributes are shaped by ingredients, fermentation, and production techniques. Conventional sensory evaluation techniques dependent on human panels frequently exhibit subjectivity and inconsistency. This study utilizes an electronic nose (e-nose) with eight sensors to detect volatile organic compounds (VOCs) emitted from four types of spice sauces. Principal Component Analysis (PCA) was employed to examine sensor responses, derive aromatic characteristics, and classify scent profiles. The findings indicate that the electronic nose successfully differentiated among sauce varieties, with Sensor 4 exhibiting the greatest sensitivity to critical volatile organic chemicals, including sulfur compounds and amines. PCA demonstrated clear clustering patterns among samples, indicating variations in raw materials and processing methods. These findings validate the efficacy of e-nose technology as a dependable instrument for product categorization, differentiation, and quality assurance in the food sector. The integration of sensor-based VOC detection with statistical modeling underscores the potential for real-time quality evaluation in food production settings.
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