TY - GEN
T1 - "Application of Electronic Nose Technology for Aroma Profiling and Quality Assessment of Seasonings"
AU - Chujan, Kornkanok
AU - Somaudon, Varanya
AU - Kerdcharoen, Teerakiat
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Aroma Profiling
KW - Electronic Nose
KW - Seasoning
KW - Sensor Response
KW - Volatile Organic Compounds (VOCs)
UR - https://www.scopus.com/pages/publications/105031732553
U2 - 10.1109/ICPEI66116.2025.11282680
DO - 10.1109/ICPEI66116.2025.11282680
M3 - Conference contribution
AN - SCOPUS:105031732553
T3 - 2025 7th International Conference on Power, Energy and Innovations, ICPEI 2025 - Proceedings
BT - 2025 7th International Conference on Power, Energy and Innovations, ICPEI 2025 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Power, Energy and Innovations, ICPEI 2025
Y2 - 15 October 2025 through 17 October 2025
ER -