Detecting cooking state of grilled chicken by electronic nose and computer vision techniques
•E-nose and computer vision are coupled to evaluate the doneness of grilled chicken.•Appearing VOCs and aerosol particle concentration are analyzed during grilling.•The highest concentration of aerosol is observed at the initial stages of cooking.•Characteristic mass-spectra allow dividing of the gr...
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Published in: | Food chemistry Vol. 345; p. 128747 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
England
Elsevier Ltd
30-05-2021
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Subjects: | |
Online Access: | Get full text |
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Summary: | •E-nose and computer vision are coupled to evaluate the doneness of grilled chicken.•Appearing VOCs and aerosol particle concentration are analyzed during grilling.•The highest concentration of aerosol is observed at the initial stages of cooking.•Characteristic mass-spectra allow dividing of the grilling process into three periods.
Determination of food doneness remains a challenge for automation in the cooking industry. The complex physicochemical processes that occur during cooking require a combination of several methods for their control. Herein, we utilized an electronic nose and computer vision to check the cooking state of grilled chicken. Thermogravimetry, differential mobility analysis, and mass spectrometry were employed to deepen the fundamental insights towards the grilling process. The results indicated that an electronic nose could distinguish the odor profile of the grilled chicken, whereas computer vision could identify discoloration of the chicken. The integration of these two methods yields greater selectivity towards the qualitative determination of chicken doneness. The odor profile is matched with detected water loss, and the release of aromatic and sulfur-containing compounds during cooking. This work demonstrates the practicability of the developed technique, which we compared with a sensory evaluation, for better deconvolution of food state during cooking. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2020.128747 |