Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination
This study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consum...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/14/10/1819 |
| _version_ | 1797572933527273472 |
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| author | Giovana Feltes Sandra C. Ballen Juliana Steffens Natalia Paroul Clarice Steffens |
| author_facet | Giovana Feltes Sandra C. Ballen Juliana Steffens Natalia Paroul Clarice Steffens |
| author_sort | Giovana Feltes |
| collection | DOAJ |
| description | This study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consumer confidence. Through the utilization of physical–chemical and instrumental analyses, the purity of EOs was evaluated via qualitative and quantitative assessments, enabling the identification of constituents or compounds within the oils. Consequently, a diverse array of techniques has been documented, encompassing organoleptic, physical, chemical, and instrumental methodologies, such as spectroscopic and chromatographic methods. Electronic noses (e-noses) exhibit significant potential for identifying cinnamon adulteration, presenting a rapid, non-destructive, and cost-effective approach. Leveraging their capability to detect and analyze volatile organic compound (VOC) profiles, e-noses can contribute to ensuring authenticity and quality in the food and fragrance industries. Continued research and development efforts in this domain will assuredly augment the capacities of this promising avenue, which is the utilization of Artificial Intelligence (AI) and Machine Learning (ML) algorithms in conjunction with spectroscopic data to combat cinnamon adulteration. |
| first_indexed | 2024-03-10T21:02:40Z |
| format | Article |
| id | doaj.art-841acaa2498a4ed8b7d7be64dcdd7a33 |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-10T21:02:40Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-841acaa2498a4ed8b7d7be64dcdd7a332023-11-19T17:23:16ZengMDPI AGMicromachines2072-666X2023-09-011410181910.3390/mi14101819Differentiating True and False Cinnamon: Exploring Multiple Approaches for DiscriminationGiovana Feltes0Sandra C. Ballen1Juliana Steffens2Natalia Paroul3Clarice Steffens4Department of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, BrazilDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, BrazilDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, BrazilDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, BrazilDepartment of Food Engineering, Universidade Regional Integrada do Alto Uruguai e das Missões, Av. Sete de Setembro, 1621, Erechim 99709-910, BrazilThis study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consumer confidence. Through the utilization of physical–chemical and instrumental analyses, the purity of EOs was evaluated via qualitative and quantitative assessments, enabling the identification of constituents or compounds within the oils. Consequently, a diverse array of techniques has been documented, encompassing organoleptic, physical, chemical, and instrumental methodologies, such as spectroscopic and chromatographic methods. Electronic noses (e-noses) exhibit significant potential for identifying cinnamon adulteration, presenting a rapid, non-destructive, and cost-effective approach. Leveraging their capability to detect and analyze volatile organic compound (VOC) profiles, e-noses can contribute to ensuring authenticity and quality in the food and fragrance industries. Continued research and development efforts in this domain will assuredly augment the capacities of this promising avenue, which is the utilization of Artificial Intelligence (AI) and Machine Learning (ML) algorithms in conjunction with spectroscopic data to combat cinnamon adulteration.https://www.mdpi.com/2072-666X/14/10/1819discriminationphysical–chemical analysisinstrumental analysisauthenticityquality assurancefood industry |
| spellingShingle | Giovana Feltes Sandra C. Ballen Juliana Steffens Natalia Paroul Clarice Steffens Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination Micromachines discrimination physical–chemical analysis instrumental analysis authenticity quality assurance food industry |
| title | Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination |
| title_full | Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination |
| title_fullStr | Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination |
| title_full_unstemmed | Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination |
| title_short | Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination |
| title_sort | differentiating true and false cinnamon exploring multiple approaches for discrimination |
| topic | discrimination physical–chemical analysis instrumental analysis authenticity quality assurance food industry |
| url | https://www.mdpi.com/2072-666X/14/10/1819 |
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