Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination
Abstract
:1. Introduction
2. Cinnamomum sp.
C. verum | C. cassia | C. burmannii | C. loureiroi | |
---|---|---|---|---|
Country where it originates | Sri Lanka | China | Indonesia | Vietnam |
Flavor | Mild Sweet | Bitter Spicy | Spicy | Sweet spicy |
Color | Light reddish brown | Dark reddish brown | Dark reddish brown | Dark reddish brown |
Coumarin content (g/kg) | 0.017 | 0.31 | 2.15 | 6.97 |
2.1. Cinnamon Essential Oil
Compounds | Content (%) | |||
---|---|---|---|---|
Bark | Leaf | |||
C. cassia | C. verum | C. verum | C. cassia | |
1,3-dimethyl-benzene | 0.23 | 0.15 | - | - |
Styrene | 0.19 | 0.14 | - | - |
Benzaldehyde | 0.41 | 0.29 | 0.05 | 0.10 |
Camphene | 0.35 | 0.21 | - | - |
Acetophenone | 0.96 | tr | - | - |
β-Pinene | 0.15 | 0.44 | - | - |
Linalool | 0.68 | - | - | - |
Camphor | 0.97 | 0.53 | - | - |
Benzene propanal | 0.64 | 0.53 | - | - |
Borneol | 0.19 | 0.12 | - | - |
Cis-cinnamaldehyde | 1.95 | 2.29 | - | - |
Trans-cinnamaldehyde | 77.21 | 74.49 | 16.25 | 30.65 |
Eugenol | 0.21 | 7.29 | 79.75 | - |
Geranyl acetate | 0.14 | 0.12 | - | - |
Benzene,1-(1,5-dimethyl-4-hexenyl)-4-methyl | 0.37 | 0.15 | - | - |
Cinnamyl acetate | 0.14 | 0.49 | - | - |
α-muuroleno | 0.47 | 0.11 | - | - |
3-Methoxy-1,2-propanediol | - | - | - | 29.30 |
Cinnamyl alcohol | - | - | 0.07 | 0.65 |
Acetaldehyde | - | - | - | 0.47 |
o-Methoxy cinnamaldehyde | - | - | - | 25.39 |
Coumarin | - | - | 0.05 | 6.36 |
2.2. Adulteration of Cinnamon Essential Oils (CEOs)
3. Methods to Detect Compounds and Adulterations
3.1. Physical
3.2. Sensorial
3.3. Analytical
3.3.1. Spectroscopic
3.3.2. Chromatographic
3.4. DNA Barcoding
3.5. Electronic Nose
- -
- Processing control and product uniformity. Maintaining consistent product quality is paramount in the food industry. Electronic noses enable real-time monitoring of aromas and odors during food processing, helping to ensure product uniformity. By providing instant feedback, they help manufacturers make timely adjustments to maintain desired product attributes.
- -
- Safety of working conditions. The safety of workers in food processing plants is of utmost importance. Electronic noses can detect harmful gases, such as ammonia or volatile organic compounds (VOCs), ensuring that working conditions remain safe. This technology helps prevent exposure to hazardous substances and enhances workplace safety.
- -
- Quality control assessments. Electronic noses are valuable tools for quality control assessments. They can identify subtle differences in aroma profiles, allowing for the precise determination of product freshness and overall quality. This is particularly important in industries where subtle variations greatly affect product value;
- -
- Contamination and maturation of food. Detecting contaminants or spoilage in food products is crucial to preventing health hazards and financial losses. Electronic noses can identify spoilage or contamination by recognizing changes in odor profiles. Additionally, they aid in monitoring the maturation process of foods such as fruits, helping to determine the optimal harvesting time;
- -
- Flavor/odor characteristics. Understanding and replicating desired flavors and aromas are essential in food manufacturing. Electronic noses assist in the analysis of complex flavor and odor characteristics, enabling the creation of products with consistent and appealing sensory attributes;
- -
- Geographical origin and confirmation of botanical origin. The origin of food products is a critical aspect of quality assurance and fraud prevention. Electronic noses can differentiate between products based on their geographical and botanical origins by analyzing unique odor fingerprints associated with specific regions or plant varieties;
- -
- Adulteration and authentication. Food fraud, such as the adulteration of high-value products, poses significant challenges to the industry. Electronic noses can quickly identify counterfeit or adulterated products by detecting inconsistencies in odor profiles, helping to ensure product authenticity;
- -
- Variety and aging. In industries such as tea, coffee, and spices, the variety and aging of products significantly impact their quality and value. Electronic noses play a vital role in characterizing these attributes, helping producers maintain product consistency and meet consumer expectations.
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Cinnamomum Species/Type | Sample | Biological Activity | Result | References |
---|---|---|---|---|
Insecticidal activity | ||||
C. verum | Essential oil | Odontotermes assamensis | 2.5 mg/g | [59] |
C. osmophloeum | Essential oil | Aedes albopictus | 40.8 µg/mL | [60] |
Culex quinquefasciatus | 31.6 µg/mL | |||
A rmigeres subalbatus | 22.1 µg/mL | |||
C. zeylanicum L. | Essential oil | Acanthoscelides obtectus | 46.8 µL/kg | [61] |
C. cassia | Bark extract | Tribolium castaneum | 3.96 µg/adult | [62] |
Lasioderma serricorne | 23.89 µg/adult | |||
Antioxidant activity | ||||
- | Cinnamon powder (raw extract) | ABTS | 1.52 mg/mL | [63] |
Cinnamon powder (in vitro digestion) | 1.18 mg/mL | |||
C. cassia | Extract | DPPH | 10 mg/mL | [64] |
C. burmannii | Essential oil (leave) | DPPH | 100 µg/mL | [65] |
C. cassia | Cinnamon bark oil | DPPH O2 | 10 mg/mL 1 mg/mL | [64] |
C. zeylanicum | Essential oil (leave) | DPPH | 4.78 μg/mL | [66] |
ABTS | 5.21 μg/mL | |||
C. zeylanicum | Extract | ABTS | 1119.9 µmol Trolox/g MS | [67] |
PCL | 177.4 µmol Trolox/g MS | |||
CV | 39.8 µmol Trolox/g MS | |||
Anti-inflammatory activity | ||||
C. osmophloeum | Essential oil (leave) | NO production in RAW 264.7 cells | 9.7 to 65.8 µg/mL | [68] |
C. cassia | Extract | NO production in RAW 264.7 cells | 9.3 to 43 µg/mL | |
Antidiabetic effect | ||||
- | Gelatin capsule with cinnamon powder | Group A: placebo in capsule | 17.4% reduction after 12 weeks | [69] |
Group B: 1000 mg/day of cinnamon powder in capsule form | 10.12% reduction after 6 weeks | |||
- | Cinnamon extract | Rats divided into 5 groups (I—placebo only, II to V extract concentrations) | The highest dose of 200 mg/kg was more effective | [70] |
- | Cinnamon Polyphenols | Mice divided into 5 groups (diabetic model, dimethylbiguanide, low, moderate and high dose of polyphenols) | Treatments with different doses of polyphenols (0.3, 0.6 and 1.2 g/kg/d caused a marked reduction in glucose | [71] |
C. osmophloeum | Essential oil (leave) | Mice were induced with diabetes and then divided into six groups receiving different concentrations of essential oil | All doses tested significantly reduced blood glucose | [72] |
Antimicrobial activity | ||||
C. verum | Essential oil | Staphylococcus hyicus | minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) values ranging from 0.078 to 0.313% | [73] |
C. verum | Essential oil | Streptococcus suis Actinobacillus pleuropneumoniae | MIC and MBC ranging from 0.01 to 0.156% (v/v) | [74] |
C. verum | Essential oil | Candida tropicalis | MIC of 7.8 µL/mL | [75] |
C. cassia | Essential oil | Candida albicans | 65 μg/mL | [76] |
C. cassia | Essential oil | Staphylococcus aureus | 1.25% MIC | [77] |
C. cassia | Essential oil | Escherichia coli, Pseudomonas aeruginosa, and Streptococcus pyogenes | 0.25 to 0.50 mg/mL MIC | [78] |
C. cassia | Essential oil | Aspergillus flavus, Penicillium viridicatum, and Aspergillus carbonarius. | 1.67 to 5.0 µL/mL MIC | [79] |
Types of Gas Sensors | Detection Principle |
---|---|
Acoustics | Frequency change |
Calorimetric | Heat or temperature change |
Catalytic | Electric field change |
Colorimetric | Color change/absorption |
Conductive polymers | Resistance change |
Electrochemicals | Current or voltage change |
Fluorescence | Fluorescent light emission |
Infrared | Infrared radiation absorption |
Metal oxide semiconductors | Resistance change |
Optics | Light modulation, optical changes |
Analysis | Gas Sensor | References |
---|---|---|
Adulteration of lard with chicken fat | Quartz crystal | [139] |
Adulteration of beef with pork | Colorimetric | [140] |
Adulteration of beef with pork | Metal oxide semiconductor | [141] |
Adulteration with inferior quality coffee | Metal oxide semiconductor | [142] |
Adulteration of milk with formalin, hydrogen peroxide and sodium hypochlorite | Metal oxide semiconductor | [143] |
Adulteration of ripe tomato juice with fresh tomato juice | Metal oxide semiconductor | [144] |
Halal Authentication and Verification | Surface acoustic wave | [145] |
Differentiation of Spanish wines | Quartz micro balance | [146] |
Authenticity of geographic origin and classification levels of green tea | Colorimetric | [147] |
Oxidized chicken fat flavor | Metal oxide semiconductor | [148] |
Fresh meat quality | Metal oxide semiconductor | [149] |
Diagnosis of apple juice contamination | Metal oxide semiconductor | [150] |
Determine the concentrations of additives in tangerine juice | Metal oxide semiconductor | [151] |
Evaluation of the quality of oil used for frying | Chemical sensor | [152] |
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Feltes, G.; Ballen, S.C.; Steffens, J.; Paroul, N.; Steffens, C. Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination. Micromachines 2023, 14, 1819. https://doi.org/10.3390/mi14101819
Feltes G, Ballen SC, Steffens J, Paroul N, Steffens C. Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination. Micromachines. 2023; 14(10):1819. https://doi.org/10.3390/mi14101819
Chicago/Turabian StyleFeltes, Giovana, Sandra C. Ballen, Juliana Steffens, Natalia Paroul, and Clarice Steffens. 2023. "Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination" Micromachines 14, no. 10: 1819. https://doi.org/10.3390/mi14101819
APA StyleFeltes, G., Ballen, S. C., Steffens, J., Paroul, N., & Steffens, C. (2023). Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination. Micromachines, 14(10), 1819. https://doi.org/10.3390/mi14101819