Method for researching correlation between sweet substances in rose essential oil and sensor based on electronic nose
By using grey relational analysis and electronic nose technology, aroma substances related to sweetness were screened out, solving the subjective problem of traditional tobacco sweetness evaluation and realizing objective and efficient detection of sweet aroma, thus supporting tobacco production and quality control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ANHUI JIAOTIANXIANG BIOTECHNOLOGY CO LTD
- Filing Date
- 2026-01-08
- Publication Date
- 2026-05-01
AI Technical Summary
Traditional tobacco sweetness evaluation relies on human sensory evaluation, which is highly subjective and inefficient. Furthermore, electronic noses lack targeted screening methods for sweetness-related substances, and the correlation between sensor selection and aroma substances is unclear.
By combining grey relational analysis and sensory evaluation, aroma compounds that are significantly associated with sweetness are screened out. An electronic nose is then used to identify the sensor with the strongest correlation to sweetness compounds, and a rapid detection system is constructed.
It enables objective and efficient evaluation of sweet aroma, supports rapid quantitative detection in tobacco production and quality control, and expands its application to the standardized evaluation of tobacco flavor characteristics.
Smart Images
Figure CN121955291A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of tobacco flavor technology, specifically relating to a method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose. Background Technology
[0002] Sweetness is one of the evaluation criteria in cigarette sensory assessment. In cigarette quality assessment, descriptions such as "clean and comfortable aftertaste with a sweet and refreshing sensation" are often used to describe the sensory experience of sweetness. Sweetness is an important evaluation criterion in sensory quality.
[0003] According to the "YC / T496-2014 Method for Evaluating Sensory Comfort of Cigarettes," sensory comfort consists of sensory quality indicators such as oral cavity, throat, nasal cavity, smoke sensation, and aroma sensation. Current research on sweetness mainly focuses on the impact of carbon and nitrogen metabolites on the sweetness of cured tobacco leaves and on improving the sensory quality of tobacco by adding different natural plant extracts or additives. Research on aroma substances that contribute to the formation of sweetness is relatively limited.
[0004] The evaluation of the sweetness of traditional tobacco relies on human sensory assessment, which is highly subjective and inefficient. While electronic noses can be used to detect tobacco aroma, they lack targeted screening methods for sweetness-related characteristic substances, and the correlation between sensor selection and aroma compounds is unclear. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention provides a method for studying the correlation between sweet and moist substances in rose essential oil and sensors based on an electronic nose. The aim is to combine grey relational analysis and sensory evaluation to screen out aroma substances and other sensory qualities that are significantly related to sweetness, and to use an electronic nose to identify the sensor with the strongest correlation to sweet and moist substances, thereby constructing a rapid detection system to achieve an objective and efficient evaluation of sweet and moist aroma.
[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0007] This invention provides a method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, the method comprising the following steps:
[0008] 1) The main sweet aroma substances in rose essential oil were added to cigarettes. The sweetness and other sensory qualities of the cigarettes were rated according to the "YC / T496-2014 Evaluation Method for Sensory Comfort of Cigarettes". The aroma substances that are significantly related to the sweetness were screened by combining grey relational analysis.
[0009] 2) The aroma substances that are significantly related to sweetness are selected and prepared into solutions with different concentration gradients according to the subthreshold, threshold and superthreshold of each substance. The odor intensity of the solutions is scored and arranged in order of low to high concentration on the electronic nose sample plate. Different sensors are used for detection and the original response data values of each sensor to each solution are obtained.
[0010] 3) Correlation analysis was performed on the raw response data of each solution using SPSS software to obtain the Pearson correlation coefficient r between the odor intensity of each aroma substance and each sensor. Based on the Pearson correlation coefficient r, the sensor most correlated with the odor intensity of each sweet substance was found.
[0011] In step 1), the main sweet aroma substances in the rose essential oil are rose ether, β-damasone, geraniol acetone, nerol acetate, geraniol acetate, β-caryophyllene, myrcene, vanillyl ester formate, β-dihydroionone, citronellol, geraniol, phenethyl alcohol, nerol, linalool, ocimene, citral, farnesol, and limonene.
[0012] In step 1), the grey relational analysis is as follows:
[0013] The sweetness score of each sample was selected as the reference series, denoted as x0; other sensory qualities of each sample were selected as the comparison series, denoted as x0. i After dimensionless transformation of all data, the grey relational coefficient is calculated according to the following formula:
[0014]
[0015] Where k is the index of the different samples; x i These are the sensory quality values of different samples, excluding sweetness; It is the minimum difference between two levels, i.e., Δmin; It is the maximum difference between the two levels, i.e., Δmax; |x0(k)-x i (k)| is the absolute difference between the reference sequence and the comparison sequence, i.e., Δ(y); in order to reduce the distortion caused by excessive absolute difference, ρ is introduced as the resolution coefficient, which is set to 0.5 here; when the gray relational degree is greater than 0.6, the judgment result is considered to be good.
[0016] In step 2), the aroma compounds that were significantly associated with sweetness were rose ether, geraniol acetate, β-dihydroionone, and farnesol.
[0017] In step 2), a 3% propylene glycol aqueous solution is used to prepare solutions of aroma substances that are significantly related to sweetness into different concentration gradients.
[0018] In step 2), the odor intensity is scored as follows: the sensory group uses 1-butanol as a reference to score the odor intensity at each concentration point and takes the average value.
[0019] In step 2), the sensors used for detection are WLSGF / A, WLSGF / B, WLSGF / C, WLSGF / D, WLSGF / E, WLSGF / F, WMSGF / A, WMSGF / B, WMSGF / C, WMSGF / D, WMSGF / E, WMSGF / F, WHSGF / A, WHSGF / B, WHSGF / C, WHSGF / D, WHSGF / E, and WHSGF / F, totaling 18 sensors.
[0020] In step 2), the electronic nose is the FOX6000 electronic nose analysis system manufactured by Alpha MOS.
[0021] In step 2), the electronic nose has a collection time of 120s, a flow rate of 150mL / min, an injection volume of 500μL, an injection speed of 500μL / s, an incubation period of 150s, an incubation temperature of 40℃, a cleaning time of 120s, a syringe temperature of 50℃, and a filling temperature of 500μL / s.
[0022] In step 3), when the Pearson correlation coefficient r > 0, it indicates that the odor intensity is positively correlated with the sensor.
[0023] When the absolute value of r is ≥0.8, it indicates that the odor intensity is highly correlated with the sensor.
[0024] When the absolute value of r is between 0.5 and 0.8 and not equal to 0.8, it indicates that the odor intensity is moderately correlated with the sensor.
[0025] When the absolute value of r is between 0.3 and 0.5 and not equal to 0.5, it indicates that the odor intensity is poorly correlated with the sensor.
[0026] When the absolute value of r is between 0 and 0.3 and not equal to 0.3, it indicates that the two variables are basically uncorrelated.
[0027] Compared with the prior art, the present invention has the following beneficial effects:
[0028] This invention rates the sweetness and other sensory qualities of cigarettes according to the "YC / T496-2014 Method for Evaluating Sensory Comfort of Cigarettes". Combining grey relational analysis, it objectively screens aroma substances significantly related to sweetness, overcoming the subjectivity problem of traditional methods. Furthermore, utilizing the strong linear relationship between electronic nose sensors and sweet substances, it identifies the sensors most correlated with the odor intensity of aroma substances significantly related to sweetness, constructing a rapid detection system to achieve objective and efficient evaluation of sweet aroma. This allows for rapid quantitative detection of sweet substances in tobacco production, quality control, and product development.
[0029] The method provided by this invention for studying the correlation between sweet substances in rose essential oil and sensors based on electronic nose can also be extended to the standardized evaluation of other tobacco flavor characteristics, thereby achieving quality control and efficient research and development in tobacco production. Attached Figure Description
[0030] Figure 1 A graph showing the correlation between the odor intensity of rose ether and the electronic nose sensor;
[0031] Figure 2 Histogram of rose ether and WLSGF / A sensor;
[0032] Figure 3 This is a normal PP plot of the regression-standardized residuals of rose ether and the WLSGF / A sensor. Detailed Implementation
[0033] The present invention will now be described in detail with reference to the embodiments.
[0034] Example
[0035] A method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose includes the following steps:
[0036] 1) The main sweet aroma substances contained in rose essential oil were added to the cigarettes. The sweet aroma substances are rose ether, β-damascone, geraniol, nerol acetate, geraniol acetate, β-caryophyllene, myrcene, vanillyl formate, β-dihydroionone, citronellol, geraniol, phenethyl alcohol, nerol, linalool, ocimene, citral, farnesol, and limonene. The sweetness and other sensory qualities of the cigarettes were rated according to the "YC / T496-2014 Method for Evaluation of Sensory Comfort of Cigarettes". The rating data are shown in Table 1.
[0037] Table 1 Sensory Evaluation Table for Cigarettes - 1
[0038]
[0039] Table 2 Sensory Evaluation Table for Cigarettes - 2
[0040]
[0041] As shown in Tables 1 and 2, rose ether, geraniol acetate, β-dihydroionone, and farnesol have the best sweetness. Among them, β-dihydroionone has the highest response to sweetness. Rose ether and geraniol acetate have good responses to sweetness, delicacy, and aroma. Farnesol has a weaker response to delicacy and aroma, which may be due to its higher aroma threshold, resulting in a lower aroma vitality value. However, farnesol itself has a variety of aromas, including floral, green, woody, and sweet, which are harmonious and mellow, and have a high sweetness when smoked.
[0042] Grey relational analysis was used to screen out other sensory quality indicators that are significantly related to sweetness. The specific process of grey relational analysis is as follows:
[0043] The sweetness score of each sample was selected as the reference series, denoted as x0; other sensory qualities of each sample were selected as the comparison series, denoted as x0. i Since aroma substances have no significant effect on the stimulation indicators of the oral cavity, the acidity and bitterness indicators of taste in the oral cavity, the stimulation indicators of the nasal cavity, and the coordination indicators of smoke perception, the grey relational degree is not calculated. After dimensionless transformation of all other data, the grey relational coefficient is calculated according to the following formula:
[0044] Where k is the index of a different sample; x i These are the sensory quality values of different samples, excluding sweetness; It is the minimum difference between two levels, i.e., Δmin; It is the maximum difference between the two levels, i.e., Δmax; |x0(k)-x i (k)| is the absolute difference between the reference sequence and the comparison sequence, i.e., Δ(y); to reduce distortion caused by excessive absolute difference, ρ is introduced as the resolution coefficient, which is set to 0.5 here; when the gray relational degree is greater than 0.6, the judgment result is considered to be good. The results are shown in Table 3.
[0045] Table 3. Grey Relational Analysis of Sweetness and Other Sensory Indicators
[0046]
[0047] The results showed that all other indicators, except for residue, were significantly related to sweetness. Among them, sweetness, delicacy, and aroma were highly correlated with sweetness, reaching 0.988, 0.966, and 0.968, respectively.
[0048] 3) The selected rose ether, geraniol acetate, β-dihydroionone and farnesol were used to prepare solutions with different concentration gradients in 3% propylene glycol aqueous solution according to the subthreshold, threshold and superthreshold of each substance;
[0049] Rose ether was diluted to prepare solutions with concentrations of 0.4 mg / kg, 0.8 mg / kg, 1.5 mg / kg, 3.0 mg / kg, 6.0 mg / kg, 12.1 mg / kg, 24.2 mg / kg, 48.4 mg / kg, 96.8 mg / kg, and 193.6 mg / kg, respectively.
[0050] Geraniol acetate was diluted to prepare solutions with concentrations of 5.2 mg / kg, 10.4 mg / kg, 20.8 mg / kg, 41.6 mg / kg, 83.2 mg / kg, 166.5 mg / kg, 333.0 mg / kg, 665.9 mg / kg, 1331.8 mg / kg, and 2663.6 mg / kg.
[0051] β-Dihydroionone was diluted to solutions with concentrations of 3.8 mg / kg, 7.6 mg / kg, 15.3 mg / kg, 30.6 mg / kg, 61.2 mg / kg, 122.4 mg / kg, 244.7 mg / kg, 489.5 mg / kg, 978.9 mg / kg, and 1957.9 mg / kg.
[0052] Farnesol was diluted to prepare solutions with concentrations of 13.9 mg / kg, 27.8 mg / kg, 55.6 mg / kg, 111.2 mg / kg, 222.4 mg / kg, 444.7 mg / kg, 889.4 mg / kg, 1778.8 mg / kg, 3557.6 mg / kg, and 7115.2 mg / kg.
[0053] The odor intensity was scored at 10 concentration points for each substance. The sensory panel used 1-butanol as a reference to score the odor intensity from 0 (no) to 10 (very strong) and took the average value. The scoring criteria reference is as follows: AANASOVA B, ANGLOIS D, NIKLAUS S, et al. Evaluation of olfactory intensity: comparative study of two methods [J]. Journal of Sensory Studies, 2004, 19(4): 307-326.
[0054] Take 2 ml of the sample to be tested and place it on the electronic nose sample plate in order of concentration from low to high for detection. The response data values of 18 sensors for each substance at different concentrations are obtained. The response data values are shown in Table 3. Among them, substance 1 represents rose ether, substance 2 represents geraniol acetate, substance 3 represents β-dihydroionone, and substance 4 represents farnesol.
[0055] Table 4. Odor intensity of sweet substances and response data of electronic nose sensor -1
[0056]
[0057] Continued from Table 4
[0058]
[0059] Table 5. Odor intensity of sweet substances and response data of electronic nose sensor -2
[0060]
[0061] Continued from Table 5
[0062]
[0063] 3) The response data values in Tables 4 and 5 were analyzed using SPSS software. The degree of correlation can be seen from the magnitude of the correlation coefficient. Pearson correlation coefficient r: (1) When r>0, it indicates that the two variables are positively correlated; (2) When the absolute value of r>=0.8, it indicates that the two variables are highly correlated; (3) When the absolute value of r is between 0.5 and 0.8, it indicates that the two variables are moderately correlated; (4) When the absolute value of r is between 0.3 and 0.5, it indicates that the two variables are poorly correlated; (5) When the absolute value of r is between 0 and 0.3, it indicates that the two variables are basically uncorrelated. Table 4-7 only lists the electronic nose sensors that are positively correlated with the odor intensity of aroma substances.
[0064] The analysis results are shown in Table 6-9:
[0065] Table 6
[0066]
[0067] As shown in Table 6, rose ether is highly positively correlated with the WLSGF / A sensor, with a correlation coefficient of 0.951.
[0068] Table 7
[0069]
[0070] As shown in Table 7, geraniol acetate is moderately positively correlated with the WLSGF / A sensor, with a correlation coefficient of 0.578.
[0071] Table 8
[0072]
[0073] As shown in Table 8, β-dihydroionone is moderately positively correlated with the sensors WLSGF / A, WMSGF / B, WMSGF / C, and WMSGF / E, with correlation coefficients of 0.541, 0.533, 0.545, and 0.535, respectively.
[0074] Table 9
[0075]
[0076] As shown in Table 9, farnesol is weakly correlated with the sensors WLSGF / C and WLSGF / B, with correlation coefficients of 0.399 and 0.347, respectively.
[0077] As shown above, rose ether, geraniol acetate, and β-dihydroionone are all positively correlated with the WLSGF / A sensor, with rose ether exhibiting the highest correlation at 0.951. Farnesol, however, only shows a low correlation with WLSGF / C. Its difference from the other three sweet substances may be due to its lack of finesse and aroma, and because its odor threshold is relatively high, the sensory panel could not accurately grasp its odor changes, resulting in a non-linear relationship between the odor intensity perceived by the artificial senses and the sensor's response value.
[0078] 4) Select the rose ether with the highest correlation coefficient and the sensor WLSGF / A, and establish scatter plots of rose ether odor intensity versus electronic nose sensor, histograms of rose ether odor intensity versus WLSGF / A, and normal PP plots of standardized residuals.
[0079] Figure 1 The scatter plot shows that the odor intensity of rose ether is linearly related to the electronic nose sensor, and the correlation is quite high.
[0080] Figure 2 histogram and Figure 3 The residual normal PP plot shows that the odor intensity of rose ether is normally distributed with respect to the sensor WLSGF / A.
[0081] In summary, the present invention provides a method for studying the correlation between sweet and moist substances in rose essential oil and sensors based on an electronic nose. It reveals that the sweetness is highly correlated with sweetness, delicacy, and aroma, and is also highly correlated with rose ether, geraniol acetate, β-dihydroionone, and farnesol. The electronic nose sensor WLSGF / A shows a high correlation with most sweet and moist substances, and can respond to the sweetness of aroma substances to a certain extent. This method is simple, quick, and provides intuitive and reliable results.
[0082] The above-described detailed description of a method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose is illustrative rather than limiting. Several embodiments may be listed within the defined scope. Therefore, variations and modifications that do not depart from the overall concept of the present invention should be within the protection scope of the present invention.
Claims
1. A method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, characterized in that, The method includes the following steps: 1) The main sweet aroma substances in rose essential oil were added to cigarettes. The sweetness and other sensory qualities of the cigarettes were rated according to the "YC / T496-2014 Evaluation Method for Sensory Comfort of Cigarettes". The aroma substances that are significantly related to the sweetness were screened by combining grey relational analysis. 2) The aroma substances that are significantly related to sweetness are selected and prepared into solutions with different concentration gradients according to the subthreshold, threshold and superthreshold of each substance. The odor intensity of the solutions is scored and arranged in order of low to high concentration on the electronic nose sample plate. Different sensors are used for detection and the original response data values of each sensor to each solution are obtained. 3) Correlation analysis was performed on the raw response data of each solution using SPSS software to obtain the Pearson correlation coefficient r between the odor intensity of each aroma substance and each sensor. Based on the Pearson correlation coefficient r, the sensor most correlated with the odor intensity of each sweet substance was found.
2. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1, is characterized in that... In step 3), when the Pearson correlation coefficient r > 0, it indicates that the odor intensity is positively correlated with the sensor. When the absolute value of r is ≥0.8, it indicates that the odor intensity is highly correlated with the sensor. When the absolute value of r is between 0.5 and 0.8 and not equal to 0.8, it indicates that the odor intensity is moderately correlated with the sensor. When the absolute value of r is between 0.3 and 0.5 and not equal to 0.5, it indicates that the odor intensity is poorly correlated with the sensor. When the absolute value of r is between 0 and 0.3 and not equal to 0.3, it indicates that the two variables are basically uncorrelated.
3. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 1), the main sweet aroma substances in the rose essential oil are rose ether, β-damasone, geraniol acetone, nerol acetate, geraniol acetate, β-caryophyllene, myrcene, vanillyl ester formate, β-dihydroionone, citronellol, geraniol, phenethyl alcohol, nerol, linalool, ocimene, citral, farnesol, and limonene.
4. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 1), the grey relational analysis is as follows: The sweetness score of each sample was selected as the reference series, denoted as x0; other sensory qualities of each sample were selected as the comparison series, denoted as x0. i After dimensionless transformation of all data, the grey relational coefficient is calculated according to the following formula: ； Where k is the index of the different samples; x i These are the sensory quality values of different samples, excluding sweetness; It is the minimum difference between two levels, i.e., Δmin; It is the maximum difference between the two levels, i.e., Δmax; |x0(k)-x i (k)| is the absolute difference between the reference sequence and the comparison sequence, i.e., Δ(y); in order to reduce the distortion caused by excessive absolute difference, ρ is introduced as the resolution coefficient, which is set to 0.5 here; when the gray relational degree is greater than 0.6, the judgment result is considered to be good.
5. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 2), the aroma compounds that were significantly associated with sweetness were rose ether, geraniol acetate, β-dihydroionone, and farnesol.
6. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 2), a 3% propylene glycol aqueous solution is used to prepare solutions of aroma substances that are significantly related to sweetness into different concentration gradients.
7. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 2), the odor intensity is scored as follows: the sensory group uses 1-butanol as a reference to score the odor intensity at each concentration point and takes the average value.
8. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 2), the sensors used for detection are WLSGF / A, WLSGF / B, WLSGF / C, WLSGF / D, WLSGF / E, WLSGF / F, WMSGF / A, WMSGF / B, WMSGF / C, WMSGF / D, WMSGF / E, WMSGF / F, WHSGF / A, WHSGF / B, WHSGF / C, WHSGF / D, WHSGF / E, and WHSGF / F, totaling 18 sensors.
9. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose, as described in claim 1 or 2, is characterized in that... In step 2), the electronic nose is the FOX6000 electronic nose analysis system manufactured by Alpha MOS.
10. The method for studying the correlation between sweet substances in rose essential oil and sensors based on an electronic nose according to claim 1 or 2, characterized in that, In step 2), the electronic nose has a collection time of 120s, a flow rate of 150mL / min, an injection volume of 500μL, an injection speed of 500μL / s, an incubation period of 150s, an incubation temperature of 40℃, a cleaning time of 120s, a syringe temperature of 50℃, and a filling temperature of 500μL / s.