Research on Using Electronic Nose to Detect the Quality of Cigarettes

Research on the Quality of Cigarettes Detected by Electronic Nose

Electronic nose, also known as odor scanner, is a novel bionic detection technology that appeared in the late 1980s and early 1990s. It integrates modern high-tech technologies such as electrochemical sensor detection, digital-to-analog conversion, computing technology, chemometrics, and artificial neural networks. All in one, imitating the function of biological senses-nose, can identify and judge various samples with odor, including gas, liquid and solid substances. Compared with other conventional instrumental analysis methods such as gas chromatography, the sample does not require pretreatment, so it basically does not require any organic solvents, and is considered to be a novel green bionic detection technology [1]. Moreover, the analysis is fast and simple. It takes a few minutes to provide timely information about the product. Compared with the olfactory judgment of humans and animals, its measurement is more objective and is not affected by the subjective factors of organisms, the results are more reliable and reproducible. Therefore, its appearance has attracted widespread attention, and is increasingly used in quality assurance (QA) and production process quality control (QC) in beverages, tobacco, food, packaging materials, cosmetics, environment, medicine and other departments. . This paper uses LabStation electronic nose instrument produced by AromaScan in the UK to conduct a preliminary study on the quality identification of domestic cigarettes. Although there are reports on the use of electronic noses to distinguish different tobaccos in the literature [3, 4], no similar reports have been seen in distinguishing different grades of cigarettes and judging their authenticity.

1 Experimental part 1.1 Instrument LabStation electronic nose of AromaScan, UK, with an array of 32 sensors and PCA and data processing and image recognition software.

1. 2 samples of authentic and authentic cigarettes of Ashima and Golden Mango are provided by Henan Tobacco Quality Inspection Station. The top grade Yunyan and ordinary Yunyan are provided by Yunnan Kunming Cigarette Factory. Before the test, the samples are stored in a sealed place at room temperature and protected from light. Cigarettes after sampling are still sealed with adhesive tape and stored for later use. Take 3 cigarettes at a time, take out the cut tobacco and mix it into the sample tube.

The distilled water used to adjust the humidity of the carrier gas during the test was purified and prepared by MilliQ water purifier from Millipore.

1. 3 Experimental conditions The temperature of the sample chamber is 30 ° C, the relative humidity is 20-50, and the analysis period of one sample is 2 min. The reference gas is pre-equilibrated for 15 sec, the sample is injected for 60 sec, the flushing is for 30 sec, and the reference gas is rebalanced for 15 sec. In order to ensure the stability, reliability and representativeness of the data, the number of repeated measurements for each sample is more than 5 times.

1. 4 Data processing All the original data were imaged using PCA and Sammon Mapping methods, and the results were compared. 2. Results and discussion 2. 1 Identification of genuine and fake cigarette products. We have determined the characteristics of Ashima smoke and Golden Mango smoke. Authentic and fake. Using dynamic headspace method, the experimental results show that there are obvious differences between genuine and fake cigarettes. In Figure 1, the genuine gold mango cigarettes are concentrated in the left area of the figure and the fakes are concentrated in the right area. The QF value is 3.934 (when the QF value is 2, the sample is not much different and can be regarded as a category). It is worth noting that the hollow experimental points in Figure 1 are far away from other similar experimental points. After inspection, these hollow experimental points are the first experimental results of each sample, indicating that the measurement system has not yet reached full equilibrium. . Therefore, ensuring that the system is fully balanced is the primary condition for obtaining reliable data.

2. Judgment of cigarette grades Under the same experiDisposable Vape, Electronic Cigarettes, vapemental conditions, three samples of Yunyan Premium, Common Products and Trial Products provided by Kunming Cigarette Factory of Yunnan were tested, and the results were also satisfactory. Figure 2 shows the measurement results of Yunyan Premium and ordinary products. Yunyan Premium is in the left area, while ordinary products are in the right area. The difference between the two is very obvious. The QF value is 13.995.

Identification of PCA (▲) and counterfeit () PCA identification chart (▲) and Need () identification PCA identification chart We compared the application of two dimensionality reduction and image display methods in cigarette quality identification. The processing results of the experimental data of golden mango real and fake products are shown in Table 1, and the comparison of the results of Yunyan Extreme Products and ordinary products is shown in Table 2.

Method Normalized correlation matrix intensity normalized automatic calibration. From the data in Table 1 and Table 2, compared with cigarette quality and grade evaluation, PCA and Sammon Mapping can be used for data dimensionality reduction and image recognition. Among them, PCA technology has three methods of normalization (normalize data), correlation matrix (correlation matrix) and automatic scaling (autoscale data). The Sammon Mapping method can be divided into normalization. From the data in the above table, it can be seen that the QF value of the same sample after using different methods to process the data is different. So generally choose the data processing method that can get the maximum QF value.

2.4 Inspection of the reproducibility of the method In order to investigate the reproducibility of the method, we sampled and measured the authentic and counterfeit products of Asma separately, and then measured them again after 3 days, 7 days, 14 days, and 22 days. As shown in Figure 3. Figure 3 shows the reproducibility of Ashima Zhen and counterfeit products. The data was fairly concentrated during the first 7 days. If S is used for samples, the subscript indicates the number of days between. The QF values of S and S data are compared with each other and it is found that the value of S is less than 2, and the value of S is normalized. The correlation matrix intensity normalized automatic calibration is greater than 2 , Indicating that the nature of the sample changed after one week. The same situation occurs in counterfeit products, and the degree of divergence and deviation shown is greater than that of genuine products, as shown in Table 3. However, the distribution areas of genuine and counterfeit products still show obvious differences, and the QF values between them are greater than 4.

▲ (△), (□), ◆ (◇), (○) represent the measurement results of the first day, 3 days, 7 days, 14 days, and 22 days. The solid points are the real data, and the hollow points are the fake data sample pairs ( Authentic product) Interval days sample pair (genuine product) Interval days 3 Conclusion Electronic nose is a fast, simple and novel detection instrument. Compared with ordinary component analysis instruments, it does not require sample preparation, little or no organic solvent. , Can quickly provide the overall information of the tested sample, indicating the hidden characteristics of the sample. The experimental results prove that it can be used to identify whether the product is qualified and graded in the tobacco industry, whether the production process is stable and normal, and the authenticity of market products. It is one of the indispensable tools for QA and QC determination.

Acknowledgements This work is provided by the Beijing office of Louis Enterprise Co., Ltd., and special thanks are given.

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[7] Yang Ruina, Hu Xiaoyuan, Jin Douman. Journal of Inorganic Chemistry, 1999, 15: 697 ～ 708.

(Continued from page 53) [1] Huang Junxiong, Tian Lijuan. Modern Instrument Application and Maintenance, 1991, 1: 6.