Infrared and Terahertz Spectra of Pu’er White Tea with Different Degrees of Oxidation

Wu, Dong-Mei; Guo, Jie; Sun, Ming-Ming; Zhang, Ying

doi:https://doi.org/10.1155/2023/3290917

Journal of Food Processing and Preservation

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Abstract Introduction Results and Discussion Conclusion Data Availability Additional Points Consent Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 3290917 | https://doi.org/10.1155/2023/3290917

Infrared and Terahertz Spectra of Pu’er White Tea with Different Degrees of Oxidation

Dong-Mei Wu,¹Jie Guo,¹Ming-Ming Sun,¹and Ying Zhang¹

Academic Editor: Jianbo Xiao

Received19 Sept 2022

Revised17 Nov 2022

Accepted16 Dec 2022

Published29 Mar 2023

Abstract

In this work, the Fourier transform infrared spectroscopy (FTIR) and Terahertz time domain spectra (THz-TDS) were employed to study Pu’er white tea with different oxidation levels by changing the withering time. The strongest absorption peak of 3359 cm^-1 in FTIR spectra comes from the proteins and polysaccharides. Several intensity ratios of the characteristic absorption peaks with different oxidation levels were analyzed. The white tea with different oxidation levels can be distinguished from the absorbance of THz-TDS in the range of 0.5–1.5 THz. The refractive index calculated from THz-TDS was between 1.42 and 1.44. Principal component analysis (PCA) using FTIR absorbance data showed that the scattered points of PC1 and PC2 can be well distributed in different districts. Hierarchical cluster analysis (HCA) helped to carry out the clustering results of different white tea samples. The sample with overoxidation level can be distinguished by PCA and HCA using THz-TDS absorbance data. Therefore, FTIR might be a convenient, fast, and nondestructive strategy for identifying white tea with different oxidation levels. THz-TDS combined with some software algorithms can be applied to distinguish the different oxidation-processed tea.

1. Introduction

White tea contains a large number of tea polyphenols, alkaloids, amino acids, vitamins, and other nutrients, which have a protective effect in cardiovascular disease, diabetes, cancer, obesity, and antibacterial [1]. High-performance liquid chromatograph (K. B. [2]) and gas chromatograph mass spectrometer [3] have been popularly used for the determination of tea constituents. After every component of tea can be isolated, the ingredients are analyzed using conventional detection techniques such as mass spectrometry [4] and electrochemical detection [5]. Liquid chromatography coupled with tandem mass spectrometry was used to study the chemical changes of tea leaves during pile-fermentation [6] and determination of pesticide residues in tea leaves [7]. Electronic tongue and its biosensors for the analysis of tea polyphenols have also been utilized for the discrimination of tea [8]. Moreover, the identification of tea leaves relies on the sensory evaluation, which is subjective and unconvincing. However, the above-mentioned methods are costly and time-consuming. It is meaningful to create a fast, facile, and nondestructive method to distinguish tea with different degrees of oxidation.

In recent years, the spectral testing methods, FITR and THz-TDS, have been applied in tea leaves testing due to the advantages such as scientific accuracy, nondestructive, and fast testing. Different container time and the content of tea polyphenols can be tested or distinguished by FTIR [8–11]. FTIR can not only be applied to food but also widely used in medical research and tumor diagnosis [12, 13]. THz-TDS has great potential in the biomedical field to detect the precise boundaries of sugars, proteins, DNA, and pathological tissues to determine cancer diagnosis [14, 15]. Terahertz spectra also play an important role in the detection of composite materials, drugs, and many nonconductive materials which are transparent in THz range [16–18]. However, only a few literatures reported the application of tea testing using THz spectra with the algorithm. Four kinds of green tea were effectively distinguished by establishing the GA-SVM model and conducted PCA on THz-TDS data [19]. SVM and -means clustering algorithms were used to identify green tea, white tea, and black tea, and the pesticide thiamethoxam residues in tea were measured [20–22]. FTIR and THz-TDS were often used to detect the origin, varieties, storage years, and pesticide residues, almost not used to detect the level of oxidation of tea, which is also the meaning of this paper [21, 23, 24]. The main process of white tea includes picking, withering, and drying. In the process of tea withering, the water content is continuously reduced with the quality components such as water extract, tea polyphenols, and amino acids changing accordingly. The quality varies greatly with the degree of withering [25]. The texture, color, and nutrients of the final tea product are closely related to the withering process technology which corresponds to degrees of oxidation. The withering process includes outdoor natural withering at the temperature 20-25°C and the indoor withering at 28-30°C and relative humidity of 65-80%. It is written in the literature that the sensory score reached the highest when the natural wilting time was 60 hours and the warming wilting time was 36 h [26]. Similar to the literature conditions, combined with actual tea making experience, the wilting time of normal oxidation tea is selected as 55 hours, and the wilting time of weak oxidation and overoxidation is selected as 35 hours and 75 hours, respectively. The research of the withering process by FTIR and THz-DTS has not been reported so far. Therefore, this paper studied FTIR (500-4000 cm^-1) and THz-TDS (0.5-1.0 THz) of white tea with different oxidation levels. The absorption spectra of tea in the infrared band were measured, and the substance in different oxidation tea was analyzed. The transmittance, absorption, and refractive index of tea in the terahertz band were calculated. In addition, the classification and identification of the three kinds of tea were carried out by PCA and HCA using the absorption data.

2. Experiment

2.1. Sample Preparation

The flow chart of sample preparation is shown in Figure 1. The white tea used in this paper comes from the spring tea of Pu’er white tea production area in Yunnan Province. Generally, the protein accounts for 20~30% and the carbohydrate accounts for 20%~25% in the dry matter of tea. Tea polyphenol accounts for about 25%~35% of the total dry matter of tea, and the catechin accounts for 65%~80% in the total tea polyphenol [27]. Epigallocatechin gallate (also known as EGCG) with the highest concentration is the most studied polyphenol component in tea and the most active as shown in Scheme 1 [28]. During the withering, the total polyphenol and the catechin content decrease with time, which can form an oxidation product of theaflavins and thearubigins meanwhile increase the levels of theaflavin, gallic, and amino acids [29, 30]. So our article focuses on the change of tea polyphenols with the withering time.

After withering and drying preservation for one year, the samples were pressed to tablets for FTIR and THz-TDS testing. The tea left and KBr powders were mixed at a ratio of 1 : 100, which were ground in an agate plate and pressed into transparent flakes under the pressure of 40 MPa for 90 seconds as shown in Figure 2(a). The white tea samples and polyethylene were mixed in a ratio of 1 : 10 and ground under the pressure of 40 MPa for 30 seconds. The fine powder was pressed into thin slices with a diameter of 13 mm and a thickness of 1 mm and stored in a dry place. The pressed samples for THz-TDS are shown in Figure 2(b).

(a)

(b)

2.2. Testing Instruments and Data Processing

The FTIR spectra were obtained by PerkinElmer equipped with DTGS detectors with the range of 4000-400 cm^-1 and a resolution of 4 cm^-1. TP15K all-fiber THz-TDS spectroscopy system was produced by Teal Times Technology Co., Ltd., which ranges from 0.2 THz to 3.5 THz. To decrease the testing errors, 10 samples for each withering time or oxidation degree were fabricated and each sample was measured 100 times. The sample average thickness was measured from three different areas. The samples were placed in the light path, which was put in a cavity with sparging nitrogen gas until the air humidity dropped below 5% before testing. SPSS26 and ORIGIN2019B software were used for HCA and PCA analysis in the range of 1075-1375 cm^-1 for FTIR and 0.5 THz-1.0 THz for THz-DTS spectra.

3. Results and Discussion

3.1. Analysis of FTIR Spectra

Figure 3 is the average FTIR spectra of three samples with different oxidation levels. It can be seen that the absorption peaks in white tea are 3359 cm^-1, 2929 cm^-1, 2871 cm^-1, 1698 cm^-1, 1654 cm^-1, 1544 cm^-1, 1455 cm^-1, 1376 cm^-1, 1240 cm^-1, 1145 cm^-1, 1041 cm^-1, 827 V 763 cm^-1, and 613 cm^-1. The FTIR spectra of the three kinds of tea are so similar that it is difficult to distinguish them from the original FTIR spectra.

Table 1 shows the absorption peaks corresponding to the characteristic vibration. The strongest absorption peak of 3359 cm^-1 comes from the proteins and polysaccharides. The peak of near 1654 cm^-1 is from the stretching vibration of C=O. The peak of near 1041 cm^-1 arrives from C-O-C symmetric stretching vibration. It can be seen that the peaks at 1520, 1460, 1370, 1238, 1145, 1030, 822, and 766 cm^-1 in FTIR belong to the catechins according to the reference [31]. However, there is no obvious absorption peaks of catechin in THz range according to the reference [21], which may be due to the influence of water, protein, sugar, and other factors.

Figure 4 shows the change of six special intensity ratios of the characteristic absorption peaks with different oxidation levels. The ratios of I₂₈₇₁/I₁₂₄₀, I₁₃₇₆/I₁₆₉₈, I₇₆₃/I₁₆₅₄, and I₁₄₅₅/I₂₉₂₉ represent the ratios of lipid to phenolic, polysaccharide to protein, aromatic compounds to proteins, and polysaccharides to lipids, respectively. The ratios of I1145/I1041 and I827/I613 indicate the relative content ratio of cellulose and aromatic compounds [31].

It can be seen that the four ratios of I₂₈₇₁/I₁₂₄₀, I₁₃₇₆/I₁₆₉₈, I₇₆₃/I₁₆₅₄, and I₁₁₄₅/I₁₀₄₁ are almost unchanged with the increase of oxidation levels, which demonstrate that the effect of oxidation on the content of lipids, phenolics, polysaccharides, protein, aromatic compounds, and proteins was weak. The ratio of I₁₄₅₅/I₂₉₂₉ decreased apparently, indicating the decomposition of the polysaccharides by the oxidation process. The obvious increase of the ratio of I₈₂₇/I₆₁₃ means the oxidation promoted the chemical synthesis of aromatic compounds.

The transmittance , the refractive index , and the absorption can be calculated using the transmittance spectra in THz range according to Equations (1)–(3). The transmittance of pure KBr sheet in THz-TDS spectrum is regarded as the reference background signal.

is the incident light intensity. is the transmittance intensity. is the angular frequency. is the sample thickness. is the speed of light. is the ratio of sample signal to the reference signal amplitude. is the delay time between sample signal and the reference signal.

Figure 5 shows the absorption spectra in the range of 0.5-1.5 THz of three samples with different oxidation levels. Catechin has a characteristic absorption peak located at 0.342 THz, 0.414 THz, 0.786 THz, 1.068 THz, 1.14 THz, 1.188 THz, 1.416 THz, and 1.272 THz [21]. No obvious absorption peak of catechin was detected in this experiment, which may be affected by water, protein, sugar, and other factors. There is little difference with nearly changing tendency. The absorption of the three samples increases with the increase of frequency, which is according to Equations (2) and (3). The absorption of the normal oxidation sample is clearly higher than the other two samples, which originated from the evaporation of water. Three kinds of white tea with different oxidation levels can be distinguished from the absorption. The absorption increases with the frequency and reaches 18 cm-1 at 1.5 THz. The absorption coefficient of 10 cm^-1 at 1.0 THz is similar to 12 cm^-1 in reference [19].

Figure 6 shows the refractive indexes of three samples with different oxidation levels. The refractive index was calculated between 1.42 and 1.44, which decreases slowly with the increase of frequency. The value of the refractive index in this paper is consistent with that in reference [19]. The three samples cannot be distinguished before 1.0 THz because of the refractive index curves overlap intensively. Between 1.0 THz and 1.5 THz, the refractive index of overoxidation sample is clearly higher than others, which indicates that some ingredients appear great changes after the overoxidation in the withering process.

3.2. PCA for FTIR and THz-DTS

Principal component analysis (PCA) is often used in spectral processing to reduce the dimension of data, which produces estimates of all peak parameters including the area, frequency, phase, and linewidth, even for peaks with very low signal-to-noise ratio [34, 35]. To further distinguish the three kinds of white tea with different levels of oxidation, FTIR absorption spectra data in the range of 1075~1375 cm^-1 was used to obtain the principal component scores of different oxidation levels as shown in Figure 7. The first two principal components PC1 and PC2 explain 99.1% of the FTIR data variance. Two active components which can effectively represent other components are extracted, with the score of the first component being 98.1% and the score of the second principal component being 1.8%. The loading plot of PCA which employed to explain the change of composition with different oxidation levels used to identify the peaks that have a high contribution to distinguish samples. According to PC1 loading plot in Figure 8, there are no strong positive weighted peaks. The load plot of PC2 has seven positive weighted peaks around 1083, 1137, 1147, 1186, 1218, 1344, and 1369 cm⁻¹. There are three positive weighted peaks located at 1147, 1344, and 1369 due to C-O stretching vibration of ester and CH3 bending vibration of lipid. The peaks around 1083, 1137, 1186, and 1344 cm⁻¹ are caused by C-O stretching vibration of polysaccharide. The peak at 1135 cm⁻¹ originates from C-O stretching vibration of tea polysaccharide. The peak at 1218 cm⁻¹ is accord to C-N stretching vibration of the aromatic compound secondary amine [24, 31, 36]. Four negatively weighted peaks at 1114, 1160, 1272, and 1359 cm⁻¹ originate from the C-O stretching vibration of polysaccharide [24, 31, 36]. The results of PCA showed that the main sources of FTIR in white tea with different oxidation levels are tea polysaccharide, lipid, ester, and aromatic compounds.

Furthermore, we use THz-TDS absorption spectra data to distinguish the samples with different oxidation levels by PCA method. Figure 9 shows the scores of PCA in the range of 0.5~1.0 THz. The first two principal components PC1 and PC2 explain 99.3% of the THz data variance, the first principal component score was 95.1%, and the second principal component score was 4.2%. The aggregation effect of three samples with three oxidation levels is not good; only the overoxidation can be distinguished. It may be that the difference in the content of weak oxidation and normal oxidation is too small to distinguish. Using the first derivative data to carry out PCA like processing FTIR data, the effect is also not ideal. The distinguishing of different oxidation levels or withering time by terahertz band needs the help of other algorithms.

3.3. HCA for FTIR and THz-DTS

HCA was also performed using the FTIR first derivative spectrum. Each kind of tea has 300 absorbance peaks corresponding to 300 wave numbers, forming a vector of 300 dimensions. The three kinds of teas are regarded as three points in the 300-dimensional space, and the similarity between two samples can be measured by the two point distance formula in the 300-dimensional space (J. [37]). The distance between points was calculated by Euclidean distance , and the distance between classes was calculated by Ward’s method in cluster analysis.

Figure 10 is the dendrogram of HCA of the FTIR, which reveals that white tea is clustered into three groups when the distance is 6, and white tea with the same oxidation level is clustered into one group. HCA using FTIR can distinguish white tea with different oxidation levels accurately.

Figure 11 is the dendrogram of HCA of absorption of white tea with different oxidation levels in the range of 0.5-1.0 THz from THz-DTS, where A represents overoxidation, B represents normal oxidation, and C represents weak oxidation. It can be seen from the figure that when the distance is 3, A1-A5 and A7-A10 gather into a group, and overoxidation gathers into a group except A6. At distances of 3 and 6, the mixture of normal oxidation and weak oxidation is gathered into two groups. The HCA using THz-DTS could distinguish overoxidation but could not distinguish normal oxidation and weak oxidation, which was consistent with PCA.

4. Conclusion

In the study, FTIR and THZ-TDS, HCA, and PCA were employed to distinguish different oxidation levels of white tea. The characteristic absorption peaks from FTIR revealed that the content of tea mainly included proteins and polysaccharides. The intensity ratios of the characteristic absorption peaks demonstrated that the effect of oxidation on the content of lipid, phenolic, polysaccharide, protein, aromatic compounds, and proteins was weak, and the decomposition of the polysaccharides by the oxidation process. By HCA and PCA algorithms, the FTIR spectra could distinguish the white tea samples with different oxidation levels, while the THz-DTS spectra could only classify the white tea sample with overoxidation level. Therefore, FTIR can be effectively applied to identify types of white tea with different oxidation levels by changing the withering time. To distinguish different oxidation levels more accurately using THz-DTS, support vector machine, partial square method, genetic algorithm, and other algorithms might be employed. Combining the HCA for FTIR and THz-DTS, which is consistent with PCA result, FTIR has a better method to distinguish tea leaves with different degrees of oxidation.

Data Availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Additional Points

We obtain all permission to reproduce material from other sources.

We obtained all informed consent from the subjects.

Conflicts of Interest

We declare that there is no conflict of interest.

Authors’ Contributions

Dongmei Wu is responsible for the investigation, conceptualization, methodology, project administration, visualization, and writing-original draft. Jie Guo is responsible for the supervision, resources, writing-review and editing, and funding acquisition. Mingming Sun is responsible for the investigation, methodology, and visualization. Ying Zhang is responsible for the supervision, writing-review and editing, and resources. All authors have contributed to the creation of this manuscript for important intellectual content and read and approved the final manuscript.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61905207) and the Yunnan Fundamental Research Projects (Grant No. 202001AU07).

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