Scientia Agricultura Sinica ›› 2025, Vol. 58 ›› Issue (22): 4757-4770.doi: 10.3864/j.issn.0578-1752.2025.22.015

• FOOD SCIENCE AND ENGINEERING • Previous Articles     Next Articles

Characterization of Non-Volatile Metabolites of White Peony Tea Make of Camellia sinensis Fu’an-dabaicha from Different Origins

LUO Qin1(), CHEN XieYong2(), XU YuYing1, WEI Hang1, HUANG Biao1, YAO QingHua1, YE NaiXing2, ZHENG DeYong3(), YAN MingJuan4()   

  1. 1 Institute of Quality Standards and Testing Technology for Agro-Products, Fujian Academy of Agricultural Sciences/Fujian Key Laboratory of Agro-Products Quality and Safety, Fuzhou 350003
    2 College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002
    3 College of Materials Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002
    4 Institute of Resources, Environment and Soil Fertilizer, Fujian Academy of Agricultural Sciences/Fujian Key Laboratory of Plant Nutrition and Fertilizer, Fuzhou 350003
  • Received:2025-06-11 Accepted:2025-09-15 Online:2025-11-16 Published:2025-11-21
  • Contact: ZHENG DeYong, YAN MingJuan

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Abstract:

【Objective】 This study aimed to explore the discrimination technology of the origin of small-region white peony tea based on non-volatile metabolite characteristics. 【Method】Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to determine the composition and content of non-volatile metabolites in white peony tea made of Camellia sinensis Fu’an-dabaicha varieties from three different production areas, including Zhenghe County (ZH), Songxi County (SX), and Fu’an City (FA). Combined with mathematical statistics methods, characteristic compounds were screened, and a discrimination model of the origin of white peony tea was constructed. 【Result】 After screening and filtering, 219 kinds of non-volatile metabolites were identified in the white peony tea from the three regions. Among them, polyphenol metabolites accounted for the highest proportion in the tea samples from the three production areas, with 30.921%, 29.046%, and 29.110% in Fu’an, Songxi, and Zhenghe, respectively. Analysis of variance showed that polyphenols and amino acids and their derivatives had significant differences among the three production areas (the order of polyphenol content from high to low was FA, SX, and ZH, while the order of amino acid and their derivatives content from high to low was ZH, FA, and SX (P<0.01), while organic acids and nucleotides and their derivatives had no significant differences among the three production areas (P>0.05). Among the 219 metabolites, 158 non-volatile metabolites, such as 5-formylsalicylic acid and quercetin 3-D-galactoside, showed significant or extremely significant differences. The orthogonal partial least squares discriminant analysis (OPLS-DA) model did not show overfitting, and the model validation effect was good. The prediction index and discrimination accuracy of the model were 0.859 and 98.89%, respectively. There were 85 characteristic non-volatile metabolites with variable importance in projection (VIP)≥1. Stepwise linear discriminant analysis (SLDA) selected 16 metabolites into the model, and the initial and cross-validation discrimination accuracy of the constructed discrimination model were both 100.00%. 【Conclusion】A discrimination technology of the origin of small-region white peony tea based on non-volatile metabolite characteristics was established. Both OPLS-DA and SLDA discrimination models can effectively discriminate against the origin of white peony tea based on non-volatile metabolites, which could provide the theoretical references for the traceability and brand building of tea origins.

Key words: Camellia sinensis Fu’an-dabaicha, non-volatile metabolites, geographical origin traceability, UHPLC-Q-TOF MS

Table 1

Abundance of nonvolatile metabolite compositional categories in white peony tea made of Camellia sinensis Fu’an- dabaicha from different origins"

代谢物类别
Metabolite category		 福安 FA 松溪 SX 政和 ZH P值
P value
均值
Average
value		 标准差
Standard deviation		 均值
Average
value		 标准差
Standard deviation		 均值
Average
value		 标准差
Standard deviation
氨基酸及其衍生物
Amino acids and their derivatives		 1359283.592 146380.771 1206285.502 222506.370 1469838.446 166681.109 0.000
多酚类 Polyphenols 7073841.109 583646.077 6693953.978 641215.590 6357090.270 643552.022 0.000
甘油酯 Glycerides 358637.569 39836.392 407219.317 42443.955 353241.921 44152.985 0.000
核苷酸及其衍生物
Nucleotides and their derivatives		 234878.064 18948.580 246588.059 27375.389 235782.908 16910.216 0.070
木脂素和香豆素
Lignans and coumarins		 24291.884 9518.496 31507.815 7916.130 33240.994 5341.380 0.000
生物碱 Alkaloid 61931.260 10319.496 53739.009 12668.201 63475.766 7954.600 0.001
萜类 Terpenoids 278234.251 31418.267 247891.861 47633.553 277394.019 43841.704 0.007
酰胺类 Amides 637092.197 81791.098 589093.297 145283.144 674614.143 106045.969 0.018
有机酸 Organic acid 3533916.268 239029.752 3514474.827 366689.745 3515382.735 172018.232 0.952
其他 Others 2176874.862 171780.527 2190098.281 230816.767 2129023.774 134364.851 0.402
219种代谢物丰度
Abundance of 219 metabolites		 15738981.056 723200.984 15180851.946 1314421.927 15109084.976 771647.835 0.027
定性总丰度
Qualitative total abundance		 22877475.980 1035655.435 23045954.470 1523997.885 21838190.180 1334396.847 0.001

Fig. 1

Percentage stacking of abundance values of metabolite categories of white peony tea made of Camellia sinensis Fu’an- dabaicha of different origins"

Fig. 2

Bar graph of the abundance of metabolite classes of white peony tea made of Camellia sinensis Fu’an-dabaicha from different origins Different lowercase letters indicate significant differences (P<0.05). The same as below"

Fig. 3

Scatter plot of OPLS-DA scores of white peony tea made of Camellia sinensis Fu’an-dabaicha from different origins"

Table 2

Results of OPLS-DA of white peony tea made of Camellia sinensis Fu’an-dabaicha from Different Origins"

组别
Group		 预测组 Prediction Group 正确率
Accuracy rate (%)		 总正确率
Overall accuracy rate (%)
FA SX ZH 无组别 No group
福安 FA 29 0 0 1 96.67 98.89
松溪 SX 0 30 0 0 100.00
政和 ZH 0 0 30 0 100.00

Fig. 4

Calculated validation plot of OPLS-DA model with 200 iterations"

Fig. 5

Heat map analysis of metabolites of white peony tea made of Camellia sinensis Fu’an-dabaicha from different origins"

Fig. 6

Scatter plot of non-volatile metabolites of SLDA in white peony tea made of Camellia sinensis Fu’an-dabaicha from different origins"

Table 3

Discriminative results of non-volatile metabolites of white peony tea made of Camellia sinensis Fu’an-dabaicha from different origins (SLDA)"

验证方法
Verification method		 组别
Group		 预测组别 Predicted group 正确率
Accuracy rate (%)		 总正确率
Overall accuracy rate (%)
FA SX ZH
原始 Original FA 30 0 0 100.00 100.00
SX 0 30 0 100.00
ZH 0 0 30 100.00
交叉验证 Cross-validation FA 30 0 0 100.00 100.00
SX 0 30 0 100.00
ZH 0 0 30 100.00

Fig. 7

Comparison of the significance of differences in 16 characteristic metabolites of Camellia sinensis Fu’an-dabaicha from different origins"

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