基于非挥发性代谢物特征的福安大白茶产地溯源

doi:10.3864/j.issn.0578-1752.2025.22.015

中国农业科学 ›› 2025, Vol. 58 ›› Issue (22): 4757-4770.doi: 10.3864/j.issn.0578-1752.2025.22.015

基于非挥发性代谢物特征的福安大白茶产地溯源

罗钦¹(), 陈谢勇²(), 徐玉英¹, 韦航¹, 黄彪¹, 姚清华¹, 叶乃兴², 郑德勇³(), 颜明娟⁴()

¹ 福建省农业科学院农业质量标准与检测技术研究所/福建省农产品质量安全重点实验室，福州 350003
² 福建农林大学园艺学院，福州 350002
³ 福建农林大学材料工程学院，福州 350002
⁴ 福建省农业科学院资源环境与土壤肥料研究所/福建省植物营养与肥料重点实验室，福州 350012

收稿日期:2025-06-11 接受日期:2025-09-15 出版日期:2025-11-16 发布日期:2025-11-21
通信作者:
郑德勇，E-mail：ffczdy@163.com。
颜明娟，E-mail：yanmj163@163.com。
联系方式: 罗钦，E-mail：33044390@qq.com。陈谢勇，E-mail：2522980156@qq.com。罗钦和陈谢勇为同等贡献作者。
基金资助:
福建省科技计划-省属公益类科研院所基本科研专项(2022R1022004); 福建省财政专项-福建省农业科学院创新团队建设项目(CXTD2021011-1); 福建省人民政府-中国农业科学院“5511”协同创新工程(XTCXGC2021020); 福建省农业科学院科技特派员团助力乡村特色项目(2024KTP06-4)

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 Han¹, HUANG Biao¹, YAO QingHua¹, YE NaiXing², ZHENG DeYong³(), YAN MingJuan⁴()

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 Published:2025-11-16 Online:2025-11-21

摘要/Abstract

摘要：

【目的】探究基于非挥发性代谢物特征的小区域白牡丹茶叶产地判别技术。【方法】采用超高效液相色谱-四极杆飞行时间质谱技术测定政和县（Zhenghe County，ZH）、松溪县（Songxi County，SX）和福安市（Fu’an City，FA）等3个不同产区福安大白茶的白牡丹茶中非挥发性代谢物的组成及含量，结合数理统计学方法，筛选特征性化合物，构建白牡丹茶叶产地判别模型。【结果】3个地区的白牡丹茶中被鉴定出的非挥发性代谢物经筛选过滤后得到10类219种，其中多酚类代谢物在3个产地茶样中占比最高，在产地福安、松溪、政和中分别占30.921%、29.046%、29.110%。方差分析显示，多酚类与氨基酸及其衍生物代谢物在3个产地之间存在显著性差异（多酚类含量由高到低的顺序为FA、SX、ZH，而氨基酸及其衍生物含量由高到低的顺序为ZH、FA、SX，P<0.01），有机酸与核苷酸及其衍生物在3个产地之间无显著性差异（P>0.05）；在219种代谢物中，5-甲酰水杨酸、槲皮素3-D-半乳糖苷等158种非挥发性代谢物存在显著或极显著性差异。正交偏最小二乘法判别分析（orthogonal partial least squares discriminant analysis，OPLS-DA）模型未出现过拟合，模型验证效果较好，模型的预测指数与判别准确率分别为0.859和98.89%，变量重要性投影量值（variable importance in projection，VIP）≥1的特征非挥发性代谢物85个。逐步线性判别分析（stepwise linear discriminant analysis，SLDA）共筛选出16种代谢物进入模型，构建的判别模型初始和交叉验证的判别准确率均为100.00%。【结论】建立了基于非挥发性代谢物特征的小区域白牡丹茶叶产地判别技术，OPLS-DA和SLDA两种判别模型均能基于非挥发性代谢物有效判别白牡丹茶的原产地，可为茶叶原产地溯源及品牌建设提供理论参考。

关键词: 福安大白茶, 非挥发性代谢物, 产地溯源, 超高效液相色谱-四极杆飞行时间质谱

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

罗钦, 陈谢勇, 徐玉英, 韦航, 黄彪, 姚清华, 叶乃兴, 郑德勇, 颜明娟. 基于非挥发性代谢物特征的福安大白茶产地溯源[J]. 中国农业科学, 2025, 58(22): 4757-4770.

LUO Qin, CHEN XieYong, XU YuYing, WEI Han, HUANG Biao, YAO QingHua, YE NaiXing, ZHENG DeYong, YAN MingJuan. Characterization of Non-Volatile Metabolites of White Peony Tea Make of Camellia sinensis Fu’an-dabaicha from Different Origins[J]. Scientia Agricultura Sinica, 2025, 58(22): 4757-4770.

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代谢物类别 Metabolite category	福安 FA		松溪 SX		政和 ZH		P值 P value
代谢物类别 Metabolite category	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	P值 P value
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

组别 Group	预测组 Prediction Group				正确率 Accuracy rate (%)	总正确率 Overall accuracy rate (%)
组别 Group	FA	SX	ZH	无组别 No group	正确率 Accuracy rate (%)	总正确率 Overall accuracy rate (%)
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

基于非挥发性代谢物特征的福安大白茶产地溯源

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

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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 (%)
验证方法 Verification method	组别 Group	FA	SX	ZH	正确率 Accuracy rate (%)	总正确率 Overall accuracy rate (%)
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

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