ORIGINAL ARTICLE
Metabolomic analysis reveals the quality characteristics of Yi Gong tea leaves at different harvesting periods
Zheng-hong Li,
Guo-qiang Zhang,
Zheng-hong Li
College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, China
Search for more papers by this authorCorresponding Author
Guo-qiang Zhang
College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, China
Correspondence
Guo-qiang Zhang, College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, Anhui, China.
Email: [email protected]
Search for more papers by this authorZheng-hong Li,
Guo-qiang Zhang,
Zheng-hong Li
College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, China
Search for more papers by this authorCorresponding Author
Guo-qiang Zhang
College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, China
Correspondence
Guo-qiang Zhang, College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu, Anhui, China.
Email: [email protected]
Search for more papers by this authorAbstract
To obtain a theoretical reference for understanding the changes in metabolites of Yigong tea leaves during different harvesting periods and to determine the optimal harvesting period, we performed a metabolome comparison using UPLC-Q-Exactive MS on Yigong tea leaves from different harvesting periods. The results indicated that a total of 41 metabolites were significantly altered during the growth of Yi Gong tea leaves. These involved 7 amino acids and their derivatives, 16 flavonols and flavonol glycosides, 4 organic acids, 3 catechins, 3 carbohydrates, 7 fatty acid esters, 1 terpene, and 3 substances from others. In particular, the levels of arginine and glutamine were higher in early-harvested tea leaves than in late-harvested tea leaves; the levels of flavonoids and flavonols were higher in late-harvested tea leaves. Metabolic pathway analysis revealed that the caffeine metabolism and the flavonoid biosynthesis perform key roles in Yigong tea leaves from different harvesting periods.
Practical Applications
At present, the application of metabolomics in tea research is focused on the study of pesticide residues, processing processes, environmental stresses, and regional differences. This study is to focus on the effect of the tea harvesting period on tea quality through metabolomics. Through metabolomics, we can better determine the optimal tea harvesting period, and this study can improve the quality of this tea product and may be able to bring some favourable favorable contributions contribution to the local tea marketing in the future.
CONFLICT OF INTEREST
The authors declared that they have no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that supports the findings of this study are available in the supplementary material of this article.
Supporting Information
| Filename | Description |
|---|---|
| jfbc14478-sup-0001-FigureS1.docxWord 2007 document , 511.5 KB |
Figure S1 |
| jfbc14478-sup-0002-TableS1.xlsxExcel 2007 spreadsheet , 33.3 KB |
Table S1 |
| jfbc14478-sup-0003-Supinfo.zipZip archive, 1.2 MB |
Appendix S1 |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
REFERENCES
- Bortolini, D. G., Haminiuk, C. W. I., Pedro, A. C., Fernandes, I. D. A., & Maciel, G. M. (2021). Processing, chemical signature and food industry applications of Camellia sinensis teas: An overview. Food Chemistry-X, 12, 100160. https://doi.org/10.1016/j.fochx.2021.100160
- Chen, S., Liu, H., Zhao, X., Li, X., Shan, W., Wang, X., Wang, S., Yu, W., Yang, Z., & Yu, X. (2020). Non-targeted metabolomics analysis reveals dynamic changes of volatile and non-volatile metabolites during oolong tea manufacture. Food Research International, 128, 108778. https://doi.org/10.1016/j.foodres.2019.108778
- Dong, F., Hu, J., Shi, Y., Liu, M., Zhang, Q., & Ruan, J. (2019). Effects of nitrogen supply on flavonol glycoside biosynthesis and accumulation in tea leaves (Camellia sinensis). Plant Physiology and Biochemistry, 138, 48–57. https://doi.org/10.1016/j.plaphy.2019.02.017
- Fang, R., Redfern, S., Kirkup, D., Porter, E., Kite, G., Terry, L., Berry, M., & Simmonds, M. (2017). Variation of theanine, phenolic, and methylxanthine compounds in 21 cultivars of Camellia sinensis harvested in different seasons. Food Chemistry, 220, 517–526. https://doi.org/10.1016/j.foodchem.2016.09.047
- Fang, Z., Yang, W., Li, C., Li, D., Dong, J., Zhao, D., Xu, H., Ye, J., Zheng, X., Liang, Y., & Lu, J. (2021). Accumulation pattern of catechins and flavonol glycosides in different varieties and cultivars of tea plant in China. Journal of Food Composition and Analysis, 97, 103772. https://doi.org/10.1016/j.jfca.2020.103772
- Fukushima, A., Kusano, M., Redestig, H., Arita, M., & Saito, K. (2009). Integrated omics approaches in plant systems biology. Current Opinion in Chemical Biology, 13(5), 532–538. https://doi.org/10.1016/j.cbpa.2009.09.022
- Gika, H., Theodoridis, G., Plumb, R., & Wilson, I. (2014). Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics. Journal of Pharmaceutical and Biomedical Analysis, 87, 12–25. https://doi.org/10.1016/j.jpba.2013.06.032
- Guo, X., Schwab, W., Ho, C., Song, C., & Wan, X. (2021). Characterization of the aroma profiles of oolong tea made from three tea cultivars by both GC-MS and GC-IMS. Food Chemistry, 376, 131933. https://doi.org/10.1016/j.foodchem.2021.131933
- He, G., Hou, X., & Han, M. (2022). Discrimination and polyphenol compositions of green teas with seasonal variations based on UPLC-QTOF/MS combined with chemometrics. Journal of Food Composition and Analysis, 105, 104267. https://doi.org/10.1016/j.jfca.2021.104267
- Hong, G., Wang, J., Zhang, Y., Hochstetter, D., Zhang, S., Pan, Y., Shi, Y., Xu, P., & Wang, Y. (2014). Biosynthesis of catechin components is differentially regulated in dark-treated tea (Camellia sinensis L.). Plant Physiology and Biochemistry, 78, 49–52. https://doi.org/10.1016/j.plaphy.2014.02.017
- Kazan, R., Seddik, H., Marstani, Z., Elsutohy, M., & Yasri, N. (2019). Determination of amino acids content in tea species using liquid chromatography via pre-column fluorescence derivatization. Microchemical Journal, 150, 104103. https://doi.org/10.1016/j.microc.2019.104103
- Lee, J., Lee, B., Chung, J., Kim, H., Kim, E., Jung, S., Lee, H., Lee, S., & Hong, Y. (2015). Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography. Food Chemistry, 174, 452–459. https://doi.org/10.1016/j.foodchem.2014.11.086
- Li, X., Li, M., Deng, W., Ahammed, G., Wei, J., Yan, P., Zhang, L., Fu, J., & Han, W. (2020). Exogenous melatonin improves tea quality under moderate high temperatures by increasing epigallocatechin-3-gallate and theanine biosynthesis in Camellia sinensis L. Journal of Plant Physiology, 253, 153273. https://doi.org/10.1016/j.jplph.2020.153273
- Li, X., Zhang, L., Ahammed, G., Li, Y., Wei, J., Yan, P., Zhang, L., Han, X., & Han, W. (2019). Salicylic acid acts upstream of nitric oxide in elevated carbon dioxide-induced flavonoid biosynthesis in tea plant (Camellia sinensis L.). Environmental and Experimental Botany, 161, 367–374. https://doi.org/10.1016/j.envexpbot.2018.11.012
- Liao, J., Shen, Q., & Li, R. (2021). GABA shunt contribution to flavonoid biosynthesis and metabolism in tea plants (Camellia sinensis). Plant Physiology and Biochemistry, 166, 849–856. https://doi.org/10.1016/j.plaphy.2021.06.042
- Liu, J., Zhang, Q., Liu, M., Ma, L., Shi, Y., & Ruan, J. (2016). Metabolomic analyses reveal distinct change of metabolites and quality of green tea during the short duration within single spring season. Journal of Agricultural and Food Chemistry, 64(16), 3302–3309. https://doi.org/10.1021/acs.jafc.6b00404
- Liu, M., Burgos, A., Zhang, Q., Tang, D., Shi, Y., Ma, L., Yi, X., & Ruan, J. (2017). Analyses of transcriptome profiles and selected metabolites unravel the metabolic response to NH4+ and NO3− as signaling molecules in tea plant (Camellia sinensis L.). Scientia Horticulturae, 218, 293–303. https://doi.org/10.1016/j.scienta.2017.02.036
- Liu, P. P., Yin, J. F., Chen, G. S., Wang, F., & Xu, Y. Q. (2018). Flavor characteristics and chemical compositions of oolong tea processed using different semi-fermentation times. Journal of Food Science & Technology, 55(25), 1–11. https://doi.org/10.1007/s13197-018-3034-0
- Miyauchi, S., Yuki, T., Fuji, H., Kojima, K., Yonetani, T., Tomio, A., Bamba, T., & Fukusaki, E. (2014). High-quality green tea leaf production by artificial cultivation under growth chamber conditions considering amino acids profile. Journal of Bioscience and Bioengineering, 118(6), 710–715. https://doi.org/10.1016/j.jbiosc.2014.05.008
- Navratilova, K., Hrbek, V., Kratky, F., Hurkova, K., Tomaniova, M., Pulkrabova, J., & Hajslova, J. (2019). Green tea: Authentication of geographic origin based on UHPLC-HRMS fingerprints. Journal of Food Composition and Analysis, 78, 121–128. https://doi.org/10.1016/j.jfca.2019.02.004
- Pignitter, M., Stolze, K., Jirsa, F., Gille, L., Goodman, B. A., & Somoza, V. (2015). Effect of copper on fatty acid profiles in non- and semifermented teas analyzed by lc-ms-based nontargeted screening. Journal of Agricultural & Food Chemistry, 63, 8519–8526. https://doi.org/10.1021/acs.jafc.5b02792
- Pongsuwan, W., Bamba, T., Harada, K., Yonetani, T., Kobayashi, A., & Fukusaki, E. (2008). High-throughput technique for comprehensive analysis of Japanese green tea quality assessment using ultra-performance liquid chromatography with time-of-flight mass spectrometry (UPLC/TOF MS). Journal of Agricultural and Food Chemistry, 56(22), 10705–10708. https://doi.org/10.1021/jf8018003
- Qian, Y., Zhao, X., Zhao, L., Cui, L., Liu, L., Jiang, X., Liu, Y., Gao, L., & Xia, T. (2015). Analysis of stereochemistry and biosynthesis of epicatechin in tea plants by chiral phase high performance liquid chromatography. Journal of Chromatography B, 1006, 1–7. https://doi.org/10.1016/j.jchromb.2015.10.024
- Ryu, H., Yuk, H., An, J., Kim, D., Song, H., & Oh, S. (2017). Comparison of secondary metabolite changes in Camellia sinensis leaves depending on the growth stage. Food Control, 73, 916–921. https://doi.org/10.1016/j.foodcont.2016.10.017
- Saeed, M., & Naveed, M. (2017). Green tea (Camellia sinensis) and l-theanine: Medicinal values and beneficial applications in a humans-A comprehensive review. Biomedicine & Pharmacotherapy, 95, 1260–1275. https://doi.org/10.1016/j.biopha.2017.09.024
- Samanta, T., Kotamreddy, J., Ghosh, B., & Mitra, A. (2017). Changes in targeted metabolites, enzyme activities and transcripts at different developmental stages of tea leaves: a study for understanding the biochemical basis of tea shoot plucking. Acta Physiologiae Plantarum, 39(1), 11. https://doi.org/10.1007/s11738-016-2298-0
- Sirotkin, A., & Kolesárová, A. (2021). The anti-obesity and health-promoting effects of tea and coffee. Physiological Research, 70, 161–168. https://doi.org/10.33549/physiolres.934674
- Sun, Y., Wang, Y., Huang, J., Ren, G., Ning, J., Deng, W., Li, L., & Zhang, Z. (2020). Quality assessment of instant green tea using portable NIR spectrometer. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 240, 118576. https://doi.org/10.1016/j.saa.2020.118576
- Tan, L. H., Zhang, D., Wang, G., Yu, B., Zhao, S. P., Wang, J. W., Yao, L., & Cao, W. G. (2016). Comparative analyses of flavonoids compositions and antioxidant activities of Hawk tea from six botanical origins. Industrial Crops and Products, 80, 123–130. https://doi.org/10.1016/j.indcrop.2015.11.035
- Touhami, N., Buhl, K., Schmidt-Heydt, M., & Geisen, R. (2016). Arginine acts as an inhibitor of the biosynthesis of several mycotoxins. International Journal of Food Microbiology, 235, 46–52. https://doi.org/10.1016/j.ijfoodmicro.2016.06.036
- Triba, M., Moyec, L., Amathieu, R., Goossens, C., Bouchemal, N., Nahon, P., Rutledge, D., & Savarin, P. (2015). PLS/OPLS models in metabolomics: the impact of permutation of dataset rows on the K-fold cross-validation quality parameters. Molecular BioSystems, 11(1), 13–19. https://doi.org/10.1039/c4mb00414k
- Vos, R., Moco, S., Lommen, A., Keurentjes, J., Bino, R., & Hall, R. (2007). Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nature Protocols, 2(4), 778–791. https://doi.org/10.1038/nprot.2007.95
- Wang, J., Chen, W., Wang, H., Li, Y., Wang, B., Zhang, L., Wan, X., & Li, M. (2021). Transcription factor CsDOF regulates glutamine metabolism in tea plants (Camellia sinensis). Plant Science, 302, 110720. https://doi.org/10.1016/j.plantsci.2020.110720
- Wen, B., Ren, S., Zhang, Y., Duan, Y., Shen, J., Zhu, X., Wang, Y., Ma, Y., Zou, Z., & Fang, W. (2020). Effects of geographic locations and topographical factors on secondary metabolites distribution in green tea at a regional scale. Food Control, 110, 106979. https://doi.org/10.1016/j.foodcont.2019.106979
- Werth, M., Halouska, S., Shortridge, M. D., Zhang, B., & Powers, R. (2010). Analysis of metabolomic PCA data using tree diagrams. Analytical Biochemistry, 399(1), 58–63. https://doi.org/10.1016/j.ab.2009.12.022
- Wu, X., Zhu, J., Wu, B., Sun, J., & Dai, C. (2018). Discrimination of tea varieties using FTIR spectroscopy and allied Gustafson-Kessel clustering. Computers and Electronics in Agriculture, 147, 64–69. https://doi.org/10.1016/j.compag.2018.02.014
- Xia, J., Liang, Q., Hu, P., Wang, Y., & Luo, G. (2009). Recent trends in strategies and methodologies for metabonomics. Chinese Journal of Analytical Chemistry, 37(1), 136–143. https://doi.org/10.1016/S1872-2040(08)60081-X
- Xu, C., Liang, L., Li, Y., Yang, T., Fan, Y., Mao, X., & Wang, Y. (2021). Studies of quality development and major chemical composition of green tea processed from tea with different shoot maturity. LWT—Food Science and Technology, 142, 111055. https://doi.org/10.1016/j.lwt.2021.111055
- Zeng, C., Lin, H., Liu, Z., & Liu, Z. (2020). Metabolomics analysis of Camellia sinensis with respect to harvesting time. Food Research International, 128, 108814. https://doi.org/10.1016/j.foodres.2019.108814
- Zhou, P., Hu, O., Fu, H., Ouyang, L., Gong, X., Meng, P., Wang, Z., Dai, M., Guo, X., & Wang, Y. (2019). UPLC-Q-TOF/MS-based untargeted metabolomics coupled with chemometrics approach for Tieguanyin tea with seasonal and year variations. Food Chemistry, 283, 73–82. https://doi.org/10.1016/j.foodchem.2019.01.050
- Zhou, Z., Wu, Q., Ni, Z., Hu, Q., Yang, Y., Zheng, Y., Bi, W., Deng, H., Liu, Z., Ye, N., Lai, Z., & Sun, Y. (2021). Metabolic flow of C6 volatile compounds from LOX-HPL pathway based on airflow during the post-harvest process of oolong tea. Frontiers in Plant Science, 12, 738445. https://doi.org/10.3389/fpls.2021.738445
- Zhu, J., Xu, Q., Zhao, S., Xia, X., Yan, X., An, Y., Mi, X., Guo, L., Samarina, L., & Wei, C. (2020). Comprehensive co-expression analysis provides novel insights into temporal variation of flavonoids in fresh leaves of the tea plant (Camellia sinensis). Plant Science, 290, 110306. https://doi.org/10.1016/j.plantsci.2019.110306
