High-speed identification system for fresh tea leaves based on phenotypic characteristics utilizing an improved genetic algorithm.

BACKGROUND: High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera. RESULTS: The influence of combinations of morphology, color, and custom corner-point morphological features on the classification results were investigated, and the necessary dimensionality of the model was tested. After feature selection and combination, the classification performance of the Naive Bayes, k-nearest neighbor, and support vector machine algorithms were compared. The recognition time of Naive Bayes was the shortest, whereas the accuracy of support vector machine had the best classification accuracy at approximately 97%. The support vector machine algorithm with only three feature dimensions (equivalent diameter, circularity, and skeleton endpoints) can meet production requirements with an accuracy rate reaching 92.5%. The proposed algorithm was tested by using the Swedish leaf and Flavia data sets, on which it achieved accuracies of 99.57% and 99.44%, respectively, demonstrating the flexibility and efficiency of the recognition scheme detailed in the present study. CONCLUSION: This research provides an efficient tea leaves recognition system that can be applied to production lines to reduce manual picking costs. © 2022 Society of Chemical Industry.

Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging.

BACKGROUND: The quality of fresh tea leaves after harvest determines, to some extent, the quality and price of commercial tea. A fast and accurate method to evaluate the quality of fresh tea leaves is required. RESULTS: In this study, the potential of hyperspectral imaging in the range of 328-1115 nm for the rapid prediction of moisture, total nitrogen, crude fiber contents, and quality index value was investigated. Ninety samples of eight tea-leaf varieties and two picking standards were tested. Quantitative partial least squares regression (PLSR) models were established using a full spectrum, whereas multiple linear regression (MLR) models were developed using characteristic wavelengths selected by a successive projections algorithm (SPA) and competitive adaptive reweighted sampling. The results showed that the optimal SPA-MLR models for moisture, total nitrogen, crude fiber contents, and quality index value yielded optimal performance with coefficients of determination for prediction (R2 p) of 0.9357, 0.8543, 0.8188, 0.9168; root mean square error of 0.3437, 0.1097, 0.3795, 1.0358; and residual prediction deviation of 4.00, 2.56, 2.31, and 3.51, respectively. CONCLUSION: The results suggested that the hyperspectral imaging technique coupled with chemometrics was a promising tool for the rapid and nondestructive measurement of tea-leaf quality, and had the potential to develop multispectral imaging systems for future online detection of tea-leaf quality. © 2020 Society of Chemical Industry.

Qualitative and quantitative diagnosis of nitrogen nutrition of tea plants under field condition using hyperspectral imaging coupled with chemometrics.

BACKGROUND: Rapid and accurate diagnosis of nitrogen (N) status in field crops is of great significance for site-specific N fertilizer management. This study aimed to evaluate the potential of hyperspectral imaging coupled with chemometrics for the qualitative and quantitative diagnosis of N status in tea plants under field conditions. RESULTS: Hyperspectral data from mature leaves of tea plants with different N application rates were preprocessed by standard normal variate (SNV). Partial least squares discriminative analysis (PLS-DA) and least squares-support vector machines (LS-SVM) were used for the classification of different N status. Furthermore, partial least squares regression (PLSR) was used for the prediction of N content. The results showed that the LS-SVM model yielded better performance with correct classification rates of 82% and 92% in prediction sets for the diagnosis of different N application rates and N status, respectively. The PLSR model for leaf N content (LNC) showed excellent performance, with correlation coefficients of 0.924, root mean square error of 0.209, and residual predictive deviation of 2.686 in the prediction set. In addition, the important wavebands of the PLSR model were interpreted based on regression coefficients. CONCLUSION: Overall, our results suggest that the hyperspectral imaging technique can be an effective and accurate tool for qualitative and quantitative diagnosis of N status in tea plants. © 2019 Society of Chemical Industry.

Significantly increased amino acid accumulation in a novel albino branch of the tea plant (Camellia sinensis).

MAIN CONCLUSION: A normal tea plant with one albino branch was discovered. RNA sequencing, albinism phenotype and ultrastructural observations provided a valuable understanding of the albino mechanism in tea plants. Tea plants with a specific color (white or yellow) have been studied extensively. A normal tea plant (Camellia sinensis cv. quntizhong) with one albino branch was discovered in a local tea plantation in Huangshan, Anhui, China. The pure albino leaves on this special branch had accumulated a fairly high content of amino acids, especially theanine (45.31 mg/g DW), and had a low concentration of polyphenols and an extremely low chlorophyll (Chl) content compared with control leaves. Ultrastructural observation of an albino leaf revealed no chloroplasts, whereas it was viable in the control leaf. RNA sequencing and differentially expressed gene (DEG) analysis were performed on the albino leaves and on control leaves from a normal green branch. The related genes involved in theanine and polyphenol biosynthesis were also investigated in this study. DEG expression patterns in Chl biosynthesis or degradation, carotenoid biosynthesis or degradation, chloroplast development, and biosynthesis were influenced in the albino leaves. Chloroplast deletion in albino leaves had probably destroyed the balance of carbon and nitrogen metabolism, leading to a high accumulation of free amino acids and a low concentration of polyphenols in the albino leaves. The obtained results can provide insight into the mechanism underlying this special albino branch phenotype, and are a valuable contribution toward understanding the albino mechanism in tea plants.

Tea Plant Information Archive: a comprehensive genomics and bioinformatics platform for tea plant.

Tea is the world's widely consumed nonalcohol beverage with essential economic and health benefits. Confronted with the increasing large-scale omics-data set particularly the genome sequence released in tea plant, the construction of a comprehensive knowledgebase is urgently needed to facilitate the utilization of these data sets towards molecular breeding. We hereby present the first integrative and specially designed web-accessible database, Tea Plant Information Archive (TPIA; http://tpia.teaplant.org). The current release of TPIA employs the comprehensively annotated tea plant genome as framework and incorporates with abundant well-organized transcriptomes, gene expressions (across species, tissues and stresses), orthologs and characteristic metabolites determining tea quality. It also hosts massive transcription factors, polymorphic simple sequence repeats, single nucleotide polymorphisms, correlations, manually curated functional genes and globally collected germplasm information. A variety of versatile analytic tools (e.g. JBrowse, blast, enrichment analysis, etc.) are established helping users to perform further comparative, evolutionary and functional analysis. We show a case application of TPIA that provides novel and interesting insights into the phytochemical content variation of section Thea of genus Camellia under a well-resolved phylogenetic framework. The constructed knowledgebase of tea plant will serve as a central gateway for global tea community to better understand the tea plant biology that largely benefits the whole tea industry.

Using stable isotope signatures to delineate the geographic point-of-origin of Keemun black tea.

BACKGROUND: Confirmation of food labeling that claims production in a small geographic region is critical to traceability, quality control and brand protection. In the current study, isotope ratio mass spectrometry (IRMS) was used to generate profiles of δ13 C and δ15 N to determine if the stable isotope signatures of Keemun black tea differ within the three counties that claim production. Other factors (cultivar type, leaf maturity and manufacturing process) were considered for their potential effects. RESULTS: Both cultivar type and leaf maturity have remarkable impact on the δ15 N values of tea leaves, and that the cultivar influenced the δ13 C values. Keemun black tea from Qimen county could be easily discriminated from samples from Dongzhi and Guichi counties based on δ15 N signatures. The k-NN model was cross-validated with an accuracy of 91.6%. Environmental factors and/or genotype seem to be the major reasons for δ15 N differences in Keemun black tea from the selected regions. CONCLUSION: This article provides a potential effective method to delineate the geographic point-of-origin of Keemun black tea based on δ15 N signatures. © 2018 Society of Chemical Industry.

Enantioselective Bromocyclization of Tryptamines Induced by Chiral Co(III)-Complex-Templated Brønsted Acids under an Air Atmosphere.

The chiral Co(III)-complex-templated Brønsted acids were found to be efficient bifunctional phase-transfer catalysts for the highly enantioselective bromocyclization of protected tryptamines with readily available N-bromosuccinimide (NBS) under an air atmosphere. The 3-bromohexahydropyrrolo[2,3- b]indoles, which are key building blocks of cyclotryptamine alkaloids, were thus obtained in up to 95% yield and 93.5:6.5 er.

Anion Channel Inhibitor NPPB-Inhibited Fluoride Accumulation in Tea Plant (Camellia sinensis) Is Related to the Regulation of Ca²âº, CaM and Depolarization of Plasma Membrane Potential.

Tea plant is known to be a hyper-accumulator of fluoride (F). Over-intake of F has been shown to have adverse effects on human health, e.g., dental fluorosis. Thus, understanding the mechanisms fluoride accumulation and developing potential approaches to decrease F uptake in tea plants might be beneficial for human health. In the present study, we found that pretreatment with the anion channel inhibitor NPPB reduced F accumulation in tea plants. Simultaneously, we observed that NPPB triggered Ca(2+) efflux from mature zone of tea root and significantly increased relative CaM in tea roots. Besides, pretreatment with the Ca(2+) chelator (EGTA) and CaM antagonists (CPZ and TFP) suppressed NPPB-elevated cytosolic Ca(2+) fluorescence intensity and CaM concentration in tea roots, respectively. Interestingly, NPPB-inhibited F accumulation was found to be significantly alleviated in tea plants pretreated with either Ca(2+) chelator (EGTA) or CaM antagonists (CPZ and TFP). In addition, NPPB significantly depolarized membrane potential transiently and we argue that the net Ca(2+) and H⁺ efflux across the plasma membrane contributed to the restoration of membrane potential. Overall, our results suggest that regulation of Ca(2+)-CaM and plasma membrane potential depolarization are involved in NPPB-inhibited F accumulation in tea plants.

[Rapid and Dynamic Determination Models of Amino Acids and Catechins Concentrations during the Processing Procedures of Keemun Black Tea].

Tea is one of the most popular beverages in the world. For the contribution to the taste and healthy functions of tea, amino acids and catechins are important components. Among different kinds of black teas in the world, Keemun black tea has the famous and specific fragrance, "Keemun aroma". During the processing procedure of Keemun black tea, the contents of amino acids and catechins changed greatly, and the differences of these concentrations during processing varied significantly. However, a rapid and dynamic determination method during the processing procedure was not existed up to now. In order to find out a rapid determination method for the contents of amino acids and catechins during the processing procedure of Keemun black tea, the materials of fresh leaves, withered leaves, twisted leaves, fermented leaves, and crude tea (after drying) were selected to acquire their corresponding near infrared spectroscopy and obtain their contents of amino acids and catechins by chemical analysis method. The original spectra data were preprocessed by the Standard Normal Variate Transformation (SNVT) method. And the model of Near Infrared (NIR) spectroscopy with the contents of amino acids and catechins combined with Synergy Interval Partial Least squares (Si-PLS) was established in this study. The correlation coefficients and the cross validation root mean square error are treated as the efficient indexes for evaluating models. The results showed that the optimal prediction model of amino acids by Si-PLS contained 20 spectral intervals combined with 4 subintervals and 9 principal component factors. The correlation coefficient and the root mean square error of the calibration set were 0. 955 8 and 1. 768, respectively; the correlation coefficient and the root mean square error of the prediction set were 0. 949 5 and 2. 16, respectively. And the optimal prediction model of catechins by Si-PLS contained 20 spectral intervals combined with 3 subintervals and 10 principal component factors. The correlation coefficient and the root mean square error of the calibration set were 0. 940 1 and 1. 22, respectively; the correlation coefficient and the root mean square error of the prediction set were 0. 938 5 and 1. 17, respectively. The results showed that the established models had good accuracy which could provide a theoretical foundation for the online determination of tea chemical components during processing.

TMDB: a literature-curated database for small molecular compounds found from tea.

BACKGROUND: Tea is one of the most consumed beverages worldwide. The healthy effects of tea are attributed to a wealthy of different chemical components from tea. Thousands of studies on the chemical constituents of tea had been reported. However, data from these individual reports have not been collected into a single database. The lack of a curated database of related information limits research in this field, and thus a cohesive database system should necessarily be constructed for data deposit and further application. DESCRIPTION: The Tea Metabolome database (TMDB), a manually curated and web-accessible database, was developed to provide detailed, searchable descriptions of small molecular compounds found in Camellia spp. esp. in the plant Camellia sinensis and compounds in its manufactured products (different kinds of tea infusion). TMDB is currently the most complete and comprehensive curated collection of tea compounds data in the world. It contains records for more than 1393 constituents found in tea with information gathered from 364 published books, journal articles, and electronic databases. It also contains experimental 1H NMR and 13C NMR data collected from the purified reference compounds or collected from other database resources such as HMDB. TMDB interface allows users to retrieve tea compounds entries by keyword search using compound name, formula, occurrence, and CAS register number. Each entry in the TMDB contains an average of 24 separate data fields including its original plant species, compound structure, formula, molecular weight, name, CAS registry number, compound types, compound uses including healthy benefits, reference literatures, NMR, MS data, and the corresponding ID from databases such as HMDB and Pubmed. Users can also contribute novel regulatory entries by using a web-based submission page. The TMDB database is freely accessible from the URL of http://pcsb.ahau.edu.cn:8080/TCDB/index.jsp. The TMDB is designed to address the broad needs of tea biochemists, natural products chemists, nutritionists, and members of tea related research community. CONCLUSION: The TMDB database provides a solid platform for collection, standardization, and searching of compounds information found in tea. As such this database will be a comprehensive repository for tea biochemistry and tea health research community.

A new norisoprenoid and other compounds from Fuzhuan brick tea.

Fuzhuan brick tea, a kind of dark tea consumed mainly in the border regions of Southwestern and Northwestern China since the 1860s, is produced from the leaves of Camellia sinensis var. sinensis by microbial fermentation. From this special fermented tea, a new norisoprenoid, 3R,9R-oxido-5-megastigmene, was isolated, together with α-linolenic acid, strictin, isovitexin, astragalin, (+)-catechin, (-)-epicatechin, (-)-epicatechin gallate, (+)-gallocatechin, (-)-epigallocatechin, (-)-epigallocatechin gallate and gallic acid. The structures of the compounds were identified by spectroscopic means. The new compound didn't show any inhibition activity against the tested enteric pathogenic microorganisms at a concentration of 800 µg/mL by the hole plate diffusion method.

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds.

BACKGROUND: Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. RESULTS: Using high-throughput Illumina RNA-seq, the transcriptome from poly (A)+ RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real time PCR (qRT-PCR). CONCLUSIONS: An extensive transcriptome dataset has been obtained from the deep sequencing of tea plant. The coverage of the transcriptome is comprehensive enough to discover all known genes of several major metabolic pathways. This transcriptome dataset can serve as an important public information platform for gene expression, genomics, and functional genomic studies in C. sinensis.

Molecular and Biochemical Characterization of Jasmonic Acid Carboxyl Methyltransferase Involved in Aroma Compound Production of Methyl Jasmonate during Black Tea Processing.

Methyl jasmonate (MeJA), a volatile organic compound, is a principal flowery aromatic compound in tea. During the processing of black tea, MeJA is produced by jasmonic acid carboxyl methyltransferase (JMT) of the jasmonic acid (JA) substrate, forming a specific floral fragrance. CsJMT was cloned from tea leaves; the three-dimensional structure of CsJMT was predicted. Enzyme activity was identified, and protein purification was investigated. Site-directed deletions revealed that N-10, S-22, and Q-25 residues in the beginning amino acids played a key functional role in enzyme activity. The expression patterns of CsJMT in tea organs differed; the highest expression of CsJMT was observed in the fermentation process of black tea. These results aid in further understanding the synthesis of MeJA during black tea processing, which is crucial for improving black tea quality using specific fragrances and could be applied to the aromatic compound regulation and tea breeding improvement in further studies.

Antiseptic activity and phenolic constituents of the aerial parts of Vitex negundo var. cannabifolia.

Four phenolics, salviaplebeiaside (1), γ-tocopherol (2), chrysosplenol-D (4), and isovitexin (5), along with α-tocoquinone (3) and ß-sitosterol (6) were isolated from the aerial parts of Vitex negundo var. cannabifolia. The isolation was performed using bio-assay tracking experiments. The structures of compounds 1-5 were established by spectroscopic means. The antibacterial activities of the compounds were assessed against Escherichia coli, Bacillus subtilis, Micrococcus tetragenus and Pseudomonas fluorescens. Chrysosplenol-D (4) exhibited activities against all the four spoilage microorganisms.

Metabolite and Transcriptome Profiling on Xanthine Alkaloids-Fed Tea Plant (Camellia sinensis) Shoot Tips and Roots Reveal the Complex Metabolic Network for Caffeine Biosynthesis and Degradation.

While caffeine is one of the most important bioactive metabolites for tea as the most consumed non-alcohol beverage, its biosynthesis and catabolism in tea plants are still not fully understood. Here, we integrated purine alkaloid profiling and transcriptome analysis on shoot tips and roots fed with caffeine, theophylline, or theobromine to gain further understanding of caffeine biosynthesis and degradation. Shoot tips and roots easily took up and accumulated high concentrations of alkaloids, but roots showed much faster caffeine and theophylline degradation rates than shoot tips, which only degraded theophylline significantly but almost did not degrade caffeine. Clearly feedback inhibition on caffeine synthesis or inter-conversion between caffeine, theophylline, and theobromine, and 3-methylxanthine had been observed in alkaloids-fed shoot tips and roots, and these were also evidenced by significant repression of TCS and MXMT genes critical for caffeine biosynthesis. Among these responsively repressed genes, two highly expressed genes TCS-4 and TCS-8 were characterized for their enzyme activity. While we failed to detect TCS-4 activity, TCS-8 displayed N-methyltransferase activities towards multiple substrates, supporting the complex metabolic network in caffeine biosynthesis in tea plants since at least 13 TCS-like N-methyltransferase genes may function redundantly. This study provides new insight into complex metabolic networks of purine alkaloids in tea plants.

Micro-NIR spectrometer for quality assessment of tea: Comparison of local and global models.

Near-infrared (NIR) spectroscopy is an effective tool for analyzing components relevant to tea quality, especially catechins and caffeine. In this study, we predicted catechins and caffeine content in green and black tea, the main consumed tea types worldwide, by using a micro-NIR spectrometer connected to a smartphone. Local models were established separately for green and black tea samples, and these samples were combined to create global models. Different spectral preprocessing methods were combined with linear partial-least squares regression and nonlinear support vector machine regression (SVR) to obtain accurate models. Standard normal variate (SNV)-based SNV-SVR models exhibited accurate predictive performance for both catechins and caffeine. For the prediction of quality components of tea, the global models obtained results comparable to those of the local models. The optimal global models for catechins and caffeine were SNV-SVR and particle swarm optimization (PSO)-simplified SNV-PSO-SVR, which achieved the best predictive performance with correlation coefficients in prediction (Rp) of 0.98 and 0.93, root mean square errors in prediction of 9.83 and 2.71, and residual predictive deviations of 4.44 and 2.60, respectively. Therefore, the proposed low-price, compact, and portable micro-NIR spectrometer connected to smartphones is an effective tool for analyzing tea quality.

Tea plant genomics: achievements, challenges and perspectives.

Tea is among the world's most widely consumed non-alcoholic beverages and possesses enormous economic, health, and cultural values. It is produced from the cured leaves of tea plants, which are important evergreen crops globally cultivated in over 50 countries. Along with recent innovations and advances in biotechnologies, great progress in tea plant genomics and genetics has been achieved, which has facilitated our understanding of the molecular mechanisms of tea quality and the evolution of the tea plant genome. In this review, we briefly summarize the achievements of the past two decades, which primarily include diverse genome and transcriptome sequencing projects, gene discovery and regulation studies, investigation of the epigenetics and noncoding RNAs, origin and domestication, phylogenetics and germplasm utilization of tea plant as well as newly developed tools/platforms. We also present perspectives and possible challenges for future functional genomic studies that will contribute to the acceleration of breeding programs in tea plants.

Guanine deaminase provides evidence of the increased caffeine content during the piling process of pu'erh tea.

Wet piling is a key process for producing pu'erh tea because various components change under the action of microorganisms. Among these components, caffeine content is increased. Evidence has indicated a salvage pathway for caffeine biosynthesis in microbes, in which xanthine is methylated in the order of N-3 → N-1 → N-7. In addition, guanine can be used to synthesize xanthine through guanine deaminase (EC: 3.5.4.3). In this study, we investigated the variation in caffeine content during piling fermentation with supplementary guanine, 15N-labeled guanine and xanthine. We cloned the guanine deaminase gene (GUD1) from Saccharomyces cerevisiae (one dominant strain in piling fermentation). The results revealed that [15N]xanthine could be synthesized from [15N]guanine, and [15N]caffeine was also detected during piling with supplementary [15N]xanthine. Furthermore, ScGUD1 could catalyze the conversion of guanine to xanthine, which is likely to be methylated for caffeine synthesis under microorganism action. The obtained results revealed the mechanism underlying the increased caffeine content during piling of pu'erh tea.

Fabricating an Acetylcholinesterase Modulated UCNPs-Cu2+ Fluorescence Biosensor for Ultrasensitive Detection of Organophosphorus Pesticides-Diazinon in Food.

In this study, a highly sensitive upconversion fluorescence (FL) biosensor was developed for the detection of organophosphorus pesticides (OPs) based on an acetylcholinesterase (AChE) modulated FL "off-on-off" strategy. The luminescence of synthesized UCNPs could be quenched strongly by Cu2+ due to an energy transfer effect. Upon addition of AChE and acetylthiocholine (ATCh), the enzymatic hydrolysate (thiocholine) could seize Cu2+ from UCNPs-Cu2+ mixture, resulting in the quenched FL triggered on. OPs could irreversibly impede the activity of AChE, which caused the formation of thiocholine to decrease, thus, reduced the recovery of FL. Under the optimum conditions, a linear detection range from 0.1 to 50 ng/mL was achieved for the representative OPs (diazinon) with LOD of 0.05 ng/mL. Furthermore, the ability of the biosensor to detect OPs was also confirmed in adulterated environmental and agricultural samples. In validation analysis, the proposed sensor showed satisfactory results ( p > 0.05) with GC-MS.

Caffeine Content and Related Gene Expression: Novel Insight into Caffeine Metabolism in Camellia Plants Containing Low, Normal, and High Caffeine Concentrations.

Caffeine is a crucial secondary metabolic product in tea plants. Although the presence of caffeine in tea plants has been identified, the molecular mechanisms regulating relevant caffeine metabolism remain unclear. For the elucidation of the caffeine biosynthesis and catabolism in Camellia plants, fresh, germinated leaves from four Camellia plants with low (2), normal (1), and high (1) caffeine concentrations, namely, low-caffeine tea 1 (LCT1, Camellia crassicolumna), low-caffeine tea 2 (LCT2, C. crassicolumna), Shuchazao (SCZ, C. sinensis), and Yunkang 43 (YK43, C. sinensis) were used in this research. Transcriptome and purine alkaloids analyses of these Camellia leaves were performed using RNA-Seq and liquid chromatography-mass spectrometry (LC-MS). Moreover, 15N-caffeine tracing was performed to determine the metabolic fate of caffeine in leaves of these plants. Caffeine content was correlated with related gene expression levels, and a quantitative real-time (qRT) PCR analysis of specific genes showed a consistent tendency with the obtained transcriptomic analysis. On the basis of the results of stable isotope-labeled tracer experiments, we discovered a degradation pathway of caffeine to theobromine. These findings could assist researchers in understanding the caffeine-related mechanisms in Camellia plants containing low, normal, and high caffeine content and be applied to caffeine regulation and breeding improvement in future research.