Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome.

Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena.

2014-2016 seasonal rainfall effects on metals in tea (Camelia sinensis (L.) Kuntze).

Plant-climate interactions affect the edible crop composition, impacting flavor, nutrition, and overall consumer liking. In this study, principal components analysis was used to assess the macro- and micronutrient metal concentrations in pre-monsoon (spring), monsoon (summer), and post-monsoon (autumn) tea (Camelia sinensis (L.) Kuntze) from Yunnan Province, China in 2014-2016. Statistical differences were observed (p = 1.35E-24). Fe, Ca, Mg, Mn, Al, and Ba concentrations were higher in June (monsoon) than in March (pre-monsoon) and September (post-monsoon) compared to Pb, K, Cu, Zn, and Na, which were higher in March and September. Although Fe, Ca, Mg, Mn, Al, and Ba concentrations increased during the monsoon season, sensory analysis did not detect metallic taste in either minimally processed or farmer-processed (commercial) teas. This finding shows the seasonal differences in flavor were due to striking differences in organic chemical composition and concentration.

Differentiation of key biomarkers in tea infusions using a target/nontarget gas chromatography/mass spectrometry workflow.

Climatic conditions affect the chemical composition of edible crops, which can impact flavor, nutrition and overall consumer preferences. To understand these effects new data analysis software capable of tracking hundreds of compounds across years of samples under various environmental conditions is needed. Our recently developed mass spectral (MS) subtraction algorithms have been used with spectral deconvolution to efficiently analyze complex samples by 2-dimensional gas chromatography/mass spectrometry (GC-GC/MS). In this paper, we address the accuracy of identifying target and nontarget compounds by GC/MS. Findings indicate that Yunnan tea contains higher concentrations of floral compounds. In contrast, Fujian tea contains higher concentrations of compounds that exhibit fruity characteristics, but contains much less monoterpenes. Principal components analysis shows that seasonal changes in climate impact tea plants similarly despite location differences. For example, spring teas contained more of the sweet, floral and fruity compounds compared to summer teas, which had higher concentrations of green, woody, herbal compounds.

Striking changes in tea metabolites due to elevational effects.

Climate effects on crop quality at the molecular level are not well-understood. Gas and liquid chromatography-mass spectrometry were used to measure changes of hundreds of compounds in tea at different elevations in Yunnan Province, China. Some increased in concentration while others decreased by 100's of percent. Orthogonal projection to latent structures-discriminant analysis revealed compounds exhibiting analgesic, antianxiety, antibacterial, anticancer, antidepressant, antifungal, anti-inflammatory, antioxidant, anti-stress, and cardioprotective properties statistically (p = 0.003) differentiated high from low elevation tea. Also, sweet, floral, honey-like notes were higher in concentration in the former while the latter displayed grassy, hay-like aroma. In addition, multivariate analysis of variance showed low elevation tea had statistically (p = 0.0062) higher concentrations of caffeine, epicatechin gallate, gallocatechin, and catechin; all bitter compounds. Although volatiles represent a small fraction of the total mass, this is the first comprehensive report illustrating how normal variations in temperature, 5 °C, due to elevational effects impact tea quality.

Metabolite profiling of Camellia sinensis by automated sequential, multidimensional gas chromatography/mass spectrometry reveals strong monsoon effects on tea constituents.

Seasonal variation in tea (Camellia sinensis (L.) Kuntze; Theaceae) chemistry was investigated using automated sequential, multidimensional gas chromatography/mass spectrometry (GC-GC/MS). Metabolite libraries were produced for teas harvested from the Bulang Mountains in Yunnan, China before and after the onset of the East Asian Monsoon. A total of 201 spring and 196 monsoon metabolites were identified, with 169 common and 59 seasonally unique compounds. An additional 163 metabolites were detected but their identity could not be confirmed. Spectral deconvolution of GC/MS data was used to measure the relative concentrations in the teas. Within each family individual metabolite concentrations increased, decreased and stayed the same. The major constituents in both teas were linalool (28%), geraniol (13%), α-terpineol (10%), hotrienol (4%) and nerol (3%). This work provides the foundation to monitor seasonal variations of tea chemistry.