The Chemistry of Green and Roasted Coffee by Selectable 1D/2D Gas Chromatography Mass Spectrometry with Spectral Deconvolution.

Gas chromatography/mass spectrometry (GC/MS) is a long-standing technique for the analysis of volatile organic compounds (VOCs). When coupled with the Ion Analytics software, GC/MS provides unmatched selectivity in the analysis of complex mixtures and it reduces the reliance on high-resolution chromatography to obtain clean mass spectra. Here, we present an application of spectral deconvolution, with mass spectral subtraction, to identify a wide array of VOCs in green and roasted coffees. Automated sequential, two-dimensional GC-GC/MS of a roasted coffee sample produced the retention index and spectrum of 750 compounds. These initial analytes served as targets for subsequent coffee analysis by GC/MS. The workflow resulted in the quantitation of 511 compounds detected in two different green and roasted coffees. Of these, over 100 compounds serve as candidate differentiators of coffee quality, AAA vs. AA, as designated by the Coopedota cooperative in Costa Rica. Of these, 72 compounds survive the roasting process and can be used to discriminate green coffee quality after roasting.

Climate and Processing Effects on Tea (Camellia sinensis L. Kuntze) Metabolome: Accurate Profiling and Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry.

This study applied an untargeted-targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu'erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu'erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu'erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.

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.

Effects of extreme climate events on tea (Camellia sinensis) functional quality validate indigenous farmer knowledge and sensory preferences in tropical China.

Climate change is impacting agro-ecosystems, crops, and farmer livelihoods in communities worldwide. While it is well understood that more frequent and intense climate events in many areas are resulting in a decline in crop yields, the impact on crop quality is less acknowledged, yet it is critical for food systems that benefit both farmers and consumers through high-quality products. This study examines tea (Camellia sinensis; Theaceae), the world's most widely consumed beverage after water, as a study system to measure effects of seasonal precipitation variability on crop functional quality and associated farmer knowledge, preferences, and livelihoods. Sampling was conducted in a major tea producing area of China during an extreme drought through the onset of the East Asian Monsoon in order to capture effects of extreme climate events that are likely to become more frequent with climate change. Compared to the spring drought, tea growth during the monsoon period was up to 50% higher. Concurrently, concentrations of catechin and methylxanthine secondary metabolites, major compounds that determine tea functional quality, were up to 50% lower during the monsoon while total phenolic concentrations and antioxidant activity increased. The inverse relationship between tea growth and concentrations of individual secondary metabolites suggests a dilution effect of precipitation on tea quality. The decrease in concentrations of tea secondary metabolites was accompanied by reduced farmer preference on the basis of sensory characteristics as well as a decline of up to 50% in household income from tea sales. Farmer surveys indicate a high degree of agreement regarding climate patterns and the effects of precipitation on tea yields and quality. Extrapolating findings from this seasonal study to long-term climate scenario projections suggests that farmers and consumers face variable implications with forecasted precipitation scenarios and calls for research on management practices to facilitate climate adaptation for sustainable crop production.

Comprehensive profiling of coal tar and crude oil to obtain mass spectra and retention indices for alkylated PAH shows why current methods err.

Investigators use C(1) to C(4) substituted polycyclic aromatic hydrocarbons (PAH) to assess ecological risk and to track fossil fuels and related pollutants in the environment. To quantify these compounds gas chromatography/mass spectrometry (GC/MS) is used. This work demonstrates single ion monitoring (SIM) or extraction (SIE) of full scan data produces inaccurate and imprecise concentration estimates due to incorrect homologue peak assignments. Profiling of coal tar and crude oil by automated sequential GC-GC/MS provided the retention windows and spectral patterns for each homologue to correctly quantify these compounds. Simultaneous pulsed flame photometric (sulfur-specific) detection differentiated PAH from polycyclic aromatic sulfur heterocycles and their alkylated homologues when they eluted within the same retention windows and had common ions. Differences between SIE and spectral deconvolution of GC/MS data based on multiple fragmentation patterns per homologue ranged from a few percent for C(1) compounds to hundreds of percent for the higher alkylated homologues. Findings show current methods produce poor quality data adversely affecting forensic investigations, risk assessments, and weathering studies.

Toward the accurate analysis of C1-C4 polycyclic aromatic sulfur heterocycles.

Polycyclic aromatic sulfur heterocycles (PASH) are sulfur analogues of polycyclic aromatic hydrocarbons (PAH). Alkylated PAH attract much attention as carcinogens, mutagens, and as diagnostics for environmental forensics. PASH, in contrast, are mostly ignored in the same studies due to the conspicuous absence of gas chromatography/mass spectrometry (GC/MS) retention times and fragmentation patterns. To obtain these data, eight coal tar and crude oils were analyzed by automated sequential GC-GC. Sample components separated based on their interactions with two different stationary phases. Newly developed algorithms deconvolved combinatorially selected ions to identify and quantify PASH in these samples. Simultaneous detection by MS and pulsed flame photometric detectors (PFPD) provided additional selectivity to differentiate PASH from PAH when coelution occurred. A comprehensive library of spectra and retention indices is reported for the C(1)-C(4) two-, three-, and four-ring PASH. Results demonstrate the importance of using multiple fragmentation patterns per homologue (MFPPH) compared to selected ion monitoring (SIM) or extraction (SIE) to identify isomers. Since SIM/SIE analyses dramatically overestimate homologue concentrations, MFPPH should be used to correctly quantify PASH for bioavailability, weathering, and liability studies.

Tracking juniper berry content in oils and distillates by spectral deconvolution of gas chromatography/mass spectrometry data.

The complex nature of botanicals and essential oils makes it difficult to identify all of the constituents by gas chromatography/mass spectrometry (GC/MS) alone. In this paper, automated sequential, multidimensional gas chromatography/mass spectrometry (GC-GC/MS) was used to obtain a matrix-specific, retention time/mass spectrometry library of 190 juniper berry oil compounds. GC/MS analysis on stationary phases with different polarities confirmed the identities of each compound when spectral deconvolution software was used to analyze the oil. Also analyzed were distillates of juniper berry and its oil as well as gin from four different manufacturers. Findings showed the chemical content of juniper berry can be traced from starting material to final product and can be used to authenticate and differentiate brands.

Quantitative identification of pesticides as target compounds and unknowns by spectral deconvolution of gas chromatographic/mass spectrometric data.

The results of gas chromatography/mass spectrometry (MS), with Ion Signature Technology, Inc. (North Smithfield, RI) quantitative deconvolution software, are discussed for pesticides identified both as target compounds by using retention and MS data and as unknowns by using only mass spectra. Target compound analysis of 32 pesticides, surrogates, and an internal standard added to lemon oil over a wide concentration range produced precision and accuracy that are well within the acceptable criteria of 25 and 50% for complex samples. When 112 pesticides were added to orange oil and searched as unknowns, 110 of the 112 compounds were correctly identified, with an average pesticide recovery of 101 +/- 19%. The injection volume of the orange oil fortified with pesticides was selected so that 4 ng per compound was injected on column. No false negatives were found, because ion signals for the 2 unidentified pesticides were not acquired by the instrument in either the standard mixture or the oil. No false positives were detected, although >750 widely different compounds were included in the library search.

Analysis of gin essential oil mixtures by multidimensional and one-dimensional gas chromatography/mass spectrometry with spectral deconvolution.

The composition of essential oils and their mixtures used to formulate gin is usually too complex to separate all sample components by standard capillary gas chromatography (GC). In particular, minor constituents that possess important organoleptic properties can be masked by co-elution with major sample components. A solution is provided that combines gas chromatography/mass spectrometry (GC/MS) with "interactive" spectral deconvolution software. Sequential two-dimensional (2D) GC/MS is used to produce a target compound library, with orthogonal GC-GC providing the separation power required to obtain peak retention times and the corresponding mass spectra needed for the deconvolution database. The combination of these two techniques, mass spectral deconvolution and automated sequential 2D-GC/MS, offers a very effective synergy for both identifying key constituents that determine the perception of flavor and aroma and the quality control needed to analyze mixtures of complex essential oils.