Simultaneous nitrogen-blow distillation extraction: A novel approach for aroma extraction of white tea

Formation of aroma characteristics driven by microorganisms during long-term storage of Liubao tea

Liubao tea (LBT) with longer storage year is believed to have better sensory quality. The aroma characteristics and fungal community succession during the storage process of LBT were studied using LBT stored for 2-15 years as materials. The results showed that the aroma characteristics of LBT showed significant changes in 3 stages. After 10 years of storage, the sensory quality of LBT was notably improved, with herbal aroma beginning to emerge and a distinctly woody aroma. In addition, fungi were involved in the transformation of substances to affect the aroma quality during the storage of LBT. Aspergillus and Penicillium may help reduce musty and green odors and enhancing woody and herbal odors based on correlation analysis. This study provided useful information on the key aroma compounds and core functional microorganisms that drive the aroma characteristics formation of LBT during storage.

Underlying characteristic aroma of white tea from diverse geographical origins and its prediction

BACKGROUND

White tea, an agriculturally distinctive product, exhibits significant aroma variations across different regions. Nevertheless, the mechanisms driving these differences, and distinguishing methods suitable for specific origins, have been scarcely reported. In this study, we analyzed the aroma characteristics and volatile components of 100 white tea samples from ten regions, utilizing sensory evaluation, headspace solid-phase microextraction-gas chromatography-mass spectrometry and chemometrics, then established a discrimination model.

RESULTS

A total of 66 volatile compounds were identified, with alcohols and esters being the most important. Linalool and geranyl alcohol were common and relatively abundant volatile compounds across all ten regions, significantly contributing to the aroma characteristics of white tea. The relative content of volatile compounds differed notably across regions, where 33 key compounds, including (E)-2-phenylbut-2-enal and methyl 2,5-octadecadiynoate, were crucial for regional prediction. Employing machine learning algorithms, such as random forest and support vector machine for regional prediction, yielded accuracies of 93.33% and 90.00%, respectively.

CONCLUSION

This study unveils new insights into aroma variation in white tea across different origins, proposing an innovative way of origin determination. © 2025 Society of Chemical Industry.

Machine learning-aided enhancement of white tea extraction efficiency using hybridized GMDH models in microwave-assisted extraction

White tea is valuable for having a high antioxidant content, which is considered to possess numerous beneficial effects on health. This study investigated the application of microwave-assisted extraction (MAE) for the extraction of total phenolic compounds from white tea. The experimental setup included four independent variables: microwave power (ranging from 100 to 300 W), extraction time (ranging from 10 to 40 min), temperature (ranging from 35 to 50 °C), and the ratio of food to solvent (ranging from 0.25 to 0.5 g/10 mL). The responses that were evaluated were IC50 (ppm) and total phenolic content (mg/g). The experimental design consisted of thirty runs conducted within the MAE system. The group method of data handling (GMDH) models were used to predict important efficiency measures (IC50 and total phenol content) in the extraction process. The models were assessed based on their ability to capture the relationships between input conditions and efficiency outputs. Three GMDH variants were compared: baseline GMDH, GMDH optimized with a genetic algorithm (GMDH-GA), and GMDH optimized with a harmony search algorithm (GMDH-HS). While all models achieved high predictive ability on a test set, GMDH-HS emerged as the superior performer. It achieved near-perfect agreement with observations (d-index > 0.998), minimal errors (NRMSE < 0.02), and effectively captured data variance (NSE > 0.99) for both outputs. Correlation diagrams and Taylor diagrams confirmed the superior performance of GMDH-HS in terms of linearity, correlation, and error minimization. This study demonstrates the effectiveness of hybridizing GMDH with a harmony search algorithm for complex modeling tasks, paving the way for improved efficiency and yield optimization in extraction processes.

A newly-discovered tea population variety processed Bai Mu Dan white tea: Flavor characteristics and chemical basis

The quality of white tea (WT) is impacted by selected tea cultivars. To explore the organoleptic quality of a recently-discovered WT ("Caicha", CC), HS-SPME/GC-MS and UPLC were employed to identify volatile and non-volatile compounds in tea samples. Multiple statistical methods demonstrated the distinctions between CC and four mainstream WT varieties from main producing areas. CC exhibited abundant volatile alcohol, terpenoids, ketone, aldehyde and ester, as well as non-volatile lignans and coumarins, phenolic acids and low-molecular carbohydrates. These substances combinedly contributed to the flavor attributes of CC, characterized by an intense herbal/citrus-like cleanness and flower/fruit-like sweetness, scarce in existing commercial WT varieties. Sensory evaluation corroborated these findings. In conclusion, we have processed a new tea variety (CC) with WT manufacturing technology, and discovered the unique cleanness and sweetness of it. This study enriches the raw material database for WT production and blending, and boosts the development of more premium WT varieties.

Unraveling the contributing factors of stale odor in Longjing tea through a sensomics approach

Longjing tea is renowned for its fresh aroma and high value. However, during storage, the emergence of an off-flavor known as "stale odor" can significantly impact the flavor quality and economic benefits of Longjing tea. Yet, the specific volatiles responsible for this stale odor in Longjing tea remain unknown. In this study, Longjing tea samples with varying degrees of stale odor intensity were analyzed using simultaneous distillation extraction coupled with gas chromatography-mass spectrometry (SDE-GC-MS). Through odor activity value (OAV) and fractional omission testing, hexanoic acid and trans-2-nonenal were identified as the primary contributors to the stale odor. Moreover, the concentration of hexanoic acid was found to be valuable in predicting the intensity of the stale odor in Longjing tea. The oxidative degradation of linoleic acid was proved as the generation pathway of stale odor in Longjing tea. These findings provide essential theoretical principles for Longjing tea production and preservation.

Metabolomics investigation of the chemical variations in white teas with different producing areas and storage durations

In this study, we employed nontargeted metabolomics and quantitative analysis to explore the variations in metabolites among white teas from different production areas and with varying storage durations. A total of 83 compounds exhibited differential levels between Zhenghe and Fuding white tea, 89 between Zhenghe and Jinggu, and 75 between Fuding and Jinggu white tea. Concerning the storage of white tea, the concentrations of flavanols, dimeric catechins, and amino acids decreased over time, while N-ethyl-2-pyrrolidone-substituted flavanols (EPSFs), caffeine, adenosine monophosphate (AMP), and adenosine increased. Galloylated flavanols showed a higher propensity to form EPSFs with theanine compared to nongalloylated flavanols during storage. Theanine and epigallocatechin gallate were more inclined to generate S-configuration EPSFs during storage in Fuding and Jinggu white tea samples, while R-configuration EPSFs were more readily formed in Zhenghe white tea samples. This study offers a comprehensive understanding of the changes in metabolites during the storage of white tea.

The characteristic of the key aroma-active components in white tea using GC-TOF-MS and GC-olfactometry combined with sensory-directed flavor analysis

BACKGROUND

White tea has become more and more popular with consumers due to its health benefits and unique flavor. However, the key aroma-active compounds of white tea during the aging process are still unclear. Thus, the key aroma-active compounds of white tea during the aging process were investigated using gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS) and gas chromatography-olfactometry (GC-O) combined with sensory-directed flavor analysis.

RESULTS

A total of 127 volatile compounds were identified from white tea samples with different aging years by GC-TOF-MS. Fifty-eight aroma-active compounds were then determined by GC-O, and 19 of them were further selected as the key aroma-active compounds based on modified frequency (MF) and odor activity value (OAV).

CONCLUSION

Aroma recombination and omission testing confirmed that 1-octen-3-ol, linalool, phenethyl alcohol, geraniol, (E)-β-ionone, α-ionone, hexanal, phenylacetaldehyde, nonanal, (E, Z)-(2,6)-nonadienal, safranal, γ-nonalactone and 2-amylfuran were the common key aroma-active compounds to all samples. Cedrol, linalool oxide II and methyl salicylate were confirmed peculiar in new white tea, while β-damascenone and jasmone were peculiar in aged white tea. This work will offer support for further studies on the material basis of flavor formation of white tea. © 2023 Society of Chemical Industry.

Construction of Sensory/Mass Spectrometry Feedback Platform for Seeking Aroma Contributors during the Aroma Enhancement of Congou Black Tea

Baking is widely accepted for aroma enhancement of black tea, and studies have mainly focused on the aroma or chemical substances under a specified baking condition. Understanding of the feedback between aroma substances and characteristics is urgently needed. Therefore, a mutual feedback platform (SES/MS) combined sensory evaluation system (SES) with gas chromatography–mass spectrometry (GC-MS) was established. Based on this platform, we found that baking at 90 °C for 4 h or 5 h could maintain the primary aroma attributes and increase characteristic aroma attributes—these were considered to be the best baking conditions for Yunnan congou black tea. Meanwhile, 47 volatiles were identified, among which, pyrrole and benzaldehyde appeared to have a caramel aroma, and 2-furanmethanol and α-terpineol presented a baked aroma. This study reveals the dynamic change of aroma profiles and compounds during the aroma enhancement, and provides an optional template for researchers, focused on the relationship between quality and aroma attributes of teas.