Journal of Pharmaceutical Analysis
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2019
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IF 4.44
Yang Huang,Tiejie Wang,Marianne Fillet,Jacques Crommen,Zhengjin Jiang
Tea is a widely consumed beverage and has many important physiological properties and potential health benefits. In this study, a novel method based on supercritical fluid chromatography coupled with mass spectrometry (SFC-MS) was developed to simultaneously determine 11 amino acids in different types of tea (green teas, Oolong tea, black tea and Pu-erh tea). The separation conditions for the analysis of the selected amino acids including the column type, temperature and backpressure as well as the type of additive, were carefully optimized. The best separation of the 11 amino acids was obtained by adding water (5%, v/v) and trifluoroacetic acid (0.4%, v/v) to the organic modifier (methanol). Finally, the developed SFC-MS method was fully validated and successfully applied to the determination of these amino acids in six different tea samples. Good linearity ( r ≥ 0.993), precision (RSDs ≤ 2.99%), accuracy (91.95%–107.09%) as well as good sample stability were observed. The limits of detection ranged from 1.42 to 14.69 ng/mL, while the limits of quantification were between 4.53 and 47.0 ng/mL. The results indicate that the contents of the 11 amino acids in the six different tea samples are greatly influenced by the degree of fermentation. The proposed SFC-MS method shows a great potential for further investigation of tea varieties.
研究领域:
食品科学
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分析化学
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DOI
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
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2024
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IF 6
Yiwen Xie,Chaofan Guo,Sakamon Devahastin,Lianzhou Jiang,Ming Du,Junjie Yi
Electronic nose along with different machine learning approaches was tested as tool to predict degree of sufu fermentation, with amino acid nitrogen content as marker. Consistent increase in E-nose signal values and amino acid nitrogen content were noted with fermentation time. The number of volatile compounds in sufu increased from 19 to 61 upon fermentation, with 46 compounds identified as major aroma contributors. Among them, acetone, ethyl palmitate and indole demonstrated strong correlations with amino acid nitrogen content. Three prediction models, i.e. , partial least-squares regression, support vector machine, and artificial neural network, were tested for abilities to predict amino acid nitrogen content. All models were capable of quantitatively predicting the content of amino acid nitrogen, with ANN-based model demonstrating the highest prediction accuracy ( R P 2 = 0.968, RMSE = 5.49 × 10 −8 ). Electronic nose along with appropriate prediction model is noted as a promising tool for evaluating the degree of sufu fermentation.
研究领域:
食品科学
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生物化学
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DOI
高影响因子
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
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2014
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IF 3.107
Quan-Jin Wu,Qing-Hua Dong,Wei-Jiang Sun,Yan Huang,Qiong-Qiong Wang,Wei-Long Zhou
This study aimed to construct objective and accurate analytical models of tea categories based on their polyphenols and caffeine. A total of 522 tea samples of 4 commonly consumed teas with different fermentation degrees (green tea, white tea, oolong tea, and black tea) were analyzed by high-performance liquid chromatography (HPLC) coupled with spectrophotometry, utilizing ISO 14502, as analytical tools. The content of polyphenols and caffeine varied significantly according to differently fermented teas, indicating that these active constituents may discriminate fermentation degrees effectively. By principal component analysis (PCA) and stepwise linear discriminant analysis (S-LDA), the vast majority of tea samples could be successfully differentiated according to their chemical markers. This study yielded three discriminant functions with the capacity to simultaneously discriminate the four tea categories with a 97.8% correct rate. In classification of oolong and other teas, there were one discriminant function and two equations with best discriminant capacity. Furthermore, the classification of different degrees of fermentation of oolong and external validation achieved the desired results. It is suggested that polyphenols and caffeine are the distinct variables to establish internationally recognized models of teas.
研究领域:
食品科学
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分析化学
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植物学
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DOI
PubMed
高影响因子
FOOD CHEMISTRY
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2024
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IF 8.5
Zhao-Jing Jiang,Xiao-Na Guo,Ke-Xue Zhu
This study investigated the effects of pre-fermentation degree and storage temperature fluctuations on the gas cells, gluten protein, rheological properties of frozen dough, and quality of steamed bread. Three pre-fermentation degrees and four fluctuating temperatures (−10 °C, 0 °C, 10 °C, and 25 °C) were used. The gas cell size increased with the pre-fermentation degree; however, the gas cells merged and ruptured during temperature fluctuations. Sodium dodecyl sulfate extraction protein content and free sulfhydryl content increased by 3.07 % and 33.62 %, respectively, in the medium pre-fermentation group at 25 °C compared with those at −10 °C. The maximum strain of dough increased as pre-fermentation degree and fluctuating temperatures increased. The specific volumes of steamed bread with medium pre-fermentation degree were 1.87 mL/g at −10 °C and 1.47 mL/g at 25 °C. In conclusion, higher temperature fluctuations exceeding the freezing point exacerbated the dough and steamed bread quality, particularly in high pre-fermentation degree dough.
研究领域:
食品科学
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生物化学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
FOOD CHEMISTRY
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2024
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IF 8.5
Jingtao Zhou,Muxue Qin,Junyu Zhu,Bernard Ntezimana,Xinfeng Jiang,De Zhang,Zhi Yu,Yuqiong Chen,Dejiang Ni
Fermentation is a key process in Congou black tea, but there is limited research on the changes in flavor factors and their interrelationships during different fermentation stages under industrial production. This study applies sensory evaluation and metabolomics techniques to explore the interactions between flavors. Sensory evaluation indicated that the 4-h fermented sample exhibited the best overall performance. The experiment of adding aroma substances further revealed the significant effects of sweet aroma and green odor on taste of sweetness and astringency. Additionally, 532 flavor compounds were identified using high-resolution liquid chromatography-mass spectrometry and gas chromatography–mass spectrometry. Moreover, significant differences were observed in the volatile compounds derived from flavonoids, amino acids, and fatty acids of samples with different fermentation degrees. Furthermore, weighted co -expression network analysis of flavor compounds showed that the oxidation of polyphenols, especially catechins, plays an important regulatory role in content changes of volatile and other non-volatile compounds during fermentation.
研究领域:
食品科学
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农学
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化学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
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