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FOOD RESEARCH INTERNATIONAL · 2024 · IF 7

Dynamic changes and the effects of key procedures on the characteristic aroma compounds of Lu’an Guapian green tea during the manufacturing process

Jieyao Yu,Jingzhe Li,Zhi Lin,Yin Zhu,Zhihui Feng,Dejiang Ni,Shengchun Zeng,Xuehong Zeng,Yijun Wang,Jingming Ning,Liang Zhang,Xiaochun Wan,Xiaoting Zhai

As a kind of green tea with unique multiple baking processes, the flavor code of Lu’an Guapian (LAGP) has recently been revealed. To improve and stabilize the quality of LAGP, further insight into the dynamic changes in odorants during the whole processing is required. In this study, 50 odorants were identified in processing tea leaves, 14 of which were selected for absolute quantification to profile the effect of processes. The results showed that spreading is crucial for key aroma generation and accumulation, while these odorants undergo significant changes at the deep baking stage. By adjusting the conditions of the spreading and deep baking, it was found that low-temperature (4 °C) spreading for 6 h and low-temperature with long-time baking (final leaf temperature: 102 °C, 45 min) could improve the overall aroma quality. These results provide a new direction for enhancing the quality of LAGP green tea.

研究领域: 食品科学 · 农学 · 茶学
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JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY · 2023 · IF 6.1

Sensomics-Assisted Characterization of Key Flowery Aroma Compounds in Lu’an Guapian Green Tea Infusion (Camellia sinensis)

Jieyao Yu,Chi-Tang Ho,Zhi Lin,Yin Zhu,Zhihui Feng,Dejiang Ni,Shengchun Zeng,Xuehong Zeng,Yijun Wang,Jingming Ning,Liang Zhang,Xiaoting Zhai,Xiaochun Wan

The volatile fraction was isolated from the premium and common grade of Lu’anGuapian green tea infusion by solvent-assisted flavor evaporation distillation. With the application of aroma extract dilution analysis, a total of 52 aroma-active compounds were revealed in the flavor dilution (FD) factor area of 32-8192. Besides, five additional odorants with higher volatility were identified using solid-phase microextraction. The aroma profiles, FD factors, and quantitative data of premium Guapian (PGP) and common Guapian (CGP) showed apparent differences. The intensity of the flowery attribute was significantly higher in PGP than in CGP, while cooked vegetable-like was the most outstanding odor note in CGP. The recombination experiment and the omission test of PGP clarified that dimethyl sulfide, (E,E)-2,4-heptadienal, (E)-β-ionone, (E,Z)-2,6-nonadienal, 2-methylbutanal, indole, 6-methyl-5-hepten-2-one, hexanal, 3-methylbutanal, γ-hexalactone, methyl epijasmonate, linalool, geraniol, and (Z)-3-hexen-1-ol were the key odorants of PGP tea infusion. The omission and addition tests of flowery odorants manifested that (E)-β-ionone, geraniol, and (E,E)-2,4-heptadienal, with higher odor activity values in PGP than in CGP, contributed to the flowery attribute most. The difference in the concentration of the abovementioned odorants with flowery odor notes could be one of the main factors which led to the difference in aroma quality between the two grades of Lu’an Guapian.

研究领域: 食品科学 · 茶叶化学 · 植物代谢组学
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FOOD RESEARCH INTERNATIONAL · 2024 · IF 7

Intelligent identification of picking periods of Lu’an Guapian tea by an indicator displacement colorimetric sensor array combined with machine learning

Yao Chen,Yuan Li,Li-Lin Lin,Yue Liao,Huan Fang,Tong Wang

Lu’an Gua Pian (LAGP) tea is one of the most famous green teas in China. The quality of green tea is related to its picking periods, especially the green tea before Qingming Festival (usually April 6th) is highly praised as precious in the market. In this work, a simple and cheap indicator displacement colorimetric sensor array combined with smartphone was developed to rapidly identify LAGP picked during different picking periods. First, the chemical component contents of LAGP picked before and after Qingming Festival were analyzed. Second, a well-designed colorimetric sensor array was proposed based on the tea component contents differences. Finally, machine learning was used to process the array data taken by a smartphone. By comparison, the accuracy of the best model for the prediction set was 97%. Meanwhile, the multi-channel advantages of the sensing array were demonstrated by an ablation experiment. In addition, the method achieved an AGREE analysis score of 0.88, indicating that it was environmental-friendly.

研究领域: 农业工程 · 食品科学 · 机器学习 · 感官科学
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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY · 2024 · IF 4.3

Identification of lu’an Guapian at different picking periods by using excitation–emission matrix fluorescence spectroscopy coupled with chemometrics

Hang Ren,Lin-Li Lin,Ming-Yue Dong,Xiao-Yue Yin,Tong Wang,Hai-Long Wu,Ru-Qin Yu

Lu’an Guapian (LAGP) is a renowned green tea, with its price significantly higher when picked before the Qingming Festival compared to after, posing risks of confusion and counterfeiting. This study proposed using an excitation-emission matrix (EEM) fluorescence method combined with chemometrics for rapid identification of tea picked before and after Qingming Festival. Firstly, the differences among the EEM fingerprints of different tea samples were analyzed using the alternating trilinear decomposition (ATLD) algorithm. To determine the differences between LAGP before and after Qingming Festival, the total contents of ten main components in tea were detected, and their effects on the EEM fluorescence fingerprint of tea were analyzed using correlation heatmaps. Finally, two chemometric algorithms, partial least squares discriminant analysis (PLS-DA) and k -nearest neighbor ( k -NN), were used to classify LAGP before and after Qingming Festival, achieving a classification accuracy of 100% for the training set, test set, and prediction set. To further explore the potential of this method, LAGP was further classified in detail according to four detailed picking periods, achieving an accuracy of over 83%. The same chemometric algorithm was used to classify the data based on the high-performance liquid chromatography (HPLC) method, yielding results comparable to those of the EEM-based method, though slightly inferior. Variable importance projection (VIP) analysis shows that catechin analogs are the main contributors to the classification of LAGP. The results demonstrated the EEM method’s significant potential in identifying the picking time of green tea.

CAS / MDL: 149-91-7
研究领域: 食品科学 · 分析化学
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FLAVOUR AND FRAGRANCE JOURNAL · 2021 ·Vol. 37 ·期 2 ·83-95 · IF 2.576

Contribution of aroma-active compounds to the aroma of Lu'an Guapian tea

Mingji Xiao,Fangling Zheng,Mengxuan Xiao,An Qi,Huiqiang Wang,Qianying Dai

In China, Lu'an Guapian (LAGP) tea consists of tea leaves without tea buds or stems. In this study, we evaluated the aromatic characteristics of LAGP by sensory analysis, aroma extract dilution analysis (AEDA), and odor activity values. The sensory analysis revealed that LAGP had cooked soybean-like, cooked chestnut-like, roasted, cooked corn-like, fishy, fruity, floral, and grass aromas. Aroma-active compounds from LAGP were identified by solvent extraction-solid phase extraction (SE-SPE) and headspace-solid phase microextraction (HS-SPME), and subjected to AEDA. A total of 91 aroma-active compounds were identified by SE-SPE-AEDA with flavor dilution (FD) factors ranging from 1 to 4096. A total of 66 aroma-active compounds were identified by HS-SPME-AEDA with FD of 1 to 128. Nine compounds with FD ≥64 and OAVs ≥1 were major aroma-active compounds to the aroma of LAGP tea: raspberry ketone (raspberry), ( E )- β -ionone (floral, raspberry), dimethyl sulfide (cooked corn-like), indole (animal), phenylacetaldehyde (floral, honey-like), 2-ethyl-3,5-dimethylpyrazine (roasted), ( Z )-4-heptenal (cooked soybean-like, fishy), ( Z )-jasmone (jasmine), and geraniol (rose).

CAS / MDL: 1634-04-4 109-66-0
研究领域: 食品科学 · 农业化学 · 分析化学 · 茶叶科学
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