11 results on '"Yingfu ZHONG"'
Search Results
2. Analysis of Active Ingredients and Taste Characteristics of Yongchuan Xiuya
- Author
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Juan YANG, Linying YUAN, Jie WANG, Tinghua WANG, Yingfu ZHONG, Hongyu LUO, Xiuhong WU, and Quan WU
- Subjects
yongchuan xiuya ,active ingredients ,principal component analysis ,electronic tongue ,taste ,Food processing and manufacture ,TP368-456 - Abstract
To provide a theoretical basis for the quality positioning, characteristic index screening and brand building of different grades of Yongchuan Xiuya, the active ingredients, color and taste performance of different grades of Yongchuan Xiuya products were analyzed. In this paper, the active ingredients’ content and L*, a*, b* color indexes of different grades of Yongchuan Xiuya products were detected, and the relationship between the characteristic indexes and grades was studied by principal component analysis (PCA); the taste characteristics of Yongchuan Xiuya products were analyzed by electronic tongue combined with sensory evaluation. The results showed that the active ingredients’ content of Yongchuan Xiuya product showed a certain trend with the change of product grade. It showed that with the decrease of product grade, the contents of tea polyphenols, water extracts and the ratio of phenol to amino acids were increased, while the contents of amino acids were decreased. And catechin (GC), epigallocatechin (EGC), catechin (C) content increased with the decrease of product grade. Four principal components were extracted by PCA analysis. And 16 characteristic indexes that have important contribution to quality were selected, including color indexes like dry tea L*, a*, b* value, fused leaf L*, b* value, chlorophyll a, chlorophyll b and total chlorophyll, and also tea polyphenols, amino acids, water extract, gallic acid (GA), GC, EGC, C, caffeine (CAF). And the score of PCA was opposite to the actual product grade ranking. The comprehensive score from high to low was: Level 6>Level 5>Level 4>Level 3>Level 2>Level 1. The taste of Yongchuan Xiuya with electronic tongue showed that with the decrease of product grade, the index values of sour taste, bitter taste and astringency gradually decreased, while the taste and richness increased. The three indexes include astringency aftertaste, umami and richness of electronic tongue had a extremely significant or significant negative correlation with the taste score and comprehensive score of reviewers (P
- Published
- 2022
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3. Multi-Metabolomics Coupled with Quantitative Descriptive Analysis Revealed Key Alterations in Phytochemical Composition and Sensory Qualities of Decaffeinated Green and Black Tea from the Same Fresh Leaves
- Author
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Jie Wang, Ying Zhang, Yan Liu, Shaorong Zhang, Linying Yuan, Yingfu Zhong, Xiuhong Wu, Juan Yang, and Ze Xu
- Subjects
tea ,caffeine ,decaffeination ,supercritical carbon dioxide ,sensory quality ,Chemical technology ,TP1-1185 - Abstract
The supercritical CO2-based decaffeination (SCD) method can be used to prepare decaffeinated tea, but its overall effect on the phytochemicals, volatiles, and sensory qualities of green and black teas is still unclear, and its suitability to prepare decaffeinated green and black teas still needs to be compared. This study revealed the effect of SCD on phytochemicals, volatiles, and sensory qualities in black and green tea prepared from the same tea leaves, and compared the suitability of preparing decaffeinated green and black teas using SCD. The results showed that the SCD could remove 98.2 and 97.1% of the caffeine in green and black tea, respectively. However, it can cause further losses of phytochemicals in green and black teas, specifically the loss of epigallocatechin gallate, epigallocatechin, epicatechin gallate, and gallocatechin gallate in green tea and the loss of theanine and arginine in green and black teas. After the decaffeination, both green and black teas lost some volatiles but also generated new volatiles. Especially, the fruit/flower-like aroma, ocimene, linalyl acetate, geranyl acetate, and D-limonene, were generated in the decaffeinated black tea, while herbal/green-like aroma, β-cyclocitral, 2-ethylhexanol, and safranal, were generated in the decaffeinated green tea. The overall acceptance of decaffeinated green tea decreased due to the substantial reduction in bitterness and astringency, while the overall acceptance of decaffeinated black tea significantly increased. Therefore, SCD is more suitable for the preparation of decaffeinated black tea.
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- 2022
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4. Rapid prediction of Yongchuan Xiuya tea quality by using near infrared spectroscopy coupled with chemometric methods
- Author
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Ying ZHANG, Jie WANG, Hongyu LUO, Juan YANG, Xiuhong WU, Quan WU, and Yingfu ZHONG
- Subjects
quality ,near infrared spectroscopy ,Yongchuan Xiuya tea ,synergy interval partial least squares ,back propagation-artificial neural network ,Food Science ,Biotechnology - Abstract
The current developmental trend is to evaluate the quality of Yongchuan Xiuya tea rapidly. After spectrum pre-processing, near infrared spectroscopy (NIRS) coupled with synergy interval partial least squares (siPLS), principal component analysis (PCA) and back propagation-artificial neural network (BP-ANN) was applied to rapidly and non-destructively predict the quality of Yongchuan Xiuya tea. External Yongchuan Xiuya tea samples were used for the actual application of the proposed model. The best pre-processing method was multiple scattering correction coupled with second derivative, and the characteristic spectral regions selected by siPLS were 4381.5-4755.6 cm-1, 4759.5-5133.6 cm-1, 6266.6-6637.8 cm-1 and 7389.9-7760.2 cm-1. The cumulative contribution rate was 99.05% for the first three principal components of the characteristic spectra regions. The transfer function, root mean square error and determinant coefficient of the best BP-ANN prediction model were the tanh function, 0.384 and 0.977, respectively. The root mean square error and determinant coefficient of the external 10 Yongchuan Xiuya tea samples were 0.406 and 0.969, respectively. These results showed that NIRS combined with BP-ANN algorithm can be used to evaluate the quality of Yongchuan Xiuya tea rapidly and accurately.
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- 2022
5. PlantTFDB: a comprehensive plant transcription factor database.
- Author
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Anyuan Guo, Xin Chen, Ge Gao, He Zhang, Qihui Zhu, Xiao-Chuan Liu, Yingfu Zhong, Xiaocheng Gu, Kun He 0012, and Jingchu Luo
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- 2008
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6. Rapid identification of the green tea geographical origin and processing month based on near-infrared hyperspectral imaging combined with chemometrics
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Yujie Wang, Luqing Li, Yuyu Chen, Junlan Huang, Ze Xu, Ying Liu, Yingfu Zhong, Chengye Lu, Qingqing Cui, Jingming Ning, and Menghui Li
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Principal Component Analysis ,Spectroscopy, Near-Infrared ,Support Vector Machine ,Tea ,Chemistry ,business.industry ,Hyperspectral imaging ,Pattern recognition ,Hyperspectral Imaging ,Green tea ,Atomic and Molecular Physics, and Optics ,Analytical Chemistry ,Rapid identification ,Chemometrics ,Support vector machine ,Principal component analysis ,Artificial intelligence ,Least-Squares Analysis ,Cluster analysis ,business ,Instrumentation ,Near infrared hyperspectral imaging ,Spectroscopy - Abstract
The geographical origin and processing month of green tea greatly affect its economic value and consumer acceptance. This study investigated the feasibility of combining near-infrared hyperspectral imaging (NIR-HSI) with chemometrics for the identification of green tea. Tea samples produced in three regions of Chongqing (southeastern Chongqing, northeastern Chongqing, and western Chongqing) for four months (from May to August 2020) were collected. Principal component analysis (PCA) was used to reduce data dimensionality and visualize the clustering of samples in different categories. Linear partial least squares-discriminant analysis (PLS-DA) and nonlinear support vector machine (SVM) algorithms were used to develop discriminant models. The PCA-SVM models based on the first four and first five principal components (PCs) achieved the best accuracies of 97.5% and 95% in the prediction set for geographical origin and processing month of green tea, respectively. This study demonstrated the feasibility of HSI in the identification of green tea species, providing a rapid and nondestructive method for the evaluation and control of green tea quality.
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- 2022
7. DPTF: a database of poplar transcription factors.
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Qihui Zhu, Anyuan Guo, Ge Gao, Yingfu Zhong, Meng Xu, Minren Huang, and Jingchu Luo
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- 2007
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8. DRTF: a database of rice transcription factors.
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Ge Gao, Yingfu Zhong, Anyuan Guo, Qihui Zhu, Wen Tang, Wei-Mou Zheng, Xiaocheng Gu, Liping Wei, and Jingchu Luo
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- 2006
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9. PlantTFDB: a comprehensive plant transcription factor database
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Jingchu Luo, Ge Gao, Xiaocheng Gu, Kun-Yan He, He-Lin Zhang, Xin-Xin Chen, Yingfu Zhong, An-Yuan Guo, Xiaochuan Liu, and Qihui Zhu
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Whole genome sequencing ,Internet ,Database ,Phenylketonurias ,Sequence analysis ,fungi ,Articles ,Biology ,computer.software_genre ,Genome ,User-Computer Interface ,Annotation ,Sequence Analysis, Protein ,Genetics ,natural sciences ,Identification (biology) ,Databases, Protein ,Transcription factor ,Gene ,computer ,Plant Proteins ,Transcription Factors - Abstract
Transcription factors (TFs) play key roles in controlling gene expression. Systematic identification and annotation of TFs, followed by construction of TF databases may serve as useful resources for studying the function and evolution of transcription factors. We developed a comprehensive plant transcription factor database PlantTFDB (http://planttfdb.cbi.pku.edu.cn), which contains 26,402 TFs predicted from 22 species, including five model organisms with available whole genome sequence and 17 plants with available EST sequences. To provide comprehensive information for those putative TFs, we made extensive annotation at both family and gene levels. A brief introduction and key references were presented for each family. Functional domain information and cross-references to various well-known public databases were available for each identified TF. In addition, we predicted putative orthologs of those TFs among the 22 species. PlantTFDB has a simple interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.
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- 2007
10. DPTF: a database of poplar transcription factors
- Author
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Ge Gao, Minren Huang, Qihui Zhu, Yingfu Zhong, Meng Xu, An-Yuan Guo, and Jingchu Luo
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Statistics and Probability ,Transcription, Genetic ,Biology ,computer.software_genre ,Biochemistry ,Manual curation ,Arabidopsis ,Gene expression ,Transcriptional regulation ,natural sciences ,Databases, Protein ,Molecular Biology ,Transcription factor ,Plant Proteins ,Web site ,Internet ,Database ,fungi ,food and beverages ,biology.organism_classification ,Computer Science Applications ,Computational Mathematics ,Populus ,Computational Theory and Mathematics ,Transcription (software) ,computer ,Transcription Factors - Abstract
Summary: The database of poplar transcription factors (DPTF) is a plant transcription factor (TF) database containing 2576 putative poplar TFs distributed in 64 families. These TFs were identified from both computational prediction and manual curation. We have provided extensive annotations including sequence features, functional domains, GO assignment and expression evidence for all TFs. In addition, DPTF contains cross-links to the Arabidopsis and rice transcription factor databases making it a unique resource for genome-scale comparative studies of transcriptional regulation in model plants.Availiability: DPTF is available at http://dptf.cbi.pku.edu.cnContact: dptf@mail.cbi.pku.edu.cn
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- 2007
11. DRTF: a database of rice transcription factors
- Author
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Qihui Zhu, Wen Tang, Ge Gao, An-Yuan Guo, Xiaocheng Gu, Jingchu Luo, Wei-Mou Zheng, Liping Wei, and Yingfu Zhong
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Statistics and Probability ,Genetics ,Internet ,Multiple sequence alignment ,Oryza sativa ,Database ,Sequence database ,Gene ontology ,Information Storage and Retrieval ,Oryza ,Biology ,computer.software_genre ,Biochemistry ,Manual curation ,Computer Science Applications ,User-Computer Interface ,Computational Mathematics ,Computational Theory and Mathematics ,Database Management Systems ,Databases, Protein ,Molecular Biology ,computer ,Transcription factor ,Transcription Factors - Abstract
Summary: DRTF contains 2025 putative transcription factors (TFs) in Oryza sativa L. ssp. indica and 2384 in ssp. japonica, distributed in 63 families, identified by computational prediction and manual curation. It includes detailed annotations of each TF including sequence features, functional domains, Gene Ontology assignment, chromosomal localization, EST and microarray expression information, as well as multiple sequence alignment of the DNA-binding domains for each TF family. The database can be browsed and searched with a user-friendly web interface. Availability: DRTF is available at Contact: drtf@mail.cbi.pku.edu.cn
- Published
- 2006
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