期刊：
Food Research International,2023年163:112278 ISSN：0963-9969
通讯作者：
Xiao-Hua Zhang<&wdkj&>Xiao-Li Yin
作者机构：
[Zhang, Xiao-Hua; Zhang, Ya-Qian; Pan, Le-Yuan; Zheng, Jing-Jing; Yang, Kai-Long; Ren, Lu-Meng] Xuchang Univ, Food & Pharm Coll, Henan Key Lab Biomarker Based Rapid detect Technol, Xuchang 461000, Peoples R China.;[Cui, Hui-Na; Yin, Xiao-Li] Yangtze Univ, Coll Life Sci, Jingzhou 434023, Peoples R China.;[Qing, Xiang-Dong] Hunan City Univ, Coll Mat & Chem Engn, Hunan Prov Key Lab Dark Tea & Jin Hua, Yiyang 413049, Peoples R China.
通讯机构：
[Xiao-Hua Zhang] H;[Xiao-Li Yin] C;College of Life Sciences, Yangtze University, Jingzhou 434023, China<&wdkj&>Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang 461000, PR China
关键词：
Aqueous two-phase systems;Chemometrics;Green tea;HPLC-DAD;Harvesting season
摘要：
The flavor and aroma quality of green tea are closely related to the harvest season. The aim of this study was to identify the harvesting season of green tea by alcohol/salt-based aqueous two-phase system (ATPS) combined with chemometric analysis. In this paper, the single factor experiments (SFM) and response surface methodology (RSM) optimization were designed to investigate and select the optimal ATPS. A total of 180 green tea samples were studied in this work, including 86 spring tea and 94 autumn tea. After the active components in green tea samples were extracted by the optimal ethanol/(NH 4 ) 2 SO 4 ATPS, the qualitative and quantitative analysis was realized based on HPLC-DAD combined with alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) algorithm, with satisfactory spiked recoveries (86.00 %–112.45 %). The quantitative results obtained from ATLD-MCR model were subjected to chemometric pattern recognition analysis. The constructed partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models showed better results than the principal component analysis (PCA) model, and the R 2 X cum values (>0.835) and R 2 Y cum (>0.937) were close to 1, the Q 2 cum values were greater than 0.75 (>0.933), and the differences between R 2 Y cum and Q 2 cum were not larger than 0.2, indicating excellent cross-validation prediction performance of the models. Furthermore, the classification results based on the hierarchical clustering analysis (HCA) were consistent with the PCA, PLS-DA and OPLS-DA results, establishing a good correlation between tea active components and the harvesting seasons of green tea. Overall, the combination of ATPS and chemometric methods is accurate, sensitive, fast and reliable for the qualitative and quantitative determination of tea active components, providing guidance for the quality control of green tea.
The flavor and aroma quality of green tea are closely related to the harvest season. The aim of this study was to identify the harvesting season of green tea by alcohol/salt-based aqueous two-phase system (ATPS) combined with chemometric analysis. In this paper, the single factor experiments (SFM) and response surface methodology (RSM) optimization were designed to investigate and select the optimal ATPS. A total of 180 green tea samples were studied in this work, including 86 spring tea and 94 autumn tea. After the active components in green tea samples were extracted by the optimal ethanol/(NH 4 ) 2 SO 4 ATPS, the qualitative and quantitative analysis was realized based on HPLC-DAD combined with alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) algorithm, with satisfactory spiked recoveries (86.00 %–112.45 %). The quantitative results obtained from ATLD-MCR model were subjected to chemometric pattern recognition analysis. The constructed partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models showed better results than the principal component analysis (PCA) model, and the R 2 X cum values (>0.835) and R 2 Y cum (>0.937) were close to 1, the Q 2 cum values were greater than 0.75 (>0.933), and the differences between R 2 Y cum and Q 2 cum were not larger than 0.2, indicating excellent cross-validation prediction performance of the models. Furthermore, the classification results based on the hierarchical clustering analysis (HCA) were consistent with the PCA, PLS-DA and OPLS-DA results, establishing a good correlation between tea active components and the harvesting seasons of green tea. Overall, the combination of ATPS and chemometric methods is accurate, sensitive, fast and reliable for the qualitative and quantitative determination of tea active components, providing guidance for the quality control of green tea.
摘要：
The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.
期刊：
Energy & Fuels,2023年37(20):15867-15878 ISSN：0887-0624
通讯作者：
Yang, FM
作者机构：
[Long, Sheng; Liang, Hai-Cheng; Zou, Pan; Yang, Fan-Ming; Liao, Min; Zhang, Ke-Yi; Xie, Du; Jiang, Kai] Hunan City Univ, Coll Mat & Chem Engn, Yiyang 413000, Hunan, Peoples R China.
通讯机构：
[Yang, FM ] H;Hunan City Univ, Coll Mat & Chem Engn, Yiyang 413000, Hunan, Peoples R China.
摘要：
Porous materials of PEI( n )/Zr ( N ) -KIT-6 were prepared by doping zirconium to the KIT-6 framework and introducing poly(ethylenimine) (PEI) to the pore channels ( n is the weight percentage of PEI to Zr ( N ) -KIT-6, and N is the molar ratio of Zr/Si). The adsorbents were characterized and tested at a 20% CO 2 concentration to investigate the influence of Zr and PEI on CO 2 adsorption. The results display that Zr–O–Si bonds are formed after the doping of Zr species. In addition, PEI is loaded on the surface through the formation of hydrogen bonds and Zr–N bonds. The synthesized PEI( n )/Zr ( N ) -KIT-6 materials keep stable when the temperature is lower than 210 °C. In addition, the materials exhibit good CO 2 adsorption performance, which is attributed to the existence of Zr and PEI. The Lewis acidity of KIT-6 is improved after the doping of Zr heteroatoms, leading to the immobilization of more PEI and the enhancement of CO 2 adsorption properties. The adsorption includes two steps: diffusion of CO 2 in the pore channels and the reaction between CO 2 and amine groups. When the gas flow rate is 40 mL/min, the maximum CO 2 adsorption capacity of 174.7 mg/g is achieved. After 20 cycles, the adsorption value keeps stable.
通讯机构：
[Xu, S ] U;[Shi, L ; Xu, S] H;Hunan Univ, Coll Chem & Chem Engn, State Key Lab Chemo Biosensing & Chemometr, Changsha 410082, Peoples R China.;Univ Jinan, Sch Chem & Chem Engn, Jinan 250022, Peoples R China.
摘要：
We propose a practical strategy to design a series of heavy-atom-free synergistic phototherapy agents (CSQs) with both photodynamic therapy (PDT) and photothermal therapy (PTT) under NIR wavelength excitation by simply replacing the indole salt of xanthene Changsha (CS) with quinoline salt.
作者机构：
[Xiao-Hua Zhang; Jing-Jing Zheng; Kai-Long Yang; Ya-Qian Zhang; Le-Yuan Pan] Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang, 461000, PR China;[Ren-Jun Liu; Jin-Fang Nie] Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, 541004, China;[Xiang-Dong Qing] Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang, 413049, PR China
通讯机构：
[Xiao-Hua Zhang] H;[Jin-Fang Nie] C;Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang, 461000, PR China<&wdkj&>Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, 541004, China
作者机构：
[Zhang, Jin; Qing, Xiang-Dong; Xu, Ling; An, Rong] Hunan City Univ, Coll Mat & Chem Engn, Hunan Prov Key Lab Dark Tea & Jin hua, Yiyang 413000, Peoples R China.;[Zhang, Xiao-Hua] Xuchang Univ, Food & Bioengn Coll, Key Lab Biomarker Based Rapid Detect Technol Food, Xuchang 461000, Peoples R China.;[Duponchel, Ludovic] Univ Lille 1, CNRS, UMR 8516, LASIRE Lab Spect Interact React & Environm, F-59000 Lille, France.
通讯机构：
[Ludovic Duponchel; Xiang-Dong Qing] A;Authors to whom correspondence should be addressed.<&wdkj&>Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang 413000, China<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>Université Lille 1, CNRS, UMR 8516–LASIRE–Laboratoire de Spectroscopie Pour Les Interactions, La Réactivité et l’environnement, F-59000 Lille, France
