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Effects of substitute group, axial ligand and volatile organic compounds on binding ability of colorimetric sensor array

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Materials and Processing Report 2014年第4期29卷 220-226页

Cobalt porphyrin and similar metalloporphyrins (MPs) were initially used in the colorimetric sensor array (CSA) system for quality assurance and quality control in beverage and food. In order to design a proper CSA sensor, density functional theory method with B3LYP/LANL2DZ basis set was performed to investigate the influences of axial ligand, substituent group and volatile organic compounds (VOCs) on the binding process. Ground state structure was determined at three spin states: low, intermediate and high spin states, based on the relative energy. The binding energy (BE) for each MP model was obtained by differentiating the energy of MP before and after binding with VOCs. The binding ability of MPs and their complexes can be divided into three classes based on the BE. This theoretical research would be used for the further design of CSA sensor to extend the application of CSA.

关键词： colorimetric sensor array Metalloporphyrin Volatile organic compounds Food quality

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MnO2 Nanosheet-Based colorimetric sensor array: Toward identification of organophosphorus pesticides

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MICROCHEMICAL JOURNAL 2022年 181卷

作者： Qian, Zhenni Tan, Renjian Zhang, Xueying Leng, Yumin Chen, Zhengbo Capital Normal Univ Dept Chem Beijing 100048 Peoples R China Nanyang Normal Univ Coll Phys & Elect Engn Nanyang 473061 Peoples R China

In recent years, two-dimensional (2D) nanomaterials have attracted more and more attention because of their high specific surface area and excellent physical and chemical properties. We herein demonstrate two kinds of 2D nanomaterials, i.e., MnO2 nanosheets and UFO-shaped Au@MnO2 nanosheets (denoted as MnO2 NSs and AM NSs), for qualitative identification and quantitative detection of organophosphorus pesticides (OPs). In the presence of acetylcholinesterase (AChE), acetylthiocholine iodide (ATCh) can be hydrolyzed to thiocholine (TCh), which is used as a reducing agent to etch ultrathin MnO2 nanosheets. During the etching process, the color of AM NSs solution changes from green to pink, and the MnO2 NSs solution changes from dark brown to light brown. OPs can inhibit the activity of AChE and thus inhibit the etching of MnO2. Based on this principle, five OPs (i.e., ethion, bromophos-ethyl, chlorpyrifos-methyl, trichlorfon, and omethoate) at 0.5 mu g.L-1 were successfully identified by this sensor array. Besides, the distinction for diverse concentrations of each OP and different ratios of OP mixtures was demonstrated. The sensor array also reveals excellent anti-interference ability toward OPs in the presence of different potentially interfering substances. The feasibilities of the sensor array were further validated by differentiating the OPs in grape samples.

关键词： Two-dimensional nanomaterials Core-shell nanocomposites colorimetric sensor array Organophosphate discrimination

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Study on the Property of colorimetric sensor array Binding Volatile Organic Compounds using Density Functional Theory

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Advance Journal of Food Science and Technology 2016年第1期11卷 77-81页

作者： Hai-Yang Gu Yan-Hui Sun Xing-Yi Huang Huang Dai School of Bio and Food Engineering Chuzhou University Chuzhou 239000 China School of Food and Biological Engineering Jiangsu University Zhenjiang 212013 China College of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310058 China

colorimetric sensor array (CSA) has been developed in the application of detection and evaluation of food quality. Theoretical study using Density Functional Theory (DFT) at B3LYP/LANL2DZ level was carried out to investigate the ability of CSA sensor binding Volatile Organic Compounds (VOCs) at molecular level. The binding energy representing the sensitivity of CSA sensor was analyzed. The ability of CSA sensor binding VOCs was classified into three groups by the comparison of binding energy. This study suggests that the theoretical calculation is useful for the optimization of CSA sensor in the further experiment.

关键词： colorimetric sensor array density functional theory food quality ruthenium porphyrin

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Monitoring the freshness of pork during storage via near-infrared spectroscopy based on colorimetric sensor array coupled with efficient multivariable calibration

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JOURNAL OF FOOD COMPOSITION AND ANALYSIS 2022年 113卷

作者： Wei, Wenya Li, Huanhuan Haruna, Suleiman A. Wu, Jizhong Chen, Quansheng Jiangsu Univ Sch Food & Biol Engn Zhenjiang 212013 Peoples R China Jimei Univ Coll Food & Biol Engn Xiamen 361021 Peoples R China

The quality of pork meat is vital since it is one of the most essential sources of proteins and other nutrients. Nearinfrared spectroscopy via colorimetric sensor array (NIRS-CSA) technology as a novel approach combined with multivariate calibrations was proposed to quantitatively evaluate total volatile basic nitrogen (TVB-N) as an indicator of freshness in pork. Using nine chemoselective dyes, the CSA was initially fabricated. The synergy interval-partial least squares (Si-PLS) was applied to select optimum variable intervals. Thereafter, different variable selection algorithms were executed, evaluated and compared. By utilizing 61 variables (7.73% of the SiPLS variables), the synergy interval- competitive adaptive reweighted sampling-partial least squares (Si-CARSPLS) model yielded preeminent performance with Rp = 0.9850, RMSEP = 0.7148, and RPD = 6.00. Therefore, this study discovered that combining NIRS-CSA with Si-CARS-PLS as efficient variable selection algorithm could be employed as a fast and cheap strategy for assessing the freshness of pork meat during storage.

关键词： Pork Freshness TVB-N Near -infrared spectroscopy colorimetric sensor array Multivariate calibration

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Comparative chemometric analysis for classification of acids and bases via a colorimetric sensor array

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JOURNAL OF CHEMOMETRICS 2018年第2期32卷 1-1页

作者： Kangas, Michael J. Burks, Raychelle M. Atwater, Jordyn Lukowicz, Rachel M. Garver, Billy Holmes, Andrea E. Doane Univ Dept Chem Crete NE 68333 USA St Edwards Univ Dept Chem Austin TX 78704 USA Doane Univ Dept Math Crete NE USA

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study. Data from a pH-sensitive colorimetric sensor array was processed using a variety of chemometric methods to determine the best method for acid and base classification, including based on concentration. colorimetric data were analyzed with principal component analysis (PCA), hierarchical cluster analysis (HCA), k nearest neighbor analysis (KNN), linear discriminant analysis (LDA), and hit quality index (HQI). PCA, LDA, and HCA allowed trends in the data to be visualized, while LDA, KNN, and HQI identified analytes with >90% accuracy.

关键词： colorimetric sensor array hit quality index (HQI) image analysis k nearest neighbor analysis (KNN) linear discriminant analysis (LDA)

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Novel colorimetric sensor array for identification of baijiu using color reactions of flavor compounds

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MICROCHEMICAL JOURNAL 2021年 167卷 106277-106277页

作者： Chen, Yunyin Wang, Songtao Hu, Ying Chen, Hengye Fu, Haiyan Zhou, Chunsong She, Yuanbin Zhejiang Univ Technol Coll Chem Engn State Key Lab Breeding Base Green Chem Synth Tech Hangzhou 310032 Peoples R China Luzhou Laojiao Co Ltd Natl Engn Res Ctr Solid State Brewing Luzhou 646000 Peoples R China South Cent Univ Nationalities Sch Pharmaceut Sci Modernizat Engn Technol Res Ctr Ethn Minor Med Hu Wuhan 430074 Peoples R China

The flavor of baijiu, a type of distilled spirit, mainly depends on the presence of certain flavor compounds. In this study, we focus on the four most important groups of flavor compounds in baijiu, viz. aldehydes, ketones, esters, and acids. Simple organic reactions, including the hydroxylamine color reaction, 2,4-dinitrophenylhydrazine (DNPH) nucleophilic addition reaction, and localized surface plasmon resonance (LSPR), exhibited by noble metal nanoparticles were used to construct an eight-channel visual array sensor, which can be used to directly and qualitatively detect the four major groups of flavor compounds in consideration. Using the optimized variable-weighted least-squares support vector machine, based on the particle swarm optimization (PSO-OVWLSSVM) model, the sensor array allowed good quantification. The results of this study were supported by principal component analysis (PCA) and hierarchical cluster analysis (HCA) techniques. The results suggested that the sensor array can be used for the rapid detection of flavor compounds in actual baijiu samples.

关键词： Color reaction colorimetric sensor array Flavor compounds Baijiu

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Comparable analysis of flavor compounds and quality assessment of fermented bean curd using HS-SPME-GC/MS and colorimetric sensor array

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FOOD BIOSCIENCE 2024年 60卷

作者： Zhang, Xiaorui Huang, Xingyi Aheto, Joshua Harrington Ren, Yi Wang, Li Yu, Shanshan Wang, Yu Jiangsu Univ Sch Food & Biol Engn Xuefu Rd 301 Zhenjiang 212013 Jiangsu Peoples R China Suzhou Polytech Inst Agr Sch Smart Agr Xiyuan Rd 279 Suzhou 215008 Jiangsu Peoples R China

This study aims to develop an effective tool by integrating traditional analysis methods with advanced sensor array technology and multiple algorithms, to achieve rapid characterization, qualitative identification, and flavor quality evaluation of fermented bean products. Firstly, the flavor compounds and flavor profiles of fermented bean curd from different manufacturers were identified using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) and quantitative descriptive analysis (QDA). A total of 63 volatile compounds were identified, of which 13 volatile compounds were identified as the key differential compounds in selected samples. Eight descriptors were selected to represent the aroma characteristics of fermented bean curd. Based on the key differential compounds, a low-cost colorimetric sensor array (CSA) was designed and constructed. Furthermore, the feasibility of CSA combined with multiple algorithms was investigated for brand discrimination and flavor quality assessment. Linear discriminant analysis (LDA) exhibited a better performance in distinguishing different flavor quality samples, and the recognition accuracy of its prediction set was 97.22%. The study suggests that CSA combined with multiple algorithms can be an effective tool for flavor characterization and qualitative discrimination of fermented bean curd, and can provide a new multidimensional analysis method for food analysis.

关键词： Fermented bean curd HS-SPME-GC/MS colorimetric sensor array Volatile flavor compounds Quality assessment Multiple algorithms

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Portable beef-freshness detection platform based on colorimetric sensor array technology and bionic algorithms for total volatile basic nitrogen (TVB-N) determination

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FOOD CONTROL 2023年 150卷

作者： Xu, Weidong He, Yingchao Li, Jiaheng Zhou, Jianwei Xu, Enbo Wang, Wenjun Liu, Donghong Zhejiang Univ Fuli Inst Food SciZhejiang Key Lab Agrofood Proc Coll Biosyst Engn & Food SciZhejiang Engn Lab Foo Natl Local Joint Engn Lab Intelligent Food Technol Hangzhou 310058 Peoples R China Zhejiang Univ Ningbo Res Inst Ningbo 315100 Peoples R China NingboTech Univ Sch Mech & Energy Engn Ningbo 315100 Peoples R China Zhejiang Univ Innovat Ctr Yangtze River Delta Jiashan 314100 Peoples R China Zhejiang Univ Coll Biosyst Engn & Food Sci 866 Yuhangtang Rd Hangzhou 310058 Zhejiang Peoples R China

colorimetric sensor array (CSA) and bionic algorithms were integrated to form a facile platform for total volatile basic nitrogen (TVB-N) determination. First, a CSA containing twelve color-sensitive materials was prepared to obtain scent information of beef and generate scent fingerprints for visualization. Second, four bionic optimi-zation algorithms, ant colony optimization (ACO), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), were used to extract the characteristic fingerprint variables from the CSA. Finally, the back-propagation neural network (BPNN) model combined with characteristic color compo-nents was constructed to determine the TVB-N during beef storage, with improved precision, robustness, and generalization performance. The results demonstrated that WOA had the best optimization performance, fol-lowed by PSO, ACO, and SA. The WOA-BPNN optimized only two materials to detect TVB-N during beef storage. The BPNN constructed by three variables from the two selected materials had the best determination results, with the RMSEC, Rc, RMSEP, Rp, and RPD were 2.502 +/- 0.083 mg/100 g, 0.966 +/- 0.002, 2.903 +/- 0.143 mg/100 g, 0.952 +/- 0.006, and 3.430 +/- 0.185, respectively. Therefore, the WOA-BPNN model could realize high-precision quantitative determination of TVB-N during beef storage and save resources for CSA preparation. The combi-nation of CSA and the excellent bionic algorithm is expected to become a facile on-site sensing platform for food freshness monitoring.

关键词： Beef quality Total volatile basic nitrogen colorimetric sensor array Bionic optimization algorithm Quantitative determination

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Discrimination of basmati rice adulteration using colorimetric sensor array system

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FOOD CONTROL 2022年第0期132卷 108513-108513页

作者： Arslan, Muhammad Zareef, Muhammad Tahir, Haroon Elrasheid Zhang, Junjun Ahmad, Waqas Rakha, Allah Shi, Jiyong Zou Xiaobo Khan, Moazzam Rafiq Jiangsu Univ Sch Food & Biol Engn 301 Xuefu Rd Zhenjiang 212013 Jiangsu Peoples R China Univ Agr Faisalabad Natl Inst Food Sci & Technol Faisalabad 38000 Pakistan

This study involved the fabrication of colorimetric sensor array system for rapid discrimination of adulterants in premium grade basmati rice. Purposely, low-grade white rice was used to adulterate the pure basmati rice at 5%, 10%, 15%, 25%, 50%, and 75% weight ratios. sensor array system was used to capture the odors of prepared samples, resulting in color difference map based on chemical environment. The principal component analysis (PCA), hierarchical cluster analysis (HCA), and k-nearest neighbors (kNN) algorithm were subsequently used to identify the similarity between authentic and adulterated samples. A decent discrimination between authentic and adulterated rice samples was observed in the scatter plot of PCA and HCA dendrogram. The multilayered kNN models were able to effectively discriminate the prepared rice samples. The study concludes that fabricated sensor array system may be used as an effective tool for rapid discrimination of authentic and adulterated samples.

关键词： Adulteration Basmati rice colorimetric sensor array GC-MS Multivariate analysis Smartphone

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Porphyrin and pH sensitive dye-based colorimetric sensor array coupled chemometrics for dynamic monitoring of tea quality during ultrasound-assisted fermentation

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MICROCHEMICAL JOURNAL 2024年 197卷

作者： Li, Huanhuan Hu, Yaqi Ma, Shuo Haruna, Suleiman A. Chen, Quansheng Zhu, Weijun Xia, Ankou Jiangsu Univ Sch Food & Biol Engn Zhenjiang 212013 Peoples R China Jimei Univ Coll Food & Biol Engn Xiamen 361021 Peoples R China Liyang Tianmu Lake Agr Dev Co Ltd Xiamen 361021 Peoples R China

In current work, the response surface methodology using Box-Behnken design was initially used to optimize the fermentation conditions of green tea via consumption rate of tea polyphenol (CROTP) as a response value. The CROTP reached its maximum (25.78 %) when the fermentation pH, ultrasonic time and ultrasonic frequency were set at 5, 15 min and 50 kHz, respectively. Based on the optimization, a novel strategy was further proposed to dynamically monitor the quality change of green tea during ultrasonic-assisted fermentation (UAF) utilizing a colorimetric sensor array (CSA) comprising nine color-sensitive dyes combined with chemometric methods. The fabricated CSA showed sensitive differential responses to green tea fermentation samples, reaching the best quantitative prediction of tea polyphenol content using support vector machines (SVM) with Rc = 0.886, RMSEC = 0.042 mg/g, Rp = 0.862, and RMSEP = 0.043 mg/g. As a result, our work proved that integrating CSA with SVM is viable for dynamic quality monitoring of green tea during UAF. Furthermore, this research could be of benefit in controlling production specifications and designing ideal green tea fermentation systems.

关键词： Green tea Tea polyphenol content Ultrasound-assisted fermentation colorimetric sensor array Chemometric methods

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