Preparation of zinc porphyrin nanoparticles and application in monitoring the ethanol content during the solid-state fermentation of Zhenjiang Aromatic vinegar

Guan, Binbin; Xue, Zhaoli; Chen, Quansheng; Hao, Lin; Zhao, Jiewen

doi:10.1016/j.microc.2019.104353

Cited by 11 publications

(4 citation statements)

References 35 publications

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“…The solid‐phase self‐assembly method is mainly a physical vapor deposition method, and the liquid‐phase self‐assembly method mainly includes reprecipitation method, surfactant‐assisted method, and ion self‐assembly method. Among them, the surfactant‐assisted method is an improvement of the reprecipitation method, which is simple to operate and can be widely used in chemo‐responsive materials of nanoparticles self‐assembly (Guan et al., 2020). Figure 5 shows the flow chart of nanoself‐assembly porphyrin.…”

Section: Modification and Improvement Of Chemo‐responsive Dyesmentioning

confidence: 99%

Advanced applications of chemo‐responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Kang

Hao

Jiang

et al. 2021

Comp Rev Food Sci Food Safe

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Public attention to foodquality and safety has been increased significantly. Therefore, appropriate analytical tools are needed to analyze and sense the food quality and safety. Volatile organic compounds (VOCs) are important indicators for the quality and safety of food products. Odor imaging technology based on chemoresponsive dyes is one of the most promising methods for analysis of food products. This article reviews the sensing and imaging fundamentals of odor imaging technology based on chemo-responsive dyes. The aim is to give detailed outlines about the theory and principles of using odor imaging technology for VOCs detection, and to focus primarily on its applications in the field of quality and safety evaluation of food products, as well as its future applicability in modern food industries and research. The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods , poultry meat, aquatic products, fruits and vegetables, and tea. It has the potential for the rapid, reliable, and inline assessment of food safety and quality by providing odor-image-basedmonitoring tool. Practical Application:The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods, poultry meat, aquatic products, fruits and vegetables, and tea.

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Section: Modification and Improvement Of Chemo‐responsive Dyesmentioning

confidence: 99%

Advanced applications of chemo‐responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Kang

Hao

Jiang

et al. 2021

Comp Rev Food Sci Food Safe

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“…Aroma changes due to a change in food quality. Therefore, colorimetric sensors have been extensively used to assess the quality of pork, fish, tea, wine, vinegar, and other foods 9‐14 . At present, spectrum analysis technology has been in widespread use in the qualitative and quantitative determination of substances.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, colorimetric sensors have been extensively used to assess the quality of pork, fish, tea, wine, vinegar, and other foods. [9][10][11][12][13][14] At present, spectrum analysis technology has been in widespread use in the qualitative and quantitative determination of substances. And one of the most normally exploited detection methods is visible-nearinfrared spectroscopy (VNIRS) technology, with the advantages of being non-destructive, inexpensive, rapid, reliable, and simple operation.…”

Section: Introductionmentioning

confidence: 99%

Application of colorimetric sensor array coupled with machine‐learning approaches for the discrimination of grains based on freshness

et al. 2023

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BackgroundVolatile organic compounds (VOCs) in grain fluctuate depending on the degree of grain freshness. A new colorimetric sensor array (CSA) was developed as capture probes for the quantification of VOCs in grains in this work, and it was designed to monitor the variation of grain VOCs. CSA spectral data acquisition using visible–near‐infrared spectroscopy and image processing of CSA's image imformation by computer were used comparatively. Then, machine‐learning‐based models – for example, synergistic interval partial least squares, genetic algorithm, competitive adaptive reweighted sampling (CARS) algorithm, and ant colony optimization (ACO) algorithm – were introduced to optimize variables. Moreover, principal component analysis, and linear discriminant analysis (LDA), and K‐nearest neighbors (KNN) were used for the classification. Ultimately, quantitative models for detecting grain freshness are developed using various variable selection strategies.ResultsCompared with the pattern recognition results of image processing, visible–near‐infrared spectroscopy could better separate the grains with different freshness from principal component analysis, and the prediction set of LDA models could correctly identify 100% of rice, 96.88% of paddy, and 97.9% of soybeans. In addition, compared with CARS and ACO, the LDA model and KNN model based on genetic algorithms show the best prediction performance. The prediction set could correctly identify 100% of rice and paddy samples and 95.83% of soybean samples.ConclusionThe method developed could be used for non‐destructive detection of grain freshness. © 2023 Society of Chemical Industry.

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“…The color difference value of the colorimetric sensor array before and after exposure to specific VOCs can be obtained by a charge coupled device (CCD) camera for qualitative and quantitative analysis, which could express smell information through color changes. Colorimetric sensors have been widely applied for aroma quality evaluation of pork, fish, tea, wine, vinegar and other kinds of food [14][15][16][17][18][19]. However, the change information that is obtained based on the colorimetric sensor array is mainly characterized by extracting the RGB difference images before and after the reaction; that is, the color change of each color-sensitive material is only characterized by the three components of R, G, and B.…”

Section: Introductionmentioning

confidence: 99%

Freshness Identification of Oysters Based on Colorimetric Sensor Array Combined with Image Processing and Visible Near-Infrared Spectroscopy

Guan

Kang

Jiang

et al. 2022

Sensors

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Volatile organic compounds (VOCs) could be used as an indicator of the freshness of oysters. However, traditional characterization methods for VOCs have some disadvantages, such as having a high instrument cost, cumbersome pretreatment, and being time consuming. In this work, a fast and non-destructive method based on colorimetric sensor array (CSA) and visible near-infrared spectroscopy (VNIRS) was established to identify the freshness of oysters. Firstly, four color-sensitive dyes, which were sensitive to VOCs of oysters, were selected, and they were printed on a silica gel plate to obtain a CSA. Secondly, a charge coupled device (CCD) camera was used to obtain the “before” and “after” image of CSA. Thirdly, VNIS system obtained the reflected spectrum data of the CSA, which can not only obtain the color change information before and after the reaction of the CSA with the VOCs of oysters, but also reflect the changes in the internal structure of color-sensitive materials after the reaction of oysters’ VOCs. The pattern recognition results of VNIS data showed that the fresh oysters and stale oysters could be separated directly from the principal component analysis (PCA) score plot, and linear discriminant analysis (LDA) model based on variables selection methods could obtain a good performance for the freshness detection of oysters, and the recognition rate of the calibration set was 100%, while the recognition rate of the prediction set was 97.22%. The result demonstrated that the CSA, combined with VNIRS, showed great potential for VOCS measurement, and this research result provided a fast and nondestructive identification method for the freshness identification of oysters.

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Preparation of zinc porphyrin nanoparticles and application in monitoring the ethanol content during the solid-state fermentation of Zhenjiang Aromatic vinegar

Cited by 11 publications

References 35 publications

Advanced applications of chemo‐responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Advanced applications of chemo‐responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Application of colorimetric sensor array coupled with machine‐learning approaches for the discrimination of grains based on freshness

Freshness Identification of Oysters Based on Colorimetric Sensor Array Combined with Image Processing and Visible Near-Infrared Spectroscopy

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