A novel colorimetric sensor array based on boron-dipyrromethene dyes for monitoring the storage time of rice

Hao, Lin; Man, Zhong-xiu; Kang, Wencui; Guan, Binbin; Chen, Quansheng; Xue, Zhaoli

doi:10.1016/j.foodchem.2018.06.097

Cited by 64 publications

(23 citation statements)

References 28 publications

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“…This kind of sensor has the advantage of being able to sense VOCs that are not detectable by electrochemical sensors and avoid the influence of humidity (Borrás‐Linares et al, ). In recent years, the CSA technique has been applied to assess wine (Ouyang, Zhao, Chen, & Lin, ), monitor black tea fermentation in real time (Li et al, ), discriminate different roasted coffee samples (Kim, Ko, Kang, & Park, ), differentiate rice with different storage time (Lin et al, ), evaluate fish freshness (Lv, Huang, Aheto, Mu, & Tian, ; Morsy et al, ), and so on. Based on the above researches, we can draw the conclusion that the CSA technology has strong ability to analyze the VOCs during the fermentation of T. aurantialba .…”

Section: Introductionmentioning

confidence: 99%

Real‐time detection of saponin content during the fermentation process of Tremella aurantialba using a homemade artificial olfaction system

Dai

Huang

et al. 2019

J Food Process Engineering

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Saponin is one of the most important products of Tremella aurantialba fermentation. The purpose of this research is to develop a portable artificial visualization system for convenient and nondestructive monitoring the saponin content during the fermentation process of T. aurantialba in real time. This system consisted of a colorimetric sensor array (CSA) and image acquisition program. Support vector machine regression (SVR) model was utilized to establish the quantitative model for predicting saponin content. Principal component analysis was applied to reduce the input dimension of

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Section: Introductionmentioning

confidence: 99%

Real‐time detection of saponin content during the fermentation process of Tremella aurantialba using a homemade artificial olfaction system

Dai

Huang

et al. 2019

J Food Process Engineering

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“…The design concept of amino acid uorescent probe is that considering the error of detection results caused by the toxicity of the probe itself, pyrimidine [32][33][34], which is widely used in the drug eld, is selected as the intermediate of targeting action to introduce the uorescent group BODIPY [35]. This design not only greatly reduces the toxicity problem of the probe, but also has certain drug activity in the overall structure.…”

Section: Resultsmentioning

confidence: 99%

Study On The Responsiveness of A Novel Pyrimidine-BODIPY Probe For Rapid Identification of Different Amino Acids

Jin¹,

Shao²,

Jin³

2021

Preprint

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Rapid identification of different amino acid responses is of great importance in the field of biomedicine. Through the combination of the drug intermediate pyrimidine with the fluorophore BODIPY, a new type of high-efficiency fluorescent probe for rapid identification of different amino acids was prepared. In terms of photophysical properties, the UV absorption and fluorescence emission of the mercapto groups were observed under the conditions of different hydroperoxide equivalents and different solvents, and the maximum values were in the range of 534–538 nm and 554–560 nm. When different amino acids were added, the UV absorption and fluorescence emission ranges were 538 ~ 540 nm and 560 ~ 564 nm. Finally, the identification sensitivity of amino acids with different equivalents under different oxidant conditions was quickly detected by fluorescence cuvette. Among them, the identification response to tyrosine was the most obvious.

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“…29 Generally, mathematical processing aims to linearly combine the original P indicators as a new comprehensive indicator. 30 In the present study, PCA was first used to eliminate possible information redundancy among the sensor features that were initially extracted, the feature space was further compressed and the spatial distribution of edible oil samples for different storage periods was visualized through the principal component score plot. Thus, fewer latent feature variables were extracted as the input features of the recognition model.…”

Section: Multivariate Data Analysis Principal Component Analysis (Pca)mentioning

confidence: 99%

Qualitative identification of the edible oil storage period using a homemade portable electronic nose combined with multivariate analysis

Jiang

Chen

2020

J Sci Food Agric

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BACKGROUND: The edible oil storage period is one of the important indicators for evaluating the intrinsic quality of edible oil. The present study aimed to develop a portable electronic nose device for the qualitative identification of the edible oil storage period. First, four metal oxide semiconductor gas sensors, comprising TGS2600, TGS2611, TGS2620 and MQ138, were selected to prepare a sensor array to assemble a portable electronic nose device. Second, the homemade portable electronic nose device was used to obtain the odor change information of edible oil samples during different storage periods, and the sensor features were extracted. Finally, three pattern recognition methods, comprising linear discriminant analysis (LDA), K-nearest neighbors (KNN) and support vector machines (SVM), were compared to establish a qualitative identification model of the edible oil storage period. The input features and related parameters of the model were optimized by a five-fold cross-validation during the process of model establishment. RESULTS:The research results showed that the recognition performance of the non-linear SVM model was significantly better than that of the linear LDA and KNN models, especially in terms of generalization performance, which had a correct recognition rate of 100% when predicting independent samples in the prediction set. CONCLUSION:The overall results demonstrate that it is feasible to apply the homemade portable electronic nose device with the help of the appropriate pattern recognition methods to achieve the fast and efficient identification of the edible oil storage period, which provides an effective analysis tool for the quality detection of the edible oil storage.

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A novel colorimetric sensor array based on boron-dipyrromethene dyes for monitoring the storage time of rice

Cited by 64 publications

References 28 publications

Real‐time detection of saponin content during the fermentation process of Tremella aurantialba using a homemade artificial olfaction system

Real‐time detection of saponin content during the fermentation process of Tremella aurantialba using a homemade artificial olfaction system

Study On The Responsiveness of A Novel Pyrimidine-BODIPY Probe For Rapid Identification of Different Amino Acids

Qualitative identification of the edible oil storage period using a homemade portable electronic nose combined with multivariate analysis

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