Preparation of Mesoporous Silica Nanosphere-Doped Color-Sensitive Materials and Application in Monitoring the TVB-N of Oysters.
Binbin GuanFuyun WangHao JiangMi ZhouHao LinPublished in: Foods (Basel, Switzerland) (2022)
In this work, a new colorimetric sensor based on mesoporous silica nanosphere-modified color-sensitive materials was established for application in monitoring the total volatile basic nitrogen (TVB-N) of oysters. Firstly, mesoporous silica nanospheres (MSNs) were synthesized based on the improved Stober method, then the color-sensitive materials were doped with MSNs. The "before image" and the "after image" of the colorimetric senor array, which was composed of nanocolorimetric-sensitive materials by a charge-coupled device (CCD) camera were then collected. The different values of the before and after image were analyzed by principal component analysis (PCA). Moreover, the error back-propagation artificial neural network (BP-ANN) was used to quantitatively predict the TVB-N values of the oysters. The correlation coefficient of the colorimetric sensor array after being doped with MSNs was greatly improved; the Rc and Rp of BP-ANN were 0.9971 and 0.9628, respectively when the principal components (PCs) were 10. Finally, a paired sample t -test was used to verify the accuracy and applicability of the BP-ANN model. The result shows that the colorimetric-sensitive materials doped with MSNs could improve the sensitivity of the colorimetric sensor array, and this research provides a fast and accurate method to detect the TVB-N values in oysters.
Keyphrases
- gold nanoparticles
- neural network
- quantum dots
- sensitive detection
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- living cells
- deep learning
- highly efficient
- high resolution
- high throughput
- visible light
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- single molecule
- gas chromatography
- high speed
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