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Discrimination of untreated and sodium sulphite treated bean sprouts by Fourier transform infrared spectroscopy and chemometrics.
- Source :
-
Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment [Food Addit Contam Part A Chem Anal Control Expo Risk Assess] 2024 Jun; Vol. 41 (6), pp. 587-600. Date of Electronic Publication: 2024 Apr 22. - Publication Year :
- 2024
-
Abstract
- Sprouts of black beans ( Phaseolus vulgaris L.), soybeans ( Glycine max L.) and mung beans ( Vigna radiata L.) are widely consumed foods containing abundant nutrients with biological activities. They are commonly treated with sulphites for the preservation and extension of shelf-life. However, our previous investigation found that immersing the bean sprouts in sulphite might convert the active components into sulphur-containing derivatives, which can affect both the quality and safety of the sprouts. This study explores the use of FTIR in conjunction with chemometric techniques to differentiate between non-immersed (NI) and sodium sulphite immersed (SI) black bean, soybean and mung bean sprouts. A total of 168 batches of raw spectra were obtained from NI and SI-bean sprouts using FTIR spectroscopy. Four pre-processing techniques, three modelling assessment techniques and four model evaluation indices were examined for differences in performance. The results show that the multiplicative scatter correction is the most effective pre-processing method. Among the models, the accuracy rate of the three models was as follows: radial basis function neural network (95%) > convolutional neural network (91%) > random forest (82%). The overall findings indicate that FTIR spectroscopy, in conjunction with appropriate chemometric approaches, has a high potential for rapidly determining the difference between NI and SI-bean sprouts.
Details
- Language :
- English
- ISSN :
- 1944-0057
- Volume :
- 41
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
- Publication Type :
- Academic Journal
- Accession number :
- 38648105
- Full Text :
- https://doi.org/10.1080/19440049.2024.2341104