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Discrimination of untreated and sodium sulphite treated bean sprouts by Fourier transform infrared spectroscopy and chemometrics.

Authors :
Li Y
Chen B
Ye S
Wu Q
Zhu L
Ding Y
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