A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin

Xiaopeng Zhang; Yaru Li; Yan Tao; Yang Wang; Changhua Xu; Ying Lu

doi:10.1016/j.foodchem.2020.127986

A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin

Food Chem. 2021 Feb 1:337:127986. doi: 10.1016/j.foodchem.2020.127986. Epub 2020 Sep 6.

Authors

Xiaopeng Zhang¹, Yaru Li², Yan Tao¹, Yang Wang³, Changhua Xu⁴, Ying Lu⁵

Affiliations

¹ College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China.
² College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai 201306, China; Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai 201306, China.
³ First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300112, China.
⁴ College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai 201306, China; Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai 201306, China. Electronic address: chxu@shou.edu.cn.
⁵ College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai 201306, China; Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai 201306, China. Electronic address: y-lu@shou.edu.cn.

PMID: 32920269
DOI: 10.1016/j.foodchem.2020.127986

Abstract

We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific detection of the fish allergen parvalbumin. SDS-PAGE and ELISA were used to validate the new method. Through training and learning with parvalbumin IR spectra from 16 fish species, IRN, support vector machine (SVM), and random forest (RF) models were successfully established and compared. The IRN model extracted highly representative features from the IR spectra, leading to high accuracy in recognizing parvalbumin (up to 97.3%) in a variety of seafood matrices. The proposed infrared spectroscopic IRN (IR-IRN) method was rapid (~20 min, cf. ELISA ~4 h) and required minimal expert knowledge for application. Thus, it could be extended for large-scale field screening and identification of parvalbumin or other potential allergens in complex food matrices.

Keywords: Allergen; Inception-resnet network; Infrared spectroscopy; Parvalbumin; Rapid detection.

MeSH terms

Allergens / chemistry
Animals
Electrophoresis, Polyacrylamide Gel
Enzyme-Linked Immunosorbent Assay
Fish Products / analysis*
Fish Proteins / analysis*
Fishes / immunology
Food Analysis / methods
Food Analysis / statistics & numerical data
Food Hypersensitivity
Mice
Mice, Inbred BALB C
Neural Networks, Computer*
Parvalbumins / analysis*
Parvalbumins / immunology
Reproducibility of Results
Spectrophotometry, Infrared / methods
Spectrophotometry, Infrared / statistics & numerical data*
Support Vector Machine

Substances

Allergens
Fish Proteins
Parvalbumins