Multiscale Deepspectra Network: Detection of Pyrethroid Pesticide Residues on the Hami Melon

Bibliographic Details
Title: Multiscale Deepspectra Network: Detection of Pyrethroid Pesticide Residues on the Hami Melon
Authors: Guowei Yu, Huihui Li, Yujie Li, Yating Hu, Gang Wang, Benxue Ma, Huting Wang
Source: Foods, Vol 12, Iss 9, p 1742 (2023)
Publisher Information: MDPI AG, 2023.
Publication Year: 2023
Collection: LCC:Chemical technology
Subject Terms: visible/near-infrared spectroscopy, deep learning, pesticide residues, spectral analysis, Hami melon, Chemical technology, TP1-1185
More Details: The problem of pyrethroid residues has become a topical issue, posing a potential food safety concern. Pyrethroid pesticides are widely used to prevent and combat pests in Hami melon cultivation. Due to its high sensitivity and accuracy, gas chromatography (GC) is used most frequently for detecting pyrethroid pesticide residues. However, GC has a high cost and complex operation. This study proposed a deep-learning approach based on the one-dimensional convolutional neural network (1D-CNN), named Deepspectra network, to detect pesticide residues on the Hami melon based on visible/near-infrared (380–1140 nm) spectroscopy. Three combinations of convolution kernels were compared in the single-scale Deepspectra network. The convolution group of “5 × 1” and “3 × 1” kernels obtained a better overall performance. The multiscale Deepspectra network was compared to three single-scale Deepspectra networks on the preprocessing spectral data and obtained better results. The coefficient of determination (R2) for lambda-cyhalothrin and beta-cypermethrin was 0.758 and 0.835, respectively. The residual predictive deviation (RPD) for lambda-cyhalothrin and beta-cypermethrin was 2.033 and 2.460, respectively. The Deepspectra networks were compared with two conventional regression models: partial least square regression (PLSR) and support vector regression (SVR). The results showed that the multiscale Deepspectra network outperformed the other models. It was found that the multiscale Deepspectra network could be a novel approach for the quantitative estimation of pyrethroid pesticide residues on the Hami melon. These findings can also provide an effective strategy for spectral analysis.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2304-8158
Relation: https://www.mdpi.com/2304-8158/12/9/1742; https://doaj.org/toc/2304-8158
DOI: 10.3390/foods12091742
Access URL: https://doaj.org/article/d34aba8da50249b7a2f11336b4417ab8
Accession Number: edsdoj.34aba8da50249b7a2f11336b4417ab8
Database: Directory of Open Access Journals
More Details
ISSN:23048158
DOI:10.3390/foods12091742
Published in:Foods
Language:English