Nanozyme-Powered Multimodal Sensing for Pesticide Detection

The detection of pesticide residues in food is crucial for ensuring food safety, safeguarding public health, and promoting sustainable development. Overusing pesticides on agricultural crops can lead to the emergence of various diseases. Traditional methods for detecting pesticides offer high precis...

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Main Authors: Binfeng Yin, Zhuoao Jiang, Rashid Muhammad, Jun Liu, Junjie Wang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Foods
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Online Access:https://www.mdpi.com/2304-8158/14/11/1957
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author Binfeng Yin
Zhuoao Jiang
Rashid Muhammad
Jun Liu
Junjie Wang
author_facet Binfeng Yin
Zhuoao Jiang
Rashid Muhammad
Jun Liu
Junjie Wang
author_sort Binfeng Yin
collection DOAJ
description The detection of pesticide residues in food is crucial for ensuring food safety, safeguarding public health, and promoting sustainable development. Overusing pesticides on agricultural crops can lead to the emergence of various diseases. Traditional methods for detecting pesticides offer high precision with limitations like high cost, the requirement of expert technicians, and tedious analytical procedures. To address these issues, nanozymes have been widely applied due to their advantages such as low cost, high stability, and high sensitivity. This review summarizes the research progress of nanozymes in the detection of pesticide residues in food over the last decade, focusing on the synthesis strategies and catalytic mechanisms of carbon-based, metal-based, metal-oxide-based, metal–organic framework (MOF)-based, fluorescence-based, and other X-based nanozymes. This review covers the application of multimodal sensing based on nanozymes in the detection of pesticides, including colorimetric/fluorescence, fluorescence/photothermal, photothermal/colorimetric, and other multimodal sensing techniques. Finally, this review discusses the main challenges currently faced by nanozymes in the detection of pesticides and the current applications of using AI with nanozymes. It also presents future development prospects, with the aim of providing references for the selection of X-based nanozymes and the choice of appropriate detection methods when dealing with traditional and new pesticides in combination with AI.
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issn 2304-8158
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spelling doaj-art-58caac486e044d0baf84a86a0b22b8ff2025-08-20T02:23:07ZengMDPI AGFoods2304-81582025-05-011411195710.3390/foods14111957Nanozyme-Powered Multimodal Sensing for Pesticide DetectionBinfeng Yin0Zhuoao Jiang1Rashid Muhammad2Jun Liu3Junjie Wang4School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, ChinaSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, ChinaSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, ChinaSuqian Product Quality Supervision and Inspection Institute, Suqian 223800, ChinaSchool of Mechanical Engineering, Yangzhou University, Yangzhou 225127, ChinaThe detection of pesticide residues in food is crucial for ensuring food safety, safeguarding public health, and promoting sustainable development. Overusing pesticides on agricultural crops can lead to the emergence of various diseases. Traditional methods for detecting pesticides offer high precision with limitations like high cost, the requirement of expert technicians, and tedious analytical procedures. To address these issues, nanozymes have been widely applied due to their advantages such as low cost, high stability, and high sensitivity. This review summarizes the research progress of nanozymes in the detection of pesticide residues in food over the last decade, focusing on the synthesis strategies and catalytic mechanisms of carbon-based, metal-based, metal-oxide-based, metal–organic framework (MOF)-based, fluorescence-based, and other X-based nanozymes. This review covers the application of multimodal sensing based on nanozymes in the detection of pesticides, including colorimetric/fluorescence, fluorescence/photothermal, photothermal/colorimetric, and other multimodal sensing techniques. Finally, this review discusses the main challenges currently faced by nanozymes in the detection of pesticides and the current applications of using AI with nanozymes. It also presents future development prospects, with the aim of providing references for the selection of X-based nanozymes and the choice of appropriate detection methods when dealing with traditional and new pesticides in combination with AI.https://www.mdpi.com/2304-8158/14/11/1957pesticide residuesnanozymesmultimodal sensingAIfood safety
spellingShingle Binfeng Yin
Zhuoao Jiang
Rashid Muhammad
Jun Liu
Junjie Wang
Nanozyme-Powered Multimodal Sensing for Pesticide Detection
Foods
pesticide residues
nanozymes
multimodal sensing
AI
food safety
title Nanozyme-Powered Multimodal Sensing for Pesticide Detection
title_full Nanozyme-Powered Multimodal Sensing for Pesticide Detection
title_fullStr Nanozyme-Powered Multimodal Sensing for Pesticide Detection
title_full_unstemmed Nanozyme-Powered Multimodal Sensing for Pesticide Detection
title_short Nanozyme-Powered Multimodal Sensing for Pesticide Detection
title_sort nanozyme powered multimodal sensing for pesticide detection
topic pesticide residues
nanozymes
multimodal sensing
AI
food safety
url https://www.mdpi.com/2304-8158/14/11/1957
work_keys_str_mv AT binfengyin nanozymepoweredmultimodalsensingforpesticidedetection
AT zhuoaojiang nanozymepoweredmultimodalsensingforpesticidedetection
AT rashidmuhammad nanozymepoweredmultimodalsensingforpesticidedetection
AT junliu nanozymepoweredmultimodalsensingforpesticidedetection
AT junjiewang nanozymepoweredmultimodalsensingforpesticidedetection