Affinity Sensing Strategies for the Detection of Pesticides in Food

This is a review of recent affinity-based approaches that detect pesticides in food. The importance of the quantification and monitoring of pesticides is firstly discussed, followed by a description of the different approaches reported in the literature. The different sensing approaches are reported...

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Main Authors: Denise Capoferri, Flavio Della Pelle, Michele Del Carlo, Dario Compagnone
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Foods
Subjects:
Online Access:http://www.mdpi.com/2304-8158/7/9/148
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author Denise Capoferri
Flavio Della Pelle
Michele Del Carlo
Dario Compagnone
author_facet Denise Capoferri
Flavio Della Pelle
Michele Del Carlo
Dario Compagnone
author_sort Denise Capoferri
collection DOAJ
description This is a review of recent affinity-based approaches that detect pesticides in food. The importance of the quantification and monitoring of pesticides is firstly discussed, followed by a description of the different approaches reported in the literature. The different sensing approaches are reported according to the different recognition element used: antibodies, aptamers, or molecularly imprinted polymers. Schemes of detection and the main features of the assays are reported and commented upon. The large number of affinity sensors recently developed and tested on real samples demonstrate that this approach is ready to be validated to monitor the amount of pesticides used in food commodities.
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spelling doaj.art-3ebdc4838dab4e8ea51a68488c4aba042022-12-22T00:50:27ZengMDPI AGFoods2304-81582018-09-017914810.3390/foods7090148foods7090148Affinity Sensing Strategies for the Detection of Pesticides in FoodDenise Capoferri0Flavio Della Pelle1Michele Del Carlo2Dario Compagnone3Faculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, ItalyFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, ItalyFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, ItalyFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, ItalyThis is a review of recent affinity-based approaches that detect pesticides in food. The importance of the quantification and monitoring of pesticides is firstly discussed, followed by a description of the different approaches reported in the literature. The different sensing approaches are reported according to the different recognition element used: antibodies, aptamers, or molecularly imprinted polymers. Schemes of detection and the main features of the assays are reported and commented upon. The large number of affinity sensors recently developed and tested on real samples demonstrate that this approach is ready to be validated to monitor the amount of pesticides used in food commodities.http://www.mdpi.com/2304-8158/7/9/148affinity sensorspesticidesimmunosensorsaptamersmolecularly imprinted polymerselectrochemical detectionoptical detection
spellingShingle Denise Capoferri
Flavio Della Pelle
Michele Del Carlo
Dario Compagnone
Affinity Sensing Strategies for the Detection of Pesticides in Food
Foods
affinity sensors
pesticides
immunosensors
aptamers
molecularly imprinted polymers
electrochemical detection
optical detection
title Affinity Sensing Strategies for the Detection of Pesticides in Food
title_full Affinity Sensing Strategies for the Detection of Pesticides in Food
title_fullStr Affinity Sensing Strategies for the Detection of Pesticides in Food
title_full_unstemmed Affinity Sensing Strategies for the Detection of Pesticides in Food
title_short Affinity Sensing Strategies for the Detection of Pesticides in Food
title_sort affinity sensing strategies for the detection of pesticides in food
topic affinity sensors
pesticides
immunosensors
aptamers
molecularly imprinted polymers
electrochemical detection
optical detection
url http://www.mdpi.com/2304-8158/7/9/148
work_keys_str_mv AT denisecapoferri affinitysensingstrategiesforthedetectionofpesticidesinfood
AT flaviodellapelle affinitysensingstrategiesforthedetectionofpesticidesinfood
AT micheledelcarlo affinitysensingstrategiesforthedetectionofpesticidesinfood
AT dariocompagnone affinitysensingstrategiesforthedetectionofpesticidesinfood