Pesticide Residue Screening Using a Novel Artificial Neural Network Combined with a Bioelectric Cellular Biosensor
We developed a novel artificial neural network (ANN) system able to detect and classify pesticide residues. The novel ANN is coupled, in a customized way, to a cellular biosensor operation based on the bioelectric recognition assay (BERA) and able to simultaneously assay eight samples in three minut...
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Published in | BioMed research international Vol. 2013; no. 2013; pp. 1 - 8 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Cairo, Egypt
Hindawi Publishing Corporation
01.01.2013
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Abstract | We developed a novel artificial neural network (ANN) system able to detect and classify pesticide residues. The novel ANN is coupled, in a customized way, to a cellular biosensor operation based on the bioelectric recognition assay (BERA) and able to simultaneously assay eight samples in three minutes. The novel system was developed using the data (time series) of the electrophysiological responses of three different cultured cell lines against three different pesticide groups (carbamates, pyrethroids, and organophosphates). Using the novel system, we were able to classify correctly the presence of the investigated pesticide groups with an overall success rate of 83.6%. Considering that only 70,000–80,000 samples are annually tested in Europe with current conventional technologies (an extremely minor fraction of the actual screening needs), the system reported in the present study could contribute to a screening system milestone for the future landscape in food safety control. |
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AbstractList | We developed a novel artificial neural network (ANN) system able to detect and classify pesticide residues. The novel ANN is coupled, in a customized way, to a cellular biosensor operation based on the bioelectric recognition assay (BERA) and able to simultaneously assay eight samples in three minutes. The novel system was developed using the data (time series) of the electrophysiological responses of three different cultured cell lines against three different pesticide groups (carbamates, pyrethroids, and organophosphates). Using the novel system, we were able to classify correctly the presence of the investigated pesticide groups with an overall success rate of 83.6%. Considering that only 70,000-80,000 samples are annually tested in Europe with current conventional technologies (an extremely minor fraction of the actual screening needs), the system reported in the present study could contribute to a screening system milestone for the future landscape in food safety control. |
Author | Blouchos, Petros Yialouris, Constantinos P. Kintzios, Spyridon Moschopoulou, Georgia Ferentinos, Konstantinos P. |
AuthorAffiliation | 1 Laboratory of Informatics, School of Food Science, Biotechnology and Development, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece 2 Laboratory of Enzyme Technology, School of Food Science, Biotechnology and Development, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece |
AuthorAffiliation_xml | – name: 2 Laboratory of Enzyme Technology, School of Food Science, Biotechnology and Development, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece – name: 1 Laboratory of Informatics, School of Food Science, Biotechnology and Development, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23984408$$D View this record in MEDLINE/PubMed |
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Copyright | Copyright © 2013 Konstantinos P. Ferentinos et al. Copyright © 2013 Konstantinos P. Ferentinos et al. 2013 |
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Snippet | We developed a novel artificial neural network (ANN) system able to detect and classify pesticide residues. The novel ANN is coupled, in a customized way, to a... |
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SubjectTerms | Animals Biosensing Techniques - instrumentation Biosensing Techniques - methods Carbamates - analysis Cell Line Electricity Humans Mice Neural Networks (Computer) Organophosphates - analysis Pesticide Residues - analysis Pyrethrins - analysis |
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Title | Pesticide Residue Screening Using a Novel Artificial Neural Network Combined with a Bioelectric Cellular Biosensor |
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