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- W2369594906 abstract "This paper presented a novel classifier built by support vector machines(SVM)and near infrared spectroscopy(NIR)to identify pesticide residue in vegetable rapidly. 86 unit Chlorpyrifos samples were confected from 0.005mg/kg to 5mg/kg,which simulated pesticide residue samples of vegetables. According to the national standard,the detection value of Chlorpyrifos was 0.05mg/kg. The experimental samples were selected by content of the gradient and Kennard-Stone respectively. The satisfying classifier can be built by adjusting the penalty parameter of SVM. Results indicated that the combination of SVM and NIR can detect pesticide residue on the vegetable directly and lossless,it also provided a possible way of rapid detection on vegetable in the future." @default.
- W2369594906 created "2016-06-24" @default.
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- W2369594906 date "2010-01-01" @default.
- W2369594906 modified "2023-09-24" @default.
- W2369594906 title "Study on rapid qualitative analysis of pesticide residue in vegetable based on near infrared spectroscopy" @default.
- W2369594906 hasPublicationYear "2010" @default.
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