Prediction of two-dimensional gas chromatography time-of-flight mass spectrometry retention times of 160 pesticides and 25 environmental organic pollutants in grape by multivariate chemometrics methods
Publish place: Advanced Journal of Chemistry-Section A، Vol: 1، Issue: 0
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_AJCS-1-0_003
تاریخ نمایه سازی: 19 تیر 1398
Abstract:
A quantitative structure–retention relation (QSRR) study was conducted on the retention times of 160 pesticides and 25 environmental organic pollutants in wine and grape. The genetic algorithm was used as descriptor selection and model development method. Modeling of the relationship between selected molecular descriptors and retention time was achieved by linear (partial least square; PLS) and nonlinear (kernel PLS: KPLS and Levenberg-Marquardt artificial neural network; L-M ANN) methods. The QSRR models were validated by cross-validation as well as application of the models to predict the retention of external set compounds, which did not have contribution in model development steps. Linear and nonlinear methods resulted in accurate prediction whereas more accurate results were obtained by L-M ANN model. The best model obtained from L-M ANN showed a good R2 value (determination coefficient between observed and predicted values) for all compounds, which was superior to those of other statistical models. This is the first research on the QSRR of the compounds in wine and grape against the retention time using the GA-KPLS and L-M ANN.
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Authors
Issa Amini
Department of Chemistry, Payame Noor University, P.O. BOX ۱۹۳۹۵-۴۶۹۷, Tehran, Iran
Kaushik Pal
Department of Nanotechnology, Bharath University,BIHER Research Park, Chennai, Tamil Nadu ۶۰۰۰۷۳, India
Sharmin Esmaeilpoor
Department of Chemistry, Payame Noor University, P.O. BOX ۱۹۳۹۵-۴۶۹۷, Tehran, Iran
Aydi Abdelkarim
Department of Chemical and Materials Engineering, College of Engineering, National College of Chemical Industry, Nancy, Polytechnic Institute of Lorraine, France Frankfurt Am Main Area, Germany.
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