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Classification of methamphetamine seized in different regions of Iran using GC–MS and chemometrics

Classification of methamphetamine seized in different regions of Iran using GC–MS and chemometrics

Authors :
Yousefinejad, Saeed
Bahram, Morteza
Baheri, Tahmineh
Source :
Journal of the Iranian Chemical Society; January 2018, Vol. 15 Issue: 1 p163-170, 8p
Publication Year :
2018

Abstract

According to the intensive physical and mental risk of methamphetamine (crystal) on human, it is important to focus on the prevention of distribution and decrease of the usage of methamphetamine. In the current study, attempts was on the application of GC–MS analysis combined with chemometrics to present a classification model for methamphetamine samples seized in different regions of Iran. In this work, principal component analysis was not able to discriminate samples from different geographic regions. For the discrimination goal, partial least squares discriminant analysis (PLS-DA) and extended canonical variate analysis (ECVA) were utilized and a classification model was constructed to differentiate methamphetamine samples seized in three regions of Iran, i.e., south, west and central. PLS-DA showed good performance in calibration step; however, ECVA indicated better prediction ability. The difference of the classified samples can be because of difference in the synthetic root used in each of three investigated regions. Class sensitivity and selectivity for all three regions were excellent in ECVA model with nonsignificant misclassifications. Cross-validation and external validation using a test set confirmed the obtained classification model. Statistical results indicated a regional production/distribution pattern in the country.

Details

Language :
English
ISSN :
1735207X and 17352428
Volume :
15
Issue :
1
Database :
Supplemental Index
Journal :
Journal of the Iranian Chemical Society
Publication Type :
Periodical
Accession number :
ejs44555500
Full Text :
https://doi.org/10.1007/s13738-017-1219-5