| Literature DB >> 30352638 |
Issam Barra1, Mohammed Alaoui Mansouri1, Mohammed Bousrabat1, Yahia Cherrah1, Abdelaziz Bouklouze1, Mourad Kharbach2.
Abstract
In this work, transform-infrared spectroscopy (FTIR) was associated with chemometric tools, especially principal component analysis (PCA) and partial least squares regression (PLSR), to discriminate and quantify gasoline adulteration with diesel. The method is composed of a total of 100 mixtures were prepared, and then FTIR fingerprints were recorded for all samples. PCA was used to verify that mixtures can be distinguished from pure products and to check that there are no outliers. As a result of using just PC1 and PC2, more than 98% of the general variability was explained. The PLSR model based on infrared spectra has shown its capabilities to be suitable for predicting gasoline adulteration in the concentration range of 0 to 98% (w/w), with a high significant coefficient of determination (R² = 99.25%) and an acceptable calibration and prediction errors (root mean squared error of calibration = 0.63 and root mean square of external validation and/or prediction = 0.69).Entities:
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Year: 2018 PMID: 30352638 DOI: 10.5740/jaoacint.18-0179
Source DB: PubMed Journal: J AOAC Int ISSN: 1060-3271 Impact factor: 1.913