0000000000121575
AUTHOR
Amir Bagheri Garmarudi
showing 7 related works from this author
Artificial neural network for quantitative determination of total protein in yogurt by infrared spectrometry
2009
Abstract A method has been introduced for quantitative determination of protein content in yogurt samples based on the characteristic absorbance of protein in 1800–1500 cm− 1 spectral region by mid-FTIR spectroscopy and chemometrics. Successive Projection Algorithm (SPA) wavelength selection procedure, coupled with feed forward Back-Propagation Artificial Neural Network (BP-ANN) model was the benefited chemometric technique. Relative Error of Prediction (REP) in BP-ANN and SPA-BP-ANN methods for training set was 7.25 and 3.70 respectively. Considering the complexity of the sample, the ANN model was found to be reliable, while the proposed method is rapid and simple, without any sample prepa…
Application of infrared spectroscopy as Process Analytics Technology (PAT) approach in biodiesel production process utilizing Multivariate Curve Reso…
2019
Abstract Process Analytical Technology means at-line collection of analytical information from the process when the reaction is in progress. Obtained information enables process engineers to better control the Critical Process Parameters and direct the reaction to desirable routs. Near-infrared spectroscopy due to its analytical features, as well as the high capability of automation, versatile sampling and spectral acquisition methods is a useful tool in process monitoring when coupled to chemometrics. The Multiple Scatter Correction preprocessing technique and Alternative Least Square method can extract spectral and concentration information of a reaction mixture simultaneously, were emplo…
Characterization of petroleum-based products by infrared spectroscopy and chemometrics
2012
Abstract The role of fossil fuels in providing the energy required for automobiles, factories and daily life has seriously concerned the authorities. Consistency of the quality of petroleum-based products is an important aspect of social and environmental criteria in a developed society. High-quality petroleum-based fuels would have several benefits (e.g., reduction in rate of consumption, less environmental pollution and durability of hardware). We review recent advances in the application of infrared spectroscopy in the petroleum industry. We focus on the methods proposed for the determination of a wide range of characteristics in petroleum-based products. We discuss methods based on the …
Synthesis and optimization of microwave-assisted exfoliated functionalized graphene as an efficient catalyst in biodiesel production
2018
In this study, the capability of functionalized graphene was investigated as heterogeneous catalyst in biodiesel production from vegetable oil. Graphene oxide was fabricated from graphite via carrier improved method, and its exfoliation was carried out by microwave radiation. The exfoliated sample was reduced and sulfonated, being analyzed by Fourier transform Infrared, Scanning Microscopy Transmission Electron Microscopy, X-ray diffraction and element mapping. The catalyst was employed in biodiesel production reaction and effective reaction parameters were studied. The optimized reaction temperature, time and catalyst percentage were 178 °C, 3 h and 1.9% respectively. It was observed that …
Quality based classification of gasoline samples by ATR-FTIR spectrometry using spectral feature selection with quadratic discriminant analysis
2013
Abstract A chemometric approach has been developed for characterization of gasoline samples regarding their quality. Attenuated total reflectance – infrared spectrometric data were processed by genetic algorithm (GA) and successive projection algorithm (SPA) feature selection techniques, being employed as an initial step prior to apply a discriminative tool. It was aimed to classify the fuel samples according to their quality passed/failed data. Chemometric predictive procedures were developed using quadratic discriminant analysis (QDA) combined with GA and SPA as a feature subset and feature selection strategy. Results showed 93.3% and 95.6% accuracy for SPA-QDA and GA-QDA models respectiv…
Origin based classification of crude oils by infrared spectrometry and chemometrics
2019
Abstract Crude oil samples from different Iranian petrol resources in both, raw and mixture forms have been characterized by attenuated total reflectance mid infrared spectroscopy. Obtained spectra were classified by chemometric techniques to propose a method for geological based classification of crude oil samples. Totally 251 samples from 7 petrol fields and 3 mixtures were analyzed. Mean centering and principal component analysis (PCA) supported – leverage value based outlier detection were used as preprocessing approaches. PCA, cluster analysis and soft independent modeling of class analogy (SIMCA) were utilized to classify the spectra. Obtained results confirmed that SIMCA is a robust …
Feature selection strategies for quality screening of diesel samples by infrared spectrometry and linear discriminant analysis.
2012
Abstract A rapid approach has been developed for the characterization of diesel quality, based on attenuated total reflectance – Fourier transform infrared (ATR-FTIR) spectrometry, which could be useful for diagnosing the sample quality condition. As a supervised technique, linear discriminant analysis (LDA) was employed to process the spectrometric data. The role of variable selection methods was also evaluated. Successive projection algorithm (SPA) and genetic algorithm (GA) feature selection techniques were applied prior to the discriminative procedure. It was aimed to compare the effect of feature selection procedures on classification capability of IR spectrometry for the diesel sample…