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    Development and Application of Miniaturized Nearinfrared Spectroscopy Coupled with Multivariate Classification Techniques for Food Authenticity

    , Ph.D. Dissertation Sharif University of Technology Ehsani, Samaneh (Author) ; Parastar Shahri, Hadi (Supervisor) ; Yazdanpanah, Hassan (Co-Supervisor)
    Abstract
    The need to measure the authenticity of food has always been an important concern of many countries. Since food fraud can cause serious problems, every year, much research is conducted in the field of food authenticity all over the world. Milk among dairy products and orange juice among fruit juices are two categories of widely consumed beverages all over the world, therefore they are exposed to various frauds from the manufacturers. Frauds such as adding water to milk and preservatives such as hydrogen peroxide, formaldehyde, and sodium hypochlorite are common frauds that are added to milk to increase its volume and storage time. Among the common cases of adulteration in orange juice, we... 

    Development of Chemometric Methods Combined with Isotope Ratio Mass Spectrometry (IRMS) for Isotope Pattern Recognition and Adulteration Detection in Foods

    , M.Sc. Thesis Sharif University of Technology Ghiasi, Ali (Author) ; Parastar Shahri, Hadi (Supervisor)
    Abstract
    The purpose of this study was to investigate the capability of Isotopic Ratio Mass Spectrometry (IRMS) in the detection of four common natural plant frauds in saffron, namely Marigold flower, Safflower, Rubia and Saffron Style. For this purpose, first natural saffron isotopes were analyzed and used to investigate fingerprints of carbon-13 and nitrogen-15 isotopes by Elemental Analyzer Isotopic Ratio Mass Spectrometry (EA-IRMS) and carbon-13 isotopic ratio of saffron components by Gas Chromatography Isotopic Ratio Mass Spectrometry (GC-C-IRMS). Then, according to the isotopic behavior of the original saffron, they were sampled to form a mixture of saffron that is representative of the... 

    Evaluation of FT-IR spectroscopy combined with SIMCA and PLS‑DA for detection of adulterants in pistachio butter

    , Article Infrared Physics and Technology ; Volume 127 , 2022 ; 13504495 (ISSN) Khanban, F ; Bagheri Garmarudi, A ; Parastar, H ; Toth, G ; Sharif University of Technology
    Elsevier B.V  2022
    Abstract
    This work scrutinized the adulteration of pistachio butter with three potential edible oils using Fourier transform infrared spectroscopy (FT-IR) and multivariate classification methods. Each of the classes, including non-adulterated samples and adulterated samples consisting of pistachio butter mixed with various concentrations of peanut oil, corn oil and sunflower oil, were classified. For this purpose, multivariate methods, including soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA), were applied to classify the FTIR data. After evaluating the model on unknown samples, the results indicated that PLS-DA was better than the SIMCA... 

    Development and Application of Chemometric Methods for Hyperspectral Image Analysis for Authentication and Adulteration Detection in Food (Saffron and Turmeric)

    , Ph.D. Dissertation Sharif University of Technology Hashemi Nasab, Fatemeh Sadat (Author) ; Parastar Shahri, Hadi (Supervisor) ; Abdollahi, Hamid (Supervisor)
    Abstract
    The use of hyperspectral images to detect food fraud has become popular and it is necessary to develop chemometrics methods for analyzing the data from these images. Additionally, food authenticity has become a major challenge, and the focus of this thesis is on developing multivariate methods in chemometrics to extract useful information from data obtained from food authenticity verification using hyperspectral imaging (HSI). This thesis consists of six chapters. In the first chapter, a brief introduction to the fundamentals of hyperspectral imaging and food authenticity verification is presented. In the second chapter, the data structure of these images and chemometric methods including... 

    Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration

    , Article Journal of Separation Science ; Volume 39, Issue 2 , 2016 , Pages 367-374 ; 16159306 (ISSN) Parastar, H ; Mostafapour, S ; Azimi, G ; Sharif University of Technology
    Wiley-VCH Verlag 
    Abstract
    Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make... 

    Chemometrics-assisted isotope ratio fingerprinting based on gas chromatography/combustion/isotope ratio mass spectrometry for saffron authentication

    , Article Journal of Chromatography A ; Volume 1657 , 2021 ; 00219673 (ISSN) Ghiasi, S ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    In the present contribution, the capability of isotopic ratio mass spectrometry (IRMS) for saffron authentication and detection of four common plant-derived adulterants (marigold flower, safflower, rubia, and saffron style) was investigated. For this purpose, 62 authentic saffron samples were analyzed by elemental analyzer-IRMS (EA-IRMS) and gas chromatography-combustion-IRMS (GC-C-IRMS). In this regard, EA-IRMS and GC-C-IRMS isotope fingerprints of carbon-13 and nitrogen-15 isotopes of saffron components were provided and then analyzed by chemometric methods. Principal component analysis (PCA) showed two different behaviors regarding two main regions. Then, a representative saffron sample... 

    Combining multivariate image analysis with high-performance thin-layer chromatography for development of a reliable tool for saffron authentication and adulteration detection

    , Article Journal of Chromatography A ; Volume 1628 , 2020 Amirvaresi, A ; Rashidi, M ; Kamyar, M ; Amirahmadi, M ; Daraei, B ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    In this work, high-performance thin-layer chromatography (HPTLC) coupled with multivariate image analysis (MIA) is proposed as a fast and reliable tool for authentication and adulteration detection of Iranian saffron samples based on their HPTLC fingerprints. At first, the secondary metabolites of saffron were extracted using ultrasonic-assisted solvent extraction (UASE) which was optimized using central composite design (CCD). Next, the RGB coordinates of HPTLC images were used for estimation of saffron origin based on principal component analysis (PCA). The PCA scores plot showed that saffron samples were clustered into two clear-cut groups which was 92% matched with the geographical...