Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Department: search.filters.department.İzmir Institute of TechnologySubject: search.filters.subject.Chemometrics

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  • Article
    FTIR Spectroscopy Coupled With Chemometrics for Evaluating Functional Food Efficacy in an in Vitro Model of Iron Deficiency Anemia
    (Elsevier Science Ltd, 2026) Dalyan, Eda; Cavdaroglu, Cagri; Ozen, Banu; Gulec, Sukru
    Vibrational spectroscopy offers a rapid, cost-effective approach for studying biological systems. This study employs Fourier Transform Infrared (FTIR) spectroscopy, combined with Soft Independent Modeling of Class Analogy (SIMCA), to evaluate treatment outcomes for iron deficiency anemia (IDA). The model was built using spectra from healthy and anemic cells, then validated with cells treated with commonly used iron supplements. In calibration, 9 of 10 control and all IDA samples were correctly classified; 14 of 15 validation samples were identified as healthy. The model was applied to cells treated with protein-iron complexes. All samples treated with a 60:1 protein-iron ratio matched the healthy group, while 3 of 4 treated with a 10:1 ratio matched the IDA group. These results were further supported by iron-regulated gene expression of transferrin receptor (TFR) and (Ankyrin Repeat Domain 37) ANKRD37. FTIR coupled with chemometrics enables rapid assessment of functional effects and shows potential for screening functional ingredients in anemia-targeted food products.
  • Article
    Citation - Scopus: 1
    Adulteration of Pomegranate Molasses With Sugar Syrups: Application of FTIR-ATR Spectroscopy and Chemometrics
    (Elsevier, 2025) Kilinc, Gizem Simge; Uncu, Oguz; Eren, Ismail; Bagdatlioglu, Neriman
    In this study, it was aimed to determine the adulteration ratio of pomegranate molasses (PM) with sugar syrups by using FTIR spectroscopy based upon chemometrics. With this intention, 34 pure PM samples were supplied from local manufacturers and adulterated with high fructose corn syrup (HFCS), glucose-fructose syrup (GFS) and beet sugar syrup (BSS) in varying ratios (5-50 %, w/w). Authentic and adulterated PM samples were analyzed in the range of 4000 and 400 cm(-1) wavenumber by FTIR spectroscopy. PCA was applied as a pretreatment for classification and regression analysis to select the spectral region and data reduction. Whereby the DD-SIMCA models were created using this information. The adulterated and authentic samples were classified correctly by the developed DD-SIMCA models. In the calibration and prediction model of DD-SIMCA, authentic and adulterated PM samples were correctly classified with high sensitivity (>= 0.91) and specificity (>= 0.94), and a clear distinction was observed with high efficiency (>= 0.94). Adulteration rates in PM samples were determined by PLS-R analysis. The correlation coefficients (R-2 >= 0.98) of models were also found quite high. As a consequence, FTIR spectroscopy in conjunction with chemometric approaches could be applied as a quick, dependable, non-destructive, and environmentally friendly tool for categorizing, distinguishing, and quantifying adulteration rates in PM samples.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 2
    Year-To Differentiation of Black Tea Through Spectroscopic and Chemometric Analysis
    (Springer Science and Business Media Deutschland GmbH, 2025) Yorulmaz, H.; Cavdaroglu, C.; Donmez, O.; Serpen, A.; Ozen, B.
    The compositions of food products such as tea can vary significantly from one harvest year to another, primarily due to factors such as shifting climatic conditions, and plant periodicity. These fluctuations in composition can significantly affect the overall product quality. Spectral methods combined with chemometric techniques can provide efficient tools to monitor and assess these variations. In this study, 205 black tea samples from two consecutive harvest years were analyzed using mid-infrared, UV–visible, and fluorescence spectroscopy. Mid-infrared spectra were collected for both infused and powdered samples, while only the infused samples were used for the other spectroscopic methods. The study used partial least-square discriminant (PLS-DA) and orthogonal partial least-square discriminant analyses (OPLS-DA) to differentiate samples by harvest year. These models, applied after various data transformations, achieved high correct classification rates. Mid-infrared spectroscopic data yielded rates of 93.33% and 90.33% for powdered and infused samples, respectively. Fluorescence and UV–visible spectra also showed excellent prediction accuracy, with success rates of 98.3% and 100%. The results indicate that these spectroscopic methods, combined with chemometric differentiation, are valuable tools for monitoring year-to-year changes in black tea. © The Author(s) 2024.