Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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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, SukruVibrational 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 Harnessing Pulse Proteins as Soy Protein Substitutes in Spreadable Cheese Analogues: Exploring Correlations Among Protein Techno-Functionality, and Cheese Textural, Rheological and Sensory Properties(Elsevier Sci Ltd, 2026) Cavdaroglu, Elif; Topcuoglu, Meryem; Acar, Eda; Polat, Nil Yaren; Berk, Berkay; Cavdaroglu, Cagri; Yemenicioglu, AhmetThis study aimed at comparing techno-functional properties of faba bean (FBP), pinto bean (PBP), cowpea (CPP) and mung bean (MBP) proteins with commercial soy protein isolate (SPI), and exploring their correlations with textural, rheological and sensory properties of plant protein-based spreadable cheese analogues. FBP and MBP showed the best solubility between pH 3.0 and 11.0. The highest and the lowest water and oil (OAC) absorption capacities were observed for SPI and MBP (7.78 and 0.79 g H2O/g), and PBP and SPI (7.79 and 3.55 g oil/g). Protein's least gelling concentrations (LGC) ranged from 10 % (SPI) to 18 % (FBP). CPP, MBP, and PBP formed harder, gummier gels at >= LGC than SPI and FBP. Pre-gels of PBP and CPP at <= LGCs showed the highest consistency and viscosity indexes. Proteins showed similar emulsification. Cheese analogue from SPI (SPIC) showed the highest firmness (37.5 N) and work to shear for spreadability (57.5 N s), followed by cheese analogues of other proteins such as MBPC, CPPC, FBPC, and PBPC in descending order. The highest and lowest elastic (G ') and viscous (G '') moduli were obtained for MBPC (G' = 4353 and G"= 1277) and PBPC (G' = 377 Pa and G"= 98 Pa). OAC of proteins correlated with cheese analogues' firmness (r =- 0.918), work to shear for spreadability (r =- 0.910), and stickiness (r =- 0.894). Tan delta (G"/G ') of cheese analogues correlated with work to shear for spreadability (r = 0.986). SPIC and FBPC received the highest overall liking scores correlated mainly with appearance, color and taste. Correlating protein techno-functionality in cheese analogue opens new horizons for effective utilization of pulse proteins as soy protein substitutes.Article Citation - WoS: 3Citation - Scopus: 3Vibrational Spectroscopy in Plant-Based Protein Research: Quantification and Structural Analysis(Elsevier Science London, 2025) Cavdaroglu, Elif; Cavdaroglu, Cagri; Ozen, BanuBackground: Plant-based proteins are gaining importance in food science, biotechnology, and human health as sustainable and nutrient-rich alternatives to animal-derived proteins. The rising demand for plant-based foods, driven by environmental concerns and dietary shifts, has intensified research into plant protein sources. Accurate determination of protein content and structure is essential for ensuring the nutritional quality, optimizing functionality, and maintaining product consistency. Traditional protein analysis methods, while effective, often require extensive sample preparation and time-consuming procedures. Vibrational spectroscopy, including Fourier-transform Infrared (FTIR), Near-Infrared (NIR), and Raman spectroscopy, offers a rapid, non-destructive, and efficient alternative for protein characterization in complex food matrices. Scope and approach: This review explores the application of vibrational spectroscopy in evaluating plant-based protein content and their secondary structure. It outlines the fundamental principles of FTIR, NIR, and Raman spectroscopy, emphasizing their advantages over conventional techniques. Key challenges, such as spectral overlap, water interference, and calibration requirements, are discussed alongside emerging solutions involving chemometric approaches, artificial intelligence, and hybrid analytical techniques. Key findings and conclusions: Vibrational spectroscopy provides precise protein quantification and structural analysis with minimal sample preparation. FTIR and Raman spectroscopy complement each other in protein conformation analysis, while NIR facilitates rapid bulk protein assessment. Advances in computational methods are enhancing spectral interpretation and accuracy. Integrating vibrational spectroscopy with complementary techniques can further improve protein characterization, supporting the development of high-quality, sustainable plant-based protein sources for food and biotechnology applications.Article Citation - WoS: 8Citation - Scopus: 8Comparative Performance of Artificial Neural Networks and Support Vector Machines in Detecting Adulteration of Apple Juice Concentrate Using Spectroscopy and Time Domain Nmr☆(Elsevier, 2025) Cavdaroglu, Cagri; Altug, Nur; Serpen, Arda; Oztop, Mecit Halil; Ozen, BanuThe detection of adulteration in apple juice concentrate is critical for ensuring product authenticity and consumer safety. This study evaluates the effectiveness of artificial neural networks (ANN) and support vector machines (SVM) in analyzing spectroscopic data to detect adulteration in apple juice concentrate. Four techniques-UV-visible, fluorescence, near-infrared (NIR) spectroscopy, and time domain 1H nuclear magnetic resonance relaxometry (1H NMR)-were used to generate data from both authentic and adulterated apple juice samples. Adulterants included glucose syrup, fructose syrup, grape concentrate, and date concentrate. The spectroscopic data were pre-processed and analyzed using ANN and SVM models, with performance metrics such as sensitivity, specificity, and correct classification rates (CCR) evaluated for both calibration and validation sets. Results indicated that NIR spectroscopy combined with SVM provided the highest overall accuracy, with nearperfect specificity and high CCR values, making it the most robust method for adulteration detection. UV-visible and fluorescence spectroscopy also demonstrated strong performance but were slightly less consistent across different adulterants. 1H NMR relaxometry, while providing detailed molecular insights, showed variable sensitivity depending on the adulterant type. The findings showed the importance of selecting appropriate analytical techniques and machine learning models for food authentication. This study contributes to the development of non-destructive, rapid, and accurate methods for detecting food adulteration, which can help support industry efforts to enhance product integrity and maintain consumer trust.Review Citation - WoS: 10Citation - Scopus: 12Trends in Authentication of Edible Oils Using Vibrational Spectroscopic Techniques(Royal Soc Chemistry, 2024) Ozen, Banu; Cavdaroglu, Cagri; Tokatli, FigenThe authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry. The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards.