Yazar "Yilmaz, Mustafa Tahsin" seçeneğine göre listele

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    Ammonia-responsive thermoplastic starch films incorporated with gallic acid-cobalt metal-organic frameworks (GA/Co-MOF) for real-time tracking of shrimp freshness
    (Elsevier, 2026) Yilmaz, Mustafa Tahsin; Parlak, Mahmut Ekrem; Uzuner, Kubra; Yildiz, Zehra Irem; Dundar, Ayse Neslihan; Sahin, Oya Irmak; Saricaoglu, Furkan Turker
    Developing ammonia-responsive biopolymer-based smart films with strong mechanical properties and reliable visual freshness indicators is a significant research focus. Integrating cobalt-based metal-organic frameworks (CoMOF) into a polymer matrix is a contemporary method for manufacturing intelligent packaging materials, primarily due to their rapid responsiveness to ammonia. This study successfully synthesized an ammonia-sensitive Co-MOF by using gallic acid as the ligand (GA/Co-MOF) and integrated them into a thermoplastic starch (TPS) matrix, creating high-performance, multifunctional TPS-based intelligent active composite films (TPS/Co-MOF). FTIR analysis indicates that cobalt exhibits a strong affinity for the carboxy and hydroxy groups of gallic acid, leading to the formation of spherical aggregates, which have diameters of between 600 and 1000 nm, as visualized using SEM. A thorough analysis assessed the impact of GA/Co-MOF on the films' physicochemical, water barrier, and morphological properties, as well as their color, optical, UV-blocking, and material characteristics (thermal, crystallographic, molecular, and mechanical) and ammonia-responsive performances. The GA/Co-MOF nanofillers were uniformly dispersed in the TPS matrix, significantly enhancing tensile strength (from 4.35 to 5.29 MPa), elongation at break (from 122.97 to 153.7 %), puncture force (from 612.78 to 1069.96 g), puncture deformation (from 3.78 to 4.87 mm), water resistance, and UV-blocking abilities. Additionally, the films exhibited improved thermal stability, toughness, elasticity, and ammonia-sensitive discoloration properties. Notably, the TPS/Co-MOF films enabled effective real-time visual monitoring of shrimp freshness, with a faster color response time than existing nanocomposite films, making them promising for active and intelligent food packaging. These findings highlight the significant potential of TPS/Co-MOF films to meet the demands of safe packaging solutions with superior mechanical performance and freshness monitoring.
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    Application of high-pressure homogenization-assisted pH-shift to enhance techno-functional and interfacial properties of lentil protein isolate
    (Elsevier Sci Ltd, 2024) Parlak, Mahmut Ekrem; Saricaoglu, Furkan Tuerker; Yilmaz, Mustafa Tahsin
    High-pressure homogenization (HPH) is a promising physical non-thermal approach to improve protein technofunctionality. This study aims to examine the effects of HPH on the lentil proteins through the perspective of the interfacial adsorption mechanism. The impact of HPH treatment on lentil protein isolate (LPI) at varying pressure levels (0-150 MPa) was determined using several analytical techniques, including SDS-PAGE, FTIR, solubility, and techno-functional properties (foaming and emulsifying properties), alongside analyses of interfacial tension and interfacial shear rheology at the o/w and a/w interfaces for two pH values (2.0 and 4.5). Results reveal that HPH treatment up to 100 MPa effectively unfolds lentil proteins by disrupting disulfide-bonded subunits into lower molecular weight fractions and unfolding highly-ordered secondary structures into random coils. LPI's capacity to produce emulsions and foams was found to be enhanced concurrently with these physicochemical changes, particularly at pressures up to 50 MPa. The findings aligned with the interfacial tension and shear rheology analyses, which show that proteins can form interfacial viscoelastic films on both o/w and a/w interfaces. Furthermore, the interfacial behavior of LPI and the effect of HPH on the interfacial behavior were found to be pH-dependent. The lower interfacial tension and the higher interfacial viscoelastic moduli (G ' and G '') were recorded at 50 MPa and 0 MPa at pH 2.0 and 4.5, respectively. These results stated that the effects of the HPH on the technofunctionality of LPI can be further enlightened by investigating the interfacial adsorption kinetics.
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    Deep eutectic solvent as plasticizing agent for the zein based films
    (Elsevier, 2024) Yilmaz, Mustafa Tahsin; Kul, Ebubekir; Saricaoglu, Furkan Turker; Odabas, Halil Ibrahim; Taylan, Osman; Dertli, Enes
    This study explores, the impacts of incorporating of deep eutectic solvent (DES) as plasticizer on the characteristics of zein films. Investigation focused on examining the mechanical, thermal, surface, and microstructural properties of zein films that were plasticized using DES. The findings of the study revealed that by adding DES to zein films, there was an observed improvement in transparency. Additionally, it was observed that up to a 20% addition of DES led to a reduction in water vapor permeability (WVP). However, beyond this level, the WVP increased as the surface hydrophobicity decreased. The films that were plasticized with DES showed higher tensile and burst strength values than control. However, there was a decrease in the elongation at break and burst distance, except for the film containing 30% DES. The addition of DES as plasticizer resulted in smoother surface morphology compared to the control, and all films revealed homogeneous and non -porous surface and crosssection microstructure. The films plasticized with DES displayed three different thermal degradation temperatures resulting in higher thermal stability. The FT-IR spectrum of films showed similar backbone structure including Amide I, II and III bands. However, 5% DES plasticized film showed different secondary structural peaks of Amide I band due to lower alpha-helix and higher beta-sheet and random coil content. The findings of this investigation indicate that the employment of DES as plasticizer in biodegradable polymer films can yield enhanced mechanical and barrier characteristics compared to conventional plasticizers, thus demonstrating its potential for effective use.
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    Explainable AI unlocks temperature-driven oscillatory viscoelastic transitions in sesame protein isolate during integrated heating-cooling cycles
    (Elsevier Sci Ltd, 2025) Yilmaz, Mustafa Tahsin; Alkabaa, Abdulaziz S.; Saricaoglu, Furkan Turker; Milyani, Ahmad H.; Gul, Osman; Parlak, Mahmut Ekrem; Hassanein, Wael S.
    The temperature-dependent viscoelastic behavior of sesame protein isolate (SePI) gels was investigated across integrated heating-cooling cycles (25-95 degrees C) under oscillatory rheometry (10 % strain, 0.1 Hz). Experiments were performed across a range of treatment conditions, including pressure levels of 0, 50, and 100 MPa and ionic concentrations (IC) of 0-200 mM. Empirical results showed that storage modulus (G ') consistently exceeded loss modulus (G ''), particularly during cooling, indicating elastic-dominant gelation. Application of pressure and ionic concentration (IC) treatments enhanced viscoelastic recovery, yet condition-specific nonlinear trends in G ' and G '' responses-particularly across temperature cycles-and associated hysteresis effects remained difficult to isolate from aggregated empirical trends alone. To address these limitations, stacking ensemble mimicry models were developed and explainable AI (XAI) methods, including SHAP values, partial dependence plots (PDPs), and variance-based sensitivity indices (VBSIs), were employed. The XGBMeta-Stacker and LGBMMeta-Stacker models predicted G ' and G '' with high accuracy, achieving R2 values above 0.94 for both training and testing sets. Despite variability and outliers in the temperature sweep dataset, both ensemble models showed strong predictive alignment with actual values, highlighting the robustness of the stacking strategy in complex rheological modeling. XAI analyses uncovered temperature-driven oscillatory viscoelastic transitions-repeated patterns unlikely to be captured when heating and cooling cycles are examined separately, particularly between 25 and 75 degrees C-highlighting the necessity of integrated cycle analysis to reveal such behavior and enabling quantitative ranking of temperature, pressure, and IC influences across the domain. Temperature emerged as the dominant driver of G ' and G '' transitions, while pressure exerted stronger effects on viscous behavior under high-intensity conditions. Integrated interpretation of SHAP, PDP, and VBSI analyses revealed condition-dependent feature dynamics and interaction effects, offering mechanistic insights inaccessible through traditional methods alone.
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    Explainable AI-driven evaluation of plant protein rheology using tree-based and Gaussian process machine learning models
    (Elsevier, 2025) Yilmaz, Mustafa Tahsin; Badurayq, Salman; Polat, Kemal; Milyani, Ahmad H.; Alkabaa, Abdulaziz S.; Gul, Osman; Saricaoglu, Furkan Turker
    In this study, we conducted a comparative analysis of the explainability of Decision Tree Regressor (DTR) and Gaussian Process Regressor (GPR) models in predicting the shear stress and viscosity of sesame protein isolate (SPI) systems, employing explainable machine learning (EML) techniques to elucidate complex, nonlinear relationships among processing parameters. SPI samples were processed across pressure levels ranging from 0 to 100 MPa and ion concentration (IC) values from 0 to 200 mM. DTR model accurately predicted shear stress (R2 = 0.999), while a GPR model achieved high performance for viscosity prediction (R2 = 0.9925). Formally, the modeling task is framed as learning a predicting mapping function f : Rp -> R, where x is an element of Rp denotes the vector of predictors (pressure, IC, shear rate) and y is an element of R is the target variable (shear stress or viscosity), by minimizing a loss function such as mean squared error. Interpretation of model predictions using SHapley Additive exPlanations (SHAP), permutation importance, and partial dependence analysis revealed that pressure and IC are the most influential factors affecting shear stress and viscosity, with pressure inducing protein conformational changes that impact rheological properties. The shear rate exhibited a lesser direct impact within the systems examined. Partial Dependence Plots (PDPs) from the DTR model revealed strong, nearly linear positive relationships between pressure and shear stress, while the GPR model depicted more nuanced responses, highlighting the models' differing sensitivities. Variance-Based Sensitivity Indices (VBSIs) further quantified these influences, with pressure and IC showing higher sensitivity scores in the DTR model compared to the GPR model. Permutation importance and SHAP interaction analyses corroborated these results, emphasizing the dominant role of pressure and IC, both independently and interactively, in determining shear stress. In contrast, viscosity predictions were influenced by more distributed and subtle interactions among all features. Employing explainable machine learning techniques enables a comprehensive understanding of feature relevance in complex, nonlinear rheological systems, facilitating the elucidation of viscosity development in sesame protein systems through rheological indices. This approach ensures no bias toward formulation composition and applied pressure, offering valuable insights for optimizing formulation and processing conditions in food applications to enhance the functional properties of SPI-based products.
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    Gelatin extraction from chicken skin by conventional and Ohmic heating methods and comparison with commercial halal gelatins
    (Elsevier Sci Ltd, 2024) Isik, Cigdem; Parlak, Mahmut Ekrem; Demirel, Fatma Tuba Kirac; Odabas, Halil Ibrahim; Dagdelen, Adnan Fatih; Yilmaz, Mustafa Tahsin; Saricaoglu, Furkan Turker
    Gelatin extraction from chicken skins using ohmic heating (OH) is a promising application in the food industry. In this study, the effects of OH parameters (electric field (5, 10, 15, and 20 V/cm) and extraction time (1, 3, and 5 h)) on the extraction yield, physicochemical, functional, rheological, thermal, and microstructural properties of chicken skin gelatin were investigated, as well as comparison with conventional extraction and commercial halal gelatins. Chicken skin gelatins obtained with OH-assisted extraction showed higher ash content resulting in more turbidity than commercial gelatins. OH parameters significantly increased the gelatin yield, and 1 h of OH treatment revealed the highest gel strength amongst the electric field applications, conventional extracted, and bovine gelatin. The melting and gelation temperatures of chicken skin gelatins were higher than bovine gelatin and OH treatment increased the thermal stability. The amino acid composition significantly changed with OH treatment, and total imino acid content, relating to the gelation properties, increased. Functional properties, water and oil binding, emulsifying, and foaming, of chicken skin gelatin were significantly higher than commercial gelatins, and OH treatment significantly increased these properties. Overall, OH extraction of gelatin from chicken skins could be a better option for less extraction time, higher extraction yield, better functionality, and higher thermal stability compared to conventional extraction. It was concluded that chicken skin gelatins extracted using OH have properties that can be an alternative to commercial gelatins, but further purification processes are required.