Pub Date : 2026-04-01Epub Date: 2025-11-20DOI: 10.1016/j.jfoodeng.2025.112886
Chunying Jiang , Yexuan Yao , Dan Liu , Chenlu Ma , Zhiyi Zhang , Jian Wu , Wei Liu , Ting Luo , Liqiang Zou
A cyclodextrin-liposome system (CL) was developed to encapsulate dihydromyricetin (DMY), to improve its water solubility, bioavailability, and to mask its bitter taste, thus expanding its application in the food field. The dihydromyricetin-cyclodextrin-liposome (DCL) prepared by film dispersion method showed a multivesicular structure with an average particle size of 86.77 nm and an encapsulation rate of 58.4 %. The stability analyzer showed that the DCL had excellent physical stability (instability index: 0.023 ± 0.003) and exhibited good slow-release properties. QCM-D analysis of DCL effectively inhibited the binding of DMY and mucin. The electronic tongue indicated that DCL significantly masked the bitterness of DMY. In vivo pharmacokinetic studies showed that the AUC0–90min and Cmax of DMY delivered by DCL significantly increased by 5.83-fold and 3.38-fold, respectively, compared with the control group. This study provides a proof-of-concept for the development of an efficient DMY delivery strategy, which is expected to greatly contribute to its potential application in the field of functional foods.
{"title":"Dual-functional cyclodextrin-liposome system for dihydromyricetin: Bitterness masking assessed by E-tongue and enhanced bioavailability","authors":"Chunying Jiang , Yexuan Yao , Dan Liu , Chenlu Ma , Zhiyi Zhang , Jian Wu , Wei Liu , Ting Luo , Liqiang Zou","doi":"10.1016/j.jfoodeng.2025.112886","DOIUrl":"10.1016/j.jfoodeng.2025.112886","url":null,"abstract":"<div><div>A cyclodextrin-liposome system (CL) was developed to encapsulate dihydromyricetin (DMY), to improve its water solubility, bioavailability, and to mask its bitter taste, thus expanding its application in the food field. The dihydromyricetin-cyclodextrin-liposome (DCL) prepared by film dispersion method showed a multivesicular structure with an average particle size of 86.77 nm and an encapsulation rate of 58.4 %. The stability analyzer showed that the DCL had excellent physical stability (instability index: 0.023 ± 0.003) and exhibited good slow-release properties. QCM-D analysis of DCL effectively inhibited the binding of DMY and mucin. The electronic tongue indicated that DCL significantly masked the bitterness of DMY. <em>In vivo</em> pharmacokinetic studies showed that the AUC<sub>0–90min</sub> and Cmax of DMY delivered by DCL significantly increased by 5.83-fold and 3.38-fold, respectively, compared with the control group. This study provides a proof-of-concept for the development of an efficient DMY delivery strategy, which is expected to greatly contribute to its potential application in the field of functional foods.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112886"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145577982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-14DOI: 10.1016/j.jfoodeng.2025.112881
Eugénio da Piedade Edmundo Sitoe, Larissa Pereira Margalho, Patrícia Monteiro Evangelista, Max Suel Alves dos Santos, Wilma Custódio Fumo, Matheus da Silva Mourão, Alanna Vitória Rocha Eliziário, Ruann Janser Soares de Castro, Anderson S. Sant’Ana
This study evaluated the effectiveness of pre-washing coconuts with ozonated water in reducing surface contamination and the effects of ozone gas in extracted coconut water on enzymatic, microbiological, and physicochemical parameters. Coconuts subjected to pre-washing (PW) or not (NPW) were treated with ozone at 10 mg L−1, flow rate of 2 L/min, for 15–120 s. Two controls were used: positive (pasteurized water at 90 °C/1 min) and negative (fresh water). Ozonation occurred in a Philozon column (1 L), followed by storage at 5 and 15 °C. On days 0 (immediately after treatment), 1, 3, and 6, the activity of the enzymes peroxidase (POD) and polyphenoloxidase (PPO), the count of mesophiles, Enterobacteriaceae, fungi, and yeasts, as well as physicochemical parameters were evaluated. PW reduced surface microbial load by 1–2 log CFU/mL compared with NPW (p < 0.05). Ozone treatment for 120 s at 5 °C decreased POD and PPO activity by 97.5 % and 88.8 %, respectively (p < 0.05), while keeping microbial counts below 1.0 log CFU/mL throughout storage. In contrast, storage at 15 °C resulted in progressive microbial growth (>3 log CFU/mL by day 6), regardless of ozone exposure. Physicochemical parameters were also better preserved at 5 °C. Total phenolics increased by ≈ 24.3 % compared with the control, while pH and soluble solids remained stable. Color stability was maintained only in PW-120 s samples at 5 °C. Multivariate analyses (Random Forest, factor analysis, K-means clustering) consistently grouped treatments with prewashing, extended ozonation, and refrigeration (C2) as the most effective, showing superior microbial and physicochemical performance. These results demonstrate that integrating preventive sanitization, ozone, and refrigeration is a robust strategy to ensure microbial safety, enzymatic stability, and extended shelf life, supporting industrial-scale application.
{"title":"Machine learning-assisted integration to evaluate the impact of fruit pre-washing, direct ozone treatment of coconut water, and storage temperature on physicochemical quality, enzymatic and microbiological inactivation","authors":"Eugénio da Piedade Edmundo Sitoe, Larissa Pereira Margalho, Patrícia Monteiro Evangelista, Max Suel Alves dos Santos, Wilma Custódio Fumo, Matheus da Silva Mourão, Alanna Vitória Rocha Eliziário, Ruann Janser Soares de Castro, Anderson S. Sant’Ana","doi":"10.1016/j.jfoodeng.2025.112881","DOIUrl":"10.1016/j.jfoodeng.2025.112881","url":null,"abstract":"<div><div>This study evaluated the effectiveness of pre-washing coconuts with ozonated water in reducing surface contamination and the effects of ozone gas in extracted coconut water on enzymatic, microbiological, and physicochemical parameters. Coconuts subjected to pre-washing (PW) or not (NPW) were treated with ozone at 10 mg L<sup>−1</sup>, flow rate of 2 L/min, for 15–120 s. Two controls were used: positive (pasteurized water at 90 °C/1 min) and negative (fresh water). Ozonation occurred in a <em>Philozon column</em> (1 L), followed by storage at 5 and 15 °C. On days 0 (immediately after treatment), 1, 3, and 6, the activity of the enzymes peroxidase (POD) and polyphenoloxidase (PPO), the count of mesophiles, Enterobacteriaceae, fungi, and yeasts, as well as physicochemical parameters were evaluated. PW reduced surface microbial load by 1–2 log CFU/mL compared with NPW (p < 0.05). Ozone treatment for 120 s at 5 °C decreased POD and PPO activity by 97.5 % and 88.8 %, respectively (p < 0.05), while keeping microbial counts below 1.0 log CFU/mL throughout storage. In contrast, storage at 15 °C resulted in progressive microbial growth (>3 log CFU/mL by day 6), regardless of ozone exposure. Physicochemical parameters were also better preserved at 5 °C. Total phenolics increased by ≈ 24.3 % compared with the control, while pH and soluble solids remained stable. Color stability was maintained only in PW-120 s samples at 5 °C. Multivariate analyses (Random Forest, factor analysis, K-means clustering) consistently grouped treatments with prewashing, extended ozonation, and refrigeration (C2) as the most effective, showing superior microbial and physicochemical performance. These results demonstrate that integrating preventive sanitization, ozone, and refrigeration is a robust strategy to ensure microbial safety, enzymatic stability, and extended shelf life, supporting industrial-scale application.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112881"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145577910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-11DOI: 10.1016/j.jfoodeng.2025.112866
Esther Guerra-Rodríguez , Patricia Cazón , Santiago P. Aubourg , Manuel Vázquez
High pressure processing (HPP) is a promising technology for improving food safety and extending shelf life. This study examined the effects of HPP (150 MPa, 2 min) followed by frozen storage at −10, −18, or −30 °C on the texture and colour of European hake (Merluccius merluccius) over 12 months. Texture parameters (toughness and firmness) were assessed in raw and cooked samples, along with instrumental colour (L∗, a∗, b∗). Results showed that storage time generally increased toughness and firmness, though this trend stabilized or reversed after 6 months. Lower storage temperatures, particularly −30 °C, better preserved textural properties. HPP-treated fish showed higher initial toughness and firmness, suggesting enhanced structural integrity and improved texture retention during storage. Colour stability was also greater in HPP-treated samples, with reduced discoloration and better maintenance of lightness (L∗) over time. Overall, combining HPP with storage at −18 or −30 °C effectively preserves both the structural and visual quality of frozen hake, offering a promising strategy for shelf-life extension.
{"title":"Kinetic modelling of texture and colour changes in frozen fish: effect of high pressure processing as a pre-freezing treatment","authors":"Esther Guerra-Rodríguez , Patricia Cazón , Santiago P. Aubourg , Manuel Vázquez","doi":"10.1016/j.jfoodeng.2025.112866","DOIUrl":"10.1016/j.jfoodeng.2025.112866","url":null,"abstract":"<div><div>High pressure processing (HPP) is a promising technology for improving food safety and extending shelf life. This study examined the effects of HPP (150 MPa, 2 min) followed by frozen storage at −10, −18, or −30 °C on the texture and colour of European hake (<em>Merluccius merluccius</em>) over 12 months. Texture parameters (toughness and firmness) were assessed in raw and cooked samples, along with instrumental colour (L∗, a∗, b∗). Results showed that storage time generally increased toughness and firmness, though this trend stabilized or reversed after 6 months. Lower storage temperatures, particularly −30 °C, better preserved textural properties. HPP-treated fish showed higher initial toughness and firmness, suggesting enhanced structural integrity and improved texture retention during storage. Colour stability was also greater in HPP-treated samples, with reduced discoloration and better maintenance of lightness (L∗) over time. Overall, combining HPP with storage at −18 or −30 °C effectively preserves both the structural and visual quality of frozen hake, offering a promising strategy for shelf-life extension.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112866"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-13DOI: 10.1016/j.jfoodeng.2025.112867
William Yesid Díaz-Ávila , Fabrice Vaillant , Francisco Javier Castellanos-Galeano , Pablo Rodríguez
Batch vacuum frying (VF) systems often face limitations in throughput and operational efficiency, whereas conventional atmospheric frying (AF) of plantains causes excessive browning, high oil uptake, and loss of sensory and nutritional quality, especially in ripe and overripe fruits. This study aimed to design, construct, and evaluate a semi-continuous VF system suitable for processing ripened plantains. The equipment, constructed from AISI 304 stainless steel, was integrated with pneumatic actuators and a sealed airlock system (SAS) to enable continuous operation under controlled vacuum. System performance was assessed through thermal and energy analyses, as well as evaluation of the vacuum generation and condensation subsystems. Plantain at three ripening stages (RS1, RS2, and RS3) were characterized (moisture, total soluble solids (TSS), and physicochemical quality), then vacuum-fried in high-oleic palm oil (HOPO) under different temperature–time combinations. The resulting chips were analyzed (oil content, color, texture, and sensory attributes), and a multicriteria desirability model was applied to determine optimal frying conditions. Compared with AF, the VF system reduced energy consumption by 32.6 %. Optimal frying conditions were 135 °C/3 min for RS1, 135 °C/5 min for RS2, and 125 °C/7 min for RS3. Chips produced under these conditions had low oil content (≤0.16 kg oil kg−1 dry matter), crisp texture, desirable light color (ΔE∗ > 20), and high sensory acceptability. Techno-economic indicators, including Internal Rate of Return (IRR) and Net Present Value (NPV), confirmed the economic feasibility of the technology. Overall, the system demonstrated scalability and sustainability for small- and medium-sized enterprises (SMEs).
{"title":"Design and evaluation of a semi-continuous vacuum frying system to produce high-quality chips from ripened fruits: Application to plantain","authors":"William Yesid Díaz-Ávila , Fabrice Vaillant , Francisco Javier Castellanos-Galeano , Pablo Rodríguez","doi":"10.1016/j.jfoodeng.2025.112867","DOIUrl":"10.1016/j.jfoodeng.2025.112867","url":null,"abstract":"<div><div>Batch vacuum frying (VF) systems often face limitations in throughput and operational efficiency, whereas conventional atmospheric frying (AF) of plantains causes excessive browning, high oil uptake, and loss of sensory and nutritional quality, especially in ripe and overripe fruits. This study aimed to design, construct, and evaluate a semi-continuous VF system suitable for processing ripened plantains. The equipment, constructed from AISI 304 stainless steel, was integrated with pneumatic actuators and a sealed airlock system (SAS) to enable continuous operation under controlled vacuum. System performance was assessed through thermal and energy analyses, as well as evaluation of the vacuum generation and condensation subsystems. Plantain at three ripening stages (RS1, RS2, and RS3) were characterized (moisture, total soluble solids (TSS), and physicochemical quality), then vacuum-fried in high-oleic palm oil (HOPO) under different temperature–time combinations. The resulting chips were analyzed (oil content, color, texture, and sensory attributes), and a multicriteria desirability model was applied to determine optimal frying conditions. Compared with AF, the VF system reduced energy consumption by 32.6 %. Optimal frying conditions were 135 °C/3 min for RS1, 135 °C/5 min for RS2, and 125 °C/7 min for RS3. Chips produced under these conditions had low oil content (≤0.16 kg oil kg<sup>−1</sup> dry matter), crisp texture, desirable light color (ΔE∗ > 20), and high sensory acceptability. Techno-economic indicators, including Internal Rate of Return (IRR) and Net Present Value (NPV), confirmed the economic feasibility of the technology. Overall, the system demonstrated scalability and sustainability for small- and medium-sized enterprises (SMEs).</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112867"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-08DOI: 10.1016/j.jfoodeng.2025.112863
Yifan Qin , Xiao Dong Chen , Haixuan Sun , Aibing Yu , Yingwen Wu , Jie Xiao
Existing 1D digestion models have difficulty in accurately capturing in vivo digestive behavior due to the over-simplification of intestinal physiological characteristics. 3D Computational Fluid Dynamics (CFD) models, though capable of describing those characteristics, are computationally demanding. This study presents an efficient methodology for developing a physiologically sound 1D intestinal digestion model by combining 3D CFD simulations and data-driven techniques. The modelling workflow was demonstrated through an example incorporating three Key Physiological Factors (KPFs): duodenal posture, gastric acid concentration and peristaltic velocity. Firstly, in silico experiments were designed by hybrid sampling of the design space of KPFs, and carried out by solving 3D CFD models considering KPFs. The sequential outputs generated were then coupled into a 1D intestinal digestion model (that neglects KPFs) via a Recurrent Neural Network (RNN). The new 1D model was further integrated with an established blood glucose-insulin interaction model to build a physiologically based glycemic prediction system. The quantitative influences of physiological variations on digestion rate and blood glucose evolution were systematically explored, highlighting the significance of the proposed modelling strategy.
{"title":"How physiology influences starch digestion: An integrated Computational Fluid Dynamics-machine learning development framework for an intestinal lumped parameter model","authors":"Yifan Qin , Xiao Dong Chen , Haixuan Sun , Aibing Yu , Yingwen Wu , Jie Xiao","doi":"10.1016/j.jfoodeng.2025.112863","DOIUrl":"10.1016/j.jfoodeng.2025.112863","url":null,"abstract":"<div><div>Existing 1D digestion models have difficulty in accurately capturing <em>in vivo</em> digestive behavior due to the over-simplification of intestinal physiological characteristics. 3D Computational Fluid Dynamics (CFD) models, though capable of describing those characteristics, are computationally demanding. This study presents an efficient methodology for developing a physiologically sound 1D intestinal digestion model by combining 3D CFD simulations and data-driven techniques. The modelling workflow was demonstrated through an example incorporating three Key Physiological Factors (KPFs): duodenal posture, gastric acid concentration and peristaltic velocity. Firstly, in silico experiments were designed by hybrid sampling of the design space of KPFs, and carried out by solving 3D CFD models considering KPFs. The sequential outputs generated were then coupled into a 1D intestinal digestion model (that neglects KPFs) via a Recurrent Neural Network (RNN). The new 1D model was further integrated with an established blood glucose-insulin interaction model to build a physiologically based glycemic prediction system. The quantitative influences of physiological variations on digestion rate and blood glucose evolution were systematically explored, highlighting the significance of the proposed modelling strategy.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112863"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-11DOI: 10.1016/j.jfoodeng.2025.112861
Gwenaëlle Verbrugghe , Hayat Benkhelifa , Steven Duret , Halima Morin , Sandra Martin-Latil , Fatou-Toutie Ndoye
This study focuses on frozen raspberries, a product highly susceptible to freeze-induced damage yet widely used in the food industry, by examining the combined effects of freezing and frozen storage conditions on their microstructure and quality. Two freezing rates (fast and slow) and three storage temperatures (−5 °C, −12 °C, and −18 °C) were evaluated over a six-month storage period. Prior to freezing, the raspberries’ cellular structure and thermophysical properties were characterized. Throughout freezing and storage, microstructural changes were monitored using X-ray micro-computed tomography. After thawing, texture and drip loss were measured to assess quality deterioration. The results demonstrated that fast freezing better preserves raspberry microstructure, inducing fewer structural changes compared to slow freezing. Conversely, higher storage temperatures promoted recrystallization, resulting in increased structural degradation. The growth of larger ice crystals caused more extensive damage to cell walls and vacuoles, leading to greater drip loss, reduced turgidity, and diminished firmness upon thawing. Importantly, the study highlights a synergistic effect between freezing rate and storage temperature on microstructural evolution. Ice crystals in slowly frozen raspberries were more prone to recrystallization regardless of storage temperature, whereas fast freezing combined with lower storage temperatures effectively maintained smaller ice crystal sizes and better structural integrity. Overall, these findings underscore the critical role of controlling both freezing and storage parameters to minimize microstructural alterations and ensure optimal quality of frozen raspberries throughout the cold chain, for both consumers and industry stakeholders.
{"title":"Insight into the relationships between microstructure development and quality changes in frozen stored raspberries","authors":"Gwenaëlle Verbrugghe , Hayat Benkhelifa , Steven Duret , Halima Morin , Sandra Martin-Latil , Fatou-Toutie Ndoye","doi":"10.1016/j.jfoodeng.2025.112861","DOIUrl":"10.1016/j.jfoodeng.2025.112861","url":null,"abstract":"<div><div>This study focuses on frozen raspberries, a product highly susceptible to freeze-induced damage yet widely used in the food industry, by examining the combined effects of freezing and frozen storage conditions on their microstructure and quality. Two freezing rates (fast and slow) and three storage temperatures (−5 °C, −12 °C, and −18 °C) were evaluated over a six-month storage period. Prior to freezing, the raspberries’ cellular structure and thermophysical properties were characterized. Throughout freezing and storage, microstructural changes were monitored using X-ray micro-computed tomography. After thawing, texture and drip loss were measured to assess quality deterioration. The results demonstrated that fast freezing better preserves raspberry microstructure, inducing fewer structural changes compared to slow freezing. Conversely, higher storage temperatures promoted recrystallization, resulting in increased structural degradation. The growth of larger ice crystals caused more extensive damage to cell walls and vacuoles, leading to greater drip loss, reduced turgidity, and diminished firmness upon thawing. Importantly, the study highlights a synergistic effect between freezing rate and storage temperature on microstructural evolution. Ice crystals in slowly frozen raspberries were more prone to recrystallization regardless of storage temperature, whereas fast freezing combined with lower storage temperatures effectively maintained smaller ice crystal sizes and better structural integrity. Overall, these findings underscore the critical role of controlling both freezing and storage parameters to minimize microstructural alterations and ensure optimal quality of frozen raspberries throughout the cold chain, for both consumers and industry stakeholders.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112861"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145518992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The detection of harmful drug molecules, such as chloramphenicol (CAP), is crucial for addressing the growing concerns about the adverse effects of antibiotics entering the human body through food and environmental sources. In this study, we present an enhanced electrochemical detection method using a novel perovskite composite material: Zinc Titanate (ZTO) nanoparticles embedded with carbon nanofibers (CNF). The structural and compositional properties of the ZTO@CNF nanomaterial were characterized using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy-Dispersive X-ray Spectroscopy (EDS), Raman Spectroscopy, X-ray Photoelectron Spectroscopy (XPS), Cyclic Voltammetry (CV), and Electrochemical Impedance Spectroscopy (EIS). These techniques provided a comprehensive understanding of the material's composition and structure. The ZTO@CNF composite was integrated into a screen-printed carbon electrode (SPCE) for electrochemical CAP detection. Furthermore, DPV is used to analyze the sensitivity of the fabricated sensor. The sensor exhibited remarkable sensitivity, with a wide linear detection range from 0.02 to 3017.61 μM and a low detection limit of 0.0205 μM. The sensor's applicability was demonstrated through the successful analysis of spiked milk and tap water samples, highlighting its potential for real-world use in monitoring antibiotic contamination in food and environmental sources, thus contributing to public health protection. This study introduces a scalable and cost-effective platform for on-site detection of CAP, with promising prospects for real-world deployment.
{"title":"ZnTiO3-CNF detector for sensitive detection of foodborne antibiotics","authors":"Nirmal Kumar Sakthivel , Perumal Murugesan , Hisham S.M. Abd-Rabboh , Mani Govindasamy","doi":"10.1016/j.jfoodeng.2025.112894","DOIUrl":"10.1016/j.jfoodeng.2025.112894","url":null,"abstract":"<div><div>The detection of harmful drug molecules, such as chloramphenicol (CAP), is crucial for addressing the growing concerns about the adverse effects of antibiotics entering the human body through food and environmental sources. In this study, we present an enhanced electrochemical detection method using a novel perovskite composite material: Zinc Titanate (ZTO) nanoparticles embedded with carbon nanofibers (CNF). The structural and compositional properties of the ZTO@CNF nanomaterial were characterized using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy-Dispersive X-ray Spectroscopy (EDS), Raman Spectroscopy, X-ray Photoelectron Spectroscopy (XPS), Cyclic Voltammetry (CV), and Electrochemical Impedance Spectroscopy (EIS). These techniques provided a comprehensive understanding of the material's composition and structure. The ZTO@CNF composite was integrated into a screen-printed carbon electrode (SPCE) for electrochemical CAP detection. Furthermore, DPV is used to analyze the sensitivity of the fabricated sensor. The sensor exhibited remarkable sensitivity, with a wide linear detection range from 0.02 to 3017.61 μM and a low detection limit of 0.0205 μM. The sensor's applicability was demonstrated through the successful analysis of spiked milk and tap water samples, highlighting its potential for real-world use in monitoring antibiotic contamination in food and environmental sources, thus contributing to public health protection. This study introduces a scalable and cost-effective platform for on-site detection of CAP, with promising prospects for real-world deployment.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112894"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145615901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-11-20DOI: 10.1016/j.jfoodeng.2025.112891
Shih-Hao Chou, Cheng-Yu Huang
We performed a systematic experimental study of axial segregation in a horizontal rotating drum by varying two key parameters, the filling degree and the composition of a bidisperse granular mixture. Experimental images were processed to capture the spatial distribution of bicolor particle concentrations in the system, from which we quantified the segregation index, dynamic angle of repose, bandwidth, and axial concentration profiles. The results demonstrate that both filling degree and mixture composition exert a strong influence on segregation behavior. At low filling degrees and high small particle fractions, sharply defined axial bands form with segregation indices approaching unity and comparatively wide bandwidths. When filling degrees are higher or small particle fractions are lower, the emerging band structures are weak or fail to appear. An ultrathin boundary layer was also observed, with a composition enriched in either small or large particles depending on conditions, which can influence the segregation pattern. By mapping our findings onto a filling degree versus small particle fraction phase diagram effectively predicts and directly identifies whether the system will exhibit uniform mixing, a single central band or a stepped alternating band pattern.
{"title":"Study of axial segregation dynamics in size-bidisperse granular flows within a horizontal rotating drum","authors":"Shih-Hao Chou, Cheng-Yu Huang","doi":"10.1016/j.jfoodeng.2025.112891","DOIUrl":"10.1016/j.jfoodeng.2025.112891","url":null,"abstract":"<div><div>We performed a systematic experimental study of axial segregation in a horizontal rotating drum by varying two key parameters, the filling degree and the composition of a bidisperse granular mixture. Experimental images were processed to capture the spatial distribution of bicolor particle concentrations in the system, from which we quantified the segregation index, dynamic angle of repose, bandwidth, and axial concentration profiles. The results demonstrate that both filling degree and mixture composition exert a strong influence on segregation behavior. At low filling degrees and high small particle fractions, sharply defined axial bands form with segregation indices approaching unity and comparatively wide bandwidths. When filling degrees are higher or small particle fractions are lower, the emerging band structures are weak or fail to appear. An ultrathin boundary layer was also observed, with a composition enriched in either small or large particles depending on conditions, which can influence the segregation pattern. By mapping our findings onto a filling degree versus small particle fraction phase diagram effectively predicts and directly identifies whether the system will exhibit uniform mixing, a single central band or a stepped alternating band pattern.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"408 ","pages":"Article 112891"},"PeriodicalIF":5.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145615907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-12-04DOI: 10.1016/j.jfoodeng.2025.112902
Seunghun Lee , Sungmin Jeong , Suyong Lee
Hyperspectral imaging combined with artificial intelligence was applied to identify eight hydrocolloids representing diverse origins and structures relevant to food applications and to predict their viscosities under various processing conditions. Distinct hyperspectral patterns were observed among the hydrocolloids, with arabic gum and xanthan gum exhibiting high signal intensity due to their complex structures. Principal component analysis reduced the hyperspectral data to two components explaining 90.89 % of the total variance, enabling clear separation of the hydrocolloids into eight clusters. Convolutional neural network classification achieved accuracies above 96 %, with precision, recall, and F1-scores exceeding 0.95. Viscosities were experimentally measured at multiple concentrations (0.2–2.0 %, w/v) and temperatures (30–90 °C), and used to train three ensemble machine learning algorithms (XGBoost, Random Forest, and AdaBoost) for rapid viscosity prediction from hyperspectral features. XGBoost and Random Forest achieved superior performance with R2 values of 0.9969 and 0.9968 and root mean square errors of 0.0085 and 0.0087, respectively, while the AdaBoost model showed lower performance (R2 = 0.9256 and root mean square error = 0.0421). These findings demonstrate that hyperspectral imaging with artificial intelligence enables rapid and non-destructive hydrocolloid identification and accurate viscosity prediction, with dimensionality reduction enhancing prediction performance. This approach offers practical benefits for food formulation, process control, and quality improvement of hydrocolloid-containing products.
应用高光谱成像与人工智能相结合的方法，鉴定了与食品应用相关的8种不同来源和结构的水胶体，并预测了它们在不同加工条件下的粘度。在水胶体中观察到明显的高光谱模式，阿拉伯胶和黄原胶由于其复杂的结构而表现出高信号强度。主成分分析将高光谱数据简化为两个分量，解释了总方差的90.89%，从而将水胶体清晰地划分为8个簇。卷积神经网络分类准确率达到96%以上，准确率、查全率、f1得分均超过0.95。粘度在多种浓度（0.2 - 2.0%,w/v）和温度（30-90°C）下进行实验测量，并用于训练三种集成机器学习算法（XGBoost， Random Forest和AdaBoost），以便从高光谱特征中快速预测粘度。XGBoost和Random Forest模型表现较好，R2分别为0.9969和0.9968，均方根误差分别为0.0085和0.0087，而AdaBoost模型表现较差，R2 = 0.9256，均方根误差为0.0421。这些发现表明，人工智能的高光谱成像能够快速、无损地识别水胶体并准确预测粘度，而降维可以提高预测性能。这种方法为食品配方、工艺控制和含水胶体产品的质量改进提供了实际的好处。
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Pub Date : 2026-04-01Epub Date: 2025-11-28DOI: 10.1016/j.jfoodeng.2025.112899
Amir Hosseinvand , Mahdi Ghafourivayghan
Food microbiology is critical to global health, especially given the substantial public health risks posed by foodborne illnesses. Rapid and accurate detection of pathogenic microorganisms in food is vital for ensuring safety and preventing outbreaks. This study presents a comprehensive review of biosensor-based approaches for identifying foodborne pathogens. Conventional detection methods including microbial culturing, colony counting, immunoassays, and PCR are often time consuming, requiring hours to days for results. These limitations have spurred the development of faster, more efficient alternatives. Biosensors, with their superior sensitivity and rapid response times, represent a transformative advancement in pathogen detection. By leveraging biorecognition elements and signal transduction mechanisms, biosensors enable real-time monitoring, significantly reducing analysis time while maintaining high accuracy. Their integration into food safety systems promises to enhance early contamination detection, improving both consumer protection and regulatory compliance. This review highlights the potential of biosensor technologies to revolutionize food microbiology diagnostics, addressing the urgent need for rapid, reliable pathogen screening in the food industry.
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