Journal of Food Engineering最新文献_第2页

AI-based framework to detect azo-dye adulteration in red chilli powder: ChoLevy-R optimiser for convolution neural network optimisation and validated using FTIR 基于人工智能的框架检测红辣椒粉中偶氮染料掺杂：用于卷积神经网络优化的ChoLevy-R优化器，并使用FTIR进行验证

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-27 DOI: 10.1016/j.jfoodeng.2026.113000

Dilpreet Singh Brar , Birmohan Singh , Vikas Nanda

The aim of this study is to evaluate the effect of Sudan(IV) adulteration on the antioxidant activity of red chilli powder (RCP) and to develop a multistage AI-based detection framework for identifying such adulteration within the industrial processing and supply chain of RCP. This paper proposed a novel optimiser, ChoLevy-R, that integrates chaotic dynamics with Lévy flight perturbations on the RMSprop update rule to improve the training stability of DenseNet-169 for identifying Sudan(IV) adulteration in red chilli powder (RCP). The DenseNet-169 with ChoLevy-R delivered a validation accuracy of 95.78 % and stabilised the training and validation processes. The further Grad-CAM heatmap provided insight into the model's decision-making, assigning a confidence score of 1.00 for all classes. The proposed AI framework was validated against FTIR spectroscopy with Support Vector Machine (SVM) classification. Moreover, PCA loading highlighted significant wavenumbers at 1300-1400 cm⁻¹ (–N=N–) and 1400-1600 cm⁻¹ (C=C stretches) linked to Sudan(IV) structural components. These influential wavenumbers enabled the SVM to achieve an adulteration detection accuracy of 96.55 %. Overall, the ChoLevy-R-optimised DenseNet-169 architecture, validated by FTIR spectroscopy, provides a dependable, interpretable, and scalable approach for real-time adulteration detection in RCP, facilitating robust food quality analyses in the food processing industry.

本研究的目的是评估苏丹（IV）掺假对红辣椒粉（RCP）抗氧化活性的影响，并开发一个基于人工智能的多阶段检测框架，用于在RCP的工业加工和供应链中识别这种掺假。为了提高DenseNet-169识别红辣椒粉（RCP）中苏丹（IV）掺假的训练稳定性，提出了一种新的优化器ChoLevy-R，该优化器在RMSprop更新规则上集成了混沌动力学和l飞行摄动。带有ChoLevy-R的DenseNet-169提供了95.78%的验证精度，并稳定了训练和验证过程。进一步的Grad-CAM热图提供了对模型决策的洞察，为所有类别分配了1.00的置信度分数。采用支持向量机（SVM）分类对该框架进行了FTIR光谱验证。此外，PCA加载突出了与苏丹（IV）结构部件相关的1300-1400 cm -1 （- N=N -）和1400-1600 cm -1 （C=C拉伸）的显著波数。这些有影响的波数使支持向量机的掺假检测准确率达到96.55%。总体而言，经FTIR光谱验证的cholevy - r优化的DenseNet-169体系结构为RCP中的实时掺假检测提供了可靠、可解释和可扩展的方法，促进了食品加工行业中可靠的食品质量分析。

{"title":"AI-based framework to detect azo-dye adulteration in red chilli powder: ChoLevy-R optimiser for convolution neural network optimisation and validated using FTIR","authors":"Dilpreet Singh Brar , Birmohan Singh , Vikas Nanda","doi":"10.1016/j.jfoodeng.2026.113000","DOIUrl":"10.1016/j.jfoodeng.2026.113000","url":null,"abstract":"<div><div>The aim of this study is to evaluate the effect of Sudan(IV) adulteration on the antioxidant activity of red chilli powder (RCP) and to develop a multistage AI-based detection framework for identifying such adulteration within the industrial processing and supply chain of RCP. This paper proposed a novel optimiser, ChoLevy-R, that integrates chaotic dynamics with Lévy flight perturbations on the RMSprop update rule to improve the training stability of DenseNet-169 for identifying Sudan(IV) adulteration in red chilli powder (RCP). The DenseNet-169 with ChoLevy-R delivered a validation accuracy of 95.78 % and stabilised the training and validation processes. The further Grad-CAM heatmap provided insight into the model's decision-making, assigning a confidence score of 1.00 for all classes. The proposed AI framework was validated against FTIR spectroscopy with Support Vector Machine (SVM) classification. Moreover, PCA loading highlighted significant wavenumbers at 1300-1400 cm<sup>−1</sup> (–N=N–) and 1400-1600 cm<sup>−1</sup> (C=C stretches) linked to Sudan(IV) structural components. These influential wavenumbers enabled the SVM to achieve an adulteration detection accuracy of 96.55 %. Overall, the ChoLevy-R-optimised DenseNet-169 architecture, validated by FTIR spectroscopy, provides a dependable, interpretable, and scalable approach for real-time adulteration detection in RCP, facilitating robust food quality analyses in the food processing industry.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 113000"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057406","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}

引用次数: 0

Simulation study of Escherichia coli electroporation induced by pulsed magnetic field 脉冲磁场诱导大肠杆菌电穿孔的模拟研究

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jfoodeng.2026.113013

Fei Guo, Hao Yuan, Guilin Dan

This paper introduces an innovative simulation model designed to explore, for the first time, the phenomenon of electroporation (EP) in Escherichia coli (E. coli) under the influence of a pulsed magnetic field (PMF). Initially, to ensure the viability and precision of the simulation model, a comparative validation was carried out. Compared with analytical model, simulation model yields more accurate results. Subsequently, the study investigates how two pivotal geometric parameters (cell radius and membrane thickness) impact the transmembrane voltage (TMV). The findings reveal that increasing the cell radius from 0.25 μm to 0.5 μm results in an approximate 0.47V rise in the maximum TMV, while increasing the cell membrane thickness from 24 nm to 29 nm leads to an approximate 0.16 V rise in the maximum TMV. Moreover, the maximum changes in pore density and conductivity have increased by approximately two orders of magnitude. Finally, to effectively validating its predictive capability regarding the likelihood of EP occurrence, the simulation model was expanded and compared against experimental data. In summary, this paper is dedicated to elucidating the complex dynamic behaviors and underlying mechanisms of irregular cells during the EP process, aiming to provide a solid theoretical foundation and crucial guidance for the potential application of PMF technology in the future food industry.

本文介绍了一种创新的模拟模型，旨在首次探索脉冲磁场（PMF）影响下大肠杆菌（E. coli）的电穿孔（EP）现象。首先，为了保证仿真模型的可行性和精度，进行了对比验证。与解析模型相比，仿真模型的计算结果更为准确。随后，研究了两个关键几何参数（细胞半径和膜厚度）如何影响跨膜电压（TMV）。结果表明，当细胞半径从0.25 μm增加到0.5 μm时，最大TMV上升约0.47V；当细胞膜厚度从24 nm增加到29 nm时，最大TMV上升约0.16 V。此外，孔隙密度和电导率的最大变化增加了大约两个数量级。最后，为了有效验证其对EP发生可能性的预测能力，对模拟模型进行了扩展，并与实验数据进行了比较。综上所述，本文致力于阐明不规则细胞在EP过程中的复杂动态行为及其潜在机制，旨在为PMF技术在未来食品工业中的潜在应用提供坚实的理论基础和重要的指导。

{"title":"Simulation study of Escherichia coli electroporation induced by pulsed magnetic field","authors":"Fei Guo, Hao Yuan, Guilin Dan","doi":"10.1016/j.jfoodeng.2026.113013","DOIUrl":"10.1016/j.jfoodeng.2026.113013","url":null,"abstract":"<div><div>This paper introduces an innovative simulation model designed to explore, for the first time, the phenomenon of electroporation (EP) in <em>Escherichia coli</em> (<em>E. coli</em>) under the influence of a pulsed magnetic field (PMF). Initially, to ensure the viability and precision of the simulation model, a comparative validation was carried out. Compared with analytical model, simulation model yields more accurate results. Subsequently, the study investigates how two pivotal geometric parameters (cell radius and membrane thickness) impact the transmembrane voltage (TMV). The findings reveal that increasing the cell radius from 0.25 μm to 0.5 μm results in an approximate 0.47V rise in the maximum TMV, while increasing the cell membrane thickness from 24 nm to 29 nm leads to an approximate 0.16 V rise in the maximum TMV. Moreover, the maximum changes in pore density and conductivity have increased by approximately two orders of magnitude. Finally, to effectively validating its predictive capability regarding the likelihood of EP occurrence, the simulation model was expanded and compared against experimental data. In summary, this paper is dedicated to elucidating the complex dynamic behaviors and underlying mechanisms of irregular cells during the EP process, aiming to provide a solid theoretical foundation and crucial guidance for the potential application of PMF technology in the future food industry.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 113013"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185768","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}

引用次数: 0

Coaxial 3D printing of surimi-based composite fruit–vegetable gels 基于鱼糜的复合果蔬凝胶的同轴3D打印

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-07 DOI: 10.1016/j.jfoodeng.2026.112970

Qiang Tong , Junhao Yang , Peng Wu , Yanwu Cao , Xiuping Dong , Guibing Pang

Food 3D printing enables precise structuring of food materials and shows strong potential for personalized nutrition. Yet most studies focus on single-material systems, with limited application of composite and multi-nutrient co-printing. In this study, a coaxial extrusion-based 3D printing system was established using surimi as the outer phase and spinach gel as the inner phase. The rheological properties, moisture distribution,and molding performance of various fruit and vegetable gels (spinach, pumpkin, strawberry, yam, and mango) were systematically analyzed. The results showed that the spinach gel exhibited the highest G′ value and a moderate tan δ (<0.7). Meanwhile, its T₂ peak (40–50 ms), together with high hardness and a pronounced elastic response obtained from single compression tests, indicated a well-balanced compromise between structural support and flowability.COMSOL simulations combined with printing experiments showed that, at an outer-phase printing speed of 0.05 mm/s and an inner-phase speed of 0.06 mm/s, the system can stably fabricate geometric models such as cubes, triangles, and pyramids, further confirming the excellent forming performance of the coaxial extrusion system. Measurements under different cooking methods indicated that the coaxial structure provides a clear protective effect on the nutrients in the inner phase. Taken together, the overall objective of this study was to develop a coaxial extrusion-based 3D-printed food system that achieved high shape fidelity while effectively protecting inner-phase nutrients.

食品3D打印可以实现食品材料的精确结构，并显示出个性化营养的强大潜力。然而，大多数研究都集中在单一材料系统上，复合材料和多营养素共印的应用有限。本研究以鱼糜为外相，菠菜凝胶为内相，建立基于同轴挤压的3D打印系统。系统分析了各种果蔬凝胶（菠菜、南瓜、草莓、山药、芒果）的流变特性、水分分布和成型性能。结果表明，菠菜凝胶的G′值最高，tan δ适中（<0.7）。同时，其T2峰值（40-50 ms），以及高硬度和单次压缩试验获得的明显弹性响应，表明其在结构支撑和流动性之间取得了很好的平衡。COMSOL仿真结合打印实验表明，在外相打印速度为0.05 mm/s、内相打印速度为0.06 mm/s的情况下，系统可以稳定地加工出立方体、三角形和金字塔等几何模型，进一步证实了同轴挤压系统的优异成形性能。在不同烹饪方法下的测量表明，同轴结构对内相的营养物质有明显的保护作用。综上所述，本研究的总体目标是开发一种基于同轴挤压的3d打印食品系统，该系统在有效保护内部营养物质的同时实现了高形状保真度。

{"title":"Coaxial 3D printing of surimi-based composite fruit–vegetable gels","authors":"Qiang Tong , Junhao Yang , Peng Wu , Yanwu Cao , Xiuping Dong , Guibing Pang","doi":"10.1016/j.jfoodeng.2026.112970","DOIUrl":"10.1016/j.jfoodeng.2026.112970","url":null,"abstract":"<div><div>Food 3D printing enables precise structuring of food materials and shows strong potential for personalized nutrition. Yet most studies focus on single-material systems, with limited application of composite and multi-nutrient co-printing. In this study, a coaxial extrusion-based 3D printing system was established using surimi as the outer phase and spinach gel as the inner phase. The rheological properties, moisture distribution,and molding performance of various fruit and vegetable gels (spinach, pumpkin, strawberry, yam, and mango) were systematically analyzed. The results showed that the spinach gel exhibited the highest G′ value and a moderate tan δ (<0.7). Meanwhile, its T<sub>2</sub> peak (40–50 ms), together with high hardness and a pronounced elastic response obtained from single compression tests, indicated a well-balanced compromise between structural support and flowability.COMSOL simulations combined with printing experiments showed that, at an outer-phase printing speed of 0.05 mm/s and an inner-phase speed of 0.06 mm/s, the system can stably fabricate geometric models such as cubes, triangles, and pyramids, further confirming the excellent forming performance of the coaxial extrusion system. Measurements under different cooking methods indicated that the coaxial structure provides a clear protective effect on the nutrients in the inner phase. Taken together, the overall objective of this study was to develop a coaxial extrusion-based 3D-printed food system that achieved high shape fidelity while effectively protecting inner-phase nutrients.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112970"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924287","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}

引用次数: 0

A Bayesian Gaussian Process Regression soft sensor for industrial sugar crystallization monitoring 用于工业糖结晶监测的贝叶斯高斯过程回归软传感器

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-19 DOI: 10.1016/j.jfoodeng.2026.112990

Humberto Morales , Estefania Aguirre-Zapata , Xudong Shi , Fernando di Sciascio , Adriana N. Amicarelli

Supersaturation is the primary variable in sugar crystallization, as it governs sucrose crystal growth and product quality, whereas the purity of the mother liquor is a key indicator of process efficiency. Both variables are difficult to measure online due to technological limitations. This study presents data-driven soft sensors based on Bayesian Gaussian Process Regression (BGPR) for predicting supersaturation and purity in industrial crystallization. A novel covariance matrix was introduced through an extended kernel design, enhancing the flexibility of the BGPR framework. Beyond accurate point predictions, the BGPR framework inherently provides calibrated uncertainty quantification, addressing an issue rarely discussed in the crystallization literature. The proposed soft sensors were trained and validated with real data from an industrial vacuum pan, achieving relative errors below 4% for both variables. The soft sensor requires only three routinely measured variables: temperature, magma brix, and mother liquor brix, which represents a practical advantage since no additional instrumentation is needed. For supersaturation, the uncertainty analysis yielded a Prediction Interval Coverage Probability (PICP) of 93.1%, narrow prediction intervals (MPIW = 0.1024), and a favorable CRPS of 0.0317, confirming robustness. The BGPR soft sensor was compared with five widely used approaches in soft-sensor design: Artificial Neural Networks (ANN), Long Short-Term Memory networks (LSTM), Support Vector Regression (SVR), Random Forest (RF), and Gradient Boosting Regression (GBR). Results showed that BGPR achieves competitive predictive accuracy while additionally providing reliable information on estimation uncertainty. These findings demonstrate the applicability of BGPR-based soft sensors for real-time monitoring of industrial sugar crystallization.

过饱和度是糖结晶的主要变量，因为它决定了糖晶体的生长和产品质量，而母液的纯度是过程效率的关键指标。由于技术限制，这两个变量都难以在线测量。本研究提出了基于贝叶斯高斯过程回归（BGPR）的数据驱动软传感器，用于预测工业结晶中的过饱和和纯度。通过扩展核设计引入新的协方差矩阵，增强了BGPR框架的灵活性。除了准确的点预测之外，BGPR框架本身提供了校准的不确定度量化，解决了结晶文献中很少讨论的问题。采用工业真空锅的真实数据对所提出的软传感器进行了训练和验证，两个变量的相对误差均低于4%。软传感器只需要三个常规测量变量：温度、岩浆沸度和母液沸度，这代表了一个实用的优势，因为不需要额外的仪器。对于过饱和，不确定性分析得出预测区间覆盖概率（PICP）为93.1%，预测区间较窄（MPIW = 0.1024）， CRPS为0.0317，具有较好的稳健性。将BGPR软传感器与人工神经网络（ANN）、长短期记忆网络（LSTM）、支持向量回归（SVR）、随机森林（RF）和梯度增强回归（GBR）五种软传感器设计方法进行了比较。结果表明，BGPR在获得具有竞争力的预测精度的同时，还提供了可靠的估计不确定性信息。这些发现证明了基于bgpr的软传感器在工业糖结晶实时监测中的适用性。

{"title":"A Bayesian Gaussian Process Regression soft sensor for industrial sugar crystallization monitoring","authors":"Humberto Morales , Estefania Aguirre-Zapata , Xudong Shi , Fernando di Sciascio , Adriana N. Amicarelli","doi":"10.1016/j.jfoodeng.2026.112990","DOIUrl":"10.1016/j.jfoodeng.2026.112990","url":null,"abstract":"<div><div>Supersaturation is the primary variable in sugar crystallization, as it governs sucrose crystal growth and product quality, whereas the purity of the mother liquor is a key indicator of process efficiency. Both variables are difficult to measure online due to technological limitations. This study presents data-driven soft sensors based on Bayesian Gaussian Process Regression (BGPR) for predicting supersaturation and purity in industrial crystallization. A novel covariance matrix was introduced through an extended kernel design, enhancing the flexibility of the BGPR framework. Beyond accurate point predictions, the BGPR framework inherently provides calibrated uncertainty quantification, addressing an issue rarely discussed in the crystallization literature. The proposed soft sensors were trained and validated with real data from an industrial vacuum pan, achieving relative errors below 4% for both variables. The soft sensor requires only three routinely measured variables: temperature, magma brix, and mother liquor brix, which represents a practical advantage since no additional instrumentation is needed. For supersaturation, the uncertainty analysis yielded a Prediction Interval Coverage Probability (PICP) of 93.1%, narrow prediction intervals (MPIW = 0.1024), and a favorable CRPS of 0.0317, confirming robustness. The BGPR soft sensor was compared with five widely used approaches in soft-sensor design: Artificial Neural Networks (ANN), Long Short-Term Memory networks (LSTM), Support Vector Regression (SVR), Random Forest (RF), and Gradient Boosting Regression (GBR). Results showed that BGPR achieves competitive predictive accuracy while additionally providing reliable information on estimation uncertainty. These findings demonstrate the applicability of BGPR-based soft sensors for real-time monitoring of industrial sugar crystallization.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112990"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035310","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}

引用次数: 0

Optimization, simulation, and application of stamp-based fabrication method of paper-based microfluidics device for food safety analysis with smartphone app-assisted detection 智能手机app辅助检测食品安全分析用纸微流控装置基于邮票制作方法的优化、仿真与应用

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jfoodeng.2026.113005

K. R. Jolvis Pou , Shervin Foroughi , Dhilippan M. Panneerselvam , Muthukumaran Packirisamy , Vijaya Raghavan

Over the last decade, microfluidic paper-based analytical devices (μPADs) have emerged as innovative platforms due to their cost-effectiveness, compatibility, availability, user-friendliness, and disposability. Wax printing is one of the most widely used techniques for the fabrication of μPADs. This study aims to optimize wax-printing fabrication parameters, simulate pressure and fluid dynamics, and apply the optimized conditions to create various microfluidic patterns and develop a pH indicator for food safety analysis. It also focuses on developing a smartphone app to automate the results of chromogenic reactions. The influences of process parameters, namely molten wax temperature (100–160 °C), applied pressure (0.1–6 g/mm²), stamp width (0.5–2 mm), and holding time (1–10 s) on the printing quality and wax spreading were studied. A smartphone app was developed using the Thunkable workspace, with Imagga integrated as the application programming interface platform. The results indicated that Whatman grade 4 exhibited the highest fluid velocity among the tested paper types, which is suggested as a suitable substrate for milk safety analysis. The optimal fabrication conditions for achieving high-quality wax printing with minimal wax spreading were determined to be at 115 °C, 1.575 g/mm², 0.875 mm, and 3.25 s for temperature, pressure, stamp width, and holding time, respectively. Using these optimized conditions, a paper-based pH sticker was developed to detect pH levels ranging from 1 to 10 for milk safety analysis. The color output ranged from red at pH 1 to blue at pH 10, with a greenish hue observed around the neutral pH range. These results indicated the reliability and adaptability of the device for on-site detection of food safety.

在过去的十年中，微流控纸基分析装置（μPADs）由于其成本效益，兼容性，可用性，用户友好性和一次性性而成为创新平台。蜡印是制备μ pad最广泛使用的技术之一。本研究旨在优化蜡印制造参数，模拟压力和流体动力学，并应用优化条件创建各种微流体模式，开发用于食品安全分析的pH指标。该公司还专注于开发一款智能手机应用程序，使显色反应的结果自动化。研究了熔蜡温度（100 ~ 160℃）、施加压力（0.1 ~ 6 g/mm2）、印模宽度（0.5 ~ 2 mm）、保温时间（1 ~ 10 s）等工艺参数对印刷质量和蜡扩散的影响。使用Thunkable工作空间开发了一款智能手机应用程序，并集成了Imagga作为应用程序编程接口平台。结果表明，Whatman 4级纸的流体流速最高，适合作为牛奶安全分析的底物。在温度、压力、印模宽度和保温时间分别为115°C、1.575 g/mm2、0.875 mm和3.25 s的条件下，可实现高质量的蜡印，且蜡铺铺最少。利用这些优化条件，开发了一种纸基pH贴纸，用于检测1至10的pH值，用于牛奶安全分析。输出的颜色范围从pH值1时的红色到pH值10时的蓝色，在中性pH值范围内观察到绿色色调。结果表明，该装置用于食品安全现场检测的可靠性和适应性强。

{"title":"Optimization, simulation, and application of stamp-based fabrication method of paper-based microfluidics device for food safety analysis with smartphone app-assisted detection","authors":"K. R. Jolvis Pou , Shervin Foroughi , Dhilippan M. Panneerselvam , Muthukumaran Packirisamy , Vijaya Raghavan","doi":"10.1016/j.jfoodeng.2026.113005","DOIUrl":"10.1016/j.jfoodeng.2026.113005","url":null,"abstract":"<div><div>Over the last decade, microfluidic paper-based analytical devices (μPADs) have emerged as innovative platforms due to their cost-effectiveness, compatibility, availability, user-friendliness, and disposability. Wax printing is one of the most widely used techniques for the fabrication of μPADs. This study aims to optimize wax-printing fabrication parameters, simulate pressure and fluid dynamics, and apply the optimized conditions to create various microfluidic patterns and develop a pH indicator for food safety analysis. It also focuses on developing a smartphone app to automate the results of chromogenic reactions. The influences of process parameters, namely molten wax temperature (100–160 °C), applied pressure (0.1–6 g/mm<sup>2</sup>), stamp width (0.5–2 mm), and holding time (1–10 s) on the printing quality and wax spreading were studied. A smartphone app was developed using the Thunkable workspace, with Imagga integrated as the application programming interface platform. The results indicated that Whatman grade 4 exhibited the highest fluid velocity among the tested paper types, which is suggested as a suitable substrate for milk safety analysis. The optimal fabrication conditions for achieving high-quality wax printing with minimal wax spreading were determined to be at 115 °C, 1.575 g/mm<sup>2</sup>, 0.875 mm, and 3.25 s for temperature, pressure, stamp width, and holding time, respectively. Using these optimized conditions, a paper-based pH sticker was developed to detect pH levels ranging from 1 to 10 for milk safety analysis. The color output ranged from red at pH 1 to blue at pH 10, with a greenish hue observed around the neutral pH range. These results indicated the reliability and adaptability of the device for on-site detection of food safety.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 113005"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185767","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}

引用次数: 0

In situ rheological monitoring during in vitro gastric digestion: Linking viscosity dynamics with lipid bioaccessibility in oil-in-water emulsions 体外胃消化过程中的原位流变学监测：水包油乳剂中粘度动力学与脂质生物可及性的联系

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-02-07 DOI: 10.1016/j.jfoodeng.2026.113020

Carolina Quezada , Andrés Arrué , Camila Mella , Karla Pérez , Rommy N. Zúñiga , Elizabeth Troncoso

Understanding how food viscosity evolves during digestion is essential to predict nutrient release, gastric emptying, and the functional performance of food matrices. However, conventional ex situ rheological measurements require enzymatic activity to be halted, potentially altering sample properties and limiting physiological relevance. In this study, we developed and tested a novel in vitro gastric digestion system integrated with in situ rheological monitoring (iGD-isRM) to continuously track apparent viscosity during digestion of oil-in-water (O/W) emulsions. Emulsions stabilized with either Quillaja saponin or soy lecithin and thickened with modified starch (oil-to-surfactant, O:S, ratios of 5:1 and 10:1) were characterized under simulated gastric conditions, including dynamic acidity adjustment, secretion-driven dilution, and controlled gastric emptying. Results showed a sharp decrease in apparent viscosity within the first 15 min, driven primarily by dilution by gastric secretions rather than enzymatic hydrolysis. Saponin-stabilized emulsions exhibited higher initial viscosity (2495-2771 mPa s) but dropped more rapidly to near-zero values during gastric digestion. Their smaller droplet sizes (0.19-0.34 μm) also contributed to greater free fatty acid (FFA) release during the intestinal phase (40.6-44.4%). In contrast, lecithin-stabilized emulsions displayed lower initial viscosity (551-1146 mPa s), a slower decrease toward near-zero values, larger droplet sizes (0.51-0.94 μm), and consequently lower FFA release (36.6-37.5%). Additionally, lower viscosity and surfactant concentration (O:S = 10:1) enhanced enzyme diffusion and improved lipid bioaccessibility. The iGD-isRM system enabled reliable real-time rheological measurements and revealed a clear relationship between chyme viscosity dynamics, structural disintegration, and intestinal lipolysis. This study demonstrates the potential of in situ rheological monitoring to improve our mechanistic understanding of digestion processes and to guide the rational design of structured food matrices for targeted nutrient delivery.

了解食物粘度在消化过程中如何演变，对于预测营养物质释放、胃排空和食物基质的功能性能至关重要。然而，传统的非原位流变测量需要停止酶活性，这可能会改变样品性质并限制生理相关性。在这项研究中，我们开发并测试了一种新型的体外胃消化系统，该系统集成了原位流变监测（iGD-isRM），以连续跟踪水包油（O/W）乳剂消化过程中的表观粘度。在模拟胃条件下，包括动态酸度调节、分泌驱动稀释和胃排空控制等，研究了用黄芪皂苷或大豆卵磷脂稳定、用变性淀粉（油与表面活性剂，O:S，比例为5:1和10:1）增稠的乳剂。结果显示，在最初的15分钟内，表观粘度急剧下降，主要是由胃分泌物稀释而不是酶水解引起的。皂苷稳定乳剂具有较高的初始粘度（2495-2771 mPa s），但在胃消化过程中迅速降至接近零的值。微滴尺寸较小（0.19-0.34 μm）也有助于在肠期释放更多的游离脂肪酸（FFA）（40.6-44.4%）。相比之下，卵磷脂稳定乳状液的初始粘度较低（551 ~ 1146 mPa s），接近于零的下降速度较慢，液滴尺寸较大（0.51 ~ 0.94 μm），因此FFA释放量较低（36.6 ~ 37.5%）。此外，较低的粘度和表面活性剂浓度（O:S = 10:1）增强了酶的扩散，提高了脂质的生物可及性。iGD-isRM系统实现了可靠的实时流变学测量，并揭示了食糜粘度动力学、结构解体和肠道脂肪分解之间的明确关系。这项研究证明了原位流变监测的潜力，可以提高我们对消化过程的机理理解，并指导合理设计结构化食物基质，以实现有针对性的营养输送。

{"title":"In situ rheological monitoring during in vitro gastric digestion: Linking viscosity dynamics with lipid bioaccessibility in oil-in-water emulsions","authors":"Carolina Quezada , Andrés Arrué , Camila Mella , Karla Pérez , Rommy N. Zúñiga , Elizabeth Troncoso","doi":"10.1016/j.jfoodeng.2026.113020","DOIUrl":"10.1016/j.jfoodeng.2026.113020","url":null,"abstract":"<div><div>Understanding how food viscosity evolves during digestion is essential to predict nutrient release, gastric emptying, and the functional performance of food matrices. However, conventional <em>ex situ</em> rheological measurements require enzymatic activity to be halted, potentially altering sample properties and limiting physiological relevance. In this study, we developed and tested a novel <em>in vitro</em> gastric digestion system integrated with <em>in situ</em> rheological monitoring (iGD-isRM) to continuously track apparent viscosity during digestion of oil-in-water (O/W) emulsions. Emulsions stabilized with either Quillaja saponin or soy lecithin and thickened with modified starch (oil-to-surfactant, O:S, ratios of 5:1 and 10:1) were characterized under simulated gastric conditions, including dynamic acidity adjustment, secretion-driven dilution, and controlled gastric emptying. Results showed a sharp decrease in apparent viscosity within the first 15 min, driven primarily by dilution by gastric secretions rather than enzymatic hydrolysis. Saponin-stabilized emulsions exhibited higher initial viscosity (2495-2771 mPa s) but dropped more rapidly to near-zero values during gastric digestion. Their smaller droplet sizes (0.19-0.34 μm) also contributed to greater free fatty acid (FFA) release during the intestinal phase (40.6-44.4%). In contrast, lecithin-stabilized emulsions displayed lower initial viscosity (551-1146 mPa s), a slower decrease toward near-zero values, larger droplet sizes (0.51-0.94 μm), and consequently lower FFA release (36.6-37.5%). Additionally, lower viscosity and surfactant concentration (O:S = 10:1) enhanced enzyme diffusion and improved lipid bioaccessibility. The iGD-isRM system enabled reliable real-time rheological measurements and revealed a clear relationship between chyme viscosity dynamics, structural disintegration, and intestinal lipolysis. This study demonstrates the potential of <em>in situ</em> rheological monitoring to improve our mechanistic understanding of digestion processes and to guide the rational design of structured food matrices for targeted nutrient delivery.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 113020"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185784","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}

引用次数: 0

Synergistic effects of pulsed electric field and ultrasound on microstructure and bioactive properties of fresh and old ginger juice 脉冲电场与超声对鲜老姜汁微观结构及生物活性的协同作用

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-20 DOI: 10.1016/j.jfoodeng.2026.112992

Zhong Han , Wenhao Xiao , Ji Ma , Muhammad Mohsin Raza , Xin-An Zeng , Muhammad Faisal Manzoor , Muhammad Talha Afraz

Ginger (Zingiber officinale) contains abundant bioactive compounds such as gingerols, shogaols, and phenolic antioxidants, which contribute to its nutritional and functional importance. However, efficient extraction remains limited due to incomplete cell wall disruption under single-field treatments. The combination of pulsed electric field (PEF) and ultrasound (US) offers a synergistic approach, where electroporation and acoustic cavitation collectively enhance cell permeability and mass transfer. To address this, the present study directly compares the combined PEF–US treatment on fresh versus old ginger for the first time. We developed a PEF–US coupling system (2.5 kV/cm and 450 W) and applied the combined treatment to both fresh and old ginger to evaluate its effects on juice yield and bioactive compound release. Under the optimized PEF–US conditions, both fresh and old ginger improved, with the strongest response in old ginger. Specifically, OG-2.5–450W produced 92.24 ± 0.88 % juice yield and 794.02 ± 1.15 μg GAE/mL total phenolic content (p < 0.05), together with about 79.9 % DPPH^• radical inhibition and 2315.05 ± 43.01 μg/g 6-gingerol (p < 0.05), exceeding the single-treatment and fresh-ginger groups. Structural and chemical changes supporting these outcomes were evidenced by FTIR, microscopy, and a high disintegration index (Z = 0.71 ± 0.02). Overall, the combined PEF–US treatment substantially enhances extraction efficiency and antioxidant-related bioactivity, particularly in old ginger. This innovative extraction strategy offers broader industrial relevance, providing a scalable and efficient approach for producing high–value ginger extracts suitable for functional foods, beverages, nutraceuticals, and natural health product formulations.

生姜（Zingiber officinale）含有丰富的生物活性化合物，如姜辣素、姜酚和酚类抗氧化剂，这有助于其营养和功能的重要性。然而，由于单场处理不完全破坏细胞壁，有效的提取仍然有限。脉冲电场（PEF）和超声（US）的结合提供了一种协同方法，其中电穿孔和声空化共同增强细胞的渗透性和传质。为了解决这个问题，本研究首次直接比较了新鲜生姜和老生姜的联合PEF-US治疗。本研究建立了一套功率为2.5 kV/cm、功率为450 W的PEF-US耦合系统，并对鲜姜和老姜进行了联合处理，考察其对姜汁产量和生物活性化合物释放的影响。在优化后的PEF-US条件下，鲜姜和老姜均有改善，其中老姜的反应最强。其中，OG-2.5-450W组的出汁率为92.24±0.98%，总酚含量为794.02±1.15 μg GAE/mL (p < 0.05)， DPPH•自由基抑制率为79.9%，6-姜辣素抑制率为2315.05±43.01 μg/g (p < 0.05)，均高于单一处理组和鲜姜组。FTIR、显微镜和高崩解指数（Z = 0.71±0.02）证实了支持这些结果的结构和化学变化。总的来说，PEF-US联合处理显著提高了提取效率和抗氧化相关的生物活性，特别是在老姜中。这种创新的提取策略提供了更广泛的工业相关性，为生产适用于功能性食品、饮料、营养保健品和天然保健品配方的高价值生姜提取物提供了可扩展和有效的方法。

{"title":"Synergistic effects of pulsed electric field and ultrasound on microstructure and bioactive properties of fresh and old ginger juice","authors":"Zhong Han , Wenhao Xiao , Ji Ma , Muhammad Mohsin Raza , Xin-An Zeng , Muhammad Faisal Manzoor , Muhammad Talha Afraz","doi":"10.1016/j.jfoodeng.2026.112992","DOIUrl":"10.1016/j.jfoodeng.2026.112992","url":null,"abstract":"<div><div>Ginger (<em>Zingiber officinale</em>) contains abundant bioactive compounds such as gingerols, shogaols, and phenolic antioxidants, which contribute to its nutritional and functional importance. However, efficient extraction remains limited due to incomplete cell wall disruption under single-field treatments. The combination of pulsed electric field (PEF) and ultrasound (US) offers a synergistic approach, where electroporation and acoustic cavitation collectively enhance cell permeability and mass transfer. To address this, the present study directly compares the combined PEF–US treatment on fresh versus old ginger for the first time. We developed a PEF–US coupling system (2.5 kV/cm and 450 W) and applied the combined treatment to both fresh and old ginger to evaluate its effects on juice yield and bioactive compound release. Under the optimized PEF–US conditions, both fresh and old ginger improved, with the strongest response in old ginger. Specifically, OG-2.5–450W produced 92.24 ± 0.88 % juice yield and 794.02 ± 1.15 μg GAE/mL total phenolic content (<em>p < 0.05</em>), together with about 79.9 % DPPH<sup>•</sup> radical inhibition and 2315.05 ± 43.01 μg/g 6-gingerol (<em>p < 0.05</em>), exceeding the single-treatment and fresh-ginger groups. Structural and chemical changes supporting these outcomes were evidenced by FTIR, microscopy, and a high disintegration index (Z = 0.71 ± 0.02). Overall, the combined PEF–US treatment substantially enhances extraction efficiency and antioxidant-related bioactivity, particularly in old ginger. This innovative extraction strategy offers broader industrial relevance, providing a scalable and efficient approach for producing high–value ginger extracts suitable for functional foods, beverages, nutraceuticals, and natural health product formulations.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 112992"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057404","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}

引用次数: 0

Machine learning-based predictive modelling of wine fermentation dynamics using temperature control data 使用温度控制数据的基于机器学习的葡萄酒发酵动力学预测建模

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-08 DOI: 10.1016/j.jfoodeng.2026.112969

Angel Sanchez-Roca , Emilio Jiménez-Macías , Juan-Ignacio Latorre-Biel , Juan Carlos Saenz-Díez , Mercedes Pérez de la Parte , Julio Blanco-Fernández

Wine fermentation is a complex exothermic biochemical process in which the glucose and fructose presents in the must is transformed into ethanol and carbon dioxide, owing to the action of yeasts. This experimental study evaluates the feasibility of using machine learning as a tool to model the dynamic behavior of wine fermentation, using characteristics extracted from temperature control data as the main variable of the process. The measurements were made in several fermentation tanks at a two-winery producing wine. The temperature time signals from industrial-scale fermentation tanks were acquired with a sampling period of 15 min and stored for later processing. Relevant thermal characteristics, such as temperature gradients, rates of change, and control system response patterns, were extracted from the time series obtained. Various supervised learning algorithms—including Linear Regression Models, Support Vector Machines, Regression Trees, Ensemble of Trees, and Gaussian Process Regression —were trained and validated to predict the dynamics of must density evolution. To validate the results, measurements obtained manually by the winemaker were compiled. The performance of the models was evaluated using standard statistical metrics demonstrating high predictive accuracy and robustness across different fermentation batches. The results of the analyses confirm a high linear correlation between the density obtained from the machine learning-based model and the densities obtained at the laboratory level, with coefficients of determination greater than 95 %. The proposed methodology is a useful tool for advancing predictive modeling of oenological systems, contributing to the development of intelligent control strategies and aiding decision-making in wineries.

葡萄酒发酵是一个复杂的放热生化过程，在此过程中，葡萄汁中的葡萄糖和果糖在酵母的作用下转化为乙醇和二氧化碳。本实验研究评估了使用机器学习作为建模葡萄酒发酵动态行为的工具的可行性，使用从温度控制数据中提取的特征作为该过程的主要变量。测量是在一个生产葡萄酒的双酒厂的几个发酵罐中进行的。工业规模发酵罐的温度时间信号以15分钟的采样周期获得，并存储以供后期处理。相关的热特性，如温度梯度、变化率和控制系统响应模式，从获得的时间序列中提取。各种监督学习算法——包括线性回归模型、支持向量机、回归树、树集合和高斯过程回归——经过训练和验证，以预测密度演化的动态。为了验证结果，编制了酿酒师手动获得的测量值。使用标准统计指标对模型的性能进行评估，显示出不同发酵批次的高预测准确性和鲁棒性。分析结果证实，从基于机器学习的模型中获得的密度与在实验室水平上获得的密度之间存在高度的线性相关性，决定系数大于95%。所提出的方法是推进酿酒系统预测建模的有用工具，有助于智能控制策略的发展和帮助酿酒厂的决策。

{"title":"Machine learning-based predictive modelling of wine fermentation dynamics using temperature control data","authors":"Angel Sanchez-Roca , Emilio Jiménez-Macías , Juan-Ignacio Latorre-Biel , Juan Carlos Saenz-Díez , Mercedes Pérez de la Parte , Julio Blanco-Fernández","doi":"10.1016/j.jfoodeng.2026.112969","DOIUrl":"10.1016/j.jfoodeng.2026.112969","url":null,"abstract":"<div><div>Wine fermentation is a complex exothermic biochemical process in which the glucose and fructose presents in the must is transformed into ethanol and carbon dioxide, owing to the action of yeasts. This experimental study evaluates the feasibility of using machine learning as a tool to model the dynamic behavior of wine fermentation, using characteristics extracted from temperature control data as the main variable of the process. The measurements were made in several fermentation tanks at a two-winery producing wine. The temperature time signals from industrial-scale fermentation tanks were acquired with a sampling period of 15 min and stored for later processing. Relevant thermal characteristics, such as temperature gradients, rates of change, and control system response patterns, were extracted from the time series obtained. Various supervised learning algorithms—including Linear Regression Models, Support Vector Machines, Regression Trees, Ensemble of Trees, and Gaussian Process Regression —were trained and validated to predict the dynamics of must density evolution. To validate the results, measurements obtained manually by the winemaker were compiled. The performance of the models was evaluated using standard statistical metrics demonstrating high predictive accuracy and robustness across different fermentation batches. The results of the analyses confirm a high linear correlation between the density obtained from the machine learning-based model and the densities obtained at the laboratory level, with coefficients of determination greater than 95 %. The proposed methodology is a useful tool for advancing predictive modeling of oenological systems, contributing to the development of intelligent control strategies and aiding decision-making in wineries.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112969"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975539","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}

引用次数: 0

Effect of 12-HSA concentration on the physicochemical properties, stability, and curcumin bioavailability of ultrasound-assisted enzymatically glycosylated casein-stabilized oleogel-structured emulsions 12-HSA浓度对超声辅助酶糖基化酪蛋白稳定油凝胶结构乳剂的理化性质、稳定性和姜黄素生物利用度的影响

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-06 DOI: 10.1016/j.jfoodeng.2026.112971

Yan Li , Wanlinhao Wei , Yingying Sui , Olayemi Eyituoyo Dudu , Wentao Liu , Mingrui Zhang , Jinju Cheng , Yujun Jiang

To investigate the effects of glycosylated covalent complexes and 12-hydroxystearic acid (12-HSA) on the properties of oleogel-structured high internal phase emulsions (OGHEs), this study prepared OGHEs with varying 12-HSA concentrations (0 %, 1 %, 3 %, 5 %, and 7 %) using 1.5 % sodium caseinate (SC) or conjugates of SC and carboxymethyl chitosan (SC-CMCS) as emulsifiers. A systematic evaluation was conducted on their droplet size, zeta potential, interfacial adsorbed protein content, rheological properties, stability, curcumin encapsulation efficiency, and in vitro digestion performance. Results showed that SC-CMCS-stabilized OGHEs exhibited significantly superior apparent viscosity and elastic modulus (with G′ consistently greater than G'') compared to SC-stabilized OGHEs. The elastic modulus (G′) reached its maximum at 7 % 12-HSA, accompanied by a smaller initial droplet size (8.02 ± 0.17 μm) and more uniform distribution. Confocal laser scanning microscopy (CLSM) revealed a dual-stabilization structure consisting of oil droplets and a fibrous network, while differential scanning calorimetry (DSC) confirmed enhanced thermodynamic stability. Meanwhile, SC-CMCS-stabilized OGHEs with high 12-HSA concentrations demonstrated markedly improved thermal stability, freeze-thaw stability, and lipid oxidation stability. After 28 d of storage, their particle size increased only to 11.88 ± 0.79 μm, and the curcumin encapsulation efficiency significantly rose to 95.85 ± 0.31 %, with a retention rate of 96.32 ± 0.38 % after 12 d of storage. These results indicate that the synergistic interaction between SC-CMCS and 12-HSA comprehensively enhances the functionality of OGHEs, providing theoretical support for the development of carriers for active ingredients in functional foods.

为了研究糖基化共价配合物和12-羟基硬脂酸（12-HSA）对油凝胶结构高内相乳状液（OGHEs）性能的影响，本研究以1.5%酪蛋白酸钠（SC）或SC与羧甲基壳聚糖（SC- cmcs）的偶联物为乳化剂，制备了不同浓度（0%、1%、3%、5%和7%）的OGHEs。对其液滴大小、zeta电位、界面吸附蛋白含量、流变性能、稳定性、姜黄素包封效率和体外消化性能进行了系统评价。结果表明，与sc - cmcs稳定的OGHEs相比，sc - cmcs稳定的OGHEs具有显著的表观粘度和弹性模量（G′始终大于G′）。弹性模量（G′）在7% 12-HSA时达到最大值，初始液滴尺寸较小（8.02±0.17 μm），分布更加均匀。共聚焦激光扫描显微镜（CLSM）显示了油滴和纤维网络组成的双稳定结构，差示扫描量热法（DSC）证实了热稳定性增强。同时，高12-HSA浓度的sc - cmcs稳定的OGHEs表现出明显的热稳定性、冻融稳定性和脂质氧化稳定性。贮藏28 d后，其粒径仅增大到11.88±0.79 μm，姜黄素包封率显著提高到95.85±0.31%，贮藏12 d后的保留率为96.32±0.38%。上述结果表明，SC-CMCS与12-HSA之间的协同作用全面增强了OGHEs的功能，为功能食品中活性成分载体的开发提供了理论支持。

{"title":"Effect of 12-HSA concentration on the physicochemical properties, stability, and curcumin bioavailability of ultrasound-assisted enzymatically glycosylated casein-stabilized oleogel-structured emulsions","authors":"Yan Li , Wanlinhao Wei , Yingying Sui , Olayemi Eyituoyo Dudu , Wentao Liu , Mingrui Zhang , Jinju Cheng , Yujun Jiang","doi":"10.1016/j.jfoodeng.2026.112971","DOIUrl":"10.1016/j.jfoodeng.2026.112971","url":null,"abstract":"<div><div>To investigate the effects of glycosylated covalent complexes and 12-hydroxystearic acid (12-HSA) on the properties of oleogel-structured high internal phase emulsions (OGHEs), this study prepared OGHEs with varying 12-HSA concentrations (0 %, 1 %, 3 %, 5 %, and 7 %) using 1.5 % sodium caseinate (SC) or conjugates of SC and carboxymethyl chitosan (SC-CMCS) as emulsifiers. A systematic evaluation was conducted on their droplet size, zeta potential, interfacial adsorbed protein content, rheological properties, stability, curcumin encapsulation efficiency, and in vitro digestion performance. Results showed that SC-CMCS-stabilized OGHEs exhibited significantly superior apparent viscosity and elastic modulus (with G′ consistently greater than G'') compared to SC-stabilized OGHEs. The elastic modulus (G′) reached its maximum at 7 % 12-HSA, accompanied by a smaller initial droplet size (8.02 ± 0.17 μm) and more uniform distribution. Confocal laser scanning microscopy (CLSM) revealed a dual-stabilization structure consisting of oil droplets and a fibrous network, while differential scanning calorimetry (DSC) confirmed enhanced thermodynamic stability. Meanwhile, SC-CMCS-stabilized OGHEs with high 12-HSA concentrations demonstrated markedly improved thermal stability, freeze-thaw stability, and lipid oxidation stability. After 28 d of storage, their particle size increased only to 11.88 ± 0.79 μm, and the curcumin encapsulation efficiency significantly rose to 95.85 ± 0.31 %, with a retention rate of 96.32 ± 0.38 % after 12 d of storage. These results indicate that the synergistic interaction between SC-CMCS and 12-HSA comprehensively enhances the functionality of OGHEs, providing theoretical support for the development of carriers for active ingredients in functional foods.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112971"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924274","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}

引用次数: 0

Development of a high-accuracy multilayer perceptron-based soft sensor for real-time monitoring of supersaturation and dry substance content in vacuum pan crystallization 基于多层感知器的高精度软传感器的研制，用于实时监测真空盘式结晶过程中的过饱和和干物质含量

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-06-01 Epub Date: 2026-01-06 DOI: 10.1016/j.jfoodeng.2026.112966

S.M. Petrov , D.V. Arapov , V.A. Kuritsyn , N.M. Podgornova

Sucrose crystallization is a key stage in sugar production, where control of the supersaturation coefficient (SS) and dry substance content (DS) is critical for product quality and energy efficiency. Direct online monitoring of these parameters remains challenging. This paper proposes a soft sensor based on a five-layer multilayer perceptron (MLP) for simultaneous prediction of SS and DS. The model utilizes three easily measurable input parameters: boiling point temperature of pure water, boiling point elevation (BPE), and the estimated purity of the intercrystalline solution. Training was performed using the RMSProp algorithm on an extensive dataset of experimental data. The developed model demonstrated superior accuracy, with a mean relative error of 1.0 % for SS and 0.49 % for DS, which is 2.1–7.0 times more accurate than state-of-the-art alternatives. An architecture for an automatic control system integrating the developed soft sensor for real-time closed-loop control is presented. Our results show that the proposed approach is a highly effective solution for automating and optimizing the massecuite boiling process.

蔗糖结晶是糖生产的关键阶段，其中过饱和系数（SS）和干物质含量（DS）的控制对产品质量和能源效率至关重要。直接在线监测这些参数仍然具有挑战性。本文提出了一种基于五层多层感知器（MLP）的软传感器，用于同时预测SS和DS。该模型利用三个易于测量的输入参数：纯水的沸点温度，沸点海拔（BPE），以及晶间溶液的估计纯度。使用RMSProp算法在广泛的实验数据集上进行训练。所开发的模型显示出优越的精度，SS的平均相对误差为1.0%，DS的平均相对误差为0.49%，比最先进的替代方法精确2.1-7.0倍。提出了一种集成所研制的软传感器的实时闭环自动控制系统结构。研究结果表明，该方法是实现马塞塞酱沸腾过程自动化和优化的有效方法。

{"title":"Development of a high-accuracy multilayer perceptron-based soft sensor for real-time monitoring of supersaturation and dry substance content in vacuum pan crystallization","authors":"S.M. Petrov , D.V. Arapov , V.A. Kuritsyn , N.M. Podgornova","doi":"10.1016/j.jfoodeng.2026.112966","DOIUrl":"10.1016/j.jfoodeng.2026.112966","url":null,"abstract":"<div><div>Sucrose crystallization is a key stage in sugar production, where control of the supersaturation coefficient (<em>SS</em>) and dry substance content (<em>DS</em>) is critical for product quality and energy efficiency. Direct online monitoring of these parameters remains challenging. This paper proposes a soft sensor based on a five-layer multilayer perceptron (MLP) for simultaneous prediction of <em>SS</em> and <em>DS</em>. The model utilizes three easily measurable input parameters: boiling point temperature of pure water, boiling point elevation (BPE), and the estimated purity of the intercrystalline solution. Training was performed using the RMSProp algorithm on an extensive dataset of experimental data. The developed model demonstrated superior accuracy, with a mean relative error of 1.0 % for <em>SS</em> and 0.49 % for <em>DS</em>, which is 2.1–7.0 times more accurate than state-of-the-art alternatives. An architecture for an automatic control system integrating the developed soft sensor for real-time closed-loop control is presented. Our results show that the proposed approach is a highly effective solution for automating and optimizing the massecuite boiling process.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112966"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924288","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}

引用次数: 0