Journal of Food Engineering最新文献_第6页

A multiscale approach to ultrasound-assisted extraction of tea polyphenols: machine learning process optimization, kinetic modeling, and molecular dynamics simulation 超声辅助提取茶多酚的多尺度方法：机器学习过程优化、动力学建模和分子动力学模拟

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-29 DOI: 10.1016/j.jfoodeng.2025.112958

Hassan A. Saeed , Andriamamonjy H. Rosa , Balarabe B. Ismail , Wenjun Wang , Donghong Liu

The efficient recovery of bioactive compounds is a critical challenge demanding advanced process optimization and deep mechanistic understanding. This study presents a multiscale framework for optimizing ultrasound-assisted extraction (UAE) of polyphenols in scientifically uncharacterized Huangshan–Chaoqing (HC) green tea, used as a model system. Machine learning (ML) approaches, such as Extreme Gradient Boosting (XGboost), Random Forest (RF), and Artificial Neural Network (ANN) and kinetic models were combined with molecular dynamics (MD) simulations to optimize UAE and explore the mechanisms involved. Among the ML models, ANN and XGBoost demonstrated superior accuracy in predicting optimal total phenolic content (TPC) (R² = 0.97) and DPPH radical scavenging activity (R² = 0.99), identifying power density as an essential process parameter. Moreover, the predicted optimal conditions were experimentally validated, with an absolute average deviation of 3.92 mgGAE/100g and 0.25 mgTrolox/100g for TPC and DPPH, respectively. Kinetic studies showed that a phenomenological model accurately described the two-stage extraction process involving an initial rapid rate followed by a slower rate until equilibrium. SEM revealed severe cellular disruption and enhanced porosity under UAE. MD simulations driven by experimentally measured bulk temperatures from UAE demonstrated that thermal effects enhance catechin diffusivity by increasing molecular flexibility and reducing intermolecular hydrogen bonds. The diffusion coefficients calculated from the MD simulations agreed with those derived from the experimental kinetic data, validating the computational model. This integrated research provides a multiscale understanding of the UAE process, establishing a rational framework for designing and intensifying the extraction of high-value natural products.

生物活性化合物的有效回收是一个关键的挑战，需要先进的工艺优化和深入的机制理解。本研究建立了超声辅助提取黄潮清绿茶中多酚的多尺度优化框架，并将其作为模型体系。机器学习（ML）方法，如极端梯度增强（XGboost）、随机森林（RF）、人工神经网络（ANN）和动力学模型与分子动力学（MD）模拟相结合，以优化阿联酋并探索其中的机制。在ML模型中，ANN和XGBoost在预测最佳总酚含量（TPC）（R2 = 0.97）和DPPH自由基清除活性（R2 = 0.99）方面表现出更高的准确性，并确定功率密度是一个重要的过程参数。此外，实验验证了预测的最佳条件，TPC和DPPH的绝对平均偏差分别为3.92 mgggae /100g和0.25 mgTrolox/100g。动力学研究表明，一个现象学模型准确地描述了两阶段的萃取过程，即最初的快速萃取，随后的缓慢萃取直到平衡。扫描电镜显示，在UAE作用下，细胞破坏严重，孔隙度增强。由实验测量的阿联酋体温度驱动的MD模拟表明，热效应通过增加分子柔韧性和减少分子间氢键来增强儿茶素的扩散性。MD模拟计算的扩散系数与实验动力学数据吻合，验证了计算模型的正确性。这项综合研究提供了对阿联酋过程的多尺度理解，为设计和加强高价值天然产品的提取建立了合理的框架。

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引用次数: 0

A three-phase mathematical model to monitor alcoholic fermentation and phenolic extraction of Vitis Vinifera L. red wines 葡萄（Vitis Vinifera L.）红葡萄酒酒精发酵和酚类提取的三相数学模型

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-20 DOI: 10.1016/j.jfoodeng.2025.112932

Kiera Lambrecht , Tobias Louw , Wessel du Toit , Jose Luis Aleixandre-Tudo

The main goal of this study was to explore the development and validation of a dynamic mathematical model to describe the oenological and phenolic development during the alcoholic fermentation process of red wines. A three-phase model including the cap, must and lees phases was attempted. The model uses grape compositional data to forecast the expected progression of phenolic extraction and production of fermentative products. The likelihood of the calculated parameters was tested on a new set of fermentations to assess model accuracy and robustness. In addition, the model parameters were explored to determine the range of applicability of the proposed mathematical model. For the must phase, the phenolic and some of the most relevant oenological parameters have shown R² often higher than 0.8 and mean average predictive error (MAPE) below 20 % indicating comparable levels of accuracy to those presented in literature while also expanding on the number of components of interest. Moreover, model validation has shown that model performance can be affected by fermentation temperature, especially when fermentations are conducted at higher temperatures (28 °C). The mathematical model presented in this study was able to accurately forecast the fermentation kinetics of both phenolic and oenological parameters. The model incorporated the polymerisation of anthocyanins and the transfer of compounds to the lees phase representing a step forward in understanding the kinetics of red wine fermentation and contributes to the development of future methods for monitoring and controlling red wine fermentations.

本研究的主要目的是探索动态数学模型的发展和验证，以描述葡萄酒酒精发酵过程中酒香和酚类物质的发展。尝试了一个三相模型，包括帽、must和lees阶段。该模型使用葡萄成分数据来预测酚提取和发酵产品生产的预期进展。在一组新的发酵中测试了计算参数的似然性，以评估模型的准确性和鲁棒性。此外，还对模型参数进行了探讨，以确定所提出数学模型的适用范围。对于必须相，酚类和一些最相关的酿酒参数显示R2通常高于0.8，平均预测误差（MAPE）低于20%，表明与文献中提出的准确度相当，同时也扩展了感兴趣的成分的数量。此外，模型验证表明，发酵温度会影响模型性能，特别是在较高温度（28°C）下进行发酵时。本研究提出的数学模型能够准确地预测发酵动力学的酚类和酒艺参数。该模型结合了花青素的聚合和化合物转移到酒渣阶段，代表了理解红酒发酵动力学的一步，并有助于开发未来监测和控制红酒发酵的方法。

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引用次数: 0

Predicting coho cold-chain quality via fractional-order models across subzero isotherms 通过分数阶模型在零度以下等温线上预测鳕鱼冷链质量

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-11 DOI: 10.1016/j.jfoodeng.2025.112915

Fabián Alberto Aguilera-Barraza , Roberto Agustín Quevedo-León , Patricia Ximena López-Álvarez , Ociel Muñoz-Fariña , María Cristina Ravanal , Luisbel González

Freezing extends the shelf life of seafood, yet physicochemical and textural degradation persists. This study evaluated coho salmon (Oncorhynchus kisutch) fillets stored isothermally at 268, 264, 260, and 255 K, measuring total volatile basic nitrogen (TVB-N), salt-soluble protein (SSP), pH, and Texture Profile Analysis (hardness, cohesiveness, adhesiveness, springiness, gumminess, chewiness). Independent triplicate determinations were performed at each time–temperature point. TVB-N started at 11.58 ± 1.48 mg/100 g and increased less at colder temperatures (45.5 % at 255 K vs. 60.8 % at 268 K). SSP declined markedly (76–80 % depending on temperature), while pH and total nitrogen remained stable. Texturally, hardness, adhesiveness, gumminess, and chewiness decreased significantly, with attenuated losses at lower temperatures, whereas cohesiveness and springiness were unchanged. A flexible phenomenological kinetic analysis showed that apparent rates consistently decreased with decreasing temperature. The temporal profile of deterioration remained comparatively stable for TVB-N, hardness, and gumminess, but became sharper for SSP, adhesiveness, and chewiness, indicating mechanism transitions linked to ice recrystallization, water redistribution, and microstructural reorganization. The novelty lies in an integrated multi-response design for O. kisutch and in validating a non-restrictive kinetic framework across a broad thermal range. Collectively, the results provide operational criteria to set time–temperature tolerances and estimate shelf life in the coho cold chain, with parameters that are readily transferable to non-isothermal profiles for quality management and process control.

冷冻延长了海鲜的保质期，但物理化学和质地的降解仍然存在。本研究评估了在268、264、260和255 K等温储存的银鲑鱼片，测量了总挥发性碱性氮（TVB-N）、盐溶性蛋白（SSP）、pH值和质地分析（硬度、黏性、粘附性、弹性、粘性、咀嚼性）。在每个时间-温度点进行独立的三次测定。TVB-N开始于11.58±1.48 mg/100 g，在较低温度下增加较少（255 K时为45.5%，268 K时为60.8%）。SSP显著下降（76 - 80%），而pH和总氮保持稳定。质地上，硬度、黏附性、胶性和咀嚼性显著下降，在较低温度下损失减弱，而黏附性和弹性不变。灵活的现象学动力学分析表明，表观速率随着温度的降低而持续降低。TVB-N、硬度和黏性的时间变化相对稳定，但SSP、黏附性和咀嚼性的时间变化更明显，这表明与冰重结晶、水重分配和微观结构重组有关的机制转变。新颖之处在于O. kisutch的综合多响应设计，并在广泛的热范围内验证非限制性动力学框架。总的来说，这些结果为设定时间-温度公差和估计鳕鱼冷链中的保质期提供了操作标准，这些参数很容易转移到质量管理和过程控制的非等温剖面。

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引用次数: 0

CFD-augmented deep learning for accurate non-destructive prediction of squid drying behavior using RGB images 利用RGB图像对鱿鱼干燥行为进行精确非破坏性预测的cfd增强深度学习

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jfoodeng.2025.112919

Timilehin Martins Oyinloye , Won Byong Yoon

This study presents a multimodal deep learning framework for non-destructive prediction of squid drying characteristics under varying drying strategies and temperatures. Drying behavior was characterized by analyzing moisture ratio (MR) and drying rate curves, which revealed faster moisture removal under intermittent drying (ID) compared to continuous drying (CD), particularly at 50 °C. Computational fluid dynamics (CFD) simulations accurately captured internal moisture and temperature distributions (RMSE <0.061 for MR; <2.12 °C for temperature), providing critical image data that compensated for the limitations of real image datasets and surface-based measurements. Convolutional neural network (CNN) models were individually trained using RGB images, infrared (IR) thermal images, and CFD-generated contours. The CFD-trained model achieved the highest classification accuracy (95.7 %), demonstrating the advantage of internal dynamic representation. However, the RGB-only model performed less reliably (87.8 %), particularly during later drying stages when surface changes diminished. To overcome this limitation, we trained a multimodal CNN using RGB, IR, and CFD data, and deployed it using only RGB images. The resulting model achieved >99 % accuracy in classifying drying stages across all conditions, including challenging ID scenarios. This improvement is attributed to cross-modal feature abstraction and knowledge transfer enabled by CFD-augmented training, allowing internal drying dynamics to be inferred from surface-level RGB inputs. This approach effectively bridges the gap between limited experimental imaging and rich, physically-informed simulation data. Compared to traditional sensor-based or unimodal image-based methods, this framework offers a more accurate and scalable solution for visual monitoring of drying processes, particularly in scenarios where internal measurements are inaccessible or cost-prohibitive.

本研究提出了一个多模态深度学习框架，用于在不同干燥策略和温度下对鱿鱼干燥特性进行无损预测。通过分析水分比（MR）和干燥速率曲线来表征干燥行为，发现间歇干燥（ID）比连续干燥（CD）去除水分更快，特别是在50°C时。计算流体动力学（CFD）模拟准确地捕获了内部水分和温度分布（MR的RMSE为0.061；温度的RMSE为2.12°C），提供了关键的图像数据，弥补了真实图像数据集和基于表面的测量的局限性。卷积神经网络（CNN）模型分别使用RGB图像、红外（IR）热图像和cfd生成的轮廓进行训练。cfd训练的模型获得了最高的分类准确率（95.7%），显示了内部动态表示的优势。然而，仅rgb模型的可靠性较低（87.8%），特别是在干燥后期，当表面变化减少时。为了克服这一限制，我们使用RGB、IR和CFD数据训练了一个多模态CNN，并仅使用RGB图像进行部署。所得到的模型在所有条件下（包括具有挑战性的ID场景）对干燥阶段进行分类的准确率达到了99%。这种改进归功于cfd增强训练实现的跨模态特征抽象和知识转移，允许从表面水平的RGB输入推断内部干燥动态。这种方法有效地弥合了有限的实验成像和丰富的物理信息模拟数据之间的差距。与传统的基于传感器或基于单峰图像的方法相比，该框架为干燥过程的视觉监控提供了更准确和可扩展的解决方案，特别是在无法获得内部测量或成本过高的情况下。

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引用次数: 0

Effect of high-pressure homogenization on surfactant-free starch-oil films 高压均质对无表面活性剂淀粉-油膜的影响

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-23 DOI: 10.1016/j.jfoodeng.2025.112939

Xi-ying Xu , Dong-ming Gao , Xu Yao , Zi-xu Zheng , Zong-qiang Fu , Gang Li , Fei-fei Li

This study aimed to improve the properties of surfactant-free starch-oil film-forming dispersions and the corresponding films. High-pressure homogenization (HPH) was applied to process the dispersions. With increasing homogenization pressure, both the apparent viscosity and particle size of the dispersions decreased significantly. Confocal laser scanning microscope revealed a uniform distribution of oil droplets within the dispersions. The HPH treatment not only improved the surface smoothness and transparency of the resulting films but also increased their retrogradation enthalpy and glass transition temperature. As the homogenization pressure increased from 0 MPa to 50 MPa, the water vapor permeability and moisture content of the films decreased, while the water contact angle rose from 38.33° to 53.00°. Furthermore, the tensile strength improved from 3.96 MPa to 6.30 MPa. In conclusion, HPH effectively enhances the stability of surfactant-free starch-oil film-forming dispersions, yielding films with superior mechanical strength and moisture barrier properties.

本研究旨在改善无表面活性剂淀粉-油成膜分散体及其膜的性能。采用高压均质（HPH）技术处理分散体。随着均质压力的增大，分散体的表观粘度和粒径均显著减小。共聚焦激光扫描显微镜观察到分散体内油滴分布均匀。HPH处理不仅提高了膜的表面光滑度和透明度，而且提高了膜的退化焓和玻璃化转变温度。随着均质压力从0 MPa增加到50 MPa，膜的水蒸气渗透率和含水率下降，水接触角从38.33°增加到53.00°。抗拉强度由3.96 MPa提高到6.30 MPa。综上所述，HPH有效地提高了无表面活性剂淀粉-油成膜分散体的稳定性，制备出具有优异机械强度和隔水性能的薄膜。

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引用次数: 0

Tailoring properties of corn starch via active extrusion: Key role of feed moisture 玉米淀粉通过主动挤压的裁剪性能：饲料水分的关键作用

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-26 DOI: 10.1016/j.jfoodeng.2025.112946

Xiaoshuai Yu , Jiangkai Zeng , Jinjie Huo , Jinming Ma , Jiaqi Song , Lin Wang , Mohamed E. Hassan , Yixin Peng , Bo Bo , Zhigang Xiao , Yumin Duan

Corn starch (CS) was modified using a one-step citric acid (CA) active extrusion. Based on the changes of system parameters, the influence of feed moisture on structural, pasting and gel properties of modified starch (ECSCA) were investigated. Results showed that the residence time of material, die pressure, torque and specific mechanical energy (SME) were closely related to feed moisture. FTIR and density functional theory (DFT) analysis confirmed that esterification had occurred and there were ester bonds between CS and CA, which altered surface morphology and particle size of CS. The relative crystallinity and short-range ordered degree of ECSCA showed a decreasing trend when feed moisture increased from 30 % to 35 %, whereas the higher level of feed moisture (37.5 % and 40 %) led to an opposite effect. Compared with natural CS, ECSCA exhibited a lower gelatinization enthalpy (ΔH), peak viscosity (PV) and setback viscosity (SB). The ΔH and PV of ECSCA reduced from 1.53 J/g and 631 cp to 1.08 J/g and 466 cp when feed moisture enhanced from 30 % to 32.5 %, while there was an increasing trend for ΔH and PV when feed moisture further increased. Additionally, increasing feed moisture reduced strength of ECSCA gels as well as altered rheological properties and water distribution of ECSCA gels. These results demonstrated that feed moisture regulated the effect of CA on starch modification via affecting the extrusion environment, which was helpful to broaden the application of one-step active extrusion in starch modification.

采用一步柠檬酸（CA）活性挤出法对玉米淀粉进行改性。在系统参数变化的基础上，研究了饲料水分对改性淀粉（ECSCA）结构、糊化和凝胶性能的影响。结果表明，物料停留时间、模具压力、扭矩和比机械能（SME）与料液含水量密切相关。FTIR和密度泛函理论（DFT）分析证实了CS与CA之间发生了酯化反应，并存在酯键，改变了CS的表面形貌和粒径。当饲料含水量从30%增加到35%时，ECSCA的相对结晶度和近程有序度呈下降趋势，而饲料含水量较高时（37.5%和40%）则相反。与天然CS相比，ECSCA具有更低的糊化焓（ΔH）、峰值粘度（PV）和挫折粘度（SB）。当饲料含水量从30%增加到32.5%时，ECSCA的ΔH和PV从1.53 J/g和631 cp降低到1.08 J/g和466 cp，而当饲料含水量进一步增加时，ΔH和PV有增加的趋势。此外，饲料水分的增加降低了ECSCA凝胶的强度，改变了ECSCA凝胶的流变性能和水分分布。上述结果表明，饲料水分通过影响挤出环境来调节CA对淀粉改性的影响，有助于拓宽一步活性挤出在淀粉改性中的应用。

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引用次数: 0

Vacuum contact drying of dairy gel granules supported by in-line monitoring of the moisture content 真空接触干燥乳凝胶颗粒支持在线监测水分含量

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2026-01-05 DOI: 10.1016/j.jfoodeng.2025.112961

Jennifer Frank , Laura Maria Sieben , Nora Alina Topp , Jörg Hinrichs , Reinhard Kohlus

By producing a storable intermediate during cheese processing by drying new flexibility is gained. Thereby, cheese can be produced detached from the production of intermediate granules and whey. The dairy gel granules tend to agglomerate without agitation and oil-out or plasticise at high temperatures making them a highly challenging product for drying. Contact drying in a modified Lödige ploughshare mixer was performed due to the possibility to apply sufficient agitation and to operate under vacuum. A design of experiments with varying granule types and jacket temperatures was performed and different responses analysed regarding drying efficiency. A higher drying temperature resulted in higher drying rates and consequently lower final moisture contents and a_W values. For more insight into the drying process, two different in-line measurement techniques were installed and calibrated for monitoring of the moisture content. While the capacitive moisture measurement could not be calibrated, the near-infrared spectroscopy was successfully calibrated with a data selection via partial least squares regression with 2nd derivative pre-processing and seven factors as a first step to a smart and dynamic drying process, where the drying parameters can be adapted to the current product properties of the granules.

在奶酪加工过程中，通过干燥产生可储存的中间体，获得了新的灵活性。因此，奶酪的生产可以脱离生产中间颗粒和乳清。乳凝胶颗粒在没有搅拌和出油或在高温下塑化的情况下倾向于凝聚，使它们成为干燥的极具挑战性的产品。由于可以充分搅拌和在真空下操作，在改进的Lödige犁头混合器中进行了接触干燥。进行了不同颗粒类型和夹套温度的试验设计，并分析了不同反应对干燥效率的影响。较高的干燥温度导致较高的干燥速率，从而降低最终水分含量和aW值。为了更深入地了解干燥过程，安装并校准了两种不同的在线测量技术，用于监测水分含量。虽然电容式水分测量无法校准，但近红外光谱通过偏最小二乘回归与二阶导数预处理和七个因素的数据选择成功校准，作为智能和动态干燥过程的第一步，其中干燥参数可以适应颗粒的当前产品特性。

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引用次数: 0

Incorporation of natural polyphenols, obtained from blueberry by-products, as active agent for raspberry packaging applications 从蓝莓副产品中获得的天然多酚，作为覆盆子包装应用的活性剂

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-11 DOI: 10.1016/j.jfoodeng.2025.112905

Federica Alchera , Alice Varaldo , Claudio Cecone , Giovanna Giacalone , Pierangiola Bracco , Marco Zanetti , Marco Ginepro

The study explores the extraction of polyphenols from blueberry by-products, using a green extraction method, and their incorporation into poly-butylene adipate terephthalate (PBAT) electrospun pads for potential use in active packaging. Different solvents were evaluated for their efficiency in extracting polyphenols. The extract obtained using ethanol as a solvent was used for pad production (TPC 370 mg/L). After solubilizing the active extract in the polymer, electrospinning technique was used for obtained the active mat. The resulting active pads were characterized to confirming the preservation of PBAT's structural integrity and thermal stability. Kinetic release tests demonstrated a rapid release of polyphenols compounds into a food simulant (acetic acid 3 % v/v), with nearly complete release observed within 5 h (maximum release 98 %). Raspberries shelf-life test has been applied to test the pads performances. A control packaging and an active packaging were compared over an 11-day storage period that simulated a realistic fruit supply chain: four days of cold refrigeration at 4 °C followed by storage at 15 °C until day 11, simulating supermarket refrigerated display cases. The active pads significantly reduced the fruits incidence of disease and maintained total polyphenol content throughout storage, without negatively impacting weight loss parameters. Overall, the study highlights the potential of utilizing natural polyphenols from food waste in creating sustainable, bioactive packaging solutions that enhance the shelf life and quality of perishable fruits.

本研究探索了从蓝莓副产品中提取多酚的方法，采用绿色提取方法，并将其掺入聚己二酸丁二酯（PBAT）静电纺丝垫中，用于活性包装。考察了不同溶剂提取多酚的效率。以乙醇为溶剂得到的提取物用于pad的生产（TPC 370 mg/L）。将活性提取物溶于聚合物后，采用静电纺丝技术制备活性垫，并对所制备的活性垫进行了表征，以保证PBAT的结构完整性和热稳定性。动力学释放试验表明，多酚类化合物快速释放到食品模拟剂（醋酸3% v/v）中，在5小时内几乎完全释放（最大释放量98%）。采用覆盆子保质期试验对垫片性能进行了测试。对照包装和活性包装在11天的储存期间进行了比较，模拟了现实的水果供应链：在4°C的低温下冷藏4天，然后在15°C的低温下储存到第11天，模拟了超市冷藏陈列柜。活性垫显著降低了果实的发病率，并在整个储存过程中保持了总多酚含量，而对减肥参数没有负面影响。总的来说，这项研究强调了利用食物垃圾中的天然多酚来创造可持续的、生物活性的包装解决方案的潜力，这些解决方案可以延长易腐水果的保质期和质量。

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引用次数: 0

Thermokinetic parameters of vitamin C and total carotenoids in carrot: Prediction and validation of their retention via 3D finite element modelling 胡萝卜中维生素C和总类胡萝卜素的热力学参数：通过三维有限元模型预测和验证它们的保留

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-28 DOI: 10.1016/j.jfoodeng.2025.112957

Miriam Gil-Gaxiola , Olivia Caro-Hernández , Marco Carrazco-Escalante , Rosalina Iribe-Salazar , Yessica Vázquez-López , Melissa González-Camacho , Roberto Gutiérrez-Dorado , José Caro-Corrales

The impact of thermal processing on the stability of bioactive compounds, including vitamin C and total carotenoids, can be reliably predicted using the Finite Element Method (FEM) to estimate temperature histories. This study aimed to integrate experimentally determined thermokinetic parameters, D_T and z, of vitamin C and total carotenoids in carrots with 3D FEM-predicted temperature histories, incorporating temperature-dependent thermophysical properties, to predict and validate their retention during thermal processing. Vitamin C retention (VCR) and total carotenoids retention (TCR) were estimated from 3D FEM-predicted temperature histories (FEMTH) and compared with retentions obtained from experimental temperature histories (ETH) and observed experimental retentions. A completely randomised design was applied for vitamin C and total carotenoids contents considering temperature (50, 60, 70, 80, and 95 °C) and time (1, 2, 3, 4, and 5 min) as factors, and D_T was assessed for each temperature. The D_T for vitamin C ranged from 49.2 to 10.4 min and for carotenoids from 161.6 to 52.5 min; decreasing with temperature. The z-parameter was 65.7 °C for vitamin C and 93.6 °C for carotenoids. The VCR predicted from FEMTH and ETH, and experimentally measured was 54.6, 55.4, and 54.8 %, while TCR was 86.7, 86.9, and 86.6 %, respectively. The activation energy for vitamin C and carotenoids was 34.6 and 24.4 kJ/mol, respectively. Validation confirmed that integrating thermokinetic parameters with FEMTH and ETH accurately predicted VCR and TCR during blanching, demonstrating the importance of considering specific vegetables extracts due to variability in nutrient distribution.

热处理对生物活性化合物（包括维生素C和总类胡萝卜素）稳定性的影响可以使用有限元法（FEM）来估计温度历史。本研究旨在将实验确定的胡萝卜中维生素C和总类胡萝卜素的热力学参数DT和z与三维fem预测的温度历史相结合，结合温度相关的热物理性质，预测和验证它们在热加工过程中的保留情况。利用三维fem预测温度史（FEMTH）估计了维生素C保留率（VCR）和总类胡萝卜素保留率（TCR），并与实验温度史（ETH）和观察到的实验保留率进行了比较。考虑温度（50、60、70、80和95°C）和时间（1、2、3、4和5 min）为因素，采用完全随机设计测定维生素C和总类胡萝卜素含量，并评估每种温度下的DT。维生素C的DT为49.2 ~ 10.4 min，类胡萝卜素的DT为161.6 ~ 52.5 min；随温度降低。维生素C的z参数为65.7°C，类胡萝卜素的z参数为93.6°C。FEMTH和ETH预测的VCR分别为54.6、55.4和54.8%，TCR分别为86.7、86.9和86.6%。维生素C和类胡萝卜素的活化能分别为34.6和24.4 kJ/mol。验证证实，将热力学参数与FEMTH和ETH相结合可以准确预测焯水过程中的VCR和TCR，这表明考虑特定蔬菜提取物的重要性，因为营养素分布的变异性。

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引用次数: 0

Investigation of heat-induced oat drink fouling: Design and validation of a technical-scale test system 热致燕麦饮料污垢的研究：技术规模测试系统的设计与验证

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-05-01 Epub Date: 2025-12-27 DOI: 10.1016/j.jfoodeng.2025.112943

Phillip Müter, Jörg Hinrichs

Production of shelf-stable oat drinks typically relies on ultra-high-temperature (UHT) treatment to ensure microbiological safety and shelf stability. This process is often challenged by severe fouling formation, reducing process efficiency and sustainability. While fouling mechanisms in dairy systems are well characterized, investigations into fouling of oat-based beverages are lacking. This study presents a systematic approach to study fouling of oat drinks under conditions representative of the hot surface temperatures encountered in UHT heat exchangers. A self-designed, technical-scale fouling test system was employed and the production of oat-based fouling material was validated for high reproducibility. The impact of key fouling parameters, including mass flow rate (ṁ between 100 and 400 kg h⁻¹), operation time (t between 60 and 120 min) and heating temperatures (ϑ_Fouling between 75 and 150 °C), was systematically assessed. Using the reference oat-based fouling material, fouling was first observed at 120 °C and increased with temperature. Deposit analysis revealed a dry, firm fouling structure with ≥90 % dry matter and <20 % protein in dry matter. Variations in mass flow rate and operation time influenced deposit mass but not structure or composition. For non-enzymatically treated oat supernatant, fouling occurred already at 90 °C and exhibited a wet, spongy structure. Overall, carbohydrates and protein were the dominant components in the fouling layer. Comparison of fouling experiments in batch recirculation and continuous mode showed no significant difference in weight or composition. The results provide the first systematic insights into fouling build-up and composition of oat-based drinks under UHT conditions and establish a basis for developing more efficient and sustainable processing strategies.

货架稳定燕麦饮料的生产通常依赖于超高温（UHT）处理，以确保微生物安全性和货架稳定性。该工艺经常受到严重污垢形成的挑战，降低了工艺效率和可持续性。虽然乳制品系统中的污垢机制很好地表征了，但对燕麦饮料污垢的调查是缺乏的。本研究提出了一种系统的方法来研究在UHT换热器中遇到的热表面温度条件下燕麦饮料的污垢。采用自行设计的技术规模污垢试验系统，验证了燕麦基污垢材料的高重现性。系统评估了关键污垢参数的影响，包括质量流量（100至400 kg h - 1之间），操作时间（t在60至120分钟之间）和加热温度（ϑFouling在75至150°C之间）。使用参考燕麦基污垢材料，在120°C时首次观察到污垢，并随着温度的升高而增加。沉积物分析表明，该结垢结构干燥、牢固，干物质含量≥90%，蛋白质含量≥20%。质量流量和操作时间的变化对沉积物质量没有影响，但对沉积物的结构和成分没有影响。对于未经酶处理的燕麦上清，在90°C时已经发生污染，并表现出潮湿的海绵结构。总体而言，碳水化合物和蛋白质是污染层的主要成分。间歇式再循环和连续模式下污垢实验的比较表明，重量和成分没有显著差异。结果提供了第一个系统的见解，污垢积聚和组成的燕麦饮料在UHT条件下，并建立了一个基础，开发更有效和可持续的加工策略。

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