Journal of Food Engineering最新文献_第6页

Exploring an electroanalytical approach in the monitoring of bread quality: the folic acid analysis 探索一种监测面包品质的电分析方法：叶酸分析

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-15 DOI: 10.1016/j.jfoodeng.2025.112917

Fernanda C.O.L. Martins , Regina G. Silva , Priscila Bredariol , Fernanda M. Vanin , Djenaine De Souza

This work developed an electroanalytical procedure for the detection of folic acid in bread using the square-wave voltammetry technique with a dental amalgam electrode. This electrode was prepared from homemade materials, providing a solid surface free of mercury and silver. It exhibited electrochemical properties similar to those of traditional mercury electrodes, without the need for manipulation or waste generation, as mercury was only manipulated during amalgam preparation. The experimental and voltammetric parameters were optimized, resulting in a well-defined voltammetric peak suitable for analytical purposes. This peak showed a small potential value, reducing interference in the voltammetric signal from the application of bread samples. Analytical curves were built over a linear range from 1.00x10⁻⁸ to 5.00x10⁻⁶ mol L⁻¹ with excellent repeatability (4.49–4.73 %), and reproducibility (5.07–5.96 %). Limit of detection of 49.0 and 2.13.

nmol L⁻¹, and limit of quantification of 163 and 0.708 nmol L⁻¹ using 70 and 250 s⁻¹ respectively, were calculated. These analytical data were compared with similar parameters obtained by high-performance liquid chromatography with photodiode detection, indicating that the DAE procedure offers excellent selectivity, sensitivity, high analytical frequency, ease of operation, and cost-effectiveness. Furthermore, the proposed procedure was used to analyze different bread samples, making a simple liquid-liquid extraction with phosphate buffer solution. Excellent recoveries were obtained, demonstrating the procedure's robustness, increased analytical frequency, and the use of no organic solvent, thereby reducing costs, time, and waste generation, in line with the guidelines of Green Analytical Chemistry.

本研究开发了一种用牙汞合金电极方波伏安法检测面包中叶酸的电分析方法。这种电极是由自制材料制成的，提供了一个不含汞和银的固体表面。它表现出与传统汞电极相似的电化学特性，不需要操纵或产生废物，因为汞只在汞合金制备过程中被操纵。优化了实验和伏安参数，得到了一个定义良好的伏安峰，适合于分析目的。该峰电位值较小，减少了面包样品应用对伏安信号的干扰。在1.00 × 10−8 ~ 5.00 × 10−6 mol L−1的线性范围内建立分析曲线，重复性好（4.49% ~ 4.73%），重现性好（5.07 ~ 5.96%）。检出限为49.0和2.13。分别用70和250 s−1计算163和0.708 nmol L−1的定量限。将这些分析数据与光电二极管检测的高效液相色谱法获得的相似参数进行比较，表明DAE方法具有良好的选择性、灵敏度、分析频率高、操作简便和成本效益。此外，将该方法应用于不同面包样品的分析，用磷酸盐缓冲液进行简单的液-液萃取。获得了极好的回收率，证明了该方法的稳健性，增加了分析频率，并且不使用有机溶剂，从而降低了成本，时间和废物产生，符合绿色分析化学的指导方针。

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引用次数: 0

Sustainable multifunctional packaging films based on chitosan and food waste-derived carbon nanodots for fruit preservation 基于壳聚糖和食物垃圾衍生碳纳米点的水果保鲜可持续多功能包装膜

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-14 DOI: 10.1016/j.jfoodeng.2025.112930

Ying Ren, Dan Chen, Shiyu Lin, Xiaoping Fan, Liming Cao

Chitosan (CS), an abundant and biodegradable natural polymer, represents a highly valuable alternative to non-biodegradable packaging materials. But it is limited by unsatisfactory mechanical, barrier, and antibacterial properties. Food waste is rich in active ingredients. Using them for food preservation not only facilitates a closed-loop of resource utilization but also reduces dependence on traditional preservatives, providing a more eco-friendly and sustainable solution. In this study, nitrogen-doped carbon dots (N-CDs) were synthesized from orange peel waste via a green hydrothermal method. Sustainable multifunctional composite films were prepared by compounding N-CDs with chitosan (CS). The results showed that adding N-CDs enhanced the mechanical properties, UV protection, water barrier, antibacterial activity, and antioxidant capabilities of the composite films. Furthermore, the films also exhibited good humidity-responsive fluorescent sensing capability, making them suitable for smart humidity monitoring. When used for fruit preservation, the composite films could effectively extend the shelf life. This study of multifunctional packaging films composed of seafood waste (CS) and fruit waste (N-CDs) providing an easy approach for the high-value utilization of food waste and the sustainable development of food packaging materials.

壳聚糖（CS）是一种储量丰富、可降解的天然高分子材料，是替代非生物降解包装材料的一种极具价值的材料。但它的机械、屏障和抗菌性能不理想。食物垃圾富含有效成分。将它们用于食品保鲜，不仅促进了资源利用的闭环，而且减少了对传统防腐剂的依赖，提供了一种更加环保和可持续的解决方案。本研究采用绿色水热法制备了氮掺杂碳点（N-CDs）。用N-CDs与壳聚糖（CS）复合制备了可持续多功能复合薄膜。结果表明，N-CDs的加入提高了复合膜的力学性能、防紫外线性能、水阻隔性能、抗菌性能和抗氧化性能。此外，该薄膜还表现出良好的湿度响应荧光传感能力，使其适合智能湿度监测。复合薄膜用于水果保鲜，可有效延长水果的保质期。本课题研究了由海鲜废弃物（CS）和水果废弃物（N-CDs）组成的多功能包装薄膜，为食品废弃物的高价值利用和食品包装材料的可持续发展提供了一条简单易行的途径。

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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 : 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

AI-powered computer vision system for veal-mutton minced meat authenticity evaluation 基于ai的小牛羊肉肉末真实性评估计算机视觉系统

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-13 DOI: 10.1016/j.jfoodeng.2025.112920

Ali Mohammad Kazempour, Sajad Kiani

As global meat product consumption rises, ensuring product quality has become increasingly critical. This study presents two analytical frameworks for quantifying veal composition ratio in minced mutton using RGB image data. In the first approach, regression models, including Partial Least Squares Regression, Bagged Linear Regression, Ridge, Lasso, and Multilayer Perceptron (MLP), were trained on RGB features extracted from 204 flattened images representing veal mixture ratios from 0 % to 100 %. Among these, the MLP model achieved the highest predictive accuracy (R² = 0.938, RMSE = 7.495), confirming the feasibility of RGB-based regression modeling. In the second scenario, a pixel-wise classification approach was developed using RGB values from pure mutton and veal samples. PCA revealed clear spectral separability between classes, and an MLP classifier achieved near-perfect performance across training, cross-validation, and internal test sets (accuracy >0.999). External validation on 49 intermediate mixture images yielded an R² of 0.908 and RMSE of 8.567, confirming the model's generalization capability in estimating composition ratios. Overall, the results demonstrate that both regression and classification strategies are effective for image-based authenticating veal-mutton minced meat. The developed AI vision system provides a robust foundation for developing automated systems to detect the adulteration of minced meat.

随着全球肉制品消费量的增加，确保产品质量变得越来越重要。本研究提出了两种利用RGB图像数据量化羊肉肉末中牛肉成分比例的分析框架。在第一种方法中，回归模型，包括偏最小二乘回归、Bagged线性回归、Ridge、Lasso和多层感知器（MLP），对从204张代表牛肉混合比例从0%到100%的扁平图像中提取的RGB特征进行训练。其中，MLP模型的预测准确率最高（R2 = 0.938, RMSE = 7.495），证实了基于rgb的回归建模的可行性。在第二个场景中，使用来自纯羊肉和小牛肉样本的RGB值开发了逐像素分类方法。PCA显示了类之间清晰的光谱可分性，MLP分类器在训练集、交叉验证集和内部测试集上实现了近乎完美的性能（准确率>；0.999）。对49幅中间混合图像进行外部验证，R2为0.908，RMSE为8.567，证实了模型在估计成分比方面的泛化能力。综上所述，回归和分类策略对基于图像的牛羊肉肉末鉴别都是有效的。开发的人工智能视觉系统为开发检测肉末掺假的自动化系统提供了坚实的基础。

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引用次数: 0

3D structure of protein networks and lipid globules in heat-treated egg yolk revealed by X-ray holo-tomography x射线全息断层扫描显示的热处理蛋黄中蛋白质网络和脂质球的三维结构

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-12 DOI: 10.1016/j.jfoodeng.2025.112916

Felix Wittwer , Nimmi Das Anthuparambil , Frederik Unger , Randeer Pratap Gautam , Silja Flenner , Imke Greving , Christian Gutt , Peter Modregger

Upon heating, egg yolk transforms from a liquid to a grainy gel due to a combination of lipid aggregation, protein denaturation–aggregation–gelation and other processes. This heat-induced solidification of egg yolk can serve as a useful model system for the investigation of protein denaturation and gelation in biological systems in general. Using X-ray holographic tomography, we studied the heat-induced changes in egg yolk on the micron to sub-micron length scale. In contrast to electron microscopy, X-ray holography does not require sample staining, fixation, or drying, which potentially alter the sample and harm sample fidelity. Our results reveal a developing separation between proteins and lipids with fatty components rapidly aggregating into large globules around 40

μ

m in diameter.

蛋黄受热后，经过脂质聚集、蛋白质变性-聚集-凝胶等过程，由液体转变为粒状凝胶。这种蛋黄的热致凝固可以作为研究生物系统中蛋白质变性和凝胶化的一个有用的模型系统。利用x射线全息断层扫描技术，研究了热致蛋黄在微米至亚微米尺度上的变化。与电子显微镜相比，x射线全息照相不需要样品染色、固定或干燥，这些都可能改变样品并损害样品的保真度。我们的研究结果揭示了蛋白质和脂质之间的分离，脂肪成分迅速聚集成直径约40 μm的大球体。

引用次数: 0

Study on the process kinetics during the concentration of medicinal food extracts 药用食品提取物浓缩过程动力学研究

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-12 DOI: 10.1016/j.jfoodeng.2025.112929

Xueni Niu , Tongtong Luan , Xiangwen Kong, Pei Wang, Wenjun Liu, Zhenzhong Wang, Liang Cao, Wei Xiao

Enhancing the batch-to-batch consistency of plant-derived products has long posed several challenges, making it crucial to study the quantity-quality transfer correlation in the manufacturing of medicinal food. Ethanolic and aqueous extraction are the primary methods used in the medicinal food engineering, and the subsequent concentration of these extracts is the vital process that governs the quality of in-process intermediates. This study investigated the concentration process of Lonicerae Japonicae Flos (LJF) and Gardeniae Fructus (GF) extracts, examining how aqueous and ethanolic medium affect critical process parameters (CPPs) and critical quality attributes (CQAs) of the concentrated paste. Crucially, the study also achieved dynamic prediction on the contents of effective components during concentration process. And a correlation model between viscosity and component transfer coefficient (k) was established through a semi-empirical approach where the ΔP instead of ΔC as the driving force, thereby determining the boundary range of relative density for the concentrate. The results showed that upon reaching the target relative density, the ethanolic GF paste had a viscosity of only 13.6 ± 0.6 mPa·s, significantly lower than the 122.5 ± 7.4 mPa·s of the aqueous LJF paste. However, it demonstrated higher contents of effective component and total solids in ethanolic GF paste. The correlation model between viscosity and component transfer coefficient further confirmed that the transfer coefficient of effective components decreased as viscosity increased throughout the process. Overall, the ethanolic medium exhibited superior transfer efficiency for effective components during concentration process compared to the aqueous medium. This study enabled the customized establishment of efficient concentration process parameters for different extraction medium (aqueous and ethanolic), ultimately improving the batch-to-batch consistency in the manufacturing of medicinal food.

长期以来，提高植物源性产品的批间一致性一直存在一些挑战，因此研究药用食品生产中的数量-质量转移相关性至关重要。乙醇和水萃取是药用食品工程中使用的主要方法，这些萃取物的后续浓缩是决定过程中中间体质量的重要过程。本研究考察了金银花（LJF）和栀子（GF）提取物的浓缩过程，考察了水溶液和乙醇介质对浓缩膏体关键工艺参数（CPPs）和关键品质属性（cqa）的影响。重要的是，本研究还实现了对浓缩过程中有效组分含量的动态预测。以ΔP代替ΔC为驱动力，采用半经验方法建立了黏度与组分传递系数k的关联模型，从而确定了精矿相对密度的边界范围。结果表明，在达到目标相对密度时，乙醇GF膏体的粘度仅为13.6±0.6 mPa·s，显著低于水相LJF膏体的122.5±7.4 mPa·s。而乙醇GF膏体的有效组分和总固形物含量较高。黏度与组分传递系数的相关模型进一步证实了整个过程中有效组分的传递系数随黏度的增大而减小。总体而言，在浓缩过程中，乙醇介质对有效组分的传递效率优于水介质。本研究可针对不同的萃取介质（水萃取和乙醇萃取）定制高效的浓缩工艺参数，最终提高药膳生产的批间一致性。

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引用次数: 0

Digital twins for autonomous thermal food processing: A model predictive control study with reduced-order models of augmented neural ordinary differential equation type 自主热食品加工的数字孪生：增广神经常微分方程型降阶模型的模型预测控制研究

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-11 DOI: 10.1016/j.jfoodeng.2025.112918

Maximilian Kannapinn , David Dorer , Michael Schäfer , Oliver Weeger

This paper presents a digital-twin-based model predictive control framework for autonomous process control, demonstrated in a virtual experiment on thermal food processing in a convection oven. In combination with prior work, this approach enables simulation-centered food scientists to deploy physics-based simulation models in live process control environments. The digital twin is realized as a physics-based, data-driven reduced-order model (ROM) that provides faster-than-real-time predictions. The ROM is trained on trajectories from a high-fidelity multiphysics finite-element model of chicken fillets. A central contribution is a model predictive control scheme that overcomes the common fixed-initial-condition limitation of augmented neural ordinary differential equation ROMs: a dedicated sub-optimization step re-synchronizes the surrogate to the measured state of the food item at each control instant, allowing reliable live re-optimization without access to internal ROM states. The controller optimizes oven temperature setpoints to meet target food-quality metrics (core temperature, moisture content, texture) and autonomously accommodates changes to the planned end time during operation. Quantitatively, the ROM achieves relative time-series errors of 0.18–0.49%, and the control algorithm evaluates 501 trajectories of 1800 s real time in a total of 46.6 s on a single core of a processor, demonstrating on-device feasibility without cloud or edge resources. Receding-horizon model predictive control of the remaining setpoints mitigates model–reality mismatch, enforces user-defined food metrics, and sustains closed-loop performance under autonomous operation.

本文提出了一种基于数字孪生模型的自主过程控制预测控制框架，并在对流烤箱热食品加工的虚拟实验中进行了验证。结合先前的工作，这种方法使以仿真为中心的食品科学家能够在现场过程控制环境中部署基于物理的仿真模型。数字孪生是一种基于物理的、数据驱动的降阶模型（ROM），可以提供比实时更快的预测。ROM是根据来自鸡柳的高保真多物理场有限元模型的轨迹进行训练的。一个核心贡献是模型预测控制方案，它克服了增强神经常微分方程ROM的常见固定初始条件限制：一个专用的子优化步骤在每个控制时刻将代理与食品的测量状态重新同步，允许可靠的实时重新优化，而无需访问内部ROM状态。控制器优化烤箱温度设定值，以满足目标食品质量指标（核心温度，水分含量，质地），并在操作过程中自动适应计划结束时间的变化。在数量上，ROM实现了0.18-0.49%的相对时间序列误差，控制算法在处理器单核上总共46.6秒的时间内实时评估了1800秒的501个轨迹，证明了在没有云或边缘资源的情况下器件上的可行性。对剩余设定值的后退水平模型预测控制减轻了模型与现实的不匹配，强制执行用户定义的食物指标，并在自主操作下维持闭环性能。

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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 : 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

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 : 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

Effects of tailoring sucrose particle size distribution and sucrose volume fraction on microstructure and fat bloom in chocolate model systems 裁剪蔗糖粒度分布和蔗糖体积分数对巧克力模型系统微观结构和脂肪华度的影响

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2025-12-11 DOI: 10.1016/j.jfoodeng.2025.112914

Jiayang Jin , Linrong Shen , Jiahui Wang , Ling Yang , Richard W. Hartel , Liming Zhao

In this study, a new bloom-reducing strategy was introduced by mixing coarse and fine sugar particles to tailor the particle size distribution (PSD) of chocolate model systems. To investigate the impact of sucrose PSD on bloom, chocolates were formulated with three sucrose mixtures of varying PSD at three volume fractions (15 %, 50 %, and 75 %) in the nonfat particle phase. Bloom formation was assessed by changes in whiteness index (ΔWI) and white area percentage (WA%), alongside polymorphic transition analysis. Both ΔWI and WA% increased significantly with time (P < 0.0001), confirming the time-dependent nature of fat bloom. Narrowing the PSD width and reducing the sucrose volume fraction significantly (P < 0.0001) decreased bloom intensity (ΔWI and WA%) during storage. Supporting results from sedimentation volume, Casson viscosity, and discrete element method (DEM) simulation further confirmed that the 2:1 coarse-to-fine sucrose ratio achieved denser packing, reducing fat migration and recrystallization, with the 2:1 ratio at 15 % sucrose volume fraction showing the best bloom resistance. These findings suggest that PSD-driven microstructural regulation via coarse-fine particle mixing effectively enhances chocolate's bloom resistance during storage.

在本研究中，引入了一种新的减少花的策略，通过混合粗糖和细糖颗粒来调整巧克力模型系统的粒度分布（PSD）。为了研究蔗糖PSD对开花的影响，在脱脂颗粒阶段用三种不同PSD体积分数（15%，50%和75%）的蔗糖混合物配制巧克力。通过白度指数（ΔWI）和白面积百分比（WA%）的变化以及多态性转变分析来评估开花形成。ΔWI和WA%均随时间显著增加（P < 0.0001），证实了脂肪开花的时间依赖性。缩小PSD宽度和显著降低蔗糖体积分数（P < 0.0001）降低了贮藏期间的开花强度（ΔWI和WA%）。沉降体积、卡森粘度和离散元法（DEM）模拟的支持结果进一步证实，2:1的粗细蔗糖比可以实现更密集的堆积，减少脂肪迁移和再结晶，其中2:1的蔗糖体积分数为15%时的抗开花性能最好。这些结果表明，psd驱动的微结构调节通过粗细颗粒混合有效地提高了巧克力在储存过程中的抗花性。

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