Journal of Food Engineering最新文献_第2页

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 : 2026-01-19 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。

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引用次数: 0

Dynamic speed adjustment based on time-code enhances filament consistency in continuous switching 3D food printing 在连续切换食品3D打印中，基于时间码的动态速度调节提高了灯丝的一致性

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-19 DOI: 10.1016/j.jfoodeng.2026.112973

Zilong Zhao , Xiaolin An , Nana Zhang , Dingxuan Xu , Bo Hu , Xing Chen , Bowen Yan , Yu Liu , Wei Chen , Daming Fan

To elucidate the causes of filament width inconsistency during continuous switching 3D food printing and solve the filament width uniformity issue while maintaining printing accuracy and efficiency. This study first investigated the consistency of filament for beef slurries with varying moisture content under different printing speeds. Furthermore, through rheological analysis, pipe mechanical analysis, and two-phase simulation, the stress state of the slurries during the switching moment in 3D printing was examined, along with variations in phase interface, viscosity, extrusion speed, and pipeline pressure. It was found that the creep behavior during the switching moment, and the friction between the beef slurry and the pipeline resulted in a reduction in extrusion speed during switching, leading to filament inconsistency. Moreover, the interaction behavior between the two-phase slurries during flow induced a flow pressure at the two-phase interface, which was identified as the key factor influencing the variation of filament consistency with the slurry properties and printing speed. Based on this, a continuous switching 3D printing technology with real-time speed variation, based on Tcode, was developed. By adjusting the printing speed at the switching moment, the phenomenon of filament width narrowing was avoided, ensuring highly personalized spatial distribution of the two-phase slurries within the printed products and the high-quality construction of voxel structures with 2 mm precision.

阐明连续切换食品3D打印中线材宽度不一致的原因，在保持打印精度和效率的同时解决线材宽度均匀性问题。本研究首先考察了在不同印刷速度下，不同含水率的牛肉浆料长丝的稠度。此外，通过流变分析、管道力学分析和两相模拟，研究了3D打印切换时刻浆料的应力状态，以及相界面、粘度、挤出速度和管道压力的变化。发现切换时的蠕变行为以及牛肉浆与管道之间的摩擦导致切换时挤压速度降低，导致长丝不一致。此外，两相浆料在流动过程中的相互作用行为在两相界面处产生了流动压力，这是影响浆料性能和打印速度变化的关键因素。在此基础上，开发了一种基于Tcode的实时变速连续开关3D打印技术。通过在切换时刻调整打印速度，避免了长丝宽度变窄的现象，确保了两相浆料在打印产品内高度个性化的空间分布，以及2毫米精度的体素结构的高质量构建。

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引用次数: 0

Mechanistic insights into the interfacial rheology of cellulose nanofibers from rice bran for stabilising pickering emulsions 米糠纤维素纳米纤维对酸洗乳稳定作用的界面流变机理研究

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-17 DOI: 10.1016/j.jfoodeng.2026.112991

Yadav K C, Jaquie Mitchell, Bhesh Bhandari, Sangeeta Prakash

This study optimised a sequential extraction process that includes alkali treatment, bleaching, and acid hydrolysis to produce cellulose nanofibers (RBNF) from defatted rice bran and examined their functionality as Pickering emulsion stabilisers. The optimised conditions (5 % KOH for 15 h, 1 % NaClO₂, and 10 % H₂SO₄ yielded 13.88 % nanofibers containing 60.5 % cellulose with 55 % crystallinity. Structural analyses (SEM, AFM, MIR, XRD) confirmed progressive removal of lignin and hemicellulose and formation of fibrillar morphologies (42 nm diameter), while zeta potential (<−26 mV) and DSC data indicated good colloidal and thermal stability. Interfacial rheology demonstrated that RBNF powders and gels exhibit similar diffusion, adsorption, and rearrangement kinetics at air–water and oil–water interfaces, forming elastic interfacial films described by first-order behaviour. Pickering emulsions prepared via ultrasonication, or high-pressure homogenization displayed comparable droplet sizes (∼3–4 μm), shear-thinning flow, and gel-like viscoelasticity (G′>G″). Microscopy (CLSM, SEM, Cryo-SEM) revealed stabilization mechanisms involving strong RBNF adsorption at the oil–water interface, entrapment of droplets within a three-dimensional fibre network, and bridging them. Overall, this work demonstrates that rice bran is a promising source of nanocellulose and provides mechanistic insights into RBNF-stabilized emulsions, highlighting the practical advantages of using powder-form nanofibers for scalable, food-grade Pickering systems.

本研究优化了从脱脂米糠中提取纤维素纳米纤维（RBNF）的顺序提取工艺，包括碱处理、漂白和酸水解，并检验了其作为皮克林乳液稳定剂的功能。优化条件（5% KOH, 1% NaClO2, 10% H2SO4）可得13.88%的纳米纤维，其中纤维素含量为60.5%，结晶度为55%。结构分析（SEM， AFM， MIR， XRD）证实了木质素和半纤维素的逐渐去除和纤维状形态的形成（42 nm直径），而zeta电位（<−26 mV）和DSC数据表明了良好的胶体和热稳定性。界面流变学表明，RBNF粉末和凝胶在空气-水和油水界面表现出相似的扩散、吸附和重排动力学，形成一阶行为描述的弹性界面膜。通过超声或高压均质制备的Pickering乳剂显示出相似的液滴大小（~ 3-4 μm）、剪切变薄流动和凝胶样粘弹性（G ' >G″）。显微镜（CLSM， SEM, cro -SEM）揭示了稳定机制，包括RBNF在油水界面的强吸附，在三维纤维网络中捕获液滴，并桥接它们。总的来说，这项工作表明米糠是一种很有前途的纳米纤维素来源，并提供了rbnf稳定乳液的机理见解，突出了在可扩展的食品级皮克林系统中使用粉末状纳米纤维的实际优势。

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引用次数: 0

Directional freezing exploits meat anisotropy to preserve muscle fibers microstructural integrity and mitigate freezing loss 定向冷冻利用肉的各向异性来保持肌肉纤维微观结构的完整性，减轻冷冻损失

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-17 DOI: 10.1016/j.jfoodeng.2026.112986

Jian Hu , Xing Chen , Wenjin Gong , Hao Zou , Bo Hu , Nana Zhang , Bowen Yan , Wei Chen , Daming Fan

Water loss of meat induced by ice crystal damage during freezing storage creates significant economic losses and environmental burdens, posing a critical challenge to the meat industry. Inspired by the anisotropic structure of meat, this study first explored the potential of directional freezing (by controlling heat flow direction) to mitigate the freezing loss of meat. A custom Peltier-based system was used to control heat flow direction and compare water-holding capacity (WHC) in meat subjected to longitudinal freezing (LF, heat flow parallel to muscle fibers), transverse freezing (TF, heat flow perpendicular to muscle fibers) and conventional freezing (CF, random heat flow). Results showed that LF, with higher freezing rates, significantly reduced thawing and centrifugal losses compared with TF and CF (by approximately 24.59–52.59 % and 18.52–28.38 %, respectively) (p < 0.05). LF produced smaller and more uniformly distributed ice crystals (approximately 30–60 % smaller than in TF and CF) and preserved muscle fibers with superior integrity, smaller gaps, and ordered parallel arrangement. Conversely, TF and CF generated larger, irregular crystals and pronounced fiber disruption. Pearson correlation analysis demonstrated that equivalent diameter and elongation were positively correlated with reduced WHC, whereas roundness exhibited a negative correlation. These findings indicate that aligning heat flow with muscle fiber orientation forms axial ice channels that guide ordered ice growth and limit transverse damage. Directional freezing thus offers a promising, field-free and additive-free strategy for improving the frozen meat quality and may be extended to other anisotropic foods in sustainable industrial applications.

肉类在冷冻过程中因冰晶损坏而导致的水分流失造成了巨大的经济损失和环境负担，对肉类行业构成了严峻的挑战。受肉类各向异性结构的启发，本研究首次探索了定向冷冻（通过控制热流方向）减轻肉类冷冻损失的潜力。采用基于peltier的定制系统控制热流方向，比较纵向冷冻（LF，平行于肌肉纤维的热流）、横向冷冻（TF，垂直于肌肉纤维的热流）和常规冷冻（CF，随机热流）下肉类的持水能力（WHC）。结果表明，与TF和CF相比，冷冻速率较高的LF显著降低了解冻损失和离心损失（分别约为24.59 ~ 52.59%和18.52 ~ 28.38%）（p < 0.05）。LF产生的冰晶更小、分布更均匀（比TF和CF小约30 - 60%），保存的肌纤维具有更好的完整性、更小的间隙和有序的平行排列。相反，TF和CF产生较大的不规则晶体和明显的纤维断裂。Pearson相关分析表明，等效直径和伸长与WHC降低呈正相关，而圆度与WHC降低呈负相关。这些发现表明，将热流与肌肉纤维取向对齐形成轴向冰通道，引导冰有序生长并限制横向损伤。因此，定向冷冻为改善冻肉品质提供了一种有前途的、无现场和无添加剂的策略，并可在可持续的工业应用中扩展到其他各向异性食品。

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引用次数: 0

Peanut protein-xanthan gum core-shell microgels: Microstructure and oral lubrication performance 花生蛋白-黄原胶核壳微凝胶：微观结构与口腔润滑性能

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-13 DOI: 10.1016/j.jfoodeng.2026.112988

Hanyu Lin , Haicheng Xu , Man Wu , Guohua Hou , Song Miao , Baodong Zheng , Longtao Zhang

Peanut protein (PP) and xanthan gum (XG) were co-assembled to form composite microgels (PP-XGM) and evaluated as a scalable, plant-based biolubricant for oral food applications. Structure-interaction-lubrication relationships were examined to relate microstructure and interfacial properties to macroscopic lubrication performance. Compared with peanut protein microgel, PP-XGM exhibited an increased mean particle size (971.9 nm), a modest reduction in absolute ζ-potential (25.7 mV) and a 60 % decrease in surface hydrophobicity, consistent with formation of a hydrated XG shell that masks surface charge and shields hydrophobic domains. Secondary-structure analysis indicated loss of α-helix (20 %–6 %) and gain of β-sheet content (8 %–37 %). Rheological analysis revealed that PP-XGM exhibits shear-thinning behavior, with an apparent viscosity of 0.0576 Pa⋅s at a shear rate of 1000 s⁻¹, which is approximately 2.5 times higher than that of PP. The expanded linear viscoelastic region (0.01–7 %) is consistent with the characteristics of a flexible weak-gel network. Under a 2 N load at 37 °C, PP-XGM reduced the mean friction coefficient from 0.333 to 0.159 (≈52 % reduction), indicating substantially improved lubrication. These findings demonstrate that PP-XGM microgels provide a promising, food-compatible approach to enhance oral lubrication using plant-derived components.

花生蛋白（PP）和黄原胶（XG）共组装形成复合微凝胶（PP- xgm），并作为一种可扩展的、基于植物的口服食品生物润滑剂进行评估。研究了结构-相互作用-润滑关系，将微观结构和界面性能与宏观润滑性能联系起来。与花生蛋白微凝胶相比，PP-XGM的平均粒径增加（971.9 nm），绝对ζ-电位适度降低（25.7 mV），表面疏水性降低60%，这与水合XG壳的形成一致，该壳掩盖了表面电荷并屏蔽了疏水结构域。二级结构分析表明α-螺旋损失（20% - 6%），β-薄片含量增加（8% - 37%）。流变学分析表明，PP- xgm具有剪切减薄特性，在剪切速率为1000 s−1时，表观粘度为0.0576 Pa⋅s，约为PP的2.5倍，线性粘弹性区扩展幅度为0.01 ~ 7%，符合柔性弱凝胶网络的特征。在37°C的2 N载荷下，PP-XGM将平均摩擦系数从0.333降低到0.159(≈降低52%)，表明显著改善了润滑。这些发现表明，PP-XGM微凝胶提供了一种有前途的、与食物相容的方法，可以使用植物源性成分来增强口腔润滑。

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引用次数: 0

Deep visual measurement of corn starch particles size via RIS-UNet 基于RIS-UNet的玉米淀粉粒度的深度视觉测量

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-12 DOI: 10.1016/j.jfoodeng.2026.112982

Xuyan Zhao , Wenlu Zhu , Xiangyang Li , Hanwen Niu , Qiao Wang , Qunfeng Niu , Li Wang , Yuan Zhang

As a key ingredient in the food industry, corn starch has a particle size distribution that directly governs product processing performance and final product quality. Although image-based analysis offers an effective approach for precise particle characterization, particle adhesion still limits the accuracy of existing segmentation algorithms. To address the small size, adhesion, and diverse morphologies of starch particles, this study developed a high-resolution imaging system and constructed a dataset covering dispersed, partially agglomerated, and densely agglomerated states. A segmentation model termed RIS-UNet was proposed, integrating ResNet50 for deep feature extraction, Inception modules, and squeeze-and-excitation (SE) attention for improved boundary detection. Experiments showed RIS-UNet achieved a mean intersection over union (mIoU) of 94.92 % and accuracy of 98.71 %, outperforming UNet, Deeplab_v3, FCN, and Lraspp. Compared with a BT-9300H laser particle size analyzer, relative errors for median diameter (D50) and mean diameters were below 5 %, with highly consistent distribution curves. Overall, the proposed method provides a robust and cost-effective solution for intelligent and quantitative starch particle analysis.

作为食品工业的关键原料，玉米淀粉的粒度分布直接决定了产品的加工性能和最终产品的质量。尽管基于图像的分析为精确的颗粒表征提供了有效的方法，但颗粒粘附性仍然限制了现有分割算法的准确性。为了解决淀粉颗粒的小尺寸、粘附性和多种形态，本研究开发了一个高分辨率成像系统，并构建了一个涵盖分散、部分凝聚和密集凝聚状态的数据集。提出了一种称为RIS-UNet的分割模型，该模型集成了用于深度特征提取的ResNet50、Inception模块和用于改进边界检测的挤压和激励（SE）注意。实验表明，RIS-UNet的平均交联率（mIoU）为94.92%，准确率为98.71%，优于UNet、Deeplab_v3、FCN和Lraspp。与BT-9300H激光粒度分析仪相比，中位粒径（D50）与平均粒径的相对误差均在5%以下，分布曲线高度一致。总的来说，该方法为智能和定量淀粉颗粒分析提供了一种鲁棒性和成本效益高的解决方案。

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引用次数: 0

Enhancing the oral processing and swallowing performance of cod soft gels 提高鳕鱼软凝胶的口腔加工和吞咽性能

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-09 DOI: 10.1016/j.jfoodeng.2025.112937

Xiliang Yu , Yue Wang , Lin Han , Shiyi Liu , Michelle Ji Yeon Yoo , Xiuping Dong

The decline in body functions caused by aging often leads to dysphagia in older adults, thereby making a comfortable and safe eating process particularly important. The study investigated the effects of oral processing, swallowing and in vitro digestive behavior of cod protein soft gels (CGs) with different amounts of HIPEs added (also with different textural properties). In oral environment (37 °C), the CGs gradually liquefied. The modulus and yield strain were significantly reduced; the viscosity was increased compared to the room temperature (25 °C). During chewing, the CGs with HIPEs required more force to chew, but the number of chewing cycles was reduced. The oil droplet in HIPEs significantly decreased the friction coefficient of CGs, which is beneficial for safety and comfort in swallowing. CGs with added HIPEs were preferred by sensory evaluators. Multivariate analysis successfully differentiated the samples and identified that sensory attributes like swallowing residue' and key lubrication parameters (VIP>1) were the primary drivers of sample classification. The addition of HIPEs significantly affected the digestibility of proteins in CGs, with a gradual decrease in the particle size and number of peptides in the digests. The results of this study can be used as a reference for the development of food products for older people with different levels of dysphagia.

衰老引起的身体机能下降往往会导致老年人吞咽困难，因此，舒适和安全的饮食过程尤为重要。本研究考察了添加不同量的HIPEs（也具有不同的质地性质）对鳕鱼蛋白软凝胶（CGs）的口腔加工、吞咽和体外消化行为的影响。在口腔环境（37℃）下，CGs逐渐液化。模量和屈服应变显著降低；与室温（25℃）相比，粘度有所增加。在咀嚼过程中，HIPEs的CGs需要更大的咀嚼力，但咀嚼次数减少。HIPEs中的油滴显著降低了CGs的摩擦系数，有利于吞咽的安全性和舒适性。感官评估者更喜欢添加HIPEs的cg。多变量分析成功地对样品进行了分类，并发现吞咽残留物和关键润滑参数（VIP>1）等感官属性是样品分类的主要驱动因素。HIPEs的添加显著影响了猪对蛋白质的消化率，消化产物的颗粒大小和多肽数量逐渐减少。本研究结果可为开发针对不同程度吞咽困难老年人的食品提供参考。

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引用次数: 0

Rice starch-ferulic acid complexes: The role of extrusion process 大米淀粉-阿魏酸配合物：挤压工艺的作用

IF 5.8 2区农林科学 Q1 ENGINEERING, CHEMICAL

Journal of Food Engineering

Pub Date : 2026-01-09 DOI: 10.1016/j.jfoodeng.2026.112974

Jinjie Huo , Yumin Duan , Jiangkai Zeng , Xiaoqi Ma , Mohamed E. Hassan , Bo Bo , Xiaoshuai Yu , Zhigang Xiao

This study evaluated the effects of ferulic acid (FA) on morphology, crystalline and fine structures of rice starch (RS) during the extrusion process. Results showed that the FA was wrapped in the starch matrix and existed in the form of aggregates from the mixing zone. Structural analysis revealed that the interaction between FA and RS through non-covalent bonds. Meanwhile, the addition of FA enhanced the disintegration temperature, reduced the iodine binding capacity of RS. X-ray diffraction results revealed that the diffraction peaks intensity of RS and RS/FA complexes in mixing zone, melting zone, and die were all decreased, and the relative crystallinity values of RS/FA was greater than that of RS in melting and die zone. Moreover, for the extrudate, the short-range ordered structure, molecular weight (Mw), number-average molecular weight (Mn) and the intensity of signals corresponding to α-1,4 and α-1,6 glycosidic linkages were increased with the incorporation of FA. Overall, the obtained findings provided a data support for understanding the formation mechanism of extruded RS/FA.

研究了阿魏酸（FA）对大米淀粉（RS）挤压过程中形态、结晶和精细结构的影响。结果表明，FA包裹在淀粉基质中，并以混合区团聚体的形式存在。结构分析表明，FA与RS通过非共价键相互作用。同时，FA的加入提高了RS的分解温度，降低了RS的碘结合能力。x射线衍射结果表明，RS和RS/FA配合物在混合区、熔化区和模具中的衍射峰强度均降低，RS/FA的相对结晶度大于RS在熔化区和模具中的相对结晶度。此外，随着FA的加入，挤出物的近程有序结构、分子量（Mw）、数平均分子量（Mn）以及α-1,4和α-1,6糖苷键对应的信号强度均有所增加。综上所述，所得结果为理解挤压RS/FA的形成机制提供了数据支持。

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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 : 2026-01-08 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。

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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 : 2026-01-07 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。

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