Journal of Food Engineering最新文献

{"title":"Particle image velocimetry analysis of indica rice motion in moderate pressure polishing","authors":"Linfeng Zhu,&nbsp;Xiaopeng Liu,&nbsp;Yonglin Zhang,&nbsp;Zhigang Hu,&nbsp;Beihai Wang,&nbsp;Qiang Yin","doi":"10.1016/j.jfoodeng.2026.112994","DOIUrl":"10.1016/j.jfoodeng.2026.112994","url":null,"abstract":"<div><div>Conventional iron-roller polishing and over-processing often cause excessive breakage of indica rice. To overcome this limitation, we developed a spherical ribbed, flexible friction–collision polishing method. We applied particle image velocimetry (PIV) to explore rice polishing, representing the first attempt of this technology in this field. Specifically, PIV was applied to analyze rice grain motion in the polishing chamber, focusing on the effects of the roller speed and pressure gate opening on breakage and polishing quality. The results showed that grain trajectories followed regular global patterns, with local variations under different operating conditions. Alternating high- and low-speed flows reduced inter-grain collisions and significantly lowered the breakage compared with traditional polishing. At 4-mm gate opening, rice movement was constrained, leading to extended residence times and high breakage (4.53–6.21 %). At 8–12 mm openings, moderate pressure and optimal grain deflection angles were achieved. Within this range, speeds of 1000–1200 r min⁻¹ yielded spiral grain trajectories along the chamber wall, ensuring uniform polishing with low breakage (2.48–3.31 %). In contrast, excessive speeds (1200–1400 r min⁻¹) caused over-polishing, while a 16-mm gate opening resulted in insufficient pressure, high chalkiness and poor surface quality. This study provides a theoretical basis for optimising polishing machine parameters to minimise breakage and improve the processing quality of indica rice.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 112994"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077119","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}

{"title":"High internal phase emulsions stabilized by milk protein-arabinoxylan-quercetin ternary complex: Enhanced environmental stability and fat digestive property (Milk protein-AX-Q complex-stabilized HIPEs: Stability and digestion)","authors":"Xuenan Gao ,&nbsp;Peizhu Liu ,&nbsp;Sirong Li ,&nbsp;Olayemi Eyituoyo Dudu ,&nbsp;Yanjun Li ,&nbsp;Yan Li ,&nbsp;Hongfang Yang ,&nbsp;Jinju Cheng ,&nbsp;Tingsheng Yan","doi":"10.1016/j.jfoodeng.2026.112997","DOIUrl":"10.1016/j.jfoodeng.2026.112997","url":null,"abstract":"<div><div>In this study, ternary complexes were constructed using whey protein concentrate (WPC), sodium caseinate (SC), arabinoxylan (AX), and quercetin (Q), named WPC-AX-Q and SC-AX-Q, respectively, and their structural and functional properties were systematically characterized and compared with individual protein, protein/AX mixture and protein-AX binary conjugate. High internal phase emulsions (HIPEs) were also prepared to investigate their effects on the stability and fat digestion in the HIPEs. Results from fluorescence spectroscopy and Fourier transform infrared spectroscopy (FTIR) revealed notable alterations in the structure of milk proteins, suggesting interactions among milk proteins, AX and Q. Dynamic investigation into interfacial characteristics revealed that, in comparison to proteins alone, the ternary complexes exhibited lower interfacial tension and greater adsorption ability at the oil-water interface. Additionally, the ternary complexes showed a marked decrease in surface hydrophobicity and a notable increase in solubility, along with the most powerful foaming, emulsifying, and antioxidant capabilities compared with protein, protein/AX mixture and protein-AX binary conjugate. The stability of HIPEs stabilized by the ternary complexes was confirmed through rheological and microstructure studies. HIPEs stabilized by the ternary complexes exhibit superior environmental and in vitro digestive stability, and can mitigate the extent of lipid oxidation, delay and reduce the release of free fatty acids. This research offers theoretical backing for how the combined effect of polysaccharides and polyphenols impacts protein structure and properties, as well as the enhancement of fat digestion traits in HIPEs.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112997"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074716","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}

{"title":"Spectral–spatial fusion attention transformer for brewing wheat variety identification and food-processing raw-material quality evaluation","authors":"Liangliang Xie ,&nbsp;Hao Zhang ,&nbsp;Juan Wang ,&nbsp;Yuansong Peng ,&nbsp;Xiang Wan ,&nbsp;Haili Yang ,&nbsp;Xinjun Hu ,&nbsp;Manjiao Chen ,&nbsp;Jianping Tian ,&nbsp;Dan Huang ,&nbsp;Anying Cai ,&nbsp;Rongzhi Wang ,&nbsp;Jianping Yang ,&nbsp;Kaiyang Yuan ,&nbsp;Haonan Yi ,&nbsp;Shunbo Zhang","doi":"10.1016/j.jfoodeng.2026.112993","DOIUrl":"10.1016/j.jfoodeng.2026.112993","url":null,"abstract":"<div><div>Current spectral reconstruction methods exhibit limitations in jointly modeling spatial and spectral features, making it difficult to fully capture complex spectral information and thereby constraining reconstruction fidelity. To address this challenge, this paper proposes a novel Multi-stage Spectral–Spatial Fusion Attention Transformer (MSFAT), designed to enable efficient fusion and collaborative modeling of spatial-spectral data, ultimately improving the accuracy of spectral reconstruction. The core innovation lies in the development of the Spectral–Spatial Fusion Attention Module (SFAM), which integrates a dual frequency-spatial attention mechanism. By combining fast-Fourier transform with channel attention, SFAM effectively extracts global spectral dependencies and local spatial features synergistically. This mechanism allows SFAM to capture long-range spectral correlations in the frequency domain while emphasizing critical spatial details, significantly boosting the model's capacity to handle complex hyperspectral data. Experimental results validate the efficacy of MSFAT, showing a 0.37 dB improvement in PSNR over MST++ for hyperspectral image reconstruction, along with a 5.6 % reduction in MRAE and a 4.8 % decrease in RMSE. Furthermore, a one-dimensional (1D)-CNN-based brewing wheat variety classification model was developed using the reconstructed hyperspectral imaging data from MSFAT. This model achieved a test accuracy, recall, and F1 score of 96.66 %, 96.66 %, and 96.63 %, respectively—representing a 2.08 % accuracy improvement over MST++ and closely approximating the performance obtained using original spectral data (97.08 %). These findings demonstrate that integrating MSFAT with 1D-CNN offers a high-precision and cost-effective solution for the identification of brewing wheat raw materials, underscoring its broad potential for applications in smart agriculture and food composition analysis.In addition, the spectral data reconstructed by the proposed model can be further applied to analyze physicochemical characteristics relevant to food processing, such as starch, protein, and moisture content. This RGB-based spectral reconstruction approach provides a new avenue for raw-material sorting, quality assessment, and process monitoring in brewing and other food-processing operations.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 112993"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185769","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}

{"title":"Deep visual measurement of corn starch particles size via RIS-UNet","authors":"Xuyan Zhao ,&nbsp;Wenlu Zhu ,&nbsp;Xiangyang Li ,&nbsp;Hanwen Niu ,&nbsp;Qiao Wang ,&nbsp;Qunfeng Niu ,&nbsp;Li Wang ,&nbsp;Yuan Zhang","doi":"10.1016/j.jfoodeng.2026.112982","DOIUrl":"10.1016/j.jfoodeng.2026.112982","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112982"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975543","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}

{"title":"Moisture adsorption characteristics of freeze-dried royal jelly: thermodynamic properties, modeling, and assessing microstructural changes","authors":"Rachida Ouaabou ,&nbsp;Lahcen Hssaini ,&nbsp;Abderrahim Alahyane ,&nbsp;Abdessamad Lahrach ,&nbsp;Nadia Massaoudi ,&nbsp;Jalal Isaad ,&nbsp;EL amine Ajal ,&nbsp;Aadil Bajoub ,&nbsp;Said Ennahli","doi":"10.1016/j.jfoodeng.2026.112989","DOIUrl":"10.1016/j.jfoodeng.2026.112989","url":null,"abstract":"<div><div>This study aimed to investigate the sorption characteristics of royal jelly (RJ) to better understand how it interacts with moisture under varying conditions. We employed gravimetric static techniques to generate sorption isotherms, using chemical salts to precisely control water activity (a_w) over a range of 0.05–0.90. The experiments were conducted at three different temperatures 30 °C, 40 °C, and 50 °C. To gain further insights, we applied the Clausius-Clapeyron equation to calculate the integral thermodynamic properties of the RJ water system under constant spreading pressure. Our goal was to determine the best storage conditions to maintain the quality and extend the shelf life of royal jelly powder.</div><div>The results showed that royal jelly's sorption isotherms followed a Type II sigmoidal pattern, meaning that moisture content increased as water activity rose. Among the models we tested, the Enderby model provided the most accurate fit to our experimental data. Furthermore, the analysis of integral entropy revealed a minimum value when the moisture content ranged between 4 and 5 % (dry basis) and the relative humidity was between 0.15 and 0.23. These specific conditions were identified as ideal for prolonging the shelf life and preserving the quality of royal jelly. Scanning Electron Microscopy revealed an agglomerated structure, and thermal analysis showed a multi-stage degradation process, with the major mass loss occurring above 246 °C. Overall, this comprehensive investigation into RJ's sorption properties, including a detailed assessment of its thermodynamic behavior, offers valuable insights for optimizing its storage and preservation, ensuring the integrity of this highly nutritious food product.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 112989"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185765","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}

{"title":"Surplus bread fermentation by Pleurotus ostreatus monitored by magnetic resonance imaging","authors":"Maja Musse ,&nbsp;Isabelle Gimbert ,&nbsp;Yves Diascorn ,&nbsp;Stéphane Quellec ,&nbsp;Sylvain Challois ,&nbsp;Craig B Faulds ,&nbsp;Tiphaine Lucas","doi":"10.1016/j.jfoodeng.2026.112967","DOIUrl":"10.1016/j.jfoodeng.2026.112967","url":null,"abstract":"<div><div>This study addresses circular approaches to reuse food surpluses and losses, focusing on starchy products like bread that are fermented by fungi to produce a nutrient-rich biomass. Traditional methods have evaluated fungal growth at a macro scale, but improving the processing of heterogeneous substrates, such as highly porous ones, requires detailed insight into local fungal activity and growth. Magnetic Resonance Imaging (MRI) offers a unique advantage by simultaneously capturing morphological details and water distribution. The present work aimed to assess MRI as a non-destructive, non-invasive tool for monitoring spatial and temporal changes in biomass during solid-state fermentation (SSF) of bread slices with <em>Pleurotus ostreatus</em>. MRI protocols were developed to measure morphological changes and map transverse NMR relaxation times. MRI data were validated against conventional measurements of water content and dry matter, with further evaluation through fibre and protein analyses to determine added nutritional value.</div><div>Bread was shown to be a suitable substrate for cultivating fungi, producing a nutritionally-valuable biomass rich in soluble fibre and changes in some amino acid composition. T₂ relaxation was an effective focus to monitor mycelial growth through association to mycelial hydrolysis and water content distribution. T₂ mapping revealed significant heterogeneities in the bread, which persisted long under experimental conditions employed (approximatively one month). While the observed changes were at the macroscopic level, future microscale investigations using multi-exponential T₂ could help isolate fungal signals and enable quantitative biomass assessment.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112967"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975542","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}

{"title":"Dual-encapsulated γ-cyclodextrin liposomal hydrogel beads crosslinked with Ca2+-SHP for pH-responsive and targeted lutein delivery","authors":"Lanxin Zhang ,&nbsp;Shengnan Wang ,&nbsp;Xuejing Tian ,&nbsp;Rui Wang ,&nbsp;He Liu","doi":"10.1016/j.jfoodeng.2026.112995","DOIUrl":"10.1016/j.jfoodeng.2026.112995","url":null,"abstract":"<div><div>In this study, core-shell hydrogel microspheres were synthesized through cross-linking of soybean hull polysaccharides (SHP) with Ca²⁺ and subsequently integrating them with γ-CD lutein liposomes (γ-CD Lu-lip) to form γ-CD Lu-lip@SHP beads. FTIR confirmed hydrogen bonding as the primary interaction between γ-CD Lu-lip and SHP. The successful encapsulation of lutein was further confirmed by XRD, DSC, and FTIR analyses in both γ-CD Lu-lip and γ-CD Lu-lip@SHP beads, with an encapsulation efficiency of 84.14 %. The resulting microspheres exhibited pH-responsive release behavior, characterized by Fick diffusion at pH 2.0, 4.0 and 6.8 values and non-Fick diffusion at pH 7.4. This pH-dependent behavior enabled controlled and sustained lutein release under simulated gastrointestinal conditions, ultimately enhancing lutein's oral bioaccessibility to 29.21 %. This study reveals that γ-CD Lu-lip@SHP bead systems can effectively deliver and protect environmentally labile bioactive compounds through controlled release mechanisms.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112995"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074718","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}

{"title":"Enhancing the oral processing and swallowing performance of cod soft gels","authors":"Xiliang Yu ,&nbsp;Yue Wang ,&nbsp;Lin Han ,&nbsp;Shiyi Liu ,&nbsp;Michelle Ji Yeon Yoo ,&nbsp;Xiuping Dong","doi":"10.1016/j.jfoodeng.2025.112937","DOIUrl":"10.1016/j.jfoodeng.2025.112937","url":null,"abstract":"<div><div>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 <em>in vitro</em> 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&gt;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.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"412 ","pages":"Article 112937"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975541","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}

{"title":"Rapid traceability of coffee bean by integrating an electronic tongue with knowledge distillation and transfer learning","authors":"Suchao Xu ,&nbsp;Zhiqiang Wang ,&nbsp;Tianrui Han ,&nbsp;Jinyang Zhang ,&nbsp;Zhen Li ,&nbsp;Yubin Lan","doi":"10.1016/j.jfoodeng.2026.113001","DOIUrl":"10.1016/j.jfoodeng.2026.113001","url":null,"abstract":"<div><div>The origin of coffee beans plays a crucial role in determining their flavor, quality, and market value. Conventional traceability methods possess several disadvantages, such as high costs, complex procedures, and time-consuming operations. This study proposes a rapid coffee beans traceability method by using an electronic tongue (ET) integrated with knowledge distillation and transfer learning. First, the taste fingerprint signals of coffee beans sourced from diverse regions were collected by a self-developed ET system. The continuous wavelet transform (CWT) was applied to convert the 1D signal into 2D spectrograms for effectively characterizing the time-frequency features within the ET signals. The resulting spectrograms were subsequently fed into the heterogeneous knowledge distillation framework to perform pattern recognition. Specifically, this framework employs a Vision Transformer (ViT) as the teacher model, which is optimized through transfer learning to strengthen its generalization performance under limited ET samples. A lightweight EfficientNet is adopted as the student model and trained under the guidance of the optimized teacher to achieve accurate discrimination among different coffee beans. Experimental results demonstrate that the distilled EfficientNet not only maintains a low computational cost but also achieves superior origin recognition performance compared with conventional deep learning models, with an accuracy of 98.33 % and a parameter count of only 11.3 M. This work provides a rapid, low-cost, and portable analytical approach for coffee bean origin traceability, making it easily deployed on edge or portable devices for on-site detection.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 113001"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185785","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}

{"title":"A computational study for batch-level diagnostics in industrial extrusion using interpretable machine learning and counterfactual analysis","authors":"Mads Kjærgaard Nielsen ,&nbsp;Jacob Mikkelsen","doi":"10.1016/j.jfoodeng.2026.112999","DOIUrl":"10.1016/j.jfoodeng.2026.112999","url":null,"abstract":"<div><div>Industrial feed extrusion involves complex interactions between raw materials, processing conditions, and product outcomes. This study develops machine learning models to predict critical process and product attributes across key stages of extrusion, conditioning, extrusion, and drying, based on a large-scale, two-year dataset with high batch and recipe variability. Ensemble methods and neural networks are applied to model outcomes such as specific mechanical energy, die pressure, bulk density, hardness, and the chemical composition of final products. Model performance was evaluated using cross-validation and test data, with XGBoost achieving the highest predictive accuracy. R² values exceeded 0.90 for specific mechanical energy and compositional attributes and were around 0.80 for physical pellet characteristics and die pressure. Beyond prediction, model interpretability was addressed using Shapley Additive Explanations to uncover key variable interactions and support process transparency. These insights enabled simulation of counterfactual scenarios to assess how adjusting upstream parameters could potentially influence product outcomes. The approach demonstrates how machine learning can support targeted batch optimization and reverse engineering in industrial settings, offering a scalable framework for integrating data-driven modelling into complex manufacturing workflows.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"413 ","pages":"Article 112999"},"PeriodicalIF":5.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077118","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}