Journal of Food Engineering最新文献

{"title":"Impact of pluronic type on the physicochemical properties of lecithin liposome/pluronic particles","authors":"Jihyo Lee ,&nbsp;Seung Jun Choi","doi":"10.1016/j.jfoodeng.2025.112540","DOIUrl":"10.1016/j.jfoodeng.2025.112540","url":null,"abstract":"<div><div>This study investigated how the ethylene oxide (EO) content in pluronic (70% for pluronic F127 and 80% for pluronic F108) affects the physicochemical attributes of lecithin liposome/pluronic particles characterized by a core/shell configuration. Additionally, their ability to encapsulate proteins was examined. Regardless of the EO content, the particles consistently exhibited a core/shell structure up to a lecithin/pluronic ratio of 0.2, with sizes ranging from 230 to 280 nm. Although liposome/pluronic particles maintained stability against pH alterations at 5 °C, storage above this temperature compromised their stability. This suggests that the EO content in pluronic does not significantly dictate the stability of these liposome/pluronic particles. Furthermore, these particles were able to encapsulate a model protein with a low isoelectric point (pI) with relative ease. However, attempts at modifying the liposome surface charge to a positive state for encapsulating proteins with higher pI values did not yield particles with a core/shell structure.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112540"},"PeriodicalIF":5.3,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488835","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":"Interaction of milk fat solidification and cheese cooling","authors":"R.G.M. van der Sman ,&nbsp;I.A.F. van den Hoek ,&nbsp;Y. Zhao","doi":"10.1016/j.jfoodeng.2025.112531","DOIUrl":"10.1016/j.jfoodeng.2025.112531","url":null,"abstract":"<div><div>In this paper, we report on the interaction between cooling and fat crystallization, that happens during the processing of mozzarella cheese. The analysis is performed using a novel physical model in which the Fourier equation is extended with a source term representing the latent heat released by fat solidification. The kinetics of fat solidification follow a model originally developed for chocolate, which we have modified for milk fat, using input from our Differential Scanning Calorimeter (DSC) measurements of Mozzarella cheese samples. The model parameter estimation was conducted using a structured parameter estimation method involving the Fisher Information Matrix. The DSC analysis, and simulations, supplemented by mathematical scaling analysis, clearly show that a significant amount of latent heat is released, affecting the total cooling time and cooling rate. The interaction between cooling rate and crystallization is also bidirectional, as the cooling rate determines the types and amounts of fat crystal polymorphs formed.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112531"},"PeriodicalIF":5.3,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydration of broken carioca beans: Kinetics and changes in composition and techno-functional properties","authors":"Elaine Kaspchak ,&nbsp;Eduardo Vicente ,&nbsp;Elizabeth Harumi Nabeshima ,&nbsp;Maria Teresa Bertoldo Pacheco ,&nbsp;Mitie Sonia Sadahira","doi":"10.1016/j.jfoodeng.2025.112537","DOIUrl":"10.1016/j.jfoodeng.2025.112537","url":null,"abstract":"<div><div>Maceration of bean grains reduce antinutritional substances and cooking time. The hydration of broken beans differs from that of whole beans due to their larger surface area and the absence of seed coat resistance to water penetration. Therefore, the aim of this work was to investigate the effect of temperature on the hydration kinetics of broken carioca beans and the chemical composition, and techno-functional properties of macerated flour. The hydration curve of broken grains showed no lag phase due to their larger surface area and exposed interiors. The hydration time decreased with the temperature rise and was shorter for broken beans compared to whole grains, while the equilibrium moisture content was similar. The protein, ash, carbohydrate, and lipid content of flours did not differ significantly between untreated and macerated flours. Phytic acid and moisture content were reduced in the macerated flour. Techno-functional properties remained unchanged, however the macerated showed higher viscosity and setback values obtained by rapid visco analyzer and produced a firmer and more adhesive gel. Off-flavor compounds from aldehyde, alcohol, ketone, and furan classes were more prevalent in the macerated flour, probably due to increased oxidation during processing. The results presented in this work show how hydration affects broken carioca beans providing information for improving the processing efficiency and quality of carioca bean byproducts.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112537"},"PeriodicalIF":5.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474611","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":"Intelligent sorting of pecan shelled products using hyperspectral fingerprints and deep learning","authors":"Ebenezer O. Olaniyi ,&nbsp;Christopher Kucha ,&nbsp;Priyanka Dahiya ,&nbsp;Allison Niu","doi":"10.1016/j.jfoodeng.2025.112533","DOIUrl":"10.1016/j.jfoodeng.2025.112533","url":null,"abstract":"<div><div>Post-harvest processing of tree nuts is an essential process that enhances their quality and economic value. Currently air lathe and handpicking are the prevailing methods used in the industry for sorting shelling products. However, the air lathe approach is inaccurate because it requires further handpicking of the remaining shell fragments, which is labor-intensive, subjective, and time-consuming. The aim of this paper was to explore the potential of visible near-infrared (VNIR) and near-infrared (NIR) hyperspectral imaging systems (HSI) to accurately classify pecan shelled products into three classes (“shells,” “inner-wall,” and “kernels”). The VNIR (400–1000 nm) and NIR (900–1700 nm) systems were used to acquire hyperspectral images. The extracted spectral data were used to develop four machine learning classifiers (Decision Tree (DT), Gradient Boosting (GB), Random Forest (RF), and Support vector machine (SVM)), and deep learning methods (convolutional neural network (CNN), hybrid CNN combined with long short-term memory (LSTM), and CNN-CNN-LSTM. Among the machine learning classifiers, the SVM achieved superior accuracies of 95.81%, and 96.91% for VNIR and NIR spectral data, respectively. The hybrid CNN-LSTM achieved an accuracy of 97.17% and 98.36% for VNIR and NIR spectra data, respectively, while the fused spectral developed on CNN-CNN-LSTM yielded the superior result of 99.29% among all the models. The results obtained in this study demonstrated the high potential of adopting HSI systems for the classification of pecan shelled products for intelligent sorting in the pecan processing industry.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112533"},"PeriodicalIF":5.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478849","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 review of mathematical models in unit operations of glutinous and non-glutinous rice processing","authors":"Puteri Nurain Megat Ahmad Azman ,&nbsp;Rosnah Shamsudin ,&nbsp;Norhashila Hashim ,&nbsp;Hasfalina Che Man","doi":"10.1016/j.jfoodeng.2025.112542","DOIUrl":"10.1016/j.jfoodeng.2025.112542","url":null,"abstract":"<div><div>Glutinous rice, commonly known as sticky rice, is a popular staple due to its distinct texture and high nutritional value. This review highlights a recent study on mathematical modeling in the processing stages of glutinous and non-glutinous rice, aimed at enhancing product quality while minimizing energy consumption, and provides a comprehensive assessment of various models applied in the soaking, drying, storage, and cooking operations of both types of rice. Water bath and chamber are used to soak the glutinous or non-glutinous rice. These approaches provide an extensive assessment of the rice's culinary characteristics and overall quality. Peleg, Fick's law, Lewis, Page, two-term, Newton, Henderson and Pabis, Wang and Singh, Midilli, Verna, Chung-Pfost, and others are used to predict the effects of soaking, drying, storage, and cooking on glutinous and non-glutinous rice. Thus, these effects of glutinous and non-glutinous rice processing can be understood from the kinetics and other constants of the models.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112542"},"PeriodicalIF":5.3,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478850","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":"Effects of ingredients on the gas phase of whole wheat flour dough","authors":"Xinyang Sun ,&nbsp;Ziwu Bu ,&nbsp;Simiao Wu","doi":"10.1016/j.jfoodeng.2025.112536","DOIUrl":"10.1016/j.jfoodeng.2025.112536","url":null,"abstract":"<div><div>Due to the bran-induced disruption on gluten-starch matrix that is against the gas bubble stability in a dough, it leads to unexpected changes in the foamed structure, texture and sensory properties of resultant products. This research objective was to monitor the time-dependent evolution of bubble dynamics in whole wheat flour doughs by synchrotron X-ray microtomography, and investigate how dough's gas-phase and matrix properties and its product quality were affected by wheat cultivar, bran content and endoxylanase. The median of lognormal fitted bubble size distribution (BSD) and matrix thickness distribution (MTD), <em>i.e.</em>, R_0b and R_0m, were good indicators for ingredient effects on gas bubble stability. Stronger doughs had a smaller amount of larger-sized bubbles and thicker matrix. Bran and endoxylanase effects promoted the disproportionation and matrix thickness increase. Resting extension facilitated the bubble growth and matrix thickness reduction. Therefore, a suitable utilization of wheat cultivar and endoxylanase has to be considered for developing the high-fibre dough formulation, along with final products with a satisfactory overall quality.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112536"},"PeriodicalIF":5.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465029","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":"Tuna defect classification and grading using Twins transformer","authors":"Punnarai Siricharoen ,&nbsp;Supanut Tangsinmankong ,&nbsp;Seree Yengsakulpaisal ,&nbsp;Natthanan Bhukan ,&nbsp;Wisawapan Soingoen ,&nbsp;Yutthana Lila ,&nbsp;Saranya Jongaroontaprangsee ,&nbsp;Stefan Mairhofer","doi":"10.1016/j.jfoodeng.2025.112535","DOIUrl":"10.1016/j.jfoodeng.2025.112535","url":null,"abstract":"<div><div>Ensuring the quality and safety of food products is of paramount importance within the food processing industry. Particularly in the seafood sector, the detection and classification of different quality defects in processed tuna loins poses a significant challenge, usually demanding the visual assessment by seasoned experts. This research proposes a technical solution to the tuna quality inspection using computer vision techniques to identify and localize different types of defects in contrast to what is considered the “standard” of a cleaned product, while additionally assessing the severity level of such defects affecting each individual loin. Image data of tuna defects are acquired under industrial conditions and compose two different datasets: a 4-common-defect dataset (TunaDefect-4) and a 6-extended-defect dataset (TunaDefect-6) including two additional types that are less common but of greater technical challenge. The quality grading process comprises 3 main steps. (1) Initially, preprocessing normalizes image input and augments the image dataset. (2) Then, a semantic segmentation model Twins-PCPVT-L, a pyramid vision transformer with self-attention and conditional positioning encoding, is employed for the TunaDefect-4 dataset. For the TunaDefect-6, a Twins-SVT-L, which amends the former model with locally-group self-attention and global sub-sampled attention, is used. The Twins-PCPVT-L applied to TunaDefect-4 has a mean pixel accuracy (mPA) of 93.96% and a mean IoU of 80.4%; while the Twins-SVT-L on the TunaDefect-6, results in an mPA of 83.82% and mIoU of 66.96%. (3) Lastly, the semantically segmented images are graded by severity ranging from level 0 to 4, where level 0 represents a fully cleaned loin and level 4, being the highest severity level, assigned to loins completely covered by various defects. The accuracy of severity grading is 84% for TunaDefect-4 and 76.6% for TunaDefect-6. Both models run within a total inference and processing time of approximately 0.20 s, faster than the conveyor's transport time. A web application prototype has been developed for the tuna quality classification and grading and is hosted on the Google Cloud Platform (GCP). The developed application responds in timely manner, to be used as a complementary identification and grading tool, with the potential to be integrated as an inline processing solution to further provide practicality to the industry.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112535"},"PeriodicalIF":5.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474493","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":"Printability prediction of food formulations for 3D printing using a Gaussian process regression model","authors":"Rubén Maldonado-Rosas ,&nbsp;Mariel Alfaro-Ponce ,&nbsp;Enrique Cuan-Urquizo ,&nbsp;Viridiana Tejada-Ortigoza","doi":"10.1016/j.jfoodeng.2025.112534","DOIUrl":"10.1016/j.jfoodeng.2025.112534","url":null,"abstract":"<div><div>The aim of the study was to address the research gap in printability prediction for nutritious formulations in Food 3D Printing. To this end, a predictive model to reduce trial-and-error operations was developed for formulation optimization. Printability characterization assessments were employed based on 2D and 3D tests to forecast the printability of formulations using a machine learning (ML) strategy. Starch concentration and printing temperature of formulations were used as predictors of printability. The predictive model was developed based on different feature extraction methods combined with Gaussian Process Regression (GPR) algorithms. In addition, a complementary laboratory validation was performed to determine a comparative percentage error between the GPR model predictions and the experimental measurements from an additional dataset. The GPR model was able to predict printability, reaching a RMSE value between 0.013 and 0.48%. Which means the model fit the data with accuracy, providing a reliable tool for formulation optimization. The laboratory validation demonstrated close values to those obtained by the model, further confirming its effectiveness. The comparative percentage errors from the laboratory validation varied between assessments and formulations, with percentage errors as low as 0.01%. The model, with its ability to predict the printability of formulations with different starch compositions and printing temperatures, could be a valuable tool in the food industry. It could assist in examining both the quality of 3D-printed structures and the adaptation of these formulations and printers for producing food products with customized sensory and nutritional profiles, opening up new possibilities for food production and customization.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112534"},"PeriodicalIF":5.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529383","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":"Aerogel-based oil sorbents derived from pomelo (Citrus grandis L.) peels as potential gel matrices for food applications: Formation, properties and in-vitro oral processing","authors":"Haoxin Wang ,&nbsp;Peng Wang ,&nbsp;Stefan Kasapis ,&nbsp;Tuyen Truong","doi":"10.1016/j.jfoodeng.2025.112532","DOIUrl":"10.1016/j.jfoodeng.2025.112532","url":null,"abstract":"<div><div>This study demonstrates the transformation of pomelo peel (PP) into aerogel templates for efficient rice bran oil absorption, producing effective oil sorbents. PP powder (5–10% w/w) of 125 and 250 μm particle sizes was emulsified with water, treated hydrothermally at 95 °C for 2 h, and freeze-dried to form aerogels. Upon immersion in oil, these templates formed gel-like sorbents. Aerogels with higher PP content exhibited an increase in density (from 26.65 to 77.75 mg/cm³), porosity (from 90.54% to 96.51%), and hardness (from 14.27 to 169.76 N), while cohesiveness decreased (from 40.00% to 21.59%) due to particle-to-particle interactions. The 250 μm PP-based aerogels with 5%–7% PP content demonstrated superior oil-holding capacity compared to the 125 μm ones; however, this capacity decreased as PP content increased from 8% to 10%. Microstructural analysis revealed a mix of mesopores and micropores, with mesopores dominating at lower PP concentrations. Fourier transform infrared spectroscopy (FTIR) analysis confirmed chemical changes post-treatment, yet no new peaks emerged after oil sorption, indicating a mainly physical process. Sorbents with lower PP content (5–6%) exhibited greater cohesiveness, increasing from 27.01% to 40.00%, due to particle-to-oil interaction, making them more suitable for food applications, as they broke down fully during <em>in-vitro</em> oral processing. Higher PP content (8%–10%) resulted in a high friction coefficient, rendering it unsuitable as a fat replacer. In contrast, sorbents with lower PP content sorbents (5%–7%) exhibited a decrease in lubrication as PP content increased, as indicated by measurements of oil release, droplet size, tribology, bolus fragmentation, and viscosity. This method offers potential for fat replacers and functional food ingredients.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"394 ","pages":"Article 112532"},"PeriodicalIF":5.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stabilization mechanism of oil and water emulsions by powdered buttermilk","authors":"Ramon Ramos de Paula ,&nbsp;Joslaine Jacumazo ,&nbsp;Natália Mello da Silva ,&nbsp;Rilton Alves de Freitas ,&nbsp;Luana Carolina Bosmuler Züge ,&nbsp;Agnes de Paula Scheer","doi":"10.1016/j.jfoodeng.2025.112513","DOIUrl":"10.1016/j.jfoodeng.2025.112513","url":null,"abstract":"<div><div>This study investigates the use of buttermilk powder to stabilize oil-in-water emulsions, focusing on casein as the stabilizer, the formation of Pickering particles at the oil-water interface, and the impact of heating on the size of stabilizing proteins. Emulsions were prepared with buttermilk powder dispersions, both before and after heating, and with isolated micellar casein powder. Analyses included surface characteristics, particle size, zeta potential, three-phase contact angle, rheological behavior, and macro and microscopic evaluations. The results showed that casein significantly reduces interfacial tension, playing a crucial role in emulsion stability. No significant increase in particle size was observed after heating, and zeta potential values remained constant (−25.2 mV for buttermilk and −23.2 mV for heated buttermilk), suggesting that heating does not affect particle charge. Stability was confirmed by the creaming index (CI) after seven days, with emulsions containing 5% buttermilk showing a CI of 7.62%, while emulsions with 1.28% micellar casein showed a CI of 8.61%, with no significant differences. Rheological analysis revealed a pseudoplastic behavior and an increase in the elastic modulus (G′) with stabilizer concentration. Microscopic analysis highlighted the importance of stabilizer concentration and demonstrated that the Pickering stabilization process is essential for the metastability of emulsions.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"394 ","pages":"Article 112513"},"PeriodicalIF":5.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437934","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}