Journal of Food Engineering最新文献

{"title":"A real-time predictive complementary relative phase shifting strategy for dual-port solid-state microwave heating process","authors":"Arjun Ghimire,&nbsp;Jiajia Chen","doi":"10.1016/j.jfoodeng.2025.112544","DOIUrl":"10.1016/j.jfoodeng.2025.112544","url":null,"abstract":"<div><div>Relative phases between two sources can be precisely and dynamically controlled in dual-port microwave processes. Previously, a combined sweeping and complementary relative phase strategy was used to deliver more uniform heating than microwave heating processes using fixed or orderly sweeping relative phases. However, extensive relative phase sweeping (e.g., ∼44% of the 3-min whole heating time) is needed to collect relative phase-dependent thermal contributions to implement the complementary strategy. This limitation can be addressed by utilizing the constructive and destructive dual-port microwave interactions to develop a more efficient complementary strategy. Built upon the observation that the spatial microwave power dissipation density varies in a sinusoidal wave shape, this study developed a Predictive-Complementary relative phase strategy. Instead of collecting relative phase-dependent thermal contributions using extensive relative phase sweeping, the predictive approach only collected three thermal contributions at relative phases of 0°, 90°, and 180° and then predicted all others for implementing the complementary strategy. The predicted thermal contributions were validated by comparing them with the experimentally collected ones in dual-port microwave heating of gellan gel samples, which showed good correlations with R² values between 0.91 and 0.97 and Root Mean Square Error (RMSE) values between 0.17 and 1.02 °C. By comparing with other reported Fixed, Sweeping, and Sweeping-Complementary relative phase strategies, the Predictive-Complementary relative phase strategy devoted ∼83% of the 3-min heating time in the complementary shifting stage and showed the best microwave heating uniformity and power absorption efficiency. The Predictive-Complementary relative phase strategy presented an efficient approach to predicting relative phase-dependent thermal contributions for more uniform microwave heating using complementary relative phases. The algorithm can be integrated as an advanced relative phase heating strategy in smart solid-state microwave systems.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112544"},"PeriodicalIF":5.3,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488834","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":"Pulsed electric field (PEF) pretreatment impact on the freezing and ultrasound-assisted atmospheric freeze-drying of butternut squash and yellow turnip","authors":"Beatriz Llavata,&nbsp;Gabriela Clemente,&nbsp;José Bon,&nbsp;Juan A. Cárcel","doi":"10.1016/j.jfoodeng.2025.112543","DOIUrl":"10.1016/j.jfoodeng.2025.112543","url":null,"abstract":"<div><div>This study explores the impact of the application of pulsed electric field (PEF) pretreatment in the freezing and in the power ultrasound-assisted (US) atmospheric freeze-drying (AFD) of two different products: butternut squash and yellow turnip. Two PEF pretreatments were applied, inducing cell disintegration indexes (CDI) of 0.25 and 0.75. The results showed that PEF pretreatments significantly altered the microstructure of butternut squash and yellow turnip, but in a different way. These changes led to a significant shortening of the freezing process by up to 11.6%. Although PEF pretreatments significantly affected the drying rate of AFD, the effect was maximum when combined with ultrasound-assisted AFD. However, the PEF treatment that most enhanced ultrasound-assisted drying kinetics varied between products: a moderate treatment (CDI of 0.25) was most effective for butternut squash (37.3% time reduction), while a more intense treatment (CDI of 0.75) was better in the case of yellow turnip (44.2% time reduction). These findings indicate an enhancement of the atmospheric freeze-drying process achieved through the combined application of PEF and US under adequate conditions.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"395 ","pages":"Article 112543"},"PeriodicalIF":5.3,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471555","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":"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}