Journal of Food Process Engineering最新文献

{"title":"Optimizing Pulsed Magnetic Field Parameters for Microbial Safety and Quality in Orange Juice","authors":"T. Pandiarajan,&nbsp;S. Dharani,&nbsp;Abhipriya Patra,&nbsp;S. Ganapathy,&nbsp;M. Balakrishnan,&nbsp;V. Arun Prasath","doi":"10.1111/jfpe.70123","DOIUrl":"https://doi.org/10.1111/jfpe.70123","url":null,"abstract":"<div>\u0000 \u0000 <p>Nonthermal technologies have garnered significant attention for fruit juice preservation due to the increasing consumer demand for fresh, high-quality, and nutritious products. These methods, being eco-friendly, effectively inactivate microorganisms and enzymes without compromising the sensory and nutritional qualities of juices. Among these, pulsed magnetic field (PMF) technology is a promising technique that involves exposing liquid foods to a magnetic field in the form of pulses, exhibiting a bactericidal effect without any rise in temperature. The study aimed to develop a PMF processing system capable of generating low-frequency, high-intensity oscillating magnetic fields and optimized its application on orange juice at varying concentrations (10%, 15%, and 20%), magnetic field intensities (2, 4, and 6 T), and treatment times (5, 10, and 15 min). Additionally, the process conditions were optimized to preserve the nutritional quality, sensory properties, and microbial safety of orange juice. Fresh orange juice had an initial bacterial load of 2.09 × 10⁶ CFU/mL, which was reduced to 1.43 × 10⁴ CFU/mL at 4 T for 15 min in 15% juice. Similarly, yeast and mold counts decreased from 1.85 × 10⁵ to 1.68 × 10⁴ CFU/mL in 20% juice. The nonthermal nature of PMF was confirmed by negligible temperature rise. Posttreatment, <i>L</i>-values ranged from 82.4 to 83.79, decreasing to 80.2–82.55 during storage, while <i>b</i>-values ranged from 16.48 to 16.96, slightly reducing to 16.34–16.86. Viscosity for 10% juice ranged from 0.0645 to 0.0687 Pas posttreatment, reducing to 0.06–0.0648 Pas after 10 days. Minimal pH variation was observed. The optimal PMF treatment (4 T, 15 min, 20% concentration) effectively reduced microbial load while preserving juice biochemical (pH, color) and rheological (viscosity) during storage at 4°C. PMF-treated orange juice showed minimal changes in color, viscosity, and microbial stability during refrigerated storage. The absence of heat-related degradation ensures retention of quality attributes. This study demonstrates that PMF is a viable, nonthermal alternative for processing high-acid fruit juices, providing a balance between microbial safety and quality preservation.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143938906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the Quantitative Damage of Apple Based on Convolutional Neural Network Combined With Mass Compensative Method","authors":"Bin Li,&nbsp;Yi-rong Wan,&nbsp;Xia Wan,&nbsp;Shang-tao Ou-yang,&nbsp;Yan-de Liu","doi":"10.1111/jfpe.70128","DOIUrl":"https://doi.org/10.1111/jfpe.70128","url":null,"abstract":"<div>\u0000 \u0000 <p>Nondestructive quantitative analysis of fruit damage can not only provide technical support for fruit quality testing, but also provide the theoretical basis for the improvement of fruit packaging and transportation conditions. However, the models of quantitative prediction of fruit damage are susceptible to influence by own factors (size). Therefore, in order to improve the accuracy of quantitative prediction of fruit damage, one-dimensional convolutional neural network (1D-CNN) combined with the mass parameter method was proposed. The study results show that the performances of the 1D-CNN models are improved by 3.4%–7.0% compared to the traditional models. The performances of 1D-CNN prediction models based on the mass compensation have been improved by 7.5%–10.3% compared with the precompensation. In conclusion, the 1D-CNN models based on the masscompensation have positive effects in eliminating the influence of apple size on the quantitative prediction models of apple damage.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Osmotic Dehydration-Assisted Freezing at Different Pressure Rates on Mass Transfer and Quality of Fresh-Cut Apple","authors":"Kehinde Peter Alabi,&nbsp;Adeshina Fadeyibi,&nbsp;Kehinde Raheef Adebayo,&nbsp;Lanre Olanipekun Gabriel","doi":"10.1111/jfpe.70133","DOIUrl":"https://doi.org/10.1111/jfpe.70133","url":null,"abstract":"<div>\u0000 \u0000 <p>This study aims to enhance the preservation of fresh-cut apple slices by applying osmotic dehydration in sucrose solutions prior to high-pressure shift freezing (HPSF). Apple slices (1 × 1 × 1 cm) were osmotically dehydrated under varying sucrose concentrations (45°Bx, 55°Bx, 65°Bx), temperatures (25°C, 35°C, 45°C), and durations (30, 60, 90 min) before freezing at pressures of 200 and 240 MPa. Mass transfer (water loss, solid gain), drip loss, total soluble solids (TSS), sensory qualities (color, sweetness, flavor, texture, acceptability), and microstructural changes (via light microscopy) were assessed using standard methods, with statistical analysis applied to evaluate differences. Optimal pretreatment at 65°Bx, 35°C, and 30 min followed by freezing at 240 MPa increased TSS and reduced drip loss by 93% compared to untreated samples. Sensory qualities and microstructure were significantly better preserved in treated samples (<i>p</i> ≤ 0.05). The study demonstrates that combining osmotic dehydration and HPSF under optimized conditions enhances fresh-cut apple preservation, offering valuable applications for the food industry.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143938907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Structural–Mechanical Property of Rice Starch Gels for Food 3D Printing and Flexible Sensing","authors":"Nuo Yan,&nbsp;Liu Yang,&nbsp;Xuan Xiao,&nbsp;Pingan Huang,&nbsp;Can Shu,&nbsp;Shaoyun Song,&nbsp;Hai Tan","doi":"10.1111/jfpe.70126","DOIUrl":"https://doi.org/10.1111/jfpe.70126","url":null,"abstract":"<div>\u0000 \u0000 <p>Starch materials have been widely used in fields of flexible sensing and food 3D printing; rice starch (new source) needs in-depth research for related applications. In this research, a mixing-temperature controlling-cold drying preparation scheme for rice starch gel with stable performance is proposed. In order to in-depth analyze the rice starch internal structural–mechanical behavior, a developed texture analyzer with in situ observation is self-established; the gel internal structure, mechanical behavior, and loading capacity are in-depth analyzed. Effects of rice starch kind (indica, japonica, glutinous) and starch concentration are investigated on internal structure evolution and mechanical behavior. Experimental results show the starch gel is of crosslink network internal structure with pores. The starch dry gel compression force–displacement curve exhibits an S-shaped relation. It can be divided into three stages: elastic deformation, micro-cracking, and overall fracture, matching with rice dry gel internal structure evolution. Rice dry gel peak bearing force order is glutinous starch &gt; indica starch &gt; japonica starch, negatively correlated with internal network structure pore size. The dry gel internal pore size turns out to be small with increasing rice starch concentration. Based on rice starch dry gel mechanical and micro-structure analysis, rice starch gels exhibit optimal structure for application.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Particle Size Distribution Model for Optimizing Coffee Grind Consistency","authors":"Kitiphong Khongphinitbunjong,&nbsp;Sirirung Wongsakul,&nbsp;Theeradech Mookum","doi":"10.1111/jfpe.70129","DOIUrl":"https://doi.org/10.1111/jfpe.70129","url":null,"abstract":"<div>\u0000 \u0000 <p>The particle size distribution (PSD) of ground coffee significantly influences its extraction, flavor, and overall beverage quality. This study aimed to develop, validate, and optimize PSD models for the coffee grinding process. Arabica coffee beans subjected to light, medium, and dark roasting were ground to 12 distinct levels ranging from fine to coarse. The PSDs were examined using laser diffraction. The Rosin–Rammler (RR) model was applied to the data by employing quasi-Newton (QN) and Levenberg–Marquardt (LM) optimization methods. Indicators of uniformity, including the uniformity index <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mi>k</mi>\u0000 </mfenced>\u0000 </mrow>\u0000 <annotation>$$ (k) $$</annotation>\u0000 </semantics></math>, coefficient of uniformity (Cu), size span (Span), and coefficient of variation (CV), were computed and subsequently compared across various grinding levels and roasting types. Both the QN and LM methodologies demonstrated an excellent fit to the PSD data, evidenced by high <i>R</i>² values across all grinding levels. The medium grinding level exhibited optimal uniformity, as indicated by the high <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>k</mi>\u0000 </mrow>\u0000 <annotation>$$ k $$</annotation>\u0000 </semantics></math> and low Cu, Span, and CV values. Although the medium roast displayed slightly superior uniformity, the Kruskal–Wallis analysis revealed no statistically significant differences in grind consistency across the various roast types. This study demonstrated the effectiveness of PSD modeling for characterizing coffee grind consistency. The results provide insights for optimizing grinding parameters to improve coffee quality, while suggesting that roast type may have a limited influence on grind uniformity compared to grinder settings. The developed models and approaches can inform coffee grinding processes and quality control.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143926141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Early Damage in Kiwifruit Based on Near-Infrared Technology","authors":"Pengpeng Ma,&nbsp;Jun Sun,&nbsp;Sunli Cong,&nbsp;Chunxia Dai,&nbsp;Zhentao Cai,&nbsp;Kunshan Yao,&nbsp;Xin Zhou,&nbsp;Xiaohong Wu,&nbsp;Jingyi Liu","doi":"10.1111/jfpe.70130","DOIUrl":"https://doi.org/10.1111/jfpe.70130","url":null,"abstract":"<div>\u0000 \u0000 <p>The internal quality of kiwifruit directly affects its taste. During harvesting or transportation, kiwifruit sustained surface invisible damage due to collisions or pressure. To conduct non-destructive detection of minor mechanical damage in kiwifruit, this study investigated two widely cultivated varieties in China. Near-infrared spectroscopy was employed to collect spectral data from both intact samples and early-damaged samples. These datasets were utilized to develop classification models aimed at assessing the extent of damage in kiwifruit. Initially, the first derivative method was applied as a spectral preprocessing technique. Three feature selection methods—Competitive Adaptive Reweighted Sampling (CARS), Genetic Algorithm (GA), and Bootstrap Soft Shrinkage (BOSS)—were implemented to extract characteristic wavelengths from the preprocessed spectra. Subsequently, classification models were constructed based on both the selected feature spectra and the original spectra. A novel Stacking ensemble model was developed using Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Extreme Gradient Boosting (XGBoost) as first-level classifiers, with Logistic Regression serving as the second-level classifier. By establishing training and testing datasets while comparing performance metrics against those of individual first-level classifiers, the study evaluated the model's efficacy. The results indicated that the Stacking model consistently demonstrated high accuracy across all feature selection algorithms; notably, when combined with CARS feature selection, it achieved accuracy rates of 100% and 98.60% on training and testing sets, respectively, underscoring its superior performance. This suggested that integrating the Stacking model with CARS provided optimal predictive capabilities for this dataset. In conclusion, employing near-infrared spectroscopy for classifying varying degrees of damage in kiwifruit was not only feasible but also offered a robust reference point for evaluating market-related damage levels.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomics Approach to Site-Specific Differential Analysis of Heat-Processed Chicory","authors":"Wataru Kobayashi,&nbsp;Ayumi Tomizawa,&nbsp;Misaki Kurawaka,&nbsp;Masako Abe,&nbsp;Akio Watanabe,&nbsp;Sonoko Ayabe","doi":"10.1111/jfpe.70099","DOIUrl":"https://doi.org/10.1111/jfpe.70099","url":null,"abstract":"<div>\u0000 \u0000 <p>Chicory (<i>Cichorium intybus</i> L.; witloof) contains bioactive compounds such as sesquiterpene lactones (SLs) and inulin, providing potential health benefits. However, the effects of cooking and processing on chicory's nutritional composition remain underexplored, particularly regarding its metabolite profile during low-temperature processing. We aimed to investigate how different heating temperatures and processing times affect the nutritional composition of the whole chicory plants. We employed a targeted metabolomics approach to analyze the impact of low (30°C, 60°C) and high (100°C, microwave)-temperature processing on chicory's nutritional profile, focusing on amino acids, sugars, organic acids, fatty acids, and other metabolites in both leaves and roots. Lower temperatures (≤ 60°C) influenced the concentration of nutritional components (sugars, free amino acids, organic acids), branched-chain amino acids (which improve exercise performance), and γ-aminobutyric acid (which has antihypertensive effects), depending on the composition of raw chicory. In contrast, high temperatures (100°C) and microwave processing, especially in chicory leaves, induced the formation of low molecular weight sugars from polysaccharides and glycosides, reduced free amino acid concentrations, and triggered heat-induced aminocarbonyl reactions. This study provides valuable information for improving the flavor profile and potential health benefits of chicory by identifying optimal heat processing parameters to maintain desirable nutritional value.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the Fouling Behavior of Whey Protein Concentrate in Polymeric Heat Exchangers","authors":"Philipp Pelz,&nbsp;Paul Egorov,&nbsp;Julian Schulz,&nbsp;Dennis Lukas,&nbsp;Sarah Brune,&nbsp;Rebekka Biedendieck,&nbsp;Erik von Harbou,&nbsp;Hans-Jörg Bart","doi":"10.1111/jfpe.70096","DOIUrl":"https://doi.org/10.1111/jfpe.70096","url":null,"abstract":"<p>Fouling in heat exchangers, particularly in the dairy industry, presents significant operational challenges, increasing energy consumption and maintenance costs. Polymeric heat exchangers, with their favorable fouling mitigation behavior, offer a potential solution to reduce these impacts. A mechanistic and an empirical fouling model were developed to predict the unique detachment mechanism of whey protein concentrate (WPC) fouling layers on polyetheretherketone (PEEK) heat exchanger surfaces caused by boiling beneath the fouling deposits. Model parameters were estimated using experimental data of the total fouling mass. Fouling experiments were carried out for different process conditions. To identify the dependency of the model parameters on the process condition, symbolic regression was applied. Previously unseen experimental data was used to validate the prediction capabilities of the models, which aim to predict fouling mass and, in case of the mechanistic model, thermal resistance. The results demonstrate that the empirical model predicts the fouling mass with an accuracy of ±20% for untrained operating conditions within the boundaries of the training set. Larger deviations (&lt; 70%) were observed for the mechanistic model. When predicting fouling mass outside the training data set, the empirical model fails to do so when extrapolating. While the mechanistic model provides better results compared to the empirical model when extrapolating, an error of &lt; 130% remains. The calculated thermal resistance shows discrepancies, particularly for high WPC concentrations and high heat flux. The findings suggest that PEEK heat exchangers may significantly reduce fouling-related downtime and energy costs in dairy processing.</p>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfpe.70096","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Predicting Moisture Content in Microcrystalline Cellulose During Fluidized Bed Drying Using Machine Learning Techniques","authors":"Armando Zanone,&nbsp;Gustavo Zamboni do Carmo,&nbsp;Martin Ropke,&nbsp;Matheus Rafael Detlinger Penteriche,&nbsp;Raphael Marchetti Calciolari,&nbsp;Kaciane Andreola","doi":"10.1111/jfpe.70119","DOIUrl":"https://doi.org/10.1111/jfpe.70119","url":null,"abstract":"<p>This research aims to develop a nonintrusive method for predicting moisture content in a fluidized bed dryer using machine learning techniques. Data were collected from experiments using microcrystalline cellulose, with sensors measuring temperature and air relative humidity at various points in the drying process. The data were preprocessed, normalized, and used to train several machine learning models, including ridge regression, support vector machines (SVR), and random forest regressors. The ridge regression model emerged as the most effective, achieving a prediction accuracy of 96.5%. The study employed k-fold cross-validation to ensure model robustness and avoid overfitting. The results demonstrate the feasibility of using machine learning for real-time moisture prediction, significantly enhancing the efficiency and accuracy of the drying process. This approach eliminates the need for process interruption for moisture content measurement, thereby improving operational efficiency and product quality.</p>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfpe.70119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143914121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Evaporative Cooling Systems for Perishables in Sub-Saharan Africa—A Review","authors":"Robert Lufu,&nbsp;Alemayehu Ambaw,&nbsp;Umezuruike Linus Opara","doi":"10.1111/jfpe.70127","DOIUrl":"https://doi.org/10.1111/jfpe.70127","url":null,"abstract":"<p>Postharvest food losses in the supply chain are currently estimated at 20% in the Sub-Saharan Africa region. In Sub-Saharan Africa, where the loss of fruits and vegetables can be particularly high, incorporating cold chain systems into value chains is an important strategy. Nevertheless, the absence of fundamental infrastructure and managerial expertise required to facilitate the advancement of cohesive cold chains, especially in rural regions, poses a substantial obstacle. Evaporative cooling has been suggested as an inexpensive cooling substitute for increasing the shelf life of fresh fruits and vegetables in hot, dry climates. Evaporative cooling is not a new concept; its use in buildings can be traced back thousands of years. However, renewed interest is spurring innovation in evaporative-cooling technologies. This comprehensive review explores the fundamental concepts and applications of different classes of evaporative cooling systems, with a particular focus on the preservation of postharvest quality of fruits and vegetables, and its economic implications. In addition, the review discusses the role of desiccant/dehumidification systems in improving the performance of evaporative cooling and furthermore presents a decision support system as a tool that promotes the effective use of evaporative coolers. The review underscores the potential of evaporative coolers as a viable solution for short-term postharvest preservation of horticultural produce. This system not only significantly lowers storage temperature, but also elevates the relative humidity within the storage environment, a critical factor in preserving the freshness and quality of the stored commodities. Thus, this paper presents a compelling case for the adoption of evaporative cooling technologies in the agri-food sector.</p>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfpe.70127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}