Journal of Food Process Engineering最新文献

{"title":"Radio Frequency Drying Characteristics of Three Scallion Parts and Their Impacts on Qualities","authors":"Guangze Liu,&nbsp;Peiying Ruan,&nbsp;Xuejiao Li,&nbsp;Yuedong Song,&nbsp;Duanyang Geng","doi":"10.1111/jfpe.70151","DOIUrl":"https://doi.org/10.1111/jfpe.70151","url":null,"abstract":"<div>\u0000 \u0000 <p>The scallion white, scallion core, and scallion leaf, with the same mass and same layer height, respectively, were subjected to RF drying at an electrode gap of 80 mm and a target temperature of 75°C, and their drying characteristics and qualities were measured and analyzed. The results showed that the scallion core required the longest drying period of 420 min and obtained the slowest temperature rise rate under the same layer height condition, while the scallion leaf of the same layer height was RF dried fastest, with an overall drying rate of over 6.0%·min⁻¹. Under the same mass condition, scallion white obtained the fastest overall drying rate of around 5.5%·min⁻¹, but scallion leaf took the least time to reach the temperature of 75°C due to its largest amount of RF power absorbed and presented the largest effective diffusion coefficient of 1.42 × 10⁻⁸ m²/s. Therefore, scallion leaf can be RF dried the easiest, which consumes the least drying time under either condition. The dried scallion leaf obtained the minimum color change and shrinkage percentage of 65% and the maximum allicin content of 30.17 mg/100 g, while the scallion core had the largest ascorbic acid (VC) content of 30.39 mg/100 g under the same mass condition, and the scallion white possessed the best rehydration ratio of 5.56 under either condition. It was found that the increase in layer height and/or mass not only caused the decrease in drying rate for the scallion parts, but also led to a slightly increased allicin content (<i>p</i> &gt; 0.05), decreased shrinkage percentage, rehydration ratio, and VC content. Particularly, VC content of the scallion core significantly decreased by 28% (<i>p</i> &lt; 0.05) as its layer height increased by 2 mm. Since the scallion core needed about two times the drying period than that for scallion white, it was recommended that they should be RF dried separately to save time and energy and guarantee product qualities. These results and findings not only revealed the different drying characteristics of the three scallion parts and their impacts on product qualities, but also could provide the drying industry some useful information about the practical processing methods in scallion drying.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245062","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":"Gelatin/Chitosan Blend Solutions Rheology: Small and Large-Amplitude Oscillatory Shear Measurements","authors":"Jasim Ahmed,&nbsp;Giorgio Luciano,&nbsp;Md. Danish Eqbal","doi":"10.1111/jfpe.70162","DOIUrl":"https://doi.org/10.1111/jfpe.70162","url":null,"abstract":"<div>\u0000 \u0000 <p>The compatibility between chitosan (CS) (1 wt%–2 wt%) and gelatin (GEL) (2 wt% and 6.25 wt%) solutions was studied by measuring small and large-amplitude oscillatory shear at selected blending ratios (CS/GEL: 25/75, 50/50, and 75/25 w/w) and temperature. CS solutions displayed sol–gel transformation, whereas GEL exhibited predominant solid-like behavior (<i>G</i>′ &gt; <i>G</i>″). The concentration of gelatin significantly influenced the blend rheology. The blend solutions (25/75) produced a physical gel (<i>G</i>′ &gt; <i>G</i>″) at 2 wt% of each polymer. Blending of 2% CS with 6.25% GEL resulted in the weakest and strongest gels at a CS/GEL ratios of 75/25 and 50/50, respectively. The rheological data demonstrated that the 3D printing of the blend solutions could be achieved within a complex viscosity range of 62.63–86.03 Pa·s. The LAOS results demonstrated a perfect elastic relationship between stress and strain of the GEL solution (6.25 wt%) at a lower strain, which transformed to viscous-dominated behavior with increased strain.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245060","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":"Advanced Chain Regression and Deep Learning Models for Fish By-Product Drying Optimization: An Intelligent Conveyor System for Sustainable Waste Valorization","authors":"Khaled Abdeen Mousa Ali,&nbsp;Chagyou Li,&nbsp;Mohamed Fawzi Abdelshafie Abuhussein,&nbsp;Elwan Ali Darwish,&nbsp;Gomaa Galal Abd El-wahhab","doi":"10.1111/jfpe.70148","DOIUrl":"https://doi.org/10.1111/jfpe.70148","url":null,"abstract":"<div>\u0000 \u0000 <p>The rapid increase in global fish waste, estimated at two-thirds of total catch, presents critical environmental and economic challenges. This study introduces an innovative approach combining a heat conveyor dryer with advanced machine learning techniques for optimizing fish by-product processing. The experimental design evaluated three critical parameters: drying temperatures (60°C, 70°C, and 80°C), air conveying speeds (1, 1.5, and 2 m/s), and product layer thicknesses (5, 7, and 9 mm). The optimal configuration achieved a 150-min drying time at 80°C, 2 m/s air velocity, and 5 mm thickness, reducing processing time by 70% compared to conventional methods. Deep Neural Networks with 12 layers demonstrated superior prediction accuracy (R² = 0.979) for moisture content, while chain regression models using XGBoost achieved 97.8% accuracy in moisture ratio prediction. The dried products retained high nutritional value with 45.08% protein and 15.1% fat content, comparable to fresh samples. Compared to the best mathematical model (Page), the optimal machine learning model (deep neural network 12) provided more accurate and robust predictions of drying behavior across all tested conditions. This integrated approach offers a sustainable solution for fish waste valorization, potentially reducing processing energy consumption by 35% while maintaining product quality. The developed models enable real-time process optimization, contributing to both economic efficiency and environmental conservation in fisheries waste management.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256088","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":"Effect of Three Different Roller Milling Techniques on the Milling Properties and Baking Quality of Wheat Flour With Varying Protein Content","authors":"Snehasis Chakraborty,&nbsp;Hemanth Bommina,&nbsp;Manoj Kumar Pulivarthi,&nbsp;Kaliramesh Siliveru","doi":"10.1111/jfpe.70154","DOIUrl":"https://doi.org/10.1111/jfpe.70154","url":null,"abstract":"<div>\u0000 \u0000 <p>The study evaluated the impact of three different roller mills (Bühler Lab, Chopin Lab, and Brabender Sr. mills) on the milling yield, particle size, proximate composition, color profile, density, rheological properties, and bread quality of wheat flour with varying protein content. Milling trials were conducted on wheat samples (hard red spring [HRS] and hard red winter [HRW]) with varying protein levels (low: 9.7% [100% HRW], mid: 12% [HRS + HRW in 1:1 ratio], and high: 14.5% [100% HRS]). The Brabender Sr. mill achieved the highest straight-grade flour recovery of 73.3% for low-protein wheat. The particle size distribution analysis revealed differences among mills, with flour from the Bühler Lab mill having finer particles than those from the Chopin Lab and Brabender Sr. mills. Proximate composition analysis indicated that moisture content ranged between 13.3% and 15.6%, protein content between 9.8% and 12.3%, and damaged starch between 4.7% and 8.2%, depending on the mill and wheat protein level. Density parameters were minimally influenced by wheat protein content but varied between mills. The high-protein flours exhibited better water absorption and dough stability, with the Brabender Sr. mill yielding the highest water absorption capacity. The interaction between milling type and protein content significantly influenced (<i>p</i> &lt; 0.05) milling yield, water absorption, and bread quality attributes. Bread with higher protein content correlated with larger and uniform cell structures. The Bühler mill performs best for low-protein bread volume. The Brabender Sr. mill offers higher milling yield, while the Chopin Lab mill delivers greater bread volume for high- and medium-protein.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256236","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":"Impact of Heat on Microbial Survival and Physicochemical Characteristics of Coconut Neera","authors":"Sukumaran Latha,&nbsp;Radhakrishnan Mahendran","doi":"10.1111/jfpe.70161","DOIUrl":"https://doi.org/10.1111/jfpe.70161","url":null,"abstract":"<div>\u0000 \u0000 <p>Coconut Neera (<i>Cocos nucifera</i> L.) is a sweet and nutritious drink by the presence of sucrose and minerals. The high sucrose content in neera makes it highly prone to spontaneous fermentation, leading to rapid deterioration of its physicochemical and sensory attributes. In this study, the efficacy of mild heat as single-stage and double-stage (tyndallization) treatment at 50°C, 55°C, and 60°C were assessed for 5 and 10 min treatment time. The decimal reduction time and microbial log reduction for single-stage and double-stage treated neera were determined in the storage period (4°C ± 1°C). The physiochemical and sensory properties of stored neera were evaluated up to 21 days. Among the treatment methods, the double-stage heat treatment at 60°C–10 min exhibited the least number of microbial survival (6.68 ± 0.02 log CFU/mL) and shortest <i>D</i>_<i>t</i> values (3.50 ± 0.04) after treatment. The microbial log reduction was extended up to the storage period of 21 days with the result of 1.16 ± 0.01—total viable count, 1.06 ± 0.01—<i>Bacillus</i>, 0.27 ± 0.01—lactic acid bacteria, and 0.86 ± 0.03—yeast in double-stage treatment at 60°C–10 min. Moreover, TEM images of this treatment confirmed the lethal effect against the microorganisms. Therefore, the double-stage treatment at 60°C–10 min depicted non-significant physicochemical changes and sensory attribute up to 21 days. Finally, the results conclude that the method of tyndallization at 60°C–10 min could be an effective temperature against microbes includes spore former of <i>Bacillus</i> in neera.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245063","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":"Enhancing Thermal Property Prediction of Corn Kernels: Integrating Cultivar Variability and Machine Learning Models","authors":"Emmanuel Baidhe,&nbsp;Clairmont L. Clementson,&nbsp;Ewumbua Monono","doi":"10.1111/jfpe.70153","DOIUrl":"https://doi.org/10.1111/jfpe.70153","url":null,"abstract":"<p>Advancements in plant breeding and genetic engineering have led to increased productivity. However, limited research has assessed whether the thermal properties of these novel cultivars align with established empirical predictive literature. This study evaluated the thermal conductivity, specific heat, and thermal diffusivity of ten (10) U.S. grown corn cultivars across five moisture content levels (13% to 21% wet basis). The study further examined the predictive capability of empirical moisture and proximate composition-based models and machine learning models for estimating thermal properties of corn cultivars. The results showed a consistent increase in thermal properties with rising moisture content across all evaluated corn cultivars. Analyses revealed that both moisture content and cultivar significantly influenced thermal properties, confirming the complex and cultivar-specific nature of thermal behavior in corn. While models based on moisture content and proximate composition provided descriptive value, they exhibited limited predictive accuracy and generalizability, particularly across diverse cultivars. Notably, Gaussian Process Regression (GPR) models significantly outperformed Linear Regression (LR) models, with over 15% accuracy improvement in mean absolute error (MAE) and root mean square error (RMSE). Among the GPR approaches assessed, the Matern 5/2 kernel (GPR-52) achieved the highest accuracy and demonstrated robust, consistent performance, particularly in predicting thermal conductivity. The results emphasize the importance of integrating advanced modeling approaches and considering cultivar-specific and compositional variability in thermal processing applications. Future research should prioritize model refinement through the inclusion of additional explanatory variables such as bulk density and structural properties to further enhance prediction accuracy and practical applicability in agricultural and industrial settings.</p>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfpe.70153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245061","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":"Microwave-Assisted Parboiling: Enhancing Milling Quality and Nutritional Profile of Kodo Millet","authors":"Khumbaron Kiranbala Kabui,&nbsp;K. A. Athmaselvi","doi":"10.1111/jfpe.70155","DOIUrl":"https://doi.org/10.1111/jfpe.70155","url":null,"abstract":"<div>\u0000 \u0000 <p>Kodo millet, a minor millet known for its high nutritional value and remarkable drought resilience, faces processing challenges due to its thick hull layers. Hydrothermal pretreatment before milling has been shown to reduce grain fragility and milling loss. Traditional parboiling methods, however, are both energy and time-intensive. This study proposes a novel parboiling approach using microwave irradiation to evaluate its effects on the milling and grain quality of Kodo millet during the soaking and gelatinization stages. The millet was soaked at three microwave power levels, 90, 270, and 450 W, for 60, 30, and 20 min, respectively, to achieve a moisture content of 30% ± 2%. Gelatinization was done at 270 W for 20 min. Milling characteristics such as head grain yield, broken, and dehulling efficiency, grain dimensions, color, cooking time, and nutritional profile were evaluated. Microwave treatment significantly reduces processing time while enhancing the hardness and milling quality of the grain when compared to conventional parboiling methods. An increase in head grain yield and a reduction in the broken percent and cooking time and lighter color grains were observed, suggesting that microwave irradiation may be more advantageous than conventional parboiling. The nutritional profile of parboiled millet was also improved by MP as it preserved more protein and ash than the conventional approach. The findings suggest that microwave-assisted parboiling can serve as an effective, time-efficient method to enhance the milling and grain quality of Kodo millet, promoting its utilization as a functional food in modern diets.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244392","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":"Investigation of Structural and Morphological Alterations and Antinutrient Reduction in Bitter Yam (Dioscorea bulbifera) Induced by Different Processing Techniques","authors":"Monalisa Sahoo,&nbsp;Suriya P. L. Balasubramaniam,&nbsp;Balunkeswar Nayak,&nbsp;Vivek Kumar,&nbsp;S. N. Naik","doi":"10.1111/jfpe.70100","DOIUrl":"https://doi.org/10.1111/jfpe.70100","url":null,"abstract":"<div>\u0000 \u0000 <p>Antinutrients in plant foods must be removed or reduced during processing before they can be consumed safely. The study evaluated the effectiveness of various processing methods in reducing antinutrient levels in yam flour. The treatments included soaking for varying durations (4, 8, and 12 h), boiling for different time intervals (5, 15, and 25 min), and autoclaving at 100°C for corresponding durations (5, 15, and 25 min). Post-treatment, the yam slices were dehydrated in a hot air oven at 50°C for 10 h and then milled into flour. The study quantitatively assessed the reduction in phytate, oxalate, tannin, saponin, trypsin, and α-amylase inhibitors. The findings demonstrated reduction ranges of 15%–35%, 20%–45%, 50%–82%, 16%–43%, 11%–78%, and 16%–51% across the different pretreatment methods. Additionally, the study investigated the effects of these pretreatments on antioxidant activity, structural modifications (via XRD and FTIR analyses), morphological changes, and thermal properties. A statistically significant impact (<i>p</i> ≤ 0.05) was observed on total phenolics, flavonoids, and antioxidant levels. The crystallinity index and granule particle size varied between 9.82% and 9.61% and 10–140 μm, respectively. Notably, boiling for 25 min emerged as the most efficacious pretreatment for antinutrient reduction, though it also induced considerable alterations in granule size and morphology, as evidenced by SEM micrographs. However, it may be proposed that a combination of boiling followed by soaking could be explored for potentially improved results and warrant further investigation.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244391","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":"Characterizing the Mechanical and Rheological Properties of Aerated Confectionery Gels","authors":"Meredith L. Cohen,&nbsp;Richard W. Hartel","doi":"10.1111/jfpe.70156","DOIUrl":"https://doi.org/10.1111/jfpe.70156","url":null,"abstract":"<p>This study varied the gelatin content, gelatin Bloom strength, and density of confectionery gels in order to ascertain the effects of the variables on mechanical and rheological properties. Rheological and texture profile analyses were conducted on the samples, and micro-computed tomography scans were taken to provide images of the internal bubble structure. Statistical analyses including data modeling and ANOVA were performed. Bloom strength did not appear to have a significant effect on any of the measured parameters, with the exception of hardness of non-aerated gels. Increased gelatin content increased hardness, elasticity, and overall stiffness. Increased air content reduced adhesiveness; the effects of aeration on hardness and viscoelasticity were dependent on bubble size distribution. These results indicate that the air cell structure of an aerated confectionery gel significantly impacts its mechanical and rheological properties. Furthermore, the increases in hardness, stiffness, and elastic properties with gelatin content indicate that the junction zone mechanism by which gelatin gels is effective regardless of air content. These results may be useful for adjustment of commercial marshmallow formulations and serve to establish a baseline for an eventual comparison with plant-based gelatin substitutes.</p>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfpe.70156","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144232487","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":"Regression Models Used in Food Science: Linearity, Reparameterization, and Rescaling","authors":"Sencer Buzrul","doi":"10.1111/jfpe.70149","DOIUrl":"https://doi.org/10.1111/jfpe.70149","url":null,"abstract":"<div>\u0000 \u0000 <p>Models can be linear or nonlinear; however, the linearity of a model refers to its parameters. Although linear regression has several advantages over nonlinear regression such as having an analytical solution and symmetric confidence intervals, most regression models used in food science are nonlinear. Therefore, nonlinear regression should be used to obtain the parameters and their uncertainties. Reparameterization can be useful to have interpretable parameters, and sometimes it is better to perform nonlinear regression instead of simple linear regression even if there is a linear relationship between the dependent and independent variable. Rescaling is a desirable method to have statistically significant parameters. The aim of this paper is to discuss the linearity of the models and to show some useful reparameterization and rescaling by using some published data. Examples are given from food microbiology (microbial inactivation kinetics) and degradation kinetics of foods.</p>\u0000 </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":"48 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144232485","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}