Food Physics最新文献

{"title":"Application of the PVSDM model for elucidating mass transfer mechanisms during adsorption and its potential applications in food research","authors":"Yue Wu ,&nbsp;Weizhi Liu ,&nbsp;Sivakumar Manickam ,&nbsp;Dandan Li ,&nbsp;Yongbin Han ,&nbsp;Zhengyang Bao ,&nbsp;Yang Tao","doi":"10.1016/j.foodp.2025.100076","DOIUrl":"10.1016/j.foodp.2025.100076","url":null,"abstract":"<div><div>The pore volume and surface diffusion model (<em>PVSDM</em>) provides a rigorous, mechanistic framework for elucidating mass transfer phenomena in adsorption processes. Unlike empirical kinetic models, <em>PVSDM</em> offers a physically grounded description that integrates solid-liquid interfacial transfer, intraparticle diffusion, and adsorption site interactions within a unified theoretical construct. Although this model holds great promise for exploring adsorption mechanisms in complex food matrices, its mathematical complexity has hindered its broader adoption in food research. This work presents a comprehensive exposition of the <em>PVSDM</em> theory, encompassing its conceptual foundations, mathematical formulations, and computational implementation. The governing assumptions and simplification strategies used to solve the <em>PVSDM</em> model are first elucidated, followed by detailed methods for calculating key mass transfer parameters prior to model computations. Subsequently, the numerical operations required to solve the partial differential equations are outlined. Furthermore, representative findings derived from <em>PVSDM</em> simulations are discussed in the context of adsorption phenomena involving food components. This study advances scientific understanding by integrating physics-based modeling frameworks with their practical implications in food science.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100076"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated cleaning strategy for ginger: Combining ultrasonic-bubbling synergy with YOLOv5-based cleanliness assessment","authors":"Haoxin Li ,&nbsp;Wenhao Zhou ,&nbsp;Xiaojie Yu ,&nbsp;Lei Zhang ,&nbsp;Yabin Feng ,&nbsp;Zhenfeng Yang ,&nbsp;Cunshan Zhou","doi":"10.1016/j.foodp.2025.100079","DOIUrl":"10.1016/j.foodp.2025.100079","url":null,"abstract":"<div><div>Ginger (<em>Zingiber officinale Roscoe</em>) is an important spice and medicinal plant widely consumed worldwide. Its irregular surface easily retains soil and microorganisms, while traditional cleaning methods are often ineffective in removing contaminants from crevices, affecting product safety and quality consistency. This study developed a combined bubbling and ultrasonic cleaning system with machine vision inspection to improve cleaning thoroughness and enable standardized cleanliness evaluation. Numerical simulations helped determine initial equipment parameters: a bubbling flow rate of 10 m/s and ultrasonic frequency of 40 kHz, with an interleaved transducer arrangement to reduce standing waves. Single-factor experiments established the best operational conditions as 8 min of bubbling combined with ultrasound (900 W) and a batch size of 10 kg per cycle. Among nine tested treatment protocols, the combination of 2 % NaHCO₃ soaking with 40 kHz ultrasound and bubbling (NS+US+Bubbling) achieved 95.78 % cleaning efficiency and reducing microbial load by 4–5 log CFU/g. Ultrasonic treatment also enhanced phenylalanine ammonia-lyase activity in ginger, leading to a 38.01 % increase in phenolic accumulation compared to untreated samples. A YOLOv5-based recognition model achieved over 98 % accuracy in cleanliness assessment. The integrated bubbling-ultrasonic system enables efficient and comprehensive ginger cleaning, while the machine vision approach provides potential support for standardized grading.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100079"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of maize seed varieties based on hyperspectral imaging combined with deep learning","authors":"Peng Xu ,&nbsp;Lixia Fu ,&nbsp;Ranbing Yang ,&nbsp;Xiongfei Chen","doi":"10.1016/j.foodp.2025.100073","DOIUrl":"10.1016/j.foodp.2025.100073","url":null,"abstract":"<div><div>Variety identification of seeds is crucial to guarantee crop quality and yield, as well as to ensure the quality and nutritional value of processed maize products. This study proposes a methodology for identifying maize seed varieties based on hyperspectral imaging (HSI) combined with deep learning. The mean spectra of the endosperm side (E1), non-endosperm side (N1), and both sides fused (F1) of maize seeds were extracted, followed by spectral pre-processing using Savitzky-Golay (SG) smoothing and multiplicative scatter correction (MSC), and feature wavelengths were selected from the spectral data using the competitive adaptive reweighted sampling (CARS) algorithm. K-nearest neighbor (KNN), decision tree (DT), support vector machine (SVM), random forest (RF), partial least squares discriminant analysis (PLS-DA), and convolutional neural networks with multi-scale feature fusion (CNN-MFF) were utilized to construct the discriminant models. The study results show that the model established using the spectra of F1 obtains better performance than E1 and N1, with an accuracy of more than 87.22 % on the prediction set. The CNN-MFF model built based on full and feature wavelengths obtained optimal results with accuracies of 97.78 % and 96.11 % on the prediction set, respectively, which proves that the CNN based on multi-scale feature fusion has better applicability and stability. In addition, visualization methods were used to demonstrate the recognition results to visualize the model's classification performance. In summary, using HSI and deep learning for the variety identification of maize seeds is feasible. The proposed method has significant potential for application in spectral analysis and can provide a reference for the online detection of seed quality in crops such as maize. Combining spectroscopic methods to analyze the distribution information of its internal nutrient elements can contribute to directing maize food processing and improving the utilization value of by-products.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subcritical water extraction as a green technology for the recovery of bioactive compounds from algae: A comprehensive review","authors":"Hadiya Tahir ,&nbsp;Aamir Hussain Dar ,&nbsp;Kshirod Kumar Dash ,&nbsp;Toiba Majeed ,&nbsp;Shivangi Srivastava ,&nbsp;Anurag Singh ,&nbsp;Madiya Manzoor ,&nbsp;Urba Shafiq Sidiqi ,&nbsp;Arsheed Ahmad Ganaie","doi":"10.1016/j.foodp.2025.100077","DOIUrl":"10.1016/j.foodp.2025.100077","url":null,"abstract":"<div><div>Subcritical water extraction is used for extraction of various bioactive compounds, antioxidants, and colorants from algae. The bioactive compound extraction utilizing sustainable environmentally technology is currently of utmost importance, particularly in relation to functional foods and advanced healthcare solutions. When using Subcritical water extraction (SWE), the alteration of temperature and pressure allows for the selective extraction of particular bio active compounds, thereby reducing the quantum of components not required. SWE enables water to dissolve both polar and non-polar compounds because its dielectric constant decreases as the temperature increases. This process allows maintaining the bioactivity as well as desirable qualities of bioactive compounds being extracted. The use of water as solvent in SWE ensures that the safe and eco-friendly procedure. These improved characteristics of subcritical water solvent leads to high extraction efficiency. The objective of this study is the extraction of the bioactive compounds from the algae using the subcritical water extraction (SWE) and to discuss the various methodologies, their implementations, advantages as well as prospective advancements of SWE in relation to algae. The study further aims to emphasize the significantly efficient and sustainable extraction of bioactive compounds from algae, with the intent of applying them in diverse industrial applications.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural, thermal and functional properties of protein isolates from oyster mushroom (Pleurotus ostreatus) isolated by alkaline iso-electric, ultra-sonication and enzymatic extraction techniques","authors":"Ringshangphi Khapudang,&nbsp;Saleem Siddiqui","doi":"10.1016/j.foodp.2025.100072","DOIUrl":"10.1016/j.foodp.2025.100072","url":null,"abstract":"<div><div>The protein isolates extracted from oyster mushroom by alkaline isoelectric precipitation, enzymatic and ultrasound assisted extraction methods were evaluated for their physicochemical and functional properties. Enzyme assisted extraction enhanced the zeta potential (-19.8 mV) and reduced particle size (288.5 nm) as compared to the standard alkaline isoelectric precipitation method having the values −5.95 mV and 621.8 nm, respectively. Enzymatic extraction with protease as well as ultrasound-assisted extraction led to a significant enhancement in the colloidal stability of the isolated proteins, attributable to improved dispersion and stronger electrostatic repulsion among protein molecules. Ultrasound assisted extraction showed a time- and amplitude-dependent effect. The highest values for water holding capacity (6.52 g/g), oil holding capacity (8.57 g/g), foaming capacity (52.17 %), and emulsifying activity (2.14 m²/g) were observed in the ultrasound-assisted extraction with 30 % for 10 min treatment, suggesting enhanced interfacial activity and surface functionality. Scanning electron microscopy confirmed structural disintegration and reduced aggregation in proteins isolated by enzymatic and ultrasound-assisted extraction methods. The findings demonstrate that both the enzyme- and ultrasound-assisted extraction methods are effective in enhancing the structural and functional quality of oyster mushroom protein isolates.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100072"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Valorization of underutilized amla (Emblica officinalis) pomace: An artificial neural network-based approach for drying kinetics and quality assessment","authors":"Sumaiya Fatima,&nbsp;Vivek Kumar","doi":"10.1016/j.foodp.2026.100085","DOIUrl":"10.1016/j.foodp.2026.100085","url":null,"abstract":"<div><div>Amla pomace, a by-product of juice processing, is abundant in phytochemicals and fiber but remains largely unutilized. Because it contains more moisture, drying is necessary to prevent microbial spoilage, improve stability, and increase shelf life, making it suitable for use in value-added foods and nutraceutical products. The drying behaviour of amla pomace dried in a computer-controlled tray drier at different drying temperatures, DT (50, 60, and 70°C) and air velocities, AV (0.9, 1.0, and 1.1 m/s) was therefore explored. Drying of amla pomace was observed to follow falling rate period pattern over the DT and AV range. Five thin-layer drying models were evaluated for amla pomace, and the Page model showed the best fit with the highest R² and lowest χ² and RMSE values. An ANN model with a 3–3–4–1 topology predicted the drying behaviour of amla pomace with greater accuracy than the page model. Furthermore, the effective moisture diffusivity (D_eff) and activation energy (E_a) were estimated using linearization and DA-nlinfit methods, with latter method predicted both D_eff and E_a at lower RMSE and higher R² values. Also, the mass transfer coefficient and Gibbs free energy increased with increasing DT, while enthalpy followed converse trend, as determined by the DA-nlinfit method. Further, rise in DT adversely affected the phytochemical attributes and colour quality of pomace powder, although AV helps in retention of all these quality attributes of amla pomace powder. Nonetheless, phenolic content, total flavonoid content and DPPH assay was found to be maximum at 60°C and 1.1 m/s, while colour attributes and ascorbic acid content was most preserved at 50°C and 1.1 m/s. Additionally, microstructural analysis confirmed that higher DT lagged behind in preserving the cellular matrix of pomace.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100085"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modulating the texture of pea-based meat analogs: Influence of methylcellulose on mechanical and rheological properties of high moisture extrudates","authors":"Gabriela I. Saavedra Isusi ,&nbsp;Laurids Pernice ,&nbsp;Valentin Glubrecht ,&nbsp;Valerie L. Stahl ,&nbsp;Nico Leister","doi":"10.1016/j.foodp.2025.100074","DOIUrl":"10.1016/j.foodp.2025.100074","url":null,"abstract":"<div><div>Adding hydrocolloids to plant-based meat analogs is a useful way to modulate the extrudates texture. However, it can alter the rheological properties of the melt, hence affect the extrusion process and change the extrudate’s structure in an unknown manner. This study focuses on the influence of methyl cellulose (MC) as a model hydrocolloid on the mechanical properties of pea protein extrudates produced through high-moisture extrusion cooking. MC was introduced in solutions with different molecular weights at varying concentrations during extrusion. The study aims to assess whether MC affects the anisotropic structure of pea extrudates due to protein interactions or melt viscosity effects. Observations included changes in specific mechanical energy and die pressure, mechanical and rheological characterizations, and protein solubility analyses. MC decreased the melt viscosity during extrusion by 20 % for all MC concentrations, although offline rheology measurements of protein-MC mixtures showed an increase dependent on concentration and type of MC. The meat analogs E-Moduli decreased due to MC addition by up to 75 %. Protein analysis revealed protein-MC complexation, regardless of the MC molecular structure. These results show that anisotropic structuring cannot be predicted alone through offline rheological characterization. Understanding these protein-hydrocolloid interactions can improve plant-based products.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145473502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasonic-assisted ethanol extraction of flavonoids from supercritical CO2 extracted propolis residues and its online UV-Vis monitoring","authors":"Lei Yi ,&nbsp;Wuli Wang ,&nbsp;Huimin Liu ,&nbsp;Haile Ma ,&nbsp;Yong Zhang ,&nbsp;Yu Zhang","doi":"10.1016/j.foodp.2026.100083","DOIUrl":"10.1016/j.foodp.2026.100083","url":null,"abstract":"<div><div>Secondary extraction of flavonoids from propolis residue following supercritical CO₂ extraction was investigated, with concurrent development of an on-line and real-time flavonoid quantification monitoring method. Ultrasonic-assisted ethanol extraction (UAE) parameters were optimized by single-factor experiments and response surface methodology (RSM), with comparative assessment against traditional extraction without ultrasound assistance. Under optimal UAE conditions, an offline quantitative detection model for the content of flavonoids was established firstly by ultraviolet-visible (UV-Vis) spectroscopy coupled with machine learning algorithms. Secondly, an online detection model was obtained by calibrating the offline model with direct standardization (DS) algorithm. The optimal extraction conditions were determined to be: ultrasonic frequency of 28 kHz, power density of 136 W/L, extraction time of 15 min, temperature of 43°C, solid-liquid ratio of 1:10 (g/mL), and ethanol concentration of 75 %. Under these optimized parameters, the extraction yield reached 9.41 mg/mL. Comparative analysis revealed that the ultrasonic method significantly outperformed both conventional extraction techniques, with low-speed agitation yielding 7.52 mg/mL and high-speed agitation yielding 8.26 mg/mL (p &lt; 0.05). offline models, support vector regression (SVR) with normalized spectra and synergy interval partial least squares (Si-PLS) feature selection demonstrated superior performance (calibration: Rc=0.9914, RMSEC=0.3224; prediction: Rp=0.9926, RMSEP=0.3003)The statement \"superior performance\" refers specifically to the comparative results within this evaluation framework. The model built using Support Vector Regression (SVR) on normalized spectra with Synergy Interval Partial Least Squares (Si-PLS) for feature selection demonstrated superior predictive accuracy and robustness compared to the other modeling methods evaluated in the study, primarily Partial Least Squares (PLS) and Backpropagation Neural Network (BPNN). The DS-corrected online migration model achieved optimal real-time quantification (Rp=0.9660, RMSEP=0.7773). This study confirms UAE as an efficient low-temperature method for flavonoid recovery from propolis residue. Integration of offline UV-Vis modeling with DS spectral correction enables robust online flavonoid monitoring during extraction.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100083"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"To investigate the effects of controlled moisture levels on the peach (Prunus persica) kernels: Dimensional, gravimetrical, frictional, optical, and mechanical properties","authors":"Rajvinder Kour ,&nbsp;Seerat Sharma ,&nbsp;Mohammad Ubaid ,&nbsp;Imran Sheikh ,&nbsp;Mohd Aaqib Sheikh ,&nbsp;Naseer Ahmed","doi":"10.1016/j.foodp.2025.100071","DOIUrl":"10.1016/j.foodp.2025.100071","url":null,"abstract":"<div><div>Moisture content markedly influences the physical and mechanical properties of peach (<em>Prunus persica</em>) kernels, thereby affecting the performance of post-harvest handling and processing equipment. This study examined the effect of five controlled moisture levels (5.83 %, 9.86 %, 14.56 %, 20.12 %, and 25.26 %, wet basis) on the dimensional, frictional, optical, and mechanical properties of peach kernels. Dimensional measurements showed significant (<em>p ≤ 0.05</em>) increases of 3.42 %, 5.84 %, and 15.88 % in the major, medium, and minor axes, respectively, with rising moisture content. Static and dynamic frictional analyses indicated reduced flowability and increased resistance to movement at higher moisture levels. Optical assessment revealed total colour differences (ΔE) of 1.68, 4.70, 5.45, and 7.60 between moisture treatments, indicating moisture-induced changes in surface reflectance. Mechanical testing demonstrated that rupture force, hardness, deformation at rupture, and toughness decreased significantly (<em>p ≤ 0.05</em>) with increasing moisture content, with the lowest rupture force (1.86 N) recorded under horizontal loading. These results provide critical engineering parameters for designing and optimizing moisture-specific storage systems, conveying equipment, and cracking processes, thereby improving energy efficiency and product quality in peach kernel processing.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100071"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145226942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of a magnetic field on the production of Monascus pigments and citrinin via regulation of intracellular and extracellular iron content","authors":"Yang Yang ,&nbsp;Qian Liao ,&nbsp;Jialan Zhang ,&nbsp;Yingbao Liu ,&nbsp;Li Li ,&nbsp;Suo Chen ,&nbsp;Mengxiang Gao","doi":"10.1016/j.foodp.2025.100070","DOIUrl":"10.1016/j.foodp.2025.100070","url":null,"abstract":"<div><div>This study aims to elucidate the influences of magnetic fields (MFs) on the production of <em>Monascus</em> pigments (MPs) and citrinin by modulating both the intracellular and extracellular iron content in <em>Monascus purpureus</em>. The organism was treated with varying concentrations of L-allylglycine (L-AG), along with MFs of different intensities for 2 days during the early fermentation phase, as well as combinations of 1 mM L-AG and the MFs. The primary indicators assessed were the biomass, MPs production, citrinin production, and intracellular and extracellular iron content. The results indicate that exposure to MFs of varying intensities had no significant effect on the biomass of <em>M. purpureus</em>, while it significantly inhibited citrinin production. Conversely, exposure to a 1.6-mT MF significantly enhanced MPs production, while exposure to a 1.2- or 1.6-mT MF promoted the extracellular excretion of intracellular iron. Further, concentrations of 3 and 5 mM of L-AG significantly inhibited the growth of <em>M. purpureus</em>, whereas different concentrations of L-AG significantly inhibited MPs and citrinin production. Moreover, following treatment with both L-AG and MFs, all combinations exhibited a significant increase in MPs and citrinin production compared to L-AG treatment alone. In contrast, citrinin production in the group treated by L-AG with either a 1.2-mT or a 1.6-mT MF was significantly lower than that in the control group. Furthermore, intracellular iron content in the group treated by L-AG and a 1.6-mT or a 2.0-mT MF was reduced compared to that in the L-AG treatment group, with no significant difference from the control group. These findings suggest that appropriate exposure to MFs can decrease intracellular iron content and mitigate reductions in MPs and citrinin production induced by L-AG. Therefore, the regulation of MPs and citrinin synthesis induced by MFs in <em>M. purpureus</em> may be related to the intracellular iron content.</div></div>","PeriodicalId":100545,"journal":{"name":"Food Physics","volume":"3 ","pages":"Article 100070"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}