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- MakaleYalnız künye2027Efficacy of blue light-assisted ClO2 for Salmonella decontamination on basil leaves: inactivation kinetics, quality preservation, and microbiota dynamics
Lian, Yi; Liu, Songlin; Ozturk, Samet; Wei, Xinyao
Frequent Salmonella outbreaks associated with basil leaves highlight the need for effective postharvest decontamination. Conventional microbial sanitizers often fail to inactivate pathogens while preserving product quality, creating a demand for novel decontamination technologies suitable for basil. In this study, the microbial safety of basil under typical consumption scenarios was evaluated and a blue light-assisted ClO2 (COM) decontamination process for basil leaves was developed. Mathematical models were used to describe the microbial inactivation kinetics, and a systematic comparison was conducted against traditional single-chemical sanitizers (H2O2, HClO, ClO2, and 75% ethanol) in terms of microbial safety and final product quality. Results showed that simulated cooking scenarios, including pizza baking and hot soup immersion, were insufficient to reduce the Salmonella levels below the detection limit (<10 CFU/g) under a high initial load of 9.7 log CFU/g. Compared to the single-chemical treatments, 100 mg/L COM treatment achieved significantly higher decontamination (p < 0.05) by reducing Salmonella and background microbiota by 4.8 and 3.5 log CFU/g, respectively, with treatment time of 15 min. The inactivation kinetics of Salmonella showed a non-linear inactivation kinetics, which was captured by the Weibull model with a low RMSE value (RMSE = 0.16), although the AICc value (11.37) indicated limited model parsimony. Furthermore, the COM treatment significantly reduced bacterial richness (with the Chao1 index decreasing from 316 to 71) and effectively inactivated key spoilage organisms (Pseudomonas) as well as members of the Enterobacteriaceae, Actinomycetota, and Bacillota groups. Compared with the 100 mg/L ClO2 treatment alone (1.40 mg/kg), the 100 mg/L COM treatment resulted in a ClO2 residue concentration below the detection limit, without significantly altering visual appearance, color, chlorophyll content, total phenolics, or polyphenol oxidase activity (p > 0.05). Overall, blue light-assisted ClO2 treatment effectively reduced microbial contamination and reduced ClO2 residues while preserving the physical quality of basil, representing a promising decontamination approach for the fresh produce industry.
- MakaleYalnız künye2026An insight of oil protection theory: Survival, structural and metabolic adaptation of Salmonella enterica Enteritidis Phage Type 30 in three triglycerides
Zhao, Huan; Sun, Rui; Cao, Shidi; Ozturk, Samet; Erdogdu, Ferruh; Liu, Xingyi; Liu, Shuxiang
Oil protection theory posits that oil enhances microbial survival and heat resistance in low-moisture foods, yet the role of triglyceride composition remains poorly defined. This study investigates how Salmonella enterica Enteritidis PT 30 adapts during desiccation in peanut oil (mixed triglycerides, aw,25 degrees C = 0.30) and two representative components, namely, trilinolein and glyceryl trioleate. The lipid-specific structural and metabolic adaptations were analyzed through confocal microscopy and transcriptomics. S. Enteritidis exhibited the lowest persistence (3.43-log reduction over 180 days) and weakest heat resistance (2.5 h at 80 degrees C to achieve 3.5-log reduction) in peanut oil. The survival of S. Enteritidis in triglycerides could be correlated with its metabolic dormancy via suppression of ribosomal and oxidative phosphorylation pathways. Trilinolein enhanced S. Enteritidis' heat resistance (30 h at 80 degrees C for 3.5-log reduction) and moderate storage mortality (1.64-log reduction at 180 d), driven by stress hyperactivity. Glyceryl trioleate balanced heat tolerance (8 h) with optimal storage survival (1.19-log reduction), mediated by partial metabolic suppression. Peanut oil preserved S. Enteritidis transient motility in water-rich microenvironments, while pure triglycerides formed compact, dehydrated aggregates. Transcriptomics identified divergent strategies. Peanut oil induced dormancy at the expense of stress resilience, whereas homogeneous lipids imposed distinct constraints; that is, trilinolein amplified oxidative stress, and glyceryl trioleate intensified desiccation. These findings refine oil protection theory, demonstrating that lipid heterogeneity-not just low water activity-shapes microbial outcomes. The mixed components of peanut oil buffer stress but limit protective efficacy, while its purified constituents reveal how specific triglycerides modulate survival. This mechanistic understanding advances theoretical models of pathogen persistence in oily matrices and guides targeted strategies to mitigate risks in low-moisture oil-rich food systems.
- MakaleYalnız künye2026Classification and detection of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes using Fourier-transform near infrared spectroscopy coupled with machine learning
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
This study was conducted to investigate the potential use of Fourier-transform near-infrared (FT-NIR) spectroscopy combined with machine learning (ML) algorithms to accurately identify three foodborne pathogens, including Salmonella spp., Listeria monocytogenes, and Escherichia coli O157:H7. Each bacterial strain (two per pathogen) was individually cultured and purified through sequential washing using ethanol–deionized (DI) water solutions. Each purified culture was transferred into each well of a 96-well cell plate covered with custom-cut filter paper and then vacuum dried at 50 °C under 20 kPa for 1 h. The absorbance spectra of dehydrated bacterial cells were then acquired across the range of 1000–2400 nm using a diffuse reflectance probe connected to a FT-NIR process analyzer. To identify the optimal classification pipeline, the acquired spectra were analyzed using ten different pre-processing methods, three feature selection methods, and supervised algorithms including partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), random forest (RF), artificial neural network (ANN), and convolutional neural network (CNN). Furthermore, the accuracy of the developed ML pipelines was further enhanced through under-sampling and boosting steps. The results demonstrated that SVM, RF, ANN and CNN outperformed PLS-DA, where the classification accuracies were above 90%. The findings demonstrate that using Savitzky-Golay first derivative (SG1) filtering to pre-process the full spectra followed by SVM classification yielded the highest accuracy, achieving 95.3% overall accuracy in ML pipeline. This study highlights the powerful capability of FT-NIR spectroscopy coupled with ML algorithms to detect and identify foodborne pathogens on dehydrated surfaces in process environments.
- MakaleYalnız künye2026Quality deterioration kinetics of roasted peanut matrices under fixed-time and estimated-lethality at various water activities
Islam, Shahriar; Li, Zhiwei; Wang, Xin; Tasci, Caner; Ozturk, Samet; Erdoǧdu, Ferruh; Zhang, Qing; Liu, Shuxiang
Water activity and particle size are critical determinants of quality stability and safety in low-moisture, lipid-rich foods. However, their combined effects during thermal processing of roasted peanut matrices remain insufficiently quantified. This study evaluated quality deterioration in roasted peanut matrices with different structural forms: crushed, flour, powder, and butter. Samples were equilibrated to water activity values of 0.11–0.92 at 25 °C and heated at 80 °C for 120 min. Colour, acid value, sensory score, and changes in relative fatty acid composition were measured. Kinetic experiments were also conducted at aw,25°C 0.32 using D-value-based thermal schedules at 85, 90, and 95 °C to relate microbial lethality to quality loss. Water activity strongly affected quality stability, with the predicted quality-favourable values varying slightly among responses. Therefore, aw,25°C (0.32) was selected as a practical condition for subsequent kinetic evaluation. Matrix performance differed between the fixed-time and D-value-based treatments. These findings describe quality deterioration under fixed-time and D-value-based thermal schedules.
- MakaleYalnız künye2026A dynamic predictive model for Bacillus cereus growth from spores under temperature abuse conditions
Juneja, Vijay K.; Osoria, Marangeli; Gao, Juan; Kapoor, Harsimran Kaur; Ozturk, Samet; Purohit, Anuj; Mishra, Abhinav
Bacillus cereus, a common foodborne pathogen, can cause emetic and diarrheal food poisoning. The associated outbreaks are commonly caused by temperature abuse during food cooling, storage, and transportation. This study developed a model to predict B. cereus growth from spores based on isothermal growth data collected at 10–54.4 °C in tryptic soy broth. A four-strain spore cocktail was heated at 80 °C for 10 min and inoculated at an initial level of ∼2 log CFU/mL. Growth curves at temperatures showing growth (15–50 °C) were fitted using the Baranyi model. The average h0 value was 3.04. The temperature dependence of the maximum specific growth rate was characterized using the modified Ratkowsky model. The estimated theoretical minimum and maximum growth temperatures were 8.94 °C and 54.11 °C, respectively. The lag phase duration was related to temperature using a hyperbolic function. All models showed good agreement with the observed data, with satisfactory fit statistics (R2 = 0.953–0.998 and RMSE = 0.073–0.904). The Baranyi differential equations were solved numerically using a fourth-order Runge–Kutta method to build the dynamic model. Model validation was conducted under two sinusoidal non-isothermal temperature profiles (10–30 °C for 30 h and 25–45 °C for 23 h). The accuracy factor (Af) and bias factor (Bf) values were 1.2117 and 1.2117 for the 10–30 °C profile, and 1.1359 and 1.1288 for the 25–45 °C profile, respectively. These results demonstrated that the dynamic model could precisely predict B. cereus growth and be used as a baseline reference for food system research and risk assessment.
- MakaleYalnız künye2026Radio frequency heating of whole peanuts for microbial safety and quality preservation using interlayer displacement under stationary and moving conditions: Effects of salt coating and natural skin on heating behavior
Kahraman, Kubra; Tasci, Caner; Cakir, Elif Nida; Liu, Shuxiang; Soncu, Eda Demirok; Erdogdu, Ferruh; Ozturk, Samet
This study aimed to improve the efficiency of a radio frequency (RF) heating system for pasteurizing whole peanuts while maintaining quality attributes using a stationary position or continuous movement. Heating efficiency was evaluated using commercially available roasted whole peanuts: salt-coated skin-on, unsalted skin-on, and unsalted peeled peanuts. To improve heating uniformity and ensure sufficient microbial inactivation of Salmonella enterica serovar Enteritidis PT30, a single interlayer-displacement strategy was applied in both stationary and continuous modes. Quality attributes including protein structure and fatty-acid profiles were assessed under the selected RF processing conditions. The RF system equipped with a conveyor belt was used to process peeled, unsalted peanuts inoculated with S. Enteritidis PT30 at approximately 7.9–8.5 log CFU/g. The three commercial peanut types exhibited differences in RF temperature distribution and heating uniformity, with salt-coated skin-on peanuts showing higher average temperature than unsalted peeled samples under the evaluated conditions. Continuous movement increased average temperature by approximately 10 °C but resulted in poorer heating uniformity, with a 3 °C higher standard deviation (SD). A single interlayer-displacement (overturning) step improved heating uniformity. This step increased Salmonella reductions from 3.41 to 4.77 log CFU/g under stationary processing and from 2.92 to 4.22 log CFU/g under continuous processing after 60 min of RF heating. The evaluated protein and lipid quality characteristics of unsalted peeled peanuts remained largely unchanged following RF processing. Overall, these findings demonstrated the potential of RF heating combined with interlayer displacement for microbial decontamination of unsalted peeled whole peanuts while maintaining the quality attributes evaluated in this study.
- MakaleYalnız künye2026Thermal inactivation kinetics of Listeria monocytogenes in fat/water emulsions and fat tissue – effect of fat content
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
Significantly increased thermal resistance was found in Listeria monocytogenes inoculated to beef tallow. However, how the relative compositions of fat and water in emulsions affect bacterial survival during heating has not been evaluated. This study aimed to evaluate the effect of fat levels in solid fat/water (SF/W) emulsions on thermal resistance of L. monocytogenes. SF/W emulsions, containing 0, 25, 50, 60, and 75 % of tallow by weight, were prepared by mixing tallow with soybean lecithin and Tween 80 in 0.1 % peptone water using an ultrasonic processor. A 4-strain cocktail of L. monocytogenes was inoculated to the emulsions and subjected to isothermal heating between 55 and 65 °C. The survival curves were analyzed to estimate the kinetic parameters and evaluate thermal resistance. Linear survival was observed in emulsions with fat below 50 %. However, increased thermal resistance, evidenced by the increasing D and z values with the fat content, was observed. For example, the average D values in SF/W emulsions at 60 °C are 0.54, 1.04, and 2.53 min, respectively, with 0, 25, and 50 % fat. For SF/W emulsions with 60 and 75 % fat and in beef trim fat (BTF, 86.9 % fat), the survival curves became convexly nonlinear and could be described with the Weibull model. The exponents of the Weibull model range between 0.45 and 0.456, suggesting almost identical convexity of the survival curves. The convex survival curves indicate initial sensitivity to heat but the resistance increases with time at each temperature. The estimated time to a 5-log reduction becomes 11.9 and 26.4 min in 60 and 75 % SF/W emulsions, respectively, and 36.5 min in BTF at 60 °C. The study demonstrates the effect of fat levels on thermal resistance of L. monocytogenes in SF/W emulsions and BTF. The results of this study may help the food industry to properly kill L. monocytogenes in fat-containing meat products during thermal processing.
- MakaleAçık Erişim2026Structure-Dependent Triglyceride Protection of Freeze-Dried Lactiplantibacillus plantarum: Storage Protection Window, Lipid Oxidation, and Stress Adaptation
Sun, Zheneng; Zhang, Nan; Wang, Xiaomai; Wei, Xinyao; Ozturk, Samet; Liu, Shuxiang
Lipid-rich matrices can protect probiotics by limiting direct exposure to moisture, oxygen, and gastrointestinal stressors. However, triglycerides are chemically dynamic during storage, and differences in fatty acid structure and oxidation susceptibility may determine whether they exert protective or detrimental effects. In this study, tricaprylin, triolein, and trilinolein were evaluated as post-drying lipid storage matrices for freeze-dried Lactiplantibacillus plantarum 124 during storage at 25 °C, and 37 °C was used to accelerate lipid oxidation. Survival during storage, fatty acid chain retention, oxidation-derived products, stress tolerance, qualitative confocal imaging of membrane-integrity patterns, and transcriptomic responses were analyzed. After 30 d at 25 °C, log reductions were 0.30, 0.24, and 0.24 log10 units in the tricaprylin, triolein, and trilinolein groups, respectively, compared with 0.60 log10 units in the oil-free control, defining a common protective window. Tricaprylin showed the highest fatty acid chain retention, whereas trilinolein exhibited the greatest loss and strongest oxidative change. GC–MS detected no representative oxidation-derived products in tricaprylin, while unsaturated triglycerides generated dimethyl azelate and methyl 9-oxononanoate. Cells recovered from the protective window showed improved acid and bile tolerance, with survival increasing from 30.48% to 53.43–55.65% and from 14.85% to 22.49–27.79%, respectively. Confocal imaging further showed better-preserved membrane-integrity patterns in the triglyceride-treated groups after acid exposure. Transcriptomics indicated enhanced transport, redox, DNA-related, and cell-envelope responses, accompanied by reduced translation and growth-associated metabolism. Within the experimental conditions tested, these results suggest that triglyceride-associated attenuation of viability loss varies among triglyceride systems and across storage stages, while excessive oxidation of unsaturated triglycerides may weaken probiotic stability.
- MakaleAçık Erişim2026Designing an industrial-scale radio frequency decontamination process for peanut butter
Coskun, Eda; Ozturk, Samet; Tasci, Caner; Kahraman, Kubra; Liu, Shuxiang; Li, Rui; Wang, Shaojin; Mert, Behic; Marra, Francesco; Erdogdu, Ferruh
Centers for Disease Control and Prevention (CDC) has reported outbreaks of Salmonella, particularly associated with low-moisture foods including peanut butter. Even though roasting is included along the processing line, the presence of these safety issues indicates the requirement of process following the packaging of the samples. Because of the lower thermal diffusivity of the peanut butter, a conventional thermal process is expected to be challenging with expected temperature non-uniformities. Therefore, radio frequency (RF) heating was considered in this study for thermal processing of peanut butter samples. For this purpose, a computational model was developed to determine the temperature change of peanut butter samples. Experimental studies for model validation were completed in a 10 kW - 27.12 MHz RF system at 3300 and 4000 V electrode potentials. Following the model validation, a comparison to the conventional thermal processing was presented, and industrial scale thermal processing studies were applied where up to 30 packaged samples were placed within the RF cavity. Process efficiency was determined with the process time decrease, temperature uniformity and decontamination effects. Science4Impact: This study demonstrated RF processing for an efficient thermal decontamination with uniform temperature distribution attained within the samples in an industrial scale process.
- Derleme MakaleYalnız künye2026Emerging thermal and non-thermal technologies addressing Salmonella contamination in low-moisture spices and herbs
Lian, Yi; Verma, Tushar; Chen, Long; Sun, Shengqian; Ozturk, Samet; Subbiah, Jeyamkondan; Liu, Shuxiang; Wei, Xinyao
Spices and herbs are vital flavoring agents in food. However, they are particularly vulnerable to microbial contamination primarily due to their open production environments and low water activity, which enhances microbial resistance to conventional pasteurization. In addition, traditional decontamination methods often struggle to balance microbial safety and product quality. This review aims to deliver valuable insights into innovative technologies designed for improving microbial safety and overall quality of spices and herbs while fostering advancements in the industry. This review comprehensively summarizes the principles, applications, and influencing factors of emerging thermal technologies (e.g., radio frequency heating, superheated steam, and vacuum steam) and non-thermal technologies (e.g., ethylene oxide, chlorine dioxide, cold plasma, and ionizing irradiation). Furthermore, it critically discusses the current limitations of these technologies and proposes strategies for future advancements. Novel decontamination technologies show promise in improving microbial safety and preserving the quality of spice and herb products. In particular, radio frequency and chlorine dioxide technologies emerge as promising options for spice decontamination due to their better ability to balance microbial control efficiency and quality retention. Further research should focus on optimizing parameters through models, developing combination technologies, and promoting pilot test verification to facilitate industrial application.
- MakaleAçık Erişim2025Effect of heating rate on thermal inactivation kinetics of Escherichia coli O157:H7 in ground beef
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
The objective of this study was to investigate the effect of heating rate on thermal inactivation kinetics of microorganisms in food, testing the survival of Escherichia coli O157:H7 in ground beef during isothermal and dynamic heating. A 4-strain cocktail of E. coli O157:H7 was inoculated to irradiation-sterilized ground beef (10 % fat) and then subjected to isothermal heating (55–63 °C) and dynamic heating (20–63 °C). One-step analysis was used to determine the kinetic parameters. Different degrees of increased thermal resistance were observed in E. coli O157:H7 during dynamic heating. In comparison to isothermal heating, slight increase in the thermal resistance was found during fast heating (1.2–1.8 °C/min). However, slow heating (0.3–0.9 °C/min) led to significantly increased thermal resistance due to heat adaption at temperatures below 61.3 °C, but E. coli O157:H7 became more sensitive to heat above this temperature, suggesting that the increased resistance may diminish after reaching a critical temperature. To account for the increased heat resistance during dynamic heating, a unified kinetic model was developed and validated by applying one-step dynamic analysis, resulting in more accurate kinetic parameters to describe the survival curves of all heating rates. This study demonstrated that the kinetic parameters derived from isothermal conditions may not be applicable to dynamic conditions. It is necessary to consider the effect of heating rate and to determine the thermal inactivation kinetic parameters under dynamic conditions. It also demonstrated the advantage of using one-step dynamic analysis for evaluating thermal processes. The results of this study may be particularly useful for designing slow-heating processes to ensure proper cooking of products.
- MakaleYalnız künye2025One-step kinetic analysis of Listeria innocua growth as a surrogate for Listeria monocytogenes on arugula leaves with background microbiota: model development and validation
Ozturk, Samet
This study investigated the growth kinetics of L. monocytogenes and L. innocua on fresh arugula leaves under abusive conditions, considering the presence of background microbiota (BM) including (APC (Aerobic Plate Count), TPC (Total Psychrotrophic Count), and LAB (Lactic Acid Bacteria)). Additionally, the feasibility of using L. innocua as a surrogate for L. monocytogenes was evaluated for industrial practices. Predictive models were developed to assess the effect of temperature and time on the growth kinetics of both microorganisms. Experiments were conducted in triplicate to observe growth kinetics at temperatures from 5 to 35°C. The growth curves were analyzed using one-step analysis with the USDA IPMP-Global Fit software, employing the Huang full/no-lag phase growth as the primary models and the Huang sub-optimal (HSRM) and Ratkowsky sub-optimal square-root as the secondary models. An additional set of isothermal data, collected at 15°C and 20°C, was used to validate the models. Results showed that the minimum growth temperatures were 2.91±0.50°C for L. monocytogenes and 2.88±0.50°C for L. innocua, while 2.05±0.89, 1.93±0.98 and 3.55±1.97°C for APC, TPC and LAB, respectively. The specific growth rates of L. monocytogenes and L. innocua ranged from 0.01 to 0.93 h⁻¹. The root mean square error (RMSE) of model validation and development was less than 0.3 log CFU/g, indicating that the combination of the Huang growth model with HSRM could accurately predict the growth of L. monocytogenes under abusive conditions. Validated models can provide useful input to quantitative risk assessment tools to predict the growth of L. monocytogenes on arugula leaves in the presence of BM during distribution or storage. The findings of this study support the use of L. innocua with R2=0.961 as a suitable surrogate in industrial practices for fresh produce.
- MakaleAçık Erişim2024Isothermal inactivation kinetics of Salmonella and Enterococcus faecium NRRL B-2354 in oat flour
Ozturk, Samet
Bu çalışma, Salmonella'nın ısıl işlemin sırasında yulaf ununda hayatta kalma ve ısıl toleransını (D- ve z-değerleri) patojenik etki göstermeyen potansiyel müdavini olan Enterococcus faecium NRRL B-2354 (E. faecium) ile birlikte belirlemeyi amaçlamıştır. Yulaf ununun su aktivite (aw) değeri , nem kontrollü bir ortamda 0.40 olarak ayarlanarak S. Enteritidis PT30 ve E. faecium ile eşit şekilde inoküle (108-9 CFU/g) edilmiştir. Yulaf unu örnekleri (1 ± 0.1 g) daha sonra plastik torbalarda vakumlanarak paketlenmiş ve bakteriyel hayatta kalmayı değerlendirmek için 75, 80 ve 85°C’de sıcak su banyosunda ısıl işleme tabi tutulmuştur. S. Enteritidis PT30 ve E. faecium'un hayatta kalma eğrileri, iki ana model (Log-lineer ve Weibull modeli) kullanılarak analiz edilmiştir ve mikroorganizmaların hayatta kalma eğrilerinin birinci dereceden kinetik izlediği ortaya çıkmıştır. S. Enteritidis PT30 ve E. faecium'un yulaf unundaki D75C, D80C ve D85C değerleri sırasıyla 16.08 ± 1.36°C'den 2.27 ± 0.35 dakikaya ve 23.61 ± 1.39'dan 3.87 ± 0.42 dakikaya düşmüştür ve karşılık gelen z-değerleri sırasıyla 13.4 ± 0.37 ve 12.1 ± 0.41°C olarak bulunmuştur. Bu araştırmadan elde edilen D- ve z-değerleri, yulaf ununun mikrobiyel güvenliğini sağlamak için ısıl işlemin doğrulanmasında kullanılabilir.
- MakaleAçık Erişim2024Thermal resistance of Listeria monocytogenes, Escherichia coli O157:H7 and Salmonella in animal fat – Kinetic analysis and mathematical modeling
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
The objective of this study was to evaluate the effect of fat on thermal resistance of L. monocytogenes, E. coli O157:H7, and Salmonella spp. A 4-strain cocktail of each microorganism was inoculated to beef tallow and heated isothermally at temperatures between 55 and 80℃. All survival curves did not follow the 1st-order inactivation kinetics but conformed to a two-stage linear pattern. The first stage was markedly less heat-resistant than the second, as manifested by significantly lower D values. The z values of E. coli O157 H7 and Salmonella spp. were 11.8 °C and 12.3 °C in the first stage (z1) but increased to 23.7 °C and 20.8 °C in the second stage (z2), respectively. For L. monocytogenes, while the z values were similar for both stages (z1 = 19.6 °C and z2 = 18.5 °C), the second stage D values are 3.6–5.9 times of those in the first stage. One-step analysis was used to fit the nonlinear curves to the Weibull model, yielding < 1 exponents for the model (0.495, 0.362, and 0.282, respectively, for L. monocytogenes, E. coli O157:H7, and Salmonella spp.), suggesting gradually increased thermal resistance during heating. The experimental results showed that these microorganisms could resist heating for longer time and at higher temperatures in tallow than they do in regular meats containing lower levels of fat. The kinetic models can be used to develop thermal processes to properly inactivate pathogens contaminated in the fat portions of meat products or other high fat products.
- MakaleAçık Erişim2024Improving radio frequency heating uniformity in peanuts: Effects of packaging geometry, electrode gap, particle size and interlayer displacement process
Tasci, Caner; Liu, Shuxiang; Erdogdu, Ferruh; Ozturk, Samet
This study aimed to assess the impact of various processing parameters including electrode gap, packaging geometry, and particle size on the heating efficiency of radio frequency (RF) processing for peanut thermal decontamination. In addition, interlayer displacements were presented to evaluate the effect of the mixing on heating uniformity. Experimental studies were carried out using 3D-printed polylactic acid (PLA) containers (square, rectangular, and cylindrical) to place the peanut samples with particle sizes ranging from 0.71 to 2.00 mm at 100–140 mm electrode gaps. Temperature changes within the samples were monitored using fiber optic sensors and surface temperature distributions were determined with an infrared camera. Heating uniformity index (λ) was then calculated to assess the effects of RF processing conditions on RF heating uniformity. Results showed that the cylindrical container exhibited a more consistent and uniform heating profile (λ = 0.12) with 1.58 °C min−1 heating rate compared to other containers, and a single interlayer displacement between top and bottom layers further improved temperature distribution uniformity. Smaller particle sizes also led to faster heating rates from 1.71 to 1.55 °C min−1 with more uniform heating due to the reduced porosity within the particles with increased thermal conduction and electromagnetic energy absorption. This study presented valuable insights for developing an effective RF process as an alternative to conventional thermal treatments for decontamination of low-moisture, high-fat particulate foods. Industrial significance: This research presented an innovative approach applying RF heating for a possible decontamination process for peanut samples. The research tackled the growing worldwide consumer demand for food products to satisfy food safety regulations while peanuts were selected to demonstrate the process effect due to the recent food safety issues in peanut butter considering that a pre-process for decontamination would lead to a decrease in the resulting safety issues.
- BildiriYalnız künye2024RADIO FREQUENCY PROCESSING OF PEANUT BUTTER: COMPUTATIONAL MODEL DEVELOPMENT AND PROCESS DESIGN
Coskun, Eda; Ozturk, Samet; Tasci, Caner; Polat, Kubra; Liu, Shuxiang; Li, Rui; Wang, Shaojin; Mert, Behic; Marra, Francesco; Erdogdu, Ferruh
Within the last decade, Centers for Disease Control and Prevention (CDC) has reported outbreaks of Salmonella, particularly associated with low -moisture foods including peanut butter. In this study, radio frequency (RF) application was carried out for thermal processing of peanut butter samples. For this purpose, a computational model was developed to determine the temperature change of peanut samples using Comsol Multiphysics v6.0 (Comsol AB, Stockholm, Sweden), and experimental studies for model validation were completed in a 10 kW 27.12 MHz RF system at 3300 and 4000 V electrode potentials Following the model validation, industrial scale thermal processing studies were done with up to 30 samples located within the RF cavity. This study demonstrated the feasibility of the RF application for an efficient processing with rather uniform temperature distribution attained within the samples.
- MakaleYalnız künye2023Increased heat tolerance and transcriptome analysis of Salmonella enterica Enteritidis PT 30 heat-shocked at 42 ℃
Qiu, Yan; Ozturk, Samet; Cui, Xinyao; Qin, Wen; Wu, Qingping; Liu, Shuxiang
In this study, we compared the heat tolerance parameter (D65℃) values of Salmonella enterica serovar Enteritidis PT 30 (S. Enteritidis ) heat adapted at different degrees (at 42 ℃ for 20–180 min) and cultivated using two methods. The treated group with the highest D65℃ value (LP-42 ℃-60 min) and the untreated groups (Control-TSB and Control-TSA) were subjected to transcriptome analysis. Heat-adaptation increased the D65℃ values of S. Enteritidis by 24.5–60.8%. The D65℃ values of the LP-42 ℃-60 min group (1.85 ± 0.13 min, 7.7% higher) was comparable to that of the Control-TSA. A total of 483 up- and 443 downregulated genes of S. enteritidis were identified in the LP-42 ℃-60 min group (log2fold change > 1, adjusted p-value < 0.05). Among these genes, 5 co-expressed and 15 differentially expressed genes in the LP-42 ℃-60 min and Control-TSA grops possibly contributed to the high D65℃ values of S. Enteritidis. The Rpo regulon was involved in the heat adaptation of S. Enteritidis, as evidenced by the significant upregulation of rpoS, rpoN, and rpoE. KEGG enrichment pathways, such as biosynthesis of secondary metabolites, tricarboxylic acid, and ribosomes were identified and mapped to reveal the molecular mechanisms of S. enteritidis during heat adaptation. This study quantified the enhanced heat tolerance of S. Enteritidis heat adapted at different degrees of heat-adaptation. The results of this study may serve as a basis for elucidating the molecular mechanisms underlying the enhanced heat tolerance at the transcriptome level.
- MakaleYalnız künye2023Microwave decontamination processing of tahini and process design considerations using a computational approach
Topcam, Huseyin; Coskun, Eda; Son, Ezgi; Kutuk, Dilay; Aytac, S. Aykut; Mert, Behic; Ozturk, Samet; Erdogdu, Ferruh
Tahini, as a low moisture food product, is linked to several outbreaks of Salmonella recently even though a high temperature roasting (of sesame seeds) through its production is involved. Therefore, a final decontamination approach might be required for safety. Considering its higher oil content and lower thermophysical properties, conventional approaches are not easy to apply while preserving the quality attributes. Therefore, microwave heating was used for decontamination purpose. For this purpose, a computational mathematical model was developed first to determine the temperature distribution of tahini during microwave heating, and microbial inactivation studies for Salmonella enteritidis (ATCC 13076) were carried out. Changes in color and peroxide values were evaluated, and the experimentally validated model was further used to design an industrial process to achieve a 5-log cycle reduction as an efficient decontamination processing. The target temperature over 80 °C within the sample was demonstrated to achieve such a process, and industrial scale process conditions were presented for 262 kg/h process capacity.
- MakaleAçık Erişim2023Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements
Bowler, Alexander; Ozturk, Samet; di Bari, Vincenzo; Glover, Zachary J.; Watson, Nicholas J.
In manufacturing environments, real-time monitoring of yoghurt fermentation is required to maintain an optimal production schedule, ensure product quality, and prevent the growth of pathogenic bacteria. Ultrasonic sensors combined with machine learning models offer the potential for non-invasive process monitoring. However, methods are required to ensure the models are robust to changing ultrasonic measurement distributions as a result of changing process conditions. As it is unknown when these changes in distribution will occur, domain adaptation methods are needed that can be applied to newly acquired data in real-time. In this work, yoghurt fermentation processes are monitored using non-invasive ultrasonic sensors. Furthermore, a transmission based method is compared to an industrially-relevant non-transmission method which does not require the sound wave to travel through the fermenting yoghurt. Three machine learning algorithms were investigated including fully-connected neural networks, fully-connected neural networks with long short-term memory layers, and convolutional neural networks with long short-term memory layers. Three real-time domain adaptation strategies were also evaluated, namely; feature alignment, prediction alignment, and feature removal. The most accurate method (mean squared error of 0.008 to predict pH during fermentation) was non-transmission based and used convolutional neural networks with long short-term memory layers, and a combination of all three domain adaption methods.
- MakaleAçık Erişim2023Near-infrared spectroscopy and machine learning for classification of food powders during a continuous process
Ozturk, Samet; Bowler, Alexander; Rady, Ahmed; Watson, Nicholas J.
In food production environments, the wrong powder material is occasionally loaded onto a production line which impacts food safety, product quality, and production economics. The aim of this study was to assess the potential of using Near Infrared (NIR) spectroscopy combined with Machine Learning to classify food powders under motion conditions. Two NIR sensors with different wavelength ranges were compared and the ML models were tasked with classifying between 25 food powder materials. Eleven different spectra pre-processing methods, three feature selection methods, and five algorithms were investigated to find the optimal ML pipeline. It was found that pre-processing the spectra using autoencoders followed by using support vector machines with the all spectral wavelengths from both sensors was most accurate. The results were improved further using under-sampling and boosting. Overall, this method achieved 99.52, 97.12, 94.08, and 91.68% accuracy for the static, 0.017, 0.036 and 0.068 m s-1 sample speeds. The models were also validated using an independent test sets.