Polynomial surface fitting and artificial neural networks‐based analysis of the storage days and garlic extract supplementation dependent microbial growths in minced raw chicken meat

Külcü, Duygu Balpetek; Kalkan, Selin; Akben, Selahaddin Batuhan

doi:10.1111/jfpp.13882

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…The models used in studies are the linear, Gompertz, Weibull Ratkowsky, Baranyi, and logistic models [19]. Similar to the present study, in their study, Külcü and coauthors [20] treated the chicken minces with garlic Brazilian Archives of Biology and Technology. Vol.65: e22200801, 2022 www.scielo.br/babt extract and modeled the microbiological parameters by using the polynomial surface fitting (PSF) method and artificial neural networks (ANN) modeling method.…”

Section: Evaluating the Mathematical Modelsmentioning

confidence: 64%

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Modeling the Microbial Shelf-Life of Chicken Mince Added Rosemary Extract

Külcü

Kalkan

2022

Braz. arch. biol. technol.

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Using the non-linear regression model, the present study aims to develop sample mathematical models for the microbial flora by utilization of the antimicrobial effects of rosemary (Rosmarinus officinalis) extracts at different concentrations (0.5, 1, 1.5, and 2%) on the raw chicken mince. For this purpose, 5 experimental groups were established for each plant extract. The samples (100 g each) treated with plant extract at different concentrations were vacuum-packaged under aseptic conditions. The packaged samples were kept in refrigerator (4ºC). The microbiological analyses of (total mesophilic aerobic bacteria, total coliform group bacteria, S. aureus, total yeast-mold, and total psychrophilic bacteria) were performed on 0 th , 1 st , 3 rd , 5 th , 7 th , and 10 th days of storage. When compared to the control group the treatment with RE resulted in a decrease in the microbial numbers by 2.5 log units for TMAB number, by 3.5 log units for S. aureus number, by 3,5 log units for TMY number and by 1.5 log units for TP bacteria on the final day of storage. In establishing the model, the plant extract and storage period were used as variable parameters, whereas the shelf-life was used as output parameter. The changes in shelf-life of raw chicken minces by storage period and extract concentration were modeled, the compliance of obtained mathematical models was tested using Variance Analysis Method (ANOVA) and regression and determination coefficients (R 2 ) were determined. After determining their compliance of models based on R 2 values, the estimated values and real values were compared. As a result of study, it was determined that R 2 values of raw chicken mince models by total mesophilic aerobic bacteria, S. aureus, total coliform bacteria, total yeast/mold, and total psychrophilic bacteria during the storage period were found to range between 0.743 and 0.978 and the models representing the microbial change were found to have a high level of compliance. HIGHLIGHTS• The microbiological properties of minced chicken changed with the use of rosemary extract.• A significant increase in shelf-life and quality was achieved depending on the extract concentration.• The use of 1% rosemary extract had a positive effect on the quality parameters.• Storage day and rosemary (Rosmarinus officinalis) extract supplementation dependent microbial values in minced chicken meat can be modelled with values close to 1.

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Section: Evaluating the Mathematical Modelsmentioning

confidence: 64%

“…RE added chicken mince samples were prepared according to Külcü and coauthors [20]. Chicken mince samples were divided into 5 equal portions (100 g each) under aseptic conditions and by using sterile gloves and 5 experimental groups were established for each plant extract used in the present study.…”

Section: Sample Preparation and Microbiological Analysesmentioning

confidence: 99%

Modeling the Microbial Shelf-Life of Chicken Mince Added Rosemary Extract

Külcü

Kalkan

2022

Braz. arch. biol. technol.

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“…The simplest way of determining which model is better represented by experimental data is to compare the determinant coefficients ( R 2 ), although there are some objections (Külcü, Kalkan, & Akben, ). As it can be seen in Figure and Table , the RMSE values are at the lowest level when the R 2 and Adj_ R 2 values are at maximum.…”

Section: Resultsmentioning

confidence: 99%

Predicting the antimicrobial effect of probiotic lactic acid bacteria against Staphylococcus aureus in white cheeses, using Fourier series modeling method

Kalkan

2019

Journal of Food Safety

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In this study, it was aimed to design the time-predicted inactivation model for various growth curves and the growth parameters representing the changes in the inactivation of Staphylococcus aureus in probiotic white cheese. For this purpose, S. aureus were inoculated in the pasteurized milk and the production of probiotic white cheese was performed in five different groups, and then samples were matured for 60 days at 4 C.S. aureus, Lactobacillus rhamnosus, Lactobacillus casei Shirota, and mesophilic starter culture levels of the samples were analyzed on the 1st, 4th, 7th, 10th, 15th, 30th, and 60th days of maturation. The inactivation model evaluation was performed by using the number of microorganisms counted with Fourier modeling method. In determining the model to be applied, the coefficient of determination (R 2 ) and the sum of squared errors (SSE) for the mean number of microorganisms detected via modeling method were used. As conclusions, the number of S. aureus has decreased by approximately 5 logarithmic units at the end of the storage period by using probiotics together with the starter culture. It was determined that the Fourier modeling method is a suitable inactivation model with R 2 values of 0.9847-0.9986 and SSE values of 0.094-0.510.

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“…Minced chicken Inhibition of microbial growth at the end of storage days and 1-day shelf-life extension upon garlic extract incorporation in raw minced chicken meat Külcü et al (2019) Abbreviations: ABTS, 2,2′ azino-bis-3-ethylbenzothiazoline-6-sulfonic acid; BHA, butylated hydroxyanisole; DPPH, 2,2-diphenyl-1-picrylhydrazyl; FFV, free fatty acid; MDA, malonaldehyde; PV, peroxide value; TBARS, thiobarbituric acid reactive substances; UAE, ultrasound-assisted extraction.…”

Section: Garlicmentioning

confidence: 99%