Journal of Food and Bioprocess Engineering

The effect of infrared on Bacillus cereus in paprika powder: Modeling through genetic algorithm-artificial neural network

Document Type : Original research

Authors

1 Department of Chemical Engineering, Iranian Research Organization for Science & Technology (IROST), Tehran-Iran

2 Department of Food Science and Technology, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

Abstract

In this study, the effect of infrared (IR) on decontamination of Bacillus cereus, color, weight losses, and temperature profiles at paprika powder was determined in difference IR radiation power (100, 200, and 300 W), different sample distances from a radiation source (5, 10, and 15 cm), and various holding times. The most reduction of B. cereus count (2.3 log CFU/g) was achieved after 1 min holding time at 200 W IR power and 5 cm distance. The highest D-value (0.18 min) was achieved after a holding time of 0.5 min at 300 W IR power and 5 cm distance. The a* value of paprika powder was slightly affected and the highest color change was observed at 100 W IR power, 10 cm distance, and 8 min resulting in a decrease of a* from 42.537 ± 0.201 to 38.645 ± 0.429. Data were analyzed to predict the antibacterial effects of IR on B. cereus in paprika powder through an artificial neural network (ANN) model. The developed GA-ANN, which included 20 hidden neurons, could predict the B. cereus population with R2 = 0.9561. The results indicated that the GA-ANN model could give a good prediction for the population of B. cereus. Sensitivity analysis results showed that IR irradiation time was the most sensitive factor for the prediction of the B. cereus population.

Keywords

Main Subjects

Atsamnia, D., Hamadache, M., Hanini, S., Benkortbi, O., & Oukrif, D. (2017). Prediction of the antibacterial activity of garlic extract on E. coli, S. aureus and B. subtilis by determining the diameter of the inhibition zones using artificial neural networks. LWT-Food Science & Technology, 82, 287-295.
Banerjee, M., & Sarkar, P. K. (2003). Microbiological quality of some retail spices in India. Food Research International, 36(5), 469-474.
Eliasson, L., Isaksson, S., Lövenklev, M., & Ahrné, L. (2015). A comparative study of infrared and microwave heating for microbial decontamination of paprika powder. Frontiers in Microbiology, 6, 1071.
Erdoğdu, S. B., & Ekiz, H. İ. (2011). Effect of ultraviolet and far infrared radiation on microbial decontamination and quality of cumin seeds. Journal of Food Science, 76(5), M284-M292.
Erdoğdu, S. B., & Ekiz, H. İ. (2013). Far infrared and ultraviolet radiation as a combined method for surface pasteurization of black pepper seeds. Journal of Food Engineering, 116(2), 310-314.
European Food Safety Authority, (2005). Opinion of the scientific panel on biological hazards on Bacillus cereus and other Bacillus spp in foodstuffs. EFSA Journal, 175, 1–48.
Funes, E., Allouche, Y., Beltrán, G., Aguliera, M. P., & Jiménez, A. (2017). A predictive artificial neural network model as a simulator of the extra virgin olive oil elaboration process. Journal of Near Infrared Spectroscopy, 25(4), 278-285.
Gonçalves, E. C., Minim, L. A., Coimbra, J. S. R., & Minim, V. P. R. (2005). Modeling sterilization process of canned foods using artificial neural networks. Chemical Engineering & Processing: Process Intensification, 44(12), 1269-1276.
Kavuncuoglu, H., Kavuncuoglu, E., Karatas, S. M., Benli, B., Sagdic, O., & Yalcin, H. (2018). Prediction of the antimicrobial activity of walnut (Juglans regia L.) kernel aqueous extracts using artificial neural network and multiple linear regression. Journal of microbiological methods, 148, 78-86.
Krishnamurthy, K. (2006). Decontamination of milk and water by pulsed UV light and infrared heating [PhD dissertation]. Pa.: Dept. of Agricultural and Biological Engineering, The Pennsylvania State Univ.
Krishnamurthy, K., Khurana, H. K., Soojin, J., Irudayaraj, J., & Demirci, A. (2008). Infrared heating in food processing: An overview. Comprehensive Reviews in Food Science and Food Safety, 7(1), 2-13.
McKee, L. H. (1995). Microbial contamination of spices and herbs: A review. LWT - Food Science and Technology, 28(1), 1-11.
Meenu, M., Guha, P., & Mishra, S. (2018). Impact of infrared treatment on quality and fungal decontamination of mung bean (Vigna radiata L.) inoculated with Aspergillus spp. Journal of the Science of Food and Agriculture, 98(7), 2770-2776.
Morimoto, T. (2006). Genetic algorithm. In Handbook of Food and bioprocess modeling techniques, (S.S. Sablani, M.S. Rahman, A.K. Datta, and A.S. Mujumdar, eds.) pp. 405-434, CRC Press, New York.
Sagdic, O., Ozturk, I., & Kisi, O. (2012). Modeling antimicrobial effect of different grape pomace and extracts on S. aureus and E. coli in vegetable soup using artificial neural network and fuzzy logic system. Expert Systems with Applications, 39, 6792-6798.
Sagoo, S. K., Little, C. L., Greenwood, M., Mithani, V., Grant, K. A., McLauchlin, J., & Threlfall, E. J. (2009). Assessment of the microbiological safety of dried spices and herbs from production and retail premises in the United Kingdom. Food microbiology, 26(1), 39-43.
Salehi, F., & Razavi, S. M. A. (2012). Dynamic modeling of flux and total hydraulic resistance in nanofiltration treatment of regeneration waste brine using artificial neural network. Desalination & Water Treatment, 41, 95-104.
Shavandi, M., Taghdir, M., Abbaszadeh, S., Sepandi, M., & Parastouei, K. (2020a). Modeling the inactivation of Bacillus cereus by infrared radiation in paprika powder (Capsicum annuum). Journal of Food Safety, 40(4), e12797.
Shavandi, M., Javanmard, M., & Basiri, A. (2022). Novel popping through infrared: Effect on some physicochemical properties of popcorn (Zea Mays L. var. Everta). LWT, 155, 112955.
Shavandi, M., Kashaninejad, M., Sadeghi, A., Jafari, S, M., & Hasani, M. (2018). Evaluation of selective infrared radiation on inactivation of Bacillus Cereus by response surface methodology. Food engineering research (Journal of Agricultural Engineering Research), 17, 57-70.
Shavandi, M., Kashaninejad, M., Sadeghi, A., Jafari, S. M., & Hasani, M. (2020b). Decontamination of Bacillus cereus in cardamom (Elettaria cardamomum) seeds by infrared radiation and modeling of microbial inactivation through experimental models. Journal of Food Safety, 40(1), e12730.
Shavandi, M., Sadeghi, A., & Sarani, A. (2020c). Modeling the effect of different infrared treatment on B. cereus in cardamom seeds and using genetic algorithm-artificial neural network. Journal of Food and Bioprocess Engineering, 3(1), 29-34.
Soleimanzadeh, B., Amoozandeh, A., Shoferpour, M., & Yolmeh, M. (2018). New approaches to modeling Staphylococcus aureus inactivation by ultrasound. Annals of Microbiology, 68(6), 313-319.
Staack, N., Ahrné, L., Borch, E., & Knorr, D. (2008). Effects of temperature, pH, and controlled water activity on inactivation of spores of Bacillus cereus in paprika powder by near-IR radiation. Journal of Food Engineering, 89(3), 319-324.
Trivittayasil, V., Tanaka, F., Hamanaka, D., & Uchino, T. (2013). Inactivation model of mold spores by infrared heating under non-isothermal conditions. Food Science & Technology Research, 19(6), 979-982.
Yolmeh, M., Najafi, M. B. H., & Salehi, F. (2014). Genetic algorithm-artificial neural network and adaptive neuro-fuzzy inference system modeling of antibacterial activity of annatto dye on Salmonella enteritidis. Microbial Pathogenesis, 67-68, 36-40.
Journal of Food and Bioprocess Engineering
Volume 5, Issue 1
June 2022
Pages 52-59