Modeling the effect of different infrared treatment on B. cereus in cardamom seeds and using genetic algorithm-artificial neural network

Document Type : Original research


1 Department of Food Process Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

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


In this study, the effect of infrared (IR) on decontamination of Bacillus cereus in cardamom seeds were determined at difference IR radiation powers (100, 200, and 300 W), different sample distances from radiation source (5, 10 and 15 cm) and various holding times. The most successful reduction in B. cereus numbers (5.11 log CFU/g) was achieved after a holding time of 8 min at 300 W IR power and 15 cm distance. Data were analyzed to predict antibacterial effects of IR against B. cereus in cardamom by artificial neural network (ANN) model. The developed genetic algorithm-ANN (GA-ANN), which included 12 hidden neurons, could predict B. cereus population with R2 = 0.908. The results indicated that GA-ANN model could give 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 B. cereus population.


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 and Technology, 82, 287-295.
Bahram Parvar, M., Salehi, F., Razavi, S. M. A. (2013). Predicting total acceptance of ice cream using artificial neural network. Journal of Food Processing and Preservation, 1-9.
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. (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.
Ginzburg, A. S. (1969). Theoretical principles of heating and drying using infra-red radiation. In A. S. Ginsberg (Ed.), Application of infra-red radiation in food processing. London: Leonhard Hill Books, pp. 1−71.
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 and Processing: Process Intensification, 44(12), 1269-1276.
Griffiths, M. W., & Schraft, H. (2017). Bacillus cereus food poisoning. In Foodborne Diseases (Third Edition) (pp. 395-405).
Hamanaka, D., Dokan, S., Yasunaga, E., Kuroki, S., Uchino, T., & Akimoto, K. (2000). The sterilization effects of infrared ray on the agricultural products spoilage microorganisms. St Joseph, 1-9.
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.
Klimešová, M., Horáček, J., Ondřej, M., Manga, I., Koláčková, I., Nejeschlebová, L., & Ponížil, A. (2015). Microbial contamination of spices used in production of meat products. Potravinarstvo Slovak Journal of Food Sciences, 9(1), 154-159.
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.
Marzouk, M., & Elkadi, M. (2016). Estimating water treatment plants costs using factor analysis and artificial neural networks. Journal of Cleaner Production, 112, 4540-4549.
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.
Nair, K. P. (2006). The agronomy and economy of Cardamom (Elettaria cardamomum M.): the “queen of spices”. Advances in agronomy, 91, 179-471.
Parthasarathy, V. A., & Prasath, D. (2012). Cardamom. In Handbook of Herbs and Spices (Second Edition), Volume 1 (pp. 131-170).
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 Applications39(8), 6792-6798.
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 and Water Treatment, 41, 95-104.
Shavandi M, Taghdir M, Abbaszadeh S, Sepandi M, Parastouei K. (2020b). Modeling the inactivation of Bacillus cereus by infrared radiation in paprika powder (Capsicum annuum). Journal of Food Safety. e12797s.
Shavandi, M., Kashaninejad, M., Sadeghi, A., Jafari, S, M., Hasani, M. (2020a). Decontamination of Bacillus cereus in cardamom (Elettaria cardamomum) seeds by infrared radiation and modeling of microbial inactivation through experimental models. Journal of Food Safety. e12730.
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.
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.
Tainter, D., Grenis, A., & Norwat, R. (2001). Spices and seasonings: a food technology handbook. John Wiley & Sons. Second edition (Vol. 1).
Trivittayasil, V., Tanaka, F., Hamanaka, D., & Uchino, T. (2013). Inactivation Model of Mold Spores by Infrared Heating under Non-Isothermal Conditions. Food Science and Technology Research, 19(6), 979-982.
Yamamura, S., Kawada, K., Takehira, R., Nishizawa, K., Katayama, S., Hirano, M., & Momose, Y. (2008). Prediction of aminoglycoside response against methicillin-resistant Staphylococcus aureus infection in burn patients by artificial neural network modeling. Biomedicine & Pharmacotherapy, 62(1), 53-58.
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.