Development and application of predictive models for fungal growth as tools to improve quality control in yogurt production Maria Gougouli a , Kelly Kalantzi b , Evangelos Beletsiotis b , Konstantinos P. Koutsoumanis a, * a Laboratory of Food Microbiologyand Hygiene, Department of Food Science and Technology, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece b Quality Assurance Department, Delta Foods S.A., 23rd km National Road Athens-Lamia, 145 65 Agios Stefanos, Greece article info Article history: Received 17 March 2011 Received in revised form 11 July 2011 Accepted 12 July 2011 Available online 20 July 2011 Keywords: Fungal growth models Temperature Inoculum size Yogurt abstract The effect of storage temperature (0e40  C) and inoculum size (10 1 e10 5 spores) on the mycelium growth kinetics of 12 fungal species on yogurt were monitored. A cardinal model with inflection (CMI) was used to describe the effect of temperature on the growth rate (m) and the lag time (l) of each isolate. Significant differences on the temperature dependence of the mycelium growth between the tested species were observed. Depending on the strain, the estimated minimum, optimum and maximum temperature parameters for m (T min , T opt , T max ) ranged from 7.6 to 9.6,19.5 to 37.8 and 29.8 to 46.9  C, respectively. Only l was found to be affected by the inoculum size and a linear relation between Ln (l) and Log (inoculum size) was revealed. The inoculum level did not influence the values of T min , T opt and T max for l. Based on the above observations, the combined effect of inoculum size and temperature on l was modeled using a modified CMI. The parameter l opt (l at optimum conditions) was expressed as a function of the inoculum size. Validation studies showed a good performance of the developed models. The application scheme of the models for improving fungi control in yogurt productions is discussed. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Yogurt, a semisolid fermented dairy product made with the use of Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus sal- ivarius subsp. thermophilus cultures, is a popular food product worldwide, known for its unique health and nutritional benefits (Lourens-Hattingh and Viljoen, 2001; Muir, 1996). Due to its bio- preservation potential, provided by the added starter cultures, yogurt is regarded as a product of enhanced safety (Schnürer and Magnusson, 2005). However, it is likely to be contaminated with fungal spores (ICMSF, 2000; Montagna et al., 1998) during the production process from various sources in the dairy plant envi- ronment including air, contaminated packaging material, starter cultures, ingredients and stabilizing agents (Cousin, 2002; ICMSF, 2000; Ndagijimana et al., 2008; Ottaviani and Ottaviani, 2003). Genera such as Penicillium, Aspergillus, Rhizopus, Fusarium and Mucor are the most frequent contaminants of yogurt (Cousin, 2002; Montagna et al., 1998; Muir, 1996; Ndagijimana et al., 2008). Considering that the majority of the above fungal species can grow in the acidic yogurt environment (ICMSF, 2000; Montagna et al., 1998), once contamination occurs the appearance of a visible mycelium on yogurt’s surface within the product’s shelf life is likely. The development of visible mycelia is one of the most significant quality problems in yogurt production with important economic implications for the dairy industry. Refrigeration storage of yogurt is usually not sufficient to prevent spore germination and mycelium growth, since most fungal species are also able to grow at low temperatures (Baert et al., 2007a, b; Cuppers et al., 1997; Lahlali et al., 2005; Magan, 2007; Ndagijimana et al., 2008; Plaza et al., 2003). Moreover, studies on the chill chain have shown that significant temperature abuses may occur during distribution, retail and domestic storage and handling of foods (Giannakourou et al., 2001, 2005; Koutsoumanis, 2001; Koutsoumanis et al., 2010; Laguerre et al., 2002). Consequently, the development of effective hygiene control measures and sampling procedures for the presence of fungi are of great importance for the quality assurance of yogurt. The concept of predictive mycology can be used as an effective tool for improving the quality control systems in yogurt production. Predictive mycology relies on quantitative data concerning the relative impact of various factors on fungal growth and germination of fungal spores (Dantigny, 2004; Dantigny et al., 2005). The last decade an increased number of predictive models for fungal growth have been developed (Cuppers et al., 1997; Gougouli and Koutsoumanis, 2010; Marín et al., 2009; Nevarez et al., 2009; Panagou et al., 2003). Most of these models focus on the single or * Corresponding author. Tel./fax: þ30 2310991647. E-mail address: kkoutsou@agro.auth.gr (K.P. Koutsoumanis). Contents lists available at ScienceDirect Food Microbiology journal homepage: www.elsevier.com/locate/fm 0740-0020/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.fm.2011.07.006 Food Microbiology 28 (2011) 1453e1462