In this review paper, several aspects of fruit juice microbiology, from past to future perspectives, are considered. An overview of the most relevant outbreaks involving foodborne pathogens and spoilage microorganisms associated with fruit juices is provided. One of the sections provides data on the sources of fruit juice contamination, followed by perspectives on preservation methods. Furthermore, considerations on the role of international guidelines about exotic fruit juices in respect to public health, and of the microbiological status of fruit juices used as food/beverage ingredients are discussed. Issues and challenges highlight how the microbiology of fruit juices has evolved over the years, when aspects of stability or microbiological safety are under consideration.

Strict requirements of scientific journals allied to the need to prove the experimental data are (in)significant from the statistical standpoint have led to a steep increase in the use and development of statistical software. In this aspect, it is observed that the increasing number of software tools and packages and their wide usage has created a generation of 'click and go' users, who are eagerly destined to obtain the p-values and multivariate graphs (projection of samples and variables on the factor plane), but have no idea on how the statistical parameters are calculated and the theoretical and practical reasons he/she performed such tests. However, in this paper, some published examples are listed and discussed in detail to provide a holistic insight (positive points and limitations) about the uses and misuses of some statistical methods using different available statistical software. Additionally, a brief description of several commercial and free statistical software is made highlighting their advantages and limitations.

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The growth parameters (growth rate, μ and lag time, λ) of three different strains each of Salmonella enterica and Listeria monocytogenes in minimally processed lettuce (MPL) and their changes as a function of temperature were modeled. MPL were packed under modified atmosphere (5% O₂, 15% CO₂ and 80% N₂), stored at 7-30 °C and samples collected at different time intervals were enumerated for S. enterica and L. monocytogenes. Growth curves and equations describing the relationship between μ and λ as a function of temperature were constructed using the DMFit Excel add-in and through linear regression, respectively. The predicted growth parameters for the pathogens observed in this study were compared to ComBase, Pathogen modeling program (PMP) and data from the literature. High R² values (0.97 and 0.93) were observed for average growth curves of different strains of pathogens grown on MPL. Secondary models of μ and λ for both pathogens followed a linear trend with high R² values (>0.90). Root mean square error (RMSE) showed that the models obtained are accurate and suitable for modeling the growth of S. enterica and L. monocytogenes in MP lettuce. The current study provides growth models for these foodborne pathogens that can be used in microbial risk assessment.

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