In industrialized countries, gradual innovations dominate the food and packaging sector whereas real breakthroughs are rare. Therefore, future developments can be predicted from the state of the art as the market penetration of new technologies may take decades.Often-mentioned innovation areas in food packaging are active and intelligent packaging and bio-based polymers. New regulations for food contact of these systems had to be created, finally leading to the 450/2009/EC in 2009 on active and intelligent materials and articles. It was expected that this new class of packaging would have a huge impact on the market. Today, the main types of active food packaging are oxygen absorbers and a gradual increase in market volume is observed.Antimicrobially active materials or materials for the control of the humidity in the interior of packages are still in the development stage. Their feasibility has been shown in principle, but successful applications are still few. Here, growth can be expected, especially in the sectors of fresh produce and meat.In the sector of intelligent packaging, monitoring and indication of the quality status of the product via freshness indicators is often believed to replace the “best before”-date. Their reliability, however, is still very limited and they have to be adapted to every individual product.Bio-based and biodegradable plastics are continuously discussed as solution for the problems of limited resources and abundant littering. Here, the limited barrier properties of fully bio-based polymers will favor the production of conventional polymers from natural raw materials. Finally, appropriate packaging for delivery at home is to be developed as current systems are still in their infancy. As a conclusion, we observe many possibilities for innovations in food packaging, but the rate for true product innovations to appear on the market will be relatively low.

Predictive food microbiology models are increasingly applied to evaluate, improve and document microbiological food safety of fresh and lightly preserved foods. Within the dairy sector, these mathematical models and software may contribute to innovations in product formulation, packaging and distribution. However, this potential seems far from fully exploited. Predictive food microbiology models can be used to evaluate the combined effect of product characteristics and storage conditions on growth or survival of human pathogenic microorganisms. In relation to product formulation or reformulation, e.g. when salt/sodium is reduced, it can be important to evaluate how other product characteristics need to be changed to compensate for the changes and obtain a sufficient microbial inhibition. Related to product distribution, models and software can be applied to evaluate the effect of constant and changing temperature on potential microbial growth after the consumers have opened the packaged products and starting storing them in their own refrigerators.To be valuable, predictive food microbiology models must be accurate and include the effect that specific processing and distribution parameters have on the microbial growth and survival.  An overview of available predictive food microbiology models for dairy products will be presented with description of the factors they included, and the models’ performance when applied for specific groups of dairy products: Raw and pasteurized milk as well as fermented products including fresh and ripened cheeses. Special focus will be on the cardinal parameter model and on software available for the dairy sector. 

Both in Europe and worldwide, cheese has caused important outbreaks of listeriosis and has been a vehicle for transmission of Listeria monocytogenes to consumers. A systematic review and a meta-analysis were conducted using scientific literature and European Food Safety Authority (EFSA) reports to summarize available data on the prevalence of L. monocytogenes in different types of cheeses produced in Europe. Multi-level random-effects meta-analysis models were used to estimate mean prevalence rates of the pathogens and to compare prevalence between types of cheeses (fresh, mould-ripened, ripened, smear-ripened and brined) and for cheeses produced using pasteurized or un-pasteurized milk. Data from a total of 177,428 samples were analysed. The mean prevalence during 2005-2013 and estimated from scientific literature (2.3%; CI: 1.4-3.8%) was more than two times higher than results from EFSA reports (0.9%; CI: 0.7-1-2%). The prevalence differed between types of cheeses including fresh (1.4%; CI: 0.6-3.2%), mould-ripened (2.0%; CI: 0.6-6.3%), ripened (2.2%; CI: 0.9-5.6%), smear-ripened (4.8%; CI: 1.5-14.5%) and brined cheeses (8.6%; CI: 1.7-34.4%). Mean prevalences of L. monocytogenes in fresh and soft/semi-soft cheeses were not significantly different (P > 0.05) for cheeses produced from pasteurized (1.0%; CI: 0.7-1.5%) or un-pasteurized (1.4%; CI: 0.9-2.1%) milk. Furthermore, this systematic review focused on groups/species of microorganisms suitable as indicator organisms for L. monocytogenes in cheeses to reflect the level of production hygiene or as index organisms to assess the prevalence of L. monocytogenes in cheeses. However, no indicator or index organisms were identified. These meta-analyses improve our understanding of L. monocytogenes prevalence in different types of cheeses and provided results that can be useful as input for quantitative risk assessment modelling.