Technology is now being developed that is able to handle vast amounts of structured and unstructured data from diverse sources and origins. These technologies are often referred to as big data, and open new areas of research and applications that will have an increasing impact in all sectors of our society. In this paper we assessed to which extent big data is being applied in the food safety domain and identified several promising trends. In several parts of the world, governments stimulate the publication on internet of all data generated in public funded research projects. This policy opens new opportunities for stakeholders dealing with food safety to address issues which were not possible before. Application of mobile phones as detection devices for food safety and the use of social media as early warning of food safety problems are a few examples of the new developments that are possible due to big data.

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In this study, a Bayesian Network (BN) was developed for the prediction of the hazard potential and biological effects with the focus on metal-and metal-oxide nanomaterials to support human health risk assessment. The developed BN captures the (inter) relationships between the exposure route, the nanomaterials physicochemical properties and the ultimate biological effects in a holistic manner and was based on international expert consultation and the scientific literature (e.g., in vitro/in vivo data). The BN was validated with independent data extracted from published studies and the accuracy of the prediction of the nanomaterials hazard potential was 72% and for the biological effect 71%, respectively. The application of the BN is shown with scenario studies for TiO 2 , SiO 2 , Ag, CeO 2 , ZnO nanomaterials. It is demonstrated that the BN may be used by different stakeholders at several stages in the risk assessment to predict certain properties of a nanomaterials of which little information is available or to prioritize nanomaterials for further screening.ARTICLE HISTORY

Barley is a small-grain cereal that can be infected by Fusarium spp. resulting in reduced quality and safety of harvested barley (products). Barley and other small-grain cereals are commonly studied together for Fusarium infection and related mycotoxin contamination, since the infection and its influencing factors are assumed to be the same for all small-grain cereals. Using relevant literature, this study reviewed Fusarium spp. infection and mycotoxin contamination, mainly T-2/HT-2 toxin and deoxynivalenol (DON), in barley specifically. For the first time, review results provide an extensive overview of the influencing factors for Fusarium infection and mycotoxin production in barley, such as weather, agricultural management and processing factors, and includes the comparison of these mechanisms in wheat. Results showed that Fusarium infection in barley is difficult to recognise in the field and mycotoxin levels cannot be estimated based on the symptoms. These factors make it difficult to establish the real severity of Fusarium infection in barley. In addition, most pre-harvest measures to mitigate initial Fusarium infection, such as cultivar use and soil cultivation, are the same for barley and wheat, but due to anatomical differences, some pre-harvest measures have a different effect on Fusarium infection in barley. For example, the effective moment (days after anthesis) of fungicide application in barley and wheat is different. Also, in wheat, there is an additional effect of multiple fungicide applications in reducing Fusarium Head Blight and DON concentrations, whereas in barley, no additional effect of multiple application is seen. Hence, care should be taken to use data from one small-grain cereal to draw conclusions on other small-grain cereals.

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