Monitoring the effect of active packaging films with silver-kaolinite using different packaging systems on the quality of beef meat.

Active packaging films based on gelatin with silver-kaolinite (Ag-Kln) were developed and their effects on the quality and microbial growth of beef meat stored in different packaging systems (cling film, vacuum and modified atmosphere packaging) at 4 °C for 13 days were evaluated. The analysis revealed that Ag-Kln packaging films had no adverse effects on the pH and colour of the beef samples irrespective of the packaging system used. Beef meat in packaging with active films lost more weight (P < 0.05) than without active films for meat in the vacuum and modified systems on day 13. In general, these gelatin films with Ag-Kln showed the potential as antibacterial films and could enhance the shelf life of food products, however, further studies are required to establish the release rate of silver from packaging films, as well as test the efficiency of these materials under different storage conditions. In conclusion, this study revealed that gelatin film with silver-kaolinite is a promising antibacterial agent and preservation material for food shelf life extension.

Analysis of spatio-temporal patterns of African swine fever cases in Russian wild boar does not reveal an endemic situation.

African swine fever (ASF) is a highly lethal viral disease of domestic pigs and wild boar. ASF was introduced into the southern Russian Federation in 2007 and is now reported to be spreading in populations of wild and domestic suids. An endemic situation in the local wild boar population would significantly complicate management of the disease in the livestock population. To date no sound method exists for identifying the characteristic pattern of an endemic situation, which describes infection persisting from generation to generation in the same population. To support urgent management decisions at the wildlife-livestock interface, a new algorithm was constructed to test the hypothesis of an endemic disease situation in wildlife on the basis of case reports. The approach described here uses spatial and temporal associations between observed diagnostic data to discriminate between endemic and non-endemic patterns of case occurrence. The algorithm was validated with data from an epidemiological simulation model and applied to ASF case data from southern Russia. Based on the algorithm and the diagnostic data available, the null hypothesis of an endemic situation of ASF in wild boar of the region was rejected.