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The effect of food simulants on properties and light barrier function of LDPE-nano TiO 2 composite film has been investigated. LDPE-nano TiO 2 composite films were prepared with 5.0wt% TiO 2 content by melt-extrusion. To simulate food contact environment, according to KFDA standards and specifications for food utensils, containers and packages, food simulants were selected with deionized water, 50% ethanol, 4% acetic acid and n-heptane and composite films were immersed in each food simulant at 70 o C, 30 min except n-heptane (25 o C, 60 min). A variety of material properties, including crystallinity, chemical bonds, surface morphology, mechanical, oxygen barrier and optical properties, of LDPEnano TiO 2 composite film were examined with and without the food simulants treatment. As a result, under regulated migration condition, LDPE-nano TiO 2 composite showed extremely stable in all properties tested in the study in contact with food simulants indicating that TiO 2 nanoparticles are physicochemically stable and quite compatible with LDPE. Results enable us to anticipate migration of TiO 2 will probably not occur. To evaluate influence of migration of TiO 2 on food stuffs, their color, pH and acidity were observed as well.

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The Big Data, the element of the Fourth Industrial Revolution, is drawing attention as the 4th Industrial Revolution is mentioned in the 2016 World Economic Forum. Big Data is being used in various fields because it predicts the near future and can create new business. However, utilization and research in the field of packaging are lacking. Today packaging has been demanded marketing elements that effect on consumer choice. Big data is actively used in marketing. In the marketing field, big data can be used to analyze sales information and consumer reactions to produce meaningful results. Therefore, this study proposed a method of applying big data in the field of packaging focusing on marketing. In this study suggest that try to utilize the private data and community data to analyze interaction between consumers and products. Using social big data will enable to understand the preferred packaging and consumer perceptions and emotions in the same product line. It can also be used to analyze the effects of packaging among various components of the product. Packaging is one of the many components of the product. Therefore, it is not easy to understand the impact of a single packaging element. However, this study presents the possibility of using Big Data to analyze the perceptions and feelings of consumers about packaging.