The secondary growth model for Salmonella was developed based on the artificial neural network (ANN) with data collected from ComBase and FoodData Central. In addition to the existing secondary model variables (temperature, pH, Na+, and water contents), more input variables (sugar, carbohydrate, lipid, and protein contents) were considered. The output variables were microbial growth parameters (lag phase duration [l] and maximum growth rate [mmax]). A commercial ANN program (NeuralWorks Predict) was utilized with training at 80%, validation at 10%, and test data at 10%. ANN models were created using all data and cleansed data. Using the cleansed data, the training/testing root mean square error (RMSE) for mmax improved from 0.14/0.16 to 0.11/0.14, whereas the RMSE for l was still not acceptable, from 11.94/33.03 to 7.09/4.18. The l data were divided into two ranges with high and low goodness of fit, whereas the ANN model for each field was built, resulting in an optimally low RMSE.

This study aims to establish the national strategy for biodiversity conservation by analyzing the current status of ecodiversity as the foundation of biodiversity conservation. Furthermore, this study has another purpose of preparing the measures for conservation and restoration of biodiversity. Ecodiversity was discussed as the basis for conserving biodiversity. Five climate zones and 14 climatic regions, eight plant geographic regions, three massifs and major geologic series, horizontal and vertical topographic conditions, 16 ecoregions, major ecosystems including forest, river and streams, wetlands, coast and marine, agriculture, and urban esosystems, and land use types were discussed as the element of the ecodiversity. In terms of biodiversity conservation, the actual conditions of each ecological unit were reviewed and measures were proposed to reduce biodiversity loss. Destruction and fragmentation of habitat, poor ecosystem management due to socioeconomic changes, the effects of exotic species and chemicals, and climate change were discussed as the major factors causing biodiversity loss. Systematic monitoring based on scientific principles and ecological restoration based on those monitoring results were recommended as measures for biodiversity conservation.

This study was carried out to evaluate the restoration effect in the restored Yangjae stream and to draw up an adaptive management plan based on the results. As the result of evaluation on the restoration effect, the restored Yangjae stream was evaluated with low naturalness in both terms of the morphology of the stream and the composition and spatial distribution of vegetation. The diverse functional groups were introduced in the vegetation restoration, but the flooding regime, which is significant in the spatial distribution of riparian vegetation, were not correctly reflected. Exotic species or species that were not ecologically suitable for the location were introduced on the embankment and thus a measure to improve those problems is required. As the ecological principle was not reflected in the restoration plan, the stream was constructed as the double terrace structure. Therefore, the width of the waterway was narrowed further, and the waterfront was not designed to accommodate changes from flooding disturbance, making the micro-topography of the stream simpler and the naturalness lower. The adaptive management plan was prepared to improve those problems, and a plan for creating an ecological network was recommended to enhance the restoration effect.