In 2002, Kobe City enacted an ordinance banning the feeding of wild boars to stop the increasing damage caused by them, including economic harm, personal injury, motor vehicle accident, residential environment or other human structures.The purpose of this study was to identify the different types of interactions between humans and wild boars in urban watershed where wild boars came and settle and mountainous areas, and to explore the relationship between human and wild boar behaviors in Higashinada Ward, Kobe City.We conducted aｎ observational study and a behavioral survey between 2010 and 2011 to document human behaviors toward wild boars and assess the reaction of wild boars toward humans in the watershed areas of the Tenjo River and in mountainous areas of Mt. Hokura. We rated human behaviors into five categories: unconcerned, active, proactive, adversarial, and escape behaviors. For the boars, four categories: active, material, and aggressive behaviors. Chi-square tests and logistic regression analysis were conducted to examine the interactions between the behavior of humans and wild boars using the variables of gender and age of the humans and the two locations.The results showed more unconcerned behavior in the watershed areas by young middle-aged adults and older adults, and more active and proactive behavior in the mountainous areas among minors. We also found that minors were more likely to feed the boars. Furthermore, wild boars reacted to the human active and proactive behaviors, which led to further proactive behavior from humans.

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In rice production, the measurement and estimation of growth indicators are indispensable for making decisions on topdressing, estimating protein content in grain for classification collection, determinant analysis of yield and quality, etc. We proposed an estimation method for dry matter weight of rice plants per unit field area (PDW), tiller number per hill (NT), nitrogen content in leaf blade per dry matter weight (N_dw), nitrogen content in leaf blade per unit leaf area (N_a), and nitrogen uptake of rice plants per unit field area (NU), based on plant area index (PAI) and chlorophyll meter readings (SPAD readings). We evaluated predictive accuracy of an estimation equation for each growth indicator and clarified the factors affecting its accuracy. Mean relative error of cross validation (MRECV) for the estimation equation of PDW was 23.3 % for overall growth period by heading. For the predictive accuracy of each growth period, MRECV in the maximum tiller number period was 48.3 %, whereas it decreased for the late growth periods. MRECV in the middle ripening period was 5.7 %. The MRECV for the estimation equation of NT was 9.5 % for the overall growth period by heading, whereas it was 16.2 % in the maximum tiller number period, which was larger than that of the other growth periods. Variations in explanatory variables in the estimation equations of PDW and NT were large in the late growth periods. Thus, the contribution of data observed during these periods to the estimation equations was large, resulting in low predictive accuracy in the maximum tiller number period. The MRECVs for the estimation equations of N_dw and N_a were 15.3 % and 13.4 %, respectively. The predictive accuracy was high for the equation of N_a because differences in a linear relationship between N_a and SPAD readings were small among the growth periods. The small differences were attributable to the fact that the N_a indicator changed with leaf thickness, similar to that observed for SPAD readings. The MRECVs for the estimation equation of NU were 9.8 % for overall growth period by heading and 4.0 % for the middle ripening period. The predictive accuracy of NU mainly depended on the predictive accuracy of nitrogen content in rice plant per unit plant area based on SPAD readings.

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