Linear programming is used to create farm planning or regional farming patterns or to evaluate the managerial impact of an agricultural technique. There are many commercial or free linear programming tools for use on a personal computer. An experienced user can easily utilize such programs if they are familiar with building linear programing models. But the user needs to master the translation of managerial conditions and farming techniques into a farm planning model. It would therefore encourage the spread of linear programming to provide a tool with which a user could automatically build models without in-depth experience. The program "BFM" reported in this article has been developed as such a program and its primary goal is "making farm plans quickly." BFM has the following important characteristics; firstly the number of settings related to farming conditions is restricted to the minimum necessary for model building, secondly the entering and modifying of managerial indices is simple, and thirdly various types of farm planning model in which the kind of farmland differs can be processed. The basic function of BFM is to build a farm planning model in which the relations between supplied quantity and required quantity in farmland and farm labor are described as constraint equations. In summary, BFM is a useful program which helps a user to build a farm planning model easily and rapidly. BFM can be downloaded from the following URLs: http://39you.net/xlp/bfm.html or http://cse.naro.affrc.go.jp/ooisi/bfm.html.

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This study has developed soil fertility map and determined crop suitability in the province of Bukidnon, Mindanao Philippines using GIS. It entails combining and analyzing agro-environmental, soil information and crops biological requirements for growth. Result of analyzed soil samples revealed that light clay soils dominated the province. Combining these results with the determined soil chemical properties showed that the province is of high soil fertility in 300-500 masl, medium fertility in 501-900 masl and medium to high fertility in 901-1500 masl part of the province. GIS analysis also showed that 44.87% of the total area of the province was suitable for farming purposes given their slope and geologic characteristic. Overlaying the generated agro-climatic map with land suitable for farming practice map and soil fertility map, a crop suitability map has been developed. Matching crops biological requirements for growth to the crop suitability map was able to identify the specific crops applicable in certain part of the province. Among the recommended crops are rice, sugarcane, corn, coconut and cassava which were found out to be suited in lower areas with high temperature, highly suitable for farming due to low slope condition and high soil fertility. Pineapple, mango and banana on the other hand were suited in above-said areas including those up to 900 masl due to their capability to survive in high and relatively low temperature but of medium soil fertility. Tomato and potato however were suited in higher areas where temperature is cool and medium to high soil fertility. GIS analysis showed that there were areas in the province that are still high potential and suitable for farming purposes given the parameters used.

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An increasing number of governmental organizations have introduced IT systems over recent years. This study attempted to assess governmental organizations' replies to e-mail inquiries from ordinary people, in order to explore the impact of these IT systems on public access to information. Selected ministries of the Japanese government and prefectural governments were sent e-mails in 1999, 2000, and 2005, asking simple questions including who should be contacted for some specific information. In 1999, 50 % of organizations replied by email, and 66.66% of organizations did so in 2000 and 2005. The time taken to reply to questions reduced, and there were improvements in terms of contents between 2000 and 2005. But still one third of the governmental organizations neglected to respond to those inquiries, even though the Freedom of Information Act was passed in 1999.

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Studies on estimated wildlife habitat distribution using GIS and Generalized Linear Modeling commonly use Digital Map 5000 land use data or vegetation data issued by the Geographical Survey Institute and the Ministry of the Environment, respectively. Since the suitability of these data types to such an application has not yet been tested, this study sought to determine which of the two data sets was better suited for the estimation of raccoon habitat. Digital Map 5000 land use data (Model 1) and vegetation data (Model 2) were thus analyzed using a GIS and a generalized linear model. The results were compared with that of the actual information on the presence of raccoons within Osaka Prefecture. The explaining variable of the natural environment was elucidated by a stepwise approach using both models. In addition, differences in land use categories and the accuracy of the two data sets were also found to have influenced to the results obtained. Thus, it is necessary to note the consideration of result to estimate the wildlife habitat distribution using two models.

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This paper briefly introduces choice experiments using R, which is a language and environment for statistical computing. Choice experiments belong to the family of stated preference methods and are applied to numerous issues in research fields such as marketing science, transportation economics, environmental economics, agricultural economics, or health economics. We explain the process of creating choice sets using the AlgDesign package and the process of statistically analyzing responses using the survival package. Since R is free software, readers of this document may find it easy to apply choice experiments to their research projects.

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