The purpose of this study is to develop application software for various hyperspectral imaging analyses in agricultural sensing and ecosystem observation. As previously reported, we constructed a software framework for hyperspectral imaging. A number of common hyperspectral image processing algorithms are available in this framework. Custom analytical software for specialized sensing tasks can be efficiently developed using the framework. Spectral processing algorithms can be switched through polymorphism, a standard object-oriented programming mechanism. Analytical software developers need only write the specialized portion of the program code that implements their spectral processing algorithm; the framework handles the common tasks. In this study, six spectral processors (for waveband extraction, false color generation, data normalization, segmentation between plant and soil, SPAD estimation, and for plant classification) were experimentally developed as examples of spectral processor development. In addition, data sampling software that can be used to obtain waveband images and pixel spectral data was developed.

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This research proposes an XML-based standard, BIX-image, for agricultural product images and image meta data exchanged through the BIX Image Broker System.
In addition, we developed a peer to peer (P2P) message handler, BIX-P2PHandler, to exchange BIX-image data as P2P messages. The BIX Image Broker System is an information sharing system developed for efficient exchange of a variety of agriculture product digital image data using P2P technology. Images and their meta data are built into P2P message and exchanged between nodes. In the work reported in this paper, we identified key attributes of agricultural product images, and defined a mapping of those attributes to XML as BIX-image. Moreover, we developed BIX-P2PHandler to transfer BIX-image data as a message between peer systems. In addition, we confirmed that we could exchange agricultural product image information between P2P nodes by developing a trial model of BIX-IBS.

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In order to improve the sugarcane yield and encourage stable management, agricultural production corporations are required to manage their work systematically and efficiently. Therefore, it is necessary to accurately comprehend the work that goes on in the agricultural production corporations for the rational planning of farming operations. This study is aimed at developing a system for recording farming data with a cellular phone equipped with a GPS (Global Positioning System) function and an Internet connection. The built-in GPS function is used to produce a field map of the measured position to indicate the location of the operator. The data entered from the cellular phone are transferred to and stored on the server of the system via the Internet. The results of experiments conducted by the sugarcane-producing agricultural corporations revealed that the precision of the GPS function of the cellular phone was sufficient to identify the current working field. Using a cellular phone, a set of recorded farming data can be input in 1-2 minutes. The system is developed using low-cost hardware and software, and it has a low operating cost. This system can collect the necessary farming data such as the date, weather, working time, composition of work, and machines used in the field. Furthermore, by adopting database technology in this system, large quantities of data of the farmland that are scattered over a wide zone could be handled efficiently.

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A regional food security policy is intended to increase the regional rate of self-sufficiency in food supplies. This study uses choice experiments to evaluate such policies. Our main aim is to determine whether food security policies at a regional level can substitute for a national food security policy. Our analysis shows that this can occur to some extent. However, the analysis also reveals that when the national food self-sufficiency rate is beyond 70 percent, citizens accord almost no value to increasing the regional rate. Currently, Japan's national rate of self-sufficiency in food supplies is approximately 40 percent; therefore, raising the regional rate could be used to compensate for the low national rate.

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The dual-fold purpose of this study was to investigate whether there was a correlation between agricultural information and beef cattle farming and to analyze what improving information services had an effect on beef cattle farming. Evaluations of the impact mechanism between beef cattle farming and prevailing conditions were fundamentally the same for the farmers or the civil servants and staff members of PAIs (Public Agricultural Institutions). All information elements had large and minus relation index values. Both responding groups thought that the change in elements involving beef cattle farming easily improved information services, whereas it did not strongly affect beef cattle farming or prevailing conditions. The Decision-Making and Evaluation Laboratory (DEMATEL) method, which separates the interacting elements of a system into cause and effect groups as a structural modeling approach, is a good technique for analyzing the correlation between pairs of elements. Principal Component Analysis (PCA) was applied to the total relation matrix to find out the extent of the cause-effect relationship on the results. The features or correlations within all elements, based on patterns of similarity between the cause or effect groups, were confirmed. The evaluation of the information itself in the AHP (Analytic Hierarchy Process) results was not the same as the magnitude of its impacts in the DEMATEL analysis. However, a serious problem is that improving information services did not affect beef cattle farming or prevailing conditions. It was established that the correlations or potential structures between pairs of elements could be confirmed more easily, in detail, by applying PCA to the total relation matrix.

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Image data is widely used for the diagnosis of problems with cultivation management, cultivation recording, growth level recording and pest diagnoses etc. In this research, we developed a system, Gateway-P2P-Node, to link the BIX Image Broker System (BIX-IBS) with existing network services. BIX-IBS provides efficient exchange of a variety of agricultural product digital image data. In this research we targeted Data Storage, the system that manages Field Server images, and ImageServer, an image processing application.
We developed Gateway-P2P-Node to link these network applications and BIX-IBS. BIX-IBS users can access both Field Server's Data Storage and ImageServer through the Gateway-P2P-Node. In this paper, we experimented via the Internet between Kinki University and Niigata University. The experimental results confirmed that BIX-IBS and the existing network service were able to be linked by Gateway-P2P-Node.

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The purpose of the present study was to explore consumer preferences for production information disclosed beef and bovine spongiform encephalopathy (BSE) tested imported beef. Three hundred and thirty five consumers living in Sapporo city, Hokkaido, served as respondents. Four different types of beef were analyzed in choice experiments using a random parameters logit model, i.e., domestic Wagyu beef, domestic dairy beef, imported Australian beef, and imported US beef. The following results were obtained: 1) Marginal Willingness to Pay (MWTP) for disclosure of information on feeds and pharmaceuticals for domestic Wagyu beef was lower than that for domestic dairy beef. It seemed to indicate that consumers believed that domestic Wagyu cattle had been fed with greater consideration for food safety than had domestic dairy cattle. 2) Consumers were willing to pay a price premium for BSE-tested US beef in preference to BSE-tested Australian beef.

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The tangential-subloading surface model for soils assumes that the tangential strain rate only has a component tangential to the subloading surface. However, this model is incapable of predicting with high accuracy the deformation behavior in the case of nonproportional loading, in which the tangential stress rate is dominant to the normal stress rate. This study examines the ability of induced rotational hardening and the similarity center of the subloading surface to improve the prediction accuracy of the tangential strain rate. It also examines the prediction accuracy of a subloading surface model with the concept of the tangential relaxation, in which the direction has components not only tangential but also outward-normal to the subloading surface. The results verify the importance of incorporating the concept of the tangential relaxation into the subloading surface model.

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LP (linear programming) and other programming techniques can be used to make a farm crop production plan or to estimate the impact of a new agricultural technology. XLP is a computer program running on Excel in Microsoft Windows to compute the optimal solution of a LP. XLP can provide an optimal solution for a LP model. It can solve a GP (goal programming) model, which can incorporate multiple objectives such as average income and reduced working time. It can also solve IP (integer programming) models, which can incorporate productive elements counted by discrete units, such as domestic animals, green houses, or fixed costs. The interface program of XLP is coded in VBA (Visual Basic for Applications). The computational engine for LPs (LP, GP and IP) is coded in Delphi. XLP is easy to use. The LP model is entered on an Excel worksheet “tableau” in a particular format. An additional XLP menu of computational options is added to the Excel menu bar at startup. The optimal solution is shown on worksheet as a “computed result”. XLP is directly used as a tool to describe an LP model and to solve it. It is also used as a computing engine in developing an Excel workbook-based application which builds a farming model automatically from collected data on farming and helps agricultural extension advisors and farmers use LP models. We have begun to develop a program like the above-mentioned application too. XLP can be downloaded from the following URLs: http://39you.net/xlp/ or http://cse.naro.affrc.go.jp/ooisi/

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Information on rainfall variations is a matter of great importance in agricultural countries. Climate and rainfall are non-linear natural phenomena whose measurement leads to complex data, primarily due to noise patterns and distribution heterogeneity. Therefore, it is difficult to develop an appropriate model in practice by using conventional modeling techniques. This study presents the use of a neuro-fuzzy system for modeling wet season tropical rainfall. The advantage of this technique was the possibility of a modified environment of input parameters for improving the data representation. Two approaches used in the neuro-fuzzy models were classification and prediction. The neuro-fuzzy classification model firstly produced a simple rule base that enables improved interpretability of variation in rainfall rate. The given fuzzy classification rules were then utilized to generate a neuro-fuzzy inference system in order to predict rainfall variation. This approach measured the accuracy of the prediction model according to the root mean square error (RMSE) estimation. The models resulted low values of the RMSE indicated that the prediction models are reliable in representing the recent inter-annual variation of the wet season tropical rainfall.

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