Agricultural Information Research
Online ISSN : 1881-5219
Print ISSN : 0916-9482
ISSN-L : 0916-9482
Volume 14, Issue 4
Displaying 1-4 of 4 articles from this issue
Original Paper
  • Daisuke Horyu, Teruaki Nanseki, Seishi Ninomiya
    2005 Volume 14 Issue 4 Pages 247-259
    Published: 2005
    Released on J-STAGE: March 31, 2013
    JOURNAL FREE ACCESS
    Each local government in Japan individually publishes farming-systems data, which describe when to plant particular crops and what cultivation and protective measures should be used. Forms of these data differ between local governments. Moreover, each entry in the form of farming-systems data has varying styles of descriptions and varying notations depending on the person who generated the data. This kind of heterogeneity prevents farm planning systems from importing farming-systems data. To deal with this heterogeneity, we have tried to use XML as a format of farming-systems data. XML is a promising tool for sharing distributed and heterogeneous data.
    We have transformed a booklet of farming-systems into XML-formatted electronic data. The booklet is issued by Iwate prefecture, and consists of 149 tables. Each table in the booklet that corresponds to a crop or its cropping type has been converted to one or more XML-formatted text files.
    We have also developed prototype applications that are able to interpret XML formatted files of farming-systems data. The process for comparing these applications with an existing relational database based “Farming-systems Analysis and Planning Support Database” revealed that we could retrieve data one needs from XML-formatted files as easily as we could retrieve the data from the relational database based system. We tested whether XML-formatted files of farming-systems data could be stored in a native XML database. There was no trouble in storing XML-formatted files of farming-systems data in the native XML database.
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  • Xujun Ye, Kenshi Sakai, Shin-Ichi Asada, Tetsuya Akita, Akira Sasao
    2005 Volume 14 Issue 4 Pages 261-272
    Published: 2005
    Released on J-STAGE: March 31, 2013
    JOURNAL FREE ACCESS
    An Airborne Imaging Spectrometer for Applications (AISA) system was used to obtain hyperspectral images over an experimental citrus orchard located at Nebukawa Agricultural Research Station, Japan during the months of April, May and June in 2003. The objective was to determine to what extent the reflectances in the 72 visible and near-infrared (NIR) wavelengths (from 407 to 898 nm) obtained in different months might be related to differences in fruit yield of citrus trees. Multiple linear regression and neural network algorithms were employed to develop yield prediction models. Correlation Coefficient Analysis (CCA), Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were used to reduce the number of input variables. Results indicated that the PLS method performed the best in extracting predictor factors that have a high correlation with citrus yield, followed by the CCA method. However, the PCA method did not yield a satisfactory result. The performance of neural network models was further verified by statistical analysis of the ensemble ten thousand models developed with random initialization of training parameters. It is demonstrated that there is a more evident correlation between the spectral characteristics in May and the citrus yield, compared to those in April and June.
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  • Naomi Sakuramoto
    2005 Volume 14 Issue 4 Pages 273-286
    Published: 2005
    Released on J-STAGE: March 31, 2013
    JOURNAL FREE ACCESS
    This Pocket Bookkeeping system is an accounting system that is made specifically for small-scale farmers, and it is designed to maximize management tasks and double entry bookkeeping. This system runs on Windows, MacOS and Linux and has the following features.
    First, it has an interface with functions that take into account farmers' characteristics so it is especially easy to use for farmers. Second, the user can carry the system and data simply, so it is convenient to receive management guidance from the appropriate institutions. As well, the system has business analysis capabilities and function which means that the interchangeability of data can be higher, recycling can be easier, and the mitigation of time management and management analysis. Thirdly, an individual user's requirements definitions can be loaded into the system because it is suitable for spreadsheets and management maintenance, and using the Internet, improvements can be added as feedback into the original system. In addition, this system is designed to cooperate with the Farming-system Database and other managerial support systems which are in development, and can be used to create detailed analyses of production and management plan systems.
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