Evaporative cooling through the use of a fogging system has recently become more common in commercial greenhouses. Since evaporative cooling is a well-understood physical phenomenon, air temperature and relative humidity inside the greenhouse under evaporative cooling can be estimated if conditions such as the outside dry and wet bulb air temperatures, ventilation rate, absorbed solar radiation and evapotranspiration rate inside the greenhouse are available. However, the calculation process is complicated and so is generally not used.
The Ventilation-Evaporation-Temperature-Humidity (VETH) chart, which shows the relationship between the ventilation rate of the greenhouse, the evapotranspiration rate inside the greenhouse, the dry bulb temperature inside the greenhouse and the relative humidity, was devised by Mihara (1980). The VETH chart is useful in the design of evaporative cooling operations, because the relationship between the four factors (ventilation, evaporation, temperature, and humidity) can be easily determined from the chart. However, when the conditions, such as outside dry or wet bulb air temperatures, or absorbed solar radiation change, it is necessary to redraw the VETH chart, and drawing the chart by hand is quite difficult. Therefore, a suite of three personal computer software applications were developed. One application can draw a VETH chart, the second can calculate the necessary water spraying rate and the third calculates the ventilation rate of the greenhouse via the heat balance method. Such software packages are useful as tools in the design and operation of evaporative cooling systems.

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It is important to eliminate the delay of the computerization in the agricultural field.
In this research, the agricultural information support by the group "Gaccomi" was proposed paying attention to human ware. "Gaccomi" is a group which works for two purposes; 1.information support in the agricultural field, 2.information education and personnel training for university students. It is run by university students and staff. This name is the coined word which combined the student (school: Gakkou) and the community (communication).
In "Gaccomi", university students study the information technology (how to operate a personal computer (PC), how to dispatch on the internet, etc.) by construction of a student portal site. This is useful website for university students, and it is mainly targeted at the students and the community around a university. After training the students, The "Gaccomi" group supports farmers and agricultural corporations that wish to construct their website, or to study the use of a PC, etc. In this paper, establishment and the activities of this group were performed. The following were evaluated: 1.the activity situation of group, 2. the result of a student portal site construction, 3.the support result for farmers and agricultural corporations, 4.award and mass media coverage achievements. The information support technique of the agricultural field used by this group is proven to be effective and serves also as information education and personnel training.

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The peat areas have a lot of patterned indented surface because of the varied forms caused by the fluvial trace and so on. Occasionally, an agricultural vehicle can not enter the farm field after the rain, because the soil of peat areas is soft ground and water table levels gain altitude. To discuss the countermeasure work about the patterned indented surface and the bearing capacity of the land, the precise geographical information of the whole farm field is required. But, the new effective investigation method is required, because the peat areas are extensive fields. In this study, the monitoring system of peat areas using the agricultural robot was developed to obtain precise field information effectively and accurately. As farm field information, the digital elevation model (DEM) is obtained by a GPS and one axis laser range finder. And the roll, pitch angle, slip ratio and subsidence of the vehicle were measured as vehicle information. The field test by an agricultural robot was conducted. Navigation sensors of the robot were an RTK-GPS and an IMU which is composed of fiber optical gyroscope. In addition, the test farm field was evaluated by generating the GIS map using the measured field and vehicle information.

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A case database system (DB System) was developed to inform the participants of a Kleingarten (similar to an English allotment garden) of appropriate crop cultivation methods based on participants' knowledge and experiences. The DB system consisted of a general database, case database, logbook database, search engine, and a management system.
The general knowledge database was constructed using information on the basic cultivation method for 11 varieties of crops that had predominantly been grown in the past four years in the Kleingarten of Utsunomiya University, and the case database was constructed from 211 cases extracted from logbooks recorded by the participants. The DB system was constructed on a Web server to accumulate the knowledge and experiences of skillful participants, and to make that information available to beginners.

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It is important that combine harvesters can operate efficiently under various crop and weather conditions. The Taguchi Method has been recognized as a leading tool to improve the robustness of control systems for many kind of machinery. The Taguchi Method utilizes Signal to Noise ratio to represent the factorial effects of control variables against outputs and also takes noise factors into consideration. A key tenet of the Taguchi Method is that control variables with strong cross interactions should not be included in design parameters. In implementing the Taguchi Method it is necessary to select control variables without strong cross interactions. Experimentally identifying unwanted variables is impractical due to the enormous number of control variables combination that must be examined. For this reason the Taguchi Method is not used in combine harvesters. Recently, Artificial Neural Networks (ANN) have been utilized to describe various non-linear systems. The performance of combine harvesters can be considered as a typical non-linear agricultural machinery system. In this paper, ANN were used to model non-linear combine harvester system in order to reveal hidden cross-interactions between control variables. After revealing hidden cross-interactions between control variables, the factorial effects were obtained based on an L18 matrix. A confirmation run proved the reliability of the factorial effects obtained. Combining the Taguchi Method and ANN was proved to be effective.

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