This paper proposes the use of a long-span ultrasonic thermometer. Conventional thermometers measure temperature at one spatial point, which is sometimes disturbed by a local turbulence. Since this can cause errors, it is inappropriate for such application as environmental management. The ultrasonic thermometer, which consists of a loud speaker and a microphone, derives the temperature from the time of flight (TOF) of sound along the propagation path as the mean-value of one-dimensional temperature distribution, using cross correlation between transmitted and received signals. In the field experiment performed in a glasshouse, the length of the propagation path is 16.0 m. The temperature (T_s) measured by the ultrasonic thermometer is compared with the mean temperature (T_tc) of five airflow-type thermocouples in the measurement area. Temperature differences (T_tc-T_s) are 0.3 degrees Celsius during daytime and 0.1 degrees Celsius during nighttime, which confirm the accuracy of the proposed method.

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Water and salinity stresses have been applied to improve the tomato fruit quality. To produce high-quality tomato fruit, the effect of stresses on chemical contents and physiological response must be known. We examined the chemical contents (sugar, organic acid, amino acid and inorganic ions) and osmotic potentials of tomato fruit (Lycopersicon esculentum Mill.) grown under water stress and salinity stress. For the two water stress treatments, the irrigation water amounts were fixed at 50% of the control (13% of soil water content), and 25% of the control. For salinity stress, the concentration of irrigation water was adjusted by mixing additional fertilizer, until it had the 2.5-fold electric conductivity of control (1.6 dSmu^-1). Comparing both stresses, which had similar levels of leaf water potential, sugar and organic acid contents on a fresh weight basis were enhanced by the salinity stress, but not by the water stress. Amino acid contents on a fresh weight basis, except for proline and γ-aminobutylic acid, were not affected for water stress, while most of the amino acid contents for the salinity stress were higher than those for the control. The high contents of amino acids could not be caused by the concentration effects such as sugar and organic acid. Furthermore, the mechanisms of osmotic adjustment were different between both stresses. We conclude that the changes in chemical contents and the physiological responses were different between both stresses, and that the use of the salinity stress was more efficient rather than the use of the water stress to produce a high quality tomato fruit.

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An artificial neural network (ANN) model that can be used to predict the shoot-tip temperature of Vinca (Catharanthus roseus) is presented. The ANN architecture consists of a threelayer network, input data (four environmental conditions of drybulb, wetbulb, glazing temperatures and shortwave radiation) and output data (shoot-tip temperature). Data for training and validation were collected every 10 seconds and 10-minute averages for at least 41 days were stored in a computer, and subsets of these data were used for training. Validation studies indicated excellent generalization over the range of obtained data. Simulation studies with the developed model were performed to evaluate the effect of environmental factors on plant shoo -tip temperature, and it became clear that drybulb had the highest contribution ratio (88%) and shortwave radiation had the lowest under our environmental conditions. The proposed model can be applicable because its inputs consist of four environmental factors that are easily and/ or commonly measured in commercial greenhouses, and may thus be a useful tool for evaluating the environmental factors that affect plant shoot-tip temperature under greenhouse conditions.

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‘Shiitake’ mushrooms have a considerable moisture content at harvest time and thus their drying is usually accompanied by rapid shrinkage of the surface area. Precise estimation of the surface area, which changes with the drying progressing, can facilitate the determination of the most suitable drying model for ‘Shiitake’ mushrooms.
In this study, two experiments for developing new relationship formula between the surface area and the moisture contents were conducted first. One is for the relationships between the surface area and the volume of drying ‘Shiitake’ mushrooms, which used an image processing technique as a measuring method. The other is for the relationships between their densities and moisture contents which used the liquid substituting method in measuring the densities. Combining these two relationships created a new relationship formula between the surface area and the volume of drying ‘Shiitake’ mushrooms.
Secondly, natural convective drying experiments for ‘Shiitake’ mushrooms were conducted at drying air temperatures of 40, 50 and 60°C. Then, the two drying models obtained from different views of the drying mechanisms were constructed. Comparison of their accuracies in estimating moisture content changes during drying showed that the drying formula based on an apparent constant rate drying model prevailed at all drying temperatures tested.
The newly constructed drying formulae induced in this study would be available not only for developing ‘Shiitake’mushrooms driers but also for application to the drying of other agricultural products with high moisture contents similar to ‘Shiitake’ mushrooms.

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As an informational infrastructure for various utilizations of records on plant production and accomplishments of advanced plant production systems, BIX-pp (Bio-Information Exchange for Plant Production) which is an integrated information record format in a setting of plant production, has been proposed. The features of the format were evaluated using three application computer programs for BIX-pp. BixComposite is a computer program to compound and display plant production information and was able to vividly re-experience the past plant production by simple input of a BIX-pp file. A BIX-pp version SearchTool analyzes the causes of fluctuation and constructs a model for predicting daily plant production volumes, the labor involved in the conventional pretreatment to associate and unify various kinds of input data was mitigated using BIX-pp. Since informational structure and its definition can also be input to application programs using the BIX-pp, the programs were able to discriminate the input information and automatic execution was enabled. Records previously compiled the Comma Separated Value (CSV) format file can easily be converted using RecordConverter, which is a data conversion program that translates between the CSV and BIX-pp formats. Thus, records can be easily shifted to BIX-pp. Using the BIX-pp, use of plant production records for advanced plant production is expected to be enhanced.

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