The object of this study is to investigate the fundamental characteristics of the rhisosphere environment control by means of the digital computer.
In this paper, as the first report, the fundamental characteristics of the soil temperature control system by means of the digital computer are being discussed.
A mathematical model of the controlled system was derived on the basis of the indicial response experiment. Then, solutions of the mathematical model were obtained by means of the digital computer. The simulated indicial response well fitted to the experimental data.
As a result, the state equations, represented by simultaneous first order linear ordinary differential equations with respect to time on the basis of the heat conduction partial differential equation and its matrix exponential type state transition solutions, were found suitable as a mathematical model of the controlled system.
Thus, a mathematical model to be used for the soil temperature control by means of the digital computer was obtained and it was confirmed that the indicial respose method is appropriate for identifying the parameters in the model.

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Tomato cultivars Zuiko (ZK), resistant to TMV causing top-necrosis by infection with TMV, Fukuju No. 2 (F2), susceptible to TMV causing mosaic, strains GCR 236, GCR 237, GCR 254, and GCR 267, resistant to TMV causing no symptoms, were used. They were tested whether or not the induced resistance does occur by changing temperatures during incubation following inoculation, by heating tomato seedlings as a shock at 45°C for 10 min immediately after inoculation, by introducing dyes, acridine orange (AO), azure B (AB), and pyronine B (PB), into tomato seedlings, and by introducing the infected tomato extract.
At 25°C, TMV concentration in ZK was 2% of that in F2, whereas it reached almost 60% at 20°C, showing that ZK was not resistant at a low temperature below the optimum for tomato growth. Heat shock induced the reduced amount of TMV in ZK as compared with non-treatment, but did not in GCR 236, GCR 237, and GCR 267. Thus, ZK alone showed an induced resistance by this treatment. ZK, GCR 236, GCR 237, and GCR 254, all showed a decrease in TMV concentration by introducing dyes through root, especially by 10 ppm AO. However, F2 cultured in 10 ppm AO showed no alteration in TMV concentration comparing with that cultured in water. When the extract obtained from non-infected ZK which was cultured in 10 ppm AO, was mixed with TMV and the mixture was inoculated on the leaves of bean (Phaseolus vulgaris), AO absorbed-ZK extract showed no inhibitory activity to TMV infection. These facts indicate that AO did not directly inactivate TMV, but induced a highly resistance in ZK except F2. F2 which had absorbed the infected F2 extract, reduced TMV concentration, but that absorbed non-infected F2 extract or infected ZK extract did not so much. ZK did not reduce TMV concentration by absorbing F2 extract or non-infected ZK extract, but did a little by absorbing infected ZK extract.
From these results, induction of resistance in tomato cultivars caused by the environmental factors is discussed.

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A device of simulation and display was developed for monitoring the controlled spectral composition of artificial light for plants. The simulation was performed in the following manner:
The spectral intensity at rated capacity is denoted by the function of wavelength, λ. Individual function, f_i (λ), i=1, 2, …6, of six kinds of the lamps is coded in digital form on ROM in the function generator and is used to generate voltage value, V_{fi (λ)} . A dimming parameter k_i is converted into voltage value, V_ki in the potentiometer. The V_{fi (λ)} is multiplied by the V_ki to produce voltage value corresponding to an optional spectral intensity of each kind of the lamps. These multiplied values of V_k1V_{f1 (λ)} , V_k2V_{f2 (λ)} , … and V_k6V_{f6 (λ)} are summed up in the summing amplifier to manipulate F (λ) which is displayed on the CRT as the spectral composition of combined light. The signals from potentiometers are also used as actuating signals in light control system.
Thus, the change of spectral composition with the variation of each parameter was examined immediately on the CRT, and at the same time, the spectral composition was controlled. Experimental results demonstrate that the simulation method employed is satisfactory for the evaluation of the spectral composition, and the developed system makes it possible to monitor the spectral composition in artificial light control.

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