Simulations were carried out on the influence of the CO₂ generated from the soil on the environment in a greenhouse. If the relationship between the photosyn-thetic rate (P), which decides the CO₂ environment, and the CO₂ concentration in a greenhouse (X) can be expressed by equation (3), then the coefficients K₁ and K₂ included in the equation can be expressed as equations (4) and (5) using light intensity (I) .
Simulation of diurnal changes in the CO₂ concentration in a greenhouse were carried out using equations (3), (4), (5) and (6) with varying amounts of CO₂ generated from the soil, leaf indices and ventilation rates.
Ventilation methods in a greenhouse were clarified from the results of these simulations. When the amount of CO₂ generated from the soil increased, the starting time of ventilation was delayed, and the ventilation rate per day was consequently reduced. When the ventilation was controlled by an on-off action with a given differential gap, the ventilation rate per day, in some cases of high ventilation rates, was less than with low rates.
These conclusions should prove profitable for the reduction of energy use in a greenhouse.

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The applicability of the P.I.D. control algorithm for an identified soil temperature system¹⁾ was investigated using both experiments and computer simulations.
Results:
1) The P.I.D. soil temperature control experiments showed that although every four optimally adjusted P.I.D. parameter sets lead the controlled variable, (the soil temperature at the logarithmical middle point) to the stepwise desired value in the steady state, the transient response curves are differ greatly when four sets of optimal P.I.D. parameters from the C.H.R. method are used. The simulated P.I.D. soil temperature controls were similar to the above experiments except for slight differences in detail. This implies that investigations of P.I.D. soil temperatue control systems can be carried out using computer simulations composed of the mathematical model for a soil temperature system developed in a previous paper¹⁾ .
2) Not only was it determined that P.I.D. soil temperature control can be performed using a digital computer, but that the P.I.D. soil temperature control system, itself, and the soil temperature distributions can be investigated with computer simulations while the soil temperature is P.I.D. controlled, if the digital computer possesses the state space simulation model of the P.I.D. soil temperature control system developed in the present paper.

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The applicability of the L.Q.G. control algorithm for the identified soil temperature system was investi-gated using a previously developed digital computer control system with both experiments and computer simulations. The characteristics of the two algorithms, the P.I.D. and the L.Q.G. were determined by comparing experimental and simulation results when soil temperatures at all the grid points are selected as controlled variables of these control algorithms.
Results:
The L.Q.G. soil temperature control using the optimal feedback matrix showed that the controlled variable, the soil temperature at the logarithmical middle point, settles very smoothly and rapidly to the stepwise desired value with no overshoot. The computer simulations of this L.Q.G. soil temperature control using the mathematical model of a soil temperature system developed in an earlier paper showed remarkable agreement with experimental values. This signifies that investigations of the optimal control systems of soil temperature using the L.Q.G. algorithm can be carried out with computer simulations composed of the mathematical model of the soil temperature system developed here.
Two indices of controller usefulness, the settling times of controlled variables and the I.S.E.s (Integrated Square Error) of the temperatures at all the grid points, were obtained from computer simulations of both the P.I.D. and L.Q.G. soil temperature control by choosing soil temperatures at all the grid points as the controlled variables in order to judge the usefulness of these two control systems. The L.Q.G. was superior to the P.I.D. in both setting time and I.S.E. In the P.I.D. soil temperature control, the settling time and the I.S.E. are not simultaneously well satisfied. That is, a P.I.D. parameter set that attains minimal settling time ( [A] and [B] in the previous paper) produces a large I.S.E. than do others ( [C] and [D] ), and vice versa.

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Plants with high respiration rate like mulberry leaves and carnations are still active after harvesting. When these are afterwards packaged during transportation, a phenomenon of getting musty occurs due to the increase of the temperature and moisture at the center of package. The authors believed that this was largely due to the respiration of plants. They therefore made the following hypothesis and based from them their deductions:
1. In the part where the‘musting’ phenomenon occurs, there is no outflow or inflow air, water, and water vapor, and is under adiabatic conditions.
2. The heat generated by the plant is due to the oxidation of the saccharoids it contains.
3. The oxidation of the saccharoids is due to the 2-order reaction based on the theory of chemical reaction rate.
4. In the process of the plant temperatures increase, there is no relative time lapse between the temperatures of plant and the surrounding air.
Based on the suppositions above, an adiabatic closed container was made. The temperatures of the plant placed inside was measured and compared it with the predicted temperatures increase based on the computation using the saccharoid reaction formula. The curves in general were similar. However there is about 5-6°C in the values on the end of the curves and there is a little discrepancy in the inclination of the curves. It might be concluded that other factors for temperature increase other than the supposed saccharoids reaction should be considered.

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Under controlled temperature and humidity conditions, the leaf temperature and electric capacitance in the stem after illumination were measured continuously by means of an infrared thermometer and a capacitance meter. Response curves observed in several species were quite different in the pattern of oscillation of leaf temperature. We thought that the differences in leaf temperature might be made clear by modelling and simulation of the dynamics from water suction in roots to transpiration in leaves.
The modelling and simulation of dynamics in plant water and leaf temperature were carried out in tobacco plant, cucumber and sunflower. Differences in oscillation of leaf temperature in these plants could be explained by the relationship between stomatal transpiration and water supply in leaves.
For wider discussion, the response curves after ABA (abscisic acid) treatment and the response curves in the leaves with different age were examined by our model and the simulation.
The result indicated that our model could clearly explain the dynamics of leaf temperature in relation both to hormone and aging effects. It was concluded that such a modelling-simulation procedure as suggested in this paper is one of the most effective approaches to make clear the dynamics of leaf temperature.

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This paper mainly deals with the influence of the interaction between the thermoperiod having sinusoidal change of temperature (27±4°C) with the 24 hour period, and the photoperiod during larval stages on the body weight, the amounts of food ingested and digested in the 4th and the 5th instar larvae, and the quantitative characters of cocoon.
Larval period was divided into such three stages as the 1st to the 3rd, the 4th and the 5th instar, and also each stage was used for the experiments.
The data taken were analyzed by the statistical method as follows.
1) Effects of the rearing conditions on the growth were remarkable in the 1st to the 4th instar of larvae, but weakened in the 5th instar. And the additive effects were observed between the 1st to 3rd and the 4th stages.
2) The growth of larvae under the thermoperiod set up at 2 p.m. of acrophase (31°C) was excellent rather than at 2 a.m.
3) The effect of illumination on the larval growth and the productivity of silk substance under the thermoperiod of sinusoidal change of temperature was the most prominent in the continuous light (LL) ; next in order were dark above 27°C (LD 12: 12), continuous dark (DD), and light above 27°C (LD 12: 12) .

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