The first plant factory in Japan was built more than 20 years ago, and industrial stage of plant factory moves to the development stage from the earlier stage. In the meantime, various automation systems have been developed for the purpose of increasing harvests, saving labor, or decreasing the workload. In this review, we examine these subjects and the range of automation devices, and look at examples of some of the related problems that companies have faced to date. Currently, the amount of time required to produce one leafy lettuce in an artificial plant factory is estimated to be 2.2 minutes. With full mechanization, this time will be reduced to 0.3 minutes. However, the investment in equipment is limited when economic efficiency is taken into consideration. The candidates for mechanization should be carefully selected so as to be compatible with shipping operations; for example, systems that involve less leaf picking and packaging, and fewer cleaning and sterilization operations for cultivation instruments and tools used in the production of 10,000 or fewer lettuces per day.

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Recently, large-scale greenhouses and plant factories have attracted attention as new forms of agriculture. The automation of the greenhouse is examined because at present there is generally little automation in greenhouses. In this review, we consider the necessity and effects of greenhouse automation. One of the effects of automation is the saving of labor. The operational times of large-scale greenhouses tend to be greater than those associated with protected horticulture. Cultivation management, harvesting, and shipment all entail long operational times. We examine the use of harvestings robots in agriculture. At present, such robots are rarely employed due to low working efficiency and high costs. However, harvesting robots would be suitable for large-scale greenhouse cultivation systems, which have long operation times. Accordingly, in large-scale greenhouses, harvesting robots will be effective in saving labor and reducing costs. Another effect of automation is informatization. Automated devices can process larger amounts of data on plants and the environment in large-scale greenhouses than can humans. Consequently, we can monitor planar distribution of the growth environment and plant growth in greenhouses. These data can provide indices for cultivation management. Cultivation management based on such data can enable more accurate control of the greenhouse environment. Automated devices can stabilize cultivation and increase the productivity of greenhouses, thereby improving the profitability of factories, and, in turn, promoting the spread of large-scale greenhouses and plant factories.

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In order to analyze the thermoregulation system in lotus, Nelumbo nucifera, from the perspective of control engineering, temperatures of thermogenic and non-thermogenic receptacles were measured outdoors. Step response tests of lotus during the thermogenic or non-thermogenic stage, in which surrounding air temperatures were changed in a similar manner to a step function, were also carried out and receptacle temperatures were measured. The lotus thermoregulation system was subsequently investigated by analyzing the measured temperatures of lotus receptacles outdoors and of those in the thermostatic chamber. From the results, we hypothesize that lotus have a reference temperature based on a biological temperature and a thermoregulation system with a target value that is a function of air temperature. Lotus produce heat equivalent to the temperature for thermogenesis and maintain their receptacles at a higher temperature than that of the surrounding air. Thus, the lotus thermoregulation system can be expressed as a control system which inputs the deviation between the target value and the feedback value from the receptacle temperature to a controller. This controller can be expressed by integral action.

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The relationship between exposure to a daytime temperature of 30°C for various periods and the ratios of colored areas in petals of the picotee cultivar of Eustoma grandiflorum was investigated under an artificial climate. To determine the conditions under which petals with various color ratios appeared, plants were cultivated at a nighttime temperature of 15°C and for 0, 2, 4, 6 and 10 hours in the daytime at 30°C in artificial climate chambers from the stage of pistil formation of the first flower bud to harvest. Daytime exposure to 30°C for 2 hours caused 10-90% coloration of the area of each petal. The ratio of the petal length to width under this condition significantly and negatively correlated with the coloration rates of petals in the second and third florets. These findings suggested that petal coloration rates increase at low temperatures concurrently with a change in petal form. Moreover, daytime exposure to 30°C for 4 or 6 hours resulted in a maximal coloration rate of 40% of the whole petal area and almost all petals were colored at a rate between 10 and 30%. The mean petal coloration rate was about 15% when exposed for 10 hours to a daytime temperature of 30°C and ‹ 10% of the area was colored in 24% of petals. These results suggested that the coloration ratio of petals can be controlled by the duration of daytime exposure to a temperature of 30°C.

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This study aimed to establish a model to predict the effects of various storage conditions of temperature, oxygen concentration and storage period on respiration rate and quality deterioration of the common bean. Beans were stored for 72 hours in respiration and storage chambers at 10°C, 25°C and 35°C ventilated with 2%, 7% and 20% oxygen, respectively, balanced with nitrogen at a flow rate of 100 ml min^-1. Respiration rate of the stored products was measured using a flow-through method. Glucose (Glu) and L-ascorbic acid (L-AsA) contents and L*a*b* color space were used as indicators of product quality. Lower temperature, but not oxygen concentration, significantly inhibited respiration rate and change in nutrient contents. These results were used to develop a model for predicting the effects of storage period, storage temperature and oxygen concentration on respiration rate and quality deterioration. Subsequently, the model was validated at 10°C, 25°C and 35°C in 10% oxygen, and the predicted values agreed well with measured values. Thus, the proposed model can predict respiration rate and quality deterioration of the common bean stored under a temperature range of 10°C to 35°C and an oxygen concentration of 2% to 20%.

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