Development of Multi-Operation Robot for Productivity Enhancement of Intelligent Greenhouses: For Construction of Integrated Pest Management Technology for Intelligent Greenhouses

Yuko UEKA, Seiichi ARIMA
2015 Environment Control in Biology  
INTRODUCTION Japanese agriculture is beginning to decline, and it is not easy to reverse this trend. If our agricultural sector was a growing industry, we would not have the problem of land use changing from agriculture to other purposes. The main problem is that landowners get much more profit by using farmland for other purposes rather than for agriculture. We believe that several operation styles of "profitable agriculture" are needed to resolve this situation. One of the most effective
more » ... ns that can be taken is to establish plant factories, which will provide efficiency through automation and the use of robots for each and every operation. In an intelligent greenhouse, manure and pesticides are managed effectively and zero emission is possible. This can triple the profit of the previous horticultural facilities, and it is estimated that the introduction of robot technology will yield further improvement. To quickly enhance the productivity of intelligent greenhouses, quality control (QC) is needed at agricultural production sites, along with the speaking plant approach (SPA) to monitor the growth conditions of plants and avoid diseased and underdeveloped plants. We are developing a multi-operation robot to eliminate the instability in environmental factors and the subsequent crop yield. This robot consists of the following units: growth information, pest detection, pest control, har-vesting, and running units. The robot gathers and effectively links together information on the cultivation environment, growth diagnosis, cultivation management, fruit quality, and harvesting. There are two types of intelligent greenhouses: an artificial light one and solar light one. The artificial light type does not need pesticides because as it is able to control the light, humidity, and gas, which makes stable crop production possible in an enclosed and sterilized space. However, the initial setup cost and the running costs for this type of facility are high. The solar light type is less expensive because it uses natural light and a larger variety of crops can be cultivated. However, because it is not enclosed (the air temperature is controlled by ventilation), it is not possible to prevent pests from entering. The establishment of the positive list system has allowed the reduction of excess chemical pesticides in a solar-powered intelligent greenhouse, and the technology for pest control is being changed to integrated pest management (IPM), which makes it possible to steadily supply safe and reliable food. Therefore, the goal of this study was the construction of IMP technology for a solar-powered intelligent greenhouse. This paper discusses the early detection of pests and the growth condition of plants; early pest control based on this information; the development of a growth diagnosis method for pest control; the development of running, pest detection, and pest control units; and the results of the basic To quickly enhance the productivity of intelligent greenhouses, quality control is needed at agricultural production sites, along with a speaking plant approach to monitor the growth conditions of plants and avoid diseased and underdeveloped plants. We are developing a multi-operation robot equipped with units that contain functions to solve the problem of the instability of environmental factors and subsequent crop yield. Growth-information, pest-detection, and pest-control units were developed for the multi-operation robot and effectively linked to report their actions in order to construct a suitable integrated pest management technology for intelligent greenhouses. The information gathering and various operations were automated by designing each unit to operate autonomously. The system was designed to detect abnormalities by mapping the information provided by the growth-information and pest-detection units. It can then determine the invasion diffusion course of the pest, which makes it easy to take appropriate prophylaxes. Furthermore, the system makes safer working conditions possible because it enables the natural dispersal of ozonated water as a preventive measure. We can expect a further reduction in pesticide consumption by adding a function to disperse a pesticide locally when pests are detected.
doi:10.2525/ecb.53.63 fatcat:xsmbh55wazaylfkrtizalp6rxi