Optimal Design for Agricultural Mchinery
Shaking Selection of Grains for Combine Harvester   
In this study, grains with straws dusts were put into the shaking selection part of a combine harvester,and the cumulative flowing down rates were obtained by examination. The influence of changing controlfactors on the shaking selection performance was investigated. The 3D-discrete element method (DEM)simulations were performed in relative examination conditions, and they were then compared. The resultsof examinations show that the cumulative flowing down rates were higher in front of the chaff sieves, and the sieve opening and revolution of the shaking motion were more highly influenced. In the 3D-DEM simulations, similar results were obtained quantitatively and qualitatively. It was shown that the states of shaking selection were understood by using the 3D-DEM simulations with the non-spherical model.

Improvement of Safety and Comfort during Agricultural Machine Operations
Analysis and improvement of tractor stability against rollover   
Tractor rollover accidents are responsible for the largest amount of fatalities amongst all agricultural machinery-related accidents. In Japan, approximately 60 % of all fatal tractor accidents in are caused by the tractor rollover . Therefore, it is very important to improve tractor safety for avoiding casualties caused by tractor rollover.The objective of this study was to investigate the tractor’s rolling behavior both on simulation and driving experiment using an actual tractor and a scaled model.

Prediction of Tractor Behavior based on Reconstructed Terrain profiles by Stereo-vision Camera   
Because most hazardous accidents involve lateral rollover, it is important to investigate tractor roll motion to predict lateral tractor rollover and improve tractor safety. This study reconstructed the ground in front of a tractor using a stereo-vision camera installed on top of the tractor weight. Then, the obtained road surface height was input into a tractor behavior simulation to compare the actual tractor movement with the simulated movement.

 コンバインは,水田を走りながら,作物を切断し,稲穂から籾を分離し,わら屑を風で飛ばし,籾をタンクに運びます。1960年代には1000 m2を収穫するのに人力で140時間かかっていましたが,コンバインの登場により30分で収穫することが可能になりました.


Study on Plant Phenotyping
Study on Measurement, Extraction, and Visualization of Plant Phenotype Using Computer Vision   
Growth evaluation of plants, which is important to improve cultivation management technique, has been established by observation of plan behavior and trial-and-error methods based on experience. Moreover, the plant growth is strongly influenced by environmental factors such as temperature, solar radiation, and soil moisture, and it has been almost impossible to capture these changes with high accuracy and detail using only conventional methods.
Recently, with the development of ICT, it has become possible to capture not only visible images but also spectral and depth images relatively easily.
In our laboratory, we are trying to develop a quantitative measurement system of plant growth and its environmental response based on techniques mentioned above.In addition, we also aim to define the plant growth indices and develop nondestructive evaluation methods for plant growth features using the information obtained.

Development of High-throughput Plant Phenotyping System   
In order to advance plant breeding and management technologies, the development of quantitative, high-speed, continuous measurement and evaluation technologies for plant growth and there environmental response have to be developed. In addition, with the remarkable ICT (Information and Communication Technology) development in recent years, researches on high-throughput plant phenotyping system for faster and more accurate measurement of plant behavior information have been actively studied and developed both in Japan and abroad. However, many of the measurement devices are very expensive in general, and these technologies have not been widely and easily available yet.
In our laboratory, we are developing an affordable phenotyping platform that can measure plant trait and behavior information with high accuracy and continuity by combining inexpensive IoT devices and open source.

Study on Smart Agriculture
Development of Environmental Monitoring and Control System Using ICT   
Agricultural production strongly depends on climate, weather, soil properties, plant type, and so on. Thus, farmers have tried to continuously modified cultivation strategy and techniques for a long time so as to fit the ambient environmental and plant conditions. Additionally, consumers’ demands have also shifted to fresh, high-quality, and high-security fruits and vegetables. In response to these issues, various researches and developments have been investigated to establish next generation of agriculture up to now. The core technology will be Information and Communication Technologies (ICT). Currently, there are a lot of ICT applications in agriculture (smart farming) including a spatio temporal data collection and a facility automation including environmental monitoring and control in a greenhouse. Various affordable devices such as low-price microcomputers and sensors and open source software are developed year by year, and then these advents have completely changed the environment and views for the utilization of ICT in agriculture. We are also developing several technologies to improve agricultural production using affordable devices and open source software for small and medium-scale farms.

Development of Low Cost Farming Support Robot and Verification of Its Validity   
 Due to the aging of the farmers and the shortage of workers, it is becoming more and more difficult to secure workers at real situation in Japanese agriculture. For this reason, the development and introduction of agricultural support robots that can be used in agricultural production is being promoted rapidly. In this laboratory, we focus on small and low-cost robots that are able to support agricultural works such as filed monitoring, plant growth and behavior sensing, transportation of agricultural materials and harvested crops, and pesticide applications. Furthermore, the developed robot is being tested in our horticultural facilities and actual fields to evaluate its performance, expand their functions, and develop new technologies with robots.