In this study, a behavior simulator of a tractor in an actual accident site was developed. The dynamic behavior of the driving tractor in slant topography was represented by movements of four degrees of freedom: vertical, pitching, rolling, and forward. Therefore, a dynamic equation of four degrees of freedom was developed. A representation method to simulate the tractor behavior was developed using the topography data obtained from the survey and hearing around the accident site. Furthermore, we identified the parameters of tractor behavior based on experiments. The behavior simulation was performed using the original code. We discussed the practicality of the dynamic equation to realize tractor behavior and also the practicality of the representation method of the topography.

Agricultural tractors with a shielded cabin were developed for decontaminating paddy fields that have been contaminated with radioactive material. The developed machines reduced the radiation dose rate of the interior of the cabin by approximately 50% or less from outside. Moreover, the dust concentration was reduced by more than 95%. The performances of the machines and the effect of the removal of surface soil were estimated via a decontamination test in Iitate, Fukushima.

Mass adjustment mechanisms perform cumbersome work that is encountered in postharvest processing of leafy vegetables such as spinach and Chinese chive to ensure that the delivery meets shipment standards.

We devised basic test equipment for the mass adjustment of the Chinese chive; the equipment combines a few small bundles to minimize such cumbersome work. The basic test equipment consists mainly of a load cell and 8 buckets, and is controlled by a programmable logic controller. Small bundles of Chinese chive are fed into buckets that are weighed and stored in order, and the minimum combinatorial bundles that weigh more than the target weight are selected. All mass adjustment tests were conducted with a target weight of 110g.

It was found that with feed bundles of 35g, 91-96% of combinatorial bundles weighed within 110-115g, whereas 83-96% of combinatorial bundles fell within same weight range with feed bundles of 55g. Further, it took about 17s and 13s for the 35g and 55g feed bundles to achieve the targeted combinatorial weights, respectively.