scholarly journals Farm work system for crop rotation on dried paddy field in snowy area. VI. On the economical aspect of the main agricultural machines and dryer on a model planning.

1990 ◽  
Vol 25 (3) ◽  
pp. 217-221
Author(s):  
Oritaro ENDO ◽  
Shizunori TAKAYAMA ◽  
Kazuhiko KURATA
1989 ◽  
Vol 24 (2) ◽  
pp. 114-125
Author(s):  
Shizunori TAKAYAMA ◽  
Oritaro ENDO ◽  
Kazuhiko KURATA ◽  
Michiaki ITO ◽  
Kazuhiro NAKANO ◽  
...  

1989 ◽  
Vol 24 (1) ◽  
pp. 10-17
Author(s):  
Kazuhiko KURATA ◽  
Oritaro ENDO ◽  
Michiaki ITO ◽  
Kazuhiro NAKANO ◽  
Takashi NAGAI ◽  
...  

1972 ◽  
Vol 1972 (15) ◽  
pp. 42-47
Author(s):  
Tosio NAITO ◽  
Michihiro NAKAJIMA
Keyword(s):  

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4082 ◽  
Author(s):  
Zhengjun Qiu ◽  
Nan Zhao ◽  
Lei Zhou ◽  
Mengcen Wang ◽  
Liangliang Yang ◽  
...  

Using intelligent agricultural machines in paddy fields has received great attention. An obstacle avoidance system is required with the development of agricultural machines. In order to make the machines more intelligent, detecting and tracking obstacles, especially the moving obstacles in paddy fields, is the basis of obstacle avoidance. To achieve this goal, a red, green and blue (RGB) camera and a computer were used to build a machine vision system, mounted on a transplanter. A method that combined the improved You Only Look Once version 3 (Yolov3) and deep Simple Online and Realtime Tracking (deep SORT) was used to detect and track typical moving obstacles, and figure out the center point positions of the obstacles in paddy fields. The improved Yolov3 has 23 residual blocks and upsamples only once, and has new loss calculation functions. Results showed that the improved Yolov3 obtained mean intersection over union (mIoU) score of 0.779 and was 27.3% faster in processing speed than standard Yolov3 on a self-created test dataset of moving obstacles (human and water buffalo) in paddy fields. An acceptable performance for detecting and tracking could be obtained in a real paddy field test with an average processing speed of 5–7 frames per second (FPS), which satisfies actual work demands. In future research, the proposed system could support the intelligent agriculture machines more flexible in autonomous navigation.


2012 ◽  
Vol 66 (5) ◽  
pp. 1074-1080 ◽  
Author(s):  
T. Hama ◽  
T. Aoki ◽  
K. Osuga ◽  
S. Sugiyama ◽  
D. Iwasaki

Japanese paddy rice systems commonly adopt the rotation of vegetables, wheat and soybeans with paddy rice. Crop rotation may, however, increase the nutrient load in effluent discharged from the district because more fertilizer is applied to the rotation crops than is applied to paddy crops. We investigated a paddy-field district subject to collective crop rotation and quantified the annual nutrient load of effluent from the district in three consecutive years. The total annual exports of nitrogen and phosphorus over the investigation period ranged from 30.3 to 40.6 kg N ha–1 and 2.62 to 3.13 kg P ha–1. The results suggest that rotation cropping increases the effluent nutrient load because applied fertilizer is converted to nitrate, and surface runoff is increased due to the absence of shuttering boards at the field outlets.


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