Analysis of Working Efficiency of Sugarcane Harvesters in Combination with Transporters on Kita Daito Island, Okinawa
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- Shikanai Takeshi
- Faculty of Agriculture, University of the Ryukyus
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- Ohshiro Rimi
- Faculty of Agriculture, University of the Ryukyus
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- Guan Senlin
- Kyushu Okinawa Agricultural Research Center, National Agriculture and Food Research Organization
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- Akachi Tohru
- Okinawa Prefectural Agricultural Research Center
Bibliographic Information
- Other Title
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- 沖縄県北大東島のサトウキビの中・小型収穫機と搬出機の連携作業に着目した作業能率分析
Abstract
<p>To use farm machinery efficiently, it is necessary to optimize methods to the conditions on each farm. To plan optimal machinery use, it is necessary to record machine operating data in the field and analyze the working area, work content, and working hours. These results can then be used to devise the optimal working method. We used an inexpensive machine-mounted commercial GPS receiver to analyze the trajectories of the harvester and the transporter in order to calculate the actual working hours with a low margin of error. The results showed effective working efficiencies of 0.29 for unidirectional harvesting and 0.37 for bidirectional harvesting by a small harvester, and 0.27 and 0.38, respectively, by a medium-sized harvester. The effective and calculated field capacities of the medium-sized harvester were nearly twice those of the small harvester. Analysis of the simultaneous movement of the harvester and transporter can identify inefficient work areas and possibly improve the working efficiency. The small harvester has the potential to raise the working efficiency by optimizing cooperation with the transporter. Considering the influence of precipitation on machine travel, we found that the operational rate of the small harvesters was 6% higher than that of the medium-sized harvester.</p>
Journal
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- Agricultural Information Research
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Agricultural Information Research 26 (4), 142-154, 2017
Japanese Society of Agricultural Informatics
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Details 詳細情報について
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- CRID
- 1390282679438640128
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- NII Article ID
- 130006287996
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- ISSN
- 18815219
- 09169482
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed