Author
Listed:
- Yi-Seo Min
(Department of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, Republic of Korea)
- Yeon-Soo Kim
(Department of Bio-Industrial Machinery Engineering, Pusan National University, Miryang 50463, Republic of Korea)
- Ryu-Gap Lim
(Department of Smart Agriculture, Korea Agriculture Technology Promotion Agency, Iksan 54667, Republic of Korea)
- Taek-Jin Kim
(Department of Drive System Team, TYM R&D Center, Iksan 54576, Republic of Korea)
- Yong-Joo Kim
(Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Republic of Korea
Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea)
- Wan-Soo Kim
(Department of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
Upland Field Machinery Research Center, Kyungpook National University, Daegu 41566, Republic of Korea)
Abstract
The load factor (LF) of a tractor represents the ratio of actual engine power and rated engine power, and is an important indicator directly used in calculating national air pollutant emissions. Currently, in the Republic of Korea, a fixed value of 0.48 is used for the LF regardless of the working conditions, making it difficult to establish a reliable national air pollutant inventory. Since tractors perform work under soil conditions, soil physical properties directly affect the tractor LF. Therefore, it is expected that more accurate LF estimation will be possible by utilizing soil physical properties. This study was conducted to assess the impact of soil physical properties on the LF. Experimental data were collected in ten different soil conditions. Correlation analysis revealed that the LF exhibited strong correlations with SMC, soil texture, and CI, in that order. The coefficient of determination for the regression model developed using soil variables ranged from 0.678 to 0.926. The developed regression models generally showed higher accuracy when utilizing multiple soil variables, as compared to using a single soil variable. Therefore, an effective estimation of the LF through non-experimental methods can be achieved by measuring various soil properties.
Suggested Citation
Yi-Seo Min & Yeon-Soo Kim & Ryu-Gap Lim & Taek-Jin Kim & Yong-Joo Kim & Wan-Soo Kim, 2023.
"The Influence of Soil Physical Properties on the Load Factor for Agricultural Tractors in Different Paddy Fields,"
Agriculture, MDPI, vol. 13(11), pages 1-16, October.
Handle:
RePEc:gam:jagris:v:13:y:2023:i:11:p:2073-:d:1269891
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