Author
Listed:
- Gholamhossein Shahgholi
(Department of Biosystems Engineering, University of Mohaghrgh Ardabili, Ardabil 56199-11367, Iran)
- Abdolmajid Moinfar
(Department of Biosystems Engineering, University of Mohaghrgh Ardabili, Ardabil 56199-11367, Iran)
- Ali Khoramifar
(Department of Biosystems Engineering, University of Mohaghrgh Ardabili, Ardabil 56199-11367, Iran)
- Sprawka Maciej
(Department of Agricultural, Forest and Transport Machinery, University of Life Sciences in Lublin, 20-950 Lublin, Poland)
- Mariusz Szymanek
(Department of Agricultural, Forest and Transport Machinery, University of Life Sciences in Lublin, 20-950 Lublin, Poland)
Abstract
Many factors contribute to soil compaction. One of these factors is the pressure applied by tires and tillage tools. The aim of this study was to study soil compaction under two sizes of tractor tire, considering the effect of tire pressure and traffic on different depths of soil. Additionally, to predict soil density under the tire, an adaptive neuro-fuzzy inference system (ANFIS) was used. An ITM70 tractor equipped with a lister was used. Standard cylindrical cores were used and soil samples were taken at four depths of the soil inside the tire tracks. Tests were conducted based on a randomized complete-block design with three replications. We tested two types of narrow and normal tire using three inflation pressures, at traffic levels of 1, 3 and 5 passes and four depths of 10, 20, 30 and 40 cm. A grid partition structure and four types of membership function, namely triangular, trapezoid, Gaussian and General bell were used to model soil compaction. Analysis of variance showed that tire size was significant on soil density change, and also, the binary effect of tire size on depth and traffic were significant at 1%. The main effects of tire pressure, traffic and depth were significant on soil compaction at 1% level of significance for both tire types. The inputs of the ANFIS model included tire type, depth of soil, number of tire passes and tire inflation pressure. To evaluate the performance of the model, the relative error (ε) and the coefficient of explanation (R 2 ) were used, which were 1.05 and 0.9949, respectively. It was found that the narrow tire was more effective on soil compaction such that the narrow tire significantly increased soil density in the surface and subsurface layers.
Suggested Citation
Gholamhossein Shahgholi & Abdolmajid Moinfar & Ali Khoramifar & Sprawka Maciej & Mariusz Szymanek, 2023.
"Investigating the Effect of Tractor’s Tire Parameters on Soil Compaction Using Statistical and Adaptive Neuro-Fuzzy Inference System (ANFIS) Methods,"
Agriculture, MDPI, vol. 13(2), pages 1-15, January.
Handle:
RePEc:gam:jagris:v:13:y:2023:i:2:p:259-:d:1042897
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:2:p:259-:d:1042897. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.