Using the Response Surface Methodology to Predict the Effect of Different Moisture Levels on the Bulk Density and Penetration Resistance of Soil Under Different Operating Conditions

Articles in Press

Document Type : Research Article-en

Authors

• M. ALmoosa ¹
• S. Al-Atab ²
• S. Almaliki ¹

¹ Department of Agriculture Machines and Equipment, College of Agriculture, University of Basrah, Iraq

² Department of Soil and water Science, College of Agriculture, University of Basrah, Iraq

10.22067/jam.2024.90031.1290

Abstract

Soil properties play a fundamental role in the success of agricultural operations through their impact on crop growth and quality, as they determine their ability to retain water and absorb nutrients, and affect soil aeration and the root system. The aim of this study is to predict bulk density and resistance to soil penetration under different moisture levels during tillage operations. It includes four moisture levels: 7, 14, 22, and 28%, and three types of plows: the moldboard plow, chisel plow, and disc plow. Moreover, soil samples were collected at two depths: 15 cm and 30 cm. The change in the physical properties of the studied soil is also measured during the growth periods of wheat crop (after tillage, beginning of the season and end of the season). The study is conducted in Al-Qurna district, north of Basra Governorate, Iraq, in clay loam soil. The results are analyzed and mathematical equations are obtained to predict the studied properties using the response surface methodology. The obtained results indicate that soil moisture during plowing, plow type, soil depth, and crop growth periods have a significant effect on soil bulk density and penetration resistance. The 14% moisture treatment is superior, recording the lowest bulk density and lowest penetration resistance of 1.12 Mg m^-3 and 1133 kN m^-2, respectively. While the 28% moisture treatment provided the highest bulk density and highest penetration resistance of 1.22 Mg m^-3 and 1379 kN m^-2, respectively. The results also show that increasing the soil depth from 15 to 30 cm increases the bulk density and soil penetration resistance, by 12 and 45.70%, respectively. Plowing with a disc plow improves soil properties, giving the lowest bulk density and penetration resistance of 1.12 Mg m^-3 and 1074 kN m^-2, respectively. While using the chisel plow leads to recording the highest bulk density and penetration resistance, which reached 1.22 Mg m^-3 and 1442 kN m^-2, respectively. As for the moldboard plow, the bulk density and soil penetration resistance reached 1.18 Mg m^-3 and 1282 kN m^-2, respectively. The growth periods have a significant effect on the studied soil properties where the beginning of the growing season provided the lowest bulk density. The bulk density reached 1.17, 1.13, and 1.23 Mg m^-3 for the periods after plowing, at the beginning of the season and its end, respectively. While the penetration resistance after plowing is superior with the lowest resistance compared to the beginning of the season and its end, as it reached 897, 1327, and 1573 kN m^-2, respectively. The results of data analysis show that the obtained mathematical models accurately and efficiently predict bulk density and soil resistance to penetration under the experimental conditions, with a high coefficient of determination (R²) of 0.6460 and 0.8114 for the bulk density and penetration resistance, respectively.

Keywords

• Bulk density
• Moisture level
• Prediction
• Soil penetration resistance
• Tillage equipment

Main Subjects

• Agricultural systems engineering (greenhouse, fish farming, mushroom production)

©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

References

1. AbdulSada, A. J., & Almaliki, S. (2023). Prediction of Soil Compaction using Conventional Tillage Systems under Different Operating Conditions. In IOP Conference Series: Earth and Environmental Science(Vol. 1259, No. 1, p. 012127). IOP Publishing.‏ https://doi.org/10.1088/1755-1315/1259/1/012127
2. Ahmadi, H., & Mollazade, K. (2009). Effect of plowing depth and soil moisture content on reduced secondary tillage. Agricultural Engineering International: The CIGR EJournal, 11, 1-9.‏ https://www.researchgate.net/publication/243457629
3. Ahmadi, I., & Ghaur, H. (2015). Effects of soil moisture content and tractor wheeling intensity on traffic-induced soil compaction. Journal of Central European Agriculture, 16(4): 489-502. https://doi.org/10.5513/jcea.v16i4.3817
4. Almaliki, S., Himoud, M., & Al-Khafajie, A. (2019). Artificial neural network and stepwise approach for predicting tractive efficiency of the tractor (CASE JX75T). The Iraqi Journal of Agricultural Science, 50, 1008-1017. https://doi.org/10.36103/ijas.v50i4.745
5. Amin, M., Khan, M. J., Jan, M. T., Rehman, M. U., Tariq, J. A., Hanif, M., & Shah, Z. (2014). Effect of different tillage practices on soil physical properties under wheat in semi-arid environment. Soil Environment, 33(1): 33-37.‏ https://www.cabidigitallibrary.org/doi/full/10.5555/20143226515
6. ASABE (2009). ASAE D497.6 Agricultural Machinery Management Data. ASAE. St. Joseph. MI:49085, 1-8. https://cutt.ly/EfMlj1q
7. Biberdzic, M., Barac, S., Lalevic, D., Djikic, A., Prodanovic, D., & Rajicic, V. (2020). Influence of soil tillage system on soil compaction and winter wheat yield. Chilean Journal of Agricultural Research, 80(1): 80-89.‏ https://doi.org/10.4067/S0718-58392020000100080
8. Black, C. A., Evans, D. D., White, L. L., Ensminger, L. E., & Clark, E. (1965). Method of soil analysis, American Society of Agronomy Madison, Wisconsin, USA. No. 9 part I and II. http://www.worldcat.org/oclc/85962062
9. Boydas, M. G., & Turgut, N. )2007(. Effect of tillage implements and operating speeds on soil physical properties and wheat emergence. Turkish Journal of Agriculture and Forestry, 31, 399-412. https://journals.tubitak.gov.tr/agriculture/vol31/iss6/6/
10. Dekemati, I., Bogunovic, I., Kisic, I., Radics, Z., Szemők, A., & Birkás, M. (2019). The effects of tillage-induced soil disturbance on soil quality. Polish Journal of Environmental Studies, 28(5), 3665-3673.‏ https://doi.org/10.15244/pjoes/97359
11. Hajabbasi, M. A. (2010). Tillage effects on soil compactness and wheat root Journal of Agricultural Science and Technology, 3, 67-77. http://jast.modares.ac.ir/article-23-4803-en.html
12. Javadi, A., & Spoor, G. (2006). The effect of spacing in dual wheel arrangements on surface load support and soil compaction Journal of Agricultural Science and Technology, 8, 119-131. http://jast.modares.ac.ir/article-23-2794-en.html
13. Kahlon, M., Lal, R., & Varughese, M. (2013). Twenty-Two Years of Tillage and mulching impacts on soil physical characteristics and carbon sequestration in central Ohio. Soil and Tillage Research, 126, 151-158. https://doi.org/10.1016/j.still.2012.08.001
14. Kostić, M. M., Rakić, D. Z., Savin, L. Đ., Dedović, N. M., & Simikić, M. Đ. (2016). Application of an original soil tillage resistance sensor in spatial prediction of selected soil properties. Computers and Electronics in Agriculture, 127, 615-624.‏ https://doi.org/10.1016/j.compag.2016.07.027
15. Kuhwald, M., Blaschek, M., Minkler, R., Nazemtseva, Y., Schwanebeck, M., Winter, J., & Duttmann, R. (2016). Spatial analysis of long‐term effects of different tillage practices based on penetration resistance. Soil Use and Management, 32(2), 240-249.‏ https://doi.org/10.1111/sum.12254
16. Kuroyanagi, N., Kaneko, A., Watanabe, T., Fujita, A., & Odahara, K. (1997). Effect of long- term application of organic matters on upland field. (2) yield of upland crop and physical properties of soil. (Fukuoka Agricultural Research Center, Chikushino, Fukuoka 818 Japan) Bull. Fukuoka Agriculture Research Center, 16, 63-66. https://cir.nii.ac.jp/crid/1571417124296650112
17. Martins, R. N., Portes, M. F., e Moraes, H. M. F., Junior, M. R. F., Rosas, J. T. F., and Junior, W. D. A. O. (2021). Influence of tillage systems on soil physical properties, spectral response and yield of the bean crop. Remote Sensing Applications: Society and Environment, 22, 100517.‏ https://doi.org/10.1016/j.rsase.2021.100517
18. Naderi-Boldaji, M., Azimi-Nejadian, H., & Bahrami, M. (2024). A Finite Element Model of Soil-Stress Probe Interaction under a Moving Rigid Wheel. Journal of Agricultural Machinery, 14(1).‏ https://doi.org/10.22067/jam.2023.84158.1185
19. Nassir, A. J. (2018). Effect of moldboard plow types on soil physical properties under different soil moisture content and tractor speed. Basrah Journal of Agricultural Sciences, 31(1), 48-58.‏ https://doi.org/10.37077/25200860.2018.75
20. Rashidi, M., Tabatabaeefar, A., Keyhani, A., & Attarnejad, R. (2007). Non-linear amodeling of pressure-sinkage behaviour in soils using the finite Element method. Journal of Agricultural Science and Technology, 9, 1-13. https://www.sid.ir/EN/VEWSSID/J_pdf/84820070101.pdf
21. Salim, A. E. A., Almaliki, S. A., & Nedawi, D. R. (2022). Smart Computing Techniques for Predicting Soil Compaction Criteria under Realistic Field Conditions. Basrah Journal of Agricultural Sciences, 35(1), 188-211.‏ https://doi.org/10.37077/25200860.2022.35.1.15
22. Shabanpour, M., Fekri, S., Bagheri, I., Payman, S. H., & Rahimi-Ajdadi, F. (2022). Effects of tillage method and drainage management on some soil physical properties. Journal of Agricultural Sciences, 24-24.‏ https://doi.org/10.15832/ankutbd.856328
23. Shittu, K., Oyedele, D., & Babatunde, K. (2017). The effects of moisture content at tillage on soil strength in maize Egyptian Journal of Basic and Applied Sciences, 4(2), 139-142. https://doi.org/10.1016/j.ejbas.2017.04.001
24. Taghavifar, H., & Mardani, A. (2014). Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices. Energy, 68, 651-657. https://doi.org/10.1016/j.energy.2014.01.048
25. Tahmasebi, M., Gohari, M., Sharifi Malvajerdi, A., & Hedayatipour, A. (2023). Development and field evaluation of a variable-depth tillage tool based on a horizontal pneumatic sensor measurement. Journal of Agricultural Machinery, 13(1), 85.‏ https://doi.org/10.22067/jam.2023.79231.1128