Design and parametric optimization of a deep-loosening culti‌vator working body for cotton inter-row tillage

Document Type : Research Paper

Authors

1 Andijan Institute of Agriculture and Agrotechnologies, Andijan, Uzbekistan

2 Termez State University, Termez, Uzbekistan

3 Tashkent State University of Economics 49, Islam Karimov str., 100066, Tashkent, Uzbekistan

10.22124/cjes.2026.9785

Abstract

Efficient soil tillage is essential for sustainable cotton production and resource-saving agriculture. Conventional inter-row cultivation requires multiple passes, leading to increased fuel consumption, soil compaction, and operational costs. This study presents the design, analytical modeling, and experimental optimization of a deep-loosening working body integrated into an inter-row cultivator for cotton cultivation. The proposed tool improves soil aeration, water infiltration, and root development while reducing energy consumption. Mathematical models were developed to determine optimal tool geometry considering soil mechanical properties, plant root protection zones, and operational parameters. Experimental investigations evaluated the effects of working width, penetration angle, and tool length on soil fragmentation, loosened layer width, and draft resistance. Regression models were established to determine optimal parameter combinations ensuring maximum agro-technical performance with minimal energy consumption. Field tests confirmed reliable operation and compliance with agronomic requirements. The developed cultivator reduced labor costs by 51% and operational expenses by 32%, while improving soil structure and moisture retention. The proposed design contributes to sustainable and energy-efficient cotton production systems.

Keywords

References

Abrorov, S 2019, The importance of sukuk in the development of economy: As an example of its impact on the income of the Malaysian population. Journal of Advanced Research in Dynamical and Control Systems, 11(7): 927–931.
Abrorov, S et al. 2025, Circular economy approaches for the management of textile waste in Tashkent: Viability and policy recommendations. Caspian Journal of Environmental Sciences, 23(5): 1167–1174.
Abo-Elnor, M, Hamilton, R & Boyle, JT 2021, Effect of subsoiler shank geometry on draft force and soil disturbance. Soil & Tillage Research, 208: 104885. https://doi.org/10.1016/j.still.2020.104885.
Al-Suhaibani, SA & Ghaly, AE 2021, Energy consumption and performance evaluation of tillage implements. Applied Engineering in Agriculture, 37(4): 645–656. https://doi.org/10.13031/aea.14622.
Bae, B-M, Kim, Y-S, Kim, W-S, Kim, Y-J, Lee, S-D & Kim, T-J 2023, The development of a draft force prediction model for agricultural tractors based on the discrete element method in loam and clay loam. Agriculture, 13: 2205. https://doi.org/10.3390/agriculture13122205.
Baskar, G et al. 2025, Optimized machine learning models for water quality prediction: Integrating support vector machines and random forest through nonlinear functional analysis. Results in Nonlinear Analysis, 8(4): 24–34.
Battiato, A & Diserens, E 2022, Tractor traffic and soil compaction in modern agriculture. Soil Use and Management, 38(1): 15–29. https://doi.org/10.1111/sum.12705.
Chen, Y, Liu, J & Kushwaha, RL 2022, Soil–tool interaction dynamics and performance optimization of tillage implements. Biosystems Engineering, 214: 1–15. https://doi.org/10.1016/j.biosystemseng.2021.11.012.
Colombi, T & Keller, T 2019, Developing strategies to recover crop productivity after soil compaction. Soil & Tillage Research, 185: 83–90. https://doi.org/10.1016/j.still.2018.08.008.
Faizrakhmanova, A et al. 2025, AI-enhanced frameworks for equity and inclusion in digital learning environments. In International Conference on Microelectronics, Electromagnetics and Telecommunication. Springer Nature Switzerland, Cham.
Fakhriddin, I et al. 2025, Load–frequency control of a restructured multi-area power system with DFIG-based wind integration using coordinated AVR–PSS–FACTS and optimized PID controllers. Journal of Operation and Automation in Power Engineering, 13(Special Issue).
Gao, W, Liu, Y & Wang, Q 2023, Influence of deep tillage on soil water infiltration and root growth in row crops. Agricultural Water Management, 280: 108224. https://doi.org/10.1016/j.agwat.2023.108224.
Hanna, HM, Quick, GR & Kushwaha, RL 2020, Energy requirements and fuel efficiency of tillage systems: A review. Applied Engineering in Agriculture, 36(3): 273–285. https://doi.org/10.13031/aea.13626.
Jabro, JD, Stevens, WB & Evans, RG 2022, Long-term conservation tillage impacts on soil properties and crop productivity. Agronomy Journal, 114(2): 789–801. https://doi.org/10.1002/agj2.20958.
Keesstra, S, Mol, G & de Vente, J 2021, Sustainable soil management for food security and ecosystem services. Sustainability, 13(21): 12011. https://doi.org/10.3390/su132112011.
Keller, T, Sandin, M, Colombi, T, Horn, R & Or, D 2019, Historical increase in agricultural machinery weights enhanced soil stress levels and adversely affected soil functioning. Soil & Tillage Research, 194: 104293. https://doi.org/10.1016/j.still.2019.104293.
Khodjayeva, M et al. 2025, Leveraging green technology systems for green accounting and environmental auditing with AI moderating. In Proceedings of the 9th International Conference on Future Networks and Distributed Systems.
Khudoyberdiev, TS & Kholdarov, MSH 2022, Determination of the driving resistance of the working body for deep loosening of cotton row interrows. Irrigation and Melioration, 2(28): 48–52.
Khudoyberdiev, TS & Kholdarov, MSh 2022, Method for adjusting working bodies of a deep ripper of a combined cultivator. Universum: Technical Sciences, 5(98). https://doi.org/10.32743/UniTech.2022. 98.5.13619.
Khudoyberdiev, TS & Kholdarov, MSH 2022, Sectional cultivator for processing between rows to develop a design of a deep softener. ISJ Theoretical & Applied Science, 3(107): 301–305. https://doi.org/10.15863/ TAS.2022.03.107.16.
Kholdarov, MS 2025, Development and justification of the parameters of a cultivator-deep loosener for inter-row cultivation of cotton. PhD dissertation, Andijan, p. 151.
Lal, R 2020, Soil conservation and ecosystem services. International Soil and Water Conservation Research, 8(4): 261–271. https://doi.org/10.1016/j.iswcr.2020.10.002.
Li, B, Chen, Y & McLaughlin, N 2023, Effects of subsoiling on soil physical properties and crop productivity: A meta-analysis. Soil & Tillage Research, 230: 105636. https://doi.org/10.1016/j.still.2023.105636.
Mamadiyarov, Z et al. 2026, Economic impacts of climate change on agricultural production and adaptive strategies for farmers in the Fergana Valley, Uzbekistan. Caspian Journal of Environmental Sciences, 23(5): 1193–1200.
Martínez, E, Blanco-Canqui, H & Wortmann, CS 2022, Strip tillage impacts on soil physical properties and crop performance. Soil Science Society of America Journal, 86(3): 689–702. https://doi.org/10.1002/ saj2.20369.
Mohammad, SI, Vasudevan, A, Zneid, BA, Al-Fawwaz, TM, Wenya, W, Rozikov, I et al. 2026, Optimization and fabrication cost management of GPL reinforcement's geometry via a semi-analytical approach. Advances in Materials Research, 15(2): 125.
Naderi-Boldaji, M & Keller, T 2021, Soil compaction and mechanical stress in arable soils: A review. Soil & Tillage Research, 213: 105155. https://doi.org/10.1016/j.still.2021.105155.
Reicosky, DC & Allmaras, RR 2020, Advances in conservation tillage and soil carbon management. Agronomy Journal, 112(2): 1003–1015. https://doi.org/10.1002/agj2.20061.
Spoor, G & Tijink, FGJ 2022, Subsoil loosening and its role in sustainable crop production. Soil & Tillage Research, 220: 105375. https://doi.org/10.1016/j.still.2022.105375.
Tagar, AA, Ji, C, Ding, Q & Adamowski, J 2020, Performance evaluation of subsoiler design parameters affecting draft force and soil disturbance. Engineering in Agriculture, Environment and Food, 13(3): 252–260. https://doi.org/10.1016/j.eaef.2020.03.002.
Tullberg, JN, Yule, DF & McGarry, D 2018, Controlled traffic farming—From research to adoption in Australia. Soil & Tillage Research, 97(2): 272–281. https://doi.org/10.1016/j.still.2007.09.007.
Ucgul, M, Fielke, J & Saunders, C 2021, Three-dimensional discrete element modelling of tillage: Recent advances and future direction. Computers and Electronics in Agriculture, 188: 106343. https://doi.org/10.1016/j.compag.2021.106343.
Ucgul, M, Saunders, C & Fielke, J 2018, Discrete element modelling of soil–tool interaction: A review of recent advances. Biosystems Engineering, 170: 29–42. https://doi.org/10.1016/j.biosystemseng.2018.03.004.
Wang, Y, He, J & Li, H 2023, Effects of strip tillage and subsoiling on soil compaction and crop yield. Field Crops Research, 295: 108868. https://doi.org/10.1016/j.fcr.2023.108868.
Zhang, R, Chen, Y & Kushwaha, RL 2020, Simulation of soil–tool interaction using discrete element modeling. Computers and Electronics in Agriculture, 169: 105174. https://doi.org/10.1016/j.compag.2019.105174
Zhang, Z, Li, H & Wang, X 2022, Optimization of tillage tool geometry for reduced energy consumption. Agriculture, 12(6): 820. https://doi.org/10.3390/agriculture12060820.
Caspian Journal of Environmental Sciences
Volume 24, Issue 3
July 2026
Pages 713-727

Files

Share

How to cite

Statistics