journal article·2026-07-01Open access

Development, Numerical Simulation and Laboratory Validation of a Load-Cell-Based Mass Flow Rate Measuring Sensor for Dry Fertilizers in Seed Drills

Mohamed Edrris, Khalid Al-Gaadi, Elkamil Tola, Yahia Gaddal

Applied Sciences· Volume 16· Issue 13

Abstract

An impact-based sensing system was developed and validated for real-time measurement of granular fertilizer mass flow rate in seed drills. Discrete Element Method (DEM) simulation was used to optimize the geometric configuration of the sensing unit, focusing on the fertilizer distance between the fertilizer tube outlet and the impact plate of the sensing unit (offset distance), using urea and NPK fertilizers. The simulation results identified an offset distance of 2.5 cm as the optimum configuration for both urea and NPK fertilizers, providing the most stable and repeatable flow response with minimum variability and flow interruption. The sensor was experimentally evaluated under controlled laboratory conditions using different positions of the fertilizer rate adjusting lever and machine forward speeds. The ANOVA results showed that both factors and their interaction significantly affected fertilizer flow rate (p < 0.0001). The measured flow rates exhibited strong agreement with gravimetric reference data, yielding a near-linear relationship (R2 = 0.9999), with an overall accuracy of approximately 97% and mean relative errors between 5.1% and 7.4%. These results demonstrate that the developed load-cell-based impact sensor enables accurate and repeatable granular fertilizer flow rate measurement. In general, the impact-based sensor developed in this study combines competitive accuracy with simplicity, affordability and broad applicability and potential for integration with variable-rate application systems.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Soil Mechanics and Vehicle Dynamics · Granular flow and fluidized beds · Polymer-Based Agricultural Enhancements

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Precision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia

Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia

Funding

King Saud University

References (35)

Show source-provided references
1. Customized fertilizer: A key for enhanced crop production10.9734/ijpss/2022/v34i232505 ↗
2. Variable rate fertilizer application technology for nutrient management: A review
3. Zhang, Q. (2022). Variable Rate Technologies for Precision Agriculture. Encyclopedia of Digital Agricultural Technologies, Springer International Publishing.
4. Evaluation of different crop model-based approaches for variable rate nitrogen fertilization in winter wheat10.1007/s11119-022-09957-5 ↗
5. Variable-rate spray system for unmanned aerial applications using lag compensation algorithm and pulse width modulation spray technology
6. Application of fibre sensor in grain drill to estimate seed flow under field operational conditions10.1016/j.compag.2016.01.006 ↗
7. Optical sensor for granular fertilizer flow rate measurement10.13031/2013.9934 ↗
8. A solid fertilizer and seed application rate measuring system for a seed-fertilizer drill machine10.1016/j.compag.2019.05.007 ↗
9. A novel in-situ sensor calibration method for building thermal systems based on virtual samples and autoencoder10.1016/j.energy.2024.131314 ↗
10. Development and experimental analysis of an intelligent sensor for monitoring seed flow rate based on a seed flow reconstruction technique10.1016/j.compag.2019.104899 ↗
11. Mirzakhaninafchi, H., Singh, M., Bector, V., Gupta, O.P., and Singh, R. (2021). Design and development of a variable rate applicator for real-time application of fertilizer. Sustainability, 13.10.3390/su13168694 ↗
12. Co-simulation of multibody dynamics and discrete element method for hydraulic excavators10.1016/j.powtec.2022.118001 ↗
13. Zhao, H., Huang, Y., Liu, Z., Liu, W., and Zheng, Z. (2021). Applications of discrete element method in the research of agricultural machinery: A review. Agriculture, 11.10.3390/agriculture11050425 ↗
14. Fertilizer sowing simulation of a variable-rate fertilizer applicator based on EDEM10.1016/j.ifacol.2018.08.185 ↗
15. Zhang, M., Niu, H., Han, Y., Zhi, Y., Yuan, T., Zhang, H., He, Y., Tang, Z., and Lan, H. (2024). A simulation and experiment of the flow fluctuation characteristics of a fertilizer distribution apparatus with a screw from the perspective of the force chain. Appl. Sci., 14.10.3390/app14031122 ↗
16. Agricultural processes simulation using discrete element method: A review10.1016/j.compag.2025.110733 ↗
17. Chen, J., Qi, S., Xu, F., Jia, P., Yuan, Z., Xi, D., Xu, H., and Wang, J. (2025). CFD-DEM-based simulation and performance analysis of key parameters in pneumatic high-speed precision maize seed-metering device. Front. Plant Sci., 16.10.3389/fpls.2025.1700037 ↗
18. Smart Sensor Technologies Shaping the Future of Precision Agriculture: Recent Advances and Future Outlooks10.1155/js/2460098 ↗
19. Flowability and handling characteristics of bulk solids and powders—A review with implications for DDGS10.1016/j.biosystemseng.2008.09.008 ↗
20. Yuan, F., Yu, H., Wang, L., Shi, Y., Wang, X., and Liu, H. (2023). Parameter calibration and systematic test of a discrete element model (DEM) for compound fertilizer particles in a mechanized variable-rate application. Agronomy, 13.10.3390/agronomy13030706 ↗
21. Development of an opto-electronic measurement system for planter laboratory tests10.1016/j.measurement.2017.01.060 ↗
22. Parameter optimization of fluted-roller meter using discrete element method
23. Calibration of DEM models for fertilizer particles based on numerical simulations and granular experiments10.1016/j.compag.2022.107507 ↗
24. Bu, H., Yu, S., Dong, W., Wang, Y., Zhang, L., and Xia, Y. (2022). Calibration and testing of discrete element simulation parameters for urea particles. Processes, 10.10.3390/pr10030511 ↗
25. Lei, X., Wu, W., Deng, X., Li, T., Liu, H., Guo, J., Li, J., Zhu, P., and Yang, K. (2023). Determination of material and interaction properties of granular fertilizer particles using DEM simulation and bench testing. Agriculture, 13.10.3390/agriculture13091704 ↗
26. Determination of pin-roller parameters and evaluation of the uniformity of granular fertilizer application metering devices in precision farming10.1016/j.compag.2020.105835 ↗
27. DEM simulation of impact force exerted by granular flow on rigid structures10.1007/s11440-011-0140-9 ↗
28. Bangura, K., Gong, H., Deng, R., Tao, M., Liu, C., Cai, Y., Liao, K., Liu, J., and Qi, L. (2020). Simulation analysis of fertilizer discharge process using the Discrete Element Method (DEM). PLoS ONE, 15.10.1371/journal.pone.0235872 ↗
29. Granular fertilizer mass prediction for electric fertilizer distribution device based on RANSAC10.15666/aeer/1704_79177925 ↗
30. Signal processing method and performance tests on weighting-sensor-based measuring system of output quantity for a seeding and fertilizing applicator10.1016/j.ifacol.2018.08.153 ↗
31. Estimation of mass flow of seeds using fibre sensor and multiple linear regression modelling10.1016/j.compag.2013.09.005 ↗
32. Research on continuous granular material flow detection method and sensor10.1016/j.measurement.2021.109773 ↗
33. A practical approach to comparative design of non-contact sensing techniques for seed flow rate detection10.1016/j.compag.2017.08.027 ↗
34. Granular fertiliser application rate control system with integrated output volume measurement10.1016/j.biosystemseng.2008.09.019 ↗
35. Real-time monitoring of the mass flow rate of granular materials in the seeder tube using a piezoelectric sensor