Engineering Technologies and Systems - 01. Popov А.Yu. Simulation of Square Cluster Planting

UDK 631.53.044-047.58

DOI: 10.15507/2658-4123.030.202004.524-549

Simulation of Square Cluster Planting

Anton Yu. Popov
Associate Professor of Chair of Design and Technical Service of Transport and Technological Systems, Don State Technical University (1 Gagarin Square, Rostov-on-Don 344000, Russian Federation), Cand.Sc. (Engineering), ORCID: https://orcid.org/0000-0002-4922-4158, This email address is being protected from spambots. You need JavaScript enabled to view it.

Introduction. For cultivated crops, the optimal form of spacing is square form, which is provided by the square cluster method of planting. Currently, due to the high metal consumption and low productivity, this method of planting has been replaced with a single-seed planting one. But this does not solve the problem of rational distribution of seeds in the field, so the problem of plant spacing with the use of the optimal square form of spacing is relevant. The aim of the study is to develop and analyze a simulation model of square cluster planting based on an algorithm for controlling the executive mechanisms of the seeder sections using devices for local coordination of the seeding apparatus.
Materials and Methods. A programmable square cluster planting using local coordination of the seeding apparatus and an algorithm for its realization are considered. The article describes the construction of a simulation model of sowing planting in Simulink Matlab with justification of its elements. The seed spreading in furrows and the seeder variable speed are taken into account. The number of pulses per revolution of the encoder shaft is theoretically justified.
Results. The graphs of the distance traveled, positions coordinates of the flap opening and control signals depending on the time are constructed. The analysis of the encoder settings is carried out. When varied the plant spacing and the coordinates of the first flap opening, the dimension of the last seed cluster changes in the range from –2.6 ∙ 10^–3 to 2.7 ∙ 10^–3 m. With the increase in the seeder speed from 1.5 to 3.0 m/s, the mathematical expectation of the seed cluster dimensions increase from 0.054 to 0.218 m, and the coefficient of variation decreases from 61.2 to 15.0%.
Discussion and Conclusion. The analysis of the simulation model of the square cluster planting showed that the algorithm for controlling executive mechanisms together with the local coordination system works adequately and provides high precision of placing seed clusters in the field. The dependences of the optimal number of pulses per an encoder shaft revolution on the specified seed spacing and radius of the track measuring wheel are determined. It was determined that the maximum dimension of the last seed cluster does not exceed 2.7 mm per 1 000 m (for x = 0.3 m and t = 0.7 m). It was found that the precision of the distribution of seed clusters in the field is determined more by the seeder speed than by the settings of the measuring device.

Keywords: control program, square cluster planting method, signal, encoder, seeding model, seed spread, the uneven distribution

For citation: Popov А.Yu. Simulation of Square Cluster Planting. Inzhenerernyye tekhnologii i sistemy = Engineering Technologies and Systems. 2020; 30(4):524-549. DOI: https://doi.org/10.15507/2658-4123.030.202004.524-549

The author has read and approved the final manuscript.

Received 10.07.2020; revised 20.08.2020; published online 30.12.2020

REFERENCES

1. Mukhin V.A, Kromm A.A, Shchukin S.G. Effect of Cereal Spike Crops Sowing Methods on the Growing Space of Plants. Sibirskiy vestnik selskokhozyaystvennoy nauki = Siberian Herald of Agricultural Science. 2005; (6):71-78. (In Russ.)

2. Vasilenko V.V., Vasilenko S.V. [Distribution of Sugar Beet Seeds and Plants at Dotted Sowing]. Tekhnika v selskom khozyaystve = Machinery in Agriculture. 1999; (1):6-9. (In Russ.)

3. Marchenko L.A., Artushin A.A., Smirnov I.G., et al. Technology of Pesticides and Fertilizers Application with Unmanned Aerial Vehicles in Digital Agriculture. Selskokhozyaystvennye mashiny i tekhnologii = Agricultural Machinery and Technologies. 2019; 13(5):38-45. (In Russ.) DOI: https://doi.org/10.22314/2073-7599-2019-13-5-38-45

4. Lichman G.I., Marchenko N.M. [Space Monitoring in Precision Farming System]. Selskokhozyaystvennye mashiny i tekhnologii = Agricultural Machinery and Technologies. 2010; (1):27-31. (In Russ.)

5. [Seed Complex Control and Management System]: Patent 167927 Russian Federation. No. 2015147700; appl. 06.11.2015; publ. 12.01.2017. Bulletin No. 2. Available at: https://new.fips.ru/registers-doc-view/fips_servlet?DB=RUPM&DocNumber=167927&TypeFile=html (accessed 12.10.2020). (In Russ.)

6. Lu W., Zeng M., Wang L., et al. Navigation Algorithm Based on the Boundary Line of Tillage Soil Combined with Guided Filtering and Improved Anti-Noise Morphology. Sensors. 2019; 19(18):3918. (In Eng.) DOI: https://doi.org/10.3390/s19183918

7. Mitterer T., Gietler H., Faller L.-M., et al. Artificial Landmarks for Trusted Localization of Autonomous Vehicles Based on Magnetic Sensors. Sensors. 2019; 19(4):813. (In Eng.) DOI: https://doi.org/10.3390/s19040813

8. Li Y., Wang X., Liu D. 3D Autonomous Navigation Line Extraction for Field Roads Based on Binocular Vision. Journal of Sensors. 2019; 2019. 16 p. (In Eng.) DOI: https://doi.org/10.1155/2019/6832109

9. Han X., Kim H.-J., Jeon Ch.W., et al. Application of a 3D Tractor-Driving Simulator for Slip Estimation-Based Path-Tracking Control of Auto-Guided Tillage Operation. Biosystems Engineering. 2019; 178:70-85. (In Eng.) DOI: https://doi.org/10.1016/j.biosystemseng.2018.11.003

10. Malavazi F.B.P., Guyonneau R., Fasquel J.-B., et al. LiDAR-Only Based Navigation Algorithm for an Autonomous Agricultural Robot. Computers and Electronics in Agriculture. 2018; 154:71-79. (In Eng.) DOI: https://doi.org/10.1016/j.compag.2018.08.034

11. Garcia-Santillan I., Guerrero J.M., Montalvo M., et al. Curved and Straight Crop Row Detection by Accumulation of Green Pixels from Images in Maize Fields. Precision Agriculture. 2018; 19:18-41. (In Eng.) DOI: https://doi.org/10.1007/s11119-016-9494-1

12. Bauer A., Bostrom A.G., Ball J., et al. Combining Computer Vision and Deep Learning to Enable Ultra-Scale Aerial Phenotyping and Precision Agriculture: A Case Study of Lettuce Production. Horticulture Research. 2019; 6:70. (In Eng.) DOI: https://doi.org/10.1038/s41438-019-0151-5

13. Yang G., Liu J., Zhao C., et al. Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives. Frontiers in Plant Science. 2017; 8. (In Eng.) DOI: https://doi.org/10.3389/fpls.2017.01111

14. Blok P.M., Boheemen K., Evert F.K., et al. Robot Navigation in Orchards with Localization Based on Particle Filter and Kalman Filter. Computers and Electronics in Agriculture. 2019; 157:261-269. (In Eng.) DOI: https://doi.org/10.1016/j.compag.2018.12.046

15. Fernandez B., Herrera P.J., Cerrada J.A. A Simplified Optimal Path Following Controller for an Agricultural Skid-Steering Robot. IEEE Access. 2019; 7. (In Eng.) DOI: https://doi.org/10.1109/ACCESS.2019.2929022

16. [Method of Ultrasonic Control of Seeders at Square Nest Sowing]: Patent 127497 USSR. No. 625573; appl. 16.04.1959; publ. 01.01.1960. 2 p. Available at: https://new.fips.ru/registers-doc-view/fips_servlet?DB=RUPAT&DocNumber=127497&TypeFile=html (accessed 12.10.2020). (In Russ.)

17. [Method of Sowing Corn Seeds]: Patent 843811 USSR. No. 2752031; appl. 12.04.1979; publ. 07.07.1981. 4 p. Available at: https://new.fips.ru/registers-doc-view/fips_servlet?DB=RUPAT&DocNumber=843811&TypeFile=html (accessed 12.10.2020). (In Russ.)

18. [Device for Sowing Crops by Square-Breeding Method]: Patent 106630 USSR. No. 454858; appl. 13.03.1956; publ. 07.07.1957. 4 p. Available at: https://new.fips.ru/registers-doc-view/fips_servlet?DB=RUPAT&DocNumber=106630&TypeFile=html (accessed 12.10.2020). (In Russ.)

19. Lobachevskiy P.Ya. [Regularities of Flow of Technological Material by Discrete Dispensers]. Vestnik rossiyskoy selskokhozyaystvennoy nauki = Bulletin of the Russian Agricultural Sciences. 1999; (6):33-35. (In Russ.)

20. [Square Nest Planter]: Patent 2363131 Russian Federation. No. 2008113792/12; appl. 08.04.2008; publ. 10.08.2009. 7 p. Available at: https://www.fips.ru/registers-doc-view/fips_servlet?DB=RUPAT&DocNumber=2363131&TypeFile=html (accessed 12.10.2020). (In Russ.)

21. [Square Cluster Sowing Method]: Patent 2369069 Russian Federation. No. 2008120457; appl. 22.05.2008; publ. 10.10.2009. 5 p. Available at: https://www.fips.ru/registers-doc-view/fips_servlet?DB=RUPAT&DocNumber=2369069&TypeFile=html (accessed 12.10.2020). (In Russ.)

22. Zubrilina Ye.M. [Distribution of Seeds of Two Crops in a Row When Sowing Together]. Mekhanizatsiya i elektrifikatsiya selskogo khozyaystva = Mechanization and Electrification of Agriculture. 2002; (7):13-15. (In Russ.)

This work is licensed under a Creative Commons Attribution 4.0 License.