Preliminary Field Evaluation of Seeds Drilling Assisted by a Tractor with Autopilot System
Seed drilling is one of the steps in agricultural operations that always needs great attention as it will eventually affect crop production. In a mechanized seed drilling, the quality of operation is measured by precision planting of seeds or seedlings in the rows. This study was conducted to evaluate a seed-drilling machine trailed by a tractor equipped with autopilot system. This machinery system was tested for planting corn on tilled soil. The tractor's operating speeds were set at three levels, i.e., 3.4 km/hr, 4.2 km/hr, and 5.5 km/hr. The effects of these different speeds were investigated towards numbers of seeds per hole, plants distance, and seedlings damage. Field capacity and average heart rate of tractor operator during conducting the operation were also measured. The findings showed significant differences between the operating speeds towards the numbers of seeds per hole and field capacity. Also, the observation showed that the operating speeds and field capacity had a close relationship. The same situation also happened between the operating speeds and average heart rates of operator. The operating speed of 5.5 km/hr was the best speed for achieving the highest field capacity, while the operating speed of 3.4 km/hr was highly recommended if seeds use efficiency become a preference. Generally, this study has successfully given introductory exploration for the potential use of tractor with autopilot system in seeds drilling operation for Malaysia's cash crop.
Deere, J., 2016, AutoTrac- RowSense Sprayer. https://www.deere.com/en/technology-products/precision-ag-technology/guidance/auto-trac-row-sense-sprayer/?panel=harvest Accessed on 8 February 2020.
Deere & Company, 1981. Fundamental of machine operation: Planting. John Deere Service Publications, Moline, Illinois, USA.
Hamdan, M.H., Pebrian, D.E., 2019, Preliminary assessment on the potential for use of an autopilot tractor on Malaysia’s flat terrain. The Planter Vol. 95 (1115), 2019:97-104.
Hunt, D., Wilson, D., 2016, Farm power & machinery management. 11st ed. Waveland Press, Inc., Long Grove, Illinois, USA.
Kepner, R.A., Bainer, R., Barger, E.L., 1978. Principle of farm machinery. 3rd ed. AVI Publishing Co. Inc., Van Nostrand Reinhold. New York. USA.
Lipinski, A. J., Markowski, P., Seweryn, L. and Pyra, P. 2016. Precision of tractor operations with soil cultivation implements using manual and automatic steering modes. Biosystem Engineering Vol, 145, 2016:22-28.
LPP (Malaysian Farmers Organisation). LPP Transformation. in Malay. Lembaga Pertubuhan Peladang (LPP) Malaysia, Vol.1, 2017: 11-12.
Ortiz, B. V., Balkcom, K. B., Duzy, L., Santen, E. van., Hartzog, D.L.,2013. Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations. Precision Agriculture, Vol .14, 2013:357-375.
Vellidis, G., Ortiz, B., Beasley, J., Hill, R., Henry, H., Brannen, H., 2014. Reducing digging losses by using automated steering to plant and invert peanuts. Agronomy, Vol.4, 2014: 337-348.
Trimble. 2015. Autopilot automated steering system. Data sheet. Trimble Agriculture Division. www.trimble.com. Accessed 20 November 2019.
Siemens, J.C., Bowers, W, Holmes, R. G., 2008. Machinery Management. 6th ed.: Deere & Co. Moline, Illinois, USA.
Srivastava, A.K., Goering, C.E., Rohrbach, R.P., Buckmaster, D.R, 2006. Engineering principles of agricultural machines.2nd ed. ASABE. 2950 Niles Road, St. Joseph, Michigan, USA.
Zorbato, C., Furlani, C.E.A, Oliveira, M. F. de., Voltarelli, M.A., Tavares, T.de.O., Carneiro, F.M., 2019. Quality of mechanical peanut sowing and digging using autopilot. Revista Brasileira de Engenharia Agrícola e Ambiental. Vol. 23 (8), 2019:630-637.
Copyright (c) 2021 darius el pebrian
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Author(s) shall retain the copyright of their work and grant the Journal/Publisher right for the first publication with the work simultaneously licensed under:
Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). This license allows for the copying, distribution and transmission of the work, provided the correct attribution of the original creator is stated. Adaptation and remixing are also permitted.
This broad license intends to facilitate free access to, as well as the unrestricted reuse of, original works of all types for non-commercial purposes.
The author(s) permits HH Publisher to publish this article that has not been submitted elsewhere.