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- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
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Vol. 12, Issue 12 (2023)
Development of an algorithm for crop row detection for autonomous fertilizer side dressing machine
Author(s):
Dr. Chirag S Matholiya, Dr. Piyush R Balas, Sanjaykumar J Pargi, Dr. Vishal V Agravat and Dr. Pankaj Gupta
Dr. Chirag S Matholiya, Dr. Piyush R Balas, Sanjaykumar J Pargi, Dr. Vishal V Agravat and Dr. Pankaj Gupta
Abstract:
Agricultural crop production involves many operations, out of which fertilizer application is one of the important and least exploited operations. At present fertilizer, especially in split doses applied manually. But, labour scarcity is becoming a problem day by day. To reduce the labour problem and to make agriculture lucrative, the use of modern technologies such as robotics, automation, etc. is the need of the hour. Considering all these, an autonomous machine was developed for fertilizer side dressing application. In the fertilizer side dressing technique, the exact metered quantity of fertilizer was applied near the periphery of the plant which overcome certain problems.
Agricultural crop production involves many operations, out of which fertilizer application is one of the important and least exploited operations. At present fertilizer, especially in split doses applied manually. But, labour scarcity is becoming a problem day by day. To reduce the labour problem and to make agriculture lucrative, the use of modern technologies such as robotics, automation, etc. is the need of the hour. Considering all these, an autonomous machine was developed for fertilizer side dressing application. In the fertilizer side dressing technique, the exact metered quantity of fertilizer was applied near the periphery of the plant which overcome certain problems.
An autonomous machine was developed using vision-based and sensor-based technology. In vision-based technology, the image processing technique was used to identify the row crop and allowed the machine to run in between the rows by correcting the lateral error. The principle of the machine was to run the machine in between the row crop and drop the exact metered quantity of fertilizer near the plant periphery. In the field test, machine trajectory parameters like tracking lateral error, angle of deviation and reaction time were found significant at 5% level of significance at camera height of 60 cm and camera angle of 45° in cotton and okra crops. The minimum tracking lateral error, angle of deviation and reaction time were found to be 4.37 cm, 9.4° and 0.47 s for cotton crop and 3.35 cm, 7.01° and 0.38 s for okra crop, respectively at camera height of 60 cm and camera angle of 45°.
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How to cite this article:
Dr. Chirag S Matholiya, Dr. Piyush R Balas, Sanjaykumar J Pargi, Dr. Vishal V Agravat, Dr. Pankaj Gupta. Development of an algorithm for crop row detection for autonomous fertilizer side dressing machine. Pharma Innovation 2023;12(12):3398-3407.
Journal code(s)
- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
Main Menu
Special Issue
Copyright Form
Identifier
The Pharma Innovation Journal
