An Exploratory Examination on Small Scale Sugarcane Harvesting Machine
Amith A Kulkarni1, M K Punith Prasad2, Manjunatha s bilagi3, Rishi J P4, S A Mohan Krishna5, Amruth E6

1Amith A Kulkarni, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
2M K Punith Prasad, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
3Manjunatha s bilagi, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
4Rishi J P, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
5Dr. S A Mohan Krishna, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
6Amruth E*, Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5265-5268 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9490038620/2020©BEIESP | DOI: 10.35940/ijrte.F9490.038620

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Abstract: The work in this paper is focused , about the sugarcane harvesting machine, as India is considered as one of the higher consumers and producers of sugarcane and its by products and to due to huge population, there is a high demand of sugarcane and to meet the demand of population, large scale production has to be adopted, hence for farming and harvesting the sugarcane an automated, low cost harvester is necessary for the farmers to reduce the efforts of sugarcane harvesting and to increase the rate of sugar cane cutting. This machine will be helpful for the farmers having both small and big farms, the work on this paper was carried to identify the major options along with the opportunities and major chances for future enhancement in the field of agriculture industries.
Keywords: Sugarcane Harvesting, Automation, Agriculture, Harvesting, Cutters, Reduction Of Time, Manual Harvesting, Mechanized Harvesting.
Scope of the Article: Machine Learning.