Optimization of Operational Parameters on Harvesting Efficiency of Lathyrus Harvester Using Response Surface Methodology
H. S. Tuteja *
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering, IGKV Raipur, India.
R. K. Naik
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering, IGKV Raipur, India.
Shubham Pandey
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering, IGKV Raipur, India.
*Author to whom correspondence should be addressed.
Abstract
Lathyrus crop [Lathyrus sativus (L.)] or grass pea is the third most important cool-season pulse crop of India, occupying an area of 0.58 million ha with an annual production of 0.43 million tonnes. The productivity is fluctuates between 369 to 605kg/ha. Traditionally, farmers harvest lathyrus by either hand-pulling or using a sickle, methods that are labor-intensive, time-consuming, and cause significant discomfort to farmers. Till date, the traditional method (manually hand plucking/sickle) is the prevailing practice in Chhattisgarh. Due to rising labor costs, labor scarcity during peak seasons, and unpredictable weather, manual harvesting has become uneconomical. There is an urgent need of introducing modern practices for harvesting of the crop. Traditional testing and statistical analysis methods used in most existing studies are limited by complex test processes, their time-consuming nature, high costs, and poor prediction accuracy. To address these problems Response surface methodology (RSM) was used for optimizing the performance parameters. Effects of various parameters viz. reel speed, cutter bar speed and height of cut which is considered as the heart of harvesting machine was evaluated to get optimum harvesting efficiency of developed tractor operated lathyrus harvester. The optimum harvesting efficiency of 90% was found at 30 mm height of cut, 250 rpm cutter bar speed and 12.5 rpm respectively.
Keywords: Grass pea, harvesting efficiency, mechanization, response surface methodology