Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2764

Full Length Research Paper

Multiple attribute decision making for selection of mechanical cotton harvester

S. S. Kohli1, Manjeet Singh2, Karun Sharma2* and Gayatri Kansal3
1Department of Science and Technology (DST), New Delhi, India. 2Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana-141004, India. 3Indira Gandhi National Open University, IGNOU Road, Maidangarhi, New Delhi, India.
Email: [email protected]

  •  Accepted: 11 December 2013
  •  Published: 25 December 2013


A numerical method called Multiple Attribute Decision Making (MADM) has been used for rational selection of a cotton harvester out of a finite number of cotton harvesters available the world over. In India, efforts are being made to design and develop a commercial cotton harvester to harvest selected cotton varieties sown by adopting common agronomic practices locally for cotton cultivation. The crop parameters for two different planting systems (existing planting system prevalent in India and experimental high density planting system) together with machine performance attributes of mechanical cotton harvesters using different types of mechanisms have been reviewed in this paper. Suitable cotton harvester was selected for both type of planting systems on the basis of attribute coding system. The main crop parameters which affect the performance of a cotton harvester like row spacing, plant height, plant population and crop yield were selected for the study. Machine performance attributes selected were picking efficiency, trash content, gin turnout, field capacity and field losses. Equal weightage was given to all machine attributes like picking efficiency, losses, trash content, gin turnout and field capacity of the cotton harvester. The spindle type cotton picker was best suited to the existing cotton planting system of India. Based upon TOPSIS method, if relative ranking was given to the pertinent attributes then the best mechanical cotton harvester for existing planting system was brush and paddle type cotton stripper. For high density planting system, if equal importance was given to all machine attributes of the cotton harvester, the finger type cotton stripper and spindle type cotton picker were best suited. On the basis of TOPSIS method, if the relative importance of pertinent attributes was considered the best mechanical cotton harvester for high density planting system was finger type cotton stripper.

Key words: Attribute coding, Multiple Attribute Decision Making (MADM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), cotton harvester, crop attributes, machine performance attributes.