Multi Criteria Approach to Determine the Suitability of Application of Motorcycle Drawn Potato Harvesters

Agricultural mechanisation is vital because it raises labour efficiency and enhances farm production per worker. However, not all fields are suitable for mechanisation. This study sought to determine the viability of introducing potato harvesting equipment drawn by motorcycles in Nyandarua County, Kenya. Soil analysis was done on samples from different parts of the county to understand the properties of soils that affect agricultural tool interaction and to study the movement of the digging part of the machines in the soil. With the help of various physical and mechanical soil tests, this study spatially determined suitable areas for potato mechanisation using Multi-Criteria Evaluation and Geographic Information System analysis. The criteria used in this analysis were soil, climate, and topography. The criteria were selected based on information available about potato mechanisation. The data from the criteria was analysed in the Quantum Geographic Information System environment. A map was generated in which the area was classified into four suitability levels for the operation of a potato harvester: Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (N) based on Food and Agriculture Organization guidelines. The Analytic Hierarchy Process decision-making tool was used to determine each criterion's deduced weights and associated influence. The weights were used as inputs in the weighted overlay analysis and final maps generated. This research aids in informed decision-making for agricultural mechanization in Nyandarua County, helping farmers and policymakers identify the most suitable regions for adopting this technology. By enhancing labour efficiency and farm productivity, the findings contribute to the overall improvement of the agricultural sector in the region, emphasizing the importance of considering multiple criteria when assessing the feasibility of introducing new farming equipment.

Authors

Institutions

Publication Details

Journal
Transactions on Engineering and Computing Sciences
Published
2025-02-17
DOI
https://doi.org/10.14738/tmlai.1301.18179
Primary Topic
Agricultural Engineering and Mechanization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi Criteria Approach to Determine the Suitability of Application of Motorcycle Drawn Potato Harvesters

Duncan Mbuge, Martin M. Nanje, Ayub Gitau
Transactions on Engineering and Computing Sciences
Agricultural Engineering and Mechanization
article

Multi Criteria Approach to Determine the Suitability of Application of Motorcycle Drawn Potato Harvesters

Duncan Mbuge, Martin M. Nanje, Ayub Gitau
article en

Abstract

Agricultural mechanisation is vital because it raises labour efficiency and enhances farm production per worker. However, not all fields are suitable for mechanisation. This study sought to determine the viability of introducing potato harvesting equipment drawn by motorcycles in Nyandarua County, Kenya. Soil analysis was done on samples from different parts of the county to understand the properties of soils that affect agricultural tool interaction and to study the movement of the digging part of the machines in the soil. With the help of various physical and mechanical soil tests, this study spatially determined suitable areas for potato mechanisation using Multi-Criteria Evaluation and Geographic Information System analysis. The criteria used in this analysis were soil, climate, and topography. The criteria were selected based on information available about potato mechanisation. The data from the criteria was analysed in the Quantum Geographic Information System environment. A map was generated in which the area was classified into four suitability levels for the operation of a potato harvester: Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (N) based on Food and Agriculture Organization guidelines. The Analytic Hierarchy Process decision-making tool was used to determine each criterion's deduced weights and associated influence. The weights were used as inputs in the weighted overlay analysis and final maps generated. This research aids in informed decision-making for agricultural mechanization in Nyandarua County, helping farmers and policymakers identify the most suitable regions for adopting this technology. By enhancing labour efficiency and farm productivity, the findings contribute to the overall improvement of the agricultural sector in the region, emphasizing the importance of considering multiple criteria when assessing the feasibility of introducing new farming equipment.

Transactions on Engineering and Computing SciencesVol. 13(01)
University of Nairobi (KE)
Openalex Percentile: Top 88%
Agricultural Engineering and Mechanization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.