Optimising maize production through farm machinery: An analysis of usage in Ghana

Maize is a major staple crop in Ghana, but low adoption of farm machinery has remained a limiting factor to its productivity. The paper assesses the perception, use and the factors that affect the use of farm machinery among the maize farmers in the Ejura-Sekyedumase municipality. A cross-sectional design was used to collect data through a structured interview from 384 farmers. The data were analysed using descriptive statistics, Relative Importance Index and binary probit regression model. From the results, only 33.64 percent of farmers use farm machinery, and most of them are still using traditional methods. Farmers with larger farm sizes and farmers who own land have better chances of adopting mechanisation, whereas age has a negative impact. Their main challenges are financial constraints, high fuel costs, mechanical failures, and the lack of skilled personnel. Farm machinery is primarily for land preparation, with limited adoption in planting and almost none in irrigation. The study indicates the need for support in terms of financial rewards, training programmes, as well as a shared pattern of machinery ownership to enhance uptake. This study is unique in that it concentrates on the local processes of agricultural mechanisation in the developing world. The results provide important information to policymakers and other stakeholders who would like to encourage sustainable farming practices and rural development.

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Publication Details

Journal
SVU-International Journal of Agricultural Sciences
Published
2025-10-26
DOI
https://doi.org/10.21608/svuijas.2025.418464.1507
Primary Topic
Agriculture and Farm Safety
Type
article
Field-Weighted Citation Impact
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article

Optimising maize production through farm machinery: An analysis of usage in Ghana

Mavis A Acheampong, Enoch Kwame Tham-Agyekum, Fred Ankuyi, Supernatural Ntem et al.
SVU-International Journal of Agricultural Sciences
Agriculture and Farm Safety
article

Optimising maize production through farm machinery: An analysis of usage in Ghana

Mavis A Acheampong, Enoch Kwame Tham-Agyekum, Fred Ankuyi, Supernatural Ntem, Miriam Joy Nhyira Botchway, Micheal Osei Mireku, James Kwesi Aganu
article en

Abstract

Maize is a major staple crop in Ghana, but low adoption of farm machinery has remained a limiting factor to its productivity. The paper assesses the perception, use and the factors that affect the use of farm machinery among the maize farmers in the Ejura-Sekyedumase municipality. A cross-sectional design was used to collect data through a structured interview from 384 farmers. The data were analysed using descriptive statistics, Relative Importance Index and binary probit regression model. From the results, only 33.64 percent of farmers use farm machinery, and most of them are still using traditional methods. Farmers with larger farm sizes and farmers who own land have better chances of adopting mechanisation, whereas age has a negative impact. Their main challenges are financial constraints, high fuel costs, mechanical failures, and the lack of skilled personnel. Farm machinery is primarily for land preparation, with limited adoption in planting and almost none in irrigation. The study indicates the need for support in terms of financial rewards, training programmes, as well as a shared pattern of machinery ownership to enhance uptake. This study is unique in that it concentrates on the local processes of agricultural mechanisation in the developing world. The results provide important information to policymakers and other stakeholders who would like to encourage sustainable farming practices and rural development.

SVU-International Journal of Agricultural SciencesVol. 0(0)
University of Cape Coast (GH), Kwame Nkrumah University of Science and Technology (GH), Agricultural & Applied Economics Association (US)
Openalex Percentile: Top 76%
Agriculture and Farm Safety
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Optimising maize production through farm machinery: An analysis of usage in Ghana — Mavis A Acheampong, Enoch Kwame Tham-Agyekum, et al. · SVU-International Journal of Agricultural Sciences (2025) | TGRS Research Map | TGRS