This study examines the determinants of plantain production and profitability in Bayelsa State, Nigeria, and their implications for human nutrition. Data were collected from plantain farmers using structured questionnaires and interviews with 120 farmers. The research used descriptive and inferential statistical methods, including multiple regression analysis, binary logit model, costs and returns, and profitability indices. The mean age of the farmers is 52.4 years, 81.7% are married, with a mean of six households and a mean farming experience of 19.52 years. Variance Inflating Factor and tolerance show that multicollinearity does not exist among the variables. The double-log functional model was chosen as the lead equation with an R² of 95.11%, where age (-0.1290), farm size (0.9151), market accessibility (-0.0073), and improved variety (0.0047) significantly determine plantain production. The high covariance percentage (0.97) of forecasting performance indicates a great capacity to reproduce real patterns. A profitability index (PI) of 45% and a return on investment (ROI) of 82% show that plantain farming is profitable. Furthermore, plantain has a high nutritional value for human health, although only 22% of people are aware of it in their diet. Farmers are unable to maximize their profits due to challenges such as limited market access, high input prices, and post-harvest losses. Plantain production has the potential to become a more profitable and sustainable sector, boosting economic growth, ensuring food security, and improving human nutrition in Bayelsa State and across Nigeria. To boost plantain production and nutrition, the research recommends investing in better road networks, storage facilities, market infrastructure, farmer education, and extension services.
This study examines the determinants of plantain production and profitability in Bayelsa State, Nigeria, and their implications for human nutrition. Data were collected from plantain farmers using structured questionnaires and interviews with 120 farmers. The research used descriptive and inferential statistical methods, including multiple regression analysis, binary logit model, costs and returns, and profitability indices. The mean age of the farmers is 52.4 years, 81.7% are married, with a mean of six households and a mean farming experience of 19.52 years. Variance Inflating Factor and tolerance show that multicollinearity does not exist among the variables. The double-log functional model was chosen as the lead equation with an R2 of 95.11%, where age, farm size, market accessibility, and improved variety significantly determine plantain production. The high covariance percentage (0.97) of forecasting performance indicates a great capacity to reproduce real patterns. The profitability index and return on investment show that plantain farming is profitable. Furthermore, plantain has a high nutritional value for human health, logistic regression shows that nutritional awareness of plantain is mainly driven by education and access to information. Farmers are unable to maximize their profits due to challenges such as limited market access, high input prices, and post-harvest losses. Plantain production has the potential to become a more profitable and sustainable sector, boosting economic growth, ensuring food security, and improving human nutrition in Bayelsa State and across Nigeria. To boost plantain production and nutrition, the research recommends investing in better road networks, storage facilities, market infrastructure, farmer education, and extension services.
Thanks as editorial and reviewers comments are awaited.
| Birincil Dil | İngilizce |
|---|---|
| Konular | Çiftlik İşletmeleri, Besinlerin Tarımsal Yönetimi |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Gönderilme Tarihi | 10 Nisan 2025 |
| Kabul Tarihi | 11 Nisan 2026 |
| Yayımlanma Tarihi | 28 Nisan 2026 |
| DOI | https://doi.org/10.15316/selcukjafsci.1669510 |
| IZ | https://izlik.org/JA37ZT47RG |
| Yayımlandığı Sayı | Yıl 2026 Cilt: 40 Sayı: 1 |
Selcuk Journal of Agriculture and Food Sciences Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.