Article citationsMore>>

Duguma, B. (2022) Farmers’ Perceptions of Major Challenges to Smallholder Dairy Farming in Selected Towns of Jimma Zone, Oromia Regional State, Ethiopia: Possible Influences, Impacts, Coping Strategies and Support Required. Heliyon, 8, e09581.
https://doi.org/10.1016/j.heliyon.2022.e09581

has been cited by the following article:

• TITLE: Resource Availability and Factors Influencing Farmers’ Adoption of Modern Rice Technologies in Bonthe District Sierra Leone

  AUTHORS: Prince Tongor Mabey, Patrick Amara Ngaojia, Daphne Sia Shirley Roy-Johnson, Jonathan Sahr Kpakima, Jusufu Abdulai, Osman Musa Kalokoh, Musu Monica Lansana, Ishmail Kakpindi Kaifala, Michaelson Maada Mawondeh, Saidu Bah, Lansana Musa

  KEYWORDS: Modern Rice Technologies, Technology Adoption, Resource Availability, Logistic Regression, Pearson Chi-Square, Kendall’s Coefficient of Concordance, Smallholder Farmers, Sierra Leone

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.16 No.9, September 24, 2026

  ABSTRACT: Modern rice technologies have the potential to improve productivity and food security among smallholder farmers; however, adoption remains constrained by limited resources and multiple socio-economic factors. This study assessed resource availability and the factors influencing farmers’ adoption of modern rice technologies in Bonthe District, Sierra Leone. A quantitative cross-sectional survey design was employed among 325 randomly selected smallholder rice farmers drawn through a multistage sampling procedure from five major rice-producing sections (Borlleh, Madina, Ngepehun, Sogballeh, and Torma). Primary data were collected in February 2026 using a structured interviewer-administered questionnaire. Descriptive statistics summarized respondents’ characteristics and resource availability, while Pearson’s Chi-square (χ2) test examined associations between categorical variables. Binary logistic regression identified significant predictors of technology adoption, and Kendall’s Coefficient of Concordance (W) assessed agreement in ranking adoption determinants. The findings revealed that farmers generally had limited access to irrigation, agricultural credit, mechanization, and timely farm inputs despite relatively good access to improved rice seed. Logistic regression showed that irrigation availability was the strongest resource-related predictor of adoption (Adjusted OR = 6.23, p χ2 analysis identified significant associations between resource availability and technology adoption (p χ2 = 29.20, p