Skip to content
Research Article Open access CC BY 4.0

Impact of Improved Cassava Technology Adoption on Farmers Output in Benue State, Nigeria

Juliet Ogadinma Onyemma, Mark Tokula, Koko Michael Tertsea, Nwafor Solomon Chimela

Journal of Applied Life Sciences International · pp. 1–10 · Published 7 Aug 2019

10.9734/jalsi/2019/v21i430112

Abstract

Aims: The aim of the study was to ascertain the impact of the adoption of improved cassava technology on the output of farmers in Benue state, Nigeria. Study Design: The study used Survey design. Place and Duration of Study: The study was carried out in Benue State, between November 2018 and May 2019. Methodology: Cluster and simple random sampling techniques were used to select 366 respondents for the study. Primary data were collected using Semi-structured questionnaire. Objective 1 was achieved using descriptive statistics such as percentages, frequencies and means while Objective 2 was achieved using multiple regression model. Results: The findings showed that the adoption of improved cassava technologies influenced the farmers in a number of ways which included increased farmers income (56%:  2.10), acquired new skills (75%:); increased output (76%: ); expanded production (67%: ); ensured more food at home (food security) ( 85%: ); and increased well being of adopters (80%: ). The result also revealed that improved cassava technologies adoption have significant impact on farmers output in Benue State was accepted. This was indicated by F-stat value of 33.42 and F-probe value of 0.000 of less than 0.05, indicating that the estimated regression model adopted in this study was statistically significant at 1%. The R2 value of 0.75 implied that 75% of dependent variable (farmers output) was explained by the independent variables (TSM0505, TSM0581, TSM0572, TMS011368, TMS961632, TMS920326 TME 419, NR8082). Conclusion: Thus it was concluded that improved cassava technologies adoption have significant impact on farmers output in Benue State The study thus recommend that Extension agencies should ensure that improved cassava technologies are accessible by farmers and that farmers acquire the necessary knowledge and skills in using such technologies. This will ensure high adoption and high impact as well.

Impact improved cassava technologies adoption output.

References (11)

  1. 1 Understanding and promoting adoption of conservation practices by rural landholders [DOI]
  2. 2 The adoption of agricultural innovations [DOI]
  3. 3 Determinants of agricultural best management practice adoption: Evidence from the literature [DOI]
  4. 4 Agricultural Technology, Productivity, and Poverty in Madagascar [DOI]
  5. 5 Agricultural Technology Adoption, Seed Access Constraints and Commercialization in Ethiopia [DOI]
  6. 6 Economics of Agricultural Production and Resource Use [DOI]
  7. 7 Adoption of Improved Cassava Varieties and Its Welfare Impact on Rural Farming Households in Edo State, Nigeria [DOI]
  8. 8 The contribution of IITA-improved cassava to food security in sub-Saharan Africa: an impact study.
  9. 9 Adoption of Improved Cassava Varieties in Ghana [DOI]
  10. 10 Determinants of adoption of upland rice varieties in Fogera district, South Gondar, Ethiopia [DOI]
  11. 11 Prospects for cassava breeding in Sub-Saharan Africa in the next decade

Cited by 5

Farmer typology and adoption of improved cassava production technologies in the Eastern Democratic Republic of the Congo

Nsharwasi Léon Nabahungu, Jackson Cirhuza Mirali, Guy Simbeko · CABI Agriculture and Bioscience · 2025

Showing 2 of 5 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

53

Page views

0

PDF downloads

29

Outbound clicks

5

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.