ArticleHeliyon2023
Farmers' response to maize production risks in Cameroon: An application of the criticality risk matrix model.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Agroecological drivers of aflatoxin contamination in maize-based systems: a review.Frontiers in plant science · 2026Review
- Multi-omics characterization of aflatoxigenic Aspergillus from grains and rhizosphere of maize across agroecological zones of Cameroon.Scientific reports · 2025Article
- Influence of Natural Risks and Non-Agricultural Income on Agricultural Trusteeship Decisions in Northeast China.Foods (Basel, Switzerland) · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Farmers' inability to successfully participate in the maize value chain due to the threats of some risk factors is one of the key reasons for rising food insecurity. This study analyses farmers' responses to risks involved in maize production in Cameroon. Data on maize production risks were collected from smallholder maize farmers operating in selected communities along the River Sanaga. The Criticality Risk Matrix model was employed to determine the severity of these risks based on their criticality and likelihood of occurrence. After deriving farmers' risk preferences from the categorization of their farm decisions, a Multinomial Logit Regression model was then used to investigate the extent to which risk severity influences farm decisions. Additionally, a Graded Response Model was utilized to predict farmers' risk responses by categorizing their probable patterns of action. The results revealed that production risks with fatal consequences such as pest invasion had a negative significant influence on-farm decisions and their perceived threats were more likely to provoke risk-averse responses. Less fatal risk threats such as fertilizer unavailability, poor farm infrastructure, labour shortage, and health risks were all significant and induced risk-averse responses from farmers. Furthermore, gender, experience and employment status also significantly influence farm decision-making. The farmers' response patterns presented on the Graded Response Model Characteristic Curves further indicated the willingness of farmers to continue farm activities despite perceived risks and the probability of engaging in diversification as an added measure to mitigate risks. We recommended that more effective measures for information dissemination on production risks as well as sustained Extension Service support to mitigate these risks be made available to farmers.
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