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Title: Determinants for adopting agricultural innovations by rice farmers in the north-west region of Cameroon
Authors: Gaston G. Ngochembo, Roland A. Balgah, Mathias F. Fonteh
Journal: International Journal of Agricultural Extension (IJAE)
Publisher: DATAPLUS (SMC- Private) Limited
Country: Pakistan
Year: 2022
Volume: 10
Issue: 2
Language: English
DOI: 10.33687/ijae.010.02.4083
Keywords: innovationFactorsRegressionAdoptionTechnologies
The importance of adopting agricultural innovations for farm productivity is well known. However, the rate of adoption is generally sub-optimal. This study investigates the determinants for adopting agricultural innovations by rice farmers in the North West Region of Cameroon. A multi-stage sampling technique was employed to identify and collect data from 800 rice farmers in Ngoketunjia division, the most important rice-producing area in Bamenda Highlands agro-ecological zone in that region of Cameroon. A structured and pretested questionnaire was used to catalogue technologies available to rice farmers and factors that might influence their adoption. Descriptive statistics were used to analyze the adoption of available technologies, and binary logistic regression to identify key determinants for their adoption. Rice farmers adopted eight of the twenty-one technologies identified. The results showed that ten of the thirty-three variables tested in the regression analysis significantly influenced the adoption of innovations by rice farmers. Household size, farm size, level of motivation, number of extension visits, and the ongoing socio-political crisis had statistically significant and positive influence while, type of labour use, qualified personnel or hired labour, innovation institutions, property rights, and social norms affected innovations adoption negatively. Based on these results, it has been recommended that major rice-producing institutions in the study area should consolidate the positive drivers while addressing the negative ones. Given that the regression model explained less than 50% of the factors influencing technology adoption in the area, future research should expand the list of independent variables so that generated results could be of greater relevance to policy-makers interested in improving rice production in the study area.
To investigate the determinants for adopting agricultural innovations by rice farmers in the North West Region of Cameroon.
A multi-stage sampling technique was employed to collect data from 800 rice farmers in Ngoketunjia division. A structured and pretested questionnaire was used. Descriptive statistics and binary logistic regression were used for data analysis.
graph TD
A[Data Collection via Questionnaire] --> B[Descriptive Statistics Analysis];
B --> C[Binary Logistic Regression Analysis];
C --> D[Identify Key Determinants];
D --> E[Formulate Recommendations];
The study highlights that while some factors like farm size, motivation, and household size positively influence adoption, others like the type of labor used, lack of innovation institutions, and property rights negatively impact it. The socio-political crisis, unexpectedly, showed a positive influence, potentially due to children providing labor due to school closures. The low adoption rate of many innovations suggests they might be too technical or costly for farmers.
Rice farmers adopted eight out of twenty-one identified technologies. Ten of the thirty-three variables tested significantly influenced adoption. Household size, farm size, level of motivation, number of extension visits, and the socio-political crisis had a positive influence. Type of labor use, innovation institutions, property rights, and social norms had a negative influence.
The adoption of agricultural innovations by rice farmers in Cameroon is suboptimal, with only a few low-tech innovations being widely adopted. Key drivers for adoption include economic factors (household and farm size), human-specific factors (motivation and extension services), and political factors (socio-political crisis). Addressing negative influences and leveraging positive ones is crucial for improving rice production.
* 800 rice farmers were sampled from Ngoketunjia division.
* Ten out of thirty-three tested variables significantly influenced innovation adoption.
* The regression model explained 48.1% of the factors influencing technology adoption.
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