Adoption of agricultural innovations in risky environment: the case of corn producers in the west of Cameroon

Abstract

The use of modern agricultural inputs has been cited as a major factor for increasing productivity in most sub-Saharan African countries. A wide range of variables influence the adoption of such inputs. It is important to identify these variables in order to ensure the implementation of more effective programmes to promote the use of modern inputs. This article examines the determinants of adoption of three new agricultural technologies (improved maize seeds, inorganic fertiliser and pesticide) by corn producers in the west of Cameroon. Rather than the univariate probit model which is commonly used, the multivariate probit model is employed to take account of the correlation between the disturbances of the three adoption models. The results indicate that the decision to adopt agricultural innovations is significantly influenced by farmers' education, income and risk perception as well as farm size. Therefore, policies aimed at setting up sustainable risk management markets, increasing the level of education of farmers and their access to credit could greatly promote the adoption of agricultural innovations by farmers of Cameroon in general and in the western region in particular.

Smallholder Palm Oil Production Sector in African Countries: State of the Art, Practices, Constraints, and Opportunities in Cameroon

“…Most smallholders in the oil palm sector in Cameroon have over 21 years of farming experience, which is correlated with their appropriate variety selection and knowledge of key parameters, such as when to plant in new fields, the economic lifespan of the plantations, pruning frequencies, and perception of farm-related risks among other technical considerations raised. Fosso and Nanfosso [9] have shown that farmers' age, education, and farm sizes are key determinants in the adoption of agricultural innovations in the West Region of Cameroon, which is consistent with the findings of Mbosso et al [10] in Southern Cameroon. Indeed, factor analyses of the correlation matrix in terms of oil palm production characteristics in the study sites indicates that the farmers' level of education, level of experience in the farm, and farmers' age are key determinants of access to farm finances, production per season, and labour safety in the plantations.…”

“…For instance, the understanding of demographic characteristics will provide information on how to direct innovations in agriculture. It has been shown that demographic characteristics play a key role in technology adoption in the corn sector [9] and the Ricinodendron heudelotii sector in South Cameroon [10]. How these characteristics play out in the oil palm sector in Cameroon is yet to be studied.…”

Promoting value addition among farmers in the cassava food value chain in Nigeria

“…In general, the recent extant studies suggest that gender (male), age, education, household size, farm size, off-farm income, access to extension services, access to credit and farmer association exert positive effects on the adoption of agricultural innovations such as inorganic fertiliser, improved crop variety and pesticides in some African countries, notably Nigeria, DR Congo, Uganda, Ghana, Cameroon and Ethiopia (Abdoulaye et al , 2014, 2015; Lambrecht et al , 2014; Obisesan, 2014; Afolami et al , 2015; Abate et al , 2016; Donkor et al , 2016; Mekonnen and Gerber, 2016; Abay et al , 2017; Alirah et al , 2018). For instance, studies have shown that male farmers are associated with higher adoption rates of agricultural innovations (namely, irrigation, pesticides and inorganic fertiliser) than their female counterparts in Nigeria, Ethiopia, Cameroon and Ghana (Obisesan, 2014; Donkor et al , 2016; Fosso and Nanfosso, 2016; Abay et al , 2017). In these African countries, male farmers are observed to own larger farms and have better access to support services such as extension services, credit and training than female farmers, thereby empowering male farmers to increase their adoption of agricultural innovations.…”

Analysis on outsourcing service behavior of rice pest and disease control based on Heckman selection model—A case study of ten counties in Fujian Province

“…Previous studies have shown that agricultural technology decision-making adoption may be affected by factors such as farmers' endowment, labor force characteristics and external environment [35,36], In particular, the labor productivity gap of specialized suppliers will affect the probability of farmers participating in agricultural production outsourcing services [37]. At the same time, the characteristics of labor force and the degree of land fragmentation are also the key factors affecting the socialized service of agricultural machinery [38].…”