Farmers’ participation in agricultural projects has a direct bearing on technology awareness, adoption, livelihoods, environment, nutrition, poverty, performance of the agricultural sector and the macro economy. therefore sought to identify factors, which delimitate farmer’s participation in agricultural projects using the case of the Agricultural Value Chain Mentorship Project.. The study adopts the binary probit model and results of the analysis indicate that number of years in school, access to production credit and agricultural extension service are factors that significantly determine farmer’s participation in agricultural projects. It appears that farmer’s interest in agricultural projects can be permanently sustained by providing them with tangible benefits such as production credit and agricultural extension services. Developmental efforts that employ the top-bottom approach with minimal input and involvement of target beneficiaries have long been recognized as an unsustainable and poor pathway to beneficiary empowerment and development. Bottom-up approaches that view beneficiaries as partners, utilize local experience and endeavour to empower target beneficiary have been promoted in the past few decades recommended farming systems research and extension as a model for agricultural development. The farming systems and extension model recognizes the critical role farmers play in the success or failure of an agricultural project. It recognizes farmer’s involvement in identifying farming problems as well as solutions for sustainable development . Agricultural Research Institute (SARI) of the Council for Scientific and Industrial Research (CSIR) has adopted the concept of farming systems research. In fact, the bottom-up approach to development has arguably been adopted by almost all agricultural projects in Ghana. The emphasis has shifted from instructing farmers to collaborating and coaching farmers to participatory identify and solve local agricultural constraints. The agricultural sector is basically responsible for achieving the first millennium development goal of halving the proportion of the population suffering from hunger. According to the Ministry of Food and Agriculture.

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Thank you very much for the response Sir

The factors which affect the probability of being a member in a farmers' organisation can be better identified, if you have knowledge of the context and study area. These factors may be different from one country to another and even with different regions of specific country. Generally speaking, your dependent variable will be the probability of participation in a farmers' organisation/group. The independent variables may be land holding, education level, purpose of the group (marketing, extension, etc.), membership experience in farmers' groups in the past, off-farm job, distance from the central market, type of group (homogenous/heterogeneous; small/big, most farmers may prefer homogenous groups that deal with a single crop and those that have small number of members), etc. However, as I mentioned before it is necessary for you to collect some information through a preliminary visit or other sources about the groups you are going to study. This will put you in a better position to identify the most important explanatory variables for your Probit model. 

Hope this will help you.

Good Luck,

Najibullah Hassanzoy