Abstract
The low yield of the agricultural sector in Sub-Saharan Africa (SSA) is not solely due to the type of agriculture (mainly traditional), but also to the crop selection process which is typically based on impressions or past experience. This approach cannot always ensure an optimal crop selection ev
Highlights
A large majority of the population in Sub-Saharan Africa (SSA) especially those living in rural areas, relies on agriculture for securing their source of revenue and fulfilling their basic needs [1]
The evaluation of the net revenue improvement was achieved by comparing the result of the system with what is usually done in some regions in Cameroon
We considered that farmer owns some resources taken into account during the net revenue optimization
Summary
A large majority of the population in Sub-Saharan Africa (SSA) especially those living in rural areas, relies on agriculture for securing their source of revenue and fulfilling their basic needs [1]. Even if recently crop selection has been extended to a multi-period LP problem [4,11], it remains that the initial set of crops is known and supposed to be cultivable, at different periods, on the given plot. The proposed approach is based on the combination of an expert system and linear programming: the expert system determines the initial set of crops based on time and environmental constraints, while linear programming is used to determine the appropriate mix of crops that will maximize the farmer’s revenue, taking available equipment, budget, acreage, and the other related operating materials and costs into account. This paper ends with a conclusion and possible directions for future developments
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