Farmers production optimizing has a wide range of benefits such as saving money, increasing yields, reducing the amount of fertilizers and pesticides needed and minimizing environmental impacts. However, this requires a change in the mindset of agricultural players who need to move away from their traditional judgment-based approach toward more formal planning processes based on mathematical models, and also where farmers implement commercial solar systems.

 

This article aims to introduce the concept of optimization and demonstrate its application in determining which crops are most suitable for cultivation in smallholder farmers’ fields by using a multicriteria model. The model combines in the same utility function different conflicting criteria such as maximization of gross margin and minimization of fertilizers used. It is also able to take into account constraints imposed by land, labor, available capital, common agricultural policy and other factors.

 

The framework was applied in two provinces in South Africa: Limpopo and Free State, which are representative of the majority of the country’s farmers who grow summer grain crops (maize, soybean, sunflower and groundnuts). Data collection was conducted by means of a questionnaire that was based on a standard format. This ensured that all farmers had similar responses to the same questions, thus ensuring that a reliable and consistent result was obtained.

 

A total of 216 farmers were sampled and surveyed. The qualitative part of the research was carried out by conducting one-on-one interviews with farmers. These were geared towards obtaining information on the possible reasons that farmers took certain crop production decisions. This data was subsequently used to refine the answers of the mathematical modeling process.

 

Once the characterization phase had been completed, it was time to start identifying the crop options that would be most suitable for cultivation in the chosen farming areas. This was achieved by reducing the initial list of potential crops through an iterative process. The final list of crop options was based on the results of the economic analyses, associated social considerations and the farmers and other stakeholders’ priority goals.Click and go to website and discover more about farmers production optimizing.

 

A break-even price and yield analysis was then performed to identify the minimum output quantities required to cover attributable costs. A mathematical programming model was then built and solved to determine the optimum crop selections for each field. This method was found to be more efficient than the previous judgment-based method and to help farmers understand the underlying dynamics of their decision making. It also helped them to find new and efficient strategies for achieving their desired output quantity and profitability. This is important because, according to the Food and Agriculture Organization of the United Nations, the world’s population will increase by 60% by 2050, which will require more agricultural production.
For more understanding of this article, visit this link: https://en.wikipedia.org/Intensive farming.