OPTIMIZATION OF PLANTING AREA FOR BROCCOLI, CABBAGE AND SQUASH IN THREE FARMS, CARTAGO, COSTA RICA

The annual per capita consumption of vegetables in Costa Rica increased 14 kilograms from 2002 to 2015, because of the adoption of low-calorie diets with high vitamin and nutritional intake. To supply the requirements of the population, it is necessary to develop models that optimize the use of prod...

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Bibliographic Details
Published in:International journal of food and agricultural economics 2023-07, Vol.11 (3), p.165-174
Main Authors: Thompson, Johanna Solorzano, Navarro, David Barboza, Molina, Javier Paniagua
Format: Article
Language:English
Subjects:
Agribusiness
Agricultural economics
agricultural markets
Agricultural production
Agriculture
Broccoli
Community/Rural/Urban Development
Costs
Crop Production/Industries
Crop rotation
Diversification
Economics
Farm Management
Farmers
Farms
food supply
Hypocaloric diet
Linear programming
Nutrient deficiency
Optimization
Optimization models
Profit maximization
Profitability
Profits
Research Methods/ Statistical Methods
Vegetables
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Summary:The annual per capita consumption of vegetables in Costa Rica increased 14 kilograms from 2002 to 2015, because of the adoption of low-calorie diets with high vitamin and nutritional intake. To supply the requirements of the population, it is necessary to develop models that optimize the use of productive resources. For this reason, the objective of this research is to develop a model to optimize the production area of broccoli, cabbage, and squash in three farms in Cartago, Costa Rica. Data were collected in the field during 2021 and the optimization model was solved by linear programming to maximize the profitability of each farm. The results showed that it is possible to make an efficient use of the available land maximizing the farmers' profit, although water and area limitations prevent covering all the market demand. It is concluded that farmers improve their business decisions based on models that optimize limited resources.
ISSN:2147-8988
2149-3766
DOI:10.22004/ag.econ.339052