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| Author(s): |
Patrícia Milan
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | Piracicaba. |
| Institution: | Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC) |
| Defense date: | 2008-02-20 |
| Examining board members: |
Jose Vicente Caixeta Filho;
Daniela Bacchi Bartholomeu;
Evaristo Marzabal Neves
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| Advisor: | Jose Vicente Caixeta Filho |
| Abstract | |
Coffee production is a historical and traditional agricultural activity in Brazil which is going through a reformulation due to new qualitative and social demands in the international market. The importance of quality to coffee resides in attending the consumer needs and in representing a specific factor for price determination. The physical and organaleptic characteristics of coffee drinks are influenced by pre and post-harvest management of the culture. In this context the demand for special coffee makes it necessary to adopt new technologies to the production systems, to manage the culture and its administration, which allow increase in productivity and a product with good quality. This elevation in complexity within the coffee chain increases the importance given to the farmer\'s administration decisions, stimulating him to search for new supporting tools for analysis. Mathematical modeling presents itself as an assisting tool to decision making with successful applications in agriculture. Therefore, this study aims to optimize the management of a coffee farm. A case study was conducted at the farm Santa Maria da Boa Vista, located in Cristais Paulista district in the State of São Paulo. The production data of the farm was used to elaborate and validate the mathematical model for special coffee production optimization. This linear programming multiobjective model with one multiobjective function, three sets of countable restrictions, seven sets of technical restrictions and two sets of endogenous variables presented itself as capable of assisting in the farms production planning, in the determination of the harvest sequencing and of the optimal volume of special coffee production. (AU) | |