Mathematical Modeling for Predicting Crop Yield and Production Cost of Oreochromis niloticus under Different Climatic Conditions

• Grant number: 24/10902-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2024
• End date: September 30, 2025
• Field of knowledge: Agronomical Sciences - Fishery Resources and Fishery Engineering - Aquaculture
• Principal Investigator: Guilherme Wolff Bueno
• Grantee: Henrique Baccarin Dissordi
• Host Institution: Faculdade de Ciências Agrárias. Universidade Estadual Paulista (UNESP). Campus do Vale do Ribeira. Registro , SP, Brazil
• Associated research grant: 22/02756-4 - BLASp4: IoT platform for predicting bioeconomic carry capacity and ecosystem aquaculture services under different climate, zootechnical and financial scenarios of fish farms in neotropical environment, AP.PNGP.PI

Abstract

Numerous operational factors can impact the management of aquaculture businesses. Notably, the barriers to using technologies that promote more agile processes in the fish value chain are significant. Thus, applying mathematical models for predicting harvests has become one of the main approaches to assist managers in their financial operations and governance of their enterprises. In this context, the project will apply mathematical modeling tools for predicting body growth and bioeconomic analysis to assist in the financial risk analysis and economic optimization of a commercial enterprise that produces O. niloticus in a cage farm at the Chavantes Hydroelectric Plant reservoir in São Paulo. A historical data series (n=1.800) with information on water quality, zootechnical performance, and production costs will be used. Concurrently, 35 field batches will be monitored during a production cycle to collect the same information obtained in the historical series. Thermal Growth Coefficient (TGC) modeling will be applied to predict weight and slaughter time, integrating economic modeling to define the costs and profitability of the enterprise. These tools will enable the optimization of aquaculture processes and assist in the financial and economic risk analysis of the activity for managers and investors in the sector.