Projection of fishmeal prices using ARIMA models based on the relationship between sea surface temperature and Engraulis ringens production
DOI:
https://doi.org/10.17268/agroind.sci.2025.03.12Keywords:
anchovy, time series, El Niño, landings, sustainabilityAbstract
Engraulis ringens is the main species used in the production of fishmeal and fish oil for the aquaculture and agri-food industries. The distribution, abundance, and production of this species are strongly influenced by sea surface temperature (SST), directly affecting the supply and demand of fishmeal and impacting its market value. However, few studies link SST with the final price of fishmeal as a predictive mechanism. Therefore, time series analysis and modeling are appropriate tools. The Box–Jenkins ARIMA model was applied to analyze univariate time series of temperature, E. ringens landings, and fishmeal price. Twenty ARIMA model interactions were performed for each variable relationship, yielding the best results over short periods. The SST-price correlation coefficient r = 0.533 at the 95% confidence level (p = 0.0004). The SST ARIMA model is an important tool for projecting fishmeal prices for up to three years, enabling the development of effective strategies to maintain the sustainability of fishery resources and ensure market stability.
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Copyright (c) 2025 Dennis Tomalá-Solano, Francisco Javier Montalvo-Márquez, Gabriela Revelo-Salgado
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