DESCRIPTIVE ANALYSIS OF CARP PRODUCTION (Cyprinus Carpio) IN BRAZIL: REGIONAL CONCENTRATION, VALUATION, AND LIMITS OF FORECASTING WITH SHORT TIME SERIES

Keywords: Machine learning, fish farming, economics

Abstract

This study uses a 10-year time series (2013–2023) to analyze the dynamics of carp (Cyprinus carpio) production and valuation in Brazil. Data processing revealed a strong production concentration in the Southern Region (over 95% of total volume), indicating a pattern of regional specialization associated with potential mechanisms of structural dependence (path dependence). The price series (R$/kg) exhibited non-stationary behavior and an upward trend, suggesting the influence of production costs and the role of higher value-added niche markets. Predictive modeling, based on ARIMA ($p, d, q$) and ETS models, was employed in an exploratory manner. Although the ARIMA model showed lower forecast error (RMSE: 818,393.5 kg) compared to ETS, the results should be interpreted with caution due to the limited length of the time series. The projections displayed an approximately constant pattern, which is consistent with informational constraints typical of short annual series, and therefore do not provide robust evidence of structural stagnation or sector maturity. The findings highlight the relevance of regional production concentration, the dynamics of economic valorization, and the need to expand and integrate data sources to support more robust predictive analyses. From a strategic perspective, opportunities are identified in value addition, production diversification, and the strengthening of specific niches, such as the ornamental carp (Koi) market.

Author Biography

Murilo Henrique Tank Fortunato, MBA USP/ESALQ

Biólogo, mestre em Ciências Ambientais e doutor em Agricultura (Aquicultura).

Published
2026-07-28
How to Cite
Tank Fortunato, M. H. (2026). DESCRIPTIVE ANALYSIS OF CARP PRODUCTION (Cyprinus Carpio) IN BRAZIL: REGIONAL CONCENTRATION, VALUATION, AND LIMITS OF FORECASTING WITH SHORT TIME SERIES. AGRI-ENVIRONMENTAL SCIENCES, 12(1), 10. https://doi.org/10.36725/agries.v12i1.11848