Prediction and Analysis of Sturgeon Aquaculture Production in Guizhou Province Based on Grey System Model

In this study, grey system theory is applied through the implementation of GM(1,1) modelling and Grey Relational Analysis (GRA) to forecast and evaluate sturgeon aquaculture production dynamics in Guizhou Province. The results demonstrate a marked temporal dependency in predictive efficacy, with GM(1,1) exhibiting a superior short-term forecasting performance that progressively diminishes with temporal extension. Utilizing 2018–2022 observational data, the GM(1,1) framework achieved Grade 2 precision (mean absolute percentage error, MAPE = 4.172%; 1% < ∆ k ¯ ≤ 5%), projecting sustained annual production growth. The decade-long forecast (2023–2032) yielded the following production estimates (×10 3 tons): 32.3, 39.1, 47.3, 57.2, 69.2, 83.7, 101.2, 122.4, 148.1, and 179.2. GRA identified three principal determinants: the aquatic seed production value ( X 9 , r = 0.8336), freshwater fishery output ( X 2 , r = 0.8019), and per capita fisher income ( X 5 , r = 0.8003). Furthermore, technological promotion funding ( X 6 ) and fishery workforce parameters ( X 4 ), while demonstrating weaker correlations (r < 0.75), maintain critical roles in technological advancement and labour competency enhancement. This methodological framework provides empirical support for sustainable development strategies in Guizhou’s sturgeon aquaculture sector, emphasizing the necessity of temporal-scale considerations and multifactorial optimization in production management.