Addressing Autocorrelation in Aquaculture Data: A Canonical Correlation Analysis of Water Quality and Shrimp Growth - Febriyani Eka Supriatin; Aulia Rahmawati; Muhammad Dailami (Statistika, 2025)
Abstract. This study evaluates the multivariate relationship between shrimp pond water quality and vannamei shrimp growth using Canonical Correlation Analysis (CCA) with autocorrelation handling. Observational data was collected from 13 ponds (3 visits/pond; N = 39) in Banyuwangi (DOC 32–50; Nov 2022–Jan 2023), encompassing pH, temperature (Temp), dissolved oxygen (DO), Average Body Weight (ABW), and Specific Growth Rate (SGR). Diagnosis indicated residual autocorrelation, so CCA inference was made robust through cluster bootstrap per pond (B = 2000), partial CCA controlling for Visit, and within-approach (demeaning per pond), as well as being triangulated with mixed-effects models and GEE AR(1). The first canonical root was significant (ρ1 = 0.648; Wilks’ Λ = 0.541; p = 0.0015) and stable based on bootstrap (median ρ1 = 0.692; 95% CI 0.340–0.894). Canonical loading shows Temp as the main contributor on the water quality side (supporting pH, low DO), while SGR dominates on the growth side and is in the opposite direction to ABW. The redundancy index indicates a moderate level of cross-set explanation (Y from X = 13.7%; X from Y = 36.8%). These findings underscore the importance of daily temperature stability (supported by pH stability) and DO monitoring in shrimp farm management.