Development of Near-Infrared Models for Selenium Content in the Pacific Oyster (Crassostrea gigas)

Near-infrared (NIR) spectroscopy is a vital non-destructive analytical tool in the food and aquaculture industries. This study pioneers the application of portable NIR spectrometers for evaluating selenium (Se) content in the Pacific oyster (Crassostrea gigas). We developed quantitative and qualitative models to predict selenium levels in oyster tissue, representing a novel application for monitoring trace elements in marine organisms. Quantitative models were developed using partial least squares (PLS) regression on spectra collected with two portable spectrometers (Micro NIR 1700, Micro PHAZIR RX) and a benchtop FT-NIR instrument, with validation via cross-validation and an independent set. Qualitative models were also constructed to categorize Se content into three levels: 0-1, 1-3, and >3 mg/kg. For quantitative analysis, the Micro NIR 1700 model performed robustly in external validation (RP = 0.932; RMSEP = 0.392; RPD = 2.46). The Micro PHAZIR RX model achieved the highest RC (0.988) and the lowest RMSEC (0.233), yet cross-validation indicated a potential risk of overfitting. In contrast, the FT-NIR instrument yielded the best external predictive ability for powdered samples (RP = 0.954, RPD = 2.60), highlighting its high precision under laboratory conditions. For qualitative discrimination, the Micro PHAZIR RX's classification module achieved a 100% correct recognition rate (AUC = 0.937). The models based on the Micro NIR 1700 and FT-NIR instruments showed cumulative contribution rates (CCR) of 98.61% and 97.59%, respectively, with high performance indices (PI) of 89.3 and 90.2, confirming their effective discrimination capability. The models established in this study enable the rapid, on-site detection of Se content in oyster samples, underscoring the significant potential of portable NIR spectroscopy for selenium analysis in shellfish.