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?:abstract
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Recent application of Fourier transform near infra-red spectroscopy (FT-NIRS) to predict age in fish otoliths has gained attention among fisheries managers as a potential alternative to costly production ageing of managed species We assessed the age prediction capability of FT-NIRS scans in whole otoliths from red snapper, Lutjanus campechanus, collected from the US Gulf of Mexico and US Atlantic Ocean (South Atlantic) Otoliths were scanned with an FT-NIR spectrometer and resulting spectral signatures were regressed with traditionally estimated ages via partial least squares regression to produce calibration models, which were validated for predictive capability against test sets of otoliths Calibration models successfully predicted age with R2 ranging 0 94–0 95, mean squared error ≤1 8 years, and bias <0 02 years Percent agreement between FT-NIRS and traditional ages was lower than within-reader agreement for traditional estimates, but average percent error was similar and Kolmogorov–Smirnov tests were not significantly different (p ≥ 0 06) between traditional and FT-NIRS predicted ages for optimal calibration models Ages >31 years were not well predicted, possibly due to light attenuation in the thickest otoliths Our results suggest that FT-NIRS can improve efficiency in production ageing for fisheries management while maintaining data quality standards
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