Fourier-transform near infrared spectroscopy (FT-NIRS) rapidly and non-destructively predicts daily age and growth in otoliths of juvenile red snapper Lutjanus campechanus (Poey, 1860)

Abstract

Fourier Transform Near Infrared Spectroscopy (FT-NIRS) has shown great promise as a rapid and non-destructive method for predicting age in years from a variety of ageing structures in fish. Herein we assess the utility of FT-NIRS to predict both daily age and otolith weight from whole otoliths of juvenile red snapper Lutjanus campechanus collected from the US Gulf of Mexico and southeastern US Atlantic Ocean. Spectral data from whole otoliths (n = 153) were collected with a FT-NIR spectrometer while manipulating otolith presentation with an external aperture to maximize signal to noise. Traditional daily age estimates and otolith weights were correlated to spectral data via partial least-squares regression to create age and otolith weight prediction models that were compared across aperture treatments and geographic region. FT-NIRS calibration models using apertured spectra were significantly better at predicting age than models using non-apertured spectra (model rank = 5 and 10, respectively) and yielded predicted age to within an average of six days relative to traditional estimates (R2 = 0.91, RMSECV = 6.08 days, bias = −0.04). Exponential growth models produced from FT-NIRS-predicted ages (Lt = 28.3*e0.01t) were not significantly different (likelihood ratio χ2 = 1.05, df = 2, p = 0.59) from those derived from traditional ages (Lt = 30.7*e0.009t). Additionally, FT-NIRS models were capable of predicting otolith weights that were not significantly different from direct measurements (t = 1.75, df = 147, p = 0.08). This study is the first to demonstrate successfully the potential of FT-NIRS to predict daily age and otolith weight in juvenile fishes, as well as the first to manipulate external apertures to optimize signal to noise. These findings support the potential for broad application of FT-NIRS in fisheries biology.