We investigated the use of Fourier transform near infrared spectroscopy (FT-NIRS), which is a method of measuring light absorbance signatures, to derive ages from eastern Bering Sea walleye pollock (Gadus chalcogrammus) otoliths. This approach is based on a predictive model between near infrared spectra in the otolith and fish age, which is calibrated and validated. The advantage of FT-NIRS over traditional methods is the speed and repeatability with which age estimates are generated. The application of FT-NIRS to walleye pollock otoliths yielded r2 values between 0.91 and 0.95 for the calibration models and good validation performance (between 0.82 and 0.93). This approach can be expected to predict fish age within ±1.0 year of age 67% of the time. When comparing approaches, the FT-NIRS had as good or slightly better precision (75% agreement) than the traditional ageing (66% agreement) and showed little or no bias at age before 12 years of age. Once the predictive FT-NIR model is calibrated and validated, age estimates using FT-NIRS can be done at 10 times the rate compared to traditional methods.
For decades, age‐structured stock assessments have been a key component to managing fishery resources worldwide. Fisheries management systems have been under increasing demand to generate a greater volume and quality of age estimates. Traditional aging techniques, which require physical preparation followed by microscopic examination of fish otoliths, are labor‐intensive, expensive, and inherently subjective among individual analysts, making repeatability and precision a challenge. Here we investigated an innovative approach to aging fish from their otoliths using Fourier‐transformed near‐infrared spectroscopy and partial least squares regression models. Models were fit to and validated on spectra and used to microscopically estimate ages of Pacific cod from three years of fishery‐independent otolith data out of the Bering sea. Calibrated and validated models for each year, as well as on an ensemble of the three years, yielded high precision for the multiyear model (R2 = 0.869, RMSE = 0.614, PA = 63%, CV = 7.412), and independent year models (R2 = 0.844–0.891, RMSE = 0.555–0.615, PA = 65%, CV = 6.313–6.775). These metrics of model performance were highly comparable to precision from the traditional microscopic aging approach (R2 = 0.763–0.869, RMSE = 0.639–0.737, PA = 63%–70%, CV = 5.671–6.698). In all cases, a two‐sided Kolmogorov–Smirnov test showed no significant difference between reference and model estimated age distributions. Our results illustrate how Fourier‐transformed near‐infrared spectroscopy can be utilized on otoliths to predict age estimates with substantially greater efficiency, good precision, high repeatability, and no loss in data integrity compared to the traditional microscopic method for aging Pacific cod.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.