Novel method for shark age estimation using near infrared spectroscopy

Abstract

Accurate age determination is an important component of assessing and managing fish populations, yet traditional ageing using growth bands is time-consuming and has limitations. In the present study, an alternative approach to shark age estimation using near infrared spectroscopy (NIRS) was investigated using two species. The ages of Sphyrna mokarran and Carcharhinus sorrah vertebrae that had been traditionally aged and validated were successfully predicted up to 10 years of age using NIRS. The correlations between the known ages of the vertebrae and their near infrared spectra were strong, with R 2 values of 0.89 and 0.84 for S. mokarran and C. sorrah respectively. The major advantage of the NIRS ageing approach was the rapid speed of age estimation, which could enable large numbers of sharks to be aged quickly. This would offer the fisheries management benefit of improving the reliability of age information for stock and risk assessments.

Classification of fish species from different ecosystems using the near infrared diffuse reflectance spectra of otoliths

“…The selected wavenumbers cover first overtones of N-H, O-H, and C-H bonds, stretching vibrations, and combinations. 37 Most variation in the spectral data was described by the first three principal components. PC1 (81.48% of captured variance) is the main direction along which the specimens separated ( Figure 5(a)).…”

“…31,32 Applications of NIR spectroscopy in fisheries science are currently limited, with five published studies having focused on biological structures such as otoliths of marine fishes [33][34][35] or shark vertebrae. 36,37 Traditional approaches to determine fish age from otoliths are often time-consuming and expensive, and can include observational subjectivity. In contrast, NIR spectroscopy methods have shown the potential to increase the efficiency and improve the repeatability of ageing studies.…”

Age estimation of barramundi (

“…Recently FT-NIR has shown promise in ageing otoliths of saddletail snapper (Lutjanus malabaricus; Wedding et al 2014), barramundi (Lates calcarifer) and snapper (Pagrus auratus; Robins et al 2015), eastern Bering Sea walleye pollock (Gadus chalcogrammus; Helser et al 2019) and red snapper (Lutjanus campechanus; Passerotti et al 2020a, b). FT-NIR has also been used to successfully age the vertebrae of hammerhead (Spyrna mokarran) and spot-tail sharks (Carcharhinus sorrah; Rigby et al 2016), and to age the dorsal fin spines, vertebrae and fin clips of deepwater sharks (Squalus magalops, Squalus montalbani; Rigby et al 2014). Although these studies relating NIR spectra to the traditionally derived age estimate or increment count of the otolith or vertebrae have shown potential, there are limitations preventing the broad uptake of FT-NIR.…”

Aging Pacific cod (Gadus macrocephalus) from otoliths using Fourier‐transformed near‐infrared spectroscopy

“…The goal to increase both the precision and cost efficiency of aging fish has led researchers to explore alternative age estimation techniques. In recent years, near-infrared spectroscopy (NIRs) has been explored as an alternative to microscopic age estimation to reduce cost, increase precision, and improve repeatability in estimating fish and elasmobranch ages (Wedding et al 2014, Rigby et al 2015, Passerotti et al 2020, Wright et al 2021. Applications of this technology are emerging in other ecological disciples including non-invasive gender identification in anurans (Vance et al 2014) and Chinook salmon (Hampton et al 2002) in addition to determination of dietary contents in fecal samples (Jean et al 2014).…”

“…In otoliths, these spectral signatures are a good proxy for fish age. Using multivariate calibration methods, such as partial least squares regression (PLSr), they can be related to the reference ages, which are estimated by the traditional microscopic approach (Wedding et al 2014, Rigby et al 2015, Passerotti et al 2020, Wright et al 2021. The model development process is complete when a predictive calibration model is evaluated against reference ages and tested by predicting a completely new set of representative unknown samples (external validation).…”