No abstract

There is a paucity of age data for chondrichthyan fishes owing, in large part, to limitations in traditional age estimation methods. Fourier transform near-infrared (FT-NIR) spectroscopy has shown promise as an alternative, more efficient method for acquiring age data from chondrichthyans. However, studies are limited to sharks in the southern hemisphere. We explored FT-NIR spectroscopy to predict age for a batoid species in the northern hemisphere. The longnose skate (Raja rhina) is one of a small number of batoids for which annual band periodicity in vertebral centra has been validated, allowing for traditional age estimation and making it an ideal candidate for this study. We fit a multivariate partial least-square predictive model between FT-NIR spectra collected from vertebral centra and traditional age estimates, and tested model predictive skill by using external validation. Using FT-NIR spectroscopy, we were able to predict age for longnose skates between the ages of 1 and 14 years with precision and bias near equal to those of traditional methods in less than a quarter of the time. These results support potential for FT-NIR spectroscopy to increase the amount of age data available for assessments used to inform the conservation and management of this sensitive group of species.

No abstract

Fourier-transform near infrared (FT-NIR) spectroscopy of ovarian tissue was used to predict maturity status of fish species with variable reproductive strategies collected at limited time periods of their spawning cycle. Reference data were derived from histologically prepared tissue samples from four species: Pacific cod ( Gadus macrocephalus), walleye pollock ( Gadus chalcogrammus) , Greenland turbot ( Reinhardtius hippoglossoides) , and northern rockfish ( Sebastes polyspinis). Each data set was classified into reproductively immature (non-spawning) and reproductively mature (spawning-capable) categories. Principal component analysis of spectral data showed separation between ovarian tissues of spawning-capable and non-spawning females. Multivariate classification using partial least squares discriminant analysis indicated good discrimination based on spawning status with high predictive accuracy. Greenland turbot and northern rockfish showed clear distinction between ovaries of spawning-capable and non-spawning females and a model validation with 100% and 96.6% classification accuracy, respectively. Pacific cod and walleye pollock had more complicated reproductive patterns at time of collection and classification rates were still 96.6% and 92.1%. This study demonstrated the potential application of FT-NIR spectroscopy to predict spawning status from ovarian tissue even for species with complicated spawning patterns and for collections outside of the preferred spawning period. Future work may include the use of this technology to classify distinct oocyte development stages.