Quantifying spawning biomass of commercially relevant fish species is important to generate fishing quotas. This will mostly rely on the annual or daily production of fish eggs. However, these have to be identified precisely to species level to obtain a reliable estimate of offspring production of the different species. Because morphological identification can be very difficult, recent developments are heading towards application of molecular tools. Methods such as COI barcoding have long handling times and cause high costs for single specimen identifications. In order to test MALDI-TOF MS, a rapid and cost-effective alternative for species identification, we identified fish eggs using COI barcoding and used the same specimens to set up a MALDI-TOF MS reference library. This library, constructed from two different MALDI-TOF MS instruments, was then used to identify unknown eggs from a different sampling occasion. By using a line of evidence from hierarchical clustering and different supervised identification approaches we obtained concordant species identifications for 97.5% of the unknown fish eggs, proving MALDI-TOF MS a good tool for rapid species level identification of fish eggs. At the same time we point out the necessity of adjusting identification scores of supervised methods for identification to optimize identification success.

Significance

Fish products are commercially highly important and many societies rely on them as a major food resource. Over many decades stocks of various relevant fish species have been reduced due to unregulated overfishing. Nowadays, to avoid overfishing and threatening of important fish species, fish stocks are regularly monitored. One component of this monitoring is the monitoring of spawning stock sizes. Whereas this is highly dependent on correct species identification of fish eggs, morphological identification is difficult because of lack of morphological features.