Rapid Quantification of Fatty Acids in Fish Eggs Through Raman Spectroscopy

ABSTRACT In aquaculture, omega‐3 fatty acids (FAs) are essential for fish health and growth during early development, making them important indicators of egg quality. The current standard for measuring FAs relies on analytical instruments that require complex sample preparation and long analysis times. In contrast, Raman spectroscopy can obtain the chemical fingerprint of an egg sample within seconds. In this study, Raman spectroscopy, coupled with chemometrics, was used to develop a rapid, in situ method for predicting FA composition in fish eggs. Raman spectra and reference FA data were collected from California yellowtail ( Seriola dorsalis ) egg samples. From this dataset, a partial least squares model was developed to predict eicosapentaenoic acid (EPA, 20:5n3) and docosahexaenoic acid (DHA, C22:6n3). Our model achieved strong predictive power and high accuracy ( R 2 CV = 0.91, RMSE CV = 2.5%), offering a practical and cost‐effective method for assessing egg FA profiles in aquaculture hatcheries.