Identification of living and dead microalgae cells with digital holography and verified in the East China Sea

The death of microalgae plays an important role in ocean energy flow and material circulation. The existing methods for the identification of dead and living microalgae cells all have defects such as the need for staining and pre-treatment. In this work, a label-free method to identify living and dead algae cells based on digital holography microscopy and machine learning was designed. At the stage of model training, ten feature vectors were extracted from the holograms, and twelve classification models of machine learning algorithm were trained. Compared with the staining method results, the accuracy of this method can reach 94.8%. At the stage of field verification, the death rate calculated by this method was also consistent with staining method. The method proposed in this paper provides a new method for the study of marine microalgae death which has the advantages of label-free, non-invasive, high accuracy and potential for in-situ application.

Automated summary

A label-free method was designed to identify living and dead algae cells with high accuracy, which has the advantages of being label-free, non-invasive, and potentially applicable in the field.