OvMeter: an automated 3D-integrated opto-electronic system for Ostreopsis cf. ovata bloom monitoring

Over the last decade, toxic events along the Mediterranean coast associated with exceptional harmful blooms of the dinoflagellate Ostreopsis cf. ovata have increased in frequency and distribution, causing not only the death of marine organisms and human health problems, but also economic loss on the tourism and aquaculture industries. In order to reduce the burden of routine algal counting, an innovative automated, low-cost, opto-electronic system called OvMeter was developed. It is able to speed up the monitoring process and therefore it enables early warning of incipient harmful algal blooms. An ad-hoc software tool provides automated cell recognition, counting and real-time calculation of the final algal concentration. The core of dinoflagellate recognition relies on a localization step which takes advantage of the synergistic exploitation of 2D bright-field and quantitative phase microscopy images, and a classification phase performed by a machine learning algorithm based on Boosted Trees approach. The architectural design of the OvMeter device is presented here, together with a performance evaluation on sea samples.