The management of plastic debris is a serious issue due to its durability. Unfortunately, million tons of plastic end up in the sea becoming one of the biggest current environmental problems. One way to monitor the amount of plastic in beaches is to collect samples and visually count and sort the plastic particles present in them. This is a very time-consuming task. In this work, we present a Computer Visionbased system which is able to automatically count and classify microplastic particles (1-5 mm) into five different visual classes. After cleaning a collected sample in the lab, the proposed system makes use of a pair of its images with different characteristics. The procedure includes a segmentation step, which is based on the Sauvola thresholding method, followed by a feature extraction and classification step. Different features and classifiers are evaluated as well as a deep learning approach. The system is tested on 12 different beach samples with a total of 2507 microplastic particles. The particles of each sample were manually counted and sorted by an expert. This data represents the ground truth, which is compared later with the results of the automatic processing proposals to evaluate their accuracy. The difference in the number of particles is 34 (1.4%) and the error in their classification is less than 4% for all types except for the line shapes particles. These results are obtained in less than half of the time needed by the human expert doing the same task manually. This implies that it is possible to process more than twice as many samples using the same time, allowing the biologists to monitor wider areas and more frequently than doing the process manually.

The presence of microplastics (MPs) in the marine environment is a concerning topic due to the ecotoxicological effects and possible seafood contamination. Data is needed to evaluate human exposure and assess risks, in the context of a healthy and beneficial seafood consumption. While microplastic ingestion by wild fish has been reported since the early 70's, farmed fish are rarely investigated. Here, for the first time the presence of microplastics in fish cultivated in the coastal water of Tenerife (Canary Island, Spain) was evaluated. From 83 examined individuals, 65% displayed microplastics in their gastrointestinal tracts, with averages between 0.6 ± 0.8 (SD) and 2.7 ± 1.85 (SD) particles per fish. The total number of microplastics detected was 119. Fibres (81%) and fragments (12%) were the predominant shapes. FTIR analysis showed that fibres were mostly composed by Cellulose (55%) and Nylon (27%), whereas fragments by PE (25%) and PP (25%).