I am proposing an innovative project that leverages advanced image processing and machine learning techniques to assess the freshness of commercially sold fish like trout, sea bass, and sea bream. Throughout my research, I have amassed a substantial collection of fish photographs, taken throughout their shelf life, alongside comprehensive microbiological and chemical analyses, including total volatile basic nitrogen levels. This work has also been the subject of a master's thesis by one of my students.

Objective: The aim is to develop a sophisticated image analysis system using machine learning. This system will be trained on the extensive image dataset I have compiled, enabling it to accurately determine the fish's freshness and specific shelf life stage. The ultimate goal is to translate this technology into a user-friendly mobile application.

Seeking Partnerships: I am seeking partners with expertise in machine learning and mobile app development, as my research has primarily focused on the laboratory aspect of fish shelf life, including microbiological, chemical, and sensory analysis. Although I have extensive research experience and can contribute further to this aspect, I need technical assistance for the machine learning and app development components.

Invitation for Collaboration: I invite interested entities, including private companies, universities, and institutions, to collaborate on this project. I have not led international projects before, so partnering would be a greatly valued opportunity. Please get in touch with me to explore this exciting venture.

The Use of Color to Determine Fish Freshness: European Seabass (Dicentrarchus labrax)

Erdag M., Ayvaz Z.

JOURNAL OF AQUATIC FOOD PRODUCT TECHNOLOGY , vol.30, no.7, pp.847-867, 2021

 Fisheries and Food

 Agrifood

 Food Safety