Illegal, unreported, and unregulated (IUU) fishing poses significant threats, violating the rights of Indigenous Peoples to their traditional fishing grounds, endangering the food security of legitimate fishers and coastal communities, and facilitating human labor trafficking. Of particular concern are bluefin and yellowfin tuna, two highly valuable species greatly impacted by IUU fishing. These tuna are often subjected to tail, fin, and head removal, making visual identification challenging. Current identification methods involve costly and time-consuming processes, hindering swift action by authorities. To address this issue, a novel biological assay and portable heater/reader device are being developed to detect different tuna species. In this proof-of-concept study, we demonstrate the ability to sensitively and specifically detect Yellowfin tuna (Thunnus albacares) within just 30 minutes, from sample collection to results. In the process of conducting bioassays. I used a Python-based algorithm to detect positive samples while the samples were being reactive. This algorithm is based on the cv2 package, which can edit images. After converting the sample image to grayscale, a threshold can be used to eliminate noise in the image. The contours function in the cv2 package can identify all samples in the picture. Finally, the algorithm can determine which target samples are based on the pixel intensity of all samples. The optimized assay specifically detected yellowfin tuna within as little as 5 minutes, crossing a detectable threshold after 13-14 minutes. This proof-of-concept workflow highlights the potential for on-site yellowfin tuna species identification, critical for combating IUU fishing. Future steps involve developing dried reagents for easy on-site setup in low-resource settings and integrating the lighting system with the microcontroller within the portable device. In summary, this combination of assay and device offers a rapid and effective method to combat IUU fishing by identifying yellowfin tuna species on-site.