Fingerprinting Based on Spectral Reflectance and Chemometrics - an Analytical Approach Aimed at Combating the Illegal Trade of Stingray Meat in the Amazon.

The survival of Amazon stingrays is threatened due to excessive fishing and habitat degradation. To address this issue, this study developed a groundbreaking method to authenticate and differentiate Amazon stingray meats using a portable spectrophotometer and chemometrics. Samples were collected from various species, including an endangered one with a commercialization ban and no population reduction records. Principal Component Analysis (PCA), identified natural groupings based on the meat's commercial origin, while Partial Least Squares-Discriminant Analysis (PLS-DA), accurately discriminated the commercial and geographic origins with 100 % accuracy. Moreover, Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA), effectively distinguished Amazon stingray meat from other marketable species. This approach offers a rapid, precise, and non-destructive means for monitoring and controlling the illegal trade of these species, thereby supporting decision-making in the field and promoting the conservation and sustainability of freshwater stingrays in the Amazon region.