Isolation of Hydroxyapatite from Atlantic Salmon Processing Waste Using an Enzyme Cocktail

There is a desperate need for a solution to the ongoing waste management issues of the food processing industries. The demand for fish, including salmon, is higher than ever because of the growing global population and protein needs, however this results in large quantities of wasted by-products. This waste is problematic because it is potentially harmful to the environment and results in significant disposal costs for industries. The salmon frame (bones) is wasted once processed, however it is a potential feedstock for hydroxyapatite, a mineral for value-added applications. While other research has been done on accessing hydroxyapatite from animal wastes, these processes either use very high temperatures or chemicals that are more costly and hazardous for industrial purposes. In this study, we developed an enzymatic treatment using proteases and lipases simultaneously to clean the residual meat from salmon frames to isolate collagen-containing hydroxyapatite (sHAP) using Design of Experiment (DoE) under benign conditions. The variables were optimized using 2x3 and 2x4 factorial designs and it was determined by characterization techniques, weight loss calculations, and thermogravimetric analysis that the meat from the salmon frame was successfully hydrolyzed with 15 microliters/g Neutrase and 7.5 microliters/g Lipozyme CALB L in 40 degrees Celsius tap water for 6 h. We developed and propose a metric called Environment and Industry Hazard (EIH) for understanding the impact of such processing methods and compare the optimized procedure with existing techniques. The method reported herein is less impactful (environment, hazard, cost, carbon footprint) than others in the literature, as there are no solvents required, enzymes are easily disposed, and temperatures do not exceed 100 degrees Celsius during the entire process. Furthermore, we treated five salmon frames with the optimized conditions and determined it is possible to use this process on a larger scale.