Machine learning algorithm review for the detection of formalin in fish

Formalin is a toxic chemical that is commonly used to preserve fish and prevent spoilage, but its use in food products is illegal in many countries. The detection of Formalin in fish is critical to ensure food safety and prevent health hazards for consumers. Artificial Intelligence (AI) can be used to detect Formalin in fish samples by analyzing various parameters such as color, texture, and chemical composition. AI-based detection methods can provide fast and accurate results compared to traditional laboratory methods, which can take several hours or days. Machine learning algorithms can be trained to recognize patterns and identify the presence of Formalin in fish samples with high accuracy. AI-based detection methods can also help identify other types of adulterants and contaminants in food products, improving overall food safety. Spectroscopy techniques, such as Fourier Transform Infrared Spectroscopy (FTIR) and Raman Spectroscopy, can be combined with AI algorithms to enhance the accuracy of Formalin detection in fish. Mobilebased applications that use AI algorithms can be developed to provide on- the-spot detection of Formalin in fish samples, making it easier for food inspectors and consumers to detect adulteration. AI-based detection methods can be scaled up to handle large volumes of fish samples, making it easier to monitor the quality of fish products in the market. The use of AI-based detection methods for Formalin in fish can help promote transparency and accountability in the food industry, ensuring that consumers have access to safe and healthy food products.