Researchers Unveil Fascinating AI-Powered Solution to Combat Food Rancidity
(Photo : Photo Giorgio Trovato on Unsplash) Chemists discover AI’s potential to combat food rancidity predicting effective antioxidant combinations, revolutionizing food preservation.
In a major breakthrough, a team of chemists has made a significant discovery in their quest to extend the shelf life of food and counteract the problem of rancidity. Their groundbreaking study, published in the Journal of Agricultural and Food Chemistry, highlights the remarkable potential of artificial intelligence (AI) in preserving the freshness of food products that contain oils and fats.
Rancidity occurs when food is exposed to air for a prolonged period, a process known as oxidation. According to a report from Phys.org, this deterioration is particularly common in lipids, which include fats and oils. The process of oxidation can be accelerated heat and UV light, leading to the formation of ketones, aldehydes, and fatty acids, which give rancid foods their distinct unpleasant odor.
Antioxidants, both natural and synthetic, are nature’s defense against oxidation and play a crucial role in maintaining food quality. However, determining the right combination of antioxidants and their precise amounts is a complex task. Adding antioxidants randomly can result in diminished protective effects or even antagonism.
Finding the optimal combinations for specific types of food requires numerous experiments, specialized personnel, and increased production costs, making it a challenging and time-consuming process.
This is where AI comes into play. AI systems, like ChatGPT, have the ability to process large datasets, identify patterns, and generate valuable insights. The research team set out to teach an AI tool how to discover novel antioxidant combinations that can effectively combat food rancidity. They selected an AI model capable of working with textual representations that describe the chemical structure of each antioxidant.
To train the AI, the scientists initially provided it with a database of around one million chemical reactions, teaching it important chemistry concepts such as molecular interactions. As the AI gained a better understanding of general chemical patterns, it was further refined using a database of over 1,100 antioxidant mixtures described in the research literature.
The AI quickly became proficient at predicting the outcomes of combining two or three antioxidants, aligning with the descriptions in the literature 90% of the time. However, real-world lab experiments did not always match the AI’s predictions, highlighting the challenges in translating computer-generated results to the laboratory.
The research team continued to improve the AI model feeding it new data. By adding approximately 200 examples from their lab experiments, the AI was able to accurately predict the effects of antioxidant combinations with minimal deviation from the actual outcomes.
The implications of this AI-powered approach are vast. It can assist scientists in developing more effective methods for preserving food determining the best antioxidant combinations for specific food products, providing valuable assistance in the lab.
As this technology continues to evolve, it holds tremendous potential in revolutionizing the food preservation industry. Stay tuned for more updates on this fascinating development.
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