A new iPhone app called Food Additive Lens uses artificial intelligence to help consumers and professionals better understand ingredients and additives in food products.<\/p>\n
Yihang Feng \u201925 (CAHNR<\/a>) (ENGR), developed the app while pursuing a dual program as a PhD candidate in the Department of Nutritional Sciences and master\u2019s student in the Department of Computer Science.<\/p>\n Designed for iPhone 14 and newer devices, the free app allows users to scan ingredient labels and receive clear, science-based explanations about food additives within seconds, right from the grocery store aisle. The app is also available as a desktop version.<\/p>\n \u201cConsumers deserve access to clear, credible information about what\u2019s in their food,\u201d Feng says. \u201cFood Additive Lens makes that information available instantly \u2014 right when people need it most, while they\u2019re shopping.\u201d<\/p>\n While accurate information about food additives exists, it is often located in scientific books, articles, and regulatory databases that are difficult for consumers to access on-demand. This app bridges that gap by delivering expert-backed information instantly through a simple smartphone scan.<\/p>\n Following encouragement and coordination between his advisors in nutritional science (Yangchao Luo, associate professor) and computer science (Song Han, associate professor), Feng created the app during a summer research assistantship at the Institute for the Advancement of Food and Nutrition Sciences (IAFNS).<\/p>\n A journal publication on the development of the app and how it addresses intensifying consumer concerns was published in Digital Discovery.<\/a><\/p>\n Feng developed a novel three-agent AI system to analyze ingredient labels. After a user photographs an ingredient list, the system categorizes the food, identifies additives, explains what they are, and what role they play in food.<\/p>\n The explanations are written in plain language to help consumers make informed decisions. The app also can provide deeper technical and regulatory details for health professionals.<\/p>\n The food classification system was trained on more than 10,000 foods from the USDA\u2019s Global Branded Food Products Database. The app also includes information on more than 4,000 FDA-approved additives, drawing definitions and regulatory descriptions from the Code of Federal Regulations. Additional information comes from trusted sources such as the FDA\u2019s Substances Added to Foods Database.<\/p>\n While developing the app, Feng had his UConn advisors, lab mates, and students help test the beta version.<\/p>\n \u201cI changed a lot in the user interface design based on the feedback,\u201d Feng says.<\/p>\n Yi Wang \u201925 (CAHNR), who is now a postdoctoral researcher at the University of Maryland, worked alongside Feng in Luo\u2019s lab and supported the development of the app. She is taking over its future development.<\/p>\n \u201cIn the future, we would like to customize the food ingredient information to the consumers,\u201d Wang says. \u201cI want it to be able to give more precise suggestions to the individual health status or dietary restrictions.\u201d<\/p>\n This work relates to CAHNR\u2019s Strategic Vision area focused on\u00a0<\/em>Enhancing Health and Well-Being Locally, Nationally, and Globally.<\/em><\/a><\/p>\n