APPLICATION OF AI AND MACHINE LEARNING TO ANALYZE PROTEIN CONTENT IN U.S. COMMERCIAL BABY FOODS.

Abstract

Proteins are essential macronutrients that support the growth, development, and maintenance of tissues in children. Nutrient requirements vary with age, weight, and physiological needs, making age-specific dietary planning critical. Adequate protein intake promotes both physical growth and cognitive development, while diverse sources such as lean meats, dairy, legumes, and nuts help meet varying nutritional needs and encourage lifelong healthy eating habits. This study analyzed a nutritional dataset of 244 baby foods using artificial intelligence (AI) and machine learning to assess protein content, categorizing items into three groups based on protein content: low (0.0-5.9 g/day), moderate (6.0-10.9 g/day), and high (11.0-15.0 g/day). The majority (n = 202) fell into the low-protein range, followed by 22 in the moderate range and 20 in the high range. Age-specific protein requirements, expressed in grams per kilogram of body weight (g/kg), were assessed for four age groups: 0-6 months (1.52 g/kg; 12.6-15.8 g/day; 5.5-6.0 kg), 7-9 months (1.20 g/kg; 9.0-10.2 g/day; 7.5-8.5 kg), 10-12 months (1.00 g/kg; 8.5-9.5 g/day; 8.5-9.5 kg), and 1-3 years (1.05 g/kg; 12.6-15.8 g/day; 12.0-15.0 kg). Low-protein foods may be insufficient for infants with reduced breastmilk or formula intake, while high-protein foods often rich in meat, dairy, or fortified products can help meet upper-range requirements. These findings underscore the need for careful alignment of complementary food protein levels with age-specific nutritional guidelines to support optimal growth and development in early childhood.