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Organisms require dietary macronutrients in specific ratios to maximize performance, and variation in macronutrient requirements plays a central role in niche determination. Although it is well recognized that development and body size can have strong and predictable effects on many aspects of organismal function, we lack a predictive understanding of ontogenetic or scaling effects on macronutrient intake. We determined protein and carbohydrate intake throughout development on lab populations of locusts and compared to late instars of field populations. Self-selected protein:carbohydrate targets declined dramatically through ontogeny, due primarily to declines in mass-specific protein consumption rates which were highly correlated with declines in specific growth rates. Lab results for protein consumption rates partly matched results from field-collected locusts. However, field locusts consumed nearly double the carbohydrate, likely due to higher activity and metabolic rates. Combining our results with the available data for animals, both across species and during ontogeny, protein consumption scaled predictably and hypometrically, demonstrating a new scaling rule key for understanding nutritional ecology.
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This content will become publicly available on August 29, 2026
APPLICATION OF AI AND MACHINE LEARNING TO ANALYZE PROTEIN CONTENT IN U.S. COMMERCIAL BABY FOODS
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.
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- PAR ID:
- 10633937
- Publisher / Repository:
- http://www.scienceijsar.com
- Date Published:
- Journal Name:
- International Journal of Science Academic Research
- ISSN:
- 2582-6425
- Subject(s) / Keyword(s):
- Baby foods Protein content AI machine learning Infants Young children
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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