Ecological and nutritional analysis of artificial intelligence-based sustainable dietary models

MakaleAçık ErişimScopus SJRQ1
  • SDG 2 · Açlığa Son
  • SDG 3 · Sağlık ve Kaliteli Yaşam
  • SDG 13 · İklim Eylemi

Özet

Growing concerns over environmental sustainability and health have increased the demand for sustainable diets. Advances in artificial intelligence (AI) offer new opportunities for diet planning. Evaluating the nutritional adequacy and environmental impact of AI-generated sustainable diets is essential. This study aimed to compare the nutritional quality and ecological footprints of sustainable diets created by four popular AI tools (Gemini, Copilot, ChatGPT, and Grok). Each AI tool generated a sustainable diet plan for a healthy adult woman. Diets were evaluated for energy, nutrient content, antioxidant capacity, glycemic index, protein quality, fatty acid profiles, Healthy Eating Index-2015 scores, and ecological footprints. All diets showed low ecological footprints but did not meet energy targets (1800 kcal/day). Gemini had the most sustainable composition. Vitamin B12 was consistently below recommended levels in diets from Gemini, Copilot, and ChatGPT. All diets had adequate carbohydrate, protein, fat quality, and overall diet quality. Carbon footprint associated with protein, energy from protein, cholesterol, pyridoxine, folate, and vitamin C. Water footprint was linked to multiple nutrients, and fruits, meat, poultry, and fish; vegetable intake correlated with carbon footprint. AI-assisted diets have potential for sustainability but nutritional completeness concerns remain, especially for vulnerable groups. Further studies comparing AI and dietitian plans are needed to assess long-term effects.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/bayburt/12761Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.jfca.2025.108814Yayıncı resmi DOI adresi
İndeks kayıtları
Kaydın indeks veri tabanlarındaki sayfası (aktarımda alınan kayıt numarasıyla). Erişim, indeksin kendi koşullarına bağlıdır.
Atıflar
Scopus
1
WoS
1
OpenAlex
3
Her kaynağın kendi saydığı toplam atıf; aktarım ve zenginleştirme sırasında alındı.
Tam Kayıt
AlanDeğerDil
dc.contributor.authorKöktürk, Seda Nur
dc.contributor.authorYardımcı, Hülya
dc.date.accessioned2026-10-29T19:09:59.943833771Z
dc.date.available2026-10-29T19:09:59.943833771Z
dc.date.issued2026
dc.description.abstractGrowing concerns over environmental sustainability and health have increased the demand for sustainable diets. Advances in artificial intelligence (AI) offer new opportunities for diet planning. Evaluating the nutritional adequacy and environmental impact of AI-generated sustainable diets is essential. This study aimed to compare the nutritional quality and ecological footprints of sustainable diets created by four popular AI tools (Gemini, Copilot, ChatGPT, and Grok). Each AI tool generated a sustainable diet plan for a healthy adult woman. Diets were evaluated for energy, nutrient content, antioxidant capacity, glycemic index, protein quality, fatty acid profiles, Healthy Eating Index-2015 scores, and ecological footprints. All diets showed low ecological footprints but did not meet energy targets (1800 kcal/day). Gemini had the most sustainable composition. Vitamin B12 was consistently below recommended levels in diets from Gemini, Copilot, and ChatGPT. All diets had adequate carbohydrate, protein, fat quality, and overall diet quality. Carbon footprint associated with protein, energy from protein, cholesterol, pyridoxine, folate, and vitamin C. Water footprint was linked to multiple nutrients, and fruits, meat, poultry, and fish; vegetable intake correlated with carbon footprint. AI-assisted diets have potential for sustainability but nutritional completeness concerns remain, especially for vulnerable groups. Further studies comparing AI and dietitian plans are needed to assess long-term effects.
dc.identifier.articlenumber108814
dc.identifier.doi10.1016/j.jfca.2025.108814
dc.identifier.eissn1096-0481
dc.identifier.issn0889-1575
dc.identifier.scopus2-s2.0-105025236677
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/12761
dc.identifier.volume149
dc.identifier.wosWOS:001648527000001
dc.language.isoen
dc.publisherAcademic Press Inc.
dc.relation.ispartofJournal of Food Composition and Analysis
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial intelligence
dc.subjectCarbon footprint
dc.subjectSustainable diet
dc.subjectWater footprint
dc.subject.classificationChemistry, Applied
dc.subject.classificationFood Science & Technology
dc.subject.classificationChemistry
dc.subject.otherCARBON FOOTPRINT
dc.subject.otherWATER FOOTPRINT
dc.subject.otherGLYCEMIC INDEX
dc.subject.otherQUALITY
dc.titleEcological and nutritional analysis of artificial intelligence-based sustainable dietary models
dc.typeArticle
rdl.citation.openalex3
rdl.citation.scopus1
rdl.citation.wos1
rdl.oa.statushybrid
rdl.oa.urlhttps://doi.org/10.1016/j.jfca.2025.108814
rdl.scopus.quartileQ1
rdl.sdgSDG03
rdl.sdgSDG02
rdl.sdgSDG13
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)