The Addition of Faba Bean Ingredients to Crackers Reduces Acute Postprandial Glycemia in Healthy Young Men
Notice bibliographique
Résumé
Background Consumers and therefore the food sector have a high interest in producing healthy commercially available snacks. One potential approach to meeting this demand is to utilize pulse ingredients to improve the nutritional quality of current commercial products. Many snack foods produce high blood glucose (BG) responses. However, there is limited information on the effects of addition of pulses and/or their components to snacks on post‐prandial glycemia (PPG). Additionally, BG levels are influenced by the properties of food ingredients and in particular starch microstructure, which remains to be studied in many pulse components such as faba beans (FB). Objective To test the effect of incorporating FB flour and FB flour fractions to wheat flour crackers on the acute, as well as the second‐meal effect, on PPG in healthy young men. Methods In a repeated‐measures, randomized crossover trial, adult males (n=15) consumed 225 kcal crackers made with: (1) 100% whole wheat flour (control), (2) 23.9g whole FB flour (FB flour) (3) 24.1g protein concentrate made from FB flour (FB protein concentrate) (4) 23.7g protein isolate made from FB flour (FB protein isolate), (5) 24.7g high starch FB flour (FB starch). All FB flours replaced 40% of calories of whole wheat flour in crackers. BG incremental area under the curve (iAUC) from 0–120 min (pre‐meal), 120–200 min (post‐meal) and 0–200 min (total) was calculated using PPG concentrations. FB flours were analyzed to ensure consistency for size using light scattering. Additionally, starch in FB flour and FB starch was analysed by differential scanning calorimetry and scanning electron microscopy to relate starch microstructure to PPG. Results All FB flours were finely ground with average sizes < 150 um. For pre‐meal BG (0–120 min), there was a time (p<0.0001), treatment (p<0.0001) and time‐by‐treatment effect (p<0.0001), whereas there was only a time (p<0.0001) but no time‐by‐treatment interaction or treatment effect (p=0.12) on post‐meal BG (120–200 min). At 30 and 45 min, BG was lower following FB protein concentrate and FB protein isolate crackers compared to wheat flour crackers with no effect of FB flour and FB starch crackers (p<0.05). At 60 min, BG was lower and similar after all FB crackers compared to wheat flour crackers (p<0.05). There was an effect of treatment pre‐meal (p<0.0001) but not post‐meal on BG iAUC. FB protein concentrate and FB protein isolate led to lower pre‐meal BG iAUC compared to wheat flour crackers and FB protein isolate compared to FB starch. Total BG iAUC (0–200 min) was lower following the FB protein isolate compared to wheat flour crackers (p<0.001). Starch gelatinization disrupts crystalline structure, which can increase PPG, and in FB starch and FB flour this occurred at 67°C, a temperature reached during baking. In addition, granules present in FB starch and FB flour showed evidence of surface erosion (exo‐ and endo‐corrosion), suggesting more efficient hydrolysis of starch and subsequent glucose release resulting in higher PPG. These results suggest that FB flours, particularly protein concentrate and isolate, are primary components of FB responsible for lowering PPG. Conclusion Addition of FB ingredients to high glycemic snacks such as crackers may aid in postprandial glucose control. Support or Funding Information This study was supported by the Saskatchewan Pulse Growers, Canada.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».