Enrichment of table eggs with selenium and lutein – our experiences
Notice bibliographique
Résumé
Received: 2018-05-06 | Accepted: 2018-05-14 | Available online: 2018-11-26 https://doi.org/10.15414/afz.2018.21.04.138-141 By modifying meals for hens it is possible to influence the content of selenium and lutein in eggs, which enables the production of eggs with an increased share of the desired functional ingredients. Such eggs on the market represent enriched or functional foods that are characterized by preventive action in order to preserve the human health. The results of our research show that the composition of meals affects the content of selenium and lutein in eggs. The use of Se-yeast in hensâ mixtures in the amount of 0.5 mg·kg of feed increases the selenium content in egg whites and yolks by 62.94% and 41.54% in comparison to eggs from hens fed with a conventional mixture. Addition of 400 mg·kg of lutein to a hens' mixture can enrich egg yolk with lutein by 86.93% with respect to eggs from hens fed with a conventional mixture (without the addition of lutein).By designing hensâ mixtures using selenium and lutein having antioxidant activity, it is possible to produce eggs with improved nutritional value and extended shelf life. Keywords: eggs, enrichment, lutein, selenium References Aljamal, A.A., Purdum, S.E., Hanford, K.J. (2014) The effect of normal and excessive supplementation of selenomethionine and sodium selenite in laying hens. International Journal of Applied Poultry Research, 3 (3), 33-38. Chung, H.Y., Rasmussen, H.M., Johnson, E.J. (2004) Lutein bioavailability is higher from lutein-enriched eggs than from supplements and spinach in men. The Journal of Nutrition, 134 (8), 1887-1893. DOI: https://dx.doi.org/10.1093/jn/134.8.1887 FaÅ¡iangová M., BoÅilová G., Hulánková R. 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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,005 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
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