Socioeconomic Survey and Physicochemical Parameters of Chicken Eggs concerning the Breeding Systems in Cameroon
Notice bibliographique
Résumé
Physicochemical characteristics of eggs are still poorly controlled in poultry farming in the city of Ngaoundéré, Cameroon. The present study was thus conducted to characterize the rearing systems in modern poultry farming and to analyze the physicochemical characteristics of eggs from hens reared in deep litter, battery, and backyard systems from August to October 2020 in Ngaoundéré, Cameroon. To this end, 33 farms with approximately 61100 hens (Cobb500 broiler and layer) were surveyed. At the end of this survey, a sample of 180 eggs was collected, with 60 eggs per system for physicochemical analyses. Data included socio-economic and technical characteristics of modern farming systems as well as the physicochemical parameters of the eggs. The obtained results indicated that 90.9% of Cobb500 chicken owners were men. Of the total of the layer’s buildings, 73% were equipped with nests. The materials used for feeders were made of wood (54.4%), plastic (21.2%), or cement (6.1%). Moreover, 81.1% of the poultry farmers buy chicken feed on the market while the others prepare their own feed from various ingredients. Preventive and curative prophylactic measures were applied by all livestock farmers, yet 54. 5% were still victims of different diseases. The selling price of a 45-day-old broiler chicken was between 4 and 6 USD, while the price of a 30-egg tray varied between 3 and 4 USD, which contributed to 60-80% of family income for 54.5% of poultry farmers. The high feed cost as well as lack of finance, ingredients, and security were the main issues of poultry farming. Concerning the physicochemical characteristics of eggs, a significant increase in egg weight was noted among backyard (43.50 ± 3.15 g), battery (58.19 ± 4.02 g), and deep litter (63.51 ± 3.91 g) systems. The Haugh’s Unit of eggs in the backyard system (72.33 ± 4.42%) was significantly lower than deep litter (82.91 ± 6.76%) and battery systems (86.83 ± 11.42%). The proportions of eggshell and edible contents were similar in all production systems. Yolk lipid (17.63%) and yolk protein (7.11%) in dry matter contents of local breed eggs were higher than those of improved breed from both systems. The findings indicated that modern poultry farming in Ngaoundéré has been poorly developed and backyard eggs were richer in nutrients and consequently highly recommended to use.
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Comment cette classification a été obtenuedéplier
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| 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 | 0,000 | 0,001 |
| 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; un appel candidat d’une seule tête enseignante, 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 ».