Evaluation of milk yield and milk ability traits of Lithuanian red cows with different genotypes during lactation in organic farms
Notice bibliographique
Résumé
Holstein cattle have been used for many decades for the breeding of other dairy cattle in order to increase milk production. Productivity of cows differs between organic and conventional herds; therefore, the ability of cows to adapt to an organic production environment has been questioned, whether these high-cost genotypes are suitable for organic farming systems. Organic dairy farming has grown, farmers have realised that many available conventional breeds of cows are not well adapted to new situations and that more robust cows are able to function well in the organic environment. The aim of this study was to investigate the milk yield and milk ability traits during lactation of Lithuanian red cows with different genotypes. The research was carried out in an organic farm in 2020 with dairy cows (n = 248) of Lithuanian red cattle population. The milk yield (MY), milking speed (MS), highest milk flow (HMF), and milking time (MT) were evaluated. Investigated traits were measured with DE Laval electronic milk meters, “Apro Windows” software. All records were between 5 and 330 days of lactation, with average 2.26 ± 0.44 of lactation. All cows had two milk-recording events per test day (morning and evening). Lactation of cows was divided into stages: (stage 1 – <= 60; stage 2 – 61–150; stage 3 – 151–240; an stage 4 – 241–330 days of lactation). The statistical analysis of data was performed using the SPSS 25.0 (SPSS Inc., Chicago, IL, USA) software. The highest number of cows was with LRxRHxRH genotype, which accounted for 37.83% (χ2 = 53.540, df = 1, P < 0.001) of all investigated cows. We observed that the highest MY and HMF in the organic farm was detected in cows with genotypes LRxAIxRH, LRxHxH and LRxRHxRH in the first and the second stages of lactation (P < 0.05). MT of LRxHxH, LRxRHxDR and LRxAIxRH genotype cows during all stages of lactation was longer, compared to cows of other genotypes (P < 0.05). We estimated that of all fixed effects the biggest influence on MS, HMF, MT (P < 0.001) and MY was by a genotype of cows (P < 0.01), while the stage of lactation showed the highest impact on MY, HMF, MT (P < 0.001) and MS (P < 0.01). Analysis of different genotypes of cows revealed that local breeds are well-adapted and more suitable for organic farming.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».