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Enregistrement W7029152934

Impact of Housing and Management on Production, Behavior, and Welfare of Dairy Cows in Automatic Milking Systems

2022· article· en· W7029152934 sur OpenAlex

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aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
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Notice bibliographique

RevueTigerPrints (Clemson University) · 2022
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueTurkey's Politics and Society
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLamenessMilkingAutomatic milkingWelfareHockDairy cattleDecision tree
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The overall objective of this research was to determine the impact of Automatic Milking System (AMS) housing and management practices on cow production, behavior, and welfare of Holstein dairy cows. The first objective was to identify factors at the farm and cow level associated with lameness on AMS farms through decision tree analysis to allocate probabilities to each input. Results indicated this novel multifactorial approach of data analysis enabled us to highlight critical points that can be focused on to lessen cow-level complications or enhance farm-level housing and management practices to reduce the incidence and severity of lameness in AMS farms. Classifiers were identified based on the decision tree classification model of 1378 data points from 36 AMS farms across Michigan and Canada. The primary classifier was identified as the type of stall base, specifically sand, rubber, or geotextile mat with the highest class membership (CM=976). The secondary classifier was the quantity of bedding, divided by the cows standing on 2 cm (CM=456) or(CM=520) of bedding. The body condition score (BCS) cow fit stall width were identified as the tertiary classifier. Cows with BCS of 3.25 to 4.5 (CM=307) were defined as non-lame with an estimated probability (EP) of 0.59, while cows with BCS of 2 to 2.5 (CM=213) were further divided by the presence of hock lesions. Cows without lesions were defined as non-lame (EP = 0.93) and cows with lesions were defined as lame (EP=0.07). Cows that fit the stall width were defined as non-lame (EP=0.66), and cows that did not fit were further divided by the width of the feed alley. Farms with ≥430 cm feed alley were defined as non-lame (EP=0.89), whereas farms with(EP=0.11). These findings suggest various cow and farm-level factors can influence the incidence of lameness in AMS farms, with specific factors, having a larger impact than others.\nThus, leads to the second study that evaluates the impact of changes in milking permission permits on dairy cow production, behavior, and welfare as an indicator of stress. The objective of this study was to determine the impact of a decrease in milking permission from milking every 4 h to every 6 h on DIM 100 on cow performance and behavior. Twenty-four Holstein dairy cows were separated into two groups balanced for the lactation stage. Six cows were randomly assigned to one of four treatment groups: PC (primiparous control: cows in 1st lactation with no change in milking permission), PT (primiparous treatment: cows in 1st lactation and milk permission transitioned on DIM 100), MC (multiparous control: cows in ³2nd lactation with no change in milking permission), MT (multiparous treatment: cows in ³2nd lactation and milk permission transitioned on DIM 100). We discovered an impact of milking transition on tail swishing (P = 0.049), displacement behavior (P = 0.041), and total time spent inside the CP (P = 0.009). The change in milking permission also revealed longer AMS time (P = 0.041), higher stepping frequencies (P = 0.031), and extended AMS exit durations (P = 0.001) while cows were inside the milking robot. Heart rate variability (HRV) parameters showed elevated stress levels while waiting in the CP and inside the milking stall. Milking transition also influenced daily lying times (P = 0.030), lying bout durations (P = 0.010), lying frequencies (P = 0.010), and inactive standing time (P = 0.029). However, no effect of change in milking permission was observed in daily milk production, but multiparous (MU) cows produced more milk/day than primiparous (PR) cows (P = 0.021). These results suggest that a decrease in milking permission and cow parity affected various cow behaviors, HRV parameters, and overall cow activity, thus demonstrating increased stress in cows after the milking transition. In conclusion, mapping of risk factors associated with lameness can allow AMS farmers to make appropriate housing and management adjustments and mitigate cow level factors to reduce risk of lameness and maximize AMS efficiency. While changes in milking permission can impact cow behavior and welfare in farms with AMS. Therefore, this thesis focused on AMS farm management and housing factors that influence the prevalence of lameness, cow performance, behavior, and welfare.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,156
Score d'incertitude au seuil0,746

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,268
Écart entre enseignants0,248 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle