PREDICTION OF COMFORT FOR DAIRY COWS, DEPENDING ON THE STATE OF THE ENVIRONMENT AND THE TYPE OF BARN
Notice bibliographique
Résumé
Material and resource conservation are important when choosing the optimal technology for keeping dairy cattle.The so-called "Canadian technologies" of frame construction that are widely used in the world are only relatively recently used in national animal husbandry.The question of ensuring the comfort of animals in such rooms remains controversial, since the climate in them is as close as possible to environmental conditions.The purpose of the study was to study the temperature and humidity regime of uninsulated rooms and assess the state of comfort of animals in barns of the frame and hangar type.The temperature and humidity of the air were measured inside and outside the premises (n = 827) periodically from January to July 2018 (in the temperature range from -7.8 to +34.2°С).Using the multiple linear regression function in STATISTICA 10 (StatSoft, Inc., 2011), the calculated temperature values in the barns for low and high temperatures of the Steppe of Ukraine were obtained.It has been established that the temperature-humidity regime of uninsulated rooms is as close as possible to the state of the external environment and depends on the design features (type) of the barn. Chapter «Veterinary communications»The temperature difference inside and outside the premises will be 3-5°C.It is necessary to provide additional space cooling (axial fans of large diameter, small-drop irrigation, as well as their combination), since the temperature-humidity index (ТHI) inside the barn will be 2-3 units higher.The material of the article will be useful for breeders when choosing a technology for keeping dairy cows.Calculated values of temperatures and THI in uninsulated rooms of frame and hangar type can be used as approximate data for assessing the comfort of cows in lightweight rooms in conditions of temperate continental climate of the Steppe of Ukraine.The values of temperature and relative humidity of air in the barns obtained by us, as well as the temperature-humidity index (as an indicator of the comfort of animals in hot conditions), require practical confirmation under conditions of extreme high and low ambient temperatures.This will be the material for our further research, as well as the influence of climate in the barn on the physiological state and productivity of dairy cows.+5.6 -20.5 +4.5 11 12.2 +1.2 12.0 +1.0 -24 -18.5 +5.5 -19.6 +4.4 12 13.1 +1.1 12.9 +0.9 -23 -17.7 +5.3 -18.7 +4.3 13 13.9 +0.9 13.8 +0.8 -22 -16.8 +5.2 -17.8 +4.2 14 14.8 +0.8 14.7 +0.7 -21 -15.9 +5.1 -16.8 +4.2 15 15.7 +0.7 15.6 +0.6 -20 -15.0 +5.0 -15.9 +4.1 16 16.6 +0.6 16.5 +0.5 -19 -14.2 +4.8 -15.0 +4.0 17 17.5 +0.5 17.4 +0.4 -18 -13.3 +4.7 -14.1 +3.9 18 18.3 +0.3 18.3 +0.3 -17 -12.4 +4.6 -13.2 +3.8 19 19.2 +0.2 19.3 +0.3 -16 -11.5 +4.5 -12.3 +3.7 20 20.1 +0.1 20.2 +0.2 -15 -10.6 +4.4 -11.4 +3.6 21 21.0 0.0 21.1 +0.1 -14 -9.8 +4.2 -10.5 +3.5 22 21.8 -0.2 22.0 0.0 -13 -8.9 +4.1 -9.6 +3.4 23 22.7 -0.3 22.9 -0.1 -12 -8.0 +4.0 -8.7 +3.3 24 23.6 -0.4 23.8 -0.2 -11 -7.1 +3.9 -7.8 +3.2 25 24.5 -0.5 24.7 -0.3 -10 -6.2 +3.8 -6.9 +3.1 26 25.4 -0.6 25.6 -0.4 -9 -5.4 +3.6 -6.0 +3.0 27 26.2-0.8 26.5 -0.5 -8 -4.5 +3.5 -5.1 +2.9 28 27.1 -0.9 27.4 -0.6 -7 -3.6 +3.4 -4.2 +2.8 29 28.0 -1.0 28.3 -0.7 -6 -2.7 +3.3 -3.3 +2.7 30 28.9 -1.1 29.2 -0.8 -5 -1.9 +3.1 -2.4 -2.6 31 29.8 -1.2 30.1 -0.9 -4 -1.0 +3.0 -1.5 +2.5 32 30.6 -1.4 31.0 -1.0 -3 -0.1 +2.9 -0.6 +2.4 33 31.5 -1.5 31.9 -1.1 -2 0.8 +2.8 0.3 +2.3 34 32.4 -1.6 32.8 -1.2 -1 1.7 +2.7 1.2 +2.2 35 33.3 -1.7 33.7 -1.3 0 2.5 +2.5 2.1 +2.1 36 34.1 -1.9 34.6 -1.4 1 3.4 +2.4 3.0 +2.0 37 35.0 -2.0 35.5 -1.5 2 4.3 +2.3 3.9 +1.9 38 35.9 -2.1 36.4 -1.6 3 5.2 +2.2 4.8 +1.8 39 36.8 -2.2 37.3 -1.7 4 6.0 +2.0 5.7 +1.7 40 37.7 -2.3 38.2 -1.8
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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 | 0,000 | 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 | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».