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Title:Napoved laktacijskih krivulj z uporabo regresijskih modelov in ocena izgube mleka zaradi povečanega števila somatskih celic pri kravah
Authors:Jeretina, Janez (Author)
Škorjanc, Dejan (Mentor) More about this mentor... New window
Files:.pdf DOK_Jeretina_Janez_2018.pdf (18,65 MB)
 
Language:Slovenian
Work type:Doctoral dissertation (mb31)
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:Izkoristek genetskega potenciala in ekonomična prireja mleka sta odvisna od spremljanja rezultatov kontrole prireje na ravni kmetije. Ta je odvisna od mlečnosti krav in njihovih potekov laktacijskih krivulj, na katere med drugim vplivajo tudi okoliški dejavniki. Oblike krivulj med pasmami se bistveno ne razlikujejo, so pa razlike med prvesnicami in kravami v kasnejših laktacijah. Za oceno parametrov Wood-ove krivulje pri poljubni mlečnosti smo razvili sistem regresijskih enačb, s pomočjo katerih lahko napovemo dnevne mlečnosti in ocenimo mlečnost v želenem intervalu standardne laktacije na podlagi prvih dnevnih kontrol. Pri prvesnicah, ki še nimajo svojih podatkov o prireji, mlečnost v standardni laktaciji napovemo s pomočjo regresijskih enačb ob poznavanju plemenskih vrednosti staršev ter proizvodnosti sovrstnic. Iz standardov laktacijskih krivulj za posamezne mlečnosti nato načrtujemo potek dnevnih mlečnosti. S prihajajočimi dnevnimi kontrolami je zanesljivost napovedi še večja. Zaradi določenih okoliških dejavnikov se pogosto zgodi, da napovedanih mlečnosti ne dosežemo. Med raznoterimi razlogi so lahko tudi subklinični mastitisi, ki v prireji mleka povzročajo velike ekonomske škode. V ta namen smo vpeljali nov kazalnik presežka števila somatskih celic, ki je definiran kot presežek ŠSC nad potekom krivulje standarda ŠSC zdravih krav v standardni laktaciji. Ugotovili smo, da so lahko izgube mleka pri istem povprečnem ŠSC zaradi različne razporeditve obdobij z visokim ŠSC večje, kot jih prinese povprečno povečanje za 100.000 SC. Dokazali smo, da primerjava zgolj na povprečjih ni primeren kazalnik zdravja mlečne žleze in je IPSC boljši, saj pri njem upoštevamo zaporedno lakacijo, stadij laktacije, ko je prišlo do obolenja, višino ŠSC in intenzivnost mlečnosti.
Keywords:govedo, laktacijska krivulja, standard laktacijske krivulje, število somatskih celic, indeks presežka somatskih celic
Year of publishing:2018
Source:Maribor
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
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Downloads:4
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Categories:FKBV
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Secondary language

Language:English
Title:LACTATION CURVE STANDARDS PREDICTION OF COWS USING REGRESSION MODELS AND ESTIMATING MILK LOSS DUE TO HIGH SOMATIC CELL COUNT
Abstract:To utilize the maximum genetic potential of each cow to achieve economical milk production on the farm depends on recording the individual cow’s milk yield. We found out that lactation curve trajectories are in close connection to a cow’s milk production potential which is influenced by environmental effects. The differences in the shape of the lactation curves exist only between primiparous and multiparous cows, but not of breeds. For the estimation of Wood curve parameters for arbitrary milk yield the regression equitation system was developed to estimate the daily milk yields and the estimation of milk production on the bases of first milk recordings. Prediction of expected milk yield in standard lactation of primiparous cows with little or no data on their milk productivity could be defined with the regression equations by knowing the parents breeding values and milk yields of relatives. Using standards of lactation curves for any milk yield we can follow daily milk yields. By including daily milk records in the model, the estimation becomes more reliable. Because environmental effects can occur, predicted milk yield may not be achieved. One of the reasons is subclinical mastitis which leads to considerable economic losses. We proposed a new somatic cell count index (SCCI), defined as the extent of somatic cell count (SCC) over the standard curve for SCC in healthy cows. We found that milk yield loss at the same average SCC in standard lactation could differ because of differences during lactation stages in which the elevated SCC appears. This means that the estimation of milk loss cannot be reliably estimated on the bases of SCC and that SCCI is a much better estimation because it also considers consecutive parity, stage of lactation, milk yield intensity and level of SCC.
Keywords:Cattle, lactation curve, standard lactation curve, somatic cell number, somatic cell count index


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