1. Izboljšane tehnologije pridelave in konzerviranja z beljakovinami bogate krme - metuljnice in njihove mešanice za prilagajanje podnebnim spremembamBranko Kramberger, Tomaž Žnidaršič, Boštjan Kristan, Miran Podvršnik, Drago Babnik, 2022 Opis: Pridelava in konzerviranje krme v obdobjih, ko ni pomanjkanja vode za rast rastlin in pridelava proti suši odpornih rastlin sta ključna elementa prilagajanja živinoreje klimatskim spremembam. V Eip- Agri projektu 'Izboljšane tehnologije pridelave in konzerviranja z beljakovinami bogate krme - metuljnice in njihove mešanice za prilagajanje podnebnim spremembam' smo primerjali pridelavo in konzerviranje metuljnic v čisti setvi ter mešanice metuljnic in trav (oboje brez gnojenja z dušikom) s pridelavo z dušikom gnojenih trav v čisti setvi. Rezultati kažejo, da je uporaba metuljnic v čisti setvi in mešanic metuljnic s travami primerna za pridelavo in konzerviranje s proteini bogate krme. Pridelava mešanic z visokim deležem metuljnic je zanesljivejša. Te mešanice dajejo primerljive pridelke z metuljnicami v čisti setvi in silaže visoke kakovosti.
Ključne besede: deteljno-travne mešanice, metuljnice, pridelava krme, podnebne spremembe, silaža
Objavljeno v DKUM: 19.01.2022; Ogledov: 397; Prenosov: 57
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2. A new somatic cell count index to more accurately predict milk yield lossesJanez Jeretina, Dejan Škorjanc, Drago Babnik, 2017, izvirni znanstveni članek Opis: Intramammary infection and clinical mastitis in dairy cows leads to considerable economic losses for farmers. The somatic cell concentration in cow's milk has been shown to be an excellent indicator for the prevalence of subclinical mastitis. In this study, a new somatic cell count index (SCCI) was proposed for the accurate prediction of milk yield losses caused by elevated somatic cell count (SCC). In all, 97238 lactations (55207 Holstein cows) from 2328 herds were recorded between 2010 and 2014 under different scenarios (high and low levels of SCC, four lactation stages, different milk yield intensities, and parities (1, 2, and _>3). The standard shape of the curve for SCC was determined using completed standard lactations of healthy cows. The SCCI was defined as the sum of the differences between the measured interpolated values of the natural logarithm of SCC (ln(SCC)) and the values for the standard shape of the curve for SCC for a particular period, divided by the total area enclosed by the standard curve and upper limit of ln(SCC)=10 for SCC. The phenotypic potential of milk yield (305-day milk yield - MY305) was calculated using regression coefficients estimated from the linear regression model for parity and breeding values of cows for milk yield. The extent of daily milk yield loss caused by increased SCC was found to be mainly related to the early stage of lactation. Depending on the possible scenarios, the estimated milk yield loss from MY305 for primiparous cows was at least 0.8 to 0.9 kg day -1 and for multiparous cows it ranged from 1.3 to 4.3 kg day-1. Thus, the SCCI was a suitable indicator for estimating daily milk yield losses associated with increased SCC and might provide farmers reliable information to take appropriate measures for ensuring good health of cows and reducing milk yield losses at the herd level.
Ključne besede: dairy cows, milk production, lactation intervals, milk yield losses, somatic cell count index
Objavljeno v DKUM: 24.10.2017; Ogledov: 1161; Prenosov: 455
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3. Prediction of standard lactation curves for primiparous Holstein cows by using corrected regression modelsJanez Jeretina, Drago Babnik, Dejan Škorjanc, 2015, izvirni znanstveni članek Opis: Prediction of the expected milk yield is important for the management of the primiparous cows (PPC) with a few or no data on their own milk productivity. We developed a system of regression equations for predicting milk yields in standard lactation. The models include the systematic effects of the calving season, the five-year rolling herd average of milk yield of PPC, the breeding values of the parents for milk production, and daily milk recordings. A total of 21,901 lactations of Holstein PPC were collected during the regular monthly milk recordings of cows in the Republic of Slovenia. By including daily milk recordings in the model, the coefficients of determination of regression models for the prediction of milk yield increase: without known recordings (M0) R 2 =0.80; with one recording (M1) R 2 =0.82; with two first consecutive recordings (M2) R 2 =0.86; and with three recordings (M3) R 2 =0.89. Deviations of milk yield up to 500 kg in a standard lactation (<1.6 kg/day) were as follows: with the model M0, they occurred in 53.4% of PPC; with M1, they occurred in 56.3% of PPC; with M2, they occurred in 64.5% of PPC; and with M3, they occurred in 70.9% of PPC. We concluded that the developed system of regression models is an appropriate method for milk yield prediction of PPC.
Ključne besede: primiparous cows, milk yield, prediction, lactation curves, regression equations
Objavljeno v DKUM: 24.07.2017; Ogledov: 950; Prenosov: 460
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