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, 97 238 lactations (55 207 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.
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.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
This study aimed at determining the efficiency of microbial protein synthesis (EMPS) in diets based on highly wilted grass silage (GS) 539 g dry matter (DM) kg
−1
with the supplementation of starch ...or water-soluble carbohydrates (WSC) rich feeds, i.e. maize silage MS, 391 g kg
−1
DM intake (DMI), fodder beet (FB, 173 g kg
−1
DMI) or molasses (M, 137 g kg
−1
DMI). All the diets were made isonitrogenous by urea supplementation (14.0, 4.0 and 2.0 g kg
−1
DMI in GS-MS, GS-FB and GS-M diets). In sacco determined crude protein (CP) and organic matter (OM) degradabilities were 756, 800, 778 and 814 (P<0.05) and 563, 577, 593 and 618 g kg
−1
(P<0.05) in GS, GS-MS, GS-FB and GS-M diets, respectively. Synchrony indexes that describe the synchrony of CP and OM degradation in the rumen were 0.75, 0.67, 0.67 and 0.79 in GS, GS-MS, GS-FB and GS-M diets, respectively. The EMPS, assessed by means of urinary purine derivative excretion, did not differ significantly (P>0.05) among the diets (36.6, 35.1, 34.7 and 34.0 g microbial nitrogen kg
−1
OM apparently digested in the rumen in GS, GS-MS, GS-FB and GS-M diets, respectively). The estimated metabolizable protein supply from GS, GS-MS, GS-FB and GS-M diets amounted to 98, 90, 93 and 87 g kg
−1
DMI, respectively. Apparently, highly wilted GS containing a high concentration of WSC (91 g kg
−1
DM) supports high EMPS in the rumen and this cannot be improved by the supplementation with starch or water-soluble carbohydrates (WSC) rich feeds.
One hundred and eighteen grass silage samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 ...to 2500 nm at 8 nm intervals. Calibration equations for the prediction of crude protein (CP), crude fi bre (CF), crude fat (F), crude ash (A), dry matter of air-dried samples (DM) and NEL were developed by the use of principal component analysis (PCA) and modifi ed partial least squares regression technique (mPLS). NIRS demonstrated high predictive ability for CP (R2 = 0.97), CF (R2 = 0.96) and A (R2 = 0.94). Moderate accuracy was characteristic for F and DM (R2 = 0.81 and 0.79). Crude protein, F and DM deviations from reference methods were comparable to those which are expected by the use of the same reference methods in different laboratories. The determination coeffi cient for in vitro assessed NEL concentration was 0.76. Seventy-seven percent of samples lied within acceptable limits of ± 0.3 MJ NEL kg-1DM. Suboptimal sample distribution, i.e. small number of samples in classes below 4.6 and above 6.0 MJ NEL kg-1DM was observed. It seems that deviations of NIRS predicted values from the reference values were related to the concentration of NEL. It was concluded that NIRS shows the potential for reliable determination of chemical composition and energy value of grass silage.
One hundred and fifty-eight hay samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 to ...2500 nm at 8 nm intervals. Calibration equations for the prediction of dry matter (DM), crude protein (CP), crude fibre (CF), crude fat, ash and NEL were developed by the use of principal component analysis. NIRS demonstrated high predictive ability for CP (R2 = 0.98), CF (R2 = 0.95) and ash (R2 = 0.94). Only moderate accuracy was characteristic for DM (0.87) and crude fat (R2 = 0.75). With exception of ash deviations from reference methods are comparable to those which are expected by the use of the same reference methods in different laboratories. NIRS has a high ability to predict in vitro assessed NEL concentration (R2 = 0.89). More than 95% of samples lied within acceptable limits of ± 0.3 MJ NEL kg–1 dry matter (DM). Despite suboptimal sample distribution, i.e. small number of samples in classes below 4.4 and above 5.6 MJ NEL kg–1 DM, the deviations of NIRS predicted values from reference values were not related to concentration of NEL. It was concluded that NIRS is rapid and reliable technique for determination of chemical composition and energy value of hay.
Mnogocvetno ljuljko smo pokosili 10. maja 1988 in silirali v poskusne silose (100 l) kot neovelo (S/0) in po 6 (S/6), 10 (S/10), 30 (S/30) in 34 (S/34) urah venenja. Vsebnost sušine (SS) se je ...povečala od 190 g kg-1 pri košnji, na 230, 267, 376 in 434 g kg-1 po 6, 10, 30 in 36 urah venenja. Iz neovele krme smo pripravili tudi silažo, tretirano z mravljinčno kislino (S/0 MK, 4 g 85 % mravljinčne kisline na kg). Silose smo odprli po 12 letih. Silaže S/0, S/0 MK, S/6, S/10, S/30 in S/34 so vsebovale 106, 171, 215, 241, 346 in 412 g SS kg-1. Vsebovale so 1,8, 104,2, 97,3, 77,4, 83,5 in 48,0 g mlečne kisline, 55,5, 34,6, 26,7, 24,0, 19,8 in 15,2 g ocetne kisline ter 53,96, 4,81, 4,05, 11,37, 0,01 in 0,00 g maslene kisline na kg SS. Deleži amoniakovega N pri S/0, S/0 MK, S/6, S/10, S/30 in S/34 so bili 552, 195, 211, 212, 108 in 69 g kg-1 skupnega N. Tako venenje kot tretiranje z mravljinčno kislino je izboljšalo obstojnost silaže. Delež amoniakovega N in vsebnost ocetne kisline sta bila negativno povezana z vsebnostjo SS (r = –0,85 in –0,89; p < 0,05). Vsebnost NEL je bila pri S/0 precej manjša (3,62 MJ kg-1 SS) kot pri silažah iz ovele krme (od 5,01 do 5,39 MJ kg-1 SS) in pri silaži z dodatkom mravljinčne kisline (5,22 MJ kg-1 SS). Vsebnost NEL je bila negativno povezana z deležem amoniakovega N (r = –0,98; p < 0,001), vsebnostjo ocetne (r = –0,91; p < 0,05), propionske (r = –0,98; p < 0,001) in maslene kisline (r = –0,99; p < 0,001). Rezultati raziskave kažejo, da je mogoče dobro fermentirane ovele silaže hraniti v zrakotesnih silosih tudi več kot deset let brez tveganja, da bi se silaže pokvarile. Pri silaži iz neovele krme se je mlečna kislina razgradila, silaža pa pokvarila. Obstojnost neovelih silaž za daljše obdobje je mogoče izboljšati z dodajanjem mravljinčne kisline.
Three models for the estimation of milk, fat and protein daily yield (DY) based on a.m. (AM) or p.m. (PM) milkings were compared. A total of 518 766 test-day records from 5078 dairy cattle farms ...obtained between March 2004 and April 2008 were analysed. The DY model was a linear model with DY as a dependent variable. In the PYR model and the DYR model, partial yield ratios (AM:DY and PM:DY) and daily yield ratios (DY:AM and DY:PM), respectively, were used as a dependent variable in the first step. In the second step, DY was estimated as a partial yield divided (PYR model) or multiplied (DYR model) by the estimated yield ratio from the first step. Models included the effect of partial yield (only in the DY model), milking interval, stage (month) of lactation and parity. Analysis of variance indicated that partial yield was the most important source of variation for the DY model whereas milking interval had the biggest effect in the PYR model and the DYR model. Differences in accuracy (correlation between the true and the estimated DY) between the models were negligible. On the other hand, models differed in the amount of bias (average error). The DYR model on average overestimated DY by 0·13 kg, 0·01 kg and 0·01 kg for milk, fat and protein, respectively. For the other two models the overall bias was almost zero. However, the DY model overestimated low and underestimated high DY owing to the well known regression property. The DYR model progressively overestimated high DY. These problems were not observed with the PYR model which seemed to be the best model. In this paper a relatively old topic was analysed and discussed from a new point of view, where the estimation of DY is based on modelling biologically more stable partial yield ratios rather than yield values from a.m. or p.m. milking.
Pri 19 vzorcih zelene krme, 5 vzorcih travne silaže in enem vzorcu sena z znano in vivo določeno prebavljivostjo smo po uradnem nemškem sistemu (DLG, 1997) ocenili vsebnost presnovljive energije (ME) ...in neto energije za laktacijo (NEL). Primerjalno smo energijsko vrednost in prebavljivost organske snovi (pOS) vzorcev ocenili na podlagi kemične sestave in prebavljivosti iz preglednic (DLG, 1997). Ugotovili smo, da na podlagi podatkov iz DLG preglednic podcenjujemo pOS za 2,1 ± 3,95%, vsebnost ME za 0,29 ± 0,52 MJ, vsebnost NEL pa za 0,21 ± 0,37 MJ kg-1 sušine (SS). Nekoliko manjše odstopanje od in vivo ocen smo dobili pri ocenjevanju ME (0,04 ± 0,45 MJ kg-1 SS) in NEL (0,03 ± 0,33 MJ kg-1 SS) na podlagi kemične sestave in regresijskih enačb iz literature (GfE, 1998). S hohenheimskim plinskim preskusom (in vitro) in uporabo primernih regresijskih enačb iz literature smo bistveno izboljšali točnost ocene. Razmeroma točna je bila enačba Menkeja in Steingassa (1987), po kateri smo v primerjavi z oceno in vivo podcenili vsebnost ME za 0,12 ± 0,26 MJ, vsebnost NEL pa za 0,09 ± 0,19 MJ kg-1 SS. Enačbe Aipleja in sod. (1995) so in vivo ocenjeno vsebnost ME precenile za 0,15 ± 0,24 MJ kg-1 SS, vsebnost NEL pa za 0,10 ± 0,17 MJ kg-1 SS. Pretežen del variabilnosti v vsebnosti ME je mogoče pojasniti z multiplo regresijsko enačbo na osnovi količine plina, ki nastane pri inkubaciji vzorcev z vampnim sokom in vsebnosti surovih maščob (R2 = 0,96).
Na podlagi kemične sestave in in vitro metode, ki temelji na plinu, razvijajočem se pri inkubaciji vzorcev z vampnim sokom, smo določili vsebnost neto energije za laktacijo (NEL) 80 vzorcev travnih ...silaž. Vrednosti smo primerjali z ocenami, pridobljenimi z običajnimi postopki ocenjevanja NEL v slovenskih laboratorijih, to je na podlagi kemične sestave ter prebavljivostnih koeficientov iz preglednic ali regresijskih enačb iz literature. Ugotovili smo, da novejše DLG preglednice in enačbe vsebnost NEL precenijo. Vsebnosti NEL, ki smo jih dobili z upoštevanjem koeficientov prebavljivosti objavljenih v DLG (1991) preglednicah precenijo in vitro ocenjene vrednosti za 0,42 ± 0,43 MJ, DLG (1997) za 0,50 ± 0,36 MJ, enačba po Menkeju in Steingassu (1987) za 0,36 ± 0,42 MJ ter enačbe GfE (1998) za 0,53 ± 0,40 MJ NEL kg–1 sušine (SS). Regresijska analiza je pokazala, da vse ocene sistematično odstopajo od in vitro ocenjenih vrednosti. Za ocenjevanje manj kakovostnih vzorcev travnih silaž, ki vsebujejo manj kot 5,5 MJ NEL kg–1 SS, priporočamo uporabo starejših nemških preglednic (DLG, 1982), za bolj kakovostne vzorce travnih silaž (> 5,5 MJ NEL kg–1 SS) pa so primernejše novejše preglednice (DLG, 1997), pa tudi uradne nemške enačbe (GfE, 1998). Pri vseh postopkih ocenjevanja smo ugotovili razmeroma velika povprečna posamična odstopanja (od 0,33 do 0,57 MJ kg–1 SS) od in vitro ocenjenih vrednosti. Največje posamično odstopanje je doseglo 1,5 MJ kg–1 SS. Predlagamo nove multiple regresijske enačbe za ocenjevanje vsebnosti presnovljive energije in NEL v travnih silažah na podlagi kemične sestave. S temi enačbami lahko zmanjšamo sistematična odstopanja od in vitro ocenjenih vrednosti, nepojasnjenim odstopanjem, ki znašajo v povprečju več kot 0,3 MJ NEL kg–1 SS, pa se z uporabo klasične weendske analize ne moremo izogniti.
Ocenjevanje energijske vrednosti mrve BABNIK, Drago; VERBIČ, Jože; ŽNIDARŠIČ, Tomaž
Acta agriculturae slovenica,
12/2001, Volume:
78, Issue:
2
Journal Article
Peer reviewed
Open access
Z in vitro metodo, ki temelji na plinu razvijajočem se pri inkubaciji vzorcev z vampnim sokom, smo ocenili vsebnost neto energije za laktacijo (NEL) 100 vzorcem mrve zbranimi v letih 1999 in 2000. ...Vrednosti smo primerjali z ocenami, pridobljenimi z običajnimi postopki ocenjevanja NEL v slovenskih laboratorijih, to je na podlagi kemične sestave ter prebavljivostnih koeficientov iz preglednic ali ob pomoči regresijskih enačb iz literature. Ugotovili smo, da so na podlagi preglednic DLG (1982) ocenjene vsebnosti NEL v mrvi odstopale od in vitro ocenjenih vrednosti za –0,22±0,35 MJ NEL kg–1 sušine (SS). Ocene na podlagi novejših DLG (1991) preglednic so odstopale od in vitro ocenjenih vrednosti za 0,25±0,31 MJ, na podlagi DLG (1997) za 0,20±0,33 MJ ter na podlagi enačb GfE (1998) za 0,16±0,33 MJ NEL kg–1 SS. Ocene z enačbo po Stekarjevi in sod. (1994) so v povprečju odstopale od in vitro ocenjenih vrednosti za 0,01±0,33 MJ NEL kg–1 SS. Regresijska analiza je pokazala, da so vse ocene sistematično odstopale od in vitro ocenjenih vrednosti. Za ocenjevanje manj kakovostnih vzorcev mrve z ekstenzivnih travnikov, ki vsebujejo manj kot 5,2 MJ NEL kg–1 sušine, priporočamo uporabo starejših nemških preglednic (DLG, 1982), za bolj kakovostne vzorce mrve (> 5,2 MJ NEL) pa so primernejše novejše preglednice (DLG, 1997) in uradne nemške enačbe (GfE, 1998). Povprečni vzorci s slovenskih kmetij so ocenjeni najbolj točno z enačbo po Stekarjevi in sod. (1994). Za vse ocene so bila značilna razmeroma velika povprečna posamična odstopanja (0,27–0,32 MJ kg–1 SS) od in vitro ocenjenih vrednosti. Največja posamična odstopanja so presegla 1 MJ kg–1 SS. Predlagali smo nove enačbe za ocenjevanje vsebnosti presnovljive energije in NEL v mrvi. Ugotovili smo, da je mogoče s temi enačbami odstopanja od in vitro ocenjenih vrednosti zmanjšati za 10 do 50 %. Nepojasnjenim odstopanjem, ki znašajo v povprečju približno 0,2 MJ NEL kg–1 SS, se z uporabo klasične weendske analize ne moremo izogniti.
PDF
