NAPOVEDOVANJE KEMIČNE SESTAVE IN ENERGIJSKE VREDNOSTI TRAVNE SILAŽE Z BLIŽNJO INFRARDEČO REFLEKSIJSKO SPEKTROSKOPIJO

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.Stoosemnajstim vzorcem travne silaže z znano kemično sestavo in in vitro določeno vsebnostjo neto energije za laktacijo (NEL) smo v valovnem območju med 1100 in 2500 nm na vsakih 8 nm izmerili spektre odbite bližnje infrardeče svetlobe. S pomočjo analize glavnih komponent (PCA) in regresijske metode modifi ciranih delnih najmanjših kvadratov (mPLS) smo razvili umeritvene enačbe za napovedovanje vsebnosti surovih beljakovin (SB), surove vlaknine (SVl), surovih maščob (M), surovega pepela (P), suhe snovi zračno suhih vzorcev (DM) in NEL. Metoda NIRS je bila zelo dobra pri napovedovanju SB (R2 = 0,97), SVl (R2 = 0,96) in A (R2 = 0,94). Za M in DM je bila značilna zmerna točnost (R2 = 0,81 in 0,79). Pri SB, M in DM so bila odstopanja od referenčnih metod primerljiva z odstopanji, ki jih lahko pričakujemo pri izvajanju istih referenčnih metod v različnih laboratorijih. Determinacijski koeficient za in vitro ocenjeno koncentracijo NEL je znašal 0,76. Sedeminsedemdeset odstotkov vzorcev je ležalo znotraj sprejemljivih meja ± 0,3 MJ NEL kg-1SS. Za vzorce travnih silaž je bila značilna ne-optimalna porazdelitev vzorcev, t.j. majhno število vzorcev v razredih pod 4,6 in nad 6,0 MJ NEL kg-1SS. Izgleda, da so odstopanja med NIRS ocenjenimi vrednostmi in referenčnimi vrednostmi povezana z vsebnostjo NEL. Sklenili smo, da je z NIRS metodo mogoče zanesljivo oceniti kemično sestavo in energijsko vrednost travne silaže

A new somatic cell count index to more accurately predict milk yield losses

Intramammary infection and clinical mastitis in dairy cows leads to considerable economic losses for farmers. The somatic cell concentration in cow\u27s 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

Prediction of standard lactation curves for primiparous Holstein cows by using corrected regression models

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 =0.80with one recording (M1) R 2 =0.82with two first consecutive recordings (M2) R 2 =0.86and 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 PPCwith M1, they occurred in 56.3% of PPCwith M2, they occurred in 64.5% of PPCand 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

PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY

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

The uncertainty of results when estimating daily milk records

Two studies were conducted to evaluate the uncertainty of measurements (daily milk yield, fat, protein and lactose content) on Slovenian milk recording data, respecting the ISO 5725 definition of precision i.e. as repeatability (s$_{\rm r})$ and reproducibility (s$_{\rm R})$ standard deviation. The aim of study 1 was to evaluate the within operator (repeatability) variability of daily measurements and to compare the precision of AT (alternating morning and evening milking records at subsequent monthly visits) and the ICAR standard reference A4 recording scheme (monthly records of two daily milkings). In study 2 we were interested in the reproducibility of milk recording results and the contribution of factors associated with the operator (official representative of the recording organization) and herd or residual variation. In addition, the precision of daily milk yield measurements was studied in relation to herd size and cow productivity. Study 1 was conducted on 332 cows from 14 herds with 14 operators. Study 2 was made on 57639 records gathered from the Slovenian central milk recording database. The results on two consecutive days were obtained by the same operator (study 1) or by operator and supervisor (study 2). Statistical analysis was performed on the differences between two consecutive days. The lower s$_{\rm r}$ obtained for the AT than A4 recording method (1.7 kg vs. 1.2 kg, respectively) indicates a loss of precision in daily milk recording results due to the passage to the AT recording scheme. In current Slovenian situation (AT recording scheme), the reproducibility standard deviation obtained on two consecutive days was about 1.7 kg, 0.40, 0.11 and 0.09 for milk yield, fat, protein and lactose percentage indicating that we can normally expect the difference between regular control and supervision up to approximately 5 kg, 1.2%, 0.3% and 0.3% for daily milk yield, fat, protein and lactose, respectively. Similar estimates were obtained for repeatability and reproducibility standard deviation. Uncertainty in milk yield results explained by the factors related to the operator pair was minor (0.4–2.5%) compared to herd related factors (11.0–15.1%), while the main part (82.4–88.6%) was due to biological variability and other uncontrolled factors. Lower reproducibility of daily milk yield was associated with small herds and/or lower productivity.Estimation de l'incertitude des résultats de performances dans le contrôle laitier. Deux études ont été menées pour évaluer l'exactitude des mesures (production laitière quotidienne, taux butyreux, taux protéique et teneur en lactose) sur les données du contrôle laitier en Slovénie, respectant la norme ISO 5725, i.e. exprimée par l'écart type de répétabilité (s$_{\rm r})$ et de reproductibilité (s$_{\rm R})$. Le but de l'étude 1 était d'estimer la répétabilité des mesures et de comparer la précision de la méthode de référence ICAR A4 (enregistrement mensuel des données sur les deux traites quotidiennes) à celle de la méthode AT (enregistrement mensuel des données sur une des deux traites, en alternance (matin et soir)). Dans l'étude 2, nous nous sommes intéressés à la reproductibilité des résultats et à l'importance des facteurs liés à l'opérateur (représentant officiel de l'organisation d'enregistrement) et au troupeau ou à la variabilité résiduelle. De plus, la précision de la mesure de la production laitière quotidienne a été étudiée par rapport à la taille du troupeau et à la productivité de la vache. L'étude 1 a été menée sur 332 vaches issues de 14 troupeaux avec 14 opérateurs. L'étude 2 a été effectuée sur 57679 enregistrements recueillis à partir de la base de données centrale slovène du contrôle laitier. Les résultats sur deux jours consécutifs ont été obtenus soit par le même opérateur (étude 1) soit par un opérateur et un contrôleur (étude 2). L'analyse statistique a été effectuée sur les différences entre les deux jours consécutifs. L'écart type de répétabilité a été supérieur avec la méthode AT comparativement à la méthode A4 (1,7 kg contre 1,2 kg, respectivement), ce qui indique une perte de précision des résultats due à l'utilisation de la méthode AT. En Slovénie, dans la situation actuelle (méthode AT), l'écart type de reproductibilité obtenu sur deux jours consécutifs était d'environ 1,7 kg, 0,40 %, 0,11 % et 0,09 % pour la production laitière quotidienne, le taux butyreux, le taux protéique et la teneur en lactose, respectivement. Ceci indique qu'une différence entre les résultats du contrôle par l'opérateur par rapport à celui du contrôleur peuvent normalement atteindre jusqu'à 5 kg, 1,2 %, 0,3 % et 0,3 % pour la production laitière quotidienne, le taux butyreux, le taux protéique et la teneur en lactose, respectivement. Des valeurs très similaires ont été obtenues pour l'écart type de répétabilité et de reproductibilité. La variabilité expliquée par les facteurs liés à l'opérateur (0,4–2,5 %) était faible comparée aux facteurs liés au troupeau (11,0–15,1%), la majeure partie (82,4–88,6 %) était due à la variabilité biologique et à d'autres facteurs non contrôlés. Une reproductibilité inférieure de la production laitière quotidienne a été associée aux petits troupeaux et/ou à une faible productivité