MiX99-ohjelmistosta jalostettiin eläinarvostelujen vientituote

MTT:ssa kehitetty MiX99-tietokoneohjelmisto on herättänyt laajaa kansainvälistä kiinnostusta. Sen avulla voidaan arvioida aikaisempaa luotettavammin jalostustyössä tarvittavia eläinten jalostusarvoja.vo

Elopaino, kuntoluokka ja maidon pitoisuudet lehmän energiataseen kuvaajana

201

Detection of bias in animal model pedigree indices of heifers

The objective of the study was to test whether the pedigree indices (PI) of heifers are biased, and if so, whether the magnitude of the bias varies in different groups of heifers. Therefore, two animal model evaluations with two different data sets were computed. Data with all the records from the national evaluation in December 1994 was used to obtain estimated breeding values (EBV) for 305-days’ milk yield and protein yield. In the second evaluation, the PIs were estimated for cows calving the first time in 1993 by excluding all their production records from the data. Three different statistics, a simple t-test, the linear regression of EBV on PI, and the polynomial regression of the difference in the predictions (EBV-PI) on PI, were computed for three groups of first parity Ayrshire cows: daughters of proven sires, daughters of young sires, and daughters of bull dam candidates. A practically relevant bias was found only in the PIs for the daughters of young sires. On average their PIs were biased upwards by 0.20 standard deviations (78.8 kg) for the milk yield and by 0.21 standard deviations (2.2 kg) for the protein yield. The polynomial regression analysis showed that the magnitude of the bias in the PIs changed somewhat with the size of the PIs

Lypsylehmien muuntokelpoisen energian saannin mallinnus rehuhyötysuhdeominaisuuksien kehittämistä varten

201

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

In Press, Corrected Proof201

Lehmien ylläpitotarpeen ja muuntokelpoisen energian käytön tehokkuuden perinnöllinen vaihtelu maidontuotannossa

201

Employing a Monte Carlo algorithm in Newton-type methods for restricted maximum likelihood estimation of genetic parameters

201

Mid-infrared spectroscopic analysis of raw milk to predict the blood nonesterified fatty acid concentrations in dairy cows

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations 1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R-2 values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for negative energy status, indicated by detrimental morning blood plasma NEFA levels (>0.6 mmol/L), could be identified with a sensitivity and specificity of, respectively, 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens an opportunity for regular metabolic screening and improved resilience phenotyping.Peer reviewe

Pohjoismainen eläinmalli maito-ominaisuuksien arvostelemiseksi

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