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Bayesian single-step genomic evaluations combining local and foreign information in Walloon Holsteins
- F. G. Colinet, J. Vandenplas, S. Vanderick, H. Hammami, R. R. Mota, A. Gillon, X. Hubin, C. Bertozzi, N. Gengler
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Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon population in the southern part of Belgium is a good example for such a small-scale population. Wallonia has also a very active community of Holstein breeders requesting high level genetic evaluation services. Single-step Genomic BLUP (ssGBLUP) methods allow the simultaneous use of genomic, pedigree and phenotypic information and could reduce potential biases in the estimation of genomically enhanced breeding values (GEBV). Therefore, in the context of implementing a Walloon genomic evaluation system for Holsteins, it was considered as the best option. However, in contrast to multi-step genomic predictions, natively ssGBLUP will only use local phenotypic information and is unable to use directly important other sources of information coming from abroad, for example Multiple Across Country Evaluation (MACE) results as provided by the Interbull Center (Uppsala, Sweden). Therefore, we developed and implemented single-step Genomic Bayesian Prediction (ssGBayes), as an alternative method for the Walloon genomic evaluations. The ssGBayes method approximated the correct system of equations directly using estimated breeding values (EBV) and associated reliabilities (REL) without any explicit deregression step. In the Walloon genomic evaluation, local information refers to Walloon EBV and REL and foreign information refers to MACE EBV and associated REL. Combining simultaneously all available genotypes, pedigree, local and foreign information in an evaluation can be achieved but adding contributions to left-hand and right-hand sides subtracting double-counted contributions. Correct propagation of external information avoiding double counting of contributions due to relationships and due to records can be achieved. This ssGBayes method computed more accurate predictions for all types of animals. For example, for genotyped animals with low Walloon REL (<0.25) without MACE results but sired by genotyped bulls with MACE results, the average increase of REL for the studied traits was 0.38 points of which 0.08 points could be traced to the inclusion of MACE information. For other categories of genotyped animals, the contribution by MACE information was also high. The Walloon genomic evaluation system passed for the first time the Interbull GEBV tests for several traits in July 2013. Recent experiences reported here refer to its use in April 2016 for the routine genomic evaluations of milk production, udder health and type traits. Results showed that the proposed methodology should also be of interest for other, similar, populations.
Mid-infrared prediction of lactoferrin content in bovine milk: potential indicator of mastitis
- H. Soyeurt, C. Bastin, F. G. Colinet, V. M.-R. Arnould, D. P. Berry, E. Wall, F. Dehareng, H. N. Nguyen, P. Dardenne, J. Schefers, J. Vandenplas, K. Weigel, M. Coffey, L. Théron, J. Detilleux, E. Reding, N. Gengler, S. McParland
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Lactoferrin (LTF) is a milk glycoprotein favorably associated with the immune system of dairy cows. Somatic cell count is often used as an indicator of mastitis in dairy cows, but knowledge on the milk LTF content could aid in mastitis detection. An inexpensive, rapid and robust method to predict milk LTF is required. The aim of this study was to develop an equation to quantify the LTF content in bovine milk using mid-infrared (MIR) spectrometry. LTF was quantified by enzyme-linked immunosorbent assay (ELISA), and all milk samples were analyzed by MIR. After discarding samples with a coefficient of variation between 2 ELISA measurements of more than 5% and the spectral outliers, the calibration set consisted of 2499 samples from Belgium (n = 110), Ireland (n = 1658) and Scotland (n = 731). Six statistical methods were evaluated to develop the LTF equation. The best method yielded a cross-validation coefficient of determination for LTF of 0.71 and a cross-validation standard error of 50.55 mg/l of milk. An external validation was undertaken using an additional dataset containing 274 Walloon samples. The validation coefficient of determination was 0.60. To assess the usefulness of the MIR predicted LTF, four logistic regressions using somatic cell score (SCS) and MIR LTF were developed to predict the presence of mastitis. The dataset used to build the logistic regressions consisted of 275 mastitis records and 13 507 MIR data collected in 18 Walloon herds. The LTF and the interaction SCS × LTF effects were significant (P < 0.001 and P = 0.02, respectively). When only the predicted LTF was included in the model, the prediction of the presence of mastitis was not accurate despite a moderate correlation between SCS and LTF (r = 0.54). The specificity and the sensitivity of models were assessed using Walloon data (i.e. internal validation) and data collected from a research herd at the University of Wisconsin – Madison (i.e. 5886 Wisconsin MIR records related to 93 mastistis events – external validation). Model specificity was better when LTF was included in the regression along with SCS when compared with SCS alone. Correct classification of non-mastitis records was 95.44% and 92.05% from Wisconsin and Walloon data, respectively. The same conclusion was formulated from the Hosmer and Lemeshow test. In conclusion, this study confirms the possibility to quantify an LTF indicator from milk MIR spectra. It suggests the usefulness of this indicator associated to SCS to detect the presence of mastitis. Moreover, the knowledge of milk LTF could also improve the milk nutritional quality.
Review and present status of the TEXTOR radiative improved (RI) mode
- P. E. VANDENPLAS, A. M. MESSIAEN, J. P. H. E. ONGENA, U. SAMM, B. UNTERBERG
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- Journal of Plasma Physics / Volume 59 / Issue 4 / June 1998
- Published online by Cambridge University Press:
- 01 June 1998, pp. 587-610
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From 1990, the boronized TEXTOR tokamak was characterized by an improved confinement (coined the ‘I mode’) at high power that was substantially better than the L mode, but densities had to be limited to n[bar]e0/nGR[lsim ]0.5–0.6, where nGR is the Greenwald density limit. With the injection of Ne, Si or Ar in order to increase the edge radiation and provided that γ=Prad/Ptot[greater, similar]0.5, PNBI-co/Ptot[greater, similar]0.25 and n[bar]e0/nGR[greater, similar]0.75, a further improved confinement called the radiative improved mode (RI mode) was discovered in 1993 on TEXTOR, a tokamak of intermediate size, and confirmed on TEXTOR-94. The radiated power fraction γ can reach 0.9, and the radiation is nearly isotropically distributed over the torus wall. The RI mode is characterized by its ability to obtain simultaneously and stationarily high densities and high confinement. It is linked to a substantial lowering of edge ne, Te and Ti, a reduction in particle transport and a peaking of the density profile. The RI-mode confinement scales on TEXTOR as τE= (n[bar]e0/nGR)τITERH93-P and values up to n[bar]e0/nGR≈1.2 are obtained. There is no detrimental concentration of the seeded impurity at the centre of the plasma. Results of three different interpretative and modelling approaches are in agreement with the improved confinement features; the preliminary indications are that ITG turbulence is strongly reduced. The Z mode observed on ISX-B has a clear resemblance to the RI mode. The very favourable features of the RI mode justify efforts in trying to establish it on larger machines to verify if the present scaling then holds.