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See detailPrediction of metabolic clusters in early-lactation dairy cows using models based on milk biomarkers
De Koster, J; Salavati, M; Grelet, Clément ULiege et al

in Journal of Dairy Science (2019), 102(3), 2631-2644

The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and β-hydroxybutyrate (BHB) using ... [more ▼]

The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and β-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immuno-gamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbal-anced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the “balanced” group (n = 43) and were compared with cows in what was referred to as the “other balanced” group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the “imbalanced” group (n = 19) and compared with cows in what was referred to as the “other imbalanced” group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids and BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-β-d-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, par-ity, milk yield features) were used to create predictive models for the metabolic clusters. Accuracy for predic-tion of balanced (80%) and imbalanced (88%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows. [less ▲]

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See detailInvited review: genetics and claw health: opportunities to enhance claw health by genetic selection
Heringstad, B.; Egger-Danner, C.; Charfeddine, N. et al

in Journal of Dairy Science (2018), 101(6), 4801-4821

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues ... [more ▼]

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from −0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future. [less ▲]

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See detailUse of a breeding bull and absence of a calving pen as risk factors for the presence of Mycoplasma bovis in dairy herds.
Gille, Linde ULiege; Callens, J.; Supre, K. et al

in Journal of Dairy Science (2018), 101(9), 8284-8290

Mycoplasma bovis is an important cause of pneumonia and mastitis in cattle throughout the world, often reported as emerging. In absence of an effective vaccine for M. bovis, current prevention and control ... [more ▼]

Mycoplasma bovis is an important cause of pneumonia and mastitis in cattle throughout the world, often reported as emerging. In absence of an effective vaccine for M. bovis, current prevention and control strategies rely on the identification of risk factors for within- and between-herd spread. The objective of this study was to determine the prevalence of M. bovis in Belgian dairy herds and to identify risk factors associated with a positive PCR or antibody ELISA bulk tank milk (BTM) test. A cross-sectional study was performed in 2016 on 100 dairy farms, analyzing BTM using PCR and antibody ELISA. Information on herd-level risk factors focusing on biosecurity and management were collected through a questionnaire and sourced from the national herd identification system (SANITRACE, Animal Health Service Flanders). Multivariable logistic regression was used to identify herd-level risk factors for the presence of M. bovis DNA and antibodies in BTM. The apparent prevalence on BTM was 7 and 17% for PCR and antibody ELISA, respectively. The true prevalence was 7.1% [95% confidence interval (CI) = 2.1-11.5%] and 24.8% (95% CI = 16.4-33.2%). There was no overlap between ELISA- and PCR-positive farms, resulting in a combined true prevalence of 31.8% of the Belgian farms being in recent contact with M. bovis. Risk factor analysis showed that herds with a breeding bull [M. bovis-positive results for 45.5 and 13.6% of herds with and without a bull, respectively, odds ratio = 4.7 (95% CI = 1.1-19.8)] and without a calving pen [M. bovis-positive result in 52.4 and 20.6% of the herds without and with a calving pen, respectively, odds ratio = 3.7 (95% CI = 1.06-12.5)] had higher odds to harbor M. bovis antigen or antibodies in BTM. In conclusion, the present study points to a several fold increase in the prevalence of M. bovis in Belgian dairy herds. The importance of the breeding bull and calving pen in the between- and within-herd spread of M. bovis might have been underestimated in the past. Focusing on these factors might contribute to more effective control programs in the future. [less ▲]

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See detailShort communication: Effect of freezer storage time and thawing method on the recovery of Mycoplasma bovis from bovine colostrum.
Gille, Linde ULiege; Boyen, F.; Van Driessche, L. et al

in Journal of Dairy Science (2018), 101(1), 609-613

Mycoplasma bovis is an important cause of mastitis in dairy cattle, and pneumonia, arthritis, and otitis in calves. Milk and colostrum are considered important sources of infection for calves. knowledge ... [more ▼]

Mycoplasma bovis is an important cause of mastitis in dairy cattle, and pneumonia, arthritis, and otitis in calves. Milk and colostrum are considered important sources of infection for calves. knowledge on the effect of on-farm freezing (-18 degrees C) and thawing methods on the recovery of M. bovis from colostrum samples is missing. In this study, 2 separate experiments were performed. The first experiment consisted of a longitudinal study examining the survival [as measured by log(10) reduction] of 2 M. bovis strains in frozen colostrum over 14 wk. The second experiment examined the effect of different thawing temperatures (45 and 20 degrees C), thawing frequencies (once or twice), and initial colostrum titer (10(4) or 10(6) cfu/mL) on M. bovis survival. A single freeze-thaw cycle led to an approximate 1 log reduction of M. bovis titer, independent of the thawing temperature. Freezing for 14 wk did not significantly further reduce the titer of bacteria compared with freezing for 2 wk. A second freeze-thaw cycle further reduced the M. bovis count by approximately 0.5 log compared with a single freeze-thaw cycle. Thawing temperature and initial bacterial concentration did not significantly affect M. bovis reduction. In conclusion, storage of colostrum samples in the freezer at -18 degrees C during epidemiological studies, herd monitoring, or test and cull programs will probably have little influence on qualitative bacteriological test results for M. bovis. The epidemiological or clinical relevance of an approximate 1 log reduction of M. bovis in colostrum is currently unclear. [less ▲]

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See detailGenetic parameters of mid-infrared methane predictions and their relationships with milk production traits in Holstein cattle
Kandel, Purna ULiege; Vanrobays, Marie-Laure ULiege; Vanlierde, Amélie ULiege et al

in Journal of Dairy Science (2017), 100(7), 5578-5591

Many countries have pledged to reduce greenhouse gases. In this context, the dairy sector is one of the identified sectors to adapt production circumstances to address socio-environmental constraints due ... [more ▼]

Many countries have pledged to reduce greenhouse gases. In this context, the dairy sector is one of the identified sectors to adapt production circumstances to address socio-environmental constraints due to its large carbon footprint related to CH4 emission. This study aimed mainly to estimate (1) the genetic parameters of 2 milk mid-infrared-based CH4 proxies [predicted daily CH4 emission (PME, g/d), and log-transformed predicted CH4 intensity (LMI)] and (2) their genetic correlations with milk production traits [milk (MY), fat (FY), and protein (PY) yields] from first- and second-parity Holstein cows. A total of 336,126 and 231,400 mid-infrared CH4 phenotypes were collected from 56,957 and 34,992 first- and second-parity cows, respectively. The PME increased from the first to the second lactation (433 vs. 453 g/d) and the LMI decreased (2.93 vs. 2.86). We used 20 bivariate random regression test-day models to estimate the variance components. Moderate heritability values were observed for both CH4 traits, and those values decreased slightly from the first to the second lactation (0.25 ± 0.01 and 0.22 ± 0.01 for PME; 0.18 ± 0.01 and 0.17 ± 0.02 for LMI). Lactation phenotypic and genetic correlations were negative between PME and MY in both first and second lactations (−0.07 vs. −0.07 and −0.19 vs. −0.24, respectively). More close scrutiny revealed that relative increase of PME was lower with high MY levels even reverting to decrease, and therefore explaining the negative correlations, indicating that higher producing cows could be a mitigation option for CH4 emission. The PME phenotypic correlations were almost equal to 0 with FY and PY for both lactations. However, the genetic correlations between PME and FY were slightly positive (0.11 and 0.12), whereas with PY the correlations were slightly negative (−0.05 and −0.04). Both phenotypic and genetic correlations between LMI and MY or PY or FY were always relatively highly negative (from −0.21 to −0.88). As the genetic correlations between PME and LMI were strong (0.71 and 0.72 in first and second lactation), the selection of one trait would also strongly influence the other trait. However, in animal breeding context, PME, as a direct quantity CH4 proxy, would be preferred to LMI, which is a ratio trait of PME with a trait already in the index. The range of PME sire estimated breeding values were 22.1 and 29.41 kg per lactation in first and second parity, respectively. Further studies must be conducted to evaluate the effect of the introduction of PME in a selection index on the other traits already included in this index, such as, for instance, fertility or longevity. [less ▲]

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See detailInvited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions
Negussie, Enyew; de Haas, Yvette; Dehareng, Frédéric et al

in Journal of Dairy Science (2017), 100(4), 2433-2453

Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH4) emissions from individual ... [more ▼]

Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH4) emissions from individual cows. Several techniques have been developed to measure CH4 in a research setting but most are not suitable for large-scale recording on farm. Several groups have explored proxies (i.e., indicators or indirect traits) for CH4; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH4 proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The proxies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbiome profiling. Proxies based on rumen samples are generally poor to moderately accurate predictors of CH4, and are costly and difficult to measure routinely on-farm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH4 emission in dairy cows. No single proxy was found to accurately predict CH4, and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of variation in CH4 and one proxy can correct for shortcomings in the other(s). The most important applications of CH4 proxies are in dairy cattle management and breeding for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavorable correlated responses. Finally, although combinations of proxies appear to provide the most accurate estimates of CH4, the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments. [less ▲]

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See detailAssessing the effect of pregnancy stage on milk composition of dairy cows using mid-infrared spectra
Laine, Aurélie ULiege; Bastin, Catherine; Grelet, Clément ULiege et al

in Journal of Dairy Science (2017), 100(4), 28632876

Changes in milk production traits (i.e., milk yield, fat, and protein contents) with the pregnancy stage are well documented. To our knowledge, the effect of pregnancy on the detailed milk composition has ... [more ▼]

Changes in milk production traits (i.e., milk yield, fat, and protein contents) with the pregnancy stage are well documented. To our knowledge, the effect of pregnancy on the detailed milk composition has not been studied so far. The mid-infrared (MIR) spectrum reflects the detailed composition of a milk sample and is obtained by a nonexhaustive and widely used method for milk analysis. Therefore, this study aimed to investigate the effect of pregnancy on milk MIR spectrum in addition to milk production traits (milk yield, fat, and protein contents). A model including regression on the number of days pregnant was applied on milk production traits (milk yield, fat, and protein contents) and on 212 spectral points from the MIR spectra of 9,757 primiparous Holstein cows from Walloon herds. Effects of pregnancy stage were expressed on a relative scale (effect divided by the squared root of the phenotypic variance); this allowed comparisons between effects on milk traits and on 212 spectral points. Effect of pregnancy stage on production traits were in line with previous studies indicating that the model accounted well for the pregnancy effect. Trends of the relative effect of the pregnancy stage on the 212 spectral points were consistent with known and observed effect on milk traits. The highest effect of the pregnancy was observed in the MIR spectral region from 968 to 1,577 cm−1. For some specific wavenumbers, the effect was higher than for fat and protein contents in the beginning of the pregnancy (from 30 to 90 or 120 d pregnant). In conclusion, the effect of early pregnancy can be observed in the detailed milk composition through the analysis of the MIR spectrum of bovine milk. Further analyses are warranted to explore deeply the use of MIR spectra of bovine milk for breeding and management of dairy cow pregnancy. [less ▲]

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See detailPhenotypes to genetically reduce greenhouse gas emissions in dairying
de Haas, Yvette; Pszczola, Marcin; Soyeurt, Hélène ULiege et al

in Journal of Dairy Science (2017), 100(2), 855-870

Phenotypes have been reviewed to select for lower-emitting animals in order to decrease the environmental footprint of dairy cattle products. This includes direct selection for breath measurements, as ... [more ▼]

Phenotypes have been reviewed to select for lower-emitting animals in order to decrease the environmental footprint of dairy cattle products. This includes direct selection for breath measurements, as well as indirect selection via indicator traits such as feed intake, milk spectral data, and rumen microbial communities. Many of these traits are expensive or difficult to record, or both, but with genomic selection, inclusion of methane emission as a breeding goal trait is feasible, even with a limited number of registrations. At present, methane emission is not included among breeding goals for dairy cattle worldwide. There is no incentive to include enteric methane in breeding goals, although global warming and the release of greenhouse gases is a much-debated political topic. However, if selection for reduced methane emission became a reality, there would be limited consensus as to which phenotype to select for: methane in liters per day or grams per day, methane in liters per kilogram of energy-corrected milk or dry matter intake, or a residual methane phenotype, where methane production is corrected for milk production and the weight of the cow. We have reviewed the advantages and disadvantages of these traits, and discuss the methods for selection and consequences for these phenotypes. [less ▲]

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See detailNational single-step genomic method that integrates multi-national genomic information
Vandenplas, J.; Spehar, M.; Potocnik, K. et al

in Journal of Dairy Science (2017), 100(1), 465-478

The aim of this paper was to develop a national single-step genomic BLUP that integrates multi-national genomic estimated breeding values (EBV) and associated reliabilities without double counting ... [more ▼]

The aim of this paper was to develop a national single-step genomic BLUP that integrates multi-national genomic estimated breeding values (EBV) and associated reliabilities without double counting dependent data contributions from the different evaluations. Simultaneous use of all data, including phenotypes, pedigree, and genotypes, is a condition to obtain unbiased EBV. However, this condition is not always fully met, mainly due to unavailability of foreign raw data for imported animals. In dairy cattle genetic evaluations, this issue is traditionally tackled through the multiple across-country evaluation (MACE) of sires, performed by Interbull Centre (Uppsala, Sweden). Multiple across-country evaluation regresses all the available national information onto a joint pedigree to obtain country-specific rankings of all sires without sharing the raw data. In the context of genomic selection, the issue is handled by exchanging sire genotypes and by using MACE information (i.e., MACE EBV and reliabilities), as a valuable source of “phenotypic” data. Although all the available data are considered, these “multi-national” genomic evaluations use multi-step methods assuming independence of various sources of information, which is not met in all situations. We developed a method that handles this by single-step genomic evaluation that jointly (1) uses national phenotypic, genomic, and pedigree data; (2) uses multi-national genomic information; and (3) avoids double counting dependent data contributions from an animal’s own records and relatives’ records. The method was demonstrated by integrating multi-national genomic EBV and reliabilities of Brown Swiss sires, included in the InterGenomics consortium at Interbull Centre, into the national evaluation in Slovenia. The results showed that the method could (1) increase reliability of a national (genomic) evaluation; (2) provide consistent ranking of all animals: bulls, cows, and young animals; and (3) increase the size of a genomic training population. These features provide more efficient and transparent selection throughout a breeding program. [less ▲]

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See detailThiamine supplementation facilitates thiamine transporter expression in the rumen epithelium and attenuates high-grain-induced inflammation in low-yielding dairy cows
Pan, X. H.; Yang, L.; Beckers, Yves ULiege et al

in Journal of Dairy Science (2017), 100(7), 5329-5342

An experiment was conducted to uncover the effects of increasing dietary grain levels on expression of thiamine transporters in ruminal epithelium, and to assess the protective effects of thiamine against ... [more ▼]

An experiment was conducted to uncover the effects of increasing dietary grain levels on expression of thiamine transporters in ruminal epithelium, and to assess the protective effects of thiamine against high-grain-induced inflammation in dairy cows. Six rumen-fistulated, lactating Holstein dairy cows (627 ± 16.9 kg of body weight, 180 ± 6 d in milk; mean ± standard deviation) were randomly assigned to a replicated 3 × 3 Latin square design trial. Three treatments were control (20% dietary starch, dry matter basis), high-grain diet (HG, 33.2% dietary starch, DM basis), and HG diet supplemented with 180 mg of thiamine/kg of dry matter intake. On d 19 and 20 of each period, milk performance was measured. On d 21, ruminal pH, endotoxic lipopolysaccharide (LPS), and thiamine contents in rumen and blood, and plasma inflammatory cytokines were detected; a rumen papillae biopsy was taken on d 21 to determine the gene and protein expression of toll-like receptor 4 (TLR4) signaling pathways. The HG diet decreased ruminal pH (5.93 vs. 6.49), increased milk yield from 17.9 to 20.2 kg/d, and lowered milk fat and protein from 4.28 to 3.83%, and from 3.38 to 3.11%, respectively. The HG feeding reduced thiamine content in rumen (2.89 vs. 8.97 μg/L) and blood (11.66 vs. 17.63 μg/L), and the relative expression value of thiamine transporter-2 (0.37-fold) and mitochondrial thiamine pyrophosphate transporter (0.33-fold) was downregulated by HG feeding. The HG-fed cows exhibited higher endotoxin LPS in rumen fluid (134,380 vs. 11,815 endotoxin units/mL), and higher plasma concentrations of lipopolysaccharide binding protein and pro-inflammatory cytokines when compared with the control group. The gene and protein expression of tumor necrosis factor α (TNFα), IL1B, and IL6 in rumen epithelium increased when cows were fed the HG diet, indicating that local inflammation occurred. The depressions in ruminal pH, milk fat, and protein of HG-fed cows were reversed by thiamine supplementation. Thiamine supplementation increased thiamine contents in rumen and blood, and also upregulated the relative expression of thiamine transporters compared with the HG group. Thiamine supplementation decreased ruminal LPS (49,361 vs. 134,380 endotoxin units/mL) and attenuated the HG-induced inflammation response as indicated by a reduction in plasma IL6, and decreasing gene and protein expression of pro-inflammatory cytokines in rumen epithelium. Western bottling analysis showed that thiamine suppressed the protein expression of TLR4 and the phosphorylation of nuclear factor kappa B (NFκB) unit p65. In conclusion, HG feeding inhibits thiamine transporter expression in ruminal epithelium. Thiamine could attenuate the epithelial inflammation during high-grain feeding, and the protective effects may be due to its ability to suppress TLR4-mediated NFκB signaling pathways. © 2017 American Dairy Science Association [less ▲]

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See detailStandardization of milk mid-infrared spectrometers for the transfer and use of multiple models
Grelet, Clément ULiege; Pierna, J. A. Fernández; Dardenne, P. et al

in Journal of Dairy Science (2017), 100(10), 7910-7921

An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows ... [more ▼]

An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching “slave” instruments to a common reference, the “master.” The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk. [less ▲]

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See detailInvited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying
de Haas, Yvette; Pszczola, Marcin; Soyeurt, Hélène ULiege et al

in Journal of Dairy Science (2017), 100(2), 855-870

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See detailInvited review: Opportunities for genetic improvement of metabolic diseases
Pryce, J. E.; Gaddis Parker, K. L.; Koeck, A. et al

in Journal of Dairy Science (2016), 99(9), 6855-6873

Metabolic disorders are disturbances to one or more of the metabolic processes in dairy cattle. Dysfunction of any of these processes is associated with the manifestation of metabolic diseases or ... [more ▼]

Metabolic disorders are disturbances to one or more of the metabolic processes in dairy cattle. Dysfunction of any of these processes is associated with the manifestation of metabolic diseases or disorders. In this review, data recording, incidences, genetic parameters, predictors, and status of genetic evaluations were examined for (1) ketosis, (2) displaced abomasum, (3) milk fever, and (4) tetany, as these are the most prevalent metabolic diseases where published genetic parameters are available. The reported incidences of clinical cases of metabolic disorders are generally low (less than 10% of cows are recorded as having a metabolic disease per herd per year or parity/lactation). Heritability estimates are also low and are typically less than 5%. Genetic correlations between metabolic traits are mainly positive, indicating that selection to improve one of these diseases is likely to have a positive effect on the others. Furthermore, there may also be opportunities to select for general disease resistance in terms of metabolic stability. Although there is inconsistency in published genetic correlation estimates between milk yield and metabolic traits, selection for milk yield may be expected to lead to a deterioration in metabolic disorders. Under-recording and difficulty in diagnosing subclinical cases are among the reasons why interest is growing in using easily measurable predictors of metabolic diseases, either recorded on-farm by using sensors and milk tests or off-farm using data collected from routine milk recording. Some countries have already initiated genetic evaluations of metabolic disease traits and currently most of these use clinical observations of disease. However, there are opportunities to use clinical diseases in addition to predictor traits and genomic information to strengthen genetic evaluations for metabolic health in the future. [less ▲]

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See detailRandom forest estimation of genomic breeding values for disease susceptibility over different disease incidences and genomic architectures in simulated cow calibration groups
Naderi Darbaghshahi, Saeid ULiege; Yin, T.; König, S.

in Journal of Dairy Science (2016), 99(9), 7261-7273

A simulation study was conducted to investigate the performance of random forest (RF) and genomic BLUP (GBLUP) for genomic predictions of binary disease traits based on cow calibration groups. Training ... [more ▼]

A simulation study was conducted to investigate the performance of random forest (RF) and genomic BLUP (GBLUP) for genomic predictions of binary disease traits based on cow calibration groups. Training and testing sets were modified in different scenarios according to disease incidence, the quantitative-genetic background of the trait (h2 = 0.30 and h2 = 0.10), and the genomic architecture [725 quantitative trait loci (QTL) and 290 QTL, populations with high and low levels of linkage disequilibrium (LD)]. For all scenarios, 10,005 SNP (depicting a low-density 10K SNP chip) and 50,025 SNP (depicting a 50K SNP chip) were evenly spaced along 29 chromosomes. Training and testing sets included 20,000 cows (4,000 sick, 16,000 healthy, disease incidence 20%) from the last 2 generations. Initially, 4,000 sick cows were assigned to the testing set, and the remaining 16,000 healthy cows represented the training set. In the ongoing allocation schemes, the number of sick cows in the training set increased stepwise by moving 10% of the sick animals from the testing set to the training set, and vice versa. The size of the training and testing sets was kept constant. Evaluation criteria for both GBLUP and RF were the correlations between genomic breeding values and true breeding values (prediction accuracy), and the area under the receiving operating characteristic urve (AUROC). Prediction accuracy and AUROC increased for both methods and all scenarios as increasing percentages of sick cows were allocated to the training set. Highest prediction accuracies were observed for disease incidences in training sets that reflected the population disease incidence of 0.20. For this allocation scheme, the largest prediction accuracies of 0.53 for RF and of 0.51 for GBLUP, and the largest AUROC of 0.66 for RF and of 0.64 for GBLUP, were achieved using 50,025 SNP, a heritability of 0.30, and 725 QTL. Heritability decreases from 0.30 to 0.10 and QTL reduction from 725 to 290 were associated with decreasing prediction accuracy and decreasing AUROC for all scenarios. This decrease was more pronounced for RF. Also, the increase of LD had stronger effect on RF results than on GBLUP results. The highest prediction accuracy from the low LD scenario was 0.30 from RF and 0.36 from GBLUP, and increased to 0.39 for both methods in the high LD population. Random forest successfully identified important SNP in close map distance to QTLexplaining a high proportion of the phenotypic trait variations. [less ▲]

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See detailChanges throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra
Vanrobays, Marie-Laure ULiege; Bastin, Catherine; Vandenplas, J. et al

in Journal of Dairy Science (2016), 99(9), 7247-7260

Abstract The aim of this study was to estimate phenotypic and genetic correlations between methane production (Mp) and milk fatty acid contents of first-parity Walloon Holstein cows throughout lactation ... [more ▼]

Abstract The aim of this study was to estimate phenotypic and genetic correlations between methane production (Mp) and milk fatty acid contents of first-parity Walloon Holstein cows throughout lactation. Calibration equations predicting daily Mp (g/d) and milk fatty acid contents (g/100 dL of milk) were applied on milk mid-infrared spectra related to Walloon milk recording. A total of 241,236 predictions of Mp and milk fatty acids were used. These data were collected between 5 and 305 d in milk in 33,555 first-parity Holstein cows from 626 herds. Pedigree data included 109,975 animals. Bivariate (i.e., Mp and a fatty acid trait) random regression test-day models were developed to estimate phenotypic and genetic parameters of Mp and milk fatty acids. Individual short-chain fatty acids (SCFA) and groups of saturated fatty acids, SCFA, and medium-chain fatty acids showed positive phenotypic and genetic correlations with Mp (from 0.10 to 0.16 and from 0.23 to 0.30 for phenotypic and genetic correlations, respectively), whereas individual long-chain fatty acids (LCFA), and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed null to positive phenotypic and genetic correlations with Mp (from −0.03 to 0.13 and from −0.02 to 0.32 for phenotypic and genetic correlations, respectively). However, these correlations changed throughout lactation. First, de novo individual and group fatty acids (i.e., C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, SCFA group) showed low phenotypic or genetic correlations (or both) in early lactation and higher at the end of lactation. In contrast, phenotypic and genetic correlations between Mp and C16:0, which could be de novo synthetized or derived from blood lipids, were more stable during lactation. This fatty acid is the most abundant fatty acid of the saturated fatty acid and medium-chain fatty acid groups of which correlations with Mp showed the same pattern across lactation. Phenotypic and genetic correlations between Mp and C17:0 and C18:0 were low in early lactation and increased afterward. Phenotypic and genetic correlations between Mp and C18:1 cis-9 originating from the blood lipids were negative in early lactation and increased afterward to become null from 18 wk until the end of lactation. Correlations between Mp and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed a similar or intermediate pattern across lactation compared with fatty acids that compose them. Finally, these results indicate that correlations between Mp and milk fatty acids vary following lactation stage of the cow, a fact still often ignored when trying to predict Mp from milk fatty acid profile. [less ▲]

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See detailDevelopment of Fourier transform mid-infrared calibrations to predict acetone, β-hydroxybutyrate, and citrate contents in bovine milk through a European dairy network
Grelet, Clément ULiege; Bastin, Catherine ULiege; Gele, M et al

in Journal of Dairy Science (2016), 99(6), 4816-4825

To manage negative energy balance and ketosis in dairy farms, rapid and cost-effective detection is needed. Among the milk biomarkers that could be useful for this purpose, acetone and β-hydroxybutyrate ... [more ▼]

To manage negative energy balance and ketosis in dairy farms, rapid and cost-effective detection is needed. Among the milk biomarkers that could be useful for this purpose, acetone and β-hydroxybutyrate (BHB) have been proved as molecules of interest regarding ketosis and citrate was recently identified as an early indicator of negative energy balance. Because Fourier transform mid-infrared spectrometry can provide rapid and cost-effective predictions of milk composition, the objective of this study was to evaluate the ability of this technology to predict these biomarkers in milk. Milk samples were collected in commercial and experimental farms in Luxembourg, France, and Germany. Acetone, BHB, and citrate contents were determined by flow injection analysis. Milk mid-infrared spectra were recorded and standardized for all samples. After edits, a total of 548 samples were used in the calibration and validation data sets for acetone, 558 for BHB, and 506 for citrate. Acetone content ranged from 0.020 to 3.355 mmol/L with an average of 0.103 mmol/L; BHB content ranged from 0.045 to 1.596 mmol/L with an average of 0.215 mmol/L; and citrate content ranged from 3.88 to 16.12 mmol/L with an average of 9.04 mmol/L. Acetone and BHB contents were log-transformed and a part of the samples with low values was randomly excluded to approach a normal distribution. The 3 edited data sets were then randomly divided into a calibration data set (3/4 of the samples) and a validation data set (1/4 of the samples). Prediction equations were developed using partial least square regression. The coefficient of determination (R2) of cross-validation was 0.73 for acetone, 0.71 for BHB, and 0.90 for citrate with root mean square error of 0.248, 0.109, and 0.70 mmol/L, respectively. Finally, the external validation was performed and R2 obtained were 0.67 for acetone, 0.63 for BHB, and 0.86 for citrate, with respective root mean square error of validation of 0.196, 0.083, and 0.76 mmol/L. Although the practical usefulness of the equations developed should be further verified with other field data, results from this study demonstrated the potential of Fourier transform mid-infrared spectrometry to predict citrate content with good accuracy and to supply indicative contents of BHB and acetone in milk, thereby providing rapid and cost-effective tools to manage ketosis and negative energy balance in dairy farms. [less ▲]

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See detailCapitalizing on fine milk composition for breeding and management of dairy cows
Gengler, Nicolas ULiege; Soyeurt, Hélène ULiege; Dehareng, Fréderic et al

in Journal of Dairy Science (2016), 99(5), 4071-4079

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of ... [more ▼]

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, and their health, behavior, and well-being as well as their environmental impact and the quality of their products (i.e., milk and subsequently dairy products). Milk composition has been identified as an important source of information because it could reflect, at least partially, all these elements. Major conventional milk components such as fat, protein, urea, and lactose contents are routinely predicted by mid-infrared (MIR) spectrometry and have been widely used for these purposes. But, milk composition is much more complex and other nonconventional milk components, potentially predicted by MIR, might be informative. Such new milk-based phenotypes should be considered given that they are cheap, rapidly obtained, usable on a large scale, robust, and reliable. In a first approach, new phenotypes can be predicted from MIR spectra using techniques based on classical prediction equations. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate) that can be then useful for management and breeding purposes. An innovation was to consider the longitudinal nature of the relationship between the trait of interest and the MIR spectra (e.g., to predict methane from MIR). By avoiding intermediate steps, prediction errors can be minimized when traits of interest (e.g., methane, energy balance, ketosis) are predicted directly from MIR spectra. In a second approach, research is ongoing to detect and exploit patterns in an innovative manner, by comparing observed with expected MIR spectra directly (e.g., pregnancy). All of these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality, and mitigate environmental impact. Under the condition that MIR data are available on a large scale, phenotypes for these traits will allow genetic and genomic evaluations. Introduction of novel traits into the breeding objectives will need additional research to clarify socio-economic weights and genetic correlations with other traits of interest. [less ▲]

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See detailModeling heat stress under different environmental conditions
Carabano, Maria-Jesus; Logar, Betka; Bormann, Jeanne et al

in Journal of Dairy Science (2016), 99(5), 37983814

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at ... [more ▼]

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across three European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat and protein test day data from official milk recording for years 1999 to 2010 in four Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO) and Southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature and humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) in SLO and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units towards larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared to quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70 - 0.80) than for SPA (0.83 - 0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA. [less ▲]

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See detailRelationship between thiamine and subacute ruminal acidosis induced by a high-gran diet in dairy cows
Pan, Xiaohua; Yang, L.; Xue, F.G. et al

in Journal of Dairy Science (2016), 99(11), 8790-8801

Two experiments were conducted to reveal the effects of grain-induced subacute rumen acidosis (SARA) on thiamine status in blood and rumen fluid in dairy cows. In both experiments, 6 multiparous, rumen ... [more ▼]

Two experiments were conducted to reveal the effects of grain-induced subacute rumen acidosis (SARA) on thiamine status in blood and rumen fluid in dairy cows. In both experiments, 6 multiparous, rumen-fistulated Holstein dairy cows were used in a 2-treatment, 2-period crossover design. Each experimental period consisted of 21 d (total of 42 d). Experiment 1 was to investigate the effects of SARA on thiamine status in blood and rumen fluid. Treatments were either control (20% starch, dry matter basis) or SARA-inducing diet (SAID, 33.2% starch, dry matter basis). In experiment 2, the effects of dietary thiamine supplementation on attenuating SARA and ruminal fermentation characteristics in dairy cows were studied. All cows received the same SAID diet during the whole experimental period; treatments were with or without thiamine (180 mg of thiamine/kg of dry matter intake). In both experiments, rumen fluid samples were collected at 0, 3, 6, 9, and 12 h after morning feeding on d 21 and 42 of the experiments for measurement of pH, thiamine, volatile fatty acid, and lactate contents. Peripheral blood was also collected at 3 h after morning feeding on d 21 and 42 to measure thiamine, carbohydrate metabolites, and enzyme activities. In experiment 1, cows fed the SAID diet had lower ruminal and plasma thiamine concentrations and higher lactate than cows fed the control diet. The ruminal thiamine contents were positively related to pH and the concentrations of acetate in the rumen, and negatively correlated with the lactate contents. Experiment 2 demonstrated that ruminal pH and the concentrations of thiamine, acetate, and total volatile fatty acids in the rumen were increased, whereas ruminal lactate contents were reduced by thiamine supplementation. The concentrations of lactate and the activity of lactate dehydrogenase in blood were reduced in the thiamine supplemented group, and the opposite was true for the nonesterified fatty acids and α-ketoneglutarate dehydrogenase contents. In conclusion, the thiamine status was affected by SARA in dairy cows and ruminal infusion of thiamine could helpattenuate SARA by improving the proportions of ruminal volatile fatty acids and reducing lactate contents in rumen fluid and blood. [less ▲]

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