References of "Gengler, Nicolas"
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See detailChallenges and priorities for modelling livestock health and pathogens in the context of climate change
Özkan, Şeyda; Vitali, Andrea; Lacetera, Nicola et al

in Environmental Research (2016), 151(Supplement C), 130-144

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role ... [more ▼]

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. [less ▲]

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

in Journal of Dairy Science (2016), 100

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 detailNovel innovative possibilities for the dairy industry opened by common format of FT-MIR instruments
Grelet, Clément ULiege; Fernandez Pierna, Juan Antonio; Dardenne, Pierre et al

Poster (2016, October 17)

FT-MIR technology is worldwide used for fast and cost effective determination of major milk components. However, due to the different individual response of each instrument the potential of this ... [more ▼]

FT-MIR technology is worldwide used for fast and cost effective determination of major milk components. However, due to the different individual response of each instrument the potential of this technology is currently underexploited as new tools cannot be easily ported to other instruments. Recently a standardization method was developed in order to harmonize the spectral response format between instruments of different brands and models but also across time for each spectrometer. The method matches monthly the infrared response of all spectrometers on the response of a reference instrument, making all machines talking a common language. The objective is to allow the creation and the use of common, new and innovative concepts by pooling resources and sharing data. Using this method, new tools for analysis of milk quality and milk technological properties have been created and shared within the network, as fatty acids and minerals predictions or milk coagulation properties. New concepts requiring a common spectral format have been developed like the untargeted detection of milk contaminant and abnormal milk or the determination of milk geographic origin. Models in relation with the status of the dairy cow were also created and shared as to predict ketosis, negative energy balance or methane emissions. Therefore models can be developed at one place and deployed within the entire network, in which 90 instruments are currently monthly standardized. [less ▲]

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See detailA simple method to predict methane emissions based on milk mid infrared spectra
Vanlierde, Amélie ULiege; Dehareng, Frédéric; Froidmont, Eric et al

Poster (2016, October)

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See detailEffect of curve traits and Age at first calving on productive life of Holstein primiparous Walloon cows
Grayaa, Marwa; Hammami, Hedi ULiege; Hanzen, Christian ULiege et al

Poster (2016, September 02)

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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 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 detailPotential of milk MIR spectra to develop new health phenotypes for dairy cows in the GplusE project
Vanlierde, Amélie ULiege; Grelet, Clément ULiege; Gengler, Nicolas ULiege et al

in Book of abstracts of the 67 rd Annual Meeting of the European Association for Animal Production (2016, August 29)

The current context leads to more and more efficient and rational animal productions. The objective of the “Genotype plus Environment” project (G plus E) is to support novel phenotyping approaches to ... [more ▼]

The current context leads to more and more efficient and rational animal productions. The objective of the “Genotype plus Environment” project (G plus E) is to support novel phenotyping approaches to provide large scale phenotypes for a genomic study and contributing to the sustainability of dairy cow production systems. In this framework, 3 European farms (AFBI-UK, UCD-IRL, AU-DK) collected observations (weight, body condition score, uterine health, residual feed intake, lameness,…) and samples (milk, blood, liver, feed,…) on 135 dairy cows, from calving until day 49. Those data constitute a substantial database which permits to link those phenotypes of interest to potential biomarkers, and especially the mid infrared (MIR) spectra of milk. Predicting phenotypes of interest from milk MIR spectra could be very interesting to detect specific status of cows in a cost effective, rapid and routine process, allowing the acquisition of data at large scale. Classification models have been developed from milk MIR spectra. For example a model built on 60 observations permits to distinguish animals with or without lameness with a good predicted classification of 68 and 71% respectively. Otherwise Regression models have been performed to predict molecules of interest from milk MIR spectra. Some of them can be used with a threshold (eg. level of milk NAGase which is associated to an inflammation status) some others present potential to be predicted quantitatively (eg. IGF1 which is linked to uterine health). This database therefore allows developing tools to predict new health indicators from milk MIR spectra that can be easily implemented at large scale. Those observations will be validated through new data collected with the same protocol from 3 other European farms. [less ▲]

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See detailOptiMIR: Use of MIR spectra to predict multiple cow status as advisory tools for dairy farms
Grelet, Clément ULiege; Gengler, Nicolas ULiege; Bastin, Catherine et al

in Book of Abstracts of the 67th Annual Meeting of the European Federation of Animal Science (2016, August)

Considering the current increasing of herd size, there is a need for precise and rapid information on individual cow state. Mid infrared (MIR) technology is already used worldwide for milk analysis; it ... [more ▼]

Considering the current increasing of herd size, there is a need for precise and rapid information on individual cow state. Mid infrared (MIR) technology is already used worldwide for milk analysis; it allows rapid and cost effective determination of milk composition. The objective of OptiMIR project was to optimize the use of MIR spectra in order to produce indications on cow status thereby providing advisory tools to dairy farmers. Hence phenotypes of interest were collected in several countries and linked to MIR spectra. Since the OptiMIR network comprised 65 MIR instruments in 6 countries, standardisation of MIR data was necessary, allowing the collation of spectral databases and the use by all milk recording organizations (MRO) of the models developed. Using chemometric tools (like PLS regression), predictive models were developed to provide indicators on fine milk composition, on milk biomarkers of physiological imbalance, and directly on status of the cows. Equations predicting fine milk composition such as fatty acids and minerals were consolidated through the OptiMIR network, providing indirectly information on technological properties of milk and cow status. As biomarker of early physiological imbalance, an equation predicting citrate in milk was developed with good accuracy (R²cv=0.86); and as milk biomarkers of ketosis, BHB and acetone were calibrated with fair results (R²cv=0.63 and 0.67 respectively). Direct classification of spectra regarding low vs high risk of ketosis was also performed (84.5% sensitivity and 84.2% specificity). Direct regressions were realized for various negative energy balance criteria (r from 0.43 to 0.57) and enteric methane (R²cv=0.7). All equations are available to be used by MRO on field and converted into advisory tools for the dairy sector. [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 detailContribution à l'optimisation technico-économique des élevages laitiers en Wallonie : l'intervalle vêlage
Dalcq, Anne-Catherine ULiege; Beckers, Yves ULiege; Dogot, Thomas ULiege et al

Conference given outside the academic context (2016)

Au cours des dernières décennies, l’intervalle vêlage des vaches laitières a eu tendance à s’allonger au niveau mondial, européen et belge. Les causes sont multiples : évolution du système de production ... [more ▼]

Au cours des dernières décennies, l’intervalle vêlage des vaches laitières a eu tendance à s’allonger au niveau mondial, européen et belge. Les causes sont multiples : évolution du système de production laitière, augmentation du niveau de production,… Les conséquences sont nombreuses également mais se traduisent-elles par un impact économique pour l’éleveur laitier ? La recherche présentée aujourd’hui se base sur près de 1800 bilans comptables de 400 exploitations laitières, fournis par le service technico-économique de l’Association Wallonne de l’Elevage, entre 2007 et 2014, pour déterminer l’impact économique de la durée de l’intervalle vêlage et définir l’optimum technico-économique de ce paramètre de management. Faut-il garder en tête « le veau par vache et par an » ou est-il intéressant économiquement d’allonger la période entre deux vêlages pour une même vache ? L’étude révèle qu’il y a bien une relation entre l’intervalle vêlage et les résultats économiques d’une exploitation. De plus, il n’y aurait pas un seul optimum d’intervalle vêlage mais plusieurs, dépendant du type d’exploitation et plus particulièrement du mode d’alimentation. L’optimum de l’intervalle vêlage a tendance à être plus court pour les exploitations à alimentation plutôt intensive et plus long pour les exploitations à alimentation plutôt extensive. Cependant il ne s’agit que de tendances observées, un travail plus approfondi doit encore être réalisé pour confirmer ces tendances et définir des objectifs plus précis à poursuivre pour maximiser la rentabilité de son exploitation. [less ▲]

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See detailMilk mid-infrared spectra enable prediction of lactation-stage-dependent methane emissions of dairy cattle within routine population-scale milk recording schemes
Vanlierde, Amélie ULiege; Vanrobays, Marie-Laure ULiege; Gengler, Nicolas ULiege et al

in Animal Production Science (2016), 56(3), 258-264

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in ... [more ▼]

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in vivo methods, the development of an easily measured proxy is desirable. An equation has been developed to predict methane from the mid-infrared (MIR) spectra of milk within routine milk-recording programs. The main goals of this study were to improve the prediction equation for methane emissions from milk MIR spectra and to illustrate its already available usefulness as a high throughput phenotypic screening tool. A total of 532 methane measurements considered as reference data (430 ± 129 g of methane/day) linked with milk MIR spectra were obtained from 165 cows using the SF6 technique. A first derivative was applied to the MIR spectra. Constant (P0), linear (P1) and quadratic (P2) modified Legendre polynomials were computed from each cows stage of lactation (days in milk), at the day of SF6 methane measurement. The calibration model was developed using a modified partial least-squares regression on first derivative MIR data points × P0, first derivative MIR data points × P1, and first derivative MIR data points × P2 as variables. The MIR-predicted methane emissions (g/day) showed a calibration coefficient of determination of 0.74, a cross-validation coefficient of determination of 0.70 and a standard error of calibration of 66 g/day. When applied to milk MIR spectra recorded in the Walloon Region of Belgium (≈2 000 000 records), this equation was useful to study lactational, annual, seasonal, and regional methane emissions. We conclude that milk MIR spectra has potential to be used to conduct high throughput screening of lactating dairy cattle for methane emissions. The data generated enable monitoring of methane emissions and production characteristics across and within herds. Milk MIR spectra could now be used for widespread screening of dairy herds in order to develop management and genetic selection tools to reduce methane emissions. [less ▲]

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See detailImprovement of robustness of forward selection of variables using split datasets: Mid-infrared methane equation
Soyeurt, Hélène ULiege; Vanlierde, Amélie ULiege; Grelet, Clément ULiege et al

in CHIMIOMETRIE XVII - Session 1: Sprectrométrie et prétraitement (2016, January 18)

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See detailOn the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs
Bastin, Catherine; Theron, Léonard ULiege; Laine, Aurélie ULiege et al

in Journal of Dairy Science (2016), 99(5), 4080-4094

Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic ... [more ▼]

Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic improvement in disease resistance and fertility. Hence, indicators are useful in the prediction of genetic merit for fertility and health traits as long as they are easier to measure than direct fitness traits, heritable, and genetically correlated. Considering that changes in (fine) milk composition over a lactation reflect the physiological status of the cow, mid-infrared (MIR) analysis of milk opens the door to a wide range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most being related to negative postpartum energy balance and body fat mobilization (e.g., fat:protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acid traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub)clinical ketosis has been related to milk-based phenotypes such as fat:protein ratio, fatty acids, and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk could be useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worthy of consideration. These include traits related to the disease response of the cow (e.g., lactoferrin), reduced secretory activity (e.g., casein), and the alteration of the blood-milk barrier (e.g., minerals). Moreover, direct MIR prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies. [less ▲]

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See detailHet Kempisch rund. Genomisch onderzoek ter ondersteuning van het ras
François, Liesbeth; Janssens, Steven; Colinet, Frédéric ULiege et al

Conference (2015, November 18)

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See detailStrategies for comparing and combining different genetic and genomic evaluations: A review
Vandenplas, J.; Gengler, Nicolas ULiege

in Livestock Science (2015), 181(Supplement C), 121-130

Exchange of genetic material within and among national populations has increased rapidly with the development of artificial insemination and frozen embryos. This has increased the need to compare genetic ... [more ▼]

Exchange of genetic material within and among national populations has increased rapidly with the development of artificial insemination and frozen embryos. This has increased the need to compare genetic evaluations across populations and ultimately to combine those evaluations for animals of interest. The combination of different sources of information became even more crucial with the development of genomic evaluation. This review summarizes different strategies and algorithms for solving issues related to comparison of methodology for genetic and genomic evaluations and their combination. Reviewed strategies and algorithms for genetic evaluations were categorized as either a post-evaluation or simultaneous combination approach. Post-evaluation approaches make external and internal estimates of genetic merit and their associated reliabilities comparable or combine them after performing external and internal evaluations. Simultaneous combination approaches combine external estimates of genetic merit and their associated reliabilities with internal phenotypic and pedigree data as interval evaluations are calculated. Several of the strategies developed for genetic evaluations were recently adapted for the context of genomic selection, and were mentioned in this paper. [less ▲]

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