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See detailPotential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation
Grelet, Clément; Froidmont, Éric; Foldager, Leslie et al

in Journal of Dairy Science (2020), 103(5), 4435-4445

Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and ... [more ▼]

Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and large-scale phenotyping methods are required to improve NUE through genetic selection and by feeding and management strategies. The aim of this study was to evaluate the possibility of using mid-infrared (MIR) spectra of milk to predict individual dairy cow NUE during early lactation. Data were collected from 129 Holstein cows, from calving until 50 d in milk, in 3 research herds (Denmark, Ireland, and the UK). In 2 of the herds, diets were designed to challenge cows metabolically, whereas a diet reflecting local management practices was offered in the third herd. Nitrogen intake (kg/d) and nitrogen excreted in milk (kg/d) were calculated daily. Nitrogen use efficiency was calculated as the ratio between nitrogen in milk and nitrogen intake, and expressed as a percentage. Individual daily values for NUE ranged from 9.7 to 81.7%, with an average of 36.9% and standard deviation of 10.4%. Milk MIR spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or sampling periods. Regression models predicting NUE using milk MIR spectra were developed on 1,034 observations using partial least squares or support vector machines regression methods. The models were then evaluated through (1) a cross-validation using 10 subsets, (2) a cow validation excluding 25% of the cows to be used as a validation set, and (3) a diet validation excluding each of the diets one by one to be used as validation sets. The best statistical performances were obtained when using the support vector machines method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. In cross-validation, the best model predicted NUE with a coefficient of determination of cross-validation of 0.74 and a relative error of 14%, which is suitable to discriminate between low- and high-NUE cows. When performing the cow validation, the relative error remained at 14%, and during the diet validation the relative error ranged from 12 to 34%. In the diet validation, the models showed a lack of robustness, demonstrating difficulties in predicting NUE for diets and for samples that were not represented in the calibration data set. Hence, a need exists to integrate more data in the models to cover a maximum of variability regarding breeds, diets, lactation stages, management practices, seasons, MIR instruments, and geographic regions. Although the model needs to be validated and improved for use in routine conditions, these preliminary results showed that it was possible to obtain information on NUE through milk MIR spectra. This could potentially allow large-scale predictions to aid both further genetic and genomic studies, and the development of farm management tools. © 2020 American Dairy Science Association [less ▲]

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See detailLe marc de pomme en post-sevrage améliore-t-il les performances et la santé digestive du porcelet ?
Dufourny, Sandrine ULiege; Antoine, Nadine; Pitchugina, Elena et al

Poster (2020, February)

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See detailStrategies of the Walloon dairy producersfaced to the uncertain dairy future
Dalcq, Anne-Catherine ULiege; Dogot, Thomas ULiege; Soyeurt, Hélène ULiege et al

Conference (2020, January 31)

This study observes the strategies, and their determinants, of the Walloon dairy producersfaced to the post quota perspective through the realisation of 245 surveys, conducted from November 2014 to ... [more ▼]

This study observes the strategies, and their determinants, of the Walloon dairy producersfaced to the post quota perspective through the realisation of 245 surveys, conducted from November 2014 to February 2015. It highlights how dairy production companies plan to evolve to cope with this great change in the sector and so how will move the production of our dairy products. Three kinds of strategical variables were defined and related to the evolution of milk production (MP) [the producerswho increase MP (HighMP) vs. keep constant MP (ConstantMP) vs. stop MP]; the valorisation of MP [alternative (ValMP)vs. classical] and the diversification of activities [with (DivMP) vs. without such activities]. The relationships between the chosen strategies and the quantitative technical variables were studied using generalised linear models. The independence between qualitative technical variables and the strategical variables was tested using Chi Square test. HighMP and ConstantMP producersrepresent 38.4% and 53.9% of respondents, respectively. HighMP producerswere significantly more declared as legal entity (p-value = 0.03), had more family members on the farm (p-value<0.01), larger agricultural area in property (p-value = 0.03) and higher MP quota(p-value = 0.01)compared to ConstantMP producers. Only 9.8% of respondents decide to valorise differently MP. ValMP producerstend to have more employees (p-value = 0.08) and an agricultural area less fragmented (p-value = 0.07)than classical producers. A total of 7.8% of respondents decide to develop other activities. DivMP producerstend to have more employees (p-value = 0.10), more agricultural area in property (p-value = 0.03) and a more recent year of installation (p-value < 0.01). Finally, 44.9% of ConstantMP producersdo not want to start an alternative valorisation of MP and diversify their activities. In conclusion, a relationship exists between, amongst others, the legal status, workforce available, characteristics of the agricultural area, the dairy production and the strategy chosen by the Walloon dairy producers. [less ▲]

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See detailEffects of hydrolysable tannin-treated grass silage on milk yield and composition, nitrogen partitioning and nitrogen isotopic discrimination in lactating dairy cows
Herremans, Sophie; Decruyenaere, Virginie; Cantalapiedra-Hijar, G. et al

in Animal (2020), 00

The objective of this study was to evaluate the effects of oak tannin extract (OTE) added in forage before ensiling on dairy cows fed at 92% of their digestible protein requirements. Six multiparous ... [more ▼]

The objective of this study was to evaluate the effects of oak tannin extract (OTE) added in forage before ensiling on dairy cows fed at 92% of their digestible protein requirements. Six multiparous lactating Holstein cows were used in a crossover design (two treatments × two periods). The control treatment (CON) was based on a diet including 50% of grass silage, whereas the experimental treatment (TAN) included grass silage sprayed with OTE (26 g/kg DM) just before baling. Milk yield (on average 24 kg fat protein corrected milk per day) was not affected, but both milk and rumen fatty acids profiles were impacted by OTE. Nitrogen intake (415 g N per cow per day) and nitrogen use efficiency (NUE; 0.25 on average) were not affected, but a shift from urine (-8% of N intake relatively to control, P = 0.06) to faecal N (+5%; P = 0.004) was observed with the TAN diet (P ≤ 0.05). Nitrogen apparent digestibility was thus reduced for TAN (-3%; P ≤ 0.05). The effect of OTE on ruminal and milk FA profiles suggests an impact on rumen microbiota. Nitrogen isotopic discrimination between animal proteins and diet ("15N) was evaluated as a proxy for NUE. While no differences in NUE were observed across diets, a lower "15N of plasma proteins was found when comparing TAN v. CON diets. This finding supports the concept that "15N would mainly sign the N partitioning at the metabolic level rather than the overall NUE, with the latter also being impacted by digestive processes. Our results agree with a N shift from urine to faeces, and this strategy can thus be adopted to decrease the environmental impact of ruminant protein feeding. © The Animal Consortium 2019. [less ▲]

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See detailContribution of milk mid-infrared spectrum to improve the accuracy of test-day body weight predicted from stage, lactation number, month of test and milk yield
Soyeurt, Hélène ULiege; Froidmont, Éric; Dufrasne, Isabelle ULiege et al

in Livestock Science (2019), 227(2019), 82-89

A regular and repeated recording of body weight (BW) is useful information for herd management. BW can bepredicted regularly from animal characteristics such as age, lactation number, or lactation stage ... [more ▼]

A regular and repeated recording of body weight (BW) is useful information for herd management. BW can bepredicted regularly from animal characteristics such as age, lactation number, or lactation stage. Those traits areunfortunately animal unspecific. Adding animal specific information, which can be easily obtained on a largescale, to the BW prediction would be of utmost importance. There are good scientific reasons to suspect linksbetween BW and animal specific characteristics, available in a repeated fashion, such as milk yield and milkcomposition. This study aimed to demonstrate the feasibility of predicting test-day BW from stage, lactationnumber, month of test, milk yield and mid-infrared spectra, representing milk composition. Five models weretested initially from 721 BW records collected in 6 herds: day in milk + number of lactation (equation 1a);equation1a + milk yield (equation 1b); only spectral data (equation 1c); equation 1c + equation 1a (equation2); equation 2 + milk yield (equation 3). Then 3 other equations included the same explicative variables, exceptthat the spectral data were regressed using second order Legendre Polynomials (PL) to take into account changesof spectral data within lactation. Equation 1a and 1b were built using linear regressions and equation 1c until 3were built using partial least square regressions. These 3 last equations had a higher number of factors. Adding ofMIR data in the equation increased of 7% the values of cross-validation R² (R²cv). Potential BW outliers werediscarded using a residual analysis based on equation 3. From 662 records, the following statistical parameterswere obtained: the calibration coefficient of determination (R²c) = 0.65, R²cv = 0.61, calibration root meansquared error of prediction (RMSEP)=38 kg, and RMSEPcv=40 kg. Low variation of R²c and RMSEPc valuesobtained from the herd validation confirmed the herd independence of predictions. However, large variabilitywas observed for RMSEPv (37 to 64 kg) suggesting the need to increase the dataset in order to improve therobustness of the equation. By applying the equations on a large spectral database, it was confirmed that theaddition of MIR data allows to better model the BW evolution within lactation. Based on these preliminaryresults, and if a larger validation confirms thesefindings, this approach could be used to develop equations thatare better able to assess BW throughout lactation(s), BW being an important element for management andselection tools. [less ▲]

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See detailBaby-SPIME: A dynamic in vitro piglet model mimicking gut microbiota during the weaning process.
Dufourny, Sandrine ULiege; Everaert, Nadia ULiege; Lebrun, Sarah ULiege et al

in Journal of microbiological methods (2019), 167

The study aimed to adapt the SHIME(R) model, developed to simulate human digestion and fermentation, to a baby-SPIME (baby Simulator of Pig Intestinal Microbial Ecosystem). What constitutes a unique ... [more ▼]

The study aimed to adapt the SHIME(R) model, developed to simulate human digestion and fermentation, to a baby-SPIME (baby Simulator of Pig Intestinal Microbial Ecosystem). What constitutes a unique feature of this model is its twofold objective of introducing an ileal microbial community and mimicking a dietary weaning transition. This model should then be ideally suited to test the dietary weaning strategies of piglets in vitro. Regarding the microbiota, the main phyla making up the model were Firmicutes, Bacteroidetes and Proteobacteria although Bacteroidetes decreased after inoculation (p=0.043 in ileum, p=0.021 in colon) and Delta-Proteobacteria were favoured (p=0.083 in ileum, p=0.043 in colon) compared to Gamma-Proteobacteria. The designed model led to a low representation of Bacilli - especially Lactobacillus sp. in the ileum and a weak representation of Bacteroidia in the proximal colon. However, Mitsuokella and Prevotella were part of the major genera of the model along with Bifidobacterium, Fusobacterium, Megasphaera and Bacteroides. As a result of weaning, two major changes - normally occurring in vivo - were detected in the system: firstly, Firmicutes diminished when Bacteroidetes increased particularly in the proximal colon; secondly, Bacteroides decreased and Prevotella increased (mean value for four runs). In terms of metabolite production, while a ratio acetate: propionate: butyrate of 60:26:14 was obtained in post-weaned colon, the expected inversion of the ratio propionate: butyrate in the post-weaned ileum was unfortunately not observed. To conclude, the so-called baby-SPIME model meets expectations regarding the resident microbiota of the proximal colon bioreactor and the metabolites produced thereof. In terms of the evolution of major groups of bacteria, the in vitro weaning process appeared to be successful. However, higher concentration of butyric acid would have been expected in ileum part of newly weaned piglets, as observed in vivo. The microbiota in the ileum bioreactor seemed in fact to act like a pre-colon. This suggests that microbial profile in ileum bioreactor had to be improved. [less ▲]

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See detailSilage additives to reduce protein degradation during ensiling and evaluation of in vitro ruminal nitrogen degradability
Herremans, Sophie ULiege; Decruyenaere, Virginie; Beckers, Yves ULiege et al

in Grass and Forage Science (2019)

Despite the high degradability of their proteins, grass and legume silages represent an important option to reach more sustainable livestock systems. To improve the nitrogen use efficiency of these crops ... [more ▼]

Despite the high degradability of their proteins, grass and legume silages represent an important option to reach more sustainable livestock systems. To improve the nitrogen use efficiency of these crops, this study assessed the potential of several additives (chestnut tannins, oak tannins, zeolite, erythritol by-product solution and wood molasses) to reduce proteolysis in the silo and in vitro nitrogen degradability. Ryegrass (Lolium multiflorum) and red clover (Trifolium pratense) were ensiled in varying proportions in laboratory-scale silos made of vacuum-packed plastic bags. Dry-matter content, chemical composition, pH, ammonia and volatile fatty acids content were analysed after 34 days of ensiling. Ruminal nitrogen degradability was assessed in vitro (Aufrère & Cartailler, 1988). We observed that the proportion of ammonia in silage was reduced by the addition of oak tannin (−12%) and zeolite (−16%). The addition of zeolite lowered in vitro organic matter digestibility. Rapidly degradable nitrogen (1-hr degradability) was reduced in vitro by both tannins (−6.8% for chestnut and −6.6% for oak) and zeolite (−5.8%), but total degradable nitrogen (24-hr degradability) was only reduced by oak (−6.5%) and chestnut tannins (−7.3%). It suggests that tannins protected proteins from plant and bacterial enzymes by forming a complex that better resists silage fermentations and in vitro protease action. The reduction effects on proteolysis in the silo and on in vitro ruminal nitrogen degradability are limited individually but could be cumulative. Erythritol by-product solution and wood molasses had no effect on silo or in vitro proteolysis. [less ▲]

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See detailOak or chestnut tannin dose responses on silage pH, proteolysis and in vitro digestibility in laboratory-scale silos
Herremans, Sophie ULiege; Decruyenaere, Virginie; Beckers, Yves ULiege et al

in Biotechnologie, Agronomie, Société et Environnement (2019), 23(2), 59-62

Description of the subject. This short note documents the use of hydrolyzable tannins as silage additives to reduce proteolysis thanks to a laboratory-scale ensiling method. Objectives. To study oak (OTE ... [more ▼]

Description of the subject. This short note documents the use of hydrolyzable tannins as silage additives to reduce proteolysis thanks to a laboratory-scale ensiling method. Objectives. To study oak (OTE) and chestnut tannin extract (CTE) dose responses on chemical composition, pH and ammoniacal nitrogen (N-NH3) content of silage. Method. A mixture of cocksfoot, white and red clovers was ensiled in vacuum packs, with OTE or CTE at doses of 0, 10, 30, 50 and 70 g.kg-1 DM. Results. Hydrolyzable tannin extracts decreased N-NH3 content of silage up to 18% (p < 0.05). For the investigated range of doses, OTE induced a linear decrease of N-NH3 content (R² = 0.76) whereas CTE resulted in a quadratic decrease (R² = 0.68). High doses of tannin extracts reduced in vitro organic matter digestibility (OMD) by 3% (p < 0.05). Conclusions. Both tannins reduced proteolysis in silos but highest doses induced a decrease in OMD. [less ▲]

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See detailCH4 emitted by dairy cows estimated from milk MIR spectra: model based on data collected in 7 countries
Vanlierde, Amélie ULiege; Dehareng, Frédéric ULiege; Gengler, Nicolas ULiege et al

in International Conference on Agricultural GHG Emissions and Food Security – Connecting research to policy and practice – Volume of Abstracts (2018, September)

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See detailInfluence of chestnut tannins on in vitro crude protein rumen degradability kinetics of red clover silage
Herremans, Sophie ULiege; Decruyenaere, Virginie; Beckers, Yves ULiege et al

Poster (2018, September)

Chestnut tannins in red clover silage reduce rumen dry matter and crude protein degradation. Adding tannins to silage could lead to better nitrogen use efficiency in ruminants.

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See detailA first approach to predict nitrogen efficiency of dairy cows through milk FT-MIR spectra
Grelet, Clément ULiege; Froidmont, Eric; Hostens, Miel et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August 29)

Protein efficiency has become a key factor in dairy production for both environmental and economic reasons. Cost effective and large-scale phenotyping methods are required to improve this trait through ... [more ▼]

Protein efficiency has become a key factor in dairy production for both environmental and economic reasons. Cost effective and large-scale phenotyping methods are required to improve this trait through genetic selection or feeding and management of cows. The aim of this study is to evaluate the possibility of using MIR spectra of milk to predict protein efficiency of dairy cows. Data were collected from 133 cows, from calving until 50 days in milk, in 3 research herds distributed in Denmark, Ireland and UK. For two herds, diets were designed to challenge cows and induce production diseases. Amounts of protein ingested (kg/day) and fat and protein corrected milk (FPCM, in kg/day) were measured daily. Protein efficiency to produce milk was ’quantified’ by using the ratio “FPCM/protein ingested”. MIR milk spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or periods. Regression models between protein efficiency and MIR milk spectra have been developed on 1145 observations using PLS or SVM methods and a cross-validation was realized using 10 subsets. The model was better in terms of R² of cross-validation and error when using SVM method compared to PLS method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. The best model was obtained by using spectra, milk yield and lactation number as predictors, and SVM modeling with R²cv of 0.75. These preliminary results show that there is a possibility to have information on protein efficiency to produce milk through milk MIR spectra. This could allow large-scale predictions for both genetic studies and farm management. [less ▲]

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See detailPotential of milk FT-MIR spectra to predict metabolic status of cows through blood components and an innovative clustering approach
Grelet, Clément ULiege; Vanlierde, Amélie ULiege; Hostens, Miel et al

in Animal (2018)

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA), and β-hydroxybutyrate (BHB) are ... [more ▼]

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA), and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to 1) evaluate the potential of milk mid-infrared spectra to predict these blood components individually and 2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on 6 experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status were defined by k-means clustering (k= 3) based on the 4 blood components. Milk mid-infrared analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using 4 subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R² of calibration of 0.55, 0.69, 0.49 and 0.77, and R² of cross-validation of 0.44, 0.61, 0.39 and 0.70. While these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the dataset into 3 groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the 3 groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-infrared analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows. [less ▲]

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See detailThe time after feeding alters methane emission kinet- ics in Holstein dry cows fed with various restricted diets
Blaise, Yannick ULiege; Andriamandroso, Andriamasinoro ULiege; Beckers, Yves ULiege et al

in Livestock Science (2018), 217

This study aims to investigate shifts in methane (CH4) emission in cattle in relation to the time after feeding, diet composition, and feed allowance. Four non-cannulated dry Holstein cows were equipped ... [more ▼]

This study aims to investigate shifts in methane (CH4) emission in cattle in relation to the time after feeding, diet composition, and feed allowance. Four non-cannulated dry Holstein cows were equipped with activity and infrared sensors to monitor feeding behavior and CH4 and carbon dioxide (CO2) levels in the breath, continuously and at a frequency of 4 Hz. The second goal pursued, was to assess the methane emission estimation (CH4, L/h) by the CO2-method based on the ratio between CH4 and CO2 in the exhaled air, using metabolic CO2 as a marker. All cows were fed twice a day at 12 h intervals with contrasting isoenergy diets in a cross-over design: LIN100 diet (5562 VEM, i.e. Voedereenheid Melk, Dutch energy unit for milk production, 1 VEM = 6.9 kJ net energy for lactation) composed of haylage, linseed and wheat, and HAY100 (5367 VEM) diet containing only haylage. After a 2 week adaptation period to the diets, 3 days were required for the measurements and immediately after, two additional experimental treatments were applied by reducing the feed allowance to 70% with the same diets to evaluate the impact of the dry matter intake, yielding the two additional treatments HAY70 and LIN70. In addition, two other rumen-cannulated cows were used to monitor time after feeding short-chain fatty acid concentrations in the rumen. On a daily basis, all indicators (daily CH4:CO2 ratio, eructation frequency and CH4 emission) followed the same trend and showed that cows on a hay-based diet produced more CH4 and feed restriction induced different production levels for the same type of diet. The average CH4 emission for the different diets were 6.86 L/h for HAY100 > 6.25 L/h for HAY70 > 4.26 L/h for LIN100 > 3.97 L/h LIN70 (P < 0.001). The LIN100 diet produced 38% lower daily CH4 emissions than HAY100 and reduced the eructation frequency by 44%. During feeding, the eructation frequency was higher (P<0.001) for HAY than LIN diets. This work underlines the daily CH4 emission dynamics observed using the CH4:CO2 ratio in the cow's exhaled air. Methane emissions (L/h) are strongly influenced by the time after feeding time (P < 0.001). They increased for up to 2 hours after the distribution of the meal, and then decreased until the next meal, with shifts between the maximum and the minimum emission of more than 100% for LIN100 and 22% for HAY100. Consistently, the acetate:proprionate ratio was smaller for the LIN100 diet between 2 to 5 hours after the meal (P < 0.001). [less ▲]

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See detailPrediction of energy status of dairy cows using MIR milk spectra
Grelet, Clément ULiege; Vanlierde, Amélie ULiege; Dehareng, Frédéric ULiege et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2017, August 30)

A key task within the GplusE project is to undertake a genetic evaluation using ten thousand cows to improve health traits of dairy cows, with energy status (ES) being a trait of major interest. To ... [more ▼]

A key task within the GplusE project is to undertake a genetic evaluation using ten thousand cows to improve health traits of dairy cows, with energy status (ES) being a trait of major interest. To achieve this, cost effective and large scale phenotyping methods are required. This study was designed to evaluate the possibility of using MIR spectra of milk to predict ES of cows. Data was collected from 241 cows, from calving until 50 days in milk (DIM) in six research herds of the GplusE consortium distributed in Belgium, Denmark, Germany, Ireland, Italy and UK. Milk MIR spectra were collected twice weekly during this period. ES was ’quantified’ by measuring daily energy balance (EB), residual feed intake (RFI), dry matter intake (DMI), and measuring at 14 and 35 DIM blood metabolites/hormones (Glucose, BHB, NEFA and IGF-1). K-means clustering was also performed based on these 4 blood components in order to discriminate 2 groups with healthy vs imbalanced cows. Regression models between each of these variables and MIR milk spectra have been developed using PLS and classification model with SVM method. The R² of cross-validation obtained when predicting EB, RFI, DMI, Glucose, BHB, NEFA and IGF-1 were respectively 0.43, 0.46, 0.47, 0.31, 0.40, 0.28 and 0.48. Discriminant model based on blood metabolite clusters was able to differentiate healthy vs imbalanced cows with sensitivity and specificity of 84% and 81%, respectively. These preliminary results demonstrate that milk MIR spectra have reasonable potential to provide information on ES related variables. This could allow large scale predictions for both genetic studies and farm management. [less ▲]

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See detailIdeal future dairy farm: a Walloon breeders’ point of view
Dalcq, Anne-Catherine ULiege; Soyeurt, Hélène ULiege; Dogot, Thomas ULiege et al

Conference (2017, August 30)

This research aims to characterize the dairy breeders regarding their idea of the ideal future farm ensuring them an income, in order to highlight their present situation and the ways to advise them ... [more ▼]

This research aims to characterize the dairy breeders regarding their idea of the ideal future farm ensuring them an income, in order to highlight their present situation and the ways to advise them towards their wished dairy model. The 245 answers to a survey of breeders, conducted between November 2014 and February 2015 provided information about, amongst others, their wishes concerning the intensification, the specialization, the technological innovation, the kind of workforce, structure, market and milk production (standard vs. differentiated quality milk). Based on this information, a Multiple Correspondence Analysis allowed to create 4 groups of breeders with a similar view of their ideal farm: global-based intensive (GBIb), local-based extensive (LBEb), intermediate and no-opinion breeders. The relationships between these groups and the other recorded qualitative variables as formation needed, obstacles and advantages of breeders organization, of diversification and so forth w ere studied using Chi Square tests and Correspondence Canonical Analysis. A moderate link was observed between the ideal future farm and the current situation of the respondent. This suggested that not all the breeders were in the production system that they considered as most profitable. As a brake to the transformation and diversification, GBIb tended to be more numerous to speak about the uncertainty of the customer loyalty (p-value = 0.07) and LBEb pointed out the size of the investments (p-value = 0.05). LBEb asked more for administrative (p-value = 0.04) and transformation and diversification formations (p-value = 0.03) while GBIb looked more for finance and management formation (p-value = 0.02). In conclusion, there were different ideal dairy farm models considered by the breeders. Their needs were not similar and indicated which tools must be developed and which domain must be studied to support them. [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 detailInnovative silage additives to reduce proteolysis in the silo
Herremans, Sophie ULiege; Decruyenaere, Virginie; Beckers, Yves ULiege et al

Poster (2017, May 10)

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