Staff Publications

Staff Publications

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    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

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Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning
Phuong, H.N. ; Boer, I.J.M. de; Schmidely, P. ; Friggens, N.C. ; Martin, O. - \ 2015
Journal of Dairy Science 98 (2015)1. - ISSN 0022-0302 - p. 618 - 632.
repeated reproductive-cycles - milk-yield - lactating cow - holstein cows - body-size - cattle - parameters - efficiency - fertility - genotype
This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise.
Factors affecting energy and nitrogen efficiency of dairy cows: A meta-analysis
Phuong, H.N. ; Friggens, N.C. ; Boer, I.J.M. de; Schmidely, P. - \ 2013
Journal of Dairy Science 96 (2013)11. - ISSN 0022-0302 - p. 7245 - 7259.
residual feed-intake - milk protein yield - rumen-protected methionine - dry-matter intake - corn-silage - metabolizable protein - dietary-protein - alfalfa silage - beef-cattle - forage
A meta-analysis was performed to explore the correlation between energy and nitrogen efficiency of dairy cows, and to study nutritional and animal factors that influence these efficiencies, as well as their relationship. Treatment mean values were extracted from 68 peer-reviewed studies, including 306 feeding trials. The main criterion for inclusion of a study in the meta-analysis was that it reported, or permitted calculation of, energy efficiency (Eeff; energy in milk/digestible energy intake) and nitrogen efficiency (Neff; nitrogen in milk/digestible nitrogen intake) at the digestible level (digestible energy or digestible protein). The effect of nutritional and animal variables, including neutral detergent fiber, acid detergent fiber (ADF), digestible energy, digestible protein, proportion of concentrate (PCO), dry matter intake, milk yield, days in milk, and body weight, on Eeff, Neff, and the Neff:Eeff ratio was analyzed using mixed models. The interstudy correlation between Eeff and Neff was 0.62, whereas the intrastudy correlation was 0.30. The higher interstudy correlation was partly due to milk yield and dry matter intake being present in both Eeff and Neff. We, therefore, also explored the Neff:Eeff ratio. Energy efficiency was negatively associated with ADF and PCO, whereas Neff was negatively associated with ADF and digestible energy. The Neff:Eeff ratio was affected by ADF and PCO only. In conclusion, the results indicate a possibility to maximize feed efficiency in terms of both energy and nitrogen at the same time. In other words, an improvement in Eeff would also mean an improvement in Neff. The current study also shows that these types of transverse data are not sufficient to study the effect of animal factors, such as days in milk, on feed efficiency. Longitudinal measurements per animal would probably be more appropriate
Relationship between milk fatty acids and body energy status in Holstein cows
Mc Parland, S. ; Schmidely, P. ; Friggens, N.C. ; Banos, G. ; Soyeurt, H. ; Coffey, M.P. ; Wall, E. ; Veerkamp, R.F. ; Berry, D.P. - \ 2011
In: Proceedings of the Agricultural Research Forum, 12-13 March 2011, Tullamore, Ireland. - - p. 47 - 47.
Evaluation of models to predict the stoichiometry of volatile fatty acid profiles in rumen fluid of lactating Holstein cows
Morvay, Y. ; Bannink, A. ; France, J. ; Kebreab, E. ; Dijkstra, J. - \ 2011
Journal of Dairy Science 94 (2011)6. - ISSN 0022-0302 - p. 3063 - 3080.
dairy-cows - milk-production - corn-silage - alfalfa silage - ruminal fermentation - mechanistic model - nutrient digestion - methane production - feeding-behavior - grazing behavior
Volatile fatty acids (VFA), produced in the rumen by microbial fermentation, are the main energy source for ruminants. The VFA profile, particularly the nonglucogenic (acetate, Ac; butyrate, Bu) to glucogenic (propionate, Pr) VFA ratio (NGR), is associated with effects on methane production, milk composition, and energy balance. The aim of this study was to evaluate extant rumen VFA stoichiometry models for their ability to predict in vivo VFA molar proportions. The models were evaluated using an independent data set consisting of 101 treatments from 24 peer-reviewed publications with lactating Holstein cows. All publications contained a full diet description, rumen pH, and rumen VFA molar proportions. Stoichiometric models were evaluated based on root mean squared prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. Of all models evaluated, the 1998 Friggens model had the lowest RMSPE for Ac and Bu (7.2 and 20.2% of observed mean, respectively). The 2006 Bannink model had the lowest RMSPE and highest CCC for Pr (14.4% and 0.70, respectively). The 2008 Bannink model had comparable predictive performance for Pr to that of the 2006 Bannink model but a larger error due to overall bias (26.2% of MSPE). The 1982 Murphy model provided the poorest prediction of Bu, with the highest RMSPE and lowest CCC (24.6% and 0.15, respectively). The 1988 Argyle and Baldwin model had the highest CCC for Ac with an intermediate RMSPE (0.47 and 8.0%, respectively). The 2006 Sveinbjörnsson model had the highest RMSPE (13.9 and 34.0%, respectively) and lowest CCC (0.31 and 0.40, respectively) for Ac and Pr. The NGR predictions had the lowest RMSPE and highest CCC in the 2 models of Bannink, whereas the lowest predictive performance was in the 2006 Sveinbjörnsson model. It appears that the type of VFA produced is not a simple linear relationship between substrate inputs and pH as currently represented. The analysis demonstrates that most rumen VFA stoichiometric approaches explain a large part of the variation in VFA molar proportions among diets, in particular for Ac, whereas predictive power for Pr and Bu differ largely among approaches. The move toward feed evaluation systems based on animal response might necessitate an improved representation of rumen fermentation, focused on improving our understanding of VFA proportions in diets that vary from the mean.
Representing tissue mass and morphology in mechanistic models of digestive function in ruminants
Bannink, A. ; Dijkstra, J. ; France, J. - \ 2011
In: Modelling nutrient digestion and utilisation in farm animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen Academic Publishers - ISBN 9789086861569 - p. 168 - 175.
Representing changes in morphological and histological characteristics of epithelial tissue in the rumen and intestine and to evaluate their implications for absorption and tissue mass in models of digestive function requires a quantitative approach. The aim of the present study was to quantify tissue mass (M) and absorptive area (AA) from parameters that are easily derived from morphological inspection and histology of tissue biopsies, and to compare this representation with approaches in current model of digestive function. Relatively small changes of 5% in some morphological and histological characteristics were calculated to affect absorptive area (AA) and epithelial tissue mass (M) strongly in the rumen and the intestine of cattle. The cumulative effect of changes in volume, height and width of primary protrusions and of secondary protrusions of the rumen wall was 18% for rumen mucosal AA and 29% for rumen serosal AA. It was 24% for intestinal mucosal AA. The cumulative effect on rumen and intestinal M was 20% and 22%, respectively. The simulations indicate that allometric functions that relate volume or weight to AA and M require exponentiation with an exponent higher than those based on geometric shape or volume.
Modelling the profile of growth in monogastric animals
Kebreab, E. ; Strathe, A.B. ; Nyachoti, C.M. ; Dijkstra, J. ; Lopez, S. ; France, J. - \ 2010
In: Modelling Nutrient Digestion and Utilisation in Farm Animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen : Wageningen Academic Publishers - ISBN 9789086861569 - p. 386 - 393.
Regression procedures for relationships between random variables
Dhanoa, M.S. ; Sanderson, R. ; Lopez, S. ; Dijkstra, J. ; Kebreab, E. ; France, J. - \ 2010
In: Modelling Nutrient Digestion and Utilisation in Farm Animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen : Wageningen Academic Publishers - ISBN 9789086861569 - p. 31 - 39.
Prediction of methane production in beef cattle within a mechanistic digestion model
Ellis, J.L. ; Dijkstra, J. ; Kebreab, E. ; Archibeque, S. ; France, J. ; Bannink, A. - \ 2010
In: Modelling Nutrient Digestion and Utilisation in Farm Animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen : Wageningen Academic Publishers - ISBN 9789086861569 - p. 181 - 188.
A generic multistage compartmental model for interpreting gas production profiles
Lopez, S. ; Dijkstra, J. ; Dhanoa, M.S. ; Bannink, A. ; Kebreab, E. ; France, J. - \ 2010
In: Modelling Nutrient Digestion and Utilisation in Farm Animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen : Wageningen Academic Publishers - ISBN 9789086861569 - p. 139 - 147.
The gas production technique has become a key tool in feed evaluation and rumen fermentation studies. The value of the technique relies on modelling experimental data to obtain estimates of rumen degradation parameters. One of the first models used to describe gas production profiles was the simple exponential equation, although it has some important limitations when applied to gas production curves: (1) the intercept is positive, (2) only fits diminishing returns profiles, and (3) models gas per se (i.e. fails to link gas production to substrate degradation). The first limitation is overcome mathematically by re-parameterisation, making the intercept zero. The second limitation can be resolved by introducing a discrete lag to mimic sigmoidicity or by using sigmoidal functions. The third limitation is overcome by modelling substrate degradation from gas production profiles, so that equations are derived from mechanistic principles, and all parameters have biological meaning. The link between substrate degradation and gas production allows for extent of substrate degradation in the rumen to be determined for a given passage rate. Several multi-phase models have been proposed, but these were originally derived empirically and assumptions made a posteriori. Based on the conceptual difference between stage and phase, a multi-stage approach is proposed, a generic model presented and the accompanying equations derived. A two-stage model with four pools (substrate, intermediate products, fermentation end-products and by-products such as fermentation gas) is illustrated. An interpretation of the breakdown of polysaccharides to monosaccharides (first stage) and the fermentation of these monosaccharides to yield gas and other products (VFA and microbial matter) (second stage) is presented. Gas production profiles were used to demonstrate fitting the two-stage model and to consider its ability to describe gas production curves.
Effects of nutritional strategies on simulated nitrogen excretion and methane emission in dairy cattle
Dijkstra, J. ; France, J. ; Ellis, J.L. ; Kebreab, E. ; Lopez, S. ; Reijs, J.W. ; Bannink, A. - \ 2010
In: Modelling Nutrient Digestion and Utilisation in Farm Animals / Sauvant, D., van Milgen, J., Faverdin, P., Friggens, N., Wageningen : Wageningen Academic Publishers - ISBN 9789086861569 - p. 394 - 402.
To assess the relation between emission of methane (CH4) and faecal and urinary losses of nitrogen (N) in dairy cattle, various dietary strategies were evaluated using a mechanistic model of fermentation and digestion processes. To simulate faecal and urinary composition, an extant dynamic, mechanistic model of rumen function and post-absorptive nutrient supply was extended with static equations that describe intestinal digestion and hindgut fermentation. The extended model predicts organic matter, carbon and N output in faeces and urine. Methane emissions were simulated using the same model including a mechanistic description of methanogenesis in the rumen and in the hindgut. Four different types of grass silage were explored at high and low N fertilization levels and early or late cutting. For each grass silage, 10 supplementation strategies that differed in level and type of supplement (no supplement, maize silage, straw, beet pulp, potatoes) and level of concentrate (20 or 40% of total diet DM) were studied. Simulated total N and CH4 excretion ranged from 211 to 588 g/d and 334 to 441 g/d, respectively, with a small, positive correlation (r2=0.15). When expressed per unit fat and protein corrected milk (FPCM), a reduced N excretion (g N/kg FPCM) was associated with increased CH4 emission (g CH4 / kg FPCM) although the coefficient of determination was small (r2=0.22). This relationship varied between different treatments. For example, reducing N fertilization level lowered N excretion per kg FPCM, but increased CH4 emission per kg FPCM, whereas supplementation with maize silage reduced both N excretion and CH4 emission per kg FPCM. The ratio of urea-N in urine to total N excretion was negatively related to emission of CH4 per kg FPCM (r2=0.54). This is of particular concern since urea in the urine, being quickly converted to ammonia, is susceptible to rapid volatilization. The present simulations indicate that measures to reduce N pollution from dairy cattle may increase CH4 emission and highlight an important area for experimental research.
Explaining variation in energy balance using high density SNP information
Verbyla, K. ; Calus, M.P.L. ; Haas, Y. de; Mulder, H.A. ; Veerkamp, R.F. - \ 2010
Introduction Severe negative energy balance (EB) has been shown to have harmful effects on health and fertility. Estimates of heritability and genetic correlations suggest that EB is not only a consequence of a poor match between nutrition and production, but is also genetically induced (Veerkamp et al.; 2003, Friggens et al., 2007). The importance of EB to animal breeders comes from the high costs of involuntary culling caused by poor health or failing to establish a successful pregnancy caused by impaired ovarian function or delayed resumption of oestrous cycles. Currently, high density SNP chips are available to investigate the genetics of EB and the use of genomic selection could increase the ability to select for complex traits such as EB. The aim of this study was to demonstrate that high density SNP information can be used to estimate genomic breeding values (GEBV) for genetically induced EB. Material and methods A total of 588 Holstein-Friesian heifers with known pedigree born between 1990 and 1997 were genotyped for the Illumina 50K SNP panel (54,001 SNPs in total). Quality control and pedigree checking was performed and 43,011 SNPs and 548 animals were retained. During the first 15 wk of lactation live weight, feed intake, and milk yield were measured on 527 of these heifers. All heifers were fed ad libitum. Fat, protein, and lactose yields were measured at a fixed day of the week. Feed intake was recorded daily using automated feed intake units. EB (MJ/d) was calculated as the difference between energy intake and calculated energy requirements for milk, fat, and protein yields and maintenance costs as a function of live weight. The EB values were averaged across 14 weeks (2-15) to provide the EB phenotype that was used. A 10-fold cross validation approach was carried out, such that the data was randomly partitioned into 10 subsets. Each subset was retained once as the validation dataset and the remaining 9 sets were used to predict the GEBV of those animals in the validation set. The model described in Calus et al., (2008) was used to predict the GEBV. The GEBV were calculated as the sum of the estimated SNP effects and the polygenic effect. The same data subsets and approach were used with a simple polygenic model excluding the SNP information for comparison. The GEBV were assessed using accuracy yg r ) of the predicted GEBV (g ) ) when compared with the phenotypes (y) and thus the 2 yg r ) . The accuracy of selection ( gg r ) ) when comparing the true breeding values (g) and GEBV has been reported to be a function of the heritability, the number of phenotypic records and the number of effective QTL (Daetwyler et al., 2008 ; Goddard, 2009). This function was adapted for use with the accuracy when comparing phenotypes and GEBV. It was then applied to predict the number of effective QTL for EB and the number of records needed to reach different levels of accuracy of selection. Results The model including the SNP information yielded an overall accuracy of 0.294 and thus an 2 yg r ) of 0.086 ( 2 gg r ) =0.265) when comparing the phenotypes and GEBV in the combined validation sets. The maximum 2 yg r ) that this model could have gained was equal to the heritability which was calculated separately as 0.325. For the model excluding the SNP information with only the polygenic effect an overall accuracy of 0.211 and 2 yg r ) of 0.044 was found. The effective number of QTL for EB was predicted to be 472 and a total of 5818 records with phenotype and genotype information was predicted as needed for an 2 gg r ) of 0.80. Conclusions. The use of SNP information confirm the genetic background of EB. Using the SNP information an increase in the accuracy of selection for EB was achieved over the simple polygenic model. Thus, EB could be selected for using genomic selection. The size of the data set directly impacts the expected accuracy and thus an increase in the total number of phenotypic records used would be required to improve the accuracy of selection. Acknowledgements The authors acknowledge funding from SABRETRAIN, Productschap Zuivel, Senter Novem and RobustMilk. References Calus, M.P.L., Meuwissen, T.H.E., De Roos, A.P.W., and Veerkamp, R.F. 2008. Genetics 178, 553-561. Daetwyler, H.D., Villanueva, B., and Woolliams J.A. 2008. PLoS ONE. 3, e3395 Goddard, M.E. 2009. Genetica 136, 245-257 Friggens, N.C., Berg, P., Theilgaard, P., Korsgaard, I.R., Ingvartsen, K.L., Løvendahl, P. and Jensen, J. 2007. Journal of Dairy Science 90, 5291-5305 Veerkamp. R.F. Beerda, B., van der Lende., T. 2003. Livestock Production Science 83, 257-275
Modelling of resource allocation patterns
Friggens, N.C. ; Waaij, E.H. van der - \ 2008
In: Resource allocation theory applied to farm animal production CABI Publishing - ISBN 9781845933944 - p. 302 - 320.
This chapter provides an introduction to the modelling of resource allocation as a way to generate insights and to make predictions. Resource allocation models provide a framework for considering genotype × environment interactions in animal production.
Electrical Conductivity of milk: ability to predict mastitis status
Norberg, E. ; Hogeveen, H. ; Korsgaard, I.R. ; Friggens, N.C. ; Sloth, K.H.M.N. ; Lovendahl, P. - \ 2004
Journal of Dairy Science 87 (2004). - ISSN 0022-0302 - p. 1099 - 1107.
somatic-cell count - subclinical mastitis - genetic-parameters - infected cows - performance - efficacy
Electrical conductivity (EC) of milk has been introduced as an indicator trait for mastitis over the last decade, and it may be considered as a potential trait in a breeding program where selection for improved udder health is included. In this study, various EC traits were investigated for their association with udder health. In total, 322 cows with 549 lactations were included in the study. Cows were classified as healthy or clinically or subclinically infected, and EC was measured repeatedly during milking on each quarter. Four EC traits were defined; the inter-quarter ratio (IQR) between the highest and lowest quarter EC values, the maximum EC level for a cow, IQR between the highest and lowest quarter EC variation, and the maximum EC variation for a cow. Values for the traits were calculated for every milking throughout the entire lactation. All EC traits increased significantly (P
The influence of parity on lactation curve coefficients in dairy cows
Friggens, N.C. ; Emmans, G.C. ; Veerkamp, R.F. - \ 1999
In: Meeting of the British society of animal science, Scarborough, 1999
On the use of simple ratios between lactation curve coefficients to describe parity effects on milk production
Friggens, N.C. ; Emmans, G.C. ; Veerkamp, R.F. - \ 1999
Livestock Production Science 62 (1999)1. - ISSN 0301-6226 - p. 1 - 13.
The objective of this study was to quantify how the pattern of milk production relative to time from calving is affected by parity in cows fed high quality rations. For this purpose two models; those of Emmans and Fisher (1986) and Dijkstra et al. (1997), were considered. Comparison with Wood's (1967) function was made to evaluate their fitting ability. Daily records of milk yield from 40 cows fed a grass silage based, high concentrate total mixed ration were used. The cows had ad libitum access to food, they were milked twice daily. Each of the cows had milk yield records from calving to 240 days post calving in parities 1, 2 and 3. The model of Dijkstra et al. (1997) was found, on inspection, to be an alternative parameterization of the Emmans and Fisher model (1986). In the analyses, the Emmans and Fisher form was used: Yield = aU exp [-c(days from calving)] where U = exp {- exp (G0 -b[days from calving])}. The Emmans and Fisher model (1986) performed marginally better than the Wood's function (1967) in terms of percentage of variance accounted for and residual standard error. There was no significant effect of parity on G0 or b, which are the main parameters describing the evolution of lactation to peak. However, there was a highly significant effect (P < 0.001) of parity on coefficients a, the scalar, and c, the decay coefficient. The coefficient values in parity 1 and 2 were found to be a constant proportion of the values in parity 3. Parity effects can therefore be described by simple ratios, offering the possibility of simplifying the inputs needed in models to describe potential milk production.
Diet choice by dairy cows. 1. Selection of feed protein content during the first half of lactation
Tolkamp, B.J. ; Dewhurst, R.J. ; Friggens, N.C. ; Kyriazakis, I. ; Veerkamp, R.F. ; Oldham, J.D. - \ 1998
Journal of Dairy Science 81 (1998)10. - ISSN 0022-0302 - p. 2657 - 2669.
Effects of weeks in milk and milk yield on diet choice were recorded during the first half of lactation. Low and high protein feeds were used, and both consisted of 30% concentrate and 70% grass silage (fresh matter basis). Both feeds contained similar amounts of energy, but the crude protein contents were 131 and 185 g/kg of dry matter (DM), respectively, for the low and high protein feeds. In a nutrient flow experiment with three cannulated lactating cows, the metabolizable protein yields of the low and high protein feeds were 75 and 114 g/kg of DM, respectively. Thirty-seven cows were divided into control groups for the low and high protein feeds, and a choice group had access to both the low and the high protein feeds. Intake of DM and milk yield by cows in the control group fed the high protein feed were higher than those by cows in the control group fed the low protein feed, but these measurements did not differ from those of cows in the choice group. Cows in the choice group consumed a mean of 683 g of high protein feed/kg of total intake, which differed from what would be considered random intake (500 g/kg total intake). Diet choice did not systematically change during the experiment and was not correlated with weeks in milk, milk yield, or milk protein output. We concluded that diet selection differed significantly from what would be considered random, which allowed cows in the choice group to perform well. However, diet choice did not reflect the estimated metabolizable protein requirements of the cows.
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