Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    '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.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Efficient and accurate computation of base generation allele frequencies
Aldridge, M.N. ; Vandenplas, J. ; Calus, M.P.L. - \ 2018
Journal of Dairy Science (2018). - ISSN 0022-0302
best linear unbiased prediction - dairy cattle - general least squares

Allele frequencies are used for several aspects of genomic prediction, with the assumption that these are equal to the allele frequency in the base generation of the pedigree. The current standard method, however, calculates allele frequencies from the current genotyped population. We compared the current standard method with BLUP and general least squares (GLS) methods explicitly targeting the base population to determine whether there is a more accurate and still efficient method of calculating allele frequencies that better represents the base generation. A data set based on a typical dairy population was simulated for 325,266 animals; the last 100,078 animals in generations 9 to 12 of the population were genotyped, with 1,670 SNP markers. For the BLUP method, several SNP genotypes were analyzed with a multitrait model by assuming a heritability of 0.99 and no genetic correlation among them. This method was limited by the time required for each BLUP to converge (approximately 6 min per BLUP run of 15 SNP). The GLS method had 2 implementations. The first implementation, using imputation on the fly and multiplication of sparse matrices, was very efficient and required just 49 s and 1.3 GB of random access memory. The second implementation, using a dense fullA22 −1 matrix, was very inefficient and required more than 1 d of wall clock time and more than 118.2 GB of random access memory. When no selection was considered in the simulations, all methods predicted equally well. When selection was introduced, higher correlations between the estimated allele frequency and known base generation allele frequency were observed for BLUP (0.96 ± 0.01) and GLS (0.97 ± 0.01) compared with the current standard method (0.87 ± 0.01). The GLS method decreased in accuracy when introducing incomplete pedigree, with 25% of sires in the first 5 generations randomly replaced as unknown to erroneously identify founder animals (0.93 ± 0.01) and a further decrease for 8 generations (0.91 ± 0.01). There was no change in accuracy when introducing 5% genotyping errors (0.97 ± 0.01), 5% missing genotypes (0.97 ± 0.01), or both 5% genotyping errors and missing genotypes (0.97 ± 0.01). The GLS method provided the most accurate estimates of base generation allele frequency and was only slightly slower compared with the current method. The efficient implementation of the GLS method, therefore, is very well suited for practical application and is recommended for implementation.

Bayesian single-step genomic evaluations combining local and foreign information in Walloon Holsteins
Colinet, F.G. ; Vandenplas, J. ; Vanderick, S. ; Hammami, H. ; Mota, R.R. ; Gillon, A. ; Hubin, X. ; Bertozzi, C. ; Gengler, N. - \ 2018
Animal 12 (2018)5. - ISSN 1751-7311 - p. 898 - 905.
Bayesian integration - dairy cattle - genomic evaluation - reliabilities
Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon population in the southern part of Belgium is a good example for such a small-scale population. Wallonia has also a very active community of Holstein breeders requesting high level genetic evaluation services. Single-step Genomic BLUP (ssGBLUP) methods allow the simultaneous use of genomic, pedigree and phenotypic information and could reduce potential biases in the estimation of genomically enhanced breeding values (GEBV). Therefore, in the context of implementing a Walloon genomic evaluation system for Holsteins, it was considered as the best option. However, in contrast to multi-step genomic predictions, natively ssGBLUP will only use local phenotypic information and is unable to use directly important other sources of information coming from abroad, for example Multiple Across Country Evaluation (MACE) results as provided by the Interbull Center (Uppsala, Sweden). Therefore, we developed and implemented single-step Genomic Bayesian Prediction (ssGBayes), as an alternative method for the Walloon genomic evaluations. The ssGBayes method approximated the correct system of equations directly using estimated breeding values (EBV) and associated reliabilities (REL) without any explicit deregression step. In the Walloon genomic evaluation, local information refers to Walloon EBV and REL and foreign information refers to MACE EBV and associated REL. Combining simultaneously all available genotypes, pedigree, local and foreign information in an evaluation can be achieved but adding contributions to left-hand and right-hand sides subtracting double-counted contributions. Correct propagation of external information avoiding double counting of contributions due to relationships and due to records can be achieved. This ssGBayes method computed more accurate predictions for all types of animals. For example, for genotyped animals with low Walloon REL (<0.25) without MACE results but sired by genotyped bulls with MACE results, the average increase of REL for the studied traits was 0.38 points of which 0.08 points could be traced to the inclusion of MACE information. For other categories of genotyped animals, the contribution by MACE information was also high. The Walloon genomic evaluation system passed for the first time the Interbull GEBV tests for several traits in July 2013. Recent experiences reported here refer to its use in April 2016 for the routine genomic evaluations of milk production, udder health and type traits. Results showed that the proposed methodology should also be of interest for other, similar, populations.
Improving accuracy of bulls' predicted genomic breeding values for fertility using daughters' milk progesterone profiles
Tenghe, A.M.M. ; Bouwman, A.C. ; Berglund, B. ; Koning, D.J. de; Veerkamp, R.F. - \ 2018
Journal of Dairy Science 101 (2018)6. - ISSN 0022-0302 - p. 5177 - 5193.
accuracy - dairy cattle - milk progesterone - multitrait genomic prediction
The main objective of this study was to investigate the benefit of accuracy of genomic prediction when combining records for an intermediate physiological phenotype in a training population with records for a traditional phenotype. Fertility was used as a case study, where commencement of luteal activity (C-LA) was the physiological phenotype, whereas the interval from calving to first service and calving interval were the traditional phenotypes. The potential accuracy of across-country genomic prediction and optimal recording strategies of C-LA were also investigated in terms of the number of farms and number of repeated records for C-LA. Predicted accuracy was obtained by estimating population parameters for the traits in a data set of 3,136 Holstein Friesian cows with 8,080 lactations and using a deterministic prediction equation. The effect of genetic correlation, heritability, and reliability of C-LA on the accuracy of genomic prediction were investigated. When the existing training population was 10,000 bulls with reliable estimated breeding value for the traditional trait, predicted accuracy for the physiological trait increased from 0.22 to 0.57 when 15,000 cows with C-LA records were added to the bull training population; but, when the interest was in predicting the traditional trait, we found no benefit from the additional recording. When the genetic correlation was higher between the physiological and traditional traits (0.7 instead of 0.3), accuracy increased less when adding the 15.000 cows with C-LA (from 0.51 to 0.63). In across-country predictions, we observed little to no increase in accuracy of the intermediate physiological phenotype when the training population from Sweden was large, but when accuracy increased the training population was small (200 cows), from 0.19 to 0.31 when 15,000 cows were added from the Netherlands (genetic correlation of 0.5 between countries), and from 0.19 to 0.48 for genetic correlation of 0.9. The predicted accuracy initially increased substantially when recording on the same farm was extended and multiple C-LA records per cow were used in prediction compared with single records; that is, accuracy increased from 0.33 with single records to 0.38 with multiple records (on average 1.6 records per cow) from 2 yr of recording C-LA. But, when the number C-LA per cow increased beyond 2 yr of recording, we noted no substantial benefit in accuracy from multiple records. For example, for 5 yr of recording (on average 2.5 records per cow), accuracy was 0.47; on doubling the recording period to 10 yr (on average 3.1 records per cow), accuracy increased by 0.07 units, whereas when C-LA was recorded for 15 yr (on average 3.3 records per cow) accuracy increased only by 0.05 units. Therefore, for genomic prediction using expensive equipment to record traits for training populations, it is important to optimize the recording strategy. The focus should be on recording more cows rather than continuous recording on the same cows.
Automated body weight prediction of dairy cows using 3-dimensional vision
Song, X. ; Bokkers, E.A.M. ; Tol, P.P.J. van der; Groot Koerkamp, P.W.G. ; Mourik, S. van - \ 2018
Journal of Dairy Science 101 (2018)5. - ISSN 0022-0302 - p. 4448 - 4459.
automation - dairy cattle - morphological trait - three-dimensional vision - uncertainty
The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure.
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?
Hutchings, N.J. ; Özkan Gülzari, Gülzari ; Haan, M. de; Sandars, D. - \ 2018
Animal 12 (2018)10. - ISSN 1751-7311 - p. 2171 - 2180.
dairy cattle - farm-scale - greenhouse gas - model
The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.
Reduced calf mortality when the calf’s needs are leading : Pledge for a renewed view on calf rearing
Ferwerda-van Zonneveld, R.T. ; Bos, A.P. ; Plomp, M. ; Gaag, M.A. van der; Antonis, A.F.G. - \ 2017
Wageningen : Wageningen University & Research - 15 p.
animal welfare - animal production - dairy cattle - calves - animal health - animal nutrition - animal housing - animal behaviour - elasticity
Hoe fokken we veerkrachtige dieren?
Mulder, H.A. - \ 2017
Wageningen : Livestock Stories blog, Wageningen University & Research
animal welfare - animal production - dairy cattle - animal health - elasticity - selective breeding
Ontstaan ‘haanburger’ is vergelijkbaar met kalfsvlees
Heeres-van der Tol, J.J. - \ 2017
Wageningen : Livestock Stories blog, Wageningen University & Research
animal welfare - animal production - dairy cattle - veal calves - animal housing - animal behaviour - animal health - animal nutrition
Van kalf tot koe, maar hoe? Wat komt daar allemaal bij kijken?
Heeres-van der Tol, J.J. - \ 2017
Wageningen : Livestock Stories blog, Wageningen University & Research
animal welfare - animal production - dairy cattle - veal calves - animal housing - animal behaviour - animal health - animal nutrition
The genetic background of bovine αs1- and αs2-casein phosphorylation
Fang, Zih-Hua - \ 2017
University. Promotor(en): E. Verrier; Henk Bovenhuis, co-promotor(en): P. Martin; Marleen Visker. - Wageningen : Wageningen University - ISBN 9789463438148 - 141
dairy cattle - alpha-s1-casein - alpha-s2-casein - phosphorylation - milk composition - milk proteins - genetic variation - genetic factors - animal genetics - melkvee - alfa-s-1-caseïne - alfa-s-2-caseïne - fosforylering - melksamenstelling - melkeiwitten - genetische variatie - genetische factoren - diergenetica

Phosphorylation of caseins (CN) is a crucial post-translational modification allowing caseins to aggregate as micelles. The formation and stability of casein micelles are important for transporting abundant minerals to the neonate and manufacturing of dairy products. Therefore, it is of great interest to explore variation in degrees of phosphorylation of caseins and study to what extent genetic and other factors contribute to this variation. This thesis aimed to investigate the genetic background of bovine milk protein composition with a focus on phosphorylation of αs1- and αs2-CN. Two studies were conducted to quantify phosphorylation levels of αs1- and αs2-CN: one in French Montbéliarde using liquid chromatography coupled with electrospray ionization mass spectrometry and the other in Dutch Holstein Friesian using capillary zone electrophoresis. In French Montbéliarde, in addition to the known isoforms αs1-CN-8P and-9P and αs2-CN-10P to -13P, three new phosphorylation isoforms were detected, namely αs2-CN-9P, αs2-CN-14P, and αs2-CN-15P. Relative concentrations of the phosphorylation isoforms varied considerably among cows. Phenotypic correlations showed that isoforms phosphorylated at higher degrees (αs1-CN-9P and αs2-CN-12P to -14P) correlated negatively with isoforms phosphorylated at lower degrees (αs1-CN-8P, αs2-CN-10P, and -11P). Furthermore, it was shown that αs1- and αs2-CN phosphorylation profiles changed across parity and lactation, and exploitable genetic variation for the phosphorylation degrees of αs1- and αs2-CN (defined as the proportion of higher-degree isoforms in αs1- and αs2-CN, respectively) exist. In Dutch Holstein Friesian, three αs2-CN isoforms, namely αs2-CN-10P to -12P, and the phosphorylation degrees of αs1- and αs2-CN were quantified. High intra-herd heritabilities were estimated for individual αs2-CN phosphorylation isoforms and the phosphorylation degrees of αs1- and αs2-CN (ranging from 0.54 to 0.89). This suggests that genetic factors contribute substantially to observed differences in αs1- and αs2-CN phosphorylation profiles. The highly positive correlation between the phosphorylation degrees of αs1- and αs2-CN (0.94) suggest that phosphorylation of αs1- and αs2-CN is related. Additionally, a total of 10 regions, distributed across Bos taurus autosomes (BTA) 1, 2, 6, 9, 11, 14, 15, 18, 24 and 28, were detected to be associated with individual αs1- and αs2-CN phosphorylation isoforms and their phosphorylation degrees. Regions on BTA1, 6, 11 and 14 were associated with multiple traits studied. Two quantitative trait loci (QTL) regions were detected on BTA1: one affecting αs2-CN production, and the other affecting αs1-CN PD and αs2-CN PD. The QTL region on BTA6 affected only individual αs2-CN isoforms. The QTL region on BTA11 and 14 affected relative concentrations of αs2-CN-10P and αs2-CN-11P, αs1-CN PD and αs2-CN PD. Results suggested that effects of identified genomic regions on αs1-CN PD and αs2-CN PD are probably due to changes in milk synthesis and phosphorus secretion in milk.

Metabolic status, lactation persistency, and udder health of dairy cows after different dry period lengths
Hoeij, Renny van - \ 2017
University. Promotor(en): Bas Kemp; T.J.G.M. Lam, co-promotor(en): Ariette van Knegsel; Jan Dijkstra. - Wageningen : Wageningen University - ISBN 9789463438070 - 285
dairy cattle - animal health - animal behaviour - dry period - metabolism - energy balance - lactation - milk production - udders - cattle feeding - melkvee - diergezondheid - diergedrag - gustperiode - metabolisme - energiebalans - lactatie - melkproductie - uiers - rundveevoeding

Cows traditionally have a 6 to 8 week non-lactating –‘dry period’- before calving and the start of the next lactation in order to maximize milk production in the subsequent lactation. An omitted, compared with a shortened, dry period reduces milk yield and improves energy availability in cows postpartum, but effects on udder health and persistency were unclear. Cows without a dry period fattened and spontaneously dried off due to the improved energy availability. Reducing the energy availability in the feed for cows without a dry period did not affect fattening or lactation persistency in late lactation. Cows with a short or without a dry period did not receive dry cow antibiotics in this study and this did not affect udder health across the dry period or in early lactation, but seemed to impair udder health in late lactation for cows without a dry period.

Predicting methane emission of dairy cows using milk composition
Gastelen, Sanne van - \ 2017
University. Promotor(en): Wouter Hendriks, co-promotor(en): Jan Dijkstra; Kasper Hettinga. - Wageningen : Wageningen University - ISBN 9789463437097 - 266
dairy cows - dairy cattle - methane production - emission - milk composition - fatty acids - cattle feeding - fermentation - nutrition physiology - animal nutrition - pollution - melkkoeien - melkvee - methaanproductie - emissie - melksamenstelling - vetzuren - rundveevoeding - fermentatie - voedingsfysiologie - diervoeding - verontreiniging

Enteric methane (CH4) is produced as a result of microbial fermentation of feed components in the gastrointestinal tract of ruminant livestock. Methane has no nutritional value for the animal and is predominately released into the environment through eructation and breath. Therefore, CH4 not only represents a greenhouse gas contributing to global warming, but also an energy loss, making enteric CH4 production one of the main targets of greenhouse gas mitigation practices for the dairy industry. Obviously, reduction of CH4 emission could be achieved by simply reducing livestock numbers. However, the global demand for dairy products has been growing rapidly and is expected to further grow in the future. Therefore, it is critical to minimize environmental impact to produce high-quality dairy products. The overall aim of this PhD research was, therefore, to develop a proxy for CH4 emission that can be measured in milk of dairy cows.

There are currently a number of potentially effective dietary CH4 mitigation practices available for the livestock sector. The results of Chapter 3 show that replacing fiber-rich grass silage with starch-rich corn silage in a common forage-based diet for dairy cattle offers an effective strategy to decrease enteric CH4 production without negatively affecting dairy cow performance, although a critical level of starch in the diet seems to be needed. Little is known whether host genetics may influence the CH4 emission response to changes in diet. Therefore, the interaction between host DGAT1 K232A polymorphism with dietary linseed oil supplementation was evaluated in Chapter 7. The results of Chapter 7 indicate that DGAT1 K232A polymorphism is associated with changes in milk composition, milk N efficiency, and diet metabolizability, but does not affect digestibility and enteric CH4 emission, whereas linseed oil reduces CH4 emission independent of the DGAT1 K232A polymorphism.

Accurate and repeatable measurements of CH4 emission from individual dairy cows are required to assess the efficacy of possible mitigation strategies. There are several techniques to estimate or measure enteric CH4 production of dairy cows, including climate respiration chambers, but none of these techniques are suitable for large scale precise and accurate measurements. Therefore, the potential of various metabolites in milk, including milk fatty acids (MFA), as a proxy (i.e., indicators or animal traits that are correlated with enteric CH4 production) for CH4 emission of dairy cows gained interest. Until recently, gas chromatography was the principal method used to determine the MFA profile, but this technique is unsuitable for routine analysis. This has led to the application of Fourier-transform infrared spectroscopy (FTIR) for determination of the MFA profile. Chapter 2 provides an overview of the recent research that relates MFA with CH4 emission, and discusses the opportunities and limitations of using FTIR to estimate, indirectly via MFA or directly, CH4 emission of dairy cattle. The recent literature on the relationship between MFA and CH4 emission gives inconsistent results. Where some studies found a clear and strong relation, other studies consider MFA to be unreliable predictors for CH4 emitted by dairy cows. Even the studies that do find a clear relation between MFA and CH4 emissions do not describe similar prediction models using the same MFA. These discrepancies can be the result of many factors, including dietary composition and lactation stage. Additionally, literature showed that the major advantages of using FTIR to predict CH4 emission include its simplicity and potential practical application on a large scale. Disadvantages include the inability to predict important MFA for the prediction of CH4 emission, and the moderate power of FTIR to directly predict CH4 emission. The latter was also demonstrated in Chapter 9, in which the CH4 prediction potential of MFA was compared with that of FTIR using data from 9 experiments (n = 218 individual cow observations) covering a broad range of roughage-based diets. The results indicate that MFA have a greater potential than FTIR spectra to estimate CH4 emissions, and that both techniques have potential to predict CH4 emission of dairy cows, but also limited current applicability in practice. Much focus has been placed on the relationship between MFA and CH4 emission, but milk also contains other metabolites, such as volatile and non-volatile metabolites. Currently, milk volatile metabolites have been used for tracing animal feeding systems and milk non-volatile metabolites were shown to be related to the health status of cows. In Chapter 4, the relationship between CH4 emission and both volatile and non-volatile metabolites was investigated, using data and milk samples obtained in the study described in Chapter 3. In general, the non-volatile metabolites were more closely related to CH4 emissions than the volatile metabolites. More specifically, the results indicate that CH4 intensity (g/kg fat- and protein-corrected milk; FPCM) may be related to lactose synthesis and energy metabolism in the mammary gland, as reflected by the milk non-volatile metabolites uridine diphosphate-hexose B and citrate. Methane yield (g/kg dry matter intake) on the other hand, may be related to glucogenic nutrient supply, as reflected by the milk non-volatile acetone. Based on the metabolic interpretations of these relationships, it was hypothesized that the addition of both volatile and non-volatile metabolites in a prediction model with only MFA would enhance its predictive power and, thus, leads to a better proxy in milk for enteric CH4 production of dairy cows. This was investigated in Chapter 5, again using data and milk samples described in Chapter 3. The results indicate that MFA alone have moderate to good potential to estimate CH4 emission. Furthermore, including volatile metabolites (CH4 intensity only) and non-volatile metabolites increases the CH4 emission prediction potential.

The work presented in Chapters 3, 4 and 5, was based upon a small range of diets (i.e., four roughage-based diets in which grass silage was replaced partly or fully by corn silage) of one experiment. Therefore, in Chapter 6, the relationship between CH4 emission and the milk metabolome in dairy cattle was further quantified. Data (n = 123 individual cow observations) were used encompassing a large of roughage-based diets, with different qualities and proportions of grass, grass silage and corn silage. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH4 production pathways. These relationships are most likely the result from changes in dietary composition that affect not only enteric CH4 production, but also the profile of volatile and non-volatile metabolites in milk. Overall, the results indicate that both volatile and non-volatile metabolites in milk might provide useful information and increase our understanding of CH4 emission of dairy cows. However, the development of CH4 prediction models revealed that both volatile and non-volatile metabolites in milk hold little potential to predict CH4 emissions despite the significant relationships found between individual non-volatile metabolites and CH4 emissions. Additionally, combining MFA with milk volatile metabolites and non-volatile metabolites does not improve the CH4 prediction potential relative to MFA alone. Hence, it is concluded that it is not worthwhile to determine the volatile and non-volatile metabolites in milk in order to estimate CH4 emission of dairy cows.

Overall, in comparison with FTIR, volatile and non-volatile metabolites, the MFA are the most accurate and precise proxy in milk for CH4 emission of dairy cows. However, most of MFA-based models to predict CH4 emission tend to be accurate only for the production system and the environmental conditions under which they were developed. In Chapter 8 it was demonstrated that previously developed MFA-based prediction equations did not predict CH4 emission satisfactory of dairy cows with different DGAT1 genotypes or fed diets with or without linseed oil. Therefore, the greatest shortcoming today of MFA-based CH4 prediction models is their lack of robustness. Additionally, MFA have restricted practical application, meaning that most MFA retained in the current CH4 prediction models cannot be determined routinely because of the use of gas chromatography. The MFA that can be determined with the use of infrared spectroscopy are however no promising predictors for CH4 emission. Furthermore, MFA have only a moderate CH4 prediction potential. This together suggests that it might not be the best option to focus in the future on MFA alone as a proxy for CH4 emission of dairy cows.

The FTIR technique has a low to moderate CH4 prediction potential. However, FTIR has a great potential for practical high throughput application, facilitating repeated measurements of the same cow potentially reducing random noise. Results of this thesis also demonstrated that FTIR spectra do not have the potential to detect differences in CH4 emission between diets which are, in terms of forage level and quality, commonly fed in practice. Moreover, the robustness of FTIR spectra is currently unknown. Hence, it remains to be investigated whether FTIR spectra can predict CH4 emissions from dairy cows housed under different conditions from those under which the FTIR-based prediction equations were developed. It is therefore concluded that the accuracy and precision to predict CH4 emission using FTIR needs to increase, and the capacity of FTIR to evaluate the differences in CH4 emission between dairy cows and different types of diets needs to improve, in order to actually be a valuable proxy for CH4 emission of dairy cows.

Monitoring verduurzaming veehouderij 1.0 : een eerste proeve van een Monitorings-systematiek voor de 15 ambities van de Uitvoeringsagenda Duurzame Veehouderij, met initiële resultaten voor drie diersectoren en een aantal keteninitiatieven
Bos, A.P. ; Puente-Rodríguez, Daniel ; Reijs, Joan W. ; Peet, G.F.V. van der; Groot Koerkamp, Peter W.G. - \ 2017
Wageningen : Wageningen Livestock Research (Wageningen Livestock Research rapport 1045) - 113
dierenwelzijn - dierlijke productie - melkvee - varkens - pluimvee - huisvesting, dieren - diergezondheid - diergedrag - animal welfare - animal production - dairy cattle - pigs - poultry - animal housing - animal health - animal behaviour
In 2013, the governance network UDV formulated fifteen ambitions towards a sustainable livestock production. In this way, the UDV’s stakeholders defined the long-term goals of an integrated and sustainable livestock production. To what extent have these 15 ambitions been achieved? And, how substantial is the contribution of supra-legal initiatives to this process? In this report, we present the first elaboration of a monitoring system that enables the visualization of the progress made. Moreover, it also enables comparing the different livestock production systems and creates the basis for a comparison between conventional animal production and supra-legal initiatives. In this concept-report the system is applied initially to the three larger livestock production sectors in the Netherlands (i.e., dairy, pigs, and poultry) and –as far as enough data is available– to four supra-legal initiatives. The system is currently under construction. Particularly because it involves interpretation and a number of value-laden choices that –notwithstanding their current support by arguments and references to the literature– should become shared and supported by (at least) the UDV stakeholders in the near future.
Evaluatie Actieplan Stalbranden 2012-2016
Bokma-Bakker, Martien ; Bokma, Sjoerd ; Ellen, Hilko ; Hagen, René ; Ruijven, Charlotte van - \ 2017
Wageningen : Wageningen Livestock Research (Wageningen Livestock Research rapport 1035) - 80
dierenwelzijn - dierlijke productie - diergezondheid - pluimvee - varkens - melkvee - schapen - geiten - paarden - stallen - brand - voorkomen van branden - veiligheid - animal welfare - animal production - animal health - poultry - pigs - dairy cattle - sheep - goats - horses - stalls - fire - fire prevention - safety
Maatregelen om weidegang te bevorderen : inventarisatie en analyse
Blokland, P.W. ; Pol-van Dasselaar, A. van den; Rougoor, C. ; Schans, F. van der; Sebek, L. - \ 2017
Wageningen : Wageningen Economic Research (Wageningen Economic Research rapport 2017-071) - ISBN 9789463436533 - 59
dierenwelzijn - dierlijke productie - melkvee - huisvesting - weiden - animal welfare - animal production - dairy cattle - housing - pastures
Monitoring integraal duurzame stallen : peildatum 1 januari 2017
Peet, G.F.V. van der; Meer, R.W. van der; Docters van Leeuwen, H. - \ 2017
Wageningen : Wageningen UR Livestock Research (Wageningen Livestock Research rapport 1027) - 19
huisvesting, dieren - stallen - monitoring - dierlijke productie - dierenwelzijn - rundvee - melkvee - pluimvee - duurzaamheid (sustainability) - animal housing - stalls - animal production - animal welfare - cattle - dairy cattle - poultry - sustainability
De overheid ambieert een integraal duurzame veehouderij in 2023. Daarom wordt jaarlijks een nieuw doel gesteld. Voor eind 2016 (peildatum 1 januari 2017) noemt het ministerie als ambitie dat minimaal 14% van de rundvee-, varkens- en pluimveestallen integraal duurzaam is. Deze studie laat zien dat op 1 januari 2017 in Nederland 13,6 % van alle stallen integraal duurzaam is.
Maatregelen Natuurinclusieve landbouw
Erisman, Jan Willem ; Eekeren, Nick van; Doorn, Anne van; Geertsema, Willemien ; Polman, Nico - \ 2017
Wageningen : Wageningen Environmental Research (Wageningen Environmental Research rapport 2821) - 49
landbouw - natuur - agrarische bedrijfsvoering - maatregelen - biologische landbouw - dierenwelzijn - huisvesting, dieren - dierlijke productie - melkvee - agriculture - nature - farm management - measures - organic farming - animal welfare - animal housing - animal production - dairy cattle
In deze notitie wordt een overzicht gegeven van maatregelen voor natuurinclusieve landbouw. Dit is een vorm van duurzame landbouw die optimaal gebruik maakt van de natuurlijke processen en deze integreert in de bedrijfsvoering. Natuurinclusieve landbouw begint met een gezonde bodem, produceert voedsel binnen de grenzen van natuur, milieu en leefomgeving en heeft positieve effecten op de biodiversiteit en het klimaat.
Wat zijn de mogelijkheden om een leverbotinfectie van melkvee te voorkomen?
Neijenhuis, Francesca ; Verwer, Cynthia ; Verkaik, Jan - \ 2017
Wageningen : Wageningen UR Livestock Research (Livestock Research rapport 1029) - 65
leverbot - fascioliasis - melkvee - melkveehouderij - parasitosen - infectieziekten - dierlijke productie - dierenwelzijn - diergezondheid - biologische landbouw - liver flukes - dairy cattle - dairy farming - parasitoses - infectious diseases - animal production - animal welfare - animal health - organic farming
Infecties met leverbot zijn in toenemende mate een knelpunt in de diergezondheid van grazende (of vers gras gevoerde) herkauwers. Leverbotinfectie leidt tot ziekte met economische gevolgen en voor melkgevende dieren zijn geen anthelmintica vrij beschikbaar. In dit project is het leverbotinstrument ontwikkeld met als doel om veehouders inzicht en handelingsperspectief te geven ten aanzien van de leverbotsituatie op hun bedrijf. In dit rapport worden de resultaten weergegeven van het leverbotinstrument en een drietal preventieve maatregelen die zijn uitgeprobeerd.
The utility of sensor technology to support reproductive management on dairy farms
Rutten, C.J. - \ 2017
University. Promotor(en): Henk Hogeveen; Michel Nielen, co-promotor(en): Wilma Steeneveld. - Wageningen : Wageningen University - ISBN 9789463431934 - 232
dairy cattle - dairy farms - sensors - reproduction - reproductive behaviour - animal health - calving - activity - management - dairy farming - technology - agricultural economics - melkvee - melkveebedrijven - voortplanting - voortplantingsgedrag - diergezondheid - kalven - activiteit - bedrijfsvoering - melkveehouderij - technologie - agrarische economie

Since the 1980s, efforts have been made to develop sensors that measure a parameter from an individual cow. The development started with individual cow recognition and was followed by sensors that measure the electrical conductivity of milk and pedometers that measure activity. Some sensors like activity meters, electrical conductivity, weight floors and somatic cell count sensors are commercially available. Adoption has in general been low and mainly driven by the AMS, with a clear exception for estrus detection. In practice, the economic benefits of using sensor systems has not been proven. So, to make sensors live up to their full potential there is a need for research to shift from technical development towards practical applications and integration with operational farm management. Estrus detection sensors can have a good detection performance and are currently applied by farmers in practice, therefore this thesis focusses on sensors that support reproductive management. The main objective of this thesis is to study the utility of sensor technology to support reproductive management on dairy farms. This main objective was split in five sub objectives that each study a part of the main objective and were discussed in the separate chapters of this thesis.

We demonstrated that utility of sensors for reproductive management can be found in economic benefits (estrus and calving detection), reduction of labor (calving and estrus detection) and more detailed management information (prognosis of insemination success). So, automated estrus detection aids reproductive management.

From this thesis the following conclusions can be drawn:

The developed theoretical framework describes four levels of sensor development, which should all be included in proper development of sensor systems. The literature review showed that no studies developed sensor systems with regard to management and decision support.

It was possible to improve the prediction of the start of calving compared to a model that only uses the expected calving date. However, predicting the start of calving within an hour was not possible with a high sensitivity and specificity.

There was financial merit in the use of calving detection, because the sensor system enables more timely intervention by the farmer. The uncertainty about the positive effects was large, which caused a wide range in the simulated financial benefits.

Investment in a sensor for estrus detection was on average profitable with a return on investment of 11%. Profitability was influenced most by the heuristic culling rules and the expected increase of the estrus detection rate between detection by visual observation and the sensor.

Routinely collected farm data can be used to estimate a prognosis on insemination success and be used to determine whether an individual cow has a higher or lower than average likelihood of insemination success. Integration of this prognostic model with an estrus detection sensor has potential.

Currently farmers only adopt sensors for estrus detection or because they were standard with an AMS. A reason for this is that sensor systems do not produce clear information for farmers. Sensor technology should be focused on management support of applications. Labor benefits of sensors are important for adoption of sensors by farmers, farmers value flexibility, increased family time and less physical workload as benefits. However, economic evaluations of technical solutions are unable to quantify these benefits. Sensor research should consider the preference of farmers regarding labor. For the appraisal of sensor technology new methods to value labor benefits of sensor are needed. Furthermore, in sensor development societal acceptance should be an important consideration. Animal rights activists may frame the use of sensors as a form of industrialized farming. Only using technical arguments and considerations to explain the benefits of sensors will hamper the societal acceptance of modern dairy farming. Application of sensors on dairy farms should be communicated smartly to society in terms that relate the values of citizens.

De PerceelVerdeler: optimaal verdelen van de beschikbare mest op het melkveebedrijf
Oenema, Jouke ; Verloop, Koos ; Hilhorst, Gerjan - \ 2017
Wageningen : Wageningen UR Livestock Research (Rapport / Koeien &amp; Kansen 78) - 25
melkvee - melkveehouderij - rundveemest - kunstmeststoffen - ruimtelijke verdeling - dairy cattle - dairy farming - cattle manure - fertilizers - spatial distribution
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