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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Development of a model forecasting Dermanyssus gallinae's population dynamics for advancing Integrated Pest Management in laying hen facilities
Mul, Monique F. ; Riel, Johannes van; Roy, Lise ; Zoons, Johan ; Andre, Geert ; George, David R. ; Meerburg, Bastiaan G. ; Dicke, Marcel ; Mourik, Simon van; Groot Koerkamp, Peter W.G. - \ 2017
Veterinary Parasitology 245 (2017). - ISSN 0304-4017 - p. 128 - 140.
Dermanyssus gallinae - Integrated Pest Management (IPM) - Population model - Poultry Gallus gallus - Treatment effect

The poultry red mite, Dermanyssus gallinae, is the most significant pest of egg laying hens in many parts of the world. Control of D. gallinae could be greatly improved with advanced Integrated Pest Management (IPM) for D. gallinae in laying hen facilities. The development of a model forecasting the pests’ population dynamics in laying hen facilities without and post-treatment will contribute to this advanced IPM and could consequently improve implementation of IPM by farmers. The current work describes the development and demonstration of a model which can follow and forecast the population dynamics of D. gallinae in laying hen facilities given the variation of the population growth of D. gallinae within and between flocks. This high variation could partly be explained by house temperature, flock age, treatment, and hen house. The total population growth variation within and between flocks, however, was in part explained by temporal variation. For a substantial part this variation was unexplained. A dynamic adaptive model (DAP) was consequently developed, as models of this type are able to handle such temporal variations. The developed DAP model can forecast the population dynamics of D. gallinae, requiring only current flock population monitoring data, temperature data and information of the dates of any D. gallinae treatment. Importantly, the DAP model forecasted treatment effects, while compensating for location and time specific interactions, handling the variability of these parameters. The characteristics of this DAP model, and its compatibility with different mite monitoring methods, represent progression from existing approaches for forecasting D. gallinae that could contribute to advancing improved Integrated Pest Management (IPM) for D. gallinae in laying hen facilities.

Individualized on-line monitoring tool to analyse the complex physiological signal of heart beat fluctuations in pigs
Dixhoorn, I.D.E. van; Andre, G. ; Lambooij, E. ; Kemp, B. ; Groot Koerkamp, P.W.G. - \ 2013
Individualized longitudinal approach to measure ECG, Blood pressure, activity and temperature in group housed growing piglets
Dixhoorn, I.D.E. van; Andre, G. ; Lambooij, E. ; Kemp, B. ; Groot Koerkamp, P.W.G. - \ 2013
Applicability of day-to-day variation in behavior for the automated detection of lameness in dairy cows
Mol, R.M. de; Andre, G. ; Bleumer, E.J.B. ; Werf, J.T.N. van der; Haas, Y. de; Reenen, C.G. van - \ 2013
Journal of Dairy Science 96 (2013)6. - ISSN 0022-0302 - p. 3703 - 3712.
lying behavior - locomotion score - hoof lesions - gait - cattle - assessments - system
Lameness is a major problem in modern dairy husbandry and has welfare implications and other negative consequences. The behavior of dairy cows is influenced by lameness. Automated lameness detection can, among other methods, be based on day-to-day variation in animal behavior. Activity sensors that measure lying time, number of lying bouts, and other parameters were used to record behavior per cow per day. The objective of this research was to develop and validate a lameness detection model based on daily activity data. Besides the activity data, milking data and data from the computerized concentrate feeders were available as input data. Locomotion scores were available as reference data. Data from up to 100 cows collected at an experimental farm during 23 mo in 2010 and 2011 were available for model development. Behavior is cow-dependent, and therefore quadratic trend models were fitted with a dynamic linear model on-line per cow for 7 activity variables and 2 other variables (milk yield per day and concentrate leftovers per day). It is assumed that lameness develops gradually; therefore, a lameness alert was given when the linear trend in 2 or more of the 9 models differed significantly from zero in a direction that corresponded with lameness symptoms. The developed model was validated during the first 4 mo of 2012 with almost 100 cows on the same farm by generating lameness alerts each week. Performance on the model validation data set was comparable with performance on the model development data set. The overall sensitivity (percentage of detected lameness cases) was 85.5% combined with specificity (percentage of nonlame cow-days that were not alerted) of 88.8%. All variables contributed to this performance. These results indicate that automated lameness detection based on day-to-day variation in behavior is a useful tool for dairy management
Automated detection of lameness in dairy cows based on day-to-day variation in behaviour
Mol, R.M. de; André, G. ; Bleumer, E.J.B. ; Werf, J.T.N. van der; Haas, Y. de; Reenen, C.G. van - \ 2012
In: Book of Abstracts of the 63rd Annual Meeting of the European Association for Animal Production, 27-31 August 2012, Bratislava, Slovakia, 27 - 31 August 2012. - Wageningen, the Netherlands : Wageningen Academic Publishers - p. 48 - 48.
Een plaag te snel af zijn
Mul, M.F. ; Andre, G. - \ 2012
De Pluimveehouderij 42 (2012)12. - ISSN 0166-8250 - p. 26 - 27.
pluimveehouderij - diergezondheid - ziektebestrijding - dermanyssus gallinae - mijtenbestrijding - plagenbestrijding - dierenwelzijn - poultry farming - animal health - disease control - mite control - pest control - animal welfare
WUR Livestock Research ontwikkelt een vogelmijtmonitor die waarschuwt wanneer een pluimveehouder moet behandelen tegen bloedluis.
Development of a model for the prediction of feed intake by dairy cows. 2. Evaluation of prediction accuracy
Zom, R.L.G. ; André, G. ; Vuuren, A.M. van - \ 2012
Livestock Science 143 (2012)1. - ISSN 1871-1413 - p. 58 - 69.
voluntary intake - holstein cows - grass silages - food-intake - equations - systems - cattle
In a previous paper we have proposed a new concept of a model for the prediction of feed intake by Holstein Friesian dairy cows (Zom et al., 2011). This model predicts feed intake from feed composition and digestibility and the cow's lactation number, stage of lactation and pregnancy. Contrary to many other often used models, this does not include animal performance (milk yield, bodyweight) to predict feed intake. However, BW and MY are highly correlated with DMI. Therefore, the objective of present study was to evaluate the accuracy and robustness of the novel feed intake model and to compare its accuracy and robustness with four other commonly used models for the prediction of feed intake. An evaluation was performed using an independent dataset containing 8974 weekly means of DMI from 348 individual cows observed in 6 feeding experiments including a wide range of diets and management practices was used in this study. Sub-datasets were formed by combining the DMI data by experiment, lactation number, lactation week, and maize silage to grass silage ratios in order to compare the accuracy of the intake models for different feeding practices and groups of cows using mean square prediction error (MSPE) and relative prediction error (RPE) as criteria. The novel model was most accurate as indicated by the MSPEs and RPEs for the whole dataset and the most of the sub-datasets. The results prove that the model of Zom et al. (2011) is able to predict DMI without the use of milk yield or body weight as inputs. It was concluded that novel model was robust and can be applied to various diets and feeding management situations in lactating HF cows.
Development of a model for the prediction of feed intake by dairy cows: 1. Prediction of feed intake
Zom, R.L.G. ; André, G. ; Vuuren, A.M. van - \ 2012
Livestock Science 143 (2012)1. - ISSN 1871-1413 - p. 43 - 57.
dry-matter intake - ruminal starch degradation - voluntary food-intake - 2 complete diets - milk-production - grass-silage - concentrate supplementation - nutritional-value - grazing behavior - crop maturity
A study was undertaken to develop a model for the prediction of dry matter intake by lactating Holstein Friesian dairy cows. To estimate the model parameters, a calibration dataset was compiled with the data from 32 feeding experiments conducted at 9 different sites. The database contained weekly information on 1507 lactating Holstein Friesian dairy cows regarding their diet composition and feed analysis, together with their individual voluntary feed intake, milk yield (MY), milk composition, parity, days in lactation and days pregnant. Dry matter intake was predicted from feed and animal characteristics. The feed chemical composition and digestibility can be related to feed degradation, bulk volume, intake rate, palatability and other factors influencing feed intake. Therefore, the data of standard feed analysis were used to estimate the satiety value of numerous commonly used feeds and forages. The satiety value is the measure of the extent to which a feed limits intake. The cows' ability to process the intake-limiting satiety value-units is expressed as the feed intake capacity, which is predicted from parity, days in milk and days of pregnancy which are indicators of the size and physiological state of the cow. This study shows that feed intake can be predicted using a limited number of easy-to-measure inputs that are available on commercial farms, yet reasonably biologically sound. Because the model inputs are not related to animal output (milk yield or body weight), future extension of the intake model with models for the prediction of animal performance is possible.
Effect of automatic feeding of total mixed rations on the diurnal visiting pattern of dairy cows to an automatic milking system
Belle, Z. ; Andre, G. ; Pompe, J.C.A.M. - \ 2012
Biosystems Engineering 111 (2012)1. - ISSN 1537-5110 - p. 33 - 39.
frequency - behavior
Automatic feeding systems (AFSs) enable more frequent delivery of feedstuffs compared to conventional feeding systems (CFSs). The objective was to estimate the effect of the feeding system (CFS versus AFS) and of the associated feeding and milking related actions on the visiting patterns to automatic milking systems (AMSs). The AMS log files of 20 Dutch dairy farms that fed total mixed rations (TMR) and milked automatically for the year 2009 were analysed: 9 farms used a CFS, 11 farms fed with an AFS. The effects of the feeding system on the mean daily AMS visits were determined using an F-test and on the hourly AMS visits using a restricted maximum likelihood (REML) analysis. To assess the effect of feeding and milking related actions on the AMS visiting patterns the patterns were decomposed into Fourier harmonics, the effects of the actions were analysed with transfer functions and lagged variables and parameters were estimated with REML. No statistical differences were found for the mean daily AMS visits between the CFS (2.567 milkings day-1, 2.056 refusals day-1 and 0.105 failures day-1) and AFS farms (2.614 milkings day-1, 2.483 refusals day-1 and 0.118 failures day-1). The cows at the AFS farms were milked significantly earlier (at 7:00 and 8:00 AM) than at the CFS farms. Feed delivery reduced the milkings cow-1 h-1 slightly and almost significantly in the hour of feed delivery, while AMS cleanings and fetching of cows had a more significant effect on the hourly cow visits to the AMS.
Fluorescence and Atomic Force Microscopy Imaging of Wall Teichoic Acids in Lactobacillus plantarum
Andre, G. ; Deghorain, M. ; Bron, P.A. ; Swam, I.I. van; Kleerebezem, M. ; Hols, P. ; Dufrene, Y.F. - \ 2011
Acs Chemical Biology 6 (2011)4. - ISSN 1554-8929 - p. 366 - 376.
gram-positive bacteria - staphylococcus-aureus - cell-wall - lipoteichoic acid - bacillus-subtilis - growth - localization - peptidoglycan - biosynthesis - spectroscopy
Although teichoic acids are major constituents of bacterial cell walls, little is known about the relationships between their spatial localization and their functional roles. Here, we used single-molecule atomic force microscopy (AFM) combined with fluorescence microscopy to image the distribution of wall teichoic acids (WTAs) in. Lactobacillus plantarum, in relation with their physiological roles. Phenotype analysis of the wild-type strain and of mutant strains deficient for the synthesis of WTAs (Delta tagO) or cell wall polysaccharides (Delta cps1-4) revealed that WTAs are required for proper cell elongation and cell division. Nanoscale imaging by AFM showed that strains expressing WTAs have a highly polarized surface morphology, the poles being much smoother than the side walls. AFM and fluorescence imaging with specific lectin probes demonstrated that the polarized surface structure correlates with a heterogeneous distribution of WTAs, the latter being absent from the surface of the poles. These observations indicate that the polarized distribution of WTAs in L. plantarum plays a key role in controlling cell morphogenesis (surface roughness, cell shape, elongation, and division).
Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model
Andre, G. ; Engel, B. ; Berentsen, P.B.M. ; Vellinga, T.V. ; Oude Lansink, A.G.J.M. - \ 2011
Journal of Dairy Science 94 (2011)9. - ISSN 0022-0302 - p. 4502 - 4513.
lactating dairy-cows - temperature - performance - climate - hot
Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on 6 experimental research farms in the Netherlands. These time series were analyzed with an adaptive dynamic model following a Bayesian method to quantify the effect of heat stress. The effect of heat stress was quantified in terms of critical temperature above which heat stress occurred, duration of heat stress periods, and resulting loss in milk yield. In addition, dynamic changes in level and trend were monitored, including the estimation of a weekly pattern. Monitoring comprised detection of potential outliers and other deteriorations. The adaptive dynamic model fitted the data well; the root mean squared error of the forecasts ranged from 0.55 to 0.99 kg of milk/d. The percentages of potential outliers and signals for deteriorations ranged from 5.5 to 9.7%. The Bayesian procedure for time series analysis and monitoring provided a useful tool for process control. Online estimates (based on past and present only) and retrospective estimates (determined afterward from all data) of level and trend in daily milk yield showed an almost yearly cycle that was in agreement with the calving pattern: most cows calved in winter and early spring versus summer and autumn. Estimated weekly patterns in terms of weekday effects could be related to specific management actions, such as change of pasture during grazing. For the effect of heat stress, the mean estimated critical temperature above which heat stress was expected was 17.8 ± 0.56°C. The estimated duration of the heat stress periods was 5.5 ± 1.03 d, and the estimated loss was 31.4 ± 12.2 kg of milk/cow per year. Farm-specific estimates are helpful to identify management factors like grazing, housing and feeding, that affect the impact of heat stress. The effect of heat stress can be decreased by modifying these factors
Adaptive models for online estimation of individual milk yield response to concentrate intake and milking interval length of dairy cows
André, G. ; Engel, B. ; Berentsen, P.B.M. ; Oude Lansink, A.G.J.M. - \ 2011
The Journal of Agricultural Science 149 (2011)6. - ISSN 0021-8596 - p. 769 - 781.
dietary energy-source - time-series analysis - ovarian-function - lactation curve - kalman filter - cattle - metabolism - balance - reproduction - fertility
Automated feeding and milking of dairy cows enables the application of individual cow settings for concentrate supply and milking frequency. Currently, general settings are used, based on knowledge about energy and nutrient requirements in relation to milk production at the group level. Individual settings, based on the actual individual response in milk yield, have the potential for a marked increase in economic profits. In the present study, adaptive dynamic models for online estimation of milk yield response to concentrate intake and length of milking interval are evaluated. The parameters in these models may change over time and are updated through a Bayesian approach for online analysis of time series. The main use of dynamic models lies in their ability to determine economically optimal settings for concentrate intake and milking interval length for individual cows at any day in lactation. Three adaptive dynamic models are evaluated, a model with linear terms for concentrate intake and length of milking interval, a model that also comprises quadratic terms, and an enhanced model (EM) in order to obtain more stable parameter estimates. The linear model is useful only for forecasting milk production and the estimated parameters of the quadratic model were found to be unstable. The parsimony of the EM leads to far more stable parameter estimates. It is shown that the EM is suitable for control and monitoring, and therefore promises to be a valuable tool for application within precision livestock farming
Dynamic feeding
Andre, Geert - \ 2011
Adaptive models for operational use in dairy farming. Increasing economic results utilizing individual variation in response.
Andre, Geert - \ 2011
Adaptive models for operational use in dairy farming : increasing economic results utilising individual variation in response
Andre, G. - \ 2011
Wageningen University. Promotor(en): Alfons Oude Lansink, co-promotor(en): Paul Berentsen; Bastiaan Engel. - [S.l.] : S.n. - ISBN 9789085858812 - 169
melkveehouderij - melkresultaten - bedrijfsresultaten in de landbouw - melkopbrengst - melkkoeien - dynamische modellen - melkinterval - melkproductie - voeropname - melktempo - nederland - dairy farming - dairy performance - farm results - milk yield - dairy cows - dynamic models - milking interval - milk production - feed intake - milking rate - netherlands
During the last century in the Netherlands milk production per cow has almost tripled. Accordingly, the amount of concentrates yearly fed per cow strongly increased. Furthermore, automation and robotisation has changed dairy management, especially by the introduction of automatic concentrate feeders and milking systems. A new management concept, emerging in the last decades, is Precision Livestock Farming (PLF). The objective of PLF is to optimize livestock production, by on-line monitoring and control of the production process, utilizing the technical possibilities of automation and robotisation. Nowadays, individual settings for daily concentrate supply and milking frequency are based on standards, ignoring individual variation in milk yield response on concentrate intake and milking frequency. This leads to the main hypothesis for this thesis research that profitability of dairy farming can be improved by utilizing information on individual variation in response. The first objective of this research was to quantify the individual variation in milk yield response to concentrate intake and milking interval length, in order to assess the economic prospects of applying individual optimal settings for concentrate supply and milking frequency. The second objective was the development and testing of adaptive models for on-line estimation of the actual individual response in milk yield to concentrate intake and milking interval length. The conclusion is that on-line estimation of the actual individual response in milk yield and milking duration is possible following a Bayesian approach for time series using an adaptive dynamic model. Besides estimation of the actual response the Bayesian approach adequately detects process deteriorations. Therefore, adaptive dynamic models provide a useful tool for control and monitoring of the dairy production process.
Milk urea concentration as an indicator of ammonia emission from dairy cow barn under restricted grazing
Duinkerken, G. van; Smits, M.C.J. ; Andre, G. ; Sebek, L.B.J. ; Dijkstra, J. - \ 2011
Journal of Dairy Science 94 (2011)1. - ISSN 0022-0302 - p. 321 - 335.
livestock buildings - nitrogen-excretion - dietary nitrogen - ventilation rate - manure stores - protein - cattle - model - volatilization - houses
Bulk milk urea concentration was evaluated to assess its potential as an indicator of ammonia emission from a dairy cow barn in a situation with restricted grazing. An experiment was carried out with a herd of, on average, 52 Holstein-Friesian dairy cows. The cows were housed in a naturally ventilated barn with cubicles and a slatted floor, were fed ensiled forages and feed supplements, and each day were allowed 8.5 h of grazing. The experiment was a balanced randomized block design, replicated 3 times. The experimental factor was the bulk milk urea level, which was adjusted to levels of 15, 35, and 55 mg of urea per 100 g of milk, respectively, by changing the level of nitrogen fertilization of the pasture, the herbage mass and grass regrowth age, and the level and type of feed supplement. Ammonia emission from the barn was measured using sulfur hexafluoride as the tracer gas. Ammonia emission generally increased upon an increase in adjusted milk urea levels. A dynamic regression model was used to predict ammonia emission from bulk milk urea concentration, temperature, and a slurry mixing index. This model accounted for 66% of the total variance in ammonia emission and showed that emission increases exponentially with increasing milk urea concentration. At levels of 20 and 30 mg of urea per 100 g of milk, ammonia emission increased by about 2.5 and 3.5%, respectively, when milk urea concentration increased by 1 mg/100 g. Furthermore, emissions from the barn increased 2.6% when temperature increased by 1°C. The study showed that bulk milk urea concentration is a useful indicator for ammonia emissions from a dairy cow barn in a situation with restricted grazing.
Method and apparatus for digestion of biomass
Andre, G. ; Timmerman, M. ; Riel, J.W. van - \ 2010
Octrooinummer: WO2010126366, verleend: 2010-11-04.
Method and apparatus for digestion of biomass for the production of biogas. The method comprises feeding biomass into a reactor comprising bacteriae for conversion of the biomass into biogas and digestate, and monitoring process physical variables including at least biogas yield and biomass feed into the reactor. The method further comprises determining a relationship forecasting biogas yield as a function of biomass feed, providing at least one process external variable to the processing unit, determining on the basis of the relationship and the at least one process external variable a desired biogas yield, determining, on the basis of the desired biogas yield and the relationship, a desired biomass feed, and adjusting the biomass feed according to the desired biomass feed.
Accounting for residual effects of previously applied nitrogen fertilizer on intensively managed grasslands
Vellinga, Th.V. ; Andre, G. ; Schils, R.L.M. ; Kraak, T. ; Oenema, O. - \ 2010
Grass and Forage Science 65 (2010)1. - ISSN 0142-5242 - p. 58 - 75.
high rainfall environment - perennial ryegrass - soil-nitrogen - rates - season - distributions - efficiency - recovery - options - systems
Only 0·20–0·70 of the fertilizer-nitrogen (N) applied to grassland is taken up in herbage in the harvest directly following application. Residual effects at subsequent harvests can be large but are poorly quantified, and rarely taken into account in current management practices. An increased understanding of N-use efficiency per harvest can improve operational management. This study systematically assessed the residual effects of previously applied N fertilizer on N uptake, dry matter (DM) yield and soil mineral-N (SMN) during the whole of the growing season. It is based on field experiments conducted on peat and mineral soils in 1991–1994. Statistical models were derived for SMN, N uptake and DM yield as a function of previously and freshly applied N fertilizer. There were clear residual effects of previously applied N in later cuts. They were relatively greater at higher levels of N fertilizer. On peat soils, 0·15–0·25 of the N applied was recovered as SMN. On mineral soils the proportion was maximally 0·08. There was a clear relationship between SMN and N uptake in the subsequent cut on mineral soils but not on peat soils. The value of SMN as a tool to adjust fertilizer-N application rates was hence found to be limited. There were clear relationships between the amount of previously applied N and the N uptake in subsequent cuts, on both soil types and over the whole of the growing season. It was concluded that the total amount of previously applied N is a useful indicator for adjusting N-fertilizer application rates
Increasing the revenues from automatic milking by using individual variation in milking characteristics
André, G. ; Berentsen, P.B.M. ; Engel, B. ; Koning, C.J.A.M. de; Oude Lansink, A.G.J.M. - \ 2010
Journal of Dairy Science 93 (2010)3. - ISSN 0022-0302 - p. 942 - 953.
simulation-model - dairy-cows - udder
The objective of this study was to quantify individual variation in daily milk yield and milking duration in response to the length of the milking interval and to assess the economic potential of using this individual variation to optimize the use of an automated milking system. Random coefficient models were used to describe the individual effects of milking interval on daily milk yield and milking duration. The random coefficient models were fitted on a data set consisting of 4,915 records of normal uninterrupted milkings collected from 311 cows kept in 5 separate herds for 1 wk. The estimated random parameters showed considerable variation between individuals within herds in milk yield and milking duration in response to milking interval. In the actual situation, the herd consisted of 60 cows and the automatic milking system operated at an occupation rate (OR) of 64%. When maximizing daily milk revenues per automated milking system by optimizing individual milking intervals, the average milking interval was reduced from 0.421 d to 0.400 d, the daily milk yield at the herd level was increased from 1,883 to 1,909 kg/d, and milk revenues increased from €498 to €507/d. If an OR of 85% could be reached with the same herd size, the optimal milking interval would decrease to 0.238 d, milk yield would increase to 1,997 kg/d, and milk revenues would increase to €529/d. Consequently, more labor would be required for fetching the cows, and milking duration would increase. Alternatively, an OR of 85% could be achieved by increasing the herd size from 60 to 80 cows without decreasing the milking interval. Milk yield would then increase to 2,535 kg/d and milk revenues would increase to €673/d. For practical implementation on farms, a dynamic approach is recommended, by which the parameter estimates regarding the effect of interval length on milk yield and the effect of milk yield on milking duration are updated regularly and also the milk production response to concentrate intake is taken into account
Economic potential of individual variation in milk yield response to concentrate intake of dairy cows
André, G. ; Berentsen, P.B.M. ; Duinkerken, G. van; Engel, B. ; Oude Lansink, A.G.J.M. - \ 2010
The Journal of Agricultural Science 148 (2010)3. - ISSN 0021-8596 - p. 263 - 276.
energy-balance - mammary-gland - lactation - cattle - variables - strategy - rations
The objectives of the current study were to quantify the individual variation in daily milk yield response to concentrate intake during early lactation and to assess the economic prospects of exploiting the individual variation in milk yield response to concentrate intake. In an observational study, data from 299 cows on four farms in the first 3 weeks of the lactation were collected. Individual response in daily milk yield to concentrate intake was analysed by a random coefficient model. Marked variation in individual milk yield response to concentrate intake was found on all four farms. An economic simulation was carried out, based on the estimated parameter values in the observational study. Individual optimization of concentrate supply is compared with conventional strategies for concentrate supply based on averaged population response parameters. Applying individual economic optimal settings for concentrate supply during early lactation, potential economic gain ranges from €0·20 to €2·03/cow/day
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