Biomedical subjects

H Hogeveen

Publications and source records attributed to H Hogeveen.

13 recordsLinked to original sources

PubMed2007

The profitability of automatic milking on Dutch dairy farms.

Several studies have reported on the profitability of automatic milking based on different simulation models, but a data-based study using actual farm data has been lacking. The objective of this study was to analyze the profitability of dairy farms having an automatic milking system (AMS) compared with farms using a conventional milking system (CMS) based on real accounting data. In total, 62 farms (31 using an AMS and 31 using a CMS) were analyzed for the year 2003 in a case control study. Differences between the years 2002 and 2003 also were analyzed by comparing a subgroup of 16 farms with an AMS and 16 farms with a CMS. Matching was based on the time of investment in a milking system (same year), the total milk production per year, and intensity of land use (kg/ha). Results from 2003 showed that the farms with an AMS used, on average, 29% less labor than farms with a CMS. In contrast, farms using a CMS grew faster (37,132 kg of milk quota and 5 dairy cows) than farms with an AMS (-3,756 kg milk quota and 0.5 dairy cows) between 2002 and 2003. Dairy farmers with a CMS had larger (euro7,899) revenues than those with an AMS. However, no difference in the margin on dairy production was detected, partly because of numerically greater (euro6,822) variable costs on CMS farms. Dairy farms were compared financially based on the amount of money that was available for rent, depreciation, interest, labor, and profit (RDILP). The CMS farms had more money (euro15,566) available for RDILP than the AMS farms. This difference was caused by larger fixed costs (excluding labor) for the AMS farms, larger contractor costs (euro6,422), and larger costs for gas, water, and electricity (euro1,549). Differences in costs for contractors and for gas, water, and electricity were statistically significant. When expressed per full-time employee, AMS farms had greater revenues, margins, and gross margins per full-time employee than did CMS farms. This resulted in a substantially greater (but not statistically significant) RDILP per full-time employee (euro12,953) for AMS farms compared with CMS farms. Depreciation and interest costs for automatic milking were not available but were calculated based on several assumptions. Assuming larger purchase costs and a shorter depreciation time for AMS than for CMS, costs for depreciation and interest were larger for AMS farms than for CMS farms. Larger fixed costs should be compensated for by the amount of labor that has become available after introducing the milking robot. Therefore, farm managers should decide whether the extra time acquired by automatic milking balances against the extra costs associated with an AMS.

Animals↗

PubMed2005

A partial budget model to estimate economic benefits of lactational treatment of subclinical Staphylococcus aureus mastitis.

Subclinical Staphylococcus aureus mastitis is rarely treated during lactation because it is widely believed to be uneconomical, although there are no economic studies that support this view. Partial budgeting was used to develop a deterministic simulation model to estimate the net cost or benefit of antibiotic treatment of subclinical S. aureus mastitis during lactation. Direct and indirect effects of treatment were taken into account, including prevention of clinical flare-ups and contagious transmission. Input variables were based on literature and on 2003-2004 prices in the Netherlands. When contagious transmission of S. aureus was likely (reproductive ratio R = 5.3), 3- and 8-d treatments resulted in an average net profit of 95.62 euros and 142.42 euros, respectively, compared with no treatment. When the probability of S. aureus transmission was low (R = 0.32), the average economic benefit of 3- or 8-d treatment was -21.12 euros and -57.70 euros, respectively. On low-transmission farms, 3-d treatment was profitable when the appropriate cows were selected for treatment using known risk factors for cure. Sensitivity analysis showed that the 6 most influential input variables in the model were chance of bacteriological cure, R, probability of culling, retention pay-off, and cost of antibiotics and bacterial culture. Although the economic outcome of lactational treatment of subclinical S. aureus mastitis is highly herd-, cow-, and strain-dependent, treatment is economically justified in many situations.

Animals↗

PubMed2004

Electrical conductivity of milk: ability to predict mastitis status.

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 < 0.001) when cows were subclinically or clinically infected. A simple threshold test and discriminant function analysis was used to validate the ability of the EC traits to distinguish between cows in different health groups. Traits reflecting the level rather than variation of EC, and in particular the IQR, performed best to classify cows correctly. By using this trait, 80.6% of clinical and 45.0% of subclinical cases were classified correctly. Of the cows classified as healthy, 74.8% were classified correctly. However, some extra information about udder health status was obtained when a combination of EC traits was used.

Animals↗

PubMed2003

Sensors and management support in high-technology milking.

Two directions can be distinguished in the development of high-tech milking equipment: 1) high-capacity milking parlors with a high throughput of cows per person per hour and 2) automatic milking systems in which manual labor is replaced by a milking robot. High-capacity milking parlors are developed in such a way that one operator is able to milk many cows, partly by automation and partly by optimization of available labor. In such parlors, one operator can milk up to 125 cows per hour. This means that there are only a few seconds available for udder preparation. In an automatic milking system, a robot takes over all manual labor during milking. Currently available systems have one robot arm working with one milking stall (one-stall system) or one robot arm working with more milking stalls (multiple-stall systems). Cows have to go to the automatic milking system voluntarily. Therefore, there is a large variation in milking intervals. Moreover, a large variation between milkings and between cows was observed in milk flow rate, machine-on time and udder preparation time. Both developments in high-tech milking have effects on the milk ejection. The small amount of time dedicated to udder preparation in high-capacity milking parlors has negative effects on the milk ejection, among others leading to more bimodal milk flow curves and longer machine-on time. In automatic milking systems, the variation in time between udder preparation and cluster attachment and in milking frequency might have an effect on milk ejection. Lactation physiology can play a role in solving the questions around milk ejection in high-tech milking systems. The introduction of high-tech milking systems makes decision support systems using sensors necessary. These systems should assist in detection of abnormal milk and mastitis. To a lesser extent, diseased cows need to be brought to the attention of the dairy farmer. Some sensors are currently available for this purpose, but they do not fulfill all demands. In the near future other sensors might be developed. It is important that this development is demand driven and not technology driven. Lactation physiology can play an important role in the determination of milk components useful for automatic detection.

Animal Husbandry↗

PubMed2001

Recovery of cow teats after milking as determined by ultrasonographic scanning.

Recovery time of teat tissue after milking was determined by ultrasonographic scanning. Teat-canal length, teat-end width, teat-wall thickness, and teat-cistern width of 18 cows varying in parity and lactation stage were measured in duplicate before and directly after milking and every hour for 8 h. The ratio between teat-wall thickness and teat-cistern width was calculated. The effects of time after milking and teat position on the teat parameters were estimated using REML models. The mean differences of ultrasound measurements of teat-end width and teat-canal length between duplicate measurements were 3.6 and 8.2%, and between d 4.4 and 7.8%, respectively. Teat-wall thickness and teat-cistern width were more variable (15.3 and 22% between duplicates, and 13.6 and 19.9% between days, respectively). Teat recovery after milking took a considerable amount of time: teat-wall thickness, 6 h; teat-end width, >8 h; teat-canal length, >8 h; teat-cistern width for rear teats, 3 h, and front teat 8 h, and the ratio of teat-wall thickness and teat-cistern width, 6 h. Ultrasonographic scanning of teat parameters was a useful tool to study teat changes caused by milking. Teat recovery took more time than expected, which makes caution necessary when increasing the milking frequency.

Animals↗

PubMed2001

Relationship between teat-end callosity and occurrence of clinical mastitis.

A longitudinal study in 15 herds, with a total of 2157 cows, was conducted to examine the relationship between teat-end callosity (TEC) and the incidence of clinical mastitis. During the 1.5-yr study period, clinical mastitis was diagnosed by the farmers based on clinical signs. Teat-end callosity was scored every month according to a teat-end callosity classification system, which discriminates between teat-end callosity thickness (TECT) and roughness (TECR). Differences in TECT between healthy and clinical mastitis quarters within infected cows were small but significant 3 mo before (0.13 higher), in the month during which the clinical mastitis occurred (0.08 higher), and in the following 2 mo (0.06 and 0.05 higher). To compare TECT and TECR between cows with and without clinical mastitis, 199 cows with clinical mastitis were paired with control cows based on herd, days in milk, and parity. Clinical mastitis cows had more TEC than their healthy herd mates, particularly when clinical mastitis occurred between the second and fifth months of lactation. Clinical Escherichia coli mastitis in the second or third month of lactation occurred in cows with less TEC than in cows with clinical mastitis caused by other pathogens. Clinical culture-negative, yeast, Klebsiella pneumoniae, and Enterobacter aerogenes mastitis cows had more TECT and TECR than other cows with clinical mastitis in the same month of lactation. Pointed teat ends had higher TECT and TECR than flat or inverted teat ends. Teat-end callosity thickness increased with a higher milk yield at peak production.

Animals↗

PubMed2000

The effect of the introduction of automatic milking systems on milk quality.

Changes in milk quality after the introduction of automatic milking systems on 28 Dutch dairy farms were examined and observations were compared with milk quality characteristics on two groups of farms milking either two (49 farms) or three times (28 farms) per day in a conventional milking parlor. Milk quality data were collected from January 1996 until March 1998. The farms with an automatic milking system are pioneers and cannot be considered representative of Dutch dairy farms. After the introduction of the automatic milking system, a statistically significant increase in total bacterial plate count and in free fatty acids was observed. Total bacterial plate count, free fatty acids, and freezing point were higher on farms using the automatic milking system than in the other two groups of farms. Somatic cell counts did not change after the introduction of the automatic milking system, but were already rather high in herds using the automatic milking system compared with the other groups of farms. The introduction of automatic milking systems used in the study resulted in a decrease in milk quality compared with conventional systems.

Animals↗

PubMed2000

Classification and longitudinal examination of callused teat ends in dairy cows.

To examine the development of teat end callosity thickness and roughness in early lactation and to quantify cow factors of interest, a system to classify teat end condition was developed. A distinction was made between rough and smooth rings around the teat orifice. In addition, a classification of the degree of callosity was developed. Kappa coefficients for the repeatability of scoring by this classification system by different workers were 0.71 for teat end callosity thickness and 0.86 for teat end callosity roughness. The teat end callosity classification system was used for a longitudinal study with 40 cows during the first 14 wk of lactation. Models were built to predict teat end callosity thickness and roughness, machine-on time, and milk yield. For the response variables, teat end callosity thickness, machine-on time, and milk yield, the consecutive measurements appeared to follow a lactation curve model with a subject-specific general slope and intercept. Teat end callosity increased rapidly the first 8 wk. Cow factors such as days in milk, parity, machine-on time, and teat end shape were associated with the degree of teat end callosity, and the probability of the callosity ring to become rough. Teat end callosity thickness did not decrease within the 14-wk trial period for most teats. Pointed or round teat ends showed more callus than inverted teat ends. Longer machine-on time resulted in a higher probability of the callosity ring to become rough. Rear teats showed less callosity than front teats in this study.

Animals↗

PubMed1996

Effects of concentrate intake on subsequent roughage intake and eating behavior of cows in an automatic milking system.

Twenty-three cows were kept in a free-stall barn with an automatic system for milking and feeding. The cows were offered mixed silage for ad libitum consumption. Concentrates were fed with the automatic milking system. This experiment examined the eating behavior of cows and the relationship between the intake of concentrate and the subsequent intake of roughage in a free-stall barn with an automatic milking system. An individual meal criterion was used to characterize the meal pattern of each cow. Daily roughage intake and the time spent on meals ranged from 25.6 to 40.2 kg/d and from 70.1 to 240.0 min/d, respectively. Meal duration and size did not differ, regardless of whether concentrate was eaten or not eaten during the premeal interval. Multiple regression analysis showed that the partial regression coefficient for the duration of the premeal interval was significant for each cow, and the regression coefficient for the intake of concentrate during the premeal interval was significant for 78% of the cows. Separation of the eating phases into concentrate and roughage showed that the cows made many repeated traffic cycles through the automatic milking system and feeding section of the barn, thus revealing a high demand for concentrate under the experimental conditions.

Animal Feed↗

PubMed1995

[Subclinical and clinical mastitis on dairy farms in The Netherlands: epidemiological developments].

In this review a number of the main epidemiological developments in the field of udder health in the Netherlands are summarized. The changes considering the bulk milk somatic cell count are described, as are the population dynamics of subclinical mastitis. Additionally, clinical mastitis caused by Escherichia coli and Staphylococcus aureus and their risk factors are reviewed. Finally, some future developments and the possible applications of these developments are discussed.

Animals↗

PubMed1995

A knowledge-based system for diagnosis of mastitis problems at the herd level. 1. Concepts.

Much specialized knowledge is involved in the diagnosis of a mastitis problem at the herd level. Because of their problem-solving capacities, knowledge-based systems can be very useful to support the diagnosis of mastitis problems in the herd. Conditional causal models with multiple layers are used as a representation scheme for the development of a knowledge-based system for diagnosing mastitis problems. Construction of models requires extensive cooperation between the knowledge engineer and the domain expert. The first layer consists of three overview models: the general overview conditional causal model, the contagious overview conditional causal model, and the environmental overview conditional causal model, giving a causal description of the pathways through which mastitis problems can occur. The conditional causal model for primary udder defense and the conditional causal model for host defense are attached to the overview models at the second layer, and the conditional causal model for deep primary udder defense is attached to the conditional causal model for the primary udder defense at the third layer. Based on quantitative user input, the system determines the qualitative values of the nodes that are used for reasoning. The developed models showed that conditional causal models are a good method for modeling the mechanisms involved in a mastitis problem. The system needs to be extended in order to be useful in practical circumstances.

Animals↗

PubMed1995

A knowledge-based system for diagnosis of mastitis problems at the herd level. 2. Machine milking.

A knowledge-based system for the diagnosis of mastitis problems at the herd level must search for possible causes, including malfunctioning milking machines or incorrect milking technique. A knowledge-based system on general mechanisms of mastitis infection, using hierarchical conditional causal models, was extended. Model building entailed extensive cooperation between the knowledge engineer and a domain expert. The extended knowledge-based system contains 12 submodels underlying the overview models. Nine submodels were concerned with mastitis problems arising from machine milking. These models are briefly described. The knowledge-based system has been validated by other experts after which the models were adjusted slightly. The final knowledge-based system was validated to data collected at 17 commercial dairy farms with high SCC in the bulk milk. Reports containing the farm data were accompanied by recommendations made by a dairy farm advisor. This validation showed good agreement between the knowledge-based system and the dairy farm advisors. The described knowledge-based system is a good tool for dairy farm advisors to solve herd mastitis problems caused by a malfunctioning milking machine or incorrect milking technique.

Animals↗

PubMed1994

Development of an on-line mastitis detection system within an integrated knowledge-based system for dairy farm management support.

Some aspects of automated clinical mastitis detection and diagnosis are discussed. Knowledge representation techniques for the different steps in the diagnostic process are presented. The main focus of this paper is on automated early detection, based on data that are automatically collected in the milking parlour. Principal component analysis, logistic regression and back-propagation neural networks were used in the analysis of the automatically collected data. The 3 techniques did not differ greatly in performance. All the techniques performed better when data from milking with observed clinical signs were used, compared with data from milking before clinical symptoms were noticed. Healthy quarters were mostly correctly classified by all techniques. It seems unlikely that all clinical mastitis cases can be detected at milking before visible clinical signs occur.

Animals↗