Analysis of relationships between veterinary recorded production diseases and milk production in dairy cows

Factors influencing pregnancy rate and late embryonic loss in dairy cattle

This trial was conducted on three Hungarian dairy farms between March 2003 and April 2004. The aims of this study were to examine the effect of milk production and milk contents, the day after calving (DAC) and the sire for the pregnancy rate (PR) and late embryonic loss (LEL) in dairies. Five thousand three hundred and eighty insemination was carried out in this period. Pregnancies (n = 1969) were detected by BioPryn test from 3919 blood samples between 30-36 days post insemination (PI). Retention of pregnancy was determined by rectal palpation on Day 60. LEL has been determined by the optical density (OD) of blood samples/cutoff ratio and the serum progesterone (P4) concentration 30-36 days PI. According to serum progesterone concentration the authors predicted a presumed or possible embryonic loss or maintenance of the pregnancy. The efficiency of the artificial inseminations (AI) was significantly lower 60 days within post-partum. Significant positive correlation was found between the result of early and late PR and DAC and the milk protein/fat ratio. Significant negative correlation was detected between the early and late PR the milk protein and fat content. A later stage (60 days PI) of pregnancy the milk production has a negative effect for retaining of pregnancy. More data would be necessary to state that sires can influence the reproduction ability of their progenies. This is a really important issue, because the AI bulls have a great impact on the herds and the one-way selection may cause decreased fertility on breed level as well.

The non-linear effect (determined by the penalised partial-likelihood approach) of milk-protein concentration on time to first insemination in Belgian dairy cows

The time to first insemination in dairy cows depends partly on the energy balance of the cow. Because milk-protein concentration is related to the energy balance, we investigated whether milk-protein concentration predicted the hazard of being inseminated. The main objective of the paper is to demonstrate that the relationship between milk-protein concentration and the hazard of being inseminated was not linear and that this non-linear relationship was modelled adequately using cubic-splines. The semiparametric Cox model was used to introduce protein concentration into the model as a time-varying covariate and additionally herd was added to the model as a frailty term to adjust for the clustering of the cows within a herd. We extended the penalised partial-likelihood technique to fit the frailty model with cubic-splines for the effect of the protein concentration. The model was fitted for a large database consisting of 5114 multiparous cows from 181 different farms. Low milk-protein concentration (<2.7%) was associated with a negative energy balance and this probably led to the decreased hazard. On the other hand, high milk-protein concentration (>4.0%) was linked with low milk production and it was probably a farmer's decision not to inseminate such cows, leading to the observed decreased hazard.

Monitoring daily milk yields with a recursive test day repeatability model (Kalman filter)

Mixed model methodology and recursive estimation techniques (Kalman filter) were combined to detect significant changes in the performance level of both individual cows and an entire herd. Yields were predicted for the next time of recording using all data available up to that time. Predicted yields were compared with actual measurements. If the error of prediction, or innovation, exceeded +/- 2 times its standard deviation, the observation was considered to be significantly different from the former yield level. The data comprised 30,199 records for 135 cows and 366 d. Effects fitted in the model were test day, breed, and lactation class as fixed effects and cow within lactation number as a random effect. A lactation curve was fitted within lactation class. Of the observed milk yields, 9.2% deviated significantly from the expected value in a negative direction. None of the innovation of the fixed-day effect exceeded the threshold of two standard deviations. Compared with the results of rolling average, which were calculated as the average of a 10-d period, over 20% of the observations of the daily milk yield were classified differently by the two methods. The mixed-model method for recursive estimation takes better account of environmental and lactational effects influencing daily milk yields as the rolling average. The mixed-model recursive estimation method was applicable for the detection of suspicious (i.e., outside a specified prediction interval) observations of individual cows at the time of the actual recording.

A review of the feeding-health-production complex in a dairy herd

Diseases may be an important link in the relationship between feeding and production in a dairy herd. The low frequency of relevant disorders calls for studies on survey data on a large population. However, this approach suffers from lack of detailed herd feeding data and consequently only few have studied feeding as a risk factor for disease. Therefore, we reviewed information from various studies to integrate what is known of the feeding-health-production complex in a dairy herd. The need for putting together information from different sources, the herd effects, and the fact that the effect of one factor cannot be kept constant for investigation in a real-life dynamic herd call for a conceptual model as a framework for the review. The complexity is minimized to allow the representation of important elements. Within-cow relationships (such as feeding-disease relationships, disease interrelationships, and disease-production relationships) are reviewed specifically for: ketosis, milk fever, displaced abomasum, acidosis, sole ulcers and laminitis, and bloat. The major feeding management factors involved are concentrate feeding (level and how it is provided) and overconditioned cows. Disease interrelationships are important. Generalization of production loss from diseases is complicated due to the variety of estimates and measures used.

Disease occurrence and risk factor analysis in Finnish Ayrshire cows

Disease occurrences and risk factors for the most common diseases among 39,727 Finnish Ayrshire dairy cows belonging to 2338 herds were studied. All the cows calved during 1993 and were followed until the next calving or culling. Lactational incidence risks, recurrence of, and number of treatments required for one episode of a disease are described for 17 different veterinary diagnoses. The 5 most common diseases and their lactational incidence risks were: acute mastitis (17.0%), anestrus (8.1%), ovarian cysts (7.3%), milk fever (5.4%), and ketosis (4.9%). The highest recurrence probability (14.2%) was observed for acute mastitis, followed by fertility disorders. Milk fever was the one disease that required the most repeated treatments, i.e., almost 30% of the cows were treated at least twice, whereas for most of the other diseases about 10% of the cows required more than one treatment per first episode of the disease. Logistic regression models were fitted to study the effect of milk yield and other risk factors on the occurrence of the 5 most common diseases. Increasing milk yield was found to be a risk factor for acute mastitis, ovarian cysts, and for anestrus among older cows (parity > 2), and for milk fever among younger cows (parity = 2). Several diseases were found to be risk factors for other diseases.

Effect of foot lesions on milk production by dairy cows

Individual curves for milk production of 428 cows affected by foot lesions were compared with control curves drawn from data of healthy lactating cows. First, differences were classified into patterns of milk loss, and their distribution was analyzed among the patterns with regard to breed, season, parity, stage of lactation, and milk production. Then, individual milk losses were estimated and analyzed according to the same factors. During early lactation, as during mid to late lactation, no marked modifications of the lactation curves occurred for about one-half of the cases. In 25% of the cases, milk production was affected for an expanded period (medians were 17 wk for early lactation and 12 wk for mid to late lactation). Corresponding median milk losses were 440 and 270 kg, respectively. Summer foot lesions were more severe than winter lesions, regardless of stage of lactation. Milk production at foot lesion onset was a determining factor of the amount and pattern of milk loss only for cases occurring during mid to late lactation.

Predictive model of mastitis occurrence in the dairy cow

Mastitis occurrence within a lactation and times of mastitis onset were studied for about 1000 cows. The number of mastitis cases within a lactation was modeled through overdispersed Poisson regression with individual and herd covariants. The results emphasized the role of the herd variable. Increased production potential increased the number of cases per lactation at a rate of 1.4/10 kg. Calving month also played an important role. The incidence of mastitis was greater when calving took place in early autumn or winter, which led to an expanded housing period. The interval from calving to the first case of mastitis and the intervals between successive cases were modeled for cases occurring during lactation through random selections from fitted gamma distributions, these distributions being truncated to consider the lactation length. The results of both steps can be used to simulate mastitis occurrence in different conditions.

Disease resistance in farm animals

Genetic variations in disease resistance of farm animals can be observed at all levels of defence against infectious agents. In most cases susceptibility to infections has polygenic origins. In domestic animals only a few instances of a single genetic locus responsible for disease resistance are known. A well-examined example is the Mx1 gene product of certain mice strains conferring selective resistance to influenza virus infections. Attempts to improve disease resistance by gene transfer of different gene constructs into farm animals include the use of monoclonal antibody gene constructs, transgenes consisting of antisense RNA genes directed against viruses and Mx1 cDNA containing transgenes.