A field study on the effects of dietary monensin on milk production and milk composition in dairy cows

The objectives of this study were to quantify the effect of 16 ppm of dietary monensin on milk production and composition of dairy cows, and to investigate factors having a potential impact on this effect. Data were generated from a total of 3577 Holstein dairy cows (47 herds) in Quebec enrolled in a herd-level, randomized clinical trial investigating the effects of monensin supplementation. Milk production and composition data were collected from monthly dairy herd improvement (DHI) testing. Monensin increased milk production by 0.9 kg/cow/d in cows under 150 days in milk (DIM) (P < 0.05). Monensin decreased milk fat percentage by 0.18 percentage points during the whole lactation (P < 0.05). This decreasing effect was larger for component-fed cows (P < 0.05) and for cows being fed low levels of dietary physically effective particles (P < 0.05) when compared respectively to cows fed total mixed ration and cows fed high levels of dietary physically effective particles. The results of this study suggest that monensin influences milk production and milk composition of dairy cows, and that diet composition and feeding system influence those effects.     

The effect of mastitis on milk progesterone concentration in dairy cows

A within cow comparison was made between milk progesterone levels in healthy and mastitic quarters. Material was collected from cows with mastitis induced by bacterial inoculation, or by inoculation with bacterial endotoxin. Furthermore material from cows with spontaneous subclinical mastitis was used. Milk progesterone levels were lowered due to mastitis. However, the decrease was not large enough to cause misinterpretation of where in the oestrous cycle (luteal phase or non-luteal phase) the samples were taken.     

检测奶牛乳汁孕酮的免疫生物传感器优化

为了完善已建立的孕酮免疫生物传感器的检测性能,本试验应用碳化二亚胺法将11α-羟基孕酮半琥珀酸和OVA制备成孕酮完全抗原,其浓度达0.6 mg/m L。在此基础上建立了以乳汁为基质的孕酮生物传感器的标准曲线(y=-4.9461x+8.7982,R2=0.993 2),进一步确立了检测乳汁孕酮的线性范围为0.31 ng/m L~50ng/m L,检测限为0.31 ng/m L,灵敏度为0.15 ng/m L,而且孕酮与皮质酮、皮质醇、雄烯二酮的免疫交叉反应较低,表明特异性较好。批内、批间变异系数分别为7.7%和7.5%,回收率为95.8%~115.7%,生物传感器稳定性在4℃保存4 d。该优化的奶牛乳汁孕酮免疫生物传感器的性能参数符合规定的标准,为检测妊娠、乏情和繁殖障碍疾病的奶牛乳汁孕酮含量提供了工具。     

Effect of post-insemination progesterone supplementation on pregnancy rate in dairy cows

Progesterone plays an important role in maintenance of pregnancy. It is hypothesized that insufficient progesterone early in pregnancy may result in embryonic loss, and that supplemental progesterone would decrease pregnancy loss in dairy cows. In Experiment 1, 84 cows and 16 heifers from a single dairy operation were selected randomly. Within each age category, controlled internal drug release (CIDR) devices were inserted into the vagina of every other female on Day 4 post-insemination and removed on Day 18 post-insemination. Transrectal ultrasonography was performed to determine pregnancy at 4 time periods [days 30 to 37 (week 5), days 44 to 51 (week 7), days 58 to 65 (week 9), and days 86 to 93 (week 13)]. Progesterone supplementation had no effect on pregnancy rate. In Experiment 2, there were no differences in progesterone concentrations between cows that did and did not receive a CIDR. Further, cows receiving CIDR devices did not have an increase in circulating progesterone concentrations 30 min or 1 h after CIDR insertion. It appears that progesterone supplementation does not increase circulating levels of progesterone in the early pregnant lactating dairy cow. Alterative methods to influence progesterone concentrations and/or early embryonic loss need to be investigated.     

The milk progesterone test as an aid to the diagnosis of cystic ovaries in dairy cows

Two field trials were carried out by five experienced veterinary surgeons to evaluate the milk progesterone test as an aid to the differential diagnosis of cystic ovaries in dairy cows. Of 200 cystic cows, 71 per cent were diagnosed clinically as follicular and 29 per cent as luteal cases; 80 per cent of the cases occurred in the six winter months November to April. The progesterone assay indicated that the diagnosis was correct in 84 per cent of the follicular cases but only 54 per cent of the luteal cases. Seventy-four per cent of the confirmed cystic cases responded to treatment within two weeks according to milk progesterone tests and there were no significant treatment differences. Overall, 80 per cent of the cows became pregnant on average 38 days after treatment having received an average of 1.70 inseminations each. Milk yield data in the first trial indicated that the cystic cows were not significantly higher yielders than their herd-mates.     

Prostaglandin F2 alpha-induced estrus in open cows and presumed abortion in pregnant cows with unobserved estrus in a herd monitored by milk progesterone assay

Data were obtained in a large Florida herd of about 1800 Holstein cows. All cows were inseminated by the herdsman who did the pregnancy checks and who also administered drugs. The herdsman injected 103 cows with prostaglandin F2 alpha during the time this herd was under continuous observation by the authors who were conducting an unrelated research project. These cows consisted of 86 open (never bred) cows which had no estrus observed during the first 70 days postpartum, or no second estrus observed within 30 days after a previous estrus, and 17 cows previously inseminated. Two-thirds (57) of the 86 open cows were in estrus within 4 days. The 17 previously inseminated cows appeared to be pregnant, based upon progesterone profiles, when these were inadvertently given prostaglandin F2 alpha by the herdsman. Progesterone declined in all cows and they were in estrus in 7 +/- 4 days (mean +/- standard error). This result of presumed abortion reflects the luteolytic effectiveness of the drug and the importance of instructing any laymen users to follow necessary precautions to avoid undesirable effects.     

Automated detection of estrus and mastitis in dairy cows

The development and test of detection models for oestrus and mastitis in dairy cows is described in a PhD thesis that was defended in Wageningen on June 5, 2000. These models were based on sensors for milk yield, milk temperature, electrical conductivity of milk, and cow activity and concentrate intake, and on combined processing of the sensor data. The models alert farmers to cows that need attention, because of possible oestrus or mastitis. A first detection model for cows, milked twice a day, was based on time series models for the sensor variables. A time series model describes the dependence between successive observations. The parameters of the time series models were fitted on-line for each cow after each milking by means of a Kalman filter, a mathematical method to estimate the state of a system on-line. The Kalman filter gives the best estimate of the current state of a system based on all preceding observations. This model was tested for 2 years on two experimental farms, and under field conditions on four farms over several years. A second detection model, for cow milked in an automatic milking system (AMS), was based on a generalization of the first model. Two data sets (one small, one large) were used for testing. The results for oestrus detection were good for both models. The results for mastitis detection were varying (in some cases good, in other cases moderate). Fuzzy logic was used to classify mastitis and oestrus alerts with both detection models, to reduce the number of false positive alerts. Fuzzy logic makes approximate reasoning possible, where statements can be partly true or false. Input for the fuzzy logic model were alerts from the detection models and additional information. The number of false positive alerts decreased considerably, while the number of detected cases remained at the same level. These models make automated detection possible in practice.     

Detection of delayed cyclicity in dairy cows based on progesterone content in monthly milk samples

We examined whether infrequent milk sampling for progesterone analysis could be used as a management or diagnostic tool by the dairy farmer to predict delayed ovarian cyclicity in dairy cows. The data included 1040 lactations from 324 Swedish Red cows and 183 Swedish Holstein cows and were randomly divided into two datasets. A logistic regression model was fit to the first dataset and the model was then validated on the other dataset. The model was also validated using a British dataset comprising 1212 lactations from 1080 British Holstein-Friesian cows. The dependent variable was whether delayed ovarian cyclicity occurred or not, delayed ovarian cyclicity defined as progesterone levels below threshold value for the first 56 or 45 days postpartum in the Swedish or British dataset, respectively. The basic model included the effects of breed, parity, season and housing type. To the basic model various progesterone-based measurements were added. These were the interval from calving to commencement of luteal activity and the percentage of samples with luteal activity within 60 days after calving, using all samples in the databases or one sample per month. The accuracy of the conditional probability of delayed ovarian cyclicity calculated with the different models was obtained using receiver operating characteristic (ROC) curves and calculating the area under curve. Sensitivity and specificity were calculated for cut-off probabilities using the ROC analyses. The accuracy was highest (0.94-0.99) when including the progesterone measurements based on milk sampling for progesterone analysis 2-3 times per week. The accuracy was between 0.85 and 0.88 when the progesterone measurements with monthly milk sampling were added to the model and 0.76 or 0.67 with the basic model. This study clearly shows that infrequent milk sampling for progesterone analysis, such as once a month as in the regular milk recording system, could be used to predict delayed ovarian cyclicity in dairy cows. This increases the opportunity for earlier treatment of anovulatory dairy cows and may therefore decrease involuntarily extended calving intervals in the herd.     

Progesterone concentration in defatted milk of dairy cows in early pregnancy.

Progesterone concentrations have been measured in defatted milk of British Friesian cows of four herds during the oestrus cycles (other than short cycles) immediately before artificial insemination (AI) at oestrus and immediately after AI (in non-pregnant cows), and during early pregnancy. Differences in mean progesterone concentrations between herds were significant (P less than 0.05) on all days within the day 10-18 period after AI, both in pregnant and in non-pregnant, inseminated cows but were not significant between pregnant and non-pregnant cows within herds until day 17 or 18. It is concluded that up to this time (that of luteolysis in non-pregnant cows) undefined factors, variable among herds, can have a much greater influence on the rate of progesterone secretion by corpora lutea and consequent progesterone concentration in plasma and milk than does the presence of conceptuses. Maximum mean progesterone concentration reached during early pregnancy in two herds did not differ significantly; it was reached in the 11-15-day period in one herd but not until 46-50 days in the second. Mean progesterone concentration declined after day 90.     

A routine 20-22 days post-service milk progesterone monitoring in dairy cows. Economic evaluation

Three hundred and sixty inseminated Holstein cows were monitored in a controlled trial for low milk progesterone concentration 21-23 days post-breeding. Information about low progesterone cows was given to herdsmen for the experimental group only. Of the cows in the experimental group with milk progesterone of less than or equal to 4.5 ng/ml, 56.0% were inseminated within 2 days of monitoring compared to 28.8% of the control animals. Of the cows reaching the 42-day rectal pregnancy diagnosis, 13.7% and 43.6% were negative for the experimental and the control groups respectively. Inter-service intervals were 34.5 +/- 14.5 days and 44.3 +/- 17.7 days for the experimental and control groups respectively. Pregnancy rates were the same for 264 cows served on routine progesterone monitoring and for 318 cows bred on behavioural oestrus when matched to farm and day of breeding. A gain of US $32.5 (an equivalent of 85 l milk) per lactation for a cow in the monitored herd was established using the data in a model of a 250-cow herd with a total pregnancy goal of 82.4%.     

Economic impact of the use of prostaglandin to induce estrus in dairy cows

An economic model concerning the value of using prostaglandin (PG) in dairy cows with nondetected estrus was developed. Considering numerous and varied assumptions, it was more profitable to treat cows with PG and to breed the cows at a detected estrus than it was not to treat the cows and to wait to breed the cows at a detected estrus. Generally, using timed artificial insemination, it was also more profitable to breed PG-treated cows than it was not to use PG. However, timed insemination was less profitable than was breeding PG-treated cows by artificial insemination at a detected estrus.     

Validation of a direct time-resolved fluoroimmunoassay for progesterone in milk from dairy and beef cows

The aim of this study was to validate a direct time-resolved fluoroimmunoassay (TR-FIA) for quantifying progesterone concentrations in milk during the bovine oestrous cycle. Holstein-Friesian and suckled and non-suckled Japanese Black cows were used to demonstrate the relationship between milk and plasma progesterone concentrations and to monitor progesterone profiles in milk and plasma during the oestrous cycle. The minimum detection level of the assay was 1.53ng/mL. Progesterone concentrations in milk and plasma changed in a similar manner throughout the oestrous cycle in dairy and beef cows, and milk and plasma progesterone profiles were significantly correlated (P<0.001). The study confirmed that a direct TR-FIA can be used to monitor the oestrous cycle in cattle and to quantify progesterone concentrations in whole milk.