JDS communications最新文献

Vitamin E is essential in mitigating the impact of oxidative stress on periparturient dairy cows and neonatal calves. Therefore, it is essential to measure circulating vitamin E concentrations accurately. Currently, the only reliable method is an expensive and time-consuming procedure using liquid chromatography-mass spectrometry (LC-MS). However, a cheaper and faster method has been developed, which allows the quantification of circulating vitamin E through the use of a handheld fluorometric analyzer (HFA) called the vitamin E iCheck (BioAnalyt GmbH). Our objective was to compare the accuracy of the HFA to the reference LC-MS method for measuring vitamin E in bovine samples. A total of 177 samples collected for other studies were used: 98 newborn calf serum samples from a vitamin E supplementation study (including treated and control animals) and 79 whole-blood samples from cows 1 to 7 d postcalving. Vitamin E concentrations were measured on thawed calf serum and fresh cow EDTA blood using the HFA, following the manufacturer's instructions. Whole blood from cows was then centrifuged to obtain plasma. Vitamin E was also quantified in calf serum and cow plasma at the Michigan State University Veterinary Diagnostic Laboratory using LC-MS. Calf and cow results were analyzed separately because they represent different biological matrices and physiological times. In each dataset, results between the HFA and LC-MS determinations were compared using Passing-Bablok regressions and Bland-Altman plots. The HFA showed a poor linear relationship with LC-MS for calf serum and cow plasma (intercept = 0.33 and 0.67 μg/mL, respectively). The HFA unreliably estimated vitamin E, with a mean bias of −3.2 and 0.6 μg/mL for calves (vitamin E concentration range: 0.28 to 30.75 μg/mL) and cows (0.8 to 5.88 μg/mL), respectively. Moreover, 40.4% of the calf samples read below the linear range of acceptable results for the HFA, making it unsuitable for this age group. Hence, under the conditions of our study, the HFA yielded unreliable results and cannot be recommended for field use.

Mastitis is among the costliest diseases affecting dairy cows, partly due to the resulting permanent reduction in the quantity and quality of milk produced. Most mastitis cases involve pathogenic organisms entering the cow's mammary gland through the teat canal. The teat has natural defenses against these pathogens that can be disrupted during milk harvesting. These disruptions of the teat's circulatory system and tissue integrity can predispose them to mastitis. Traditionally, machine milking–induced changes in teat blood circulation and tissue integrity have been assessed by means of manual evaluation and ultrasonography. Infrared thermography has previously been shown to produce precise and consistent measurements of skin surface temperatures (SST) on cows' hind teats. Our objective was to describe the variability in the teat SST following machine milking. Describing the variability in teat SST before and after milking could be useful to guide further studies to elucidate the physiology of the effects of milking on teat defense mechanisms. In this observational study, thermographic images of both hind teats from 140 cows immediately pre- and postmachine milking were analyzed. The average SST were subsequently determined at the proximal, middle, and distal aspects of each hind teat using image analysis software. The LSM (95% CI) from general linear mixed models of the pre- and postmilking SST, respectively, were 33.6 (33.5–33.8)°C and 35.4 (35.3–35.5)°C at the proximal aspect, 33.2 (33.1–33.4)°C and 35.2 (35.1–35.3)°C at the middle aspect, and 32.3 (32.1–32.5)°C and 34.0 (33.9–34.1)°C at the distal aspect. The observed increase in SST from pre- to postmilking SST at all 3 aspects of the teat suggest that some of the variability in the SST can be attributed to the milking event. Future research is warranted to investigate the biological relevance of SST changes during machine milking and any potential change in teat defense mechanisms, risk of mastitis, or other pathologies.

Balancing dairy cow diets for AA is an effective strategy to reduce dietary CP concentration, maintain levels of productivity, and increase nitrogen use efficiency. Most studies evaluating supplemental rumen-protected Met (sRPMet) focus on cows in established lactation; however, there is an increasing body of evidence suggesting that initiating sRPMet feeding to transition dairy cows is beneficial to production, reproduction, and health. Therefore, the objective of this study was to evaluate the effects of feeding sRPMet before and after calving through meta-analysis on pre- and postpartum performance and selected metabolic parameter responses. A literature search was conducted for published papers reporting on the effects of feeding sRPMet starting before parturition and continuing through early lactation, resulting in 21 publications with 40 treatment comparisons. Studies provided sRPMet both before (average of 8.20 [±2.94 SD] g of metabolizable sRPMet/d, which began at 19.3 [±4.23 SD] d before calving) and after calving (10.53 [±3.30 SD] g of metabolizable sRPMet/d for an average of 85.9 [±38.36 SD] DIM). Prepartum DMI and pre- and postpartum BW and BCS were unaffected by sRPMet. In contrast, postpartum DMI, milk yield, milk fat and true protein yield, and milk fat and true protein concentration were increased by sRPMet. Most production responses to sRPMet declined as lactation progressed where the predicted response in milk fat and true protein yield was 118 and 92 g/d at 21 DIM, respectively. Postpartum circulating metabolites were unaffected by sRPMet; however, the sample sizes for these analyses were much lower than for production responses. This meta-analysis indicates that feeding sRPMet before and after calving results in increased productivity beyond that which would be expected by providing sRPMet in established lactation alone.

This study aimed to evaluate the effectiveness of an automated tail movement sensor device (Moocall; Bluebell, Dublin, Ireland) to predict time of calving in dairy cows. At a commercial dairy farm in southern Ontario, Moocall (MC) devices were attached with the device's strap, and an additional elastic wrap, to the tail of cows approximately 3 d before their expected calving date. The MC has 2 types of alarm, a high activity alarm in the previous hour (1HA), and a high activity alarm in the previous 2 h (2HA); these alarms were sent and registered to the MC software. The calving and close-up pens were video monitored to determine the exact time of the onset of stage II of calving (amniotic sac visible at the vulva) and the end of stage II of calving (total expulsion of the calf). A total of 49 cows were enrolled, but we excluded 13 animals from the analysis as they had 3 or more MC drops from the tail (n = 6), a swollen tail (n = 3), or the MC device was lost (n = 4); this left 36 cows. In total, the device dropped off 21 (42%) cows. The average number of alarms (1HA and 2HA) per cow before stage II of calving was 2.7 ± 2.3 (± standard error). The first alarm after fitting the device on the tail was used to determine the device's sensitivity and specificity. Depending on the interval before the onset of parturition (i.e., 2, 4, 8, 12 h) in which the alarm was triggered, sensitivity varied from 5% to 72% and specificity from 50% to 93%. The false positive rate varied between 6% and 50% depending on the interval from the alarm to the onset of parturition. The high false positive and device drop rates (despite the addition of the elastic wrap) may compromise the applicability of this sensor device in a commercial setting.

Proinflammatory cytokines are involved in regulating several reproductive processes that occur during the periovulatory period, including ovulation, corpus luteum formation, and preimplantation embryo development. The objective of this study was to determine whether stimulation of proinflammatory cytokines through administration of mycobacterium cell wall fraction (MCWF; Amplimune, NovaVive) could improve embryo development following superovulation in dairy heifers. A total of 34 independent embryo recovery procedures were performed using nulliparous Holstein heifers (n = 20; age 12–18 mo) as donors. For superovulation, dominant follicle removal was performed and an intravaginal progesterone device was inserted on d −6. Thirty-six hours later, on d −4, FSH (420 IU total) was administered in a decreasing dose regimen consisting of 8 injections given twice daily at 12-h intervals. Prostaglandin F_2α was administered in conjunction with the fifth and sixth injections of FSH on d −2 and the intravaginal progesterone device was removed on the morning of d −1. Twenty-four hours later, on d 0, donors received their randomly assigned treatment (sterile saline or MCWF, 5 mL, i.m.) and gonadotropin-releasing hormone was administered to induce ovulation. Donors were artificially inseminated with frozen-thawed semen at 12 and 24 h after induced ovulation. Nonsurgical embryo recovery procedures were performed on d 7. Recovered structures were evaluated using a stereomicroscope to assess embryo development. There was no effect of MCWF treatment on the numbers of total structures, unfertilized oocytes, degenerate embryos, transferable embryos, or blastocysts. However, there was a trend for donors treated with MCWF to have a greater proportion of blastocysts out of total structures recovered. Overall, the efficacy of superovulation in virgin dairy heifer donors was not improved by administration of MCWF during the peri-ovulatory period, but results indicate that MCWF treatment may enhance embryo developmental kinetics.

Quantification of potassium (K) excretion in dairy cattle is important to understand the environmental impact of dairy farming. To improve and monitor the environmental impact of dairy cows, there is a need for a simple, inexpensive, and less laborious method to quantify K excretion on dairy farms. The adoption of empirical mathematical models has been shown to be a promising tool to address this issue. Thus, the current study aimed to develop empirical predictive models for K excretion in dairy cattle from urine and feces that can help evaluate efficiency and monitor the environmental impact of milk production. To develop urine K (K_Ur, g/d) and fecal K (K_Fa, g/d) excretion prediction models, published literature that involved 45 and 54 treatment means from 10 and 14 studies, respectively, were used. Some studies reported either urinary or fecal K excretion or both, but in total, treatment means used to develop the models were from 17 studies. The linear mixed models were fitted with the fixed effect of K intake, DMI, dietary K content, urine volume, milk yield, and water intake, and the random effect of study weighted according to the number of observations. Leave-one-study out cross-validation was used to evaluate the performance of the proposed models and the best model was based on the lowest root mean square prediction error as a percentage of the observed mean values (RMSPE%) and highest concordance correlation coefficient (CCC). As expected, most daily K excretion was through urine (202.5 ± 92.1 g/d) than through feces (43.5 ± 21.0 g/d), and among the proposed models, the model including dietary K concentration showed poor predictive ability for both K_Ur and K_Fa with the lowest CCC values (−0.15 and −0.02, respectively) and systematic bias. The model developed using DMI to predict K_Fa excretion showed reasonable accuracy, as indicated by RMSPE, CCC, and R²_marginal of 46.6%, 0.42, and 48%, respectively. Among the proposed models for K_Ur and K_Fa, the model with K intake demonstrated better predictive performance, showing minimal systematic bias and random errors due to data variability of >92%. While these proposed models suggested that reducing K intake can lead to a decrease in K excretion, it is important to ensure that dairy cows receive adequate amounts of this nutrient to maintain optimal health and productivity, especially during periods of heat stress.