The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage ($0.213{\pm}0.007$). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.
We investigated the effect of reproductive herd health program (RHHP) on the reproductive performance in high yielding dairy herds. Data collected from 205 lactations at Boeun County, Chungbuk from April 2001 to Dec. 2003 included postpartum reproductive and metabolic diseases, body condition score (BCS), reproductive performance and milking records. First we compared the reproductive performance of cows without RHHP (pre-RHHP group) and cows with RHHP (RHHP group). Intervals from calving to first service (99.6 vs. 81.8 days) and to conception (160.3 vs. 131.8 days) were shorter in the RHHP group than in the pre-RHHP group. Secondly, we determined the effect of milk yield (305 days) on the occurrence of postpartum diseases, BCS changes, and reproductive performance in cows under RHHP. The occurrence of metritis and metabolic diseases were greater in the over-10,000 kg group than in the under-10,000 kg group. The over-10,000 kg group lost more body condition than the under-10,000 kg group from calving to month 3 postpartum. Nevertheless, reproductive performance did not differ between the two groups. These results indicate that reproductive performance can be improved by the application of RHHP in high yielding dairy herds and that reproductive performance in the cows under RHHP are not affected by high milk yielding.
The daily food intake for dairy cows has to be effectively controlled to breed a sound group of cows as well as to enhance the productivity of the cows. But, feed stuffs are fed in the common bulk for a group of cows in most cases despite that the individual food intake has to be varied. To obtain the feed for each cow, both the nutrient requirements and the nutrient composition of fred have to be provided in advance, which are based on the status of cows such as weigh marginal weight amount of milk, fat concentration in milk, growth and milking stages, and rough feed ratio, etc. Then, the mixed ration fur diet would be computed by the nutrient requirements constraints. However, when TMR (Total Mixed Ration) is conventionally supplied for a group of cows, it is almost impossible to get an optimal feed mixed ration meeting the nutrient requirements of each individual cow since the constraints are usually conflicting and over-constrained although they are linear. Hence, addressed in this paper is a simulated annealing (SA) technique to find the food intake for dairy cows, considering the characteristics of individual or grouped cows. Appropriate parameters fur the successful working of SA are determined through preliminary experiments. The parameters include initial temperature, epoch length. cooling scheduling, and stopping criteria. In addition, a neighborhood solution generation method for the effective improvement of solutions is presented. Experimental results show that the final solution for the mixture of feed fits the rough feed ratio and some other nutrient requirements such as rough fiber, acid detergent fiber, and neutral detergent fiber, with 100 percent, while fulfilling net energy for lactating, metabolic energy, total digestible nutrients, crude protein, and undegraded intake protein within average five percent.
This study was conducted to survey the relationship between the somatic cell count (SCC), and California mastitis test (CMT) & mastitis. A total of 328 quarter milk samples were collected from 211 cows suspected to have mastitis; Both SCC and CMT were performed on the samples. Milk smear was stained with Broadhurst and Paley stain and the cells were classified into either epithelial or blood cells. Bacterial isolation was made and antimicrobial susceptibility was tested. Of the 328 quarters, 78 ($23.8{\%}$) were CMT negative with SCC <750,000/ml. As expected, CMT score increased with the increase of SCC. The number of epithelial cells decreased with the increasing number of somatic cells, while the opposite was the case with the number of blood cells. The critical point was when the SCC reached 1,000,000/ml. Up to 1,000,000 cells/ml, the number of epithelial cells was greater than that of blood cells. The results indicate that when epithelia:blood cell ratio is 58.1:41.9, the milking line should be checked and bacterial isolation be performed on the samples in order to identity mastitis.
Eom, Jun Sik;Kim, Eun Tae;Kim, Hyun Sang;Choi, You Young;Lee, Shin Ja;Lee, Sang Suk;Kim, Seon Ho;Lee, Sung Sill
Animal Bioscience
/
v.34
no.2
/
pp.213-222
/
2021
Objective: The metabolites that constitute the rumen fluid and milk in dairy cattle were analyzed using proton nuclear magnetic resonance (1H-NMR) spectroscopy and compared with the results obtain for other dairy cattle herds worldwide. The aim was to provide basic dataset for facilitating research on metabolites in rumen fluid and milk. Methods: Six dairy cattle were used in this study. Rumen fluid was collected using a stomach tube, and milk was collected using a pipeline milking system. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by principal component analysis, partial least squares discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. Results: The total numbers of metabolites in rumen fluid and milk were measured to be 186 and 184, and quantified as 72 and 109, respectively. Organic acid and carbohydrate metabolites exhibited the highest concentrations in rumen fluid and milk, respectively. Some metabolites that have been associated with metabolic diseases (acidosis and ketosis) in cows were identified in rumen fluid, and metabolites associated with ketosis, somatic cell production, and coagulation properties were identified in milk. Conclusion: The metabolites measured in rumen fluid and milk could potentially be used to detect metabolic diseases and evaluate milk quality. The results could also be useful for metabolomic research on the biofluids of ruminants in Korea, while facilitating their metabolic research.
Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.
Objective: The aim was to compare the behavioral response to full separation of cows and calves maintained together for 100 days or 24 h. Methods: Twelve Holstein-Friesian cow-calf pairs were enrolled into either treatment or industry groups (n = 6 cow-calf pairs/group). The treatment cows and calves were maintained on pasture together for 106±8.6 d and temporarily separated twice a day for milking. The Industry cows and their calves, were separated within 24 h postpartum. Triaxial accelerometer neck-mounted sensors were fitted to cows 3 weeks before separation to measure hourly rumination and activity. Before separation, cow and calf behavior was observed by scan sampling for 15 min. During the separation process, frequency of vocalizations and turn arounds were recorded. At separation, cows were moved to an observation pen where behavior was recorded for 3 d. A CCTV camera was used to record video footage of cows within the observation pens and behavior was documented from the videos in 15 min intervals across the 3 d. Results: Before separation, industry calves were more likely to be near their mother than Treatment calves. During the separation process, vocalization and turn around behavior was similar between groups. After full separation, treatment cows vocalized three times more than industry cows. However, the frequency of time spent close to barrier, standing, lying, walking, and eating were similar between industry and treatment cows. Treatment cows had greater rumination duration, and were more active, than industry cows. Conclusion: These findings suggest a similar behavioral response to full calf separation and greater occurrence of vocalizations, from cows maintained in a long-term, pasture-based, cow-calf rearing system when ompared to cows separated within 24 h. However, further work is required to assess the impact of full separation on calf behavior.
Hyun Sang Kim;Jun Sik Eom;Shin Ja Lee;Youyoung Choi;Seong Uk Jo;Sang Suk Lee;Eun Tae Kim;Sung Sill Lee
Animal Bioscience
/
v.36
no.8
/
pp.1199-1208
/
2023
Objective: The purpose of this study was to perform a comparative analysis of metabolite levels in serum and milk obtained from cows fed on different concentrate to forage feed ratios. Methods: Eight lactating Holstein cows were divided into two groups: a high forage ratio diet (HF; 80% Italian ryegrass and 20% concentrate of daily intake of dry matter) group and a high concentrate diet (HC; 20% Italian ryegrass and 80% concentrate) group. Blood was collected from the jugular vein, and milk was sampled using a milking machine. Metabolite levels in serum and milk were estimated using proton nuclear magnetic resonance and subjected to qualitative and quantitative analyses performed using Chenomx 8.4. For statistical analysis, Student's t-test and multivariate analysis were performed using Metaboanalyst 4.0. Results: In the principal component analysis, a clear distinction between the two groups regarding milk metabolites while serum metabolites were shown in similar. In serum, 95 metabolites were identified, and 13 metabolites (include leucine, lactulose, glucose, betaine, etc.) showed significant differences between the two groups. In milk, 122 metabolites were identified, and 20 metabolites (include urea, carnitine, acetate, butyrate, arabinitol, etc.) showed significant differences. Conclusion: Our results show that different concentrate to forage feed ratios impact the metabolite levels in the serum and milk of lactating Holstein cows. A higher number of metabolites in milk, including those associated with milk fat synthesis and the presence of Escherichia coli in the rumen, differed between the two groups compared to that in the serum. The results of this study provide a useful insight into the metabolites associated with different concentrate to forge feed ratios in cows and may aid in the search for potential biomarkers for subacute ruminal acidosis.
Data including 1,372,050 milk records pertaining to 438,019 cows from 1983 to 2011 collected during performance tests conducted by the National Livestock Cooperative Dairy Improvement Center were used to calculate milk income and profit of individuals and investigate the effects of production levels of early lactation (parity 1 and 2, respectively). Individuals with a moderate level of early lactation stayed longer in herds. Among parity 1, the 9,000 kg or higher group had a lower mean number of lactations than the overall mean of 3.13. The 7,000 kg or lower and 10,000 kg or higher groups had lower mean life time milking days than the overall mean of 1,076.8 days. Standard deviations of lifetime traits tended to decrease as production levels increased. For parity 2, the 11,000 kg or higher group had a lower mean number of lactation than the overall mean of 3.43. The lifetime milking days was highest in the 12,000 kg group (1,212.0 days), and generally smaller in the lower groups. Profit increased as the production level of groups increased for both parity 1 and 2. In groups with low production levels, profit of parity 1 was higher than that of parity 2, while the reverse was true in groups with high production levels. These results suggest that individuals in the low production groups had a greater likelihood to be culled due to reproductive or other problems. Furthermore, the accuracy of the prediction of lifetime profit of individuals with a milk yield of 305 days seems to be higher for parity 2 than parity 1; therefore, it is desirable to predict lifetime profit using the 305d milk yield of parity 2. In conclusion, breeding goals are based on many factors in functions for the estimation of profit; however, production levels during early lactation (parity 1 and 2) can be used as indicators of profit to extend profitability.
The study was carried out to find out the changes of the sex hormone levels in the milk of Holstein cows during the reproductive stages such as the estrous cycle, pregnancy and periparturient period. The FSH, LH, estradiol-17$\beta$ and progesterone from the milk samples were assayed by radioimmunoassay methods. The results of this study were summarized as follows: 1. The levels of progesterone and estradiol-17$\beta$ were similar among inter-quarters, but they were higher in after milking than before milking times, with no statistical significance. 2. The milk progesterone levels during the estrous cycles reached a peak mean level of 3.55$\pm$0.26ng/$m\ell$ at 15 days after estrus and they did not show any differences among the length of estrous cycles. The estradiol-17$\beta$ levels during the estrous cycles showed a peak level of 36.40$\pm$2.38pg/$m\ell$ at estrus, and decreased(17.20$\pm$0.46 pg/$m\ell$ to 18.65$\pm$1.26pg/$m\ell$) at luteal phase. 3. The FSH levels during the estrous cycles ranged from 2.25$\pm$0.23mIU/$m\ell$ to 4.35$\pm$0.24mIU/$m\ell$ showing significant changes. The LH levels during the estrous cycles gradually increased and remained a peak level of 10.90$\pm$0.36mIU/$m\ell$ from 20 to 25 days after estrus. 4. The progesterone levels during the pregnancy were decreased from 30 to 60 days after artificial insemination, and therafter continuously increased until 240 days. The estradiol-17$\beta$ levels during the pregnancy were 24.56$\pm$1.19pg/$m\ell$ at day 30 after artificial inseminaton, and increased rapidly until 180 days. The levles were agagin decreased by 26.17$\pm$3.03pg/$m\ell$ until 210 days and markedly increased by 68.00$\pm$8.70pg/$m\ell$ until 240 days. 5. The prolactin levels during the pregnancy were 31.27$\pm$2.31ng/$m\ell$ and 42.60$\pm$2.37ng/$m\ell$ at day 150 and 240 after artificial insemination respectively. The LH levels during the pregnancy reached a peak of 27.47$\pm$7.90mIU/$m\ell$ at day 30 after artificial insemination, and thereafter gradually decreased. 6. The progesterone levels during the periparturient period reached a peak of 4.61$\pm$0.34ng/$m\ell$ at day 3 prepartum, and thereafter gradually decreased, and showed 2.05$\pm$0.60ng/$m\ell$ at day 7 postpartum. The estradiol-17$\beta$ levels during the periparturient period showed high level from 207.23$\pm$6.04pg/$m\ell$ at day 1 prepartum to 239.90$\pm$13.90pg/$m\ell$ at day 2 prepartum, and thereafter began to decline and reached 51.87$\pm$1.72pg/$m\ell$ at by 7 postpartum. 7. The prolactin levels during the periparturient period showed relatively higher level at the time of parturition. The LH levels during the periparturient period rnage from 6.32$\pm$0.32mIU/$m\ell$ to 13.90$\pm$1.37mIU/$m\ell$ showing significant changes. 8. The progesterone levels(4.6$\pm$0.8ng/$m\ell$) of the pregnant cows were significantly higher than those (1.84$\pm$1.4ng/$m\ell$) of nonpregnant cows. The cows of artificial insemination from 61 to 90 days after parturition showed higher progesterone levels. 9. During 20 to 25 days after artificial insemination, the accuracy of pregnancy diagnosis from milk progesterone levels were 94.4% for nonpregnant cows(<2.3ng/$m\ell$), and 75.0% for pregnant cows( 3.2ng/$m\ell$). The average overall accuracy of pregnancy prediction for nonpregnant and pregnant cows 83.3% 10. The results obtained this study suggest that the understanding of the endocrinological mechanisms by means of milk hormone analysis during the estrous cycle, pregnancy and parturition would give the basic information needed for increasing efficiency of reproduction. This study would not only provide an accurate method of the early pregnancy diagnosis by milk progesterone levels but also contribute to the research of providing the method of detecting of FSH levels in milk, which was difficult in blood serum.
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