• Journal of Veterinary Science
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• 제21권2호
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• pp.25.1-25.16
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• 2020

Porcine epidemic diarrhea virus (PEDV) emerged into Canada in January 2014, primarily affecting sow herds. Subsequent epidemiological analyses suggested contaminated feed was the most likely transmission pathway. The primary objective of this study was to describe general biosecurity and management practices implemented in PEDV-positive sow herds and matched control herds at the time the virus emerged. The secondary objective was to determine if any of these general biosecurity and farm management practices were important in explaining PEDV infection status from January 22, 2014 to March 1, 2014. A case herd was defined as a swine herd with clinical signs and a positive test result for PEDV. A questionnaire was used to a gather 30-day history of herd management practices, animal movements on/off site, feed management practices, semen deliveries and biosecurity practices for case (n = 8) and control (n = 12) herds, primarily located in Ontario. Data was analyzed using descriptive statistics and random forests (RFs). Case herds were larger in size than control herds. Case herds had more animal movements and non-staff movements onto the site. Also, case herds had higher quantities of pigs delivered, feed deliveries and semen deliveries on-site. The biosecurity practices of case herds were considered more rigorous based on herd management, feed deliveries, transportation and truck driver practices than control herds. The RF model found that the most important variables for predicting herd status were related to herd size and feed management variables. Nonetheless, predictive accuracy of the final RF model was 72%.

• Asian-Australasian Journal of Animal Sciences
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• 제18권9호
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• pp.1209-1216
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• 2005

This study aimed to use field data collected by the Hokkaido Dairy Cattle Milk Recording and Testing programs to estimate genetic parameters for concentration of milk urea nitrogen (MUN) and predicted Digestive Crude Protein Percentage of requirement (DCPun). Edited data consisted of 5,797,500 test-day records of MUN and yields of milk, fat, and protein obtained from 783,271cows in Holstein herds in Hokkaido, Japan. Data were divided into four datasets; for the first, second, third and fourth lactations. Two analyses were performed on data from each lactation. First, ANOVA was used to estimate the significance of the effects of several environmental factors on MUN and DCPun, after absorbing the Herd-Test-Day (HTD) effects. The effects of DIM and age.season effects had significant impact on MUN and DCPun. The second used a multi-traits repeatability model (MTRM) to estimate heritabilities and genetic correlations of milk with MUN and DCPun. Heritability estimates for MUN and DCPun in the first, second, and third lactations were 0.21:0.16, 0.20:0.16, and 0.20:0.18, respectively. Genetic correlations for milk with MUN and DCPun in the first, second, and third lactations were 0.02 - 0.17, and -0.25 - -0.39, respectively. The results indicate that MUN and DCPun are possibly effective tools for improving the energy balance, but that the relationships between MUN and other economically important traits such as feed efficiency, metabolic disease and fertility are still necessary.

• 대한수의학회지
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• 제42권4호
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• pp.485-493
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• 2002

The purpose of this study was to develope a computer program to help with gross diagnosis of protein-energy balance and feeding management practice and with the prediction about the risk possibility of productive disease such as reproductive and metabolic disorders by evaluating fat, protein, and milk urea nitrogen (MUN) from individual cow milk in dairy herd Somatic cell counts also represent the condition of udder health. The principal flow charts of this program was to check on herd management, sampling the composite milk, analysis the milk composition, conversion of data from milking equipment to program, input and analysis of data in program, and report. This program is compatible with window 95/98 system. The major analytical elements of this program were presented as; the profile of herd lactation curve analysis of the test-day milk production level, the distribution of somatic cell count, the fat to protein ratio to evaluate body energy balance, and the interpretation of dietary protein-energy balance by milk protein and MUN contents for individual cows. This program using milk fat, protein, MUN, and somatic cell counts will serve as a monitoring tool for the protein-energy balance and the feeding management practice, and for distribution of mastitis in individual cows. It will also be used to manage the nutritional and reproductive disorders and mastitis at the farm level.

• Asian-Australasian Journal of Animal Sciences
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• 제33권3호
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• pp.408-415
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• 2020

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas. Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit. Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values. Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

• Asian-Australasian Journal of Animal Sciences
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• 제28권3호
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• pp.303-310
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• 2015

The study was conducted to analyze the genetic parameters of somatic cell score (SCS) of Holstein cows, which is an important indicator to udder health. Test-day records of somatic cell counts (SCC) of 305-day lactation design from first to fifth lactations were collected on Holsteins in Korea during 2000 to 2012. Records of animals within 18 to 42 months, 30 to 54 months, 42 to 66 months, 54 to 78 months, and 66 to 90 months of age at the first, second, third, fourth and fifth parities were analyzed, respectively. Somatic cell scores were calculated, and adjusted for lactation production stages by Wilmink's function. Lactation averages of SCS ($LSCS_1$ through $LSCS_5$) were derived by further adjustments of each test-day SCS for five age groups in particular lactations. Two datasets were prepared through restrictions on number of sires/herd and dams/herd, progenies/sire, and number of parities/cow to reduce data size and attain better relationships among animals. All LSCS traits were treated as individual trait and, analyzed through multiple-trait sire models and single trait animal models via VCE 6.0 software package. Herd-year was fitted as a random effect. Age at calving was regressed as a fixed covariate. The mean LSCS of five lactations were between 3.507 and 4.322 that corresponded to a SCC range between 71,000 and 125,000 cells/mL; with coefficient of variation from 28.2% to 29.9%. Heritability estimates from sire models were within the range of 0.10 to 0.16 for all LSCS. Heritability was the highest at lactation 2 from both datasets (0.14/0.16) and lowest at lactation 5 (0.11/0.10) using sire model. Heritabilities from single trait animal model analyses were slightly higher than sire models. Genetic correlations between LSCS traits were strong (0.62 to 0.99). Very strong associations (0.96 to 0.99) were present between successive records of later lactations. Phenotypic correlations were relatively weaker (<0.55). All correlations became weaker at distant lactations. The estimated breeding values (EBVs) of LSCS traits were somewhat similar over the years for a particular lactation, but increased with lactation number increment. The lowest EBV in first lactation indicated that selection for SCS (mastitis resistance) might be better with later lactation records. It is expected that results obtained from these multi-trait lactation model analyses, being the first large scale SCS data analysis in Korea, would create a good starting step for application of advanced statistical tools for future genomic studies focusing on selection for mastitis resistance in Holsteins of Korea.

• Asian-Australasian Journal of Animal Sciences
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• 제33권9호
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• pp.1387-1399
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• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.787-794
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• 2005

The aim of this study was 1) to confirm the practical efficiency of a routine milk P4 monitoring system for postpartum reproductive management of a dairy herd, and 2) to evaluate the relationship between the blood metabolic profiles, milk quality and body weight of individual cows in the farm records, which may reflect the postpartum nutritional condition, and the time of postpartum resumption of ovarian activity of dairy cows. A total of 116 Holstein cows was used in the present study. First, during the period of Experiment 1, postpartum reproductive management based on weekly measured milk P4 concentration from individual cows was conducted. Compared with the reproductive records of the past two years without P4 monitoring, although the day from calving to first AI did not change, both the number of AI until pregnant (with P4; 1.9 times vs. without P4; 2.9 times) and the days open (with P4; 95.1 days vs. without P4; 135.8 days and 133.8 days) were significantly decreased. In Experiment 2, the measurement of blood constituents such as albumin, blood urea nitrogen, packed cell volume, ammonia, glucose, total cholesterol, non-esterified, AST and $\gamma$-GTP was performed on the blood samples taken once approximately 14 days postpartum, to monitor both health and nutritional conditions. The milk constituent parameters, such as milk protein (MP), milk fat (MF), SNF and lactose, collected from the monthly progeny test of individual cows, were used to monitor the postpartum nutritional status. Furthermore, the data obtained from the routine measurements of body weight were used to calculate the rate of peripartum body weight loss. The resumption day of the postpartum estrous cycle was assumed from the milk P4 profiles of individual cows. There was no clear relationship between each parameter from blood examination and those from resumption time. However, the cows had low values of MP, and SNF, which significantly affected the resumption of the postpartum estrous cycle. Similarly, a higher rate of body weight loss indicated a significant delay (more than 1 month) in the resumption of the postpartum estrous cycle, compared with the groups that had a medium or lower rate of body weight loss. The results of the present study demonstrated that the implementation of routine milk P4 monitoring-based postpartum reproductive management, together with milk quality parameters and routine BW data available in field conditions may be utilized as a practical approach for increasing the postpartum reproductive efficiency of a high yielding dairy herd.

• Asian-Australasian Journal of Animal Sciences
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• 제29권12호
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• pp.1682-1687
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• 2016

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.

• Journal of Animal Science and Technology
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• 제47권2호
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• pp.147-158
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• 2005

The purpose of this study was to find out the effects that daughters' incomplete lactation records affect sire's breeding values through genetic evaluation using RRTDM(random regression test-day model). First, we estimated genetic parameters and breeding values on sires having complete lactation records of daughter by RRTDM, second, we changed complete lactation records of specific sires into incomplete records by various methods. Third, the breeding values were compared between complete and incomplete records. Finally, this study aimed to find out the methods to minimize the estimation errors of young bulls' breeding values. Data used in this study were collected from the dairy herd improvement program, and a total of 97,562 records were composed of 10,929 first parity with both parents known, since 1999. Breeding values on the daughters from randomly chosen sires were calculated and compared with among 90 day, 150day, and 200 day's incomplete records. For milk yields, sire's ranks of breeding values used by complete lactation records were very different from sire's ranks of breeding values obtained by incomplete lactation records(Rank_90 cut, 150cut, 200 cut).The differences were also obtained between complete lactation records(per305_full) and incomplete lactation record (per_90 cut, 150cut, 200 cut) in breeding values regarding persistency. Especially, the differences between per_90 cut and per305_full were very large(from 1.8 kg to 145kg).

• Journal of Animal Science and Technology
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• 제48권2호
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• pp.143-150
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• 2006

본 연구는 현재 유전평가에 사용하는 모델보다 많은 장점을 지니고 있는 임의회귀 검정일 모형(Random regression test-day model)을 이용할 때 마지막 세대의 불완전한 검정기록이 유전능력에 어떤 영향을 주는지 알아보고자 실시하였다.이용된 재료는 유우군능력검정사업을 통하여 수집된 2000년 1월부터 2005년 6월까지의 825,157개의 초산의 검정일 자료를 이용하였으며, 유전모수와 종모우의 육종가 추정은 REMLF90, BLUPF90을 이용하였다.