Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

Singh, Ajay,Singh, Avtar,Singh, Manvendra,Prakash, Ved,Ambhore, G.S.,Sahoo, S.K.,Dash, Soumya Asian Australasian Association of Animal Productio 2016 Animal Bioscience Vol.29 No.6

A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

정량적 관리 기반 무기체계 시험업무 프로세스 개선 연구

나태흠,이주연,김영민 한국시스템엔지니어링학회 2024 시스템엔지니어링학술지 Vol.20 No.spc1

Today, the importance of test and evaluation of defense systems is increasing day by day. In performing efficient defense systems test works, process improvement based on quantitative management is essential. The purpose of this paper is to present the results of process improvement for the defense systems test works of the test organization based on quantitative management activities. As a methodology to confirm process improvement performance, the ‘MPM(Managing Performance and Measurement)’ practice area of the CMMI model was applied. The quantitative management model for defense systems test works was developed so that it could be practically applied not only to the entire test organization but also to the organization at the department level that actually performs the test work. Finally, the application cases of the quantitative management model for defense system test works and the results of process improvement were described.

Estimation of Genetic Parameters for Milk Production Traits Using a Random Regression Test-day Model in Holstein Cows in Korea

Kim, Byeong-Woo,Lee, Deukhwan,Jeon, Jin-Tae,Lee, Jung-Gyu Asian Australasian Association of Animal Productio 2009 Animal Bioscience Vol.22 No.7

This study was conducted to compare three models: two random regression models with and without considering heterogeneity in the residual variances and a lactation model (LM) for evaluating the genetic ability of Holstein cows in Korea. Two datasets were prepared for this study. To apply the test-day random regression model, 94,390 test-day records were prepared from 15,263 cows. The second data set consisted of 14,704 lactation records covering milk production over 305 days. Raw milk yield and composition data were collected from 1998 to 2002 by the National Agricultural Cooperative Federation' dairy cattle improvement center by way of its milk testing program, which is nationally based. The pedigree information for this analysis was collected by the Korean Animal Improvement Association. The random regression models (RRMs) are single-trait animal models that consider each lactation record as an independent trait. Estimates of covariance were assumed to be different ones. In order to consider heterogeneity of residual variance in the analysis, test-days were classified into 29 classes. By considering heterogeneity of residual variance, variation for lactation performance in the early lactation classes was higher than during the middle classes and variance was lower in the late lactation classes than in the other two classes. This may be due to feeding management system and physiological properties of Holstein cows in Korea. Over classes e6 to e26 (covering 61 to 270 DIM), there was little change in residual variance, suggesting that a model with homogeneity of variance be used restricting the data to these days only. Estimates of heritability for milk yield ranged from 0.154 to 0.455, for which the estimates were variable depending on different lactation periods. Most of the heritabilities for milk yield using the RRM were higher than in the lactation model, and the estimate of genetic variance of milk yield was lower in the late lactation period than in the early or middle periods.

Comparison of the fit of automatic milking system and test-day records with the use of lactation curves

Sitkowska, B.,Kolenda, M.,Piwczynski, D. Asian Australasian Association of Animal Productio 2020 Animal Bioscience Vol.33 No.3

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.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle

Naserkheil, Masoumeh,Miraie-Ashtiani, Seyed Reza,Nejati-Javaremi, Ardeshir,Son, Jihyun,Lee, Deukhwan Asian Australasian Association of Animal Productio 2016 Animal Bioscience Vol.29 No.12

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.

Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

Cho, C.I.,Alam, M.,Choi, T.J.,Choy, Y.H.,Choi, J.G.,Lee, S.S.,Cho, K.H. Asian Australasian Association of Animal Productio 2016 Animal Bioscience Vol.29 No.5

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of $polynomials{\times}3$ types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

임의회귀 검정일 모형을 이용한 홀스타인 젖소의 1산차 산유형질 및 체세포지수에 대한 유전모수

이득환,조주현,한광진 한국동물자원과학회 2003 한국축산학회지 Vol.45 No.5

The objective of this study was to estimate genetic parameters for test-day milk production and somatic cell score using field data collected by dairy herd improvements program in Korea. Random regression animal models were applied to estimate genetic variances for milk production and somatic cell score. Heritabilities for milk yields, fat percentage, protein percentage, solid-not-fat percentage, and somatic cell score from test day records of 5,796 first lactation Holstein cows were estimated by REML algorithm in single trait random regression test-day animal models. For these analyses, Legendre polynomial covariate function was applied to model the fixed effect of age-season, the additive genetic effect and the permanent environment effect as random. Homogeneous residual variance was assumed to be equal throughout lactation. Heritabilities as a function of time were calculated from curve parameters from univariate analyses. Heritability estimates for milk yields were in range of 0.13 to 0.29 throughout first lactation. Heritability estimates for fat percentage, protein percentage and solid-not-fat percentage were withing 0.09 to 0.11, 0.12 to 0.19 and 0.17 to 0.23, respectively. For somatic cell score, heritabilities were within 0.02 to 0.04. Heritabilities for milk productions and somatic cell score were fluctuated by days in milk with comparing 305d milk production.

조선후기 유생전강 운영 연구

정지연 교육사학회 2019 교육사학연구 Vol.29 No.2

This study focuses on examining the tendencies of the operation of Yuseang-jeon'gang(儒生殿講) in the late Joseon dynasty. From King Injo's reign to King Gyeongjong's(1623-1724), due to the many times regular Yuseang-jeon'gang was skipped, the king implemented the irregular Yuseang-jeon'gang and the regular Yuseang-jeon'gang supervised by the king. From King Yeongjo's reign to King Jeongjo's(1724-1800), Yuseang-jeon'gang was conducted without major interruptions. King Yeongjo preferred Dogi-jeon'gang(到記殿講), an irregular test, to Ilcha-jeon'gang(日次殿講), a regular test. King Jeongjo spilt the regular Yuseang-jeon'gang into Ilcha-jeon'gang and ChunChuDogi(春秋到記), a test originating from Dogi-jeon'gang. From King Sunjo's reign to King Cheoljong's(1800-1863), the core of Yuseang-jeon'gang was ChunChuDogi. While the focus of Yuseang-jeon'gang was supplementation of regular Yuseang-jeon'gang up until King Yeongjo's reign, starting from King Jeongjo's reign it changed to the stable conduct of Yuseang-jeon'gang by ChunChuDogi. 본고는 조선후기 유생전강의 규정 및 운영 과정을 검토함으로써 해당시기 유생전강 운영의 경향성을 파악하고자 했다. 연구의 결과는 다음과 같다. 인조-경종 연간(1623-1724) 유생전강은 다른 성균관 과시와 마찬가지로 간헐적으로 시행되었다. 이 시기 유생전강은 1년 6번의 시행 횟수를 채우지는 못했지만, 후대로 갈수록 장기간 결행하는 경우는 은사의 혜택이 큰 친림전강이나 불시의 도기전강을 실시하여 정기전강의 결행을 보완하였다. 영조‧정조대(1724-1800) 유생전강은 정기전강의 결행을 보완함과 동시에 유생들의 경학 공부를 장려하기 위한 방책으로 활용되었다. 영조는 정기의 일차전강보다는 불시에 시행하는 도기전강을 자주 실시함으로써 유생들의 경서 학습과 성균관 거재를 장려했다. 정조는 영조대 중반에 시행되었던 도기유생에 대한 분제강(分製講)을 춘‧추도기로 정식화하고 성균관 과시 중 가장 높은 위상을 확립시켰다. 정조는 일차전강에 관‧학 재임의 자원일경강(自願一經講)을 시행함으로써 사학 재임의 경학 공부를 장려하고, 상재생제술(上齋生製述)을 겸행함으로써 생원‧진사의 제술 실력을 향상시키는 방편으로 일차전강을 활용했다. 순조-철종 연간(1800-1863) 유생전강은 정조대까지 확립된 규정을 기본으로 하여 운영되었다. 이 시기 일차전강은 특정시기를 제외하고는 거의 운영되지 않은 반면, 춘‧추도기 전강은 대부분 1년 2번의 시행 횟수를 채우며 안정되게 운영되었다. 순조-철종 연간 장기간의 일차전강 결행에 대한 문제제기가 없었던 것은 춘‧추도기 전강을 통하여 전강 응시자의 은사 획득이 가능했기 때문이다. 영조대까지 유생전강이 정기전강의 결행을 보완하는 데 중점을 두었다면, 정조대 이후 유생전강은 춘‧추도기의 설치를 통해 1년 2번의 안정적인 유생전강의 시행을 보장했다. 순조-철종대 유생전강은 영조‧정조대의 경서 학습 및 성균관 거재 장려 등과 같은 정책적 지향보다는, 유생들의 공부 경향을 인정하고 그에 따른 인센티브를 보장하는 방식을 유지했다.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

S. Meseret,B. Tamir,G. Gebreyohannes,M. Lidauer,E. Negussie 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.9

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

Meseret, S.,Tamir, B.,Gebreyohannes, G.,Lidauer, M.,Negussie, E. Asian Australasian Association of Animal Productio 2015 Animal Bioscience Vol.28 No.9

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.