• Journal of Animal Science and Technology
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• v.51 no.2
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• pp.111-122
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• 2009

This study was performed to make it possible to adjust milk production records which are changing with days in milk more accurately as developing new 305-day adjustment factors considering current circumstance and to offer easier application by converting adjustment factors to formulas. Total 4,264,347 records were used in this analysis after eliminating unusual value and data was classified by first parity and over second parity. Herd-year effects were classified with 2,878 and 19,783 classes in first parity and over second parity, respectively and number of subclass of age-calving season-lactation stage effects were 136 (age 2, calving season 4, lactation stage 17). For calculation of least square mean, SAS GLM was used and multiplicative adjustment factors were developed. The result of error analysis, deviations between means of adjusted yields and cumulated yields were the lowest in new adjustment factor which was developed in this study comparing with other adjustment factors which were developed in the past (94', 02') in first parity and in over second parity, results of adjustment factors which were developed in 2002 and this study were similar. For easier application, formulas of 305-day adjustment factors were developed using SAS NLIN.

• Journal of Animal Science and Technology
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• v.50 no.3
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• pp.285-292
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• 2008

Data were taken from the dairy herd improve- ment program from the year 2000, composed of 10,929 first lactation cows consisting of 290,144 test-day records and 37,723 udder type records. The objective of the study was to estimate genetic and phenotypic correlation between fore udder attachment, rear udder height, rear udder width, udder cleft, udder depth, and somatic cell score (SCS) and to calculate heritability of udder depth, front teat length and SCS in Holstein cattle in Korea. The variance component estima- tion using test day model was determined by a derivative-free algorithm-restricted maximum likeli- hood(DF-REML) analysis method. Generally phenotypic correlations were very low between udder traits and lactation SCS which varied from －0.03 to －0.06. Heritability of all type traits and SCS was smaller than 0.12. The results of this study would be applicable to SCS using linear genetic evaluation for future studies.

• Journal of Animal Science and Technology
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• v.47 no.6
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• pp.919-924
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• 2005

This study was carried out to estimate the effects of parity, milking time, milking interval and days in milk(DIM) on variation in milk yield between consecutive milkings(am to pm to am), morning and evening milk yield and its components, somatic cell counts(SCS), milking duration, milk flow rate and peak milk flow in Holstein dairy cattle. Records from one hundred and twenty two heads of Holstein cattle at National Livestock Research Institute, Korea were used for this study from July 1 to August 8, 2005. The experimental herd had average 1.6$\pm$0.9 parities, 199.8$\pm$109.1 DIM and 12.26$\pm$4.06kg milk yields at each milking. Milking yield, percent milk fat and SNF, milking duration and average milk flow were significantly varied by parity, milking time and DIM. Percent milk protein and lactose were varied by parity and DIM, however SCS and average milk flow were affected by parity and milking time. Milking interval significantly affected the consecutive, morning and evening milk yield and average milk flow. However, MUN was not affected by parity, milking time, DIM and milking interval. Milk yield was decreased with increasing parity. Milk yield in the morning was higher than that of in the evening. Milk yield between consecutive milking was not affected by parity, however, affected by milking time. Percent milk Fat, SNF and SCS were higher at in evening milk than those of in morning milk. Milk protein, lactose, SNF, SCS, milking duration and peak milk flow rate were influenced by parity. This study suggested that milk yield variation between consecutive milking, milking flow rate, and milking duration could be important traits for enhancing Holstein cattle productivity however, and more study is needed to estimate genetic parameters for such traits.

• Journal of agriculture & life science
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• v.50 no.5
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• pp.173-182
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• 2016

This study was aimed to identify the phenotypic relationships between calving interval and lactation curve parameters in Korean Holstein cow. The data of 36,505 lactation records was obtained from the Dairy Herd Improvement program run by Dairy Cattle Improvemnet Center of National Agricultural Federation of Korea. All lactation records were collectied from the multiparous cows calving between 2011 to 2013. The estimated lactation curves were drawn using Wood model based on actual milk yield records, and NLIN Procedure of SAS program (ver. 9.2). General linear multivariate models for calving interval, 305-d milk yield, lactation parameters(A, b, c), persistency, peak day, and peak yield included fixed effects of calving year-season (spring, summer, fall and winter) and parity(2, 3 and 4). For calving interval, 305-d milk yield, lactation parameters(A, b, c), persistency, peak day and peak yield, all two fixed effect(calving year-season, parity) were significant(p<0.05). The estimated lactation functions using Wood model for 2, 3, and 4 parity were yt=24.66t0.175e-0.00302t, yt=24.69t0.192e-0.00334t, and yt=24.22t0.200e-0.00341t, respectively. Phenotypic correlation (partial residual correlation) between calving interval and 305-d milk yield, A, b, c, persistency, peak day, and peak yield were 0.093, -0.014, 0.028, -0.046, 0.099, 0.085, and 0.052, respectively. To conclude, if calving interval increase then ascent to peak, persistency, peak day and peak yield are increase, and descent after peak is decrease. So, total 305-d milk yield is increase.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.739-748
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• 2003

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 improvement 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 the estimated 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 within 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.

• Journal of agriculture & life science
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• v.51 no.6
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• pp.89-105
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• 2017

This study utilized 32,312 records of 17 linear type and 10 conformation traits(including final scores) of Hanwoo cows in the KAIA(Korea Animal Improvement Association) ('09~'10), with 60,556 animals in the pedigree file. Traits included stature, body length, strength, body depth, angularity, shank thickness, rump angle, rump length, pin bone width, thigh thickness, udder volume, teat length, teat placement, foot angle, hock angle, rear leg back view, body balance, breed characteristic, head development, forequarter quality, back line, rump, thigh development, udder development, leg line, and final score. Genetic and residual(co) variances were estimated using bi-trait pairwise analyses with EM-REML algorithm. Herd-year-classifier, year at classification, and calving stage were considered as fixed effects with classification months as a covariate. The heritability estimates ranged from 0.03(teat placement) to 0.42(body length). Rump length had the highest positive genetic correlation with pin bone width(0.96). Moreover, stature, body length, strength, and body depth had the highest positive genetic correlations with rump length, pin bone width, and thigh thickness(0.81-0.94). Stature, body length, strength, body depth, rump length, pin bone width, and thigh thickness traits also had high positive genetic correlations.