• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.39-48
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• 2006

This study utilized test day of somatic cell score data of dairy cattle from 2000 to 2004. The number of data used were 124,635 of first parity, 134,308 of second parity, 77,862 of third parity, 41,787 of forth parity and 37,412 of fifth parity. The data was analyzed by least square mean method using GLM to estimate the effects of calving year, age, lactation stage, parity and season on somatic cell score. Variance component estimation using test day model was determined by using expectation maximization algorithm- restricted maximum likelihood (EM-REML) analysis method. In each parity, somatic cell score was low for younger group and was relatively high in older groups. Likewise, for lactation stage, the score was low in early-lactation and high in late-lactation in first parity and second parity. Nevertheless, for the third, fourth and fifth parity, however, high somatic cell score was observed in mid-lactation. Generally, the score was high in the peak. Although in fourth and fifth parity, the score was low in late-lactation. Environmental effect of season, somatic cell score was generally low from September to November for all parities. The score was high between June and August when the milk production is usually low. The heritability in each parity were 0.05, 0.09, 0.10, 0.05 and 0.05 for parity 1, 2, 3, 4, 5, respectively. Genetic variance value was estimated to be high in second, third and fifth parity in early-lactation and to be low in first and forth parity.

• 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 the korean veterinary medical association
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• v.30 no.10
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• pp.592-615
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• 1994

1. 체세포점수(SCS)는 적절히 사용되었을 때 큰 이익을 가져다 주는 가치있는 조사항목이다. 2. 권장된 유방염 예방관리계획을 잘 적용할 수 있는 대부분의 우군에서는 SCS 목표를 3.0으로 잡는 것이 바람직하다. 3. 체세포점수(SCS)자료는 비유횟수, 착유일수와 신규감염, 만성감염, 중증감염된 그 해의 달 그리고 평균 SCS별로 정돈하면 아주 유용하다. 4. 체세포점수(SCS)양상과 SCS치가 높은 젖소들은 우군의 유방염 문제를 진단하는데 유용하며 목표를 세우고 유방염 예방대책을 수립하는데 도움을 준다. 5. 임상관찰과 치료기록, 원인균 검사성적자료와 연관시킨 SCS 자료는 가장 좋은 유방염 평가기록일 수 있다. 6. 목장에 근무하는 전직원이 유방염에 관한 자료의 이용에 있어 전문적 지식을 갖추고 있으면 초기에 유방염 문제에 개입할 수 있게 되어 비유기중에 항생제에 사용을 줄일 수 있다. 따라서 유질이 향상되고 농가의 수입증대를 도모할 수 있다.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.113-121
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• 2012

A total of 150,624 records of Holstein milk production collected from 2005 to 2009 were analyzed to investigate the effects of two different contemporary group definitions, parity and somatic cell score (SCS). The first definition (H BY S) of contemporary group was milking cows and heifers born in the same year and season. And the second thing (H CY S) was milking cow and heifers that delivered calves in the same year and season. Effects of contemporary group, parity and regression effect on SCS from two models were highly significant sources of variation. Coverage of variation ($R^2$) was somewhat higher in models with H BY S as contemporary group. From multivariate models with H BY S, phenotypic correlation coefficients of milk components were estimated high and positive. However, the phenotypic correlation coefficient between milk yield and SCS was -0.09, which was low enough to evidence no correlation between them. Phenotypic correlation between SCS and butter fat or between SCS and protein were also negligible but negative. From multivariate models with H CY S as contemporary group, phenotypic correlation among milk traits and SCS were similar to the estimates from models with H BY S. However, SCS in these models were lowly but negatively correlated with milk yield, milk protein, butter fat or SNF, and the phenotypic correlation coefficients of which were -0.10, -0.08, -0.08, -0.11, respectively.

• The Science & Technology
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• no.11 s.414
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• pp.6-7
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• 2003

암 · 뇌졸중, 세포로 치료한다/ 연구목적외 체세포 복제 금지/ 삼성전자, 70㎚ 4G 메모리 세계 첫 개발/ 100% 생분해성 일회용기 개발/ 원자까지 보는 전자현미경 본격 가동/ 한국, 정보통신분야 종합점수 세계 6위/ 정통부 중소 · 벤처기업 컨설팅 비용지원 대폭 향상/ 종근당 항암제 '캄토벨주'신약 허가

• Journal of The Korean Association For Science Education
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• v.31 no.5
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• pp.680-693
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• 2011

In conceptual ecology, a concept does not exist independently but occupies an ecological niche in ecological environment. Among many biological concepts, genetic concepts are connected to several units including the genetics unit, and within the genetics unit the concepts of sub-areas are highly dependent on one another. For this reason, we analyzed conceptual diversity and conceptual proximity of genetic concepts through the ecological niche approach. For this purpose, we surveyed 995 9th graders. The areas covered in the survey were four genetic concepts: gene, chromosome, mitosis, and meiosis. The questionnaire presented biological concepts or terms related to each area, and the respondent marked the relevance between the presented biological concepts or terms and each area on a scale of 1~30 points. With 9th grade students, we analyzed the change of genetic concepts through class by the ecological niche approach. Through class, the total number of concepts increased in all of the areas, and the increase was smallest in the area of meiosis followed by mitosis, chromosome and gene. Relative density decreased with increases in the number of concepts. The conceptual diversity index also increased through class in all of the areas, and the increase was smallest in the area of meiosis followed by mitosis, chromosome and gene. In addition, difference in the relative density of concepts was reduced after class, and difference in the score of relevance was also reduced and consequently similarity among concepts increased. From these results were drawn conclusions as follows: First, through class, the conceptual diversity of genetic concepts increased. Second, through class, the conceptual proximity of genetic concepts increased.