Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (2): 403-414.doi: 10.3864/j.issn.0578-1752.2022.02.014

• ANIMAL SCIENCE·VETERINARY SCIENCE·RESOURCE INSECT • Previous Articles     Next Articles

Impacts of Somatic Cell Count in Early Lactation on Production Performance over the Whole Lactation and Its Genetic Parameters in Holsteins Cattle

ZHU Lei1,2(),ZHANG HaiLiang1,CHEN ShaoKan1,3,AN Tao1,2,LUO HanPeng1,LIU Lin4,HUANG XiXia2,WANG YaChun1()   

  1. 1China Agricultural University College of Animal Science and Technology, Beijing 100193
    2Xinjiang Agricultural University College of Animal Science, Urumqi 830052
    3Beijing Sunlon Livestock Development Co., Ltd, Beijing 100029
    4Beijing Dairy Center, Beijing 100085
  • Received:2020-12-01 Accepted:2021-07-11 Online:2022-01-16 Published:2022-01-26
  • Contact: YaChun WANG E-mail:936510062@qq.com;wangyachun@cau.edu

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Abstract:

【Objective】 The objective of this study was to explore the relationship between somatic cell count in early lactation (6-35 d) (SCCel) and test-day somatic cell count (SCC), test-day milk yield in different lactation stages, and to estimate genetic parameters of SCSel in Holstein, so as to provide a new idea for the breeding of Holstein mastitis resistance. 【Method】Dairy herd improvement (DHI) records for 182 378 Holstein cows were collected from 141 dairy farms from 2008 to 2018. After quality control, a total of 1 869 976 date records were obtained for 150 864 cattle. The pedigree information of three generations were collected (father, mother, grandfather and grandmother from both father side and mother side) to form the pedigree file, comprising a total of 6 451 bulls and 103 452 cows. The GLM process of SAS software analyzed the factors affecting SCSel, such as measurement scale of pasture, measurement season, measurement year, number of lactation days and fetal secondary, etc, and the relationships between SCSel and test-day SCS and test-day milk yield in different lactation stages by REG procedure using SAS software. The genetic parameters for SCSel traits were estimated by single trait repetition model, single trait and two traits animal model using DMU software, and including heritability and genetic correlation. 【Result】The results showed that the SCC of Holstein changed significantly at 2 weeks postpartum. SCCel of Holstein showed a trend of gradual decline with the increase of lactation days. The farm scale, parity, test season and days in milk had significant impacts on SCCel (P<0.05), and the SCSel of cows with an average annual measurement size of more than 1 000 cows in early lactation was significant lower than the average annual measured size of less than 1 000 (P<0.05). SCSel was firstly decreased and then increased with the increase of parity. The SCSel was the highest in summer and the lowest in winter. There were highly significant regression relationships between SCSel and the test-day SCS in different lactation stages (P<0.01), with regression coefficients ranging from 0.06 to 0.19. There was a highly significant regression relationships between SCSel and the test-day milk yield in different lactation stages (P<0.01), and the regression coefficient ranged from -0.46 to -0.16, and early lactation SCSel could affect breast health and performance during lactation. The heritability of SCSel in 1st, 2nd, 3rd parity and over all parity was 0.05 ± 0.005, 0.07 ± 0.01, 0.04 ± 0.01, and 0.03 ± 0.01, respectively. There were moderate to high genetic correlations among SCSel traits under different parity in Holstein, ranging from 0.54 to 0.87. 【Conclusion】The SCC of Holstein cows in early lactation (6-35 days) was affected by the number of conception and season, and the SCC of early lactation had the population characteristics different from those of the SCC of the measurement date of lactation. A high level of SCCel would have impact on the health and production performance over the whole lactation in Holstein cow. This study provided a theoretical basis for differentiated management by SCCel in postpartum cow pasture, laid a foundation for exploring the genetic mechanism of somatic cell number difference in early lactation of Holstein, and the development of new SCS traits in early lactation was helpful to improve mastitis resistance selection of Holstein in China.

Key words: Holstein, early lactation, somatic cell count, milk production, genetic parameter

Fig. 1

The change trends of somatic cell count during early lactation under different parities in Holstein"

Table 1

The impacts of different herd test scale, parity, test season on the somatic cell score during early lactation in Holstein"

效应 Effect 水平 Level 数据量N 最小二乘均值 ± 标准误 LSM ± SE
年牧场测定规模（头）
Herd yearly test scale (cow)		 200—500 62 809 2.87 ± 0.01a
501—1000 74 450 2.89 ± 0.01a
≥1001 36 787 2.61 ± 0.01b
胎次
Parity		 1胎Parity1 83 363 2.87 ± 0.01a
2胎Parity2 29 832 2.65 ± 0.01b
3胎 Parity3 60 851 2.85 ± 0.01a
测定季节
Test season		 春季 Spring 43 587 2.73 ± 0.01b
夏季 Summer 45 278 3.10 ± 0.01a
秋季 Autumn 39 966 2.70 ± 0.01b
冬季 Winter 45 215 2.64 ± 0.01c

Fig. 2

The difference of somatic cell count during the whole lactation period among the cows with different performance on somatic cell count in early lacatation The performance level of SCCel (103/mL) included: level 1, ≤50×103/mL; level 2, 50-200 103/mL; level 3, 200 - 500×103/mL; level 4, 500-1 000×103/mL; level 5, ≥1 000×103/mL"

Fig. 3

The difference of daily milk yield during the whole lactation period among the cows with different performance on somatic cell count in early lacation The performance level of SCCel (103/mL) included: level 1, ≤ 50×103/mL; level 2, 50 - 200 103/mL; level 3, 200 - 500×103/mL; level 4, 500 - 1 000×103/mL ; level 5, ≥1 000×103/mL"

Table 2

Multiple linear regression of somatic cell score in early lactation on test-day somatic cell score in different lactation stages"

变量 Variables 36—65 d 66—95 d 96—125 d
数据量 N 139 018 140 059 138 406
参数估计值Parameter P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 2.31 ± 0.02 <0.01 2.31 ± 0.02 <0.01 2.37 ± 0.02 <0.01
SCSel 0.19 ± 0.00 <0.01 0.16 ± 0.00 <0.01 0.13 ± 0.00 <0.01
DIMel 0.003 ± 0.00 <0.01 0.003 ± 0.00 <0.01 0.003 ± 0.00 <0.01
1胎Parity1 Ref Ref Ref
2胎Parity2 0.16 ± 0.01 <0.01 0.17 ± 0.01 <0.01 0.22 ± 0.01 <0.01
3胎 Parity3 0.31 ± 0.01 <0.01 0.34 ± 0.01 <0.01 0.38 ± 0.01 <0.01
变量 Variables 126—155 d 156—185 d 186—215 d
数据量 N 133 851 128 790 126 002
参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 2.47 ± 0.02 <0.01 2.54 ± 0.02 <0.01 2.65 ± 0.02 <0.01
SCSel 0.11 ± 0.00 <0.01 0.10 ± 0.00 <0.01 0.10 ± 0.00 <0.01
DIMel 0.003 ± 0.000 <0.01 0.002 ± 0.000 <0.01 0.003 ± 0.000 <0.01
1胎Parity1 Ref Ref Ref
2胎Parity2 0.19 ± 0.01 <0.01 0.23 ± 0.01 <0.01 0.31 ± 0.01 <0.01
3胎 Parity3 0.43 ± 0.01 <0.01 0.44 ± 0.01 <0.01 0.51 ± 0.01 <0.01
变量 Variables 216—245 d 246—275 d 275—305 d
数据量 N 122 628 114 772 90 192
参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 2.66 ± 0.02 <0.01 2.75 ± 0.02 <0.01 2.90 ± 0.02 <0.01
SCSel 0.08 ± 0.00 <0.01 0.07 ± 0.00 <0.01 0.06 ± 0.02 <0.01
DIMel 0.002 ± 0.000 <0.01 0.002 ± 0.000 <0.01 0.001 ± 0.000 <0.01
1胎Parity1 Ref Ref Ref
2胎Parity2 0.33 ± 0.00 <0.01 0.40 ± 0.01 <0.01 0.44 ± 0.01 <0.01
3胎 Parity3 0.56 ± 0.01 <0.01 0.61 ± 0.01 <0.01 0.66 ± 0.01 <0.01

Table 3

Multiple linear regression of somatic cell score in early lactation on test-day milk yield"

变量 Variables 36—65 d 66—95 d 96—125 d
数据量 N 139 018 140 059 138 406
参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 34.59 ± 0.10 <0.01 36.28 ± 0.09 <0.01 35.97 ± 0.09 <0.01
SCSel -0.46 ± 0.02 <0.01 -0.41 ± 0.02 <0.01 -0.31 ± 0.02 <0.01
DIMel 0.02 ± 0.00 <0.01 -0.03 ± 0.00 <0.01 -0.03 ± 0.00 <0.01
1胎Parity1 Ref Ref Ref
2胎Parity2 8.21 ± 0.05 <0.01 6.87 ± 0.05 <0.01 5.25 ± 0.05 <0.01
3胎 Parity3 7.88 ± 0.07 <0.01 6.52 ± 0.07 <0.01 5.15 ± 0.06 <0.01
变量 Variables 126—155 d 156—185 d 186—215 d
数据量 N 133 851 128 790 126 002
参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 35.52 ± 0.09 <0.01 34.66 ± 0.09 <0.01 33.69 ± 0.09 <0.01
SCSel -0.31 ± 0.02 <0.01 -0.27 ± 0.02 <0.01 -0.25 ± 0.02 <0.01
DIMel -0.04 ± 0.00 <0.01 -0.03 ± 0.00 <0.01 -0.03 ± 0.00 <0.01
1胎 Parity1 Ref Ref Ref
2胎 Parity2 3.81 ± 0.05 <0.01 2.10 ± 0.05 <0.01 0.66 ± 0.05 <0.01
3胎 Parity3 3.72 ± 0.06 <0.01 1.90 ± 0.06 <0.01 0.30 ± 0.06 <0.01
变量 Variables 216—245 d 246—275 d 275—305 d
数据量 N 122 628 114 772 90 192
参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value		 参数估计值
Parameter		 P值
P value
Intercept 32.72 ± 0.09 <0.01 31.42 ± 0.09 <0.01 30.07 ± 0.10 <0.01
SCSel -0.21 ± 0.02 <0.01 -0.16 ± 0.02 <0.01 -0.16 ± 0.02 <0.01
DIMel -0.03 ± 0.00 <0.01 -0.03 ± 0.00 <0.01 -0.02 ± 0.00 <0.01
1胎Parity1 Ref Ref Ref
2胎Parity2 -0.88 ± 0.05 <0.01 -2.06 ± 0.05 <0.01 -2.77 ± 0.06 <0.01
3胎 Parity3 -1.25 ± 0.07 <0.01 -2.63 ± 0.07 <0.01 -2.57 ± 0.08 <0.01

Table 4

Estimates of variance components and genetic parameters for somatic cell score during early lactation in Holstein"

性状
Traits		 加性遗传方差
Additive variance		 永久环境方差
Permanent environment variance		 残差方差
Residual variance		 遗传力
Heritability		 遗传力标准误
Standard error
SCSel 0.12 0.79 1.45 0.05 0.005
SCSel (1胎Parity1) 0.15 - 2.01 0.07 0.01
SCSel (2胎Parity2) 0.09 - 2.33 0.04 0.01
SCSel (3胎 Parity3) 0.06 - 2.31 0.03 0.01

Table 5

Phenotypic correlations and genetic correlations among somatic cell score during early lactation under different parities in Holstein"

性状
Trait		 SCSel (1胎
Parity 1)		 SCSel (2胎
Parity 2)		 SCSel (3胎
Parity 3)
SCSel (1胎Parity1) 0.07 0.04
SCSel (2胎Parity2) 0.70 ± 0.10 0.10
SCSel (3胎 Parity3) 0.54 ± 0.19 0.87 ± 0.17
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