动物营养学报 >

2020 , Vol. 32 >Issue 7: 3199 - 3213

DOI: https://doi.org/10.3969/j.issn.1006-267x.2020.07.030

反刍与草食动物营养与饲料 RUMINANT AND HERBIVORE NUTRITION AND FEED

北京地区不同泌乳水平中国荷斯坦奶牛乳成分模型建立及相关性分析

  • 吴富鑫 ,
  • 童津津 ,
  • 张华 ,
  • 毛胜勇 ,
  • 熊本海 ,
  • 麻柱 ,
  • 蒋林树
展开
  • 1. 北京农学院动物科学技术学院, 奶牛营养学北京市重点实验室, 北京 102206;
    2. 南京农业大学动物科技学院, 南京 210095;
    3. 中国农业科学院北京畜牧兽医研究所, 北京 100193;
    4. 北京奶牛中心首农集团, 北京 100085
吴富鑫(1995-),男,山东济宁人,硕士研究生,研究方向为奶牛营养与免疫。E-mail:2996440432@qq.com

收稿日期: 2020-01-09

  网络出版日期: 2020-07-15

基金资助

"十三五"国家重大科技专项（2016YFD0700201，2016YFD0700205，2017YFD0701604）；北京市现代农业产业技术体系奶牛创新团队；国家自然科学基金（31802091，31702302，31772629）

收起

Establishment and Correlation Analysis of Milk Composition Model of Chinese Holstein Cows with Different Lactation Levels in Beijing Area

  • WU Fuxin ,
  • TONG Jinjin ,
  • ZHANG Hua ,
  • MAO Shengyong ,
  • XIONG Benhai ,
  • MA Zhu ,
  • JIANG Linshu
Expand
  • 1. Beijing Key Laboratory of Dairy Cattle Nutrition, Institute of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China;
    2. Institute of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China;
    3. Beijing Institute of Animal Husbandry and Veterinary Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China;
    4. Beijing Cow Center Shounong Group, Beijing 100085, China

Received date: 2020-01-09

  Online published: 2020-07-15

Fold

摘要

为探索北京地区不同泌乳水平中国荷斯坦奶牛泌乳量和乳成分特征，本研究应用曲线回归分析方法构建泌乳量及乳成分变化规律模型。以2016-2019年北京地区中国荷斯坦奶牛的阿菲金在线乳成分分析仪记录的数据为基础，构建泌乳量和乳成分随泌乳天数变化的模型，分析不同泌乳水平中国荷斯坦奶牛的乳成分-泌乳天数曲线的差异性以及泌乳量和电导率与各乳成分之间的相关关系。结果表明：不同泌乳水平的中国荷斯坦奶牛在乳成分和泌乳量上均存在极显著差异（P<0.01）。对各曲线模型进行对比分析发现，三次方模型能较好地拟合北京地区不同泌乳水平中国荷斯坦奶牛各乳成分-泌乳天数曲线。不同泌乳阶段的高、低产奶牛的乳糖率、乳脂率、乳蛋白率和脂蛋比与泌乳量及电导率均具有显著或极显著相关性（P<0.05或P<0.01）。由此可知，泌乳量和电导率是引起乳成分改变的重要因素，因此，对不同泌乳水平的奶牛分别拟合分析具有一定的实践指导意义。

关键词： 奶牛; 泌乳量; 乳成分; 曲线回归分析

本文引用格式

吴富鑫 , 童津津 , 张华 , 毛胜勇 , 熊本海 , 麻柱 , 蒋林树 . 北京地区不同泌乳水平中国荷斯坦奶牛乳成分模型建立及相关性分析[J]. 动物营养学报, 2020 , 32(7) : 3199 -3213 . DOI: 10.3969/j.issn.1006-267x.2020.07.030

Abstract

In order to explore the characteristics of lactation yield and milk composition of Chinese Holstein dairy cows with different lactation levels in Beijing area, this study applied a curve regression analysis method to build models of lactation yield and milk composition changes. Based on the data recorded by Affitin's online milk composition analyzer for Chinese Holstein cows in Beijing area from 2016 to 2019, the models of changes in lactation yield and milk composition with lactation days were built, and the difference in milk composition-lactation time curve and the correlation between lactation yield and electrical conductivity and each milk composition of Chinese Holstein cows with different levels of lactation were analyzed. The results showed that Chinese Holstein cows with different lactation levels had extremely significant differences in milk composition and lactation yield (P<0.01). A comparative analysis of each curve model showed that the cubic model could well fit the milk composition-lactation days curves of Chinese Holstein cows with different lactation levels in Beijing area. The lactose rate, milk fat rate, milk protein rate and lipoprotein ratio of high and low-yielding cows at different lactation stages had significant or extremely significant correlations with lactation yield and electrical conductivity (P<0.05 or P<0.01). It can be seen that lactation yield and electrical conductivity are important factors that cause changes in milk composition. Therefore, it is of practical significance to fit and analyze dairy cows with different lactation levels.

Key words： dairy cows; lactation yield; milk composition; curvilinear regression analysis

参考文献

[1] ZEMPLENI J,AGUILAR-LOZANO A,SADRI M,et al.Biological activities of extracellular vesicles and their cargos from bovine and human milk in humans and implications for infants[J].The Journal of Nutrition,2016,147(1):3-10.
[2] 国务院办公厅.国务院办公厅关于推进奶业振兴保障乳品质量安全的意见[EB/OL].(2018-06-11).http://www.gov.cn/zhengce/content/2018-06/11/content_5297839.htm.
[3] KATZ G,MERIN U,BEZMAN D,et al.Real-time evaluation of individual cow milk for higher cheese-milk quality with increased cheese yield[J].Journal of Dairy Science,2016,99(6):4178-4187.  
[4] MACRAE A.Assessment of energy balance in dairy cattle[J].Livestock,2019,24(5):229-235.  
[5] CHESTER-JONES H,HEINS B J,ZIEGLER D,et al.Relationships between early-life growth,intake,and birth season with first-lactation performance of Holstein dairy cows[J].Journal of Dairy Science,2017,100(5):3697-3704.  
[6] WELLER J I,EZRA E.Genetic and phenotypic analysis of daily Israeli Holstein milk,fat,and protein production as determined by a real-time milk analyzer[J].Journal of Dairy Science,99(12):9782-9795.
[7] MEIR Y A B,NIKBACHAT M,FORTNIK Y,et al.Eating behavior,milk production,rumination,and digestibility characteristics of high-and low-efficiency lactating cows fed a low-roughage diet[J].Journal of Dairy Science,2018,101(12):10973-10984.  
[8] 吴富鑫,童津津,张华,等.不同泌乳量奶牛行为学差异及其与泌乳性能的相关性[J].动物营养学报,2019,31(7):3156-3163.
[9] TONG J J,ZHANG H,YANG D L,et al.Illumina sequencing analysis of the ruminal microbiota in high-yield and low-yield lactating dairy cows[J].PLoS One,2018,13(11):e198225.
[10] ZHANG H,TONG J J,ZHANG Y H,et al.Metabolomics reveals potential biomarkers in the rumen fluid of dairy cows with different levels of milk productionJ].Asian-Australasian Journal of Animal Sciences,2019,33(1):79-90.
[11] 李欣,温万,脱征军,等宁夏地区荷斯坦奶牛产奶量以及乳成分变化模型的构建与分析[J]. 中国畜牧杂志(11):40-46.
[12] DÓREA J R R,FRENCH E A,ARMENTANO L E.Use of milk fatty acids to estimate plasma nonesterified fatty acid concentrations as an indicator of animal energy balance[J].Journal of Dairy Science,2017,100(8):6164-6176.  
[13] BERRY D P,FRIGGENS N C,LUCY M,et al.Milk production and fertility in cattle[J].Annual Review of Animal Biosciences,2016,4(1):269-290.  
[14] HERVE L,QUESNEL H,VERON M,et al.Milk yield loss in response to feed restriction is associated with mammary epithelial cell exfoliation in dairy cows[J].Journal of Dairy Science,2019,102(3):2670-2685.  
[15] KHATUN M,BRUCKMAIER R M,THOMSON P C,et al.Suitability of somatic cell count,electrical conductivity,and lactate dehydrogenase activity in foremilk before versus after alveolar milk ejection for mastitis detection[J].Journal of Dairy Science,2019,102(10):9200-9212.  
[16] STEENEVELD W,VERNOOIJ J C M,HOGEVEEN H.Effect of sensor systems for cow management on milk production,somatic cell count,and reproduction[J].Journal of Dairy Science,2015,98(6):3896-3905.  
[17] ADDIS M F,BRONZO V,PUGGIONI G M G,et al.Relationship between milk cathelicidin abundance and microbiologic culture in clinical mastitis[J].Journal of Dairy Science,2017,100(4):2944-2953.  
[18] 冯军科,周焕梅,刘闯,等.电导率监控奶牛隐性乳房炎阈值的确定及分析[J].中国奶牛,2010(7):47-48.
[19] ROCA A,ROMERO G,ALEJANDRO M,et al.Milk electrical conductivity in Manchega ewes:Variation throughout milking and relation with mammary gland health status[J].Czech Journal of Animal Science,2019,64(7):300-308.  
[20] ZHANG F,MURPHY M D,SHALLOO L,et al.An automatic model configuration and optimization system for milk production forecasting[J].Computers and Electronics in Agriculture,2016,128:100-111.
[21] 熊本海,杨亮,杨琴,等.中国北方荷斯坦奶牛乳产量及乳成分变化的普适模型构建[J].畜牧兽医学报,2014,45(12):1939-1948.
[22] 熊本海,马毅,庞之洪,等.天津市中国荷斯坦奶牛乳成分变化规律及模型[J].中国农业科学,2012,45(23):4891-4897.
[23] BEN MEIR Y,NIKBACHAT M,JACOBY S,et al.Effect of lactation trimester and parity on eating behavior,milk production and efficiency traits of dairy cows[J].Animal,2019,13(8):1736-1743.  
[24] VAN KNEGSEL A,VAN DEN BRAND H,DIJKSTRA J,et al.Dietary energy source in dairy cows in early lactation:energy partitioning and milk composition[J].Journal of Dairy Science,2007,90(3):1467-1476.  
[25] BEN MEIR Y,NIKBACHAT M,PORTNIK Y,et al.Dietary restriction improved feed efficiency of inefficient lactating cows[J].Journal of Dairy Science,2019,102(10):8898-8906.  
[26] PETROVSKA S,JONKUS D.Body condition score influence on milk yield productivity in lactation[C]//Zina tniski praktiska konference li dzsvarota lauksaimnieci ba,jelgava,latvia 19-20 februa ri 2015.Latvijas Lauksaimnieci bas Universita te,2015:177-181.
[27] 孙宇,牛连信,张彦林,等.奶牛乳体细胞数的变化规律及其与乳成分的关系[J].畜牧与饲料科学,2009,30(6):133-134.
[28] 赵萌.中国荷斯坦牛不同泌乳阶段乳腺基因差异表达研究[D].硕士学位论文.泰安:山东农业大学,2017.
Options
文章导航

/

〈 〉

    联系我们

  • 地址：北京市海淀区圆明园西路2号
    　　　中国农业大学动科动医大楼153室
  • 邮编：100193
  • 电话：010－62817823
  • 网址：http://www.chinajan.com
  • E-mail：cjan@chinajan.com
京公网安备 11010802041926号    京ICP备17050989号-2