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Variation in nutrients formulated and nutrients supplied on 5 California dairies

机译:加利福尼亚5家奶牛场中配制的养分和提供的养分的变化

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摘要

Computer models used in ration formulation assume that nutrients supplied by a ration formulation are the same as the nutrients presented in front of the cow in the final ration. Deviations in nutrients due to feed management effects such as dry matter changes (i.e., rain), loading, mixing, and delivery errors are assumed to not affect delivery of nutrients to the cow and her resulting milk production. To estimate how feed management affects nutrients supplied to the cow and milk production, and determine if nutrients can serve as indexes of feed management practices, weekly total mixed ration samples were collected and analyzed for 4 pens (close-up cows, fresh cows, high-milk-producing, and low-milk-producing cows, if available) for 7 to 12 wk on 5 commercial California dairies. Differences among nutrient analyses from these samples and nutrients from the formulated rations were analyzed by PROC MIXED of SAS (SAS Institute Inc., Cary, NC). Milk fat and milk protein percentages did not vary as much [coefficient of variation (CV) = 18 to 33%] as milk yield (kg; CV = 16 to 47 %) across all dairies and pens. Variability in nutrients delivered were highest for macronutrient fat (CV = 22%), lignin (CV = 15%), and ash (CV = 11%) percentages and micronutrients Fe (mg/kg; CV = 48%), Na (%; CV = 42%), and Zn (mg/kg; CV = 38%) for the milking pens across all dairies. Partitioning of the variability in random effects of nutrients delivered and intraclass correlation coefficients showed that variability in lignin percentage of TMR had the highest correlation with variability in milk yield and milk fat percentage, followed by fat and crude protein percentages. But, variability in ash, fat, and lignin percentages of total mixed ration had the highest correlation with variability in milk protein percentage. Therefore, lignin, fat, and ash may be the best indices of feed management to include effects of variability in nutrients on variability in milk yield, milk fat, and milk protein percentages in ration formulation models.
机译:日粮配方中使用的计算机模型假定,日粮配方提供的养分与最终日粮中出现在母牛前面的养分相同。假定由于饲料管理效应(例如干物质变化(即下雨),装载,混合和输送错误)而造成的养分偏差不会影响到牛的养分输送以及由此产生的产奶量。为了估计饲料管理如何影响供应给奶牛和奶牛生产的养分,并确定养分是否可以用作饲料管理实践的指标,每周收集总混合定量样品并分析4支钢笔(特写奶牛,新鲜奶牛,高奶牛)。 -产奶和产奶量低的奶牛,如果有的话)在加利福尼亚州的5家商业奶牛场上每周7至12周。通过SAS的PROC MIXED(北卡罗来纳州卡里的SAS Institute Inc.)分析了这些样品中营养成分分析与配给口粮中营养成分之间的差异。在所有奶牛场和围栏中,乳脂和乳蛋白百分比的变化[变异系数(CV)= 18至33%]与产奶量(kg; CV = 16至47%)的变化不大。常量养分脂肪(CV = 22%),木质素(CV = 15%)和灰分(CV = 11%)百分比和微量养分Fe(mg / kg; CV = 48%),Na(%)的养分输送最高;所有奶牛场的挤奶笔的CV = 42%)和Zn(mg / kg; CV = 38%)。分配的养分随机效应的变异性和组内相关系数的变化表明,TMR木质素百分比的变异性与牛奶产量和乳脂百分比的变异性相关性最高,其次是脂肪和粗蛋白百分比。但是,总混合日粮中灰分,脂肪和木质素百分比的变化与牛奶蛋白百分比的变化具有最高的相关性。因此,木质素,脂肪和灰分可能是饲料管理的最佳指标,包括日粮配方模型中营养成分变化对牛奶产量,牛奶脂肪和牛奶蛋白质百分比变化的影响。

著录项

  • 来源
    《Journal of dairy science》 |2013年第11期|7371-7381a7|共12页
  • 作者

    H. A. Rossow; S. S. Aly;

  • 作者单位

    Veterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, 18830 Road 112, Tulare 93274,Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, CA 95616;

    Veterinary Medicine Teaching and Research Center, School of Veterinary Medicine, University of California, Davis, 18830 Road 112, Tulare 93274,Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, CA 95616;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    nutrient variability; ration formulation variability; milk production variability;

    机译:营养素变异性定量配方的可变性;牛奶产量差异;
  • 入库时间 2022-08-17 23:24:19

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