4个瑞士奶牛品种的乳尿素氮含量与尿氮排泄的关系。

IF 3.7 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
A. Burren , M. Terranova , M. Kreuzer , T. Kupper , S. Probst
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引用次数: 0

摘要

来自农业的氨(NH3)增加了环境氮负荷,并通过诱导土壤富营养化和酸化威胁敏感生态系统。为了战略性地减少NH3的排放,本研究旨在建立一个模型来预测尿氮(UN)排泄(g/d),这是不同奶牛品种的主要NH3来源,基于一个易于确定的代理作为农场工具。为此,没有考虑饮食特征。其中一个代表就是MUN的含量,可以从奶牛场的罐奶样本中确定。因此,我们调查了在瑞士进行的21种不同喂养实验的UN和MUN值,其中包括4种不同的奶牛品种。其中162头棕色瑞士奶牛(BS)、348头荷斯坦奶牛(HO)、44头泽西奶牛(JE)和50头瑞士弗列克维奶牛(SF)。我们使用各种线性混合模型研究了UN和MUN系数之间的关系。正演模型选择表明,在建模UN时,必须考虑MUN和品种之间的相互作用,以及体重和品种之间的相互作用。此外,UN和MUN之间存在明显的异方差,较高的MUN值(bb0 - 14mg /dL)。必须通过显式建模或对数转换来解释这种异方差。最终模型包括固定效应、模量、体重和品种、交互作用、模量×品种和体重×品种,以及实验作为随机效应。该模型还考虑了异方差。在最终模型中,R2很高,为81.2%。回归系数和最高后验密度区间分别为7.28 (5.42;9.02), 10.41 (9.16;11.65), 9.00 (6.20;11.94)和11.79 (9.15;BS、HO、JE和SF的UN每mg/dL分别增加14.25 g/d。体重和最高后验密度区间的估计回归系数为0.09 (-0.01;0.19), 0.17 (0.11;0.27), 0.51 (0.21;0.80)和0.28 (0.03;BS、HO、JE和SF分别为0.53)。估计UN (g/d)的边际均值±SE分别为117±12、147±12、119±14和135±14。这些结果证实,正如以前的研究所表明的那样,MUN含量是预测泌乳奶牛UN排泄的有用工具。然而,与以往的研究结果相比,我们的研究结果强调了在预测模型中考虑品种和体重的必要性。所建立的模型提高了质量流模型的准确性,该模型基于粪便管理链开始时牲畜的联合国排泄物来估计NH3排放量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The relationship between milk urea nitrogen content and urinary nitrogen excretion as determined in 4 Swiss dairy breeds
Ammonia (NH3) originating from agriculture substantially contributes to the environmental nitrogen load and threatens sensitive ecosystems by inducing eutrophication and acidification of the soil. To strategically minimize NH3 emissions, this study aimed to develop a model to predict urinary nitrogen (UN) excretion (g/d), the major NH3 source of cows of different dairy breeds, based on an easy-to-determine proxy as an on-farm tool. For that purpose, dietary characteristics were not considered. One such proxy would be the MUN content, which could be determined in tank milk samples from dairy farms. We therefore investigated the UN and MUN values from 21 different feeding experiments performed in Switzerland with 4 contrasting dairy breeds. These were 162 Brown Swiss (BS), 348 Holstein (HO), 44 Jersey (JE), and 50 Swiss Fleckvieh (SF) cows. We investigated the relationship between the coefficients of the UN and MUN using various linear mixed models. The forward model selection demonstrated that it is essential to consider the interaction between MUN and breed, as well as BW and breed, when modeling UN. Furthermore, there was a pronounced heteroscedasticity between UN and MUN for higher MUN values (>14 mg/dL). This heteroscedasticity must be accounted for, either through explicit modeling or log transformation. The final model included fixed effects, MUN, BW, and breed, the interactions, MUN × breed and BW × breed, as well as the experiment as random effect. This model also considered the heteroscedasticity. In the final model, R2 was high, at 81.2%. The regression coefficients and highest posterior density intervals were 7.28 (5.42; 9.02), 10.41 (9.16; 11.65), 9.00 (6.20; 11.94) and 11.79 (9.15; 14.25) g/d of increase in UN per mg/dL of MUN for BS, HO, JE, and SF, respectively. The estimated regression coefficients for BW and highest posterior density intervals were 0.09 (−0.01; 0.19), 0.17 (0.11; 0.27), 0.51 (0.21; 0.80) and 0.28 (0.03; 0.53) for BS, HO, JE, and SF, respectively. The estimated marginal means ± SE for UN (g/d) were 117 ± 12, 147 ± 12, 119 ± 14, and 135 ± 14 for BS, HO, JE, and SF, respectively. These results confirm MUN content to be a useful tool to predict UN excretion in lactating dairy cows, as suggested by previous studies. However, in contrast to previous findings, our results underscore the necessity of accounting for breed and BW in the predictive model. The established model improves the accuracy of mass flow models that estimate NH3 emissions based on the UN excretion of livestock at the beginning of the manure management chain.
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来源期刊
Journal of Dairy Science
Journal of Dairy Science 农林科学-奶制品与动物科学
CiteScore
7.90
自引率
17.10%
发文量
784
审稿时长
4.2 months
期刊介绍: The official journal of the American Dairy Science Association®, Journal of Dairy Science® (JDS) is the leading peer-reviewed general dairy research journal in the world. JDS readers represent education, industry, and government agencies in more than 70 countries with interests in biochemistry, breeding, economics, engineering, environment, food science, genetics, microbiology, nutrition, pathology, physiology, processing, public health, quality assurance, and sanitation.
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