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Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

机译:简短交流:利用仅从呼吸室获得的参考数据,开发估算牛奶傅里叶变换中红外光谱的奶牛甲烷排放的方程式

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摘要

Evaluation and mitigation of enteric methane (CH4) emissions from ruminant livestock, in particular from dairy cows, have acquired global importance for sustainable, climate-smart cattle production. Based on CH4 reference measurements obtained with the SF6 tracer technique to determine ruminal CH4 production, a current equation permits evaluation of individual daily CH4 emissions of dairy cows based on milk Fourier transform mid-infrared (FT-MIR) spectra. However, the respiration chamber (RC) technique is considered to be more accurate than SF6 to measure CH4 production from cattle. This study aimed to develop an equation that allows estimating CH4 emissions of lactating cows recorded in an RC from corresponding milk FT-MIR spectra and to challenge its robustness and relevance through validation processes and its application on a milk spectral database. This would permit confirming the conclusions drawn with the existing equation based on SF6 reference measurements regarding the potential to estimate daily CH4 emissions of dairy cows from milk FT-MIR spectra. A total of 584 RC reference CH4 measurements (mean +/- standard deviation of 400 +/- 72 g of CH4/d) and corresponding standardized milk mid-infrared spectra were obtained from 148 individual lactating cows between 7 and 321 d in milk in 5 European countries (Germany, Switzerland, Denmark, France, and Northern Ireland). The developed equation based on RC measurements showed calibration and cross-validation coefficients of determination of 0.65 and 0.57, respectively, which is lower than those obtained earlier by the equation based on 532 SF6 measurements (0.74 and 0.70, respectively). This means that the RC-based model is unable to explain the variability observed in the corresponding reference data as well as the SF6-based model. The standard errors of calibration and cross-validation were lower for the RC model (43 and 47 g/d vs. 66 and 70 g/d for the SF6 version, respectively), indicating that the model based on RC data was closer to actual values. The root mean squared error (RMSE) of calibration of 42 g/d represents only 10% of the overall daily CH4 production, which is 23 g/d lower than the RMSE for the SF6 based equation. During the external validation step an RMSE of 62 g/d was observed. When the RC equation was applied to a standardized spectral database of milk recordings collected in the Walloon region of Belgium between January 2012 and December 2017 (1,515,137 spectra from 132,658 lactating cows in 1,176 different herds), an average +/- standard deviation of 446 +/- 51 g of CH4/d was estimated, which is consistent with the range of the values measured using both RC and SF6 techniques. This study confirmed that milk FT-MIR spectra could be used as a potential proxy to estimate daily CH4 emissions from dairy cows provided that the variability to predict is covered by the model.
机译:反刍动物,特别是奶牛反刍动物的肠甲烷(CH4)排放的评估和缓解,对于可持续的,气候智能的牛生产具有全球重要性。基于使用SF6示踪技术获得的CH4参考测量值来确定瘤胃CH4的产生,当前方程式允许基于牛奶傅里叶变换中红外(FT-MIR)光谱评估奶牛的每日CH4排放量。但是,呼吸室(RC)技术被认为比SF6更准确,可以测量牛的CH4产量。这项研究旨在建立一个方程,该方程可以根据相应的牛奶FT-MIR光谱估算RC中记录的泌乳牛的CH4排放,并通过验证过程及其在牛奶光谱数据库中的应用来挑战其稳健性和相关性。这将允许根据基于SF6参考测量的现有方程式得出的结论得到确认,该结论涉及从牛奶FT-MIR光谱估计奶牛每日CH4排放的潜力。总共584 RC参考CH4测量(平均+/-标准偏差400 +/- 72 g CH4 / d)和相应的标准化牛奶中红外光谱是从148头7至321 d之间的泌乳奶牛获得的。 5个欧洲国家(德国,瑞士,丹麦,法国和北爱尔兰)。基于RC测量的已开发方程显示的校准系数和交叉验证系数分别为0.65和0.57,这比基于532 SF6测量的方程(分别为0.74和0.70)所获得的校准系数和交叉验证系数要低。这意味着基于RC的模型无法解释在相应参考数据以及基于SF6的模型中观察到的变异性。 RC模型的校准和交叉验证的标准误差较低(分别为43和47 g / d,而SF6版本分别为66和70 g / d),这表明基于RC数据的模型更接近实际价值观。校准的均方根误差(RMSE)为42 g / d,仅代表每日总CH4产量的10%,比基于SF6方程的RMSE低23 g / d。在外部验证步骤中,观察到的RMSE为62 g / d。将RC方程应用于2012年1月至2017年12月在比利时瓦隆地区收集的牛奶记录的标准化光谱数据库时(来自1,176个不同牛群的132,658头泌乳牛的1,515,137光谱),平均+/-标准差为446 +估计了51 g CH4 / d,这与使用RC和SF6技术测得的值范围一致。这项研究证实,只要该模型涵盖了预测的可变性,牛奶FT-MIR光谱就可以用作估算奶牛每日CH4排放的潜在指标。

著录项

  • 来源
    《Journal of dairy science》 |2018年第8期|7618-7624|共7页
  • 作者单位

    Walloon Agr Res Ctr, Valorizat Agr Prod, B-5030 Gembloux, Belgium;

    Univ Liege, Gembloux Agrobio Tech, Agrobiochem Dept, B-5030 Gembloux, Belgium;

    Univ Liege, Gembloux Agrobio Tech, Agrobiochem Dept, B-5030 Gembloux, Belgium;

    Univ Liege, Gembloux Agrobio Tech, Agrobiochem Dept, B-5030 Gembloux, Belgium;

    Walloon Agr Res Ctr, Prod & Sect Dept, B-5030 Gembloux, Belgium;

    Swiss Fed Inst Technol, Inst Agr Sci, CH-8092 Zurich, Switzerland;

    Qualitas AG, CH-6300 Zug, Switzerland;

    Agrifood & Biosci Inst, Large Pk, Hillsborough BT26 6DR, North Ireland;

    Aarhus Univ, AU Foulum, Dept Anim Sci, DK-8830 Tjele, Denmark;

    Aarhus Univ, AU Foulum, Dept Anim Sci, DK-8830 Tjele, Denmark;

    Univ Clermont Auvergne, VetAgro Sup, INRA, UMR Herbivores, F-63122 St Genes Champanelle, France;

    Univ Clermont Auvergne, VetAgro Sup, INRA, UMR Herbivores, F-63122 St Genes Champanelle, France;

    Leibniz Inst Farm Anim Biol FBN, Inst Nutr Physiol, D-18196 Dummerstorf, Germany;

    Walloon Agr Res Ctr, Valorizat Agr Prod, B-5030 Gembloux, Belgium;

  • 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

    cattle; greenhouse gas; spectroscopy; proxy;

    机译:牛;温室气体;光谱学;代理;
  • 入库时间 2022-08-18 04:03:00

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