Persistence of differences between dairy cows categorized as low or high methane emitters, as estimated from milk mid-infrared spectra and measured by GreenFeed


  • Denninger, T. . , Dohme-Meier, F. , Eggerschwiler, L. , Vanlierde, A. , Grandl, F. , Gredler, B. , Kreuzer, M. , Schwarm, A. & Münger, A. (2019). Persistence of differences between dairy cows categorized as low or high methane emitters, as estimated from milk mid-infrared spectra and measured by GreenFeed. Journal of Dairy Science, 102: (12), 11751-11765.
Type Journal Article
Year 2019
Title Persistence of differences between dairy cows categorized as low or high methane emitters, as estimated from milk mid-infrared spectra and measured by GreenFeed
Journal Journal of Dairy Science
Volume 102
Issue 12
Pages 11751-11765
Date Decembre 2019
Endnote keywords methane emission, among-animal differences, eating behavior, mid-infrared
Abstract Currently, various attempts are being made to implement breeding schemes aimed at producing low methane (CH4) emitting cows. We investigated the persistence of differences in CH4 emission between groups of cows categorized as either low or high emitters over a 5-mo period. Two feeding regimens (pasture vs. indoors) were used. Early- to mid-lactation Holstein Friesian cows were categorized as low or high emitters (n = 10 each) retrospectively, using predictions from milk mid-infrared (MIR) spectra, before the start of the experiment. Data from MIR estimates and from measurements with the GreenFeed (GF; C-Lock Technology Inc., Rapid City, SD) system over the 5-mo experiment were combined into 7-, 14-, and 28-d periods. Feed intake, eating and ruminating behavior, and ruminal fluid traits were determined in two 7-d measurement periods in the grazing season. The CH4 emission data were analyzed using a split-plot ANOVA, and the repeatability of each of the applied methods for determining CH4 emission was calculated. Traits other than CH4 emission were analyzed for differences between low and high emitters using a linear mixed model. The initial category-dependent differences in daily CH4 production persisted over the subsequent 5 mo and across 2 feeding regimens with both methods. The repeatability analysis indicated that the biweekly milk control scheme, and even a monthly scheme as practiced on farms, might be sufficient for confirming category differences. However, the relationship between CH4 data estimated by MIR and measured with GF for individual cows was weak (R2 = 0.26). The categorization based on CH4 production also generated differences in CH4 emission per kilogram of milk; differentiation between cow categories was not persistent based on milk MIR spectra and GF. Compared with the high emitters, low emitters tended to show a lower acetate-to-propionate ratio in ruminal volatile fatty acids, whereas feed intake and ruminating time did not differ. Interestingly, the low emitters spent less time eating than the high emitters. In conclusion, the CH4 estimation from analyzing the milk MIR spectra is an appropriate proxy to form and regularly control categories of cows with different CH4 production levels. The categorization was also sufficient to secure similar and persistent differences in emission intensity when estimated by MIR spectra of the milk. Further studies are needed to determine whether MIR data from individual cows are sufficiently accurate for breeding.
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Authors Denninger, T. ., Dohme-Meier, F., Eggerschwiler, L., Vanlierde, A., Grandl, F., Gredler, B., Kreuzer, M., Schwarm, A., Münger, A.