Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 506688
Title Prediction of methane emission from lactating dairy cows using milk fatty acids and mid-infrared spectroscopy
Author(s) Gastelen, Sanne van; Dijkstra, Jan
Source Journal of the Science of Food and Agriculture 96 (2016)12. - ISSN 0022-5142 - p. 3963 - 3968.
DOI http://dx.doi.org/10.1002/jsfa.7718
Department(s) Animal Nutrition
LR - Animal Nutrition
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2016
Keyword(s) dairy cows - methane emission - mid-infrared spectroscopy - milk fatty acids
Abstract

Enteric methane (CH4) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH4 emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH4 production because of the common biochemical pathway between CH4 and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH4 emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid-infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH4 emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH4 prediction, and the moderate predictive power for CH4 emission. It may not be sufficient to predict CH4 emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH4 emission using MIR spectra. © 2016 Society of Chemical Industry.

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