Literature DB >> 26026761

Hot topic: Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra.

A Vanlierde1, M-L Vanrobays2, F Dehareng1, E Froidmont3, H Soyeurt2, S McParland4, E Lewis4, M H Deighton5, F Grandl6, M Kreuzer6, B Gredler7, P Dardenne1, N Gengler8.   

Abstract

The main goal of this study was to develop, apply, and validate a new method to predict an indicator for CH4 eructed by dairy cows using milk mid-infrared (MIR) spectra. A novel feature of this model was the consideration of lactation stage to reflect changes in the metabolic status of the cow. A total of 446 daily CH4 measurements were obtained using the SF6 method on 142 Jersey, Holstein, and Holstein-Jersey cows. The corresponding milk samples were collected during these CH4 measurements and were analyzed using MIR spectroscopy. A first derivative was applied to the milk MIR spectra. To validate the novel calibration equation incorporating days in milk (DIM), 2 calibration processes were developed: the first was based only on CH4 measurements and milk MIR spectra (independent of lactation stage; ILS); the second included milk MIR spectra and DIM information (dependent on lactation stage; DLS) by using linear and quadratic modified Legendre polynomials. The coefficients of determination of ILS and DLS equations were 0.77 and 0.75, respectively, with standard error of calibration of 63g/d of CH4 for both calibration equations. These equations were applied to 1,674,763 milk MIR spectra from Holstein cows in the first 3 parities and between 5 and 365 DIM. The average CH4 indicators were 428, 444, and 448g/d by ILS and 444, 467, and 471g/d by DLS for cows in first, second, and third lactation, respectively. Behavior of the DLS indicator throughout the lactations was in agreement with the literature with values increasing between 0 and 100 DIM and decreasing thereafter. Conversely, the ILS indicator of CH4 emission decreased at the beginning of the lactation and increased until the end of the lactation, which differs from the literature. Therefore, the DLS indicator seems to better reflect biological processes that drive CH4 emissions than the ILS indicator. The ILS and DLS equations were applied to an independent data set, which included 59 respiration chamber measurements of CH4 obtained from animals of a different breed across a different production system. Results indicated that the DLS equation was much more robust than the ILS equation allowing development of indicators of CH4 emissions by dairy cows. Integration of DIM information into the prediction equation was found to be a good strategy to obtain biologically meaningful CH4 values from lactating cows by accounting for biological changes that occur throughout the lactation.
Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  dairy cattle; lactation stage; methane; mid-infrared; milk

Mesh:

Substances:

Year:  2015        PMID: 26026761     DOI: 10.3168/jds.2014-8436

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  10 in total

1.  Estimates of the genetic contribution to methane emission in dairy cows: a meta-analysis.

Authors:  Navid Ghavi Hossein-Zadeh
Journal:  Sci Rep       Date:  2022-07-19       Impact factor: 4.996

2.  In-line near-infrared analysis of milk coupled with machine learning methods for the daily prediction of blood metabolic profile in dairy cattle.

Authors:  Diana Giannuzzi; Lucio Flavio Macedo Mota; Sara Pegolo; Luigi Gallo; Stefano Schiavon; Franco Tagliapietra; Gil Katz; David Fainboym; Andrea Minuti; Erminio Trevisi; Alessio Cecchinato
Journal:  Sci Rep       Date:  2022-05-16       Impact factor: 4.996

3.  Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance.

Authors:  Rainer Roehe; Richard J Dewhurst; Carol-Anne Duthie; John A Rooke; Nest McKain; Dave W Ross; Jimmy J Hyslop; Anthony Waterhouse; Tom C Freeman; Mick Watson; R John Wallace
Journal:  PLoS Genet       Date:  2016-02-18       Impact factor: 5.917

4.  Body fat mobilization in early lactation influences methane production of dairy cows.

Authors:  A Bielak; M Derno; A Tuchscherer; H M Hammon; A Susenbeth; B Kuhla
Journal:  Sci Rep       Date:  2016-06-16       Impact factor: 4.379

5.  Prediction of Acute and Chronic Mastitis in Dairy Cows Based on Somatic Cell Score and Mid-Infrared Spectroscopy of Milk.

Authors:  Lisa Rienesl; Negar Khayatzdadeh; Astrid Köck; Christa Egger-Danner; Nicolas Gengler; Clément Grelet; Laura Monica Dale; Andreas Werner; Franz-Josef Auer; Julie Leblois; Johann Sölkner
Journal:  Animals (Basel)       Date:  2022-07-18       Impact factor: 3.231

6.  Genetic Parameters for Methane Emissions Using Indirect Prediction of Methane and Its Association with Milk and Milk Composition Traits.

Authors:  Heydar Ghiasi; Beata Sitkowska; Dariusz Piwczyński; Magdalena Kolenda
Journal:  Animals (Basel)       Date:  2022-08-14       Impact factor: 3.231

7.  The use of milk Fourier transform mid-infrared spectra and milk yield to estimate heat production as a measure of efficiency of dairy cows.

Authors:  Sadjad Danesh Mesgaran; Anja Eggert; Peter Höckels; Michael Derno; Björn Kuhla
Journal:  J Anim Sci Biotechnol       Date:  2020-05-07

8.  Genetic Analysis of Milk Production Traits and Mid-Infrared Spectra in Chinese Holstein Population.

Authors:  Chao Du; Liangkang Nan; Lei Yan; Qiuyue Bu; Xiaoli Ren; Zhen Zhang; Ahmed Sabek; Shujun Zhang
Journal:  Animals (Basel)       Date:  2020-01-15       Impact factor: 2.752

9.  Inhibition of enteric methanogenesis in dairy cows induces changes in plasma metabolome highlighting metabolic shifts and potential markers of emission.

Authors:  Bénédict Yanibada; Ulli Hohenester; Mélanie Pétéra; Cécile Canlet; Stéphanie Durand; Fabien Jourdan; Julien Boccard; Cécile Martin; Maguy Eugène; Diego P Morgavi; Hamid Boudra
Journal:  Sci Rep       Date:  2020-09-24       Impact factor: 4.379

Review 10.  Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems.

Authors:  Tiago Bresolin; João R R Dórea
Journal:  Front Genet       Date:  2020-08-20       Impact factor: 4.599

  10 in total

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