Literature DB >> 28007048

Non-invasive individual methane measurement in dairy cows.

E Negussie1, J Lehtinen2, P Mäntysaari3, A R Bayat3, A-E Liinamo1, E A Mäntysaari1, M H Lidauer1.   

Abstract

Attempts to lower the environmental footprint of milk production needs a sound understanding of the genetic and nutritional basis of methane (CH4) emissions from the dairy production systems. This in turn requires accurate and reliable techniques for the measurement of CH4 output from individual cows. Many of the available measurement techniques so far are either slow, expensive, labor intensive and are unsuitable for large-scale individual animal measurements. The main objectives of this study were to examine and validate a non-invasive individual cow CH4 measurement system that is based on photoacoustic IR spectroscopy (PAS) technique implemented in a portable gas analysis equipment (F10), referred to as PAS-F10 method and to estimate the magnitude of between-animal variations in CH4 output traits. Data were collected from 115 Nordic Red cows of the Minkiö experimental dairy farm, at the Natural Resources Institute Finland (Luke). Records on continuous daily measurements of CH4, milk yield, feed intake and BW measurements over 2 years period were compiled for data analysis. The daily CH4 output was calculated using carbon dioxide as a tracer method. Estimates from the non-invasive PAS-F10 technique were then tested against open-circuit indirect respiration calorimetric chamber measurements and against estimates from other widely used prediction models. Concordance analysis was used to establish agreement between the chamber and PAS-F10 methods. A linear mixed model was used for the analysis of the large continuous data. The daily CH4 output of cows was 555 l/day and ranged from 330 to 800 l/day. Dry matter intake, level of milk production, lactation stage and diurnal variation had significant effects on daily CH4 output. Estimates of the daily CH4 output from PAS-F10 technique compared relatively well with the other techniques. The concordance correlation coefficient between combined weekly CH4 output estimates of PAS-F10 and chamber was 0.84 with lower and upper confidence limits of 0.65 and 0.93, respectively. Similarly, when chamber CH4 measurements were predicted from PAS-F10 measurements, the mean of two separate weekly PAS-F10 measurements gave the lowest prediction error variance than either of the separate weekly PAS-F10 measurements alone. This suggests that every other week PAS-F10 measurements when combined would improve the estimation of CH4 output with PAS-F10 technique. The repeatability of daily CH4 output from PAS-F10 technique ranged from 0.40 to 0.46 indicating that some between-animal variation exist in CH4 output traits.

Entities:  

Keywords:  cattle; methane; mitigation; photoacoustic IR spectroscopy; repeatability

Mesh:

Substances:

Year:  2016        PMID: 28007048     DOI: 10.1017/S1751731116002718

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  10 in total

1.  Heritability of methane emissions from dairy cows over a lactation measured on commercial farms.

Authors:  M Pszczola; K Rzewuska; S Mucha; T Strabel
Journal:  J Anim Sci       Date:  2017-11       Impact factor: 3.159

2.  Genetic evaluation including intermediate omics features.

Authors:  Ole F Christensen; Vinzent Börner; Luis Varona; Andres Legarra
Journal:  Genetics       Date:  2021-10-02       Impact factor: 4.402

3.  Prediction of enteric methane emissions from lactating cows using methane to carbon dioxide ratio in the breath.

Authors:  Tomoyuki Suzuki; Yuko Kamiya; Kohei Oikawa; Itoko Nonaka; Takumi Shinkai; Fuminori Terada; Taketo Obitsu
Journal:  Anim Sci J       Date:  2021       Impact factor: 1.974

4.  Genome-wide association identifies methane production level relation to genetic control of digestive tract development in dairy cows.

Authors:  M Pszczola; T Strabel; S Mucha; E Sell-Kubiak
Journal:  Sci Rep       Date:  2018-10-11       Impact factor: 4.379

5.  A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions.

Authors:  R John Wallace; Goor Sasson; Philip C Garnsworthy; Ilma Tapio; Emma Gregson; Paolo Bani; Pekka Huhtanen; Ali R Bayat; Francesco Strozzi; Filippo Biscarini; Timothy J Snelling; Neil Saunders; Sarah L Potterton; James Craigon; Andrea Minuti; Erminio Trevisi; Maria L Callegari; Fiorenzo Piccioli Cappelli; Edward H Cabezas-Garcia; Johanna Vilkki; Cesar Pinares-Patino; Kateřina O Fliegerová; Jakub Mrázek; Hana Sechovcová; Jan Kopečný; Aurélie Bonin; Frédéric Boyer; Pierre Taberlet; Fotini Kokou; Eran Halperin; John L Williams; Kevin J Shingfield; Itzhak Mizrahi
Journal:  Sci Adv       Date:  2019-07-03       Impact factor: 14.136

6.  Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle.

Authors:  Philip C Garnsworthy; Gareth F Difford; Matthew J Bell; Ali R Bayat; Pekka Huhtanen; Björn Kuhla; Jan Lassen; Nico Peiren; Marcin Pszczola; Diana Sorg; Marleen H P W Visker; Tianhai Yan
Journal:  Animals (Basel)       Date:  2019-10-21       Impact factor: 2.752

Review 7.  Phenomes: the current frontier in animal breeding.

Authors:  Miguel Pérez-Enciso; Juan P Steibel
Journal:  Genet Sel Evol       Date:  2021-03-05       Impact factor: 4.297

8.  Detection of Methane Eructation Peaks in Dairy Cows at a Robotic Milking Station Using Signal Processing.

Authors:  Ali Hardan; Philip C Garnsworthy; Matt J Bell
Journal:  Animals (Basel)       Date:  2021-12-23       Impact factor: 2.752

9.  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

Review 10.  Global Warming and Dairy Cattle: How to Control and Reduce Methane Emission.

Authors:  Dovilė Bačėninaitė; Karina Džermeikaitė; Ramūnas Antanaitis
Journal:  Animals (Basel)       Date:  2022-10-06       Impact factor: 3.231

  10 in total

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