Meat Consumption and Green Gas Emissions: a Chemometrics Analysis

Chapman, J, Power, A, Chandra, S and Cozzolino, D 2019, 'Meat Consumption and Green Gas Emissions: a Chemometrics Analysis', Food Analytical Methods, vol. 12, pp. 469-474.


Document type: Journal Article
Collection: Journal Articles

Title Meat Consumption and Green Gas Emissions: a Chemometrics Analysis
Author(s) Chapman, J
Power, A
Chandra, S
Cozzolino, D
Year 2019
Journal name Food Analytical Methods
Volume number 12
Start page 469
End page 474
Total pages 6
Publisher Springer New York LLC
Abstract The aim of this study was to relate greenhouse gas emissions (GHGE) from both livestock production (enteric) and agriculture emissions with the consumption of meat from meat producer and importer countries. Data for meat consumption and emission levels of agriculture and livestock production were sourced from the Food and Agriculture Organisation (FAO) database statistics (1961 to 2013). This data is freely available to the public and research community from the FAO webpage. Statistical data was analysed using principal component analysis (PCA), and regression models between GHGE and meat consumption were developed using partial least squares regression (PLS) and validated using cross-validation. Results of this study confirmed observations and anecdotal evidence that enteric and green gas emissions contribute to the perception of meat consumption. Although the results presented in this study are based on the data collected by an international organisation, the authors believe that results from this study can be utilised and incorporated to climate change modelling systems, in order to better understand and define the effect of GHGE on the environmental and economical sustainabilities of the meat production.
Subject Quality Assurance, Chemometrics, Traceability and Metrological Chemistry
Analytical Spectrometry
Keyword(s) Meat consumption
Partial least squares
Gas emissions
Agriculture emissions
Enteric emissions
DOI - identifier 10.1007/s12161-018-1378-8
Copyright notice © Springer Science+Business Media, LLC, part of Springer Nature 2018
ISSN 1936-9751
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