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A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems

SIMPLE SUMMARY: The carbon footprint (CF) is, at present, the most widely used indicator to quantify the impact of livestock farming on global warming, fulfilling also the purpose of identifying production practices that develop more efficient uses of available resources, as well as ways to minimize...

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Autores principales: Mancilla-Leytón, Juan Manuel, Morales-Jerrett, Eduardo, Muñoz-Vallés, Sara, Mena, Yolanda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525792/
https://www.ncbi.nlm.nih.gov/pubmed/37760264
http://dx.doi.org/10.3390/ani13182864
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author Mancilla-Leytón, Juan Manuel
Morales-Jerrett, Eduardo
Muñoz-Vallés, Sara
Mena, Yolanda
author_facet Mancilla-Leytón, Juan Manuel
Morales-Jerrett, Eduardo
Muñoz-Vallés, Sara
Mena, Yolanda
author_sort Mancilla-Leytón, Juan Manuel
collection PubMed
description SIMPLE SUMMARY: The carbon footprint (CF) is, at present, the most widely used indicator to quantify the impact of livestock farming on global warming, fulfilling also the purpose of identifying production practices that develop more efficient uses of available resources, as well as ways to minimize their environmental impact. The aim of this study was to characterize the CF in the four different production systems of autochthonous dairy goat breeds currently occurring in Andalusia (S Spain), from confined to pastoral systems, also considering the carbon sink ability by vegetation associated with land-based livestock systems. Despite the difficulties of calculation, the relevance of using a species-specific standardization equation and of taking into account land carbon sink ability was demonstrated. The four production systems analyzed obtained similar CF values, all showing room for improvement. This must be translated into the adoption of specific actions for each production system and territory, particularly regarding the improvement of grazing activity, optimal use of farm resources, and appropriate management of manure or the use of local food. Professional advice, training, and the use of specific management tools are essential for the implementation of these strategies to move towards low-carbon goat production. ABSTRACT: The small ruminant livestock sector faces the challenge of reducing greenhouse gas (GHG) emissions. Carbon footprint (CF) studies on dairy goats, the most widely used indicator to quantify the impact of livestock farming on global warming, are still few. The aim of this study was to calculate the CF of the different production systems of autochthonous dairy goat breeds presently occurring in Andalusia (S Spain) and identify systems and practices that can minimize their environmental impact in these terms. Twenty-one farms were monitored during a year, obtaining valuable information that allowed the CF calculation on a “cradle-to-gate” approach, taking into account both GHG emissions at the farm level and carbon sink by vegetation associated with land-based systems. Results showed similar CF values for the analyzed systems (1.42, 1.04, 1.15, and 1.17 kg CO(2)-eq kg(−1) fat–protein corrected milk for indoor systems without associated crops, indoor systems with associated crops, grazing systems with high feed supply, and pastoral systems, respectively). To minimize their environmental impact, specific actions must be developed for each system, particularly regarding genetic improvement, reproductive and feeding management, including pasture management, and the integration of livestock activity into the bio-circular economy with the help of professional advice.
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spelling pubmed-105257922023-09-28 A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems Mancilla-Leytón, Juan Manuel Morales-Jerrett, Eduardo Muñoz-Vallés, Sara Mena, Yolanda Animals (Basel) Article SIMPLE SUMMARY: The carbon footprint (CF) is, at present, the most widely used indicator to quantify the impact of livestock farming on global warming, fulfilling also the purpose of identifying production practices that develop more efficient uses of available resources, as well as ways to minimize their environmental impact. The aim of this study was to characterize the CF in the four different production systems of autochthonous dairy goat breeds currently occurring in Andalusia (S Spain), from confined to pastoral systems, also considering the carbon sink ability by vegetation associated with land-based livestock systems. Despite the difficulties of calculation, the relevance of using a species-specific standardization equation and of taking into account land carbon sink ability was demonstrated. The four production systems analyzed obtained similar CF values, all showing room for improvement. This must be translated into the adoption of specific actions for each production system and territory, particularly regarding the improvement of grazing activity, optimal use of farm resources, and appropriate management of manure or the use of local food. Professional advice, training, and the use of specific management tools are essential for the implementation of these strategies to move towards low-carbon goat production. ABSTRACT: The small ruminant livestock sector faces the challenge of reducing greenhouse gas (GHG) emissions. Carbon footprint (CF) studies on dairy goats, the most widely used indicator to quantify the impact of livestock farming on global warming, are still few. The aim of this study was to calculate the CF of the different production systems of autochthonous dairy goat breeds presently occurring in Andalusia (S Spain) and identify systems and practices that can minimize their environmental impact in these terms. Twenty-one farms were monitored during a year, obtaining valuable information that allowed the CF calculation on a “cradle-to-gate” approach, taking into account both GHG emissions at the farm level and carbon sink by vegetation associated with land-based systems. Results showed similar CF values for the analyzed systems (1.42, 1.04, 1.15, and 1.17 kg CO(2)-eq kg(−1) fat–protein corrected milk for indoor systems without associated crops, indoor systems with associated crops, grazing systems with high feed supply, and pastoral systems, respectively). To minimize their environmental impact, specific actions must be developed for each system, particularly regarding genetic improvement, reproductive and feeding management, including pasture management, and the integration of livestock activity into the bio-circular economy with the help of professional advice. MDPI 2023-09-09 /pmc/articles/PMC10525792/ /pubmed/37760264 http://dx.doi.org/10.3390/ani13182864 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mancilla-Leytón, Juan Manuel
Morales-Jerrett, Eduardo
Muñoz-Vallés, Sara
Mena, Yolanda
A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title_full A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title_fullStr A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title_full_unstemmed A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title_short A Comparative Analysis of Carbon Footprint in the Andalusian Autochthonous Dairy Goat Production Systems
title_sort comparative analysis of carbon footprint in the andalusian autochthonous dairy goat production systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525792/
https://www.ncbi.nlm.nih.gov/pubmed/37760264
http://dx.doi.org/10.3390/ani13182864
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