Carcass weight of Greenlandic lambs in relation to grazing area biomass

Abstract This study set out to investigate possible relationships between lamb carcass weight and quality with feed availability during the main growing season in southern Greenland where farms are sparsely distributed over a large area. In early May, ewes and new-born lambs are let out to graze per...

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Bibliographic Details
Published in:Open Agriculture
Main Authors: Lehmann, Jesper Overgård, Odgaard, Mette Vestergaard, Kristensen, Troels
Format: Article in Journal/Newspaper
Language:English
Published: Walter de Gruyter GmbH 2020
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Online Access:http://dx.doi.org/10.1515/opag-2020-0009
https://www.degruyter.com/view/journals/opag/5/1/article-p85.xml
https://www.degruyter.com/document/doi/10.1515/opag-2020-0009/xml
https://www.degruyter.com/document/doi/10.1515/opag-2020-0009/pdf
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Summary:Abstract This study set out to investigate possible relationships between lamb carcass weight and quality with feed availability during the main growing season in southern Greenland where farms are sparsely distributed over a large area. In early May, ewes and new-born lambs are let out to graze permanent nature areas until slaughter towards the end of September. In our study, we used data from 157,477 lambs slaughtered between 2010 and 2017 as well as the Normalized Differentiated Vegetation Index (NDVI) as an indicator of biomass growth. Mean carcass weight of lambs ranged from 13.4 kg in 2015 to 16.5 kg in 2010 where 70.5% of all lambs scored well for conformation and fat. Both farm, year, and NDVI significantly correlated with carcass weight and quality. Lambs raised in the northern and the southern grazing areas generally were smaller than lambs raised in the central part. Finally, NDVI explained between 0 and 74% of the variation in mean carcass weight across years within each grazing area. Our work exemplifies the use of satellite-derived data to attempt an explanation of spatial variation in productivity, which in the future could be coupled with other spatial variables such as soil quality, vegetation, and topography.