Raymond, Joanna, Mackay, Ian, Penfield, Steven, Lovett, Andrew ORCID: https://orcid.org/0000-0003-0554-9273, Philpott, Haidee and Dorling, Stephen
(2023)
Combining historical agricultural and climate datasets sheds new light on early 20th century barley performance.
Annals of Applied Biology, 182 (3).
pp. 381-396.
ISSN 0003-4746
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Abstract
Barley (Hordeum vulgare ssp. vulgare) is cultivated globally across a wide range of environments, both in highly productive agricultural systems and in subsistence agriculture and provides valuable feedstock for the animal feed and malting industries. However, as the climate changes there is an urgent need to identify adapted barley varieties that will consistently yield highly under increased environmental stresses. Our ability to predict future local climates is only as good as the skill of the climate model, however we can look back over 100 years with much greater certainty. Historical weather datasets are an excellent resource for identifying causes of historical yield variability. In this research we combined recently digitised historical weather data from the early 20th century with published Irish spring barley trials data for two heritage varieties: Archer and Goldthorpe, following an analysis first published by Student in 1923. Using linear mixed models, we show that interannual variation in observed spring barley yields can be partially explained by recorded weather variability, in particular July maximum temperature and rainfall, and August maximum temperature. We find that while Archer largely yields more highly, Goldthorpe is more stable under wetter growing conditions, highlighting the importance of considering growing climate in variety selection. Furthermore, this study demonstrates the benefits of access to historical trials and climatic data and the importance of incorporating climate data in modern day breeding programmes to improve climate resilience of future varieties.
Item Type: | Article |
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Uncontrolled Keywords: | spring barley,student,breeding,climate variability,statistical modelling,agronomy and crop science ,/dk/atira/pure/subjectarea/asjc/1100/1102 |
Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
UEA Research Groups: | Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Social Sciences > Research Centres > Water Security Research Centre Faculty of Science > Research Groups > Environmental Social Sciences Faculty of Science > Research Centres > Centre for Social and Economic Research on the Global Environment (CSERGE) |
Related URLs: | |
Depositing User: | LivePure Connector |
Date Deposited: | 28 Apr 2023 11:30 |
Last Modified: | 14 Aug 2024 00:32 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/91908 |
DOI: | 10.1111/aab.12826 |
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