Combining historical agricultural and climate datasets sheds new light on early 20th century barley performance

Author:

Raymond Joanna1ORCID,Mackay Ian2ORCID,Penfield Steven3,Lovett Andrew1,Philpott Haidee4,Dorling Stephen1

Affiliation:

1. School of Environmental Sciences University of East Anglia Norwich UK

2. Principal's Academic Team Scotland's Rural College (SRUC) Edinburgh UK

3. Crop Genetics John Innes Centre Norwich UK

4. Cambridge Crop Research National Institute for Agricultural Botany Cambridge UK

Abstract

AbstractBarley (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.

Funder

Natural Environment Research Council

Publisher

Wiley

Subject

Agronomy and Crop Science

Reference44 articles.

1. Changes in agricultural climate in South-Eastern England from 1892 to 2016 and differences in cereal and permanent grassland yield

2. Swath‐Grazing Potential for Small‐Grain Species with a Delayed Planting Date

3. Bates D. Mächler M. Bolker B. M. &Walker S. C.(2020).lme4:Linear mixed‐effects models. R package version 1.1.21. Retrieved from.https://github.com/lme4/lme4/

4. A crop calendar for spring wheat and for spring barley;Bauer A.;North Dakota Farm Research,1992

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