Continuing genetic improvement and biases in genetic gain estimates revealed in historical UK variety trials data

Raymond, Joanna, Mackay, Ian, Penfield, Steven, Lovett, Andrew ORCID: https://orcid.org/0000-0003-0554-9273, Philpott, Haidee and Dorling, Stephen (2023) Continuing genetic improvement and biases in genetic gain estimates revealed in historical UK variety trials data. Field Crops Research, 302. ISSN 0378-4290

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Abstract

Context The current pace of yield increase for major crops is not fast enough to meet future demand. Crop breeding programmes are under increasing pressure to improve existing crops further. Quantifying the contribution of these programmes to observed yield increases is important for evaluating their success and identifying if crop improvement goals are likely to be met. Objective In this paper we explore methods to study the genetic gain of two cereal species, wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). Specifically, the objective of this research was to identify sources of bias in genetic gain estimates of UK variety trials data. Methods Genetic gain was estimated for fungicide-treated and untreated UK winter wheat, winter barley and spring barley for 1982–2018 using UK National List and Recommended List variety trials data. Subsets of the winter wheat variety trials dataset were used to replicate shorter breeding cycles to quantify the impact of the number and choice of long-term check varieties on estimating genetic gain. Results While genetic and non-genetic contributions to changes in UK cereal performance are in line with previous estimates, we were able to identify previously undetected changes and biases in estimates of variety performance. Specifically, we observed an increasing yield difference between fungicide treated and untreated variety trials as varieties age, driven by both a breakdown in disease resistance and a previously unobserved long-term increase in yield as varieties age in treated trials. This shows that yields of long-term check varieties cannot be assumed to be stable over time. We found that genetic gain estimates were highly sensitive to the long-term check varieties chosen, whilst the inclusion of multiple checks decreased the standard error of the estimate. Conclusion The estimation of genetic gain is highly susceptible to bias. We provide recommendations on how to reduce the risk of bias for estimating genetic gain. Implications Accounting for sources of bias in genetic gain calculations is important in any programme of selection to prevent inaccurate quantification of yield progress.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA
UEA Research Groups:	Faculty of Social Sciences > Research Centres > Water Security Research Centre Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Environmental Social Sciences Faculty of Science > Research Centres > Centre for Social and Economic Research on the Global Environment (CSERGE)
Depositing User:	LivePure Connector
Date Deposited:	22 Aug 2023 08:30
Last Modified:	25 Sep 2024 17:26
URI:	https://ueaeprints.uea.ac.uk/id/eprint/92899
DOI:	10.1016/j.fcr.2023.109086

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