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Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus
Journal article   Peer reviewed

Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus

Jeremy T Brawner, David J Lee, Roger Meder, A Almeida and M J Dieters
Euphytica, Vol.191(3), pp.403-414
2013
url
https://doi.org/10.1007/s10681-013-0892-4View
Published Version

Abstract

adaptation genotype by environmental interactions Eucalyptus Corymbia functional groups process-based model
A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species' productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

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Agronomy
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Plant Sciences

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