Genotype×environment interaction studies highlight the role of phenology in specific adaptation of canola (Brassica napus) to contrasting Mediterranean climates

► Seed yield and oil content of canola genotypes and their interactions with environment were investigated. ► Significant genotype crossover yield responses to environment but little G×E interaction effect on oil content. ► The medium flowering genotypes produced higher yield than the early flowerin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Field crops research 2013-03, Vol.144, p.77-88
Hauptverfasser: Zhang, Heping, Berger, Jens D., Milroy, Steve P.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:► Seed yield and oil content of canola genotypes and their interactions with environment were investigated. ► Significant genotype crossover yield responses to environment but little G×E interaction effect on oil content. ► The medium flowering genotypes produced higher yield than the early flowering ones in the high rainfall areas but yielded poorly in the low rainfall areas, and vice versa. ► Two mega-environments were identified for targeted breeding in south-western Australia. While genotype (G)×environment (E) interaction (G×E) complicates broad crop adaptation, understanding its causes facilitates breeding for specific adaptation. South-western Australia captures a broad range of Mediterranean climates, from a very warm short season with low rainfall in the north and east to a longer season with high rainfall in the southwest, and provides a unique opportunity to investigate G×E interaction. In this study, we evaluate G×E interaction for seed yield and oil content of canola genotypes with wide ranging phenology across south-western Australia. Environments were separated into year (Y) and location (L) and a factor analytic (FA) model used to partition G×E interactions into G×Y, G×L and G×Y×L across four years (2006–2009). G×E interaction contributed 34% to total variance of seed yield compared with 9% for G. An additive main effects and multiplicative interaction (AMMI) model was used to further evaluate the significance of G×L, and delineate mega-environments (ME) and determine the best performing cultivar in each year. AMMI identified two MEs with different seasonal climates. ME1 combines >330mm seasonal rainfall with a cooler, longer post-anthesis growing period. ME2 is more terminally drought-prone, with higher temperatures and
ISSN:0378-4290
1872-6852
DOI:10.1016/j.fcr.2013.01.006