Journal
ANNALS OF APPLIED BIOLOGY
Volume -, Issue -, Pages -Publisher
WILEY
DOI: 10.1111/aab.12856
Keywords
isoflavone content; phenotypic plasticity; root distribution; root nodule formation; soil moisture fluctuation
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Three ecotypes of Trifolium subterraneum ssp. yanninicum L. showed different responses to soil moisture fluctuation, with Ecotype A demonstrating better adaptation to WL-WD treatment, especially in terms of rapid growth post-WL. This finding has significant implications for understanding the adaptation of pasture legumes to fluctuating soil moisture conditions.
The pasture legume Trifolium subterraneum ssp. yanninicum L. is waterlogging tolerant, but water-deficit (WD) susceptible. The interactive effect of waterlogged (WL) and WD (soil moisture fluctuation [SMF]) results in a severe stress impact. We studied three diverse ecotypes to identify traits associated with adaptation to SMF. Ecotypes were established in a glasshouse with two treatments imposed at 21 days: well-watered (WW-WW; 80% field capacity [FC]) and WL to WD (WL-WD). For WL-WD, pots were WL for 28 days (Harvest I), and then transitioned to WD (drained to 40% FC) and maintained for 10 days (Harvest II). For shoot relative growth rates (RGR) at Harvest I, WL had relatively little impact, although there was a greater reduction for Ecotype A (80% of WW) than Ecotypes B (92%) and C (87%). However, between Harvests I and II, the impact of WL-WD varied among ecotypes with Ecotype A being less affected (75% of WW-WW) than Ecotypes B (57%) and C (63%). For root RGR at Harvest I, WL resulted in a greater reduction for Ecotype A (52% of WW) than Ecotypes B (77%) and C (74%), while for WL-WD between Harvests I and II, Ecotype A showed a large increase (117% of WW-WW) compared to Ecotypes B (95%) and C (87%). In conclusion, the response to WD following WL varied among ecotypes, which demonstrates contrasting adaptation responses to SMF unrelated to WL tolerance. High yield under WL together with capacity for rapid growth post-WL in a drying soil profile could enhance adaptation to SMF.
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