Effect of drought stress on flowering characteristics in rice (Oryza sativa L.): a study using genotypes contrasting in drought tolerance and flower opening time.

Rice is most susceptible to heat and drought stress at flowering stage, but flowering characteristics under drought stress are not well characterized. This study investigated flowering characteristics of rice genotypes contrasting in their flower opening time (FOT) and level of drought tolerance. Near-isogenic lines for the early-morning flowering trait (IR64+ qEMF3) and for drought tolerance (IR87707-445-B-B-B), and their recurrent parent cultivar (IR64) were used. IR64+ qEMF3 had stable earlier FOT than IR64 and IR87707-445-B-B-B under drought stress conditions. Drought stress occasionally affects FOT depending on genotype. The number of open spikelets was higher in IR87707-445-B-B-B than in IR64 and IR64+ qEMF3, and the difference among genotypes increased as the rice plants were subjected to more severe stress levels. Panicle temperature increased under drought stress conditions and was similar among genotypes when it was measured at the same time of day, demonstrating that earlier FOT in IR64+ qEMF3 must be beneficial to avoid heat stress at flowering under drought stress conditions. However, IR64+ qEMF3 did not exhibit drought avoidance, as evidenced by the root mass at depth. To assess the potential for the EMF trait to complement ongoing drought breeding efforts, heat tolerance among 13 advanced drought breeding lines and released cultivars was tested. Wide variation in heat tolerance at flowering was observed and, notably, none of the 13 lines possessed the EMF trait. This study therefore proposes that a breeding strategy that transfers the EMF trait into drought tolerant lines could enhance the resilience of rice spikelets to the combined stresses of heat and drought at flowering. Abbreviations: Analysis of variance (ANOVA), dry season (DS), early-morning flowering (EMF), flower opening time (FOT), near-isogenic line (NIL), panicle water potential (PWP), quantitative trait locus (QTL), wet season (WS) [ABSTRACT FROM AUTHOR]