Search

Abstract Drought has a significant impact on rice yield by restricting the crop's ability to grow and develop. Producing rice cultivars adapted to water deficit conditions is still the main interest of rice breeders and geneticists. To address this challenge, a set of 413 highly diverse rice populations were evaluated under normal and water deficit conditions for two growing seasons of 2021 and 2022. High genetic variation was found among genotypes for all studied traits. The heritability estimates ranged from 0.82 (panicle length) to 0.95 (plant height). Sterility percentage (SET%) was the most trait affected by water deficit in two growing seasons. 22 Rice genotypes were classified as drought tolerant in both years. Genome-wide association mapping was performed for all traits in the two growing seasons under both conditions using a total of 700,000 SNPs. The GWAS results revealed important and major SNPs associated with all traits. 26 Significant SNPs with stable allele effects were found to be associated with yield traits under water deficit conditions in both years. The results of this study provided rice genotypes that can be adapted under water deficit conditions and important stable SNP markers that can be used for marker-assisted selection after validation in different genetic backgrounds.

Abstract Background Water deficit is one of the most significant abiotic factors affecting rice and agricultural production worldwide. In hybrid rice, cytoplasmic male sterility (CMS) is an important technique for creating high-yielding crop based on heterosis. The phytohormone kinetin (Kin) regulates cell division in plant during the early stages of grain formation, as well as flow assimilation and osmotic regulation under water stress. The present study performed to estimate the effects of irrigation intervals (irrigation each six days (I6), nine days (I9), twelve days (I12) and fifteen days (I15) against continuous flooding (CF, each three days)) and kinetin exogenously application (control, 15 mg L−1 and 30 mg L−1) on hybrid rice (L1, IR69625A; L2, G46A and R, Giza 178 R) seed production. Results Leaves traits (Chlorophyll content (CHC), relative water content (RWC), stomatal conductance (SC), Leaf temperature (LT) and transpiration rate (TR)), floral traits such as style length (SL) and total stigma length (TSL), in addition to root traits (i.e., root length (RL), root volume (RV), root: shoot ratio (RSR), root thickness (RT), root xylem vessels number (RXVN) and root xylem vessel area (RXVA) were evaluated and a significant enhancement in most traits was observed. Applying 30 mg L−1 kinetin significantly and positively enhanced all growth, floral and roots traits (RV and RXVA recorded the most increased values by 14.8% and 23.9%, respectively) under prolonging irrigation intervals, in comparison to non-treated plants. Conclusions Subsequently, spraying kinetin exogenously on foliar could be an alternative method to reduce the harmful influences of water deficiency during seed production in hybrid rice.

Rice production faces challenges related to diverse climate change processes. Heat stress combined with low humidity, water scarcity, and salinity are the foremost threats in its cultivation. The present investigation aimed at identifying the most resilient rice genotypes with yield stability to cope with the current waves of climate change. A total of 34 rice genotypes were exposed to multilocation trials. These locations had different environmental conditions, mainly normal, heat stress with low humidity, and salinity-affected soils. The genotypes were assessed for their yield stability under these conditions. The newly developed metan package of R-studio was employed to perform additive main effects and multiplicative interactions modelling and genotype-by-environment modelling. The results indicated that there were highly significant differences among the tested genotypes and environments. The main effects of the environments accounted for the largest portion of the total yield sum of squared deviations, while different sets of genotypes showed good performance in different environments. AMMI1 and GGE biplots confirmed that Giza179 was the highest-yielding genotype, whereas Giza178 was considered the most-adopted and highest-yielding genotype across environments. These findings were further confirmed by the which–won–where analysis, which explained that Giza178 has the greatest adaptability to the different climatic conditions under study. While Giza179 was the best under normal environments, N22 recorded the uppermost values under heat stress coupled with low humidity, and GZ1968-S-5-4 manifested superior performance regarding salinity-affected soils. Giza 177 was implicated regarding harsh environments. The mean vs. stability-based rankings indicated that the highest-ranked genotypes were Giza179 > Giza178 > IET1444 > IR65600-77 > GZ1968-S-5-4 > N22 > IR11L236 > IR12G3213. Among them, Giza178, IR65600-77, and IR12G3213 were the most stable genotypes. Furthermore, these results were confirmed by cluster-analysis-based stability indices. A significant and positive correlation was detected between the overall yield under all the environments with panicle length, number of panicles per plant, and thousand grain weight. Our study sheds light on the notion that the Indica/Japonica and Indica types have greater stability potential over the Japonica ones, as well as the potential utilization of genotypes with wide adaptability, stability, and high yield, such as Giza178, in the breeding programs for climate change resilience in rice.