Floods are major constraints to crop production worldwide. In low-lying, flood-prone areas of the tropics, longer-term partial submergence (stagnant flooding [SF]) greatly reduces rice yield. This study assesses shoot growth and several physiological mechanisms associated with SF tolerance in rice. Five rice genotypes with contrasting responses to SF were evaluated in field ponds. Following transplanting, floodwater was gradually increased at a rate of ∼2 cm day(-1) to reach a final depth of 50 cm and then maintained until maturity. Although plants were not fully submerged, the yield was reduced by 47 % across genotypes compared with those grown under control conditions (6.1 vs. 3.3 t ha(-1)). This reduction was mainly attributed to the reduction in biomass caused by reduced light interception and leaf growth above the water. Stagnant flooding also reduced panicle number per unit area by 52 % because of reduced tillering. Shoot elongation rate kept pace with rising floodwater and correlated positively with leaf growth and biomass production. Conversely, stem non-structural carbohydrate (NSC) concentration correlated negatively with shoot elongation rate, suggesting that fast-elongating genotypes actively consume NSCs to avoid complete submergence. Moderate shoot elongation rate strongly and positively correlated with grain yield under SF; however, elongation at rates >2.0 cm day(-1) was associated with reduced harvest index due to a smaller panicle size and increased lodging. Tolerant varieties were found to be either inherently tall or elongate moderately with rising floodwater. Our studies suggest that to improve tolerance of SF an appropriate phenotype should combine both of these traits. Fine-tuning for optimum shoot elongation with rising floodwater is, therefore, a priority for future work.

Background and Aims: Rice ecosystems in the tropical coastal areas are subject to two types of flooding stress: transient complete submergence and long-term water stagnation (stagnant flooding). Here, we aimed to dissect the mechanisms for stagnant flooding tolerance of rice genotypes carrying SUB1, a quantitative trait locus for submergence tolerance. Methods: We screened 80 elite genotypes under stagnant flooding stress in the lowland rice fields in the wet and dry seasons, and examined the tolerance mechanisms of promising genotypes for the two following seasons. Key results: Yield reduction under stagnant flooding averaged 48 % in the dry season and 89 % in the wet season. Elite genotypes carrying SUB1 showed 49 % lower yield than those without SUB1 under stagnant flooding, with no differences under shallow water conditions. However, we identified a few high-yielding Sub1 genotypes that were as tolerant of stagnant flooding as a reference genotype that lacked SUB1. These genotypes had intermediate stature with more shoot elongation in response to rising water than a moderately tolerant Sub1 reference variety, resulting in greater canopy expansion and higher yield. It was important to increase lodging resistance, since plant height >140 cm increased lodging under stagnant flooding. The culm diameter was closely associated with culm strength; reduced aerenchyma formation and increased lignin accumulation in the culm should increase lodging resistance. Conclusions: The study demonstrated a successful combination of submergence and stagnant flooding tolerance in a rice breeding programme, and identified elite Sub1 genotypes that also tolerate stagnant flooding. Our results will support genetic improvement of Sub1 varieties for stagnant flooding tolerance.

Unmanned aerial vehicle (UAV) and structure from motion (SfM) photogrammetry techniques are widely used for field-based, high-throughput plant phenotyping nowadays, but some of the intermediate processes throughout the workflow remain manual. For example, geographic information system (GIS) software is used to manually assess the 2D/3D field reconstruction quality and cropping region of interests (ROIs) from the whole field. In addition, extracting phenotypic traits from raw UAV images is more competitive than directly from the digital orthomosaic (DOM). Currently, no easy-to-use tools are available to implement previous tasks for commonly used commercial SfM software, such as Pix4D and Agisoft Metashape. Hence, an open source software package called easy intermediate data processor (EasyIDP; MIT license) was developed to decrease the workload in intermediate data processing mentioned above. The functions of the proposed package include (1) an ROI cropping module, assisting in reconstruction quality assessment and cropping ROIs from the whole field, and (2) an ROI reversing module, projecting ROIs to relative raw images. The result showed that both cropping and reversing modules work as expected. Moreover, the effects of ROI height selection and reversed ROI position on raw images to reverse calculation were discussed. This tool shows great potential for decreasing workload in data annotation for machine learning applications.