Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3–11% historically to 10–20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.

Models are key tools in our quest to better understand the impacts of soil waterlogging on plant growth and crop production. Here, we reviewed the state of the art of modeling approaches and compared the conceptual design of these models with recent experimental findings. We show that many models adopt an aeration stress (AS) principle where surplus water reduces air‐filled porosity, with implications for root growth. However, subsequent effects of AS within each model vary considerably. In some cases, AS inhibits biomass accumulation (e.g. AquaCrop), altering processes prior to biomass accumulation such as light interception (e.g. APSIM), or photosynthesis and carbohydrate accumulation (e.g. SWAGMAN Destiny). While many models account for stage‐dependent waterlogging effects, few models account for experimentally observed delays in phenology caused by waterlogging. A model intercomparison specifically designed for long‐term waterlogged conditions (APSIM‐Oryza) with models developed for dryland conditions with transient waterlogging would advance our understanding of the current fitness for purpose of exsiting frameworks for simulating transient waterlogging in dryland cropping systems. Of the point‐based dynamic models examined here, APSIM‐Soybean and APSIM‐Oryza simulations most closely matched with the observed data, while GLAM‐WOFOST achieved the highest performance of the spatial‐regional models examined. We conclude that future models should incorporate waterlogging effects on genetic tolerance parameters such as (1) phenology of stress onset, (2) aerenchyma, (3) root hydraulic conductance, (4) nutrient‐use efficiency, and (5) plant ion (e.g. Fe/Mn) tolerance. Incorporating these traits/effects into models, together with a more systematic model intercomparison using consistent initialization data, will significantly improve our understanding of the relative importance of such factors in a systems context, including feedbacks between biological factors, emergent properties, and sensitive variables responsible for yield losses under waterlogging.

In‐crop soil waterlogging can be caused by extreme rainfall events, high ground water tables, excessive irrigation, lateral ground water flow, either individually or in concert, and together these factors inhibit potential grain yields. However, the extent to which yield is influenced by the timing and duration of waterlogging relative to crop phenology is unknown. To investigate this, we conducted a range of waterlogging treatments on modern barley genotypes differing in their waterlogging tolerance, with tolerance conferred through aerenchyma formation under oxygen deficit conditions. Experiment 1 was conducted in a controlled environment using four waterlogging treatments: waterlogging at Zadoks stage (ZS) 12.5 for 1 or 2 months (WL1 and WL2, respectively), waterlogging at ZS 15 for 2 months (WL3), and waterlogging initiated 1 day before heading for 15 days (WL4). Experiment 2 was conducted in the field with WL2. Averaged across experiments, yield was reduced by 35% in W1 to 52% in WL3 due to fewer spikes/m² and kernels/spike. WL4 had the greatest impact on yield (70% reduction) due to its effect on spikelet fertility and grain filling. Phenology was delayed 1–8 ZS at the end of waterlogging treatments, with the waterlogging‐susceptible cultivar Franklin showing the greatest delays, and waterlogging tolerant genotypes (Macquarie+, TAMF169) capable of aerenchyma formation under waterlogging having the least delays (0–4 ZS). Genotypes with aerenchyma formation QTL (Macquarie+) showed nonsignificant yield reduction compared with nonwaterlogged controls, preventing 23% yield loss under early phenological waterlogging stress. Late growth stage waterlogging substantially reduced average final grain yield by 70%.

Waterlogging has increasingly become one of the major constraints to maize productivity in some maize production zones because it causes serious yield loss. Bulked segregant RNA-seq (BSR-seq) has been widely applied to profile candidate genes and map associated Single Nucleotide Polymorphism (SNP) markers in many species. In this study, ten waterlogging sensitive and eight tolerant inbred lines were selected from 60 maize inbred lines with waterlogging response determined and preselected by the International Maize and Wheat Improvement Center (CIMMYT) from over 400 tropical maize inbred lines. BSR-seq was performed to identify differentially expressed genes (DEGs) and SNPs associated with waterlogging tolerance. Upon waterlogging stress, 354 and 1094 genes were differentially expressed in the tolerant and sensitive pools, respectively, compared to untreated controls. When tolerant and sensitive pools were compared, 593 genes were differentially expressed under untreated and 431 genes under waterlogged conditions, of which 122 genes overlapped. To validate the BSR-seq results, the expression levels of six genes were determined by qRT-PCR. The qRT-PCR results were consistent with BSR-seq results. Comparison of allelic polymorphism in mRNA sequences between tolerant and sensitive pools revealed 165 (normal condition) and 128 (waterlogged condition) high-probability SNPs. We found 18 overlapping SNPs with genomic positions mapped. Eighteen SNPs were contained in 18 genes, and eight and nine of 18 genes were responsive to waterlogging stress in tolerant and sensitive lines, respectively. Six alleles of the 18 originated from tolerant pool were significantly up-regulated under waterlogging, but not those from sensitive pool. Importantly, one allele (GRMZM2G055704) of the six genes was mapped between umc1619 and umc1948 on chromosome 1 where a QTL associated with waterlogging tolerance was identified in a previous research, strongly indicating that GRMZM2G055704 is a candidate gene responsive to waterlogging. Our research contributes to the knowledge of the molecular mechanism for waterlogging tolerance in maize.

Rice is one of the major staple cereals in the world, but heat stress is increasingly threatening its yield. Analyzing the thermotolerance mechanism from new thermotolerant germplasms is very important for rice improvement. Here, physiological and transcriptome analyses were used to characterize the difference between two germplasms, heat-sensitive MH101 and heat-tolerant SDWG005. Two genotypes exhibited diverse heat responses in pollen viability, pollination characteristics, and antioxidant enzymatic activity in leaves and spikelets. Through cluster analysis, the global transcriptomic changes indicated that the ability of SDWG005 to maintain a steady-state balance of metabolic processes played an important role in thermotolerance. After analyses of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, we found that the thermotolerance mechanism in SDWG00 was associated with reprogramming the cellular activities, such as response to abiotic stress and metabolic reorganization. In contrast, the down-regulated genes in MH101 that appeared to be involved in DNA replication and DNA repair proofreading, could cause serious injury to reproductive development when exposed to high temperature during meiosis. Furthermore, we identified 77 and 11 differentially expressed genes (DEGs) involved in lignin and flavonoids biosynthetic pathways, respectively. Moreover, we found that more lignin deposition and flavonoids accumulation happened in SDWG005 than in MH101 under heat stress. The results indicated that lignin and flavonoid biosynthetic pathways might play important roles in rice heat resistance during meiosis.