ArticleFrontiers in plant science2023
Developing functional relationships between waterlogging and cotton growth and physiology-towards waterlogging modeling.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 17 citations in OpenAlex.
- Exogenous Glutathione and Nitric Oxide Improve Waterlogging Stress Tolerance in Maize.Plant-environment interactions (Hoboken, N.J.) · 2026Article
- Root system architecture remodeling under oxygen-mediated subsurface drip irrigation: a mechanistic hypothesis framework linking multiphase mass transfer to root foraging decisions.Frontiers in plant science · 2026Review
- Current Research on Quantifying Cotton Yield Responses to Waterlogging Stress: Indicators and Yield Vulnerability.Plants (Basel, Switzerland) · 2025Review
- Decoding plant responses to waterlogging: from stress signals to molecular mechanisms and their future implications.Plant molecular biology · 2025Review
- Gaps and strategies for accurate simulation of waterlogging impacts on crop productivity.Nature food · 2025Review
- A minimal mechanistic model of plant responses to oxygen deficit during waterlogging.Quantitative plant biology · 2025Article
- Optimizing pineapple production under waterlogged soil condition in low input management using adequate ridge tillage height and plant density.Frontiers in plant science · 2025Article
- Response to Waterlogging Stress in Wild and Domesticated Accessions of Timothy (Plants (Basel, Switzerland) · 2023Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cotton crop is known to be poorly adapted to waterlogging, especially during the early growth stages. Developing functional relationships between crop growth and development parameters and the duration of waterlogging is essential to develop or improve existing cotton crop models for simulating the impact of waterlogging. However, there are only limited experimental studies conducted on cotton specifically aimed at developing the necessary functional relationships required for waterlogging modeling. Further research is needed to understand the effects of waterlogging on cotton crops and improve modeling capabilities in this area. The current study aimed to conduct waterlogging experiments and develop functional relationships between waterlogging and cotton growth and physiology. The experiments were conducted in pots, and the waterlogging was initiated by plugging the drain hole at the bottom of the pot using a wooden peg. In the experiments, eight waterlogging treatments, including the control treatment, were imposed at the vegetative growth stage (15 days after sowing). Control treatment had zero days of water-logged condition; other treatments had 2, 4, 6, 8, 10, 12, and 14 days of waterlogging. It took five days to reach zero oxygen levels and one to two days to return to control after the treatment. After a total treatment duration of 14 days (30 days after sowing), the growth, physiological, reproductive, and nutrient analysis was conducted. All physiological parameters decreased with the number of days of waterlogging. Flavonoid and anthocyanin index increased with increased duration of waterlogging. Photosynthesis and whole plant dry weight in continuously waterlogged conditions were 75% and 78% less compared to 0, and 2-day water-logged plants. Plant height, stem diameter, number of main stem leaves, leaf area, and leaf length also decreased with waterlogging duration. When waterlogging duration increased, leaf, stem, and root macronutrients decreased, while micronutrients showed mixed trends. Based on the experimental study, functional relationships (linear, quadratic, and exponential decay) and waterlogging stress response indices are developed between growth and development parameters and the duration of waterlogging. This can serve as a base for developing or improving process-based cotton models to simulate the impact of waterlogging.
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