ArticleScientific reports2019
Accounting for soil moisture improves prediction of flowering time in chickpea and wheat.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Growth and yield responses of sorghum (Sorghum bicolor [L.] Moench) varieties to sowing time in a rainforest zone of Nigeria.Scientific reports · 2025Article
- Multi-modal few-shot learning for anthesis prediction of individual wheat plants.Plant phenomics (Washington, D.C.) · 2025Article
- Linking phenology, harvest index, and genetics to improve chickpea grain yield.Journal of experimental botany · 2025Article
- An innovative natural speed breeding technique for accelerated chickpea (Cicer arietinum L.) generation turnover.Plant methods · 2024Article
- The reduced growth due to elevated COFrontiers in plant science · 2024Article
- Crop/Plant Modeling Supports Plant Breeding: I. Optimization of Environmental Factors in Accelerating Crop Growth and Development for Speed Breeding.Plant phenomics (Washington, D.C.) · 2023Review
- Whole farm planning raises profit despite burgeoning climate crisis.Scientific reports · 2022Article
- Relationships of frequencies of extreme low temperatures with grain yield of some Australian commercial chickpea cultivars.International journal of biometeorology · 2022Article
- Is timing of reproduction according to temperature sums an optimal strategy?Ecology and evolution · 2019Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Matching crop phenology to environment is essential to improve yield and reduce risk of losses due to extreme temperatures, hence the importance of accurate prediction of flowering time. Empirical evidence suggests that soil water can influence flowering time in chickpea and wheat, but simulation models rarely account for this effect. Adjusting daily thermal time accumulation with fractional available soil water in the 0-60 cm soil layer improved the prediction of flowering time for both chickpea and wheat in comparison to the model simulating flowering time with only temperature and photoperiod. The number of post-flowering frost events accounted for 24% of the variation in observed chickpea yield using a temperature-photoperiod model, and 66% of the variation in yield with a model accounting for top-soil water content. Integrating the effect of soil water content in crop simulation models could improve prediction of flowering time and abiotic stress risk assessment.
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