ArticleHeliyon2025
Climatic drivers for assessment of false smut risk in rice ecosystems: A guide for planning effective management trials.
Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Ustiloxins as Emerging Contaminants in Rice Agroecosystems: Environmental Occurrence, Ecotoxicological Impacts, and Risk Implications-A Complete Review.Journal of basic microbiology · 2026Review
- Ustiloxins and Ustilaginoidins in the Sclerotia Generated from Rice False Smut Balls and Their Contents.Toxins · 2026Article
- False smut of rice: integrating molecular pathogenicity and epidemiology for next-generation disease management.Frontiers in fungal biology · 2026Review
- Comparative genomics of Eastern-IndianFrontiers in fungal biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emergence of false smut (RFS) in rice agroecosystems is causing significant yield losses due to its direct impact on grains. To assess the factors associated with host-pathogen interaction, maximum entropy principle is used to identify bioclimatic variables behind the geo-spatial distribution patterns of RFS. Bioclimatic variables with ecological significance, derived from the monthly temperature and precipitation, such as precipitation in the wettest month, mean temperature of the warmest quarter and precipitation seasonality are linked to the occurrence of the disease. These three variables are identified as the strongest predictors of RFS distribution contributing 47.81 %, 26.63 % and 12.43 % respectively. Seasonal precipitation and its variability have played as a limiting factor for the disease. Temperature plays a crucial role in pathogen growth and development (mycelial growth, sclerotial germination and infection) and exerts influences on disease distribution. Spatial distribution pattern of the disease and its intensity, as well as the number of sclerotia/panicle development, germination and infection suitability, suggest that temperature response and daily precipitation during the booting stage have a significant impact on disease development. Number of favourable days composed of temperature response [
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Registered trials
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