Abstract
Rice (Oryza sativa L.) is a major dietary source of arsenic (As) for humans. Understanding the mechanisms of As accumulation in rice is essential for mitigating human exposure. However, the effects of environmental factors on As accumulation in rice have been insufficiently quantified under field conditions. To address these issues, we modeled temporal dynamics of As accumulation in rice plants and grains using a Bayesian state–space model (SSM). In this SSM, As concentrations in flag leaves and rice grains were treated as response variables, whereas four environmental factors, i.e., number of flooding days, temperature, crop evapotranspiration and precipitation, served as explanatory variables. The nonlinear effects of physiological factors were also incorporated into the SSM. The results indicated that among the four environmental factors, flooding days exerted the greatest positive effect on As accumulation in rice plants, with the effect peaking 5–10 days after heading. High temperatures and increased crop evapotranspiration promoted As accumulation, whereas increased precipitation reduced As accumulation. This work is among the first studies to quantify the effects of environmental factors on As accumulation in rice under field conditions, and the findings contribute to the development of region-specific cultivation guidelines for mitigating As exposure through rice.
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Data availability
The dataset and analysis code that support the findings of this study are available from the corresponding author upon reasonable request.
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Acknowledgements
We are grateful to Dr. Ryoko Morioka, Dr. Takehiko Yamanaka, Dr. Tomohiko Takayama and Dr. Noriyuki Murakami from the Research Center for Agricultural Information Technology, NARO, and Dr. Sunao Itahashi and Dr. Yuji Maejima from the Institute for Agro-Environmental Sciences, NARO, for their support and helpful comments.
Funding
This study was conducted under the Regulatory Research Projects for Food Safety, Animal Health and Plant Protection (JPJ008617.18065121) funded by the Ministry of Agriculture, Forestry and Fisheries of Japan.
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KI: Conceptualization, Data curation, Formal analysis, Methodology, Writing-original draft; IA: Conceptualization, Data curation, Investigation, Methodology, Writing-review & editing; SK: Data curation, Formal analysis, Methodology, Writing-review & editing, Supervision; KB: Investigation, Resources, Writing-review & editing; NY: Writing-review & editing, Supervision; KO: Writing-review & editing; KN: Writing-review; SI: Writing-review & editing, Supervision.
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This study was conducted in accordance with all relevant institutional, national, and international guidelines and legislation. The rice plants used were common cultivated varieties grown in agricultural paddy fields, and no endangered or protected species were involved.
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Ishito, K., Akahane, I., Kishi, S. et al. Unraveling effects of environmental factors on arsenic accumulation in rice under field conditions using a Bayesian state space model.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-33897-5
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DOI: https://doi.org/10.1038/s41598-025-33897-5
Keywords
- Arsenic
- Rice
- Time series analysis
- State–space model
- Bayesian statistics
Source: Ecology - nature.com
