Abstract
Selenium constitutes an essential trace element for the human body. Moderate Se intake plays a pivotal role in preserving overall health. The absorption of Se by plants is primarily influenced by the available Se levels in soils, rather than by the soil total Se content, offering potential for exploring Se-rich crops in Se-deficient regions. In this study, we explore the factors influencing the Se bioaccumulation coefficient in corn based on a land quality geochemical survey at a 1:50,000 scale and establish predictive models for corn seed Se content using random forest and multiple linear regression approaches. The results indicate that the surface soil in the study area is deficient in Se (0.18–1.21 mg/kg), but 54% of the corn grain samples met the standards for Se-rich products (0.02–0.30 mg/kg). The factors influencing the Se biological enrichment coefficient in corn seeds are soil pH and CaO and MgO content, with impact levels of 0.54, 0.42, and 0.35, respectively. Compared to multiple linear regression models, the RF model provides more accurate and reliable predictions of corn Se content. The random forest model indicates that approximately 41% of the farmland within the study area is conducive to the cultivation of naturally Se-rich corn, which is a 26% increase in the planting area compared to recommendations based solely on soil Se content. In this research, we introduce an innovative methodological framework for organically cultivating naturally Se-rich corn within regions affected by Se deficiency.
Graphical abstract
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmad, A., Liu, Y., & Ge, Q. (2022). Assessing environmental thresholds in relation to plant structure and nutritional value for improved maize calendar ensuring food security. The Science of the Total Environment, 834, 155120.
Aqdam, K. K., Mahabadi, N. Y., Ramezanpour, H., Rezapour, S., Mosleh, Z., & Zare, E. (2022). Comparison of the uncertainty of soil organic carbon stocks in different land uses. Journal of Arid Environments, 205, 104805.
Chen, Y., Ma, T., Ke, R., Lu, M., An, J., Wang, Y., Huang, K., Luo, Y., Li, J. C., & Cheng, N. (2023). Rapid and user-friendly detection of selenium-rich foods using a THEATER colorimetric device with Pt–Co–N–C as viewing glasses. Chemical Engineering Journal, 472, 144787.
Chen, Z., Pei, J., Wei, Z., Ruan, X., Hua, Y., Xu, W., Zhang, C., Liu, T., & Guo, Y. (2021). A novel maize biochar-based compound fertilizer for immobilizing cadmium and improving soil quality and maize growth. Environmental Pollution, 277, 116455.
Chen, Z., Wu, Q., Han, S., Zhang, J., Yang, P., & Liu, X. (2022). A study on geological structure prediction based on random forest method. Artificial Intelligence in Geosciences, 3, 226–236.
Chilimba, A. D., Young, S. D., Black, C. R., Rogerson, K. B., Ander, E. L., Watts, M. J., Lammel, J., & Broadley, M. R. (2011). Maize grain and soil surveys reveal suboptimal dietary selenium intake is widespread in Malawi. Scientific Reports, 1, 72.
Dabba, A., Tari, A., Meftali, S., & Mokhtari, R. (2021). Gene selection and classification of microarray data method based on mutual information and moth flame algorithm. Expert Systems with Applications, 166, 114012.
Dhenge, R., Langialonga, P., Alinovi, M., Lolli, V., Aldini, A., & Rinaldi, M. (2022). Evaluation of quality parameters of orange juice stabilized by two thermal treatments (helical heat exchanger and ohmic heating) and non-thermal (high-pressure processing). Food Control, 141, 109150.
Dinh, Q. T., Cui, Z., Huang, J., Tran, T. A., Wang, D., Yang, W., Zhou, F., Wang, M., Yu, D., & Liang, D. (2018). Selenium distribution in the Chinese environment and its relationship with human health: A review. Environment International, 112, 294–309.
Faramarzi, S. E., Pazira, E., Masihabadi, M. H., Torkashvand, A. M., & Motamedvaziri, B. (2022). Modeling and estimating the spatial distribution of soil organic matter content in irrigated lands. International Journal of Environmental Science and Technology, 19, 7399–7410.
Fordyce, F. (2007). ‘Selenium geochemistry and health’, AMBIO. A Journal of the Human Environment, 36, 94–97.
Fu, C., He, Y., Yang, C., He, J., Sun, L., Pan, Y., Deng, L., Huang, R., Li, M., & Chang, K. (2023). Utilizing biochar to decorate nanoscale FeS for the highly effective decontamination of Se(IV) from simulated wastewater. Ecotoxicology and Environmental Safety, 263, 115285.
Gu, Q., Yang, Z., Yu, T., Ji, J., Hou, Q., & Zhang, Q. (2019). Application of ecogeochemical prediction model to safely exploit seleniferous soil. Ecotoxicology and Environmental Safety, 177, 133–139.
Guo, Q., Ye, J., Zeng, J., Chen, L., Korpelainen, H., & Li, C. (2023). Selenium species transforming along soil-plant continuum and their beneficial roles for horticultural crops. Horticulture Research, 10, uhac270.
Hartikainen, H. (2005). Biogeochemistry of selenium and its impact on food chain quality and human health. Journal of Trace Elements in Medicine and Biology, 18, 309–318.
Impellitteri, C. A., & Scheckel, K. G. (2006). The distribution, solid-phase speciation, and desorption/dissolution of as in waste iron-based drinking water treatment residuals. Chemosphere, 64, 7.
Jiang, T., Yu, T., Qi, H., Li, F., & Yang, Z. (2022). Analysis of phosphorus and sulfur effect on soil selenium bioavailability based on diffusive gradients in thin films technique and sequential extraction. Chemosphere, 302, 134831.
Joao, O. M., Andrea, M., Karen, W., Fraser Lee, A., Della Gaspera, E., & vanEmbden, J. (2023). Substrate morphology directs (001) Sb2Se3 thin film growth by crystallographic orientation filtering. Small (Small Weinheim an der Bergstrasse, Germany). https://doi.org/10.1002/smll.202302721
Kushwaha, A., Goswami, L., Lee, J., Sonne, C., Brown, R. J., & Kim, K. H. (2022). Selenium in soil-microbe-plant systems: Sources, distribution, toxicity, tolerance, and detoxification. Critical Reviews in Environmental Science and Technology, 52, 2383–2420.
Li, S., Long, B., Hu, J., & Jinggang, X. (2011). School of resources, environment, northeast agricultural University, Harbin, China 2 The university of Texas at El Paso, El Paso, Texas, and USA. 2011. Cmparison btween Fly Ash and Zeolite for Cu,Cd,Pb and Zn Passivation in Brewery Sludge Composting Process. pp. 430–33
Last, K. W., Cornelius, V., Delves, T., Sieniawska, C., Fitzgibbon, J., Norton, A., Amess, J., Wilson, A., Rohatiner, A. Z., & Lister, T. A. (2003). Presentation serum selenium predicts for overall survival, dose delivery, and first treatment response in aggressive non-Hodgkin’s lymphoma. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 21, 2335–2341.
Lee, S., & Soonho, S. (2020). A rapid compression machine study of hydrogen effects on the ignition delay times of n-butane at low-to-intermediate temperatures. Fuel, 266, 116895.
Lyu, C., Qin, Y., Chen, T., Zhao, Z., & Liu, X. (2021). Microbial induced carbonate precipitation contributes to the fates of Cd and Se in Cd-contaminated seleniferous soils. Journal of Hazardous Materials, 423, 126977.
Ma, X., Yang, Z., Yu, T., & Guan, D. X. (2022). Probability of cultivating Se-rich maize in Se-poor farmland based on intensive field sampling and artificial neural network modelling. Chemosphere, 309, 136690.
Mahar, A., Wang, P., Ali, A., Guo, Z., Awasthi, M. K., Lahori, A. H., Wang, Q., Shen, F., Li, R., & Zhang, Z. (2016). “Impact of CaO, fly ash, sulfur and Na2S on the (im)mobilization and phytoavailability of Cd Cu and Pb in contaminated soil.” Ecotoxicology and Environmental Safety, 134, 116–123.
Mohrazi, A., Ghasemi-Fasaei, R., Mojiri, A., & Shirazi, S. S. (2023). Investigating an electro-bio-chemical phytoremediation of multi-metal polluted soil by maize and sunflower using RSM-based optimization methodology. Environmental and Experimental Botany, 211, 105352.
Rácz, A., Fodor, M., & Héberger, K. (2018). Development and comparison of regression models for the determination of quality parameters in margarine spread samples using NIR spectroscopy. Analytical Methods, 10, 3089–3099.
Ran, J., Wang, D., Wang, C., Zhang, G., & Zhang, H. (2016). Heavy metal contents, distribution, and prediction in a regional soil–wheat system. Science of the Total Environment, 544(544), 422–431.
Sharma, S., Gupta, R., Bhatia, R., Toor, A. P., & Setia, H. (2021). Predicting microbial response to anthropogenic environmental disturbances using artificial neural network and multiple linear regression. International Journal of Cognitive Computing in Engineering., 2, 65–70.
Tan, L. C., Nancharaiah, Y. V., van Hullebusch, E. D., & Lens, P. N. (2016). Selenium: Environmental significance, pollution, and biological treatment technologies. Biotechnology Advances, 34, 9–71.
Wang, C., Ji, J., & Zhu, F. (2017). Characterizing Se transfer in the soil-crop systems under field condition. Plant and Soil, 415, 535–548.
Wang, J., Wang, Z., Mao, H., Zhao, H., & Huang, D. (2013). Increasing Se concentration in maize grain with soil: Or foliar-applied selenite on the Loess Plateau in China. Field Crops Research, 150, 83–90.
Wang, Y., Yu, T., Yang, Z., Bo, H., Lin, Y., Yang, Q., Liu, X., Zhang, Q., Zhuo, X., & Wu, T. (2021). Zinc concentration prediction in rice grain using back-propagation neural network based on soil properties and safe utilization of paddy soil: A large-scale field study in Guangxi, China. Science of the Total Environment, 798, 149270.
Wang, Y., Liu, H. Y., Wang, Z. J., Zhang, X. D., & Wang, D. H. (2022). Enrichment factors of soil-Se in the Farmland in Shizuishan City, Ningxia. Huan jing ke xue = Huanjing kexue, 43(8), 4179–4189.
Yadav, P., Singh, B., Garg, V. K., Mor, S., & Pulhani, V. (2016). Bioaccumulation and health risks of heavy metals associated with consumption of rice grains from croplands in northern India. Human and Ecological Risk Assessment: an International Journal, 23, 14–27.
Yang, W., Deng, M., Tang, J., & Luo, L. (2022). Geographically weighted regression with the integration of machine learning for spatial prediction. Journal of Geographical Systems, 25, 213–236.
Yu, D., Liang, D., Lei, L., Zhang, R., Sun, X., & Lin, Z. (2015). ‘Selenium geochemical distribution in the environment and predicted human daily dietary intake in northeastern QinghaiChina.’ Environmental Science and Pollution Research International, 22, 11224.
Zhang, M., Xing, G., Tang, S., Pang, Y., Yi, Q., Huang, Q., Huang, X., Huang, J., Li, P., & Fu, H. (2019). Improving soil selenium availability as a strategy to promote selenium uptake by high-Se rice cultivar. Environmental and Experimental Botany, 163, 45–54.
Funding
This work was supported by the Ministry of Natural Resources of China Geological Survey [Project Nos. DD20211576、DD20230480].
Author information
Authors and Affiliations
Contributions
JZ involved in formal analysis, writing—original draft, and funding acquisition; ZH involved in writing—original draft and formal analysis; CM involved in investigation and formal analysis; HG involved in formal analysis and investigation; LD involved in writing—original draft, formal analysis, and methodology; HZ involved in investigation and methodology; WW involved in formal analysis and investigation; WC involved in investigation and methodology; JL involved in conceptualization and supervision; SF involved in methodology and writing—review and editing.
Corresponding author
Ethics declarations
Conflict of interest
We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.
Ethical approval
Not applicable. This work did not describe experiments with animals, human subjects, or human tissue samples.
Consent to participate
Not applicable. This work did not describe experiments with animals, human subjects, or human tissue samples.
Consent to publish
The manuscript entitled, “Modeling the Feasibility of Se-rich Corn Cultivation in Se-Deficient Agricultural Fields Using Random Forest Algorithm” is prepared in accordance with the Guide for Authors available on the journal’s website, and it has not been published elsewhere in part or in its entirety. All authors attest to the validity of its contents and agree to its submission.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhang, J., Huo, Z., Mao, C. et al. Modeling the feasibility of Se-rich corn cultivation in Se-deficient agricultural fields using random forest algorithm. Environ Geochem Health 46, 46 (2024). https://doi.org/10.1007/s10653-023-01831-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10653-023-01831-1