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Nutrient management modulates acidification-induced risks to yield and cadmium contents in paddy rice

Nature Food volume 7, pages 272–282 (2026)Cite this article

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Abstract

Cropland acidification in China has decreased crop yields and accelerated cadmium accumulation in edible crops. Enhancing manure recycling effectively mitigates soil acidification but increases the risks for cadmium accumulation due to elevated cadmium contents in manure. Here we coupled a dynamic cadmium model with the soil acidification model VSD+ to assess the spatial-temporal impacts of nutrient management on soil acidification and cadmium dynamics in a typical Chinese paddy rice system. Enhancing manure recycling decreased soil acidification and almost completely reduced mineral phosphorus fertilizer use, but accelerated soil cadmium accumulation through increased manure cadmium inputs and reduced cadmium leaching. Raising soil pH without lowering cadmium inputs reduced rice cadmium contents in the short to medium term, but continued soil cadmium accumulation offset these benefits in the long term. Under current cadmium deposition levels, only around 20% of the manure can be safely recycled without exceeding cadmium safety thresholds, which is lower than the current manure recycling ratio of 30%. When cadmium deposition is minimized, the manure recycling ratio can increase up to 85%. To enhance manure recycling sustainably, a lowering of cadmium content in manure and cadmium deposition is required.

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Fig. 1: Schematic overview of the coupled cadmium mass balance and soil acidification model VSD+.
Fig. 2: Historical trends in cadmium inputs and outputs and soil cadmium in paddy soils.
Fig. 3: Effects of management scenarios on cadmium inputs and outputs in paddy soils.
Fig. 4: Impacts of management on soil pH and cadmium concentrations in soils and rice grain.
Fig. 5: Spatial variation in cadmium inputs by manure and deposition under different management scenarios for Qiyang County.
Fig. 6: Spatial variations in the required lime application rate under different management scenarios for Qiyang County.

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Data availability

The datasets supporting the findings of this study, including cadmium model inputs and outputs, scenario analysis and point-based observational data are available from Zenodo via https://doi.org/10.5281/zenodo.18152505 (ref. 58). The site-specific climate data (including mean annual temperature, mean annual precipitation and mean sunshine hours) used in this Article were obtained from the Climatic Research Unit of East Anglia University (https://crudata.uea.ac.uk/cru/data/hrg). The site-specific soil properties (comprising soil clay content, SOC and soil pH) in 1985 can be extracted from the Harmonized World Soil Data (https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/). Administrative boundary data obtained from the geoBoundaries project are publicly available from the geoBoundaries website (Open Data Commons Open Database License, ODbL). The land use dataset used to derive the paddy soil coverage was obtained from the Resource and Environment Science and Data Platform (Chinese Academy of Sciences, accessed in 2023). Other site-specific data were derived from farm surveys and soil sampling. The original farm survey data on site-specific crop yield and fertilization are subject to restrictions due to data-sharing agreements and are therefore not publicly available, but can be obtained from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

Data were structured and coded using Microsoft Excel. The soil acidification model VSD+ and the MetHyd model used in this study are publically available via https://www.umweltbundesamt.de/en/data-models. R (v.4.5.1) was used for regression models, cadmium dynamics simulation and scenario analysis, together with data analysis and visualization. We made use of R packages including sf (v.1.0-21), raster (v.3.6-32), stars (v.0.6-8) and gstat (v.2.1-4) for spatial analyses. Data manipulation and visualization were performed using dplyr (v.1.1.4), tidyr (v.1.3.1) and ggplot2 (v.3.5.2). The code used in this Article is from GitHub via https://github.com/xu624/cadmium-management.

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Acknowledgements

The research for this work was supported by the National Key Research and Development Program of China (2022YFD1900601), the China Scholarship Council (number 201913043) and Hainan University.

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Authors and Affiliations

  1. Wageningen University and Research, Earth Systems and Global Change Group, Wageningen, Netherlands

    Donghao Xu, Gerard H. Ros & Wim de Vries

  2. College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China

    Donghao Xu, Pengqi Liu, Qichao Zhu & Fusuo Zhang

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Contributions

W.d.V., Q.Z. and D.X. conceived and designed the study. D.X. and P.L. collected data and carried out fieldwork supervised by W.d.V., Q.Z., G.H.R. and F.Z. Figures were produced by D.X. with the help of G.H.R. The results were critically assessed and interpreted by D.X., W.d.V., Q.Z., G.H.R. and F.Z. The draft paper was written by D.X., G.H.R. and W.d.V. All authors revised and approved the paper.

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Correspondence to Donghao Xu or Qichao Zhu.

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Extended data

Extended Data Fig. 1 Model performance in predicting soil cadmium contents, organic carbon contents and pH.

(a) Point-by-point comparison between predicted and observed soil cadmium (Cd) contents (mg kg-1). (b), Point-by-point comparison between predicted and observed soil organic carbon (SOC) contents (%). (c) Point-by-point comparison between predicted and observed soil pH. All comparisons use data from 2014 and 2019. Note that the predictions for pH are limited to non-calcareous paddy rice since VSD+ assumes equilibrium dissolution of carbonates, leading to a fixed pH value near pH 7 in calcareous soils as long as carbonate is available, while observed pH values range from approximately 6 to 8.

Source data

Extended Data Fig. 2 Effects of soil properties on cadmium concentrations in soil solution under the business as usual (BAU) scenario.

(a) Relationship between cadmium concentrations in soil solution against soil pH. (b) Relationship between cadmium leaching rate and soil pH. Each point represents an individual plot in one year in the BAU scenario, with scatter reflecting variation in soil clay contents and soil organic carbon (SOC) contents.

Source data

Extended Data Fig. 3 Total and critical cadmium inputs across scenarios and sites.

Average values and ranges of the total cadmium inputs (fertilizer, manure, atmospheric deposition and irrigation) across different scenarios and the critical inputs for 56 paddy sites in calcareous and non-calcareous soils. Diamonds indicate mean current or critical cadmium inputs.

Source data

Extended Data Fig. 4 Scenario effects on manure recycling and cadmium deposition.

(a, c) Cumulative frequency distributions of manure input rates and average manure recycling ratios under different scenarios in non-calcareous (a) and calcareous soils (c). (b, d) Cumulative frequency distributions of cadmium (Cd) deposition rates and average cadmium deposition rate under different scenarios in non-calcareous (b) and calcareous soils (d). The manure recycling ratio in the BNPR scenario was assumed 100%; in other scenarios, this ratio was calculated based on the ratio of mean cadmium input by manure divided by that in BNPR scenario. Cadmium deposition in the BAU, BNP and BNPR scenarios were all similar.

Source data

Extended Data Fig. 5 Critical values for soil pH, total and dissolved cadmium across paddy sites.

(a) critical soil pH. (b) Critical total cadmium contents in soil (mg kg−1). (c) Critical cadmium concentration in soil solution (µg L−1). Boxplots show medians (black lines), interquartile ranges (25th–75th percentiles), and 90% ranges (5th–95th percentiles) across 56 paddy sites in Qiyang County. Red dots indicate means, diamonds denote observed means, and dots represent outliers.

Source data

Extended Data Fig. 6 Validation of model predictions for cadmium concentrations in crops and soil solution.

(a) Comparison between predicted and measured cadmium contents in crops for 109 paired crop–soil samples, including grain–soil (red) and straw–soil (blue) pairs in 109 paired crop–soil samples. (b) Comparison between predicted and measured cadmium concentrations in soil solution extracted with CaCl2 for 136 soils, including paddy soils (red) and upland soils (blue). Values are shown on a log10 scale. The red dashed line indicates the 1:1 relationship. Sites with estimated soil clay content based on the World Soil Grid dataset are indicated by hollow symbols (est_clay), whereas measured values are shown as filled symbols (mea_clay). Outliers were excluded from the regression analyses.

Source data

Extended Data Fig. 7 Spatial distribution of sampling and monitoring sites in Qiyang County, China.

(a) Location of Qiyang County in the Chinese mainland. (b) Distribution of 83 sampled paddy sites used for the relationships between cadmium in soil and in rice (grain and straw), including 32 sites without farm survey data (red) and 51 sites with survey data (black), together with 53 surveyed upland sites (green) used to analyse relationships between cadmium in soil, soil solution and plants. (c) Locations of sites used for monitoring cadmium concentrations in irrigation water and atmospheric deposition. Basemap in a from Natural Earth (public domain). Basemap administrative boundaries in b and c from the geoBoundaries project under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.

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Xu, D., Ros, G.H., Liu, P. et al. Nutrient management modulates acidification-induced risks to yield and cadmium contents in paddy rice. Nat Food 7, 272–282 (2026). https://doi.org/10.1038/s43016-026-01315-2

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