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Producing more grain with lower environmental costs

Nature volume 514, pages 486–489 (2014)Cite this article

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Abstract

Agriculture faces great challenges to ensure global food security by increasing yields while reducing environmental costs1,2. Here we address this challenge by conducting a total of 153 site-year field experiments covering the main agro-ecological areas for rice, wheat and maize production in China. A set of integrated soil–crop system management practices based on a modern understanding of crop ecophysiology and soil biogeochemistry increases average yields for rice, wheat and maize from 7.2 million grams per hectare (Mg ha−1), 7.2 Mg ha−1 and 10.5 Mg ha−1 to 8.5 Mg ha−1, 8.9 Mg ha−1 and 14.2 Mg ha−1, respectively, without any increase in nitrogen fertilizer. Model simulation and life-cycle assessment3 show that reactive nitrogen losses and greenhouse gas emissions are reduced substantially by integrated soil–crop system management. If farmers in China could achieve average grain yields equivalent to 80% of this treatment by 2030, over the same planting area as in 2012, total production of rice, wheat and maize in China would be more than enough to meet the demand for direct human consumption and a substantially increased demand for animal feed, while decreasing the environmental costs of intensive agriculture.

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Figure 1: Reactive nitrogen losses and GHG emissions for four management treatments, based on empirical models of losses and life-cycle assessment.
Figure 2: Substantially increased yields can be produced with lower inputs of nitrogen fertilizer, and so lower human and environmental costs.
Figure 3: The projected demand of grain production for 2030 in China.

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References

  1. Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011)

    Article  ADS  CAS  Google Scholar 

  2. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011)

    Article  ADS  CAS  Google Scholar 

  3. Audsley, E. et al. Harmonisation of Environmental Life Cycle Assessment for Agriculture. Final Report. Concerted Action MR3-CT94-2028 (Silsoe Research Institute, 1997)

  4. Alston, J. M., Beddow, J. M. & Pardey, P. G. Agricultural research, productivity, and food prices in the long run. Science 325, 1209–1210 (2009)

    Article  CAS  Google Scholar 

  5. Grassini, P., Eskridge, K. M. & Cassman, K. G. Distinguishing between yield advances and yield plateaus in historical crop production trends. Nat. Commun. 4, 2918–2928 (2013)

    Article  ADS  Google Scholar 

  6. Ray, D. K., Mueller, N. D., West, P. C. & Foley, J. A. Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8, e66428 (2013)

    Article  ADS  CAS  Google Scholar 

  7. Ray, D. K. et al. Recent patterns of crop yield growth and stagnation. Nat. Commun. 3, 1293–1299 (2012)

    Article  ADS  Google Scholar 

  8. Davidson, E. A. The contribution of manure and fertilizer nitrogen to atmospheric nitrous oxide since 1860. Nat. Geosci. 2, 659–662 (2009)

    Article  ADS  CAS  Google Scholar 

  9. Christopher, M. C. & Tilman, D. Loss of plant species after chronic low-level nitrogen deposition to prairie grasslands. Nature 451, 712–715 (2008)

    Article  ADS  Google Scholar 

  10. Diaz, R. J. & Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science 321, 926–929 (2008)

    Article  ADS  CAS  Google Scholar 

  11. Guo, J. H. et al. Significant acidification in major Chinese croplands. Science 327, 1008–1010 (2010)

    Article  ADS  CAS  Google Scholar 

  12. Statistics Division of the Food and Agriculture Organization of the United Nations Agriculture database. FAOSTAT http://faostat3.fao.org/faostat-gateway/go/to/home/E (29 July 2014)

  13. Cassman, K. G., Dobermann, A. & Walters, D. T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. Ambio 31, 132–140 (2002)

    Article  Google Scholar 

  14. Zhang, F. S., Chen, X. P. & Vitousek, P. Chinese agriculture: an experiment for the world. Nature 497, 33–35 (2013)

    Article  ADS  CAS  Google Scholar 

  15. Chen, X. P. et al. Integrated soil–crop system management for food security. Proc. Natl Acad. Sci. USA 108, 6399–6404 (2011)

    Article  ADS  CAS  Google Scholar 

  16. Wart, J., Grassini, P. & Cassman, K. G. Impact of derived global weather data on simulated crop yields. Glob. Change Biol. 19, 3822–3834 (2013)

    Article  ADS  Google Scholar 

  17. Tilman, D. et al. Forecasting agriculturally driven global environmental change. Science 292, 281–284 (2001)

    Article  ADS  CAS  Google Scholar 

  18. Dobermann, A. in IFA Int. Workshop on Enhanced-Efficiency Fertilizers, 28–30 June 2005, Frankfurt, Germany (International Fertilizer Industry Association, 2005)

    Google Scholar 

  19. Cui, Z. L. et al. Closing the yield gap could reduce projected greenhouse gas emissions: a case study of maize production in China. Glob. Change Biol. 19, 2467–2477 (2013)

    Article  ADS  Google Scholar 

  20. Grassini, P. & Cassman, K. G. High-yield maize with large net energy yield and small global warming intensity. Proc. Natl Acad. Sci. USA 109, 1074–1079 (2012)

    Article  ADS  CAS  Google Scholar 

  21. Zhang, W. F. et al. New technologies reduce greenhouse gas emissions from nitrogenous fertilizer in China. Proc. Natl Acad. Sci. USA 110, 8375–8380 (2013)

    Article  ADS  CAS  Google Scholar 

  22. Chien, S. H., Prochnow, L. I. & Cantarella, H. Recent developments of fertilizer production and use to improve nutrient efficiency and minimize environmental impacts. Adv. Agron. 102, 267–322 (2009)

    Article  CAS  Google Scholar 

  23. National Bureau of Statistics of China. China Statistical Yearbook (China Statistics, 2013)

  24. Zwart, S. J. & Bastiaanssen, G. M. Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize. Agric. Water Manage. 69, 115–133 (2004)

    Article  Google Scholar 

  25. Ma, L. et al. Environmental assessment of management options for nutrient flows in the food chain in China. Environ. Sci. Technol. 47, 7260–7268 (2013)

    Article  ADS  CAS  Google Scholar 

  26. Chen, X. P. et al. Synchronizing N supply from soil and fertilizer and N demand of winter wheat by an improved Nmin method. Nutr. Cycl. Agroecosyst. 74, 91–98 (2006)

    Article  Google Scholar 

  27. Denmead, O. T. in Gaseous Loss of Nitrogen from Plant-Soil Systems (eds Freney, J. R. & Simpson, J. R. ) 133–157 (Martinus Nijhoff, 1983)

    Book  Google Scholar 

  28. Braschkat, J., Mannheim, T., Horlacher, D. & Marschner, H. Measurement of ammonia emissions after liquid manure application: I. Construction of a wind tunnel system for measurements under field conditions. Z. Pflanz. Bodenkunde 156, 393–396 (1993)

    Article  CAS  Google Scholar 

  29. Holland, E. et al. in Standard Soil Methods for Long-Term Ecological Research (eds Robertson, G. P., Coleman, D. C., Bledsoe, C. S. & Sollins, P. ) 185–201 (Oxford Univ. Press, 1999)

  30. Lehmann, J. & Schroth, G. in Trees, Crops and Soil Fertility: Concepts and Research Methods (eds Schroth, G. & Sinclair, F. L. ) 151–166 (CAB International, 2003)

    Google Scholar 

  31. Zhao, R., Chen, X. & Zhang, F. Nitrogen cycling and balance in winter wheat/summer maize rotation system in Northern China [in Chinese]. Acta Pedol. Sin. 46, 684–697 (2009)

    Google Scholar 

  32. Grassini, P. & Cassman, K. G. High-yield maize with large net energy yield and small global warming intensity. Proc. Natl Acad. Sci. USA 109, 1074–1079 (2012)

    Article  ADS  CAS  Google Scholar 

  33. Hou, P. et al. Grain yields in relation to N requirement: optimizing nitrogen management for spring maize grown in China. Field Crops Res. 129, 1–6 (2012)

    Article  Google Scholar 

  34. Yue, S. C. et al. Change in nitrogen requirement with increasing grain yield for winter wheat. Agron. J. 104, 1–7 (2012)

    Article  ADS  Google Scholar 

  35. Intergovernmental Panel on Climate Change in 2006 IPCC Guidelines for National Greenhouse Gas Inventories 11.1–11.54. (National Greenhouse Gas Inventories, 2006)

  36. Feng, J. F. et al. Impacts of cropping practice on yield-scale greenhouse gas emission from rice fields in China: a meta-analysis. Agric. Water Manage. 164, 220–228 (2013)

    Google Scholar 

  37. Smith, P. et al. in Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Metz, B. et al.) 497–540 (Cambridge Univ. Press, 2007)

  38. SAS Institute. SAS User’s Guide: Statistics. (SAS Institute, 1998)

  39. National Bureau of Statistics of China. Chinese Statistical Yearbook 2013. (China Statistics, 2013)

  40. National Bureau of Statistics of China. Nongken Agriculture Yearbook. (China Statistics, 2013)

Download references

Acknowledgements

We thank P. A. Matson, G. P. Robertson, I. Ortiz-Monasterio and G. Maltais-Landry for their comments on an earlier version of the manuscript or assistance during the manuscript revision, and we thank C. L. Kou, D. S. Tan, Z. M. Wang, Z. A. Lin, X. Y. Zhang, J. L. Gao and Y. Zhu for joining field experiments. We also acknowledge all those who provided local assistance or technical help to the Integrated Nutrient Management Network in China. This work was financially supported by the Chinese National Basic Research Program (2009CB118600), the Innovative Group Grant from the NSFC (31121062) and the Special Fund for Agro-scientific Research in the Public Interest (201103003).

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Author notes

  1. Xinping Chen and Zhenling Cui: These authors contributed equally to this work.

Authors and Affiliations

  1. College of Resources & Environmental Sciences, China Agricultural University, Beijing, 100193, China

    Xinping Chen, Zhenling Cui, Mingsheng Fan, Guiliang Wang, Liang Wu, Ning An, Liangquan Wu, Lin Ma, Weifeng Zhang & Fusuo Zhang

  2. Department of Biology, Stanford University, Stanford, 94305, California, USA

    Peter Vitousek

  3. Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China

    Ming Zhao & Weijian Zhang

  4. College of Resources & Environmental Sciences, Agricultural University of Hebei, Baoding, 071001, China

    Wenqi Ma

  5. College of Agronomy, Shandong Agricultural University, Tai’an, 271000, China

    Zhenlin Wang, Jiwang Zhang & Mingrong He

  6. Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China

    Xiaoyuan Yan

  7. Key Laboratory of Crop Genetics and Physiology of Jiangsu Province, Yangzhou University, Yangzhou, 225009, China

    Jianchang Yang

  8. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest Agriculture and Forestry University, Yangling, 712100, China

    Xiping Deng & Shiqing Li

  9. College of Resources & Environmental Sciences, Jilin Agricultural University, Changchun, 130118, China

    Qiang Gao

  10. Institute of Agricultural Environment and Resource, Shanxi Academy of Agricultural Sciences, Taiyuan, 030031, China

    Qiang Zhang

  11. College of Resources & Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095, China

    Shiwei Guo

  12. Research Center of Agricultural Environment & Resources, Jilin Academy of Agricultural Sciences, Changchun, 130033, China

    Jun Ren

  13. College of Resources & Environmental Sciences, Henan Agricultural University, Zhengzhou, 450000, China

    Youliang Ye & Yunji Zhu

  14. Northwest Agriculture and Forestry University, Yangling, 712100, China

    Zhaohui Wang & Jiquan Xue

  15. College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, China

    Jianliang Huang

  16. Crop Physiology, Ecology & Production Center, Hunan Agricultural University, Changsha, 410128, China

    Qiyuan Tang

  17. Soil & Fertilizer Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China

    Yixiang Sun

  18. College of Resources & Environmental Sciences, Northeast Agricultural University, Harbin, 150030, China

    Xianlong Peng

Authors
  1. Xinping Chen
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  2. Zhenling Cui
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  3. Mingsheng Fan
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  4. Peter Vitousek
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  5. Ming Zhao
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  31. Lin Ma
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  33. Fusuo Zhang
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Contributions

X.C. and F.Z. designed the research. Z.C., Z.W., M.Z., W.M., W.Z., X.Y., J.Y., X.D., Q.G., Q.Z., S.G., J.R., S.L., Y.Y., Z.W., J.H., Q.T., Y.S., X.P., J.Z., M.H., Y.Z. and J.X. conducted field experiments. Z.C., M.F., G.W., L.W., N.A., L.W., L.M. and W.Z. collected the data sets and analysed the data. X.C., Z.C. and P.V. wrote the manuscript.

Corresponding author

Correspondence to Fusuo Zhang.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 The distribution of experiments for grain from 2009 to 2012 in China.

a, Rice (n = 57); b, wheat (n = 40); c, maize (n = 56). The background green colour represents the planting area for each crop; darker green means a larger density of planting area regionally for that crop. The dots represent sites, and each colour in a dot represents a year of measurements.

Extended Data Figure 2 Linear models of NH3 volatilization based on nitrogen application rate.

Rate of nitrogen fertilizer application was plotted against NH3-N volatilization for (a) rice (n = 265) (Supplementary Information, extended references 1–36 for rice), (b) wheat (n = 34) and (c) maize (n = 29) (Supplementary Information, extended references 37–60 for wheat and maize) growing seasons, respectively. **P = 0.01. Filled and hollow circles represent data from Chinese journals (or theses) and ISI journals, respectively.

Extended Data Figure 3 Exponential models of N2O emissions and nitrogen leaching based on nitrogen surplus.

Nitrogen surplus was plotted against N2O-N emissions for (a) rice (n = 118) (Supplementary information, extended references 7, 36, 61–84 for rice), (b) wheat (n = 40) and (c) maize (n = 48) growing seasons (Supplementary information, extended references 85–99 for wheat and maize), and against nitrogen leaching for (d) rice (n = 52) (Supplementary information, extended references 7, 100–113 for rice), (e) wheat (n = 59) and (f) maize (n = 56) (Supplementary information, extended references 44, 114–121 for wheat and maize). Nitrogen surplus was defined as nitrogen application rate minus above-ground nitrogen uptake. **Regression significant at P < 0.01. Solid and hollow circles represent data from Chinese journals (or theses) and ISI journals, respectively.

Extended Data Figure 4 Exponential model of nitrogen runoff based on nitrogen surplus for rice production.

Nitrogen surplus was defined as nitrogen application rate minus above-ground nitrogen uptake (n = 81) (Supplementary information, extended references 8, 104, 122–134). **P < 0.01. Solid and hollow circles represent data from Chinese journals (or theses) and ISI journals, respectively.

Extended Data Figure 5 Rice yields over time in smallholder and large-scale farms in Heilongjiang province from 1982 to 2011.

Large-scale farms were around 20 ha; smallholder farms were less than 2 ha. Data from refs 39, 40.

Extended Data Table 1 Grain yields, nitrogen application rates, calculated PFPN, nitrogen surplus, the total and the intensity of reactive nitrogen losses and GHG emissions in farmers’ fields for rice (n = 6,592), wheat (n = 6,940) and maize (n = 5,406) in China
Full size table
Extended Data Table 2 Above-ground biomass, harvest index (HI) and crop nitrogen uptake for rice (n = 57), wheat (n = 40) and maize (n = 56) in field experiments with four management treatments
Full size table
Extended Data Table 3 Yield and nitrogen rates of farmer average, top farmers and ISSM
Full size table
Extended Data Table 4 Total production, weighted average of grain yield and nitrogen rate, total land use, nitrogen fertilizer use, reactive nitrogen losses, and GHG emissions in 2005, 2012 and projected in 2030 under three scenarios for all three crops (rice, wheat and maize) in China
Full size table

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Supplementary information

Supplementary Information

This file contains an extended reference list for establishing the reactive N loss models, Supplementary Table 1, a Supplementary Discussion and additional references. (PDF 684 kb)

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Chen, X., Cui, Z., Fan, M. et al. Producing more grain with lower environmental costs. Nature 514, 486–489 (2014). https://doi.org/10.1038/nature13609

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