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Identifying exemplary sustainable cropping systems using a positive deviance approach: Wheat-maize double cropping in the North China Plain

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  • Liang, Zhengyuan
  • van der Werf, Wopke
  • Xu, Zhan
  • Cheng, Jiali
  • Wang, Chong
  • Cong, Wen-Feng
  • Zhang, Chaochun
  • Zhang, Fusuo
  • Groot, Jeroen C.J.

Abstract

Sustainable cropping systems need to balance productivity and profitability with resource and environmental conservation. Within a population of cropping system observations, there might be positive deviants that outperform others in terms of sustainability, which could serve as “model systems” for future development. Wheat-maize double cropping is the dominant system in the North China Plain, which is facing multiple economic, societal, and environmental sustainability challenges. Identifying exemplary positive deviants out of a multitude of wheat-maize observations might provide solutions to enhance overall sustainability.

Suggested Citation

  • Liang, Zhengyuan & van der Werf, Wopke & Xu, Zhan & Cheng, Jiali & Wang, Chong & Cong, Wen-Feng & Zhang, Chaochun & Zhang, Fusuo & Groot, Jeroen C.J., 2022. "Identifying exemplary sustainable cropping systems using a positive deviance approach: Wheat-maize double cropping in the North China Plain," Agricultural Systems, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:agisys:v:201:y:2022:i:c:s0308521x2200107x
    DOI: 10.1016/j.agsy.2022.103471
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    1. Moreira, Tatiana & Groot Koerkamp, Peter & Janssen, Arni & Stomph, Tjeerd-Jan & van der Werf, Wopke, 2023. "Breaking the mould: Developing innovative crop protection strategies with Reflexive Interactive Design," Agricultural Systems, Elsevier, vol. 210(C).
    2. Xingmei Xu & Lu Wang & Xuewen Liang & Lei Zhou & Youjia Chen & Puyu Feng & Helong Yu & Yuntao Ma, 2023. "Maize Seedling Leave Counting Based on Semi-Supervised Learning and UAV RGB Images," Sustainability, MDPI, vol. 15(12), pages 1-17, June.

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