Journal of Integrative Agriculture ›› 2021, Vol. 20 ›› Issue (2): 460-469.DOI: 10.1016/S2095-3119(20)63384-6

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  • 收稿日期:2020-04-20 出版日期:2021-02-01 发布日期:2021-01-28

A new feasible method for yield gap analysis in regions dominanted by smallholder farmers, with a case study of Jiangsu Province, China

SHAO Jing-jing1, ZHAO Wen-qing1, 2, ZHOU Zhi-guo1, 2, DU Kang1, KONG Ling-jie3, WANG You-hua1, 2   

  1. 1 Key Laboratory of Crop Eco-physiology and Management, Ministry of Agriculture and Rural Affairs/Agronomy College, Nanjing Agricultural University, Nanjing 210095, P.R.China 
    2 Jiangsu Collaborative Innovation Center for Modern Crop Production (JCIC-MCP), Nanjing Agricultural University, Nanjing 210095, P.R.China 
    3 Food Crop Research Institute, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, P.R.China
  • Received:2020-04-20 Online:2021-02-01 Published:2021-01-28
  • Contact: WANG You-hua, Tel: +86-25-84396397, E-mail: w_youhua@njau.edu.cn
  • Supported by:
    This work was funded by the National Key Research and Development Program of China (2016YFD0300109).

Abstract: In the regions where crops were mostly produced by smallholder farmers, the analysis of yield gap is difficult due to diverse cultivars, crop managements and yield levels. In order to find an effective method that can reasonably verify the yield gap and the limiting cultivation factors in narrowing yield gaps in areas that are dominanted by smallholder farmers, we worked out a method consisting five progressive procedures as follows: questionnaire investigation of farmer cultivation regime, identification of yield levels and yield gaps, generalization of key cultivation measurements, reconstruction of representative maize populations, and process-based analysis of yield gap. A case study was carried out in Jiangsu Province, China, in which maize is mostly produced by smallholder farmers. A questionnaire investigation of 1 023 smallholder farmers was carried out firstly, then the frequency distribution of maize yield was simulated by an normal distribution function, and then the covering range and average value of the basic yield, farmer yield and high-yield farmer yield levels were calculated out from the equation. Hereby, the yield gaps 1, 2 and 3 were calculated along with the record highest yield from literature and experts, which were 2 564, 2 346 and 2 073 kg ha–1, respectively. Moreover, with the covering range of each yield level, the suveyed farmers belonging to each yield level were grouped together and then their major cultivation measures were traced and generalized. With the generalized cultivation measures, representative maize populations of the four yield levels were reconstructed, and thereby clarifing lots of characters of the populations or single plant of each population with process-based analysis of the reconstructed populations. In this case, the main factors causing the yield gap were plant density, fertilizer application rate, logging caused by hurricane, and damages caused by pests. The case study primarily indicated that this five-step method is feasible and effective in yield gap study, especially in smallholder farmers dominant regions.

Key words: Jiangsu Province , maize, production investigation , yield level , yield gap