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The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China

Received: 24 June 2019     Accepted: 16 July 2019     Published: 7 October 2019
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Abstract

Food security has become an important part of the security of all countries in the world, especially in a populous country like China. This paper analyzes the impact of different influencing factors on food security in Yunnan Province, and establishes an appropriate evaluation index system to analyze and evaluate the food security of Yunnan Province under the changing environment of 2001-2016. Firstly, the principal factors analysis method is used to divide the factors affecting food security in Yunnan Province into three levels: natural conditions, social development and technology level, and agricultural management level. Secondly, the entropy weight method is combined with the OWA operator to obtain the Yunnan Province. The main influencing factors are the total power of agricultural machinery, the amount of agricultural chemical fertilizer and the proportion of the primary industry's output value to GDP. Finally, using the improved gray correlation TOPSIS model, the food security in Yunnan Province has basically shown a trend of volatility growth since 2001. The calculation results show that since 2001, food security in Yunnan Province has shown a growth trend, the grain production has been effectively secured in Yunnan Province. In its three criteria levels, social development and technological level and agricultural management levels are steadily increasing, except for natural condition is volatile. In the future, Yunnan Province should reduce its dependence on mechanical power and fertilizer in the grain production process, further expand the development of green agriculture and organic agriculture, and ensure food safety production in many aspects.

Published in International Journal of Food Science and Biotechnology (Volume 4, Issue 3)
DOI 10.11648/j.ijfsb.20190403.11
Page(s) 56-63
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Grain Security, Grey TOPSIS Model, Entropy and OWA Weight

References
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[3] Lu, Y., Jenkins, A., Ferrier, R. C., Bailey, M., Gordon, I. J., Song, S. & Feng, Z. (2015) Addressing China’s grand challenge of achieving grain security while ensuring environmental sustainability. Science advances, 1 (1), e1400039.
[4] Garnett, T. (2014) Three perspectives on sustainable grain security: efficiency, demand restraint, grain system transformation. What role for life cycle assessment? Journal of Cleaner Production, 73: 10-18.
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[7] Aggarwal, P. K., Thornton, P. K., Dunnett, A., Shirsath, P. B., Joshi, P. K., Pal, B. D., ... & Ghosh, J. (2018) Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions.
[8] Yi, F., Sun, D., & Zhou, Y. (2015) Grain subsidy, liquidity constraints and grain security—Impact of the grain subsidy program on the grain-sown areas in China. Grain policy, 50: 114-124.
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[10] Wu, J., Zhang, J., Wang, S., & Kong, F. (2016) Assessment of grain security in China: A new perspective based on production-consumption coordination. Sustainability, 8 (3): 183.
[11] Eicher-Miller, H. A., & Zhao, Y. (2018) Evidence for the age-specific relationship of grain insecurity and key dietary outcomes among US children and adolescents. Nutrition research reviews, 31 (1): 98-113.
[12] Wu Sen, Li Hujie, Chen Guohui, et al. (2016) Sensitivity analysis of regional landslide impact factors based on contribution rate weighting method. Chinese Journal of Geological Hazard and Control, pp26-31.
[13] Qiao Jianping, Shi Lili, Wang Meng. (2008) Landslide risk zoning based on overlapping weights of contributions. Geology, 27 (11): 1787-1794.
[14] Qiao Jianping, WANG Meng. (2011) Research on landslide hazard zoning with overlapping weights of contributions. Journal of Natural Disasters, 20 (2): 8-13.
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[16] Liu Yumin, Kang Qianqian, Wang Ning. (2016) Research on Airport Service Quality Evaluation Method Based on OWA Operator. Management Modernization, pp, 76-79.
[17] Jiang Junchao, Zhao Liangshi, Zheng Defeng. (2018) Analysis of Grain Security and Its Provincial Contribution in Mainland China from 1998 to 2016. Journal of Liaoning Normal University (Natural Science Edition), (41): 395-402.
[18] Dong Ying, Mu Yueying. (2014) Changes in China's Grain Production Efficiency and Its Influencing Factors——Analysis Based on Energy Perspective. Journal of Northwest A&F University (Social Science Edition), (6): 103-111.
[19] SHI Changliang, GUO Wei, ZHU Junfeng. (2016) Evaluation and Influencing Factors of Fertilizer Excessive Application in China's Grain Production. Journal of Agricultural Modernization Research, 37 (4): 671-679.
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  • APA Style

    Kun Tong, Chao Yang. (2019). The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China. International Journal of Food Science and Biotechnology, 4(3), 56-63. https://doi.org/10.11648/j.ijfsb.20190403.11

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    ACS Style

    Kun Tong; Chao Yang. The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China. Int. J. Food Sci. Biotechnol. 2019, 4(3), 56-63. doi: 10.11648/j.ijfsb.20190403.11

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    AMA Style

    Kun Tong, Chao Yang. The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China. Int J Food Sci Biotechnol. 2019;4(3):56-63. doi: 10.11648/j.ijfsb.20190403.11

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  • @article{10.11648/j.ijfsb.20190403.11,
      author = {Kun Tong and Chao Yang},
      title = {The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China},
      journal = {International Journal of Food Science and Biotechnology},
      volume = {4},
      number = {3},
      pages = {56-63},
      doi = {10.11648/j.ijfsb.20190403.11},
      url = {https://doi.org/10.11648/j.ijfsb.20190403.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijfsb.20190403.11},
      abstract = {Food security has become an important part of the security of all countries in the world, especially in a populous country like China. This paper analyzes the impact of different influencing factors on food security in Yunnan Province, and establishes an appropriate evaluation index system to analyze and evaluate the food security of Yunnan Province under the changing environment of 2001-2016. Firstly, the principal factors analysis method is used to divide the factors affecting food security in Yunnan Province into three levels: natural conditions, social development and technology level, and agricultural management level. Secondly, the entropy weight method is combined with the OWA operator to obtain the Yunnan Province. The main influencing factors are the total power of agricultural machinery, the amount of agricultural chemical fertilizer and the proportion of the primary industry's output value to GDP. Finally, using the improved gray correlation TOPSIS model, the food security in Yunnan Province has basically shown a trend of volatility growth since 2001. The calculation results show that since 2001, food security in Yunnan Province has shown a growth trend, the grain production has been effectively secured in Yunnan Province. In its three criteria levels, social development and technological level and agricultural management levels are steadily increasing, except for natural condition is volatile. In the future, Yunnan Province should reduce its dependence on mechanical power and fertilizer in the grain production process, further expand the development of green agriculture and organic agriculture, and ensure food safety production in many aspects.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China
    AU  - Kun Tong
    AU  - Chao Yang
    Y1  - 2019/10/07
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ijfsb.20190403.11
    DO  - 10.11648/j.ijfsb.20190403.11
    T2  - International Journal of Food Science and Biotechnology
    JF  - International Journal of Food Science and Biotechnology
    JO  - International Journal of Food Science and Biotechnology
    SP  - 56
    EP  - 63
    PB  - Science Publishing Group
    SN  - 2578-9643
    UR  - https://doi.org/10.11648/j.ijfsb.20190403.11
    AB  - Food security has become an important part of the security of all countries in the world, especially in a populous country like China. This paper analyzes the impact of different influencing factors on food security in Yunnan Province, and establishes an appropriate evaluation index system to analyze and evaluate the food security of Yunnan Province under the changing environment of 2001-2016. Firstly, the principal factors analysis method is used to divide the factors affecting food security in Yunnan Province into three levels: natural conditions, social development and technology level, and agricultural management level. Secondly, the entropy weight method is combined with the OWA operator to obtain the Yunnan Province. The main influencing factors are the total power of agricultural machinery, the amount of agricultural chemical fertilizer and the proportion of the primary industry's output value to GDP. Finally, using the improved gray correlation TOPSIS model, the food security in Yunnan Province has basically shown a trend of volatility growth since 2001. The calculation results show that since 2001, food security in Yunnan Province has shown a growth trend, the grain production has been effectively secured in Yunnan Province. In its three criteria levels, social development and technological level and agricultural management levels are steadily increasing, except for natural condition is volatile. In the future, Yunnan Province should reduce its dependence on mechanical power and fertilizer in the grain production process, further expand the development of green agriculture and organic agriculture, and ensure food safety production in many aspects.
    VL  - 4
    IS  - 3
    ER  - 

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Author Information
  • Key Laboratory of Watershed Geographic Science, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing, China

  • Nanjing Guohuan Science and Technology Co Ltd, Nanjing, China

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