Research on World Agricultural Economy

Resources Integration Theory and Gray Correlation Analysis: A Study for Evaluating China's Agri-food Systems Supply Capacity

Shaowen Yang

School of Business, Lingnan Normal University, Zhanjiang, 524048, China

Ping Wang

School of Sport Science, Lingnan Normal University, Zhanjiang, 524048, China

Zhaogang Fu

School of Business, Lingnan Normal University, Zhanjiang, 524048, China

DOI: https://doi.org/10.36956/rwae.v4i3.902

Received: 18 July 2023; Received in revised form: 24 August 2023; Accepted: 28 August 2023; Published: 6 September 2023

---

Abstract

China's agri-food systems face the challenge of ensuring food and grain security for a large population with limited resources. This paper constructs a resources integration theory, which classifies agricultural resources into six types and measures their correlation with food and grain supply capacity using grey correlation analysis. The results show that, during 2002-2020, among the factor resources, the highest correlation with food and grain was technology; among the related industry resources, the highest correlation with food was rural roads, and with grain was agricultural machinery; among the demand resources, the highest correlation was domestic market; among the six types of resources, the highest correlation was government resources; and the static correlation evaluation indices of agricultural resources with food and grain supply capacity were 0.8312 and 0.8090, respectively, indicating a compare match. Based on the results, this paper argues that the Chinese agri-food system is matched with agricultural resources, but still needs to be improved to achieve a high match. Opportunity resources, foreign investment, and international markets are disadvantageous resources because China has insufficient ability to stably utilize foreign resources. China’s proposal of a "big food view" is conducive to reducing dependence on factor resources, especially cultivated land and water resources.

Keywords: Agri-food systems, Supply capacity, Resources integration, Gray correlation, Matching degree

---

References

[1] Wang, J., Zhang, X., 2023. The big food view and human health from the prospect of bio-manufacturing and future food. Frontiers in Nutrition. 10, 1160743. DOI: https://doi.org/10.3389/fnut.2023.1160743

[2] Fan, S.G., Gao, H.X., Feng, X.L., 2022. Nong shi xi tong zhuan xing yu xiang cun zhen xing (Chinese) [Transformation of agri-food systems to boost rural revitalization]. Journal of South China Agricultural University (Social Science Edition). 21(1), 1-8.

[3] Tao, F., Yokozawa, M., Zhang, Z., et al., 2005. Remote sensing of crop production in China by production efficiency models: Models comparisons, estimates and uncertainties. Ecological Modelling. 183(4), 385-396. DOI: https://doi.org/10.1016/j.ecolmodel.2004.08.023

[4] Fang, Y., 2020. Changes in the food supply capacity of alpine grassland ecosystem: A dialectic synthesis of natural and anthropogenic drivers. Advances in Climate Change Research. 11(1), 1-10. DOI: https://doi.org/10.1016/j.accre.2020.05.006

[5] Colasanti, K.J.A., Hamm, M.W., 2010. Assessing the local food supply capacity of Detroit, Michigan. Journal of Agriculture, Food Systems, and Community Development. 1(2), 41-58. DOI: https://doi.org/10.5304/jafscd.2010.012.002

[6] Dai, L.W., Tang, H.P., Zhang, Q., et al., 2020. Bei fang nong mu jiao cuo dai duo lun xian sheng tai xi tong fu wu quan heng yu xie tong guan xi yan jiu (Chinese) [The trade-off and synergistic relationship among ecosystem services: A case study in Duolun County, the agropastoral ecotone of Northern China]. Acta Ecologica Sinica. 40(9), 2863-2876.

[7] Wang, Q., Yue, T.X., Lu, Y.M., et al., 2010. Zhong guo shi wu gong gei neng li fen xi (Chinese) [An analysis of the capacity of China’s food provision]. Acta Geographica Sinica. 65(10), 1229-1240.

[8] Feng, Z., Yang, Y., Zhang, J., 2008. The land carrying capacity of China based on man-grain relationship. Journal of Natural Resources. 23(5), 865-875. DOI: https://doi.org/10.11849/zrzyxb.2008.05.014

[9] Yin, P.H., Fang, X.Q., 2008. Zhong guo liang shi an quan cui ruo qu de shi bie ji kong jian fen yi te zheng (Chinese) [Assessment on vulnerable regions of food security in China]. Acta Geographica Sinica. 63(10), 1064-1072.

[10] Ji, X., Liu, L., Qi, X., 2014. Risk assessment method of grain production guarantee capacity of regional cultivated land. Transactions of the Chinese Society of Agricultural Engineering. 30(7), 219-226.

[11] Wang W., Yan H., Yang Y., et al., 2019. Evaluation of land resources carrying capacity of Tibetan counties based on dietary nutritional demand. Journal of Natural Resources. 34(5), 921-933. DOI: https://doi.org/10.31497/zrzyxb.20190502

[12] D’Angelo, C., Gloinson, E.R., Draper, A., et al., 2020. Food Consumption in the UK: Trends, Attitudes and Drivers [Internet]. RAND Corporation. Available from: https://www.rand.org/pubs/research_reports/RR4379.html

[13] Adhikari, B., Prapaspongsa, T., 2019. Environmental sustainability of food consumption in Asia. Sustainability. 11(20), 5749. DOI: https://doi.org/10.3390/su11205749

[14] Chaudhary, A., Gustafson, D., Mathys, A., 2018. Multi-indicator sustainability assessment of global food systems. Nature Communications. 9(1), 848. DOI: https://doi.org/10.1038/s41467-018-03308-7

[15] Pedersen, E., Remmen, A., 2022. Challenges with product environmental footprint: A systematic review. International Journal of Life Cycle Assessment. 27, 342-352. DOI: https://doi.org/10.1007/s11367-022-02022-3

[16] Esculier, F., Le Noë, J., Barles, S., et al., 2019. The biogeochemical imprint of human metabolism in Paris Megacity: A regionalized analysis of a water-agro-food system. Journal of Hydrology. 573, 1028-1045. DOI: https://doi.org/10.1016/j.jhydrol.2019.04.029

[17] Wang, H.G., 2023. Basic conclusions on global food security. China’s food security. Palgrave Macmillan: Singapore. DOI: https://doi.org/10.1007/978-981-99-0730-4_11

[18] Porter, M.E., 1998. Competitive advantage of nations. Free Press: New York. pp. 102-172.

[19] Patil, A., Walke Gaurish, A., Mahesh, G., 2019. Grey relation analysis methodology and its application. Research Review International Journal of Multidisciplinary. 4, 409-411. DOI: https://doi.org/10.5281/zenodo.2578088

[20] Wang, L., Yin, K., Cao, Y., et al., 2019. A new grey relational analysis model based on the characteristic of inscribed core (IC-GRA) and its application on seven-pilot carbon trading markets of China. International Journal of Environmental Research and Public Health. 16(1), 99. DOI: https://doi.org/10.3390/ijerph16010099

[21] Sun, J.S., Wang, Q.Z., 2012. Cheng xiang shou ru cha ju shi du xing ce du yan jiu—yi zhe jiang sheng wei li (Chinese) [Measurement of urban-rural income gap moderately—A case study of Zhejiang Province]. Journal of Agrotechnical Economics. 8, 72-80. DOI: https://doi.org/10.13246/j.cnki.jae.2012.08.011

[22] Chen, Y.Y., 2022. Wo guo liang shi sheng chan he bao zhang neng li qian jing fen xi (Chinese) [Analysis on the prospect of grain production and security capability in China]. Journal of Green Science and Technology. 24(1), 268-271+276. DOI: https://doi.org/10.16663/j.cnki.lskj.2022.04.001

[23] Feng, Z., Sun, T., Yang Y.Z., 2016. Study on the Spatiotemporal Patterns and Contribution Factors of China’s Grain Output Increase during 2003-2013. Journal of Natural Resources. 31(6), 895-907. DOI: https://doi.org/10.11849/zrzyxb.20151220

[24] Feng, Q., Bi, Z.F., Liu, J., 2022. Spatial and temporal evolution of water footprints of main crops in Huaihe River Basin and analysis of influencing factors. Journal of Water Resources and Water Engineering. 33(6), 213-219. Available from: http://szyysgcxb.alljournals.ac.cn/szyysgcxben/ch/reader/view_abstract.aspx?flag=1&file_no=20220627&journal_id=szyysgcxb

[25] Lv, M.K., Zhang, L.J., Qin, Y.C., et al., 2021. 1987-2016 nian zhong guo liang shi mao yi shi kong ge ju yan bian ji mao yi jie gou an quan xing ping gu (Chinese) [Spatiotemporal pattern of Chinese food trade and structural security assessment, 1987-2016]. Resources Science. 43(4), 838-848.

[26] Zhang, X.B., Yan, B., Jiang, M.L., et al., 2019. Zhong guo liang ji qi ye “zou chu qu” mian lin de wen ti yu zheng ce jian yi (Chinese) [Problems and policy recommendations of Chinese grain machinery manufacturing “going global”]. World Agriculture. (4), 83-88+99.

[27] Shao, L., Sheng, Y., 2011. Review of Chinese food security issue. Agricultural Economics and Management. 3, 17-25. DOI: https://doi.org/10.3969/j.issn.1674-9189.2011.03.003

[28] Li, D.L., Jiao, D., Li, C.D., 2022. Ru shi 20 nian yu zhong guo nong ye mao yi fa zhan bian qian (Chinese) [The development and changes of China’s agricultural trade after entry into WTO 20 years]. World Agriculture. (6), 31-46.

[29] Yang, S., Xiong, Q., 2015. Measuring the China’s agricultural openness ratio and comparing with other countries:1991～2011. Rural Economy. 3, 13-17. Available from: https://d.wanfangdata.com.cn/periodical/ncjj201503003

[30] Zhu, J., Li, T.X., Lin, D.Y., 2018. Kai fang jin cheng zhong de zhong guo nong chan pin mao yi: Fa zhan li cheng, wen ti tiao zhan yu zheng ce xuan ze (Chinese) [China’s agricultural trade in economic opening-up: Development challenges, and future policy alternatives]. Issues in Agricultural Economy. (12), 19-32.

[31] McGreevy, S.R., Rupprecht, C.D., Niles, D., et al., 2022. Sustainable agrifood systems for a post-growth world. Nature Sustainability. 5(12), 1011-1017. DOI: https://doi.org/10.1038/s41893-022-00933-5

[32] Zhi, Y.L., Wang, H.M., Zhang, F., et al., 2022. Xi bei di qu shui zi yuan, neng yuan he liang shi xi tong xie tong guan xi ping gu—Ji yu fu za xi tong xie tong jin hua shi jiao (Chinese) [Assessment on the synergy of water-energy-food system in the Northwest China—Based on the complex system co-evolution theory]. Journal of Arid Land Resources and Environment. 36(1), 76-85.