Spatio-Temporal Pattern of Green Agricultural Science and Technology Progress: A Case Study in Yangtze River Delta of China

Int J Environ Res Public Health. 2022 Jul 17;19(14):8702. doi: 10.3390/ijerph19148702.

Abstract

Green agricultural science and technology progress (GASTP) plays an important role in the green transformation of agriculture. This study calculates the contribution rate of GASTP by using the Super-SBM model in the Yangtze River Delta (YRD) from 2011 to 2020. The exploratory spatial data analysis (ESDA) method and the Fixed Effect (FE) panel data model method were adopted to empirically analyze the spatio-temporal patterns of GASTP and its driving mechanism in the YRD. The results showed that: (i) except for Shanghai from 2011 to 2015, the contribution rate of GASTP in the YRD was generally lower than 1 in Anhui Province, Jiangsu Province, and Zhejiang Province, (ii) the level of GASTP had a positive spatial correlation with the study period, except for 2017, and (iii) per capita GDP, agricultural mechanization level, agricultural financial support, and planting structure are four influencing factors of GASTP in the YRD, while total retail sales of social consumer goods and total exports did not have significant effects on GASTP in the YRD. Therefore, we need to increase the opportunities to exchange GASTP experience between cities, improve the environment for agricultural technology extension, and develop follow-up monitoring mechanisms.

Keywords: Yangtze river delta; carbon emission; driving mechanism; food security; green agricultural science and technology progress.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • China
  • Cities
  • Environmental Monitoring*
  • Rivers*
  • Technology

Grants and funding

This research was supported by the Major Research Project of Humanities and Social Sciences in Colleges and Universities of Zhejiang Province (Grant No. 2021QN062), Zhejiang Soft Science Research Program of China (Grant No. 2022C35104), Research Development Fund of Zhejiang A&F University (Grant No. 2020FR066), the Zhejiang Provincial Natural Science Foundation of China (Grant No. Z22D010686), the National Natural Science Foundation of China (Grant No. 42071283), and the Special Project of Cultivating Leading Talents in Philosophy and Social Science of Zhejiang Province (Grant No. 21YJRC12-2YB and 21YJRC2ZD).