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The battle of crops: unveiling the shift from grain to non-grain use of farmland in China?
- Source :
- International Journal of Agricultural Sustainability; 2023, Vol. 21 Issue 1, p1-18, 18p
- Publication Year :
- 2023
-
Abstract
- China is issuing a warning regarding the 'unprecedented' hurdles it faces in safeguarding its food security. The substantial conversion of farmland for non-grain cultivation is exacerbating the situation, necessitating urgent investigation into the underlying causes. Nonetheless, previous studies have revealed a dearth of village-level analysis and have been marred by a bias stemming from econometric methodologies. To remedy this, the present paper employs a sophisticated approach combining econometric modelling and machine learning techniques to unravel the intricate driving forces at the village level. The study yields three principal findings. Firstly, the availability of farmland, poverty incidence, and the age of village leaders exert a detrimental influence on non-grain use of farmland (NGUF). Secondly, a conglomerate of factors, such as the aging rural workforce, income levels, positively impact the planting of non-grain crops, with remarkably increasing effects. Finally, it is pivotal to acknowledge that the influencing factors display sensitivity to the spatial scale examined. Village-level research provides a comprehensive overview, transcending individual household decisions. Collectively, this study underscores the indispensability of incorporating the underlying principles into policy formulation. Township and county authorities should craft guidelines, policies, and regulations in accordance with the ascertained village-level drivers, rather than relying solely on household-level determinants. [ABSTRACT FROM AUTHOR]
- Subjects :
- MACHINE learning
CROPS
ECONOMETRIC models
FOOD security
Subjects
Details
- Language :
- English
- ISSN :
- 14735903
- Volume :
- 21
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- International Journal of Agricultural Sustainability
- Publication Type :
- Academic Journal
- Accession number :
- 174099968
- Full Text :
- https://doi.org/10.1080/14735903.2023.2262752