Dhillon, B., Kataria, P. & Dhillon, P. National food security for agriculture sustainability in high crop productivity regions. Curr. SCI. 33–36 (2010).
Winters, La Digging for Victory: Agricultural Policy and National Security. World Econ. 13170–191 (1990).
Google Scholar
Sun, B. et al. China's agriculture nonpoint source pollution: causes and mitigation measures. Ambio 41370–379 (2012).
Chen, Y., Miao, J. & Zhu, Z. Measurement of green total factor productivity in China's agricultural sector: a three-stage SBM-DEA model with non-point source pollution and CO2 emissions. J. Clean. product. 318128543 (2021).
Google Scholar
Xiong, H., Zhan, J., Xu, Y., Zuo, A. & LV, X. Issues or drivers? The threshold effect of environmental regulations on agricultural green productivity in China. J. Clean. product. 429139503 (2023).
Google Scholar
Liu, Sy Artificial Intelligence (AI) in Agriculture. It's a pro twenty two14–15 (2020).
Google Scholar
Ding, T., Li, J., Shi, X., Li, X. & Chen, Y. A case in China. resource. policy 85103892 (2023).
Google Scholar
Liu, J., Qian, Y., Yang, Y. & Yang, Z. Can artificial intelligence improve energy efficiency for manufacturers? Evidence from China. int. J. Environment. res. Public heels. 192091 (2022).
Google Scholar
Li, Y., Zhang, Y., Pan, A., Han, M. & Veglianti, E. Effects of carbon emission reduction effects: heterogeneity characteristics and impact mechanisms. Technor. Soc. 70102034 (2022).
Google Scholar
Meng, X., Xu, S. & Zhang, J. Empirical analysis based on panel data from Chinese states. J. Clean. product. 376134273 (2022).
Google Scholar
LV, H., Shi, B., Li, N. & Kang, R. Intelligent manufacturing and reducing carbon emissions: evidence from the use of Chinese industrial robots. int. J. Environment. res. Public heels. 1915,538 (2022).
Google Scholar
Zhao, P., Gao, Y. & Sun, X. How will artificial intelligence affect green economic growth? SCI. total. environment. 834155306 (2022).
Google Scholar
Alzubi, A. A. & Galyna, K. Artificial intelligence and the Internet of Things for sustainable and smart agriculture. IEEE Access (2023).
Moore, J. Dartmouth University Artificial Intelligence Conference: The next 50 years. ai mag. 2787–87 (2006).
Google Scholar
Huang, R. Building rural governance digital powered by artificial intelligence and big data. Mathematics. problem. Eng. 20228145913 (2022).
Google Scholar
Lee, C.-C., Yan, J. & Wang, F. The impact of population aging on food security in the context of artificial intelligence: evidence from China. Technor. forecast. Soc. Chan. 199123062 (2024).
Google Scholar
Ikram, A. Etal. Application of artificial intelligence (AI) in food quality management and ensuring global food security. Cyta-Journal of Food twenty two2393287 (2024).
Google Scholar
How, M.-L., Chan, Y.J. & Cheah, S.-M. Predictive insights to improve global food security resilience using artificial intelligence. Sustainability 126272 (2020).
Google Scholar
Chen, Y. & Jin, S. Artificial intelligence and carbon emissions in manufacturing companies: the mitigation role of green innovation. process 112705 (2023).
Google Scholar
Liang, P., Sun, X. &Qi, L. environment. Developer. last. 2621651–21687 (2024).
Google Scholar
Chen, P., Gao, J., Ji, Z., Liang, H. & Peng, Y. Do artificial intelligence applications affect carbon emission performance? Energy 155730 (2022).
Google Scholar
Adams, B. Green Development: Environment and Sustainability in Developing Countries (Routledge, 2008).
Xinyu, Z. et al. Does the agricultural trade promote green development of China's agriculture? – Agricultural Green Factors Based on the perspective of productivity. Agriculture. & for. econ. manager. 736–43 (2024).
Google Scholar
Shen, Z., Wang, S., Boussemart, JP. &hao, Y. Digital transition and green growth in Chinese agriculture. Technol.Forecast. Soc. Chan. 181121742 (2022).
Google Scholar
Luo, X. et al. Improve levels of agricultural mechanization and promote sustainable development of agriculture. Transaction chin. Soc. Agriculture. Eng. 321–11 (2016).
Google Scholar
Ma, G., Li, M., Luo, Y. & Jiang, T. Agri-advances in ecological policies, human capital and agricultural green technology. Agriculture 13941 (2023).
Google Scholar
Zhang, M., Fang, K., Zhang, D. & Zeng, D. The relationship between assessments of agricultural scientific and technological innovation capabilities and the influential factors of green agriculture. PLOS 1 18E0295281 (2023).
Chen, Y., Hu, S. & Wu, H. Agriculture 131961 (2023).
Google Scholar
Chen, Y. Etal. Artificial intelligence, aging, economic growth. econ. res. J. 5447–63 (2019).
Google Scholar
Acemoglu, D. & Restrepo, P. Robots and Jobs: Evidence from the US labor market. J. Politics Econ. 1282188–2244 (2020).
Google Scholar
Chowdhury, S. et al. Unlock the value of artificial intelligence in human resource management through an AI feature framework. ham. resource. manager. Pastor 33100899 (2023).
Google Scholar
Brown, S., Pereira, M. & Guvlor, I. Implementation of an artificial intelligence framework to enhance Indonesia's human resource capabilities. int. J. Cyber IT Serve. manager. 465–71 (2024).
Google Scholar
Wang, M., Xu, M. & Ma, S. struct. Chan. econ. dynasty. 59427–441 (2021).
Google Scholar
Czapiewski, K. & Janc, K. Education, human capital and knowledge – paradigm shifts and future scenarios in rural Poland. Three decades of transformation in rural eastern and central Europe 351–367 (2019).
Aldieri, L., Barra, C. & Vinci, the role of human capital in identifying factors for innovation in CP products and processes: an empirical study from Italy. quality. & Quant. 531209–1238 (2019).
Google Scholar
Ren, J., Lei, H. &Ren, H. Livelihood capital, ecological cognition, and farmer's green production behavior. Sustainability 1416671 (2022).
Google Scholar
Cai, Q. & Han, X. The influence and mechanisms of digital village structure on total factor productivity of agricultural greens. front. last. Food system. 81431294 (2024).
Google Scholar
Xia, L., Han, Q. &Yu,S. Industrial information and changes in industrial structure: effects and mechanisms. int. Pastor Econ. &finance 931494–1506 (2024).
Google Scholar
Cano-Kollmann, M., Cantwell, J., Hannigan, T. J. & Mudambi, R. & Song, J (Agenda for Innovation Research in International Business, Knowledge Connection, 2016).
Google Scholar
Stalidis, G., Karapistolis, D. & Vafeiadis, A. Marketing decision support using artificial intelligence and knowledge modeling: application to tourism management. Procedia-social action. SCI. 175106–113 (2015).
Google Scholar
Liu, Q. Analysis of the effectiveness of artificial intelligence on joint driving on knowledge innovation management. Sci.program. 20228223724 (2022).
Google Scholar
Colombelli, A. & Quatraro, F. New enterprise formation and regional knowledge production modes: evidence of Italy. Res Policy 47139–157 (2018).
Google Scholar
Govindan, K. How Artificial Intelligence Drives Sustainable and Frugal Innovation: A Multi-view. IEEE Transformer. Eng. manager. 71638–655 (2022).
Google Scholar
Qayyum, M. et al. Advances in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils. J. Environment. manager. 347119147 (2023).
Google Scholar
Rong, J., Hong, J., Guo, Q., Fang, Z. & Chen, S. Path mechanisms and spatial ripple effects of green technology innovation on agricultural CO2 emission strength: a case study from Jiangsu Province, China. Ecole. India. 157111147 (2023).
Google Scholar
Deng, H., Zheng, W., Shen, Z. &štreimikienė, D. Fiscal expenditures promote increased green agricultural productivity. Survey on corn production. Applied energy 334120666 (2023).
Google Scholar
Wang, X., Hua, C. & Miao, J. Energy Source, Part A: Recovery. Activities. environment. Eff. 1–17 (2022).
Khezri, M., Heshmati, A. & Khodaei, M. The role of R&D in the effectiveness of renewable energy determinants: a spatial econometric analysis. Energy Econ. 99105287 (2021).
Google Scholar
Zhou, W., Zhang, Y. & Li, X. Artificial Intelligence, Green Technological Advancements, Energy Savings, and China's Carbon Emission Reduction: Tests based on Dynamic Spatial Durbin Modeling. J. Clean. product. 446141142 (2024).
Google Scholar
Hou, M., Deng, Y. &Yao, S. Rural labor transfer, application strength of fertilizer, agricultural eco-efficiency: interactive effects and spatial turmoil. Journal of Agrotechnical Economics 1079–94 (2021).
Google Scholar
Huang, Y., Huang, X., Xie, M., Cheng, W. & Shu, Q. Study on the impact of regional differences on agricultural water resource utilization efficiency using a super-efficient SBM model. SCI. manager 119953 (2021).
Du, J., Liang, L. & Zhu, J. EUR. j.oper. res. 204694–697 (2010).
Google Scholar
