Abstract
The low-carbon agriculture strategy equipped with green economy is developed to encourage the substantial growth of green assets of the natural resources. In order to achieve growth in agricultural energy efficiency, this paper mainly uses the directional distance function and the ML index to analyze the agricultural total factor energy efficiency in the 11 provinces and cities of the Yangtze River Economic Belt from both dynamic and static aspects, and uses the fixed-effect panel model method. The main influencing factors are regression analysis of panel data. The results of the study show that for every 1% increase in crop damage, the agricultural energy efficiency will drop by 0.452%; the literacy level of the labor force at the level of 5% significantly affects agricultural energy efficiency. This work contributes in improving the smart city planning along with the reduction in the degree of damage to crops due to the negative impact of industrial structure and the level of mechanization. This work enables the futuristic technologies by promoting the level of urbanization, labor education and the government’s financial support for agriculture.
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References
Arundel A, Sawaya D (2009) The bioeconomy to 2030: designing a policy agenda
Barker T, Bashmakov I, Alharti A., Amann M, Cifuentes L, Drexhage J, Yamaji K (2007) Mitigation from a cross sectoral perspecti ve. climate change 2007: mitigation. Contribution of working group iii to the fourth assessment report of the intergovernmental panel on climate change, eds Metz B, Davidson OR, Bosch PR, Dave R, Meyer LA. Cambridge, UK and New York.
Bellarby J, Foereid B, Hastings A (2008) Cool Farming: climate impacts of agriculture and mitigation potential
Bharti R, Khamparia A, Shabaz M, Dhiman G, Pande S, Singh P (2021) Prediction of heart disease using a combination of machine learning and deep learning. Comput Intell Nneurosci. https://doi.org/10.1155/2021/8387680
Blandford D (2011) The contribution of agriculture to green growth. Report to the OECD, 1–36
Blandford D (2010) Agricultural policies and rural development–a synthesis of recent OECD work
Brentrup F, Pallière C (2008) GHG emissions and energy efficiency in European nitrogen fertiliser production and use. In: Proceedings-international fertiliser society (No 639, pp 1–25). International fertiliser society
Chu J-F, Wu J, Song M-L (2016) An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application. Ann Oper Res 270(1–2):105–124. https://doi.org/10.1007/s10479-016-2264-7
Crutzen PJ, Mosier AR, Smith KA, Winiwarter W (2007) N 2 O release from agro-biofuel production negates global warming reduction by replacing fossil fuels. Atmos Chem Phys Discuss 7(4):11191–11205
Davidson EA (2009) The contribution of manure and fertilizer nitrogen to atmospheric nitrous oxide since 1860. Nat Geosci 2(9):659–662. https://doi.org/10.1038/ngeo608
Du J, Chen Y, Huang Y (2018) A modified Malmquist-luenberger productivity index: assessing environmental productivity performance in China. Eur J Oper Res 269(1):171–187
Dwivedi R, Dey S, Chakraborty C, Tiwari S (2021) Grape disease detection network based on multi-task learning and attention features. IEEE Sens J 21(16):17573–17580. https://doi.org/10.1109/jsen.2021.3064060
Fingleton B, Le Gallo J, Pirotte A (2018) A multidimensional spatial lag panel data model with spatial moving average nested random effects errors. Empiri Econ 55(1):113–146
Hockstad L, Hanel L (2018) Inventory of U.S. greenhouse gas emissions and sinks [Data set]. Environmental system science data infrastructure for a virtual ecosystem. https://doi.org/10.15485/1464240
Jensen H, Pérez Domínguez I, Fellmann T, Lirette P, Hristov J, Philippidis G (2019) Economic impacts of a low carbon economy on global agriculture: the bumpy road to Paris. Sustainability 11(8):2349. https://doi.org/10.3390/su11082349
Jorge-Martinez D, Butt SA, Onyema EM, Chakraborty C, Shaheen Q, De-La-Hoz-Franco E, Ariza-Colpas P (2021) Artificial intelligence-based Kubernetes container for scheduling nodes of energy composition. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-021-01195-8
Lee Y, Mukherjee D, Ullah A (2019) Nonparametric estimation of the marginal effect in fixed-effect panel data models. J Multivar Anal 171:53–67. https://doi.org/10.1016/j.jmva.2018.11.013
Li J, Glibert P, Zhou M, Lu S, Lu D (2009) Relationships between nitrogen and phosphorus forms and ratios and the development of dinoflagellate blooms in the East China Sea. Mar Ecol Prog Ser 383:11–26. https://doi.org/10.3354/meps07975
Liu T, Liu S, Shi L (2020) Time series analysis using SAS enterprise guide. Springer Nature
Manne R (2020) Covid-19 and its impact on air pollution. Int J Res Appl Sci Eng Technol 8(11):344–346. https://doi.org/10.22214/ijraset.2020.32139
Nazer MNR, Noorwali A, Tajuddin MFN, Khan MZ, Tazally MAIA, Ahmed J, Kumar NM (2021) Scenario based investigation on the effect of partial shading condition patterns for different static solar photovoltaic array configurations. IEEE Access
Norse D, Zhang FS (2010) Improved nutrient management in agriculture-a neglected opportunity for China’s low carbon growth path. UK-China Sustainable Agriculture Innovation Network, Yangling
Norse D, Powlson D, Lu Y (2011) China case study: integrated nutrient management as a key contributor to China’s low carbon agriculture. Climate change mitigation and agriculture. Earthscan, London
Organisation for Economic Co-operation and Development (2010) Interim report of the green growth strategy: implementing our commitment for a sustainable future. OECD Publishing
Pastor JT, Aparicio J, Alcaraz J, Vidal F, Pastor D (2018) Bounded directional distance function models. CEJOR 26(4):985–1004. https://doi.org/10.1007/s10100-018-0562-7
Powlson DS, Whitmore AP, Goulding KWT (2011) Soil carbon sequestration to mitigate climate change: a critical re-examination to identify the true and the false. Eur J Soil Sci 62(1):42–55. https://doi.org/10.1111/j.1365-2389.2010.01342.x
Rafiq Nazer MN, Noorwali A, Tajuddin MFN, Khan MZ, Ahmad Tazally MAI, Ahmed J, Babu TS, Ghazali NH, Chakraborty C, Kumar M, N (2021) Scenario-based investigation on the effect of partial shading condition patterns for different static solar photovoltaic array configurations. IEEE Access 9:116050–116072. https://doi.org/10.1109/access.2021.3105045
Rathee G, Sharma A, Kumar R, Iqbal R (2019) A secure communicating things network framework for industrial IoT using blockchain technology. Ad Hoc Netw 94:101933. https://doi.org/10.1016/j.adhoc.2019.101933
Rathee G, Sharma A, Saini H, Kumar R, Iqbal R (2019) A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology. Multimed Tools Appl 79(15–16):9711–9733. https://doi.org/10.1007/s11042-019-07835-3
Ratta P, Kaur A, Sharma S, Shabaz M, Dhiman G (2021) Application of blockchain and internet of things in healthcare and medical sector: applications, challenges, and future perspectives. J Food Qual. https://doi.org/10.1155/2021/7608296
Ruomei W, Hailiang MA, Jin W, School B, University H (2019) Spatial and temporal differences of agricultural carbon emissions and impact factors of the yangtze river economic belt based on a water-land perspective. Resources ence
Sharma A, Singh PK, Sharma A, Kumar R (2019) An efficient architecture for the accurate detection and monitoring of an event through the sky. Comput Commun 148:115–128. https://doi.org/10.1016/j.comcom.2019.09.009
Shi W, Lee L (2018) A spatial panel data model with time varying endogenous weights matrices and common factors. Reg Sci Urban Econ 72:6–34. https://doi.org/10.1016/j.regsciurbeco.2017.03.007
Tang S, Shabaz M (2021) A new face image recognition algorithm based on cerebellum-basal ganglia mechanism. J Healthc Eng. https://doi.org/10.1155/2021/3688881
Wang Q, Huang Y (2019) Evaluation and optimization of total factor energy efficiency of manufacturing system based on DEA. Ind Eng J 22(5):19
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Ji, H., Hoti, A. Green economy based perspective of low-carbon agriculture growth for total factor energy efficiency improvement. Int J Syst Assur Eng Manag 13 (Suppl 1), 353–363 (2022). https://doi.org/10.1007/s13198-021-01421-3
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DOI: https://doi.org/10.1007/s13198-021-01421-3