苏凯, 孟海波, 张辉. 中国农业绿色发展指标体系构建及其"十四五"趋势预判[J]. 农业工程学报, 2021, 37(20): 287-294. DOI: 10.11975/j.issn.1002-6819.2021.20.032
    引用本文: 苏凯, 孟海波, 张辉. 中国农业绿色发展指标体系构建及其"十四五"趋势预判[J]. 农业工程学报, 2021, 37(20): 287-294. DOI: 10.11975/j.issn.1002-6819.2021.20.032
    Su kai, Meng Haibo, Zhang Hui. Construction of the green development indicators for agriculture and its prediction in the 14th Five-Year Plan in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(20): 287-294. DOI: 10.11975/j.issn.1002-6819.2021.20.032
    Citation: Su kai, Meng Haibo, Zhang Hui. Construction of the green development indicators for agriculture and its prediction in the 14th Five-Year Plan in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(20): 287-294. DOI: 10.11975/j.issn.1002-6819.2021.20.032

    中国农业绿色发展指标体系构建及其"十四五"趋势预判

    Construction of the green development indicators for agriculture and its prediction in the 14th Five-Year Plan in China

    • 摘要: 构建农业绿色发展评价指标体系有利于定量评价中国农业绿色发展水平,为实现路径探索、政策制定等提供有益参考。基于此,该研究在充分理解农业绿色发展科学内涵的基础上,综合考量系统性、数据可得性等原则,构建了中国农业绿色发展评价指标体系。而后应用熵值法、主成分分析法和层次分析法等分别计算各指标权重值,同时基于组合赋权法求出各指标最终综合权重值,对2007-2019年中国农业绿色发展水平进行评价。在此基础上,应用灰色Verhulst模型预测"十四五"时期的发展趋势。研究结果显示:2007-2019年中国农业绿色发展水平总体上呈稳步上升趋势且逐渐迈向绿色发展路径;"十四五"中国农业绿色发展将进入快车道,农业绿色发展综合指数将达到77.9,比2019年提高了11.67%;"资源节约与高效利用"与"政策支持与科技支撑"指标是影响中国农业绿色发展的重要指标。因此,各级政府应将其作为后续施政重点,以稳步推进农业高质量绿色发展,助力农业现代化进程。

       

      Abstract: Abstract: The ever-increasing needs for a better life have proposed much higher requirements for agricultural development, as socialism with Chinese characteristics has entered a new era. The Agricultural Green Development (AGD) has been the re-creation under the Sinicization for the concept of sustainable development. The construction of green development indicators for agriculture can greatly contribute to quantitatively valuating the AGD level, particularly for path exploration and policy-making. Accordingly, this study aims to first construct the evaluation index system of AGD in China. Then, the entropy, Principal Component Analysis (PCA), and Analytic Hierarchy Process (AHP) were applied to calculate the weight value of each indicator. As such, a combination weighting was used to calculate the final comprehensive weight value of each indicator to evaluate the AGD level in China from 2007 to 2019. Finally, a grey Verhulst model was adopted to predict the development trend in the 14th Five-Year Plan. The findings of this study revealed that China's AGD level showed a steady upward trend, and gradually moved towards the path of green development during 2007-2019. The comprehensive index of AGD rose from 26.20 in 2007 to 70.76 in 2019, with an average annual increase of 13.08%. Among them, the comprehensive index of AGD in 2017, 2018, and 2019 increased by 4.5%, 1.8%, and 5.1%, respectively, higher than the average level from 2013 to 2016. This was because, 1) a series of important policies were released to promote the AGD in recent years, including the relevant mechanism for AGD, the national AGD pilot zones, the supporting capacity of science and technology. 2) The agricultural development was oriented towards the path of green development during policy decision-making. More importantly, the weight value of the first-level index "Resource conservation and efficient utilization" was the largest (0.386), and the rest of the three first-level indicators were ranked in descending order "Policy support and science & technology support" (0.223), "Natural resources and ecological security" (0.212) and "High-quality products and affluence" (0.179). 3) China's AGD was predicted to enter the fast lane during the 14th Five-Year Plan, where the comprehensive index of AGD reached 77.9, an increase of 11.67% over 2019. It was also found that there were much larger weight values for the indicators of energy consumption per unit of agricultural output, carbon base productivity, and R&D investment intensity. It inferred that scientific and technological innovation can be an effective way to reduce resource consumption for higher efficient use, which was the power source for AGD. Therefore, three recommendations can be addressed during this time: 1) To further improve the system and mechanism of AGD; 2) To explore diversified agricultural and ecological compensation (e.g., carbon compensation), and 3) to strengthen the tackling of key green technologies (e.g., green technology for higher production and efficiency of crops, green and low-carbon planting and breeding technology). This finding can provide potential decision-making support to promote the AGD for the construction of the evaluation index system.

       

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