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The development of green agriculture is an effective way to realize the sustainable development of agriculture, which is of great significance for guaranteeing national food security, improving the supply ability of agricultural products, promoting the healthy development of cultivated land, and realizing green development. Since the 18th National Congress of the Communist Party of China, China has proposed the establishment of a green-development-oriented agricultural support system, which intends to reverse the worsening of the agricultural ecological environment; however, in 2019, the input of agricultural chemical fertilizer still exceeded the international limit of the safe application of chemical fertilizer. In recent years, agriculture has surpassed industry to become the largest non-point source pollution industry in China, seriously affecting the rural ecological civilization construction and the advancement of green sustainable development coordinated. To analyze the key factors affecting the development of green agriculture, in this study, logistic binary regression analysis was used to measure the main factors affecting farmers’ green agricultural production willingness and green agricultural production behavior. The results show that a farmer’s age, land type, compensation for land transfer, technical service organization, related training, and economic and technological subsidies had significant effects on their green agricultural production willingness. The age of farmers, number of staff, risk of green agricultural production technology, technical service organization, and economic and technological subsidies were shown to have significant effects on the green agricultural production behavior of farmers, where the different factors influenced the behavior to different degrees. Based on the above findings, it is suggested that the Chinese government should help farmers to carry out agricultural green transformation through technical training, policy popularization, economic subsidies, and educational support.
Li et al. (Fri,) studied this question.