Study on the Impact of Unified Control on Pesticide Reduction of Tea Farms Based on the Empirical Analysis of Fujian and Zhejiang Provinces
The control of pests and diseases can drive the large-scale reduction of application and efficiency increase of pesticides,which is of great significance for promoting the high-quality development of agriculture.Based on the micro-sur-vey data of 530 tea growers in Fujian Province and Zhejiang Province,this study empirically analyzed the impact and mechanism of tea farmers'pesticide use behavior by using endogenous transformation model.The results show that:(1)The adoption of tea farmers'unified pest and disease prevention and control is affected by different factors.The youn-ger the tea farmers and the worse the tea farmers'physical health,the more risk they can take and the more they tend to a-dopt unified prevention and control.(2)The adoption of the unified control rule can significantly reduce the use of pesti-cides by tea farmers.If the tea farmers who had adopted the unified control rule but withdrew from it afterward,their per u-nit area pesticide expenditure would have increased by 31.02％.If the tea farmers who did not adopt the unified control rule adopted it afterward,their pesticide expenditure would have decreased by 12.32％.(3)The adoption of the unified control rule can significantly increase the income of tea farmers.For tea farmers who had adopted the unified control rule withdrew from it afterward,their family's annual per capita total income would have decreased by 59.23％.If the tea farm-ers who did not adopt the unified control rule adopted it afterward,the total annual per capita income of their families would have increased by 32.60％.The results of this study is of great significance for farmers to adopt unified pest and dis-ease control,so as to achieve pesticide reduction,to promote the green and high-quality development of modern agricul-ture,and to increase farmers'income.
unified controlpesticide use behaviorpesticide reductionfarmers'income increaseendogenous switching regression model
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