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Journal of Tea Science ›› 2017, Vol. 37 ›› Issue (3): 308-314.

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An Empirical Study on the Impact Factors of Adoption of Green Prevention and Control Technology by Tea-growers

HU Linying, DU Pei, CHEN Fuqiao*, JIANG Aiqin, JIANG Renhua, LU Chengyin*   

  1. Tea Reserch Institute, Chinese Academy of Agricutural Sciences, Hangzhou 310008, China
  • Received:2017-01-10 Revised:2017-02-24 Online:2017-06-15 Published:2019-08-22

Abstract: Survey data were collected from 2β210 tea-growers from sixteen major tea producing provinces and then the Logit model was established to analyze the imfact factors of Green Prevention and Control Technology (GPCT) adoption by tea-growers. The results showed that GPCT adoption by tea-growers was affected by personality variables, family characteristics, operating characteristics of tea plantation, organizational and technical service characteristics. The most effective factor was organizational and technical service characteristics. Concretely, the farmer’s age, household size, cultivated area had significantly negative effects on technology adoption. The knowledge of the pesticide residues’ limitation standard (PRLS), household income, the connection with cooperation, pest control training frequency and communication with others had positive effects on technology adoption. The technology adoption rate of tea-growers who knew the PRLS was about 2 times higher than the rest. An increase of household income by ten thousand yuan could increase the technology adoption rate by 2%. Cooperative members’ technology adoption rate was 1.73 times higher than non-members. Every training of farmers could promote technology adoption rate by 1.50 times. However, the farmers’ educational status, non-agricultural income didn’t significantly affect their choices. Therefore, the related government department should improve farmers’ organization, increase training times and cut down the cost of technology adoption to promote GPCT adoption to achieve green agriculture.

Key words: tea-growers, green prevention and control technology, technology adoption, impact factors

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