Foresight from the hometown of green tea in China: Tea farmers’ adoption of pro-green control technology for tea plant pests

Abstract

The use of pesticides can lead to respiratory, reproductive, genetic, and nervous system diseases, which are major potential threats to human health. The abuse of pesticides by farmers and farm workers reportedly results in the death of about 180,000 people worldwide every year. With an increasing number of tea-drinkers in the world, people are paying closer attention to the presence of pesticide residues in tea and to the green production mode of tea. The pro-green control technology (PGCT) has recently been popularized as an environmentally friendly pest control method for pests of tea plants. In order to study the factors influencing tea farmers' adoption of PGCT for tea plant pest control, this study utilized the theory of planned behavior (TPB) and structural equation model (SEM) to empirically study the adoption behavior of 304 tea farmers in Shucheng County, China. Firstly, through meta-analysis, we integrated 23 studies related to farmers and preliminarily verified the hypotheses that attitude, subjective norms and perceived behavioral control have positive and significant impact on tea farmers' behavior intention were valid. Then we used SEM for analysis, the results indicated that subjective norms and perceived behavioral control have a positive and significant effect on intention, while attitude has no significant effect on intention. Moreover, there is a positive and significant relationship between the behavioral intention and behavior, while perceived behavioral control has a significant negative impact on behavior. In addition, this study verified the significant positive correlation between attitude, subjective norms and perceived behavioral control, indicating that the theoretical framework of the TPB is applicable for the study of tea farmers' behavior. The results of this study support the need for the government to promote the use of PGCT for tea plant pest control, as well as advance integrated prevention and control in the agricultural industry.