As the world's largest consumer of agricultural chemicals, China has used more than 30 percent of global pesticides on only 9 percent of the world's crop land. Pesticides are often applied to crops to provide protection against pest damage and to limit yield losses in China. These applications are often done on an insurance basis rather than a prescriptive basis because pest abundance is high. With sustainable crop protection becoming more important to achieve the "Net-zero emission" plan in China, there is increasing demand for new pest management tools that can help Chinese farmers grow more sustainably with fewer chemical inputs and reduced soil erosion.

This project will explore the feasibility of utilising mobile intelligence techniques as a cost-effective farmer-centred pest management solution with improved economic benefits and environmental sustainability in China. We will rely on our existing deep learning based mobile wheat pest recognition technique developed from an Innovate-UK project, in partnership with the University of Sheffield and China Academy of Sciences (CAS). The technique offers: rapid detection and effective quantification of wheat pests; places pest quantification into context of regionally relevant pest tolerance thresholds; determines whether a pesticide application is advised to use.

This project will examine the acceptability of using mobile pest management apps by Chinese smallholder farmers and farmer cooperatives via questionnaires and interviews, analysis the perceived impact of the apps in supporting sustainable agricultural development in China via comprehensive literature reviews, and predict the potential long-term economic benefits of using above technique in China. Through existing collaboration with CAS, we will engage with 4 smallholder farmers and 2 farmer cooperatives at Anhui Province in China.

This project will deliver a comprehensive analysis and evaluation report discussing above technique for sustainable pest management in China in terms of user acceptability, environment impacts and business return. This report should include: 1) Farmer requirement identification and their acceptance results analysis of mobile apps usage in sustainable pest management in China; 2) Analysis the strong and weak points of the mobile pest management solution using agronomic, environmental, and social-economic criteria; 3) potential open-source business model that provides basic mobile applications to small-size growers and public for free. 4) The business-to-business approach, which sells professional software licenses, services and professional training to middle-size growers and agronomists in China.