Feasibility Analysis of Farmer-centered Mobile Intelligence for Sustainable Pest Management in China

以农民为中心的移动智能可持续害虫治理在中国的可行性分析

• 批准号: 10018696
• 金额: $ 2.45万
• 依托单位: MUTUS TECH LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10018696
• 关键词: Feasibility; Analysis; Farmer; centered; Mobile

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.

作为世界上最大的农药消费国，中国仅在全球9%的耕地上使用了全球30%以上的农药。在中国，农药通常用于农作物，以防止害虫损害并限制产量损失。这些应用通常是在保险的基础上而不是在规定的基础上进行的，因为害虫的丰度很高。随着可持续作物保护对中国实现“净零排放”计划变得越来越重要，中国农民对新的虫害管理工具的需求日益增加，这些工具可以帮助中国农民在更少的化学投入和减少土壤侵蚀的情况下实现更可持续的增长。本项目将探索利用移动的智能技术作为成本效益农民的可行性-为中国提供了一个集中的害虫管理解决方案，提高了经济效益和环境可持续性。我们将依靠我们现有的基于深度学习的移动的小麦害虫识别技术，该技术是与谢菲尔德大学和中国科学院（CAS）合作开发的，来自Innovate-UK项目。该技术提供：快速检测和有效量化小麦害虫;将害虫量化纳入区域相关的害虫耐受阈值;决定是否建议使用农药。本项目将通过问卷调查和访谈，考察中国小农和农民合作社使用移动的害虫管理应用程序的可接受性，通过综合文献综述，分析了应用程序在支持中国农业可持续发展方面的感知影响，并预测了在中国使用上述技术的潜在长期经济效益。通过与中科院现有的合作，我们将与中国安徽省的4个小农户和2个农民合作社合作，该项目将从用户可接受性、环境影响和商业回报等方面对上述技术在中国的可持续害虫管理进行全面的分析和评估。该报告应包括：1）农民对移动的应用程序在中国可持续害虫管理中的使用需求识别及其接受结果分析; 2）使用农艺、环境和社会经济标准分析移动的害虫管理解决方案的优缺点; 3）向小型种植者和公众免费提供基本移动的应用程序的潜在开源商业模式。4)通过企业对企业的方式，向中国的中等规模种植者和农艺师销售专业软件许可证、服务和专业培训。