Digital Agriculture: How diffusion of innovations occur from planning to adoption

数字农业：创新如何从规划到采用进行传播

• 批准号: 2425507
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2425507
• 关键词: Digital; Agriculture; How; diffusion; innovations

Digital Agriculture: How diffusion of innovations occur from planning to adoption - Understanding how digital technologies, data science and remote sensing can lead to the transfer of agricultural innovation.New technologies and approaches are required if the planet is to achieve the Sustainable Development Goals (SDGs). Policies and approaches to dealing with local trends (declining yields) and shocks (pests, diseases, erratic climate) need to be co-created using local indigenous knowledge, data and models. This data is needed at increasingly fine spatial and temporal resolutions. Decision makers and scientists need to be able to feed important information to farmers on expected impacts from climate models, new farming practices and seed varieties. However, farmers need to be able to trial these and feed-back information on local contextual issues that will render some practices and seeds inappropriate. In 2018, DFID launched its Digital Strategy to increase the capabilities of digital technology for development. This project seeks to contribute to this strategy and will utilise the unique connections that the CASE Partner (Appendix 2) has with local organisations in Indonesia as well as the DFID Data Science Campus in Scotland to explore how innovations in agricultural practices can be shared to co-create new knowledge on how to best deal with erratic climate. Link to EPSRC remit: the project falls under the Living with Environmental Change Theme (LWEC). It will involve interdisciplinary research on how information and communications technologies can be developed to create a two way pipeline of data and information to deal with future climatic and environmental changes that present challenges for rural farmers and decision makers.Potential research questions:How are innovations in agricultural practices currently transferred between stakeholders?What are the processes involved in introduction, adoption and scaling up of digital tools in agriculture? & what are the challenges involved in introducing digital tools in agriculture?What are the socio-cultural dynamics involved in adoption of digital tools in agriculture?How geospatial techniques and big data can be used to develop innovative diffusion practices?Methodology: Digital Agriculture is fast emerging, but is it about the technology, or the processes and who benefits and who gets left behind? How do we adopt the right technologies in an inclusive manner? This joint project between NIRAS/LTS Data Futures Hub and UoE will answer these questions. The student will identify with the supervisor team and in collaboration with the CASE partners and the data Futures Hub in Indonesia which locations, agricultural system(s) and innovations on which to focus. The project will involve interdisciplinary research into agricultural innovations which will involve local indigenous knowledge systems, precision agriculture, data science and remote sensing. The focus will be on identifying technologies that can be implemented to help the co-creation of information rather than a linear top-down or bottom-up approach.

数字农业：创新如何从规划扩散到采用--了解数字技术、数据科学和遥感如何导致农业创新的转移。如果地球要实现可持续发展目标(SDGs)，就需要新的技术和方法。应对当地趋势(产量下降)和冲击(虫害、疾病、反复无常的气候)的政策和方法需要利用当地本土知识、数据和模型共同制定。这些数据需要越来越精细的空间和时间分辨率。决策者和科学家需要能够向农民提供有关气候模型、新的耕作做法和种子品种的预期影响的重要信息。然而，农民需要能够试验这些措施，并就当地的背景问题反馈信息，这些信息将使一些做法和种子变得不合适。2018年，DFID启动了数字战略，以提高数字技术促进发展的能力。该项目旨在为这一战略做出贡献，并将利用CASE合作伙伴(附录2)与印度尼西亚当地组织以及苏格兰DFID数据科学园区之间的独特联系，探索如何分享农业实践中的创新，共同创造如何最好地应对反复无常的气候的新知识。EPSRC职权范围的链接：该项目属于与环境变化一起生活(LWEC)主题。它将涉及跨学科研究，即如何开发信息和通信技术，以创建数据和信息的双向管道，以应对未来给农村农民和决策者带来挑战的气候和环境变化。潜在的研究问题：当前农业实践中的创新如何在利益相关者之间转移？在农业中引入、采用和扩大数字工具涉及哪些过程？在农业中引入数字工具涉及哪些挑战？在农业中采用数字工具涉及什么社会文化动态？如何利用地理空间技术和大数据来开发创新的传播实践？方法论：数字农业正在迅速崛起，但这是技术的问题，还是过程的问题，谁受益，谁落后？我们如何以包容的方式采用正确的技术？NIRAS/LTS数据期货中心和UOE之间的这个联合项目将回答这些问题。学生将与主管团队合作，并与案例合作伙伴和印度尼西亚的数据期货中心合作，确定要重点关注的地点、农业系统(S)和创新。该项目将涉及对农业创新的跨学科研究，这将涉及当地本土知识系统、精准农业、数据科学和遥感。重点将是确定可用于帮助共同创造信息的技术，而不是线性的自上而下或自下而上的方法。