Design and Development of Mechanized Systems to Increase Farm Efficiency, Create Farm Traceability and Monitor True Cost of Production: A Pathway to Digital Agriculture

传统的农业耕作是不可持续的，迫切需要新的工程进步，以保持在当地和全球市场的竞争力。需要增加发现和创新，以填补知识空白，从而开发新技术和可追溯性协议，提高农场效率，更有效地利用环境资源。该研究计划的长期目标是开发新颖，创新，综合和环保的系统，通过基本和应用原理来实施，尖端的数字系统，以提高农场效率，创建农场可追溯性和监控生产的真实成本。通过拟议的发现补助金完成的短期目标将揭示负责完整农场可追溯性的基本因素。创新的新型传感器和控制设备以及预测建模方法将用于可持续的农场管理。将设计实时作物、疾病和害虫管理软件，允许对重要活动进行高级警报通知，同时提供预测性决策和内置成本监控。通过这项研究设计和实施的完整的农场可追溯性协议将首次为农业社区，加工商和最终消费者提供一流食品质量的满意度和安全性。将研究每一项创新（害虫检测传感器、作物预测建模、水果可追溯系统、自动化成本监测和投入处方）与传统耕作方法相比的社会经济和环境影响。在接下来的5年里，我将培养一个多元化和性别平衡的高素质人才（HQP）团队。1名博士，4名硕士和5名本科生将在公平和支持的环境中接受培训。作为一名早期职业研究人员，我将利用我与我所在部门的教师以及国内和国际机构的合作者已经建立的联系，进一步增加我的资源和HQP的学习机会。这项研究将填补知识空白，并培养HQP在先进机械化系统的新领域。通过这项研究发现的新想法和发明将在科学期刊、国家和国际会议记录、概况介绍和生产者会议上传播。这项研究符合联邦政府的战略目标，为继续研究开辟了新的途径。野生蓝莓将成为新发现和新发展的初始测试平台;然而，这些技术随后可以进行修改并应用于其他园艺作物。向数字农业的转变将提高作物生产力，减少对环境的影响，并允许下一代加拿大农民积极继承，以帮助用有限的自然资源养活世界不断增长的人口。

Traditional agricultural farming is not sustainable and severely requires new engineering advancements to remain competitive in both local and global markets. Increased discovery and innovation are required to fill the knowledge gap allowing development of new technologies and traceability protocols that will increase farm efficiency and use environmental resources more effectively. The long-term goal of this research program is to develop novel, innovative, integrated and environmentally sound systems, through fundamental and applied principals to implement, cutting-edge digital systems to increase farm efficiency, create farm traceability and monitor the true cost of production. The short-term objectives to be completed through this proposed Discovery Grant will uncover the fundamental factors responsible for complete farm traceability. Innovative new sensors and control devices coupled with predictive modelling methods will be developed for sustainable farm management. Real-time crop, disease and pest management software will be designed allowing advanced alert notification of vital activities while offering predictive decisions and built in cost monitoring. The complete farm traceability protocol that will be designed and implemented through this research will for the first time, give the farming community, processors, and the end consumer the satisfaction and security of top-notch food quality. The socio-economic and environmental impact will be studied with each developed innovation (pest detection sensors, crop forecast modelling, fruit traceability system, automated cost monitoring and prescriptions for inputs) as compared to traditional methods of farming. Over the next 5-years I will train a diverse and gender balanced team of highly qualified personnel (HQP). 1 PhD, 4 MSc and 5 undergraduate students will be trained in a fair and supportive environment. As an early career researcher, I will use my already established links with faculty within my department as well as collaborators at institutions both nationally and internationally to further increase my resources and learning opportunities for HQP. This research will fill the knowledge gap and train HQP in the new area of advanced mechanized systems. Novel ideas and inventions discovered through this research will be disseminated in scientific journals, national and international conference proceedings, factsheets and producer meetings. This research aligns with the federal governments strategic objectives opening new avenues for continued research. Wild blueberry will be the initial testing platform for new discoveries and developments; however, these technologies can then be modified and implemented into other horticultural crops. The shift to digital agriculture will increase crop productivity, reduce environmental impact and allow a positive succession to the next generation of upcoming Canadian farmers to help feed the worlds growing population with limited natural resources.