Precision Agriculture Web Portal Server for Canadian Farmers

尼亚加拉大学研究与创新分部尼亚加拉研究中心是NSERC精密农业和环境技术学院工业研究主席Mike Duncan博士的中心。随着郊区的扩大，安大略省的可耕地变得越来越有价值，拥有当地/国内的粮食供应是必不可少的。2012年，安大略省初级农业部门创造了39.8亿美元的国内生产总值(GDP)。最大限度地提高目前耕地的产量的最佳机会是提高产量。精准农业的重点是增加产量，同时减少化肥投入，从而降低成本，增加收入，并将对环境的影响降至最低。邓肯博士和他的团队开发了各种网络应用程序，提供实时数据、地图绘制、地图分析和/或增值农民数据。目前，该团队的精准农业工作正处于可以应用于种植者和种植者顾问以提高他们的生产率和竞争力的阶段。使用类似方法的种植者发现，投入节省高达20%，这对现代种植业务意义重大。为了正确地应用和测试精确农业理论，需要15-30名种植者，将需要最先进的服务器和磁盘系统，特别是因为种植者需要在将投入应用到他们的田地之前快速数据周转。在项目结束时，算法和系统将被开发成一个自动化实体，有能力及时处理来自数千个农场(安大略省有2.8万名种粮农民)的数据。这笔资金将提供一个世界级的计算机引擎，用于开发这个系统。

The Niagara College Research and Innovation division, Niagara Research, is the hub for Dr. Mike Duncan, the NSERC Industrial Research Chair for Colleges (IRCC) in Precision Agriculture and Environmental Technologies. With the suburbs expanding, arable land in Ontario is becoming increasingly valuable, and it is essential to have a local/domestic supply of food. Ontario's primary agriculture sector produced 3.98 Billion dollars in Gross Domestic Product (GDP) in 2012. The best opportunity to maximize the production from the currently farmed land is by increasing the yield. Precision agriculture is focused on increasing the yield, while decreasing the fertilizer inputs, which reduces costs, increases revenue, and minimizes environmental impact. Dr. Duncan and his team have developed a variety of web applications that provide real time data, mapping, map analysis, and/or value added farmer data. Currently, the team's Precision Agriculture work is at the stage where it can be applied with growers and grower consultants to increase their productivity and competitiveness. Growers using similar methods have discovered input savings as high as 20%, which is significant for a modern growing operation. To properly apply and test precision agriculture theories, with 15-30 growers as is required, a state of the art server and disk system will be required, particularly due to growers' needs for quick data turnaround prior to applying inputs to their fields. At the end of the project, the algorithms and the system will be developed into an automated entity that has the capacity to process data from thousands of farms (there are 28,000 grain farmers in Ontario) in a timely manner. The funding will provide a world-class computer engine that will be used to develop this system.