16AGRITECHCAT5: Feasibility of a Hyper Spectral Crop Camera (HCC) for agriculture optimisation

农民和园艺师面临着各种各样的困难，这些困难需要他们多年来积累的对田地和作物的经验和知识。这些困难包括但不限于：田地生长/产量不均；不准确和估计的肥料施用；灌溉不均和病虫害杂草的地方差异。此外，最佳的收获时间仍然是推测的，而且往往是不准确的。面对众多变量，农民无法避免成本和作物产量每年的高变化。帮助农民优化肥料和水应用或早期发现疾病的工具将为作物生长的最佳控制提供有用的诊断和管理能力。目前，针对这些挑战的解决方案确实存在，然而，当前的系统又大又重，不便携，因此不容易部署。它们的价格也非常昂贵，一般为1万至15万英镑，通常只适合用于航空或卫星成像应用或实验室分析。实际上，目前可用于上述农业挑战的解决方案仅限于大规模耕作和/或高价值作物。在这些昂贵的系统中，在可见光和/或红外波段拍摄作物的光谱仪扫描或图像，并分析显示与作物生长条件相关的光谱图像特征变化。感兴趣的特征因植物和原因而异。作物的“颜色”（可见光和红外光谱）也随着其接近成熟而变化，光谱仪扫描为与作物水化、施肥、疾病进展和收获有关的明智管理决策提供科学信息。高光谱成像（HSI）可以捕获这些变化：高光谱成像系统捕获大量场景图像，每个图像在传感器技术确定的一定范围内具有不同的波长，以产生所谓的高光谱数据立方体，其中空间域中的每个像素包含被观察对象的光谱轮廓。在我们的应用中，可以分析这些光谱信息，以便对最大限度地提高作物产量的挑战做出诊断/管理决策。所提出的高光谱作物相机（HCC）将具有：低成本、紧凑便携、操作简单、坚固耐用等特点。相机外壳将包含传感器、电池和电子设备，以生产一个简单轻便的小设备。该设备将适用于手持使用或可能安装在低成本无人机进行本地机载分析。HSI技术在农业和农业方面的成本从1万英镑到15万英镑不等。应用HCC可以使农民和/或农学家：-通过提供优化或局部灌溉来节约用水-及时识别害虫/疾病/杂草区域进行早期干预-优化肥料使用-确定最佳收获时间并帮助提高作物产量-提高作物产量的均匀性-减少人工时间，手动测量田地等-减少对技术农艺培训/知识的需求。

Farmers and horticulturists face varying difficulties that require experience and knowledge of their fields and crops, gained over many years. These difficulties include, but are not limited to: uneven growth/yield of their fields; inexact and estimated fertiliser application; uneven irrigation and local variations in pests/diseases/weeds. Additionally, the optimum harvest timing is still speculated and often inexact. Faced with numerous variables, farmers cannot avoid high variations in costs and crop yields from year to year. Tools to assist farmers to optimise e.g. fertiliser & water applications or early detection of disease will provide a useful diagnostic and management capability for optimum control of crop growth. Currently, solutions for these challenges do exist, however, current systems are large, heavy, not portable and as such are not readily deployable. They are also prohibitively expensive - typically £10,000 - £150,000 each - and are generally only suitable for use in airborne or satellite imaging applications or laboratory analysis. In effect, the current solutions available for the aforementioned agricultural challenges are limited to large scale farming and/ or high value crops. In these expensive systems, a spectrometer scan or image of the crop is taken at visible and/or infrared wavelengths with analysis showing spectral image signature changes relating to crop growth conditions. The signatures of interest varies from plant to plant and from cause to cause. The "colour" of a crop (visible and IR) also changes as it approaches maturity, with spectrometer scans providing scientific information for informed management decisions in relation to crop hydration, fertiliser application, disease progression and harvesting. Hyperspectral Imaging (HSI) can capture these changes: HSI systems capture a large number of images of the scene, each at a different wavelength within some range determined by the sensor technology, to produce a so called hyperspectral data cube in which each pixel in the spatial domain contains a spectral profile of the object observed. For our application, this spectral information can be analysed to make decisions about the diagnostics/management of challenges in maximising crop yield. The proposed Hyperspectral Crop Camera (HCC) will be: low-cost, compact & portable, simple in operation and robust. A camera housing will contain the sensor, battery and electronics to produce one small simple lightweight device. This device would be suitable for handheld use or potentially mountable in a low cost drone for local airborne analysis. HSI technology in farming and agriculture which can cost anything from £10k - £150k. Application of HCC can allow a farmer and/ or agriculturists to: - Save water by providing optimised or localised irrigation - Timely identify areas of pests/diseases/weeds for early intervention - Optimise use of fertiliser - Determine optimum harvest time and help increase crop yield - Improve evenness of crop yield across field area - Reduced man hours, manually surveying fields etc - Reduce need for technical agronomy training/knowledge.