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

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.

Low cost Hyperspectral Crop Camera (HCC).

A consortium from a broad range of disciplines have come together to develop a revolutionary low cost crop camera that could potentially allow farmers to improve crop yield, use less fertiliser, use less pesticide and spot pests and diseases earlier.

The project will be led and coordinated by Wideblue Limited - a developer and manufacturer of specialist cameras. The project will also call on the skills of the the James Hutton Institutes expertise in crop nutrition and monitoring, the University of Strathclyde's Hyperspectral Imaging Centre, the University of the West of Scotland's Institute of Thin Films, Sensors and Imaging and Galloway & MacLeod's intelligent agriculture division.

The main beneficiaries of the proposed research will be the agricultural industry and environmental research, with a wider range of potential beneficiaries who will discover ways to apply the outputs of the work. The design and operation of this system will be targeted at agricultural systems, and will be tested using agricultural field trials for its ability to detect disease, drought symptoms and nutritional deficiencies in crops. For the agricultural industry, detection of disease and other problems with crop condition often occurs when it is too late to resolve the situation, usually with the resulting loss of all or a major part of the crop. A portable, hand-held and robust monitoring device capable of detection of specific crop problems would enable much more rapid detection, with associated economic savings for the grower. For academics research, the proposed work would provide a tool to allow much more detailed and rapid crop monitoring than before as part of experiments, and also to monitor vegetation condition in the field for ecological surveys. The overall impact of the proposed work will be felt through improved agricultural productivity and food security through the rapid detection of disease and monitoring of crop conditions, and will enable researchers to improve their experimental data capture. Both of these aspects will result in more resilient agricultural systems.