16AGRITECHCAT5: Feasibility of a Hyper Spectral Crop Camera (HCC) for agriculture optimisation
16AGRITECHCAT5: Feasibility of a Hyper Spectral Crop Camera (HCC) for agriculture optimisation
批准号:
BB/P004873/1
负责人:
Stephen Marshall
金额:
$8.66万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
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英文摘要
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.
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DOI:
10.1016/j.jfoodeng.2018.06.015
发表时间:
2018-12-01
期刊:
JOURNAL OF FOOD ENGINEERING
影响因子:
5.5
作者:
[Mishra, Puneet, Nordon, Alison, Marshall, Stephen]
通讯作者:
Marshall, Stephen
DOI:
10.1109/access.2020.2969847
发表时间:
2020-01-01
期刊:
IEEE ACCESS
影响因子:
3.9
作者:
[Fabiyi, Samson Damilola, Vu, Hai, Marshall, Stephen]
通讯作者:
Marshall, Stephen
Superpixel based Feature Specific Sparse Representation for Spectral-Spatial Classification of Hyperspectral Images
高光谱图像光谱空间分类的基于超像素的特征特定稀疏表示
DOI:
10.3390/rs11050536
发表时间:
2019-03-01
期刊:
REMOTE SENSING
影响因子:
5
作者:
[Sun, He, Ren, Jinchang, Marshall, Stephen]
通讯作者:
Marshall, Stephen
DOI:
10.1007/s00138-017-0826-6
发表时间:
2017-02
期刊:
Machine Vision and Applications
影响因子:
3.3
作者:
[S. M. Z. A. Shah;S. Marshall;P. Murray]
通讯作者:
S. M. Z. A. Shah;S. Marshall;P. Murray
A new tool for bioimaging based on super-resolution Raman microscopy
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批准号:BB/S005056/1
-
项目类别:Research Grant
-
资助金额:$1.42万
-
财政年份:2018
-
负责人:Stephen Marshall
-
依托单位:
Incubators of Public Spaces
-
批准号:ES/M008495/1
-
项目类别:Research Grant
-
资助金额:$19.34万
-
财政年份:2014
-
负责人:Stephen Marshall
-
依托单位:
National Non-Human Primate Research Facility
-
批准号:nhmrc : 465373
-
项目类别:NHMRC Enabling Grants
-
资助金额:$20.54万
-
财政年份:2006
-
负责人:Stephen Marshall
-
依托单位:
海外基金