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Identification of the onset of disease within a potato crop using a UAV equipped with un-modified and modified commercial off-the-shelf digital cameras

Published online by Cambridge University Press:  01 June 2017

S. Gibson-Poole ,
S. Humphris ,
I. Toth  and
A. Hamilton
S. Gibson-Poole
Affiliation:
Scotland’s Rural College, Peter Wilson Building, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
S. Humphris
Affiliation:
The James Hutton Institute, Invergowrie Dundee DD2 5DA, UK
I. Toth
Affiliation:
The James Hutton Institute, Invergowrie Dundee DD2 5DA, UK
A. Hamilton
Affiliation:
Scotland’s Rural College, Peter Wilson Building, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
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Abstract

This paper investigates the effectiveness of using a UAV with dual commercial off-the-shelf (COTS) cameras, one un-modified and one modified to sense near infra-red (NIR) wavelengths to identify the onset of disease within a trial crop of potatoes. The trial was composed of 2 plots of 16 drills containing 12 tubers exposed to the blackleg disease-causing bacterial pathogen (Pectobacterium atrosepticum) in order to demonstrate best practise tuber storage and haulm destruction methods. Eleven sets of aerial data were gathered between 27/5/2016~29/7/2016 and compared with ground truth data collected on 14/7/2016. Visual analysis of the data could only detect the onset of disease and not the specific infection and resulted in a user accuracy (UA) of 83% and producer accuracy (PA) of 78%, with a total accuracy (TA) of 91% and Kappa coefficient (K) of 0.75. The building blocks of an automated classification routine have been constructed using pixel and object based image analysis (OBIA) methods, which have shown promising first results (UA 65%, PA 73%, TA 87%, K 0.61) but requires further refinement to achieve an equivalent level of accuracy as that of the visual analysis.

Keywords

UAVCOTSOBIAblackleg
Type
UAV applications
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 812 - 816
Copyright
© The Animal Consortium 2017 

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