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Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

1
Precision Agriculture Research Group (PARG), University of New England, Armidale, NSW 2351, Australia
2
Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, Brisbane, QLD 4001, Australia
3
Stahmann Farms, McDougall Street., Toowoomba, QLD 4350, Australia
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(2), 226; https://doi.org/10.3390/rs10020226
Received: 28 November 2017 / Revised: 25 January 2018 / Accepted: 26 January 2018 / Published: 1 February 2018
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
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Abstract

Phytophthora root rot (PRR) infects the roots of avocado trees, resulting in reduced uptake of water and nutrients, canopy decline, defoliation, and, eventually, tree mortality. Typically, the severity of PRR disease (proportion of canopy decline) is assessed by visually comparing the canopy health of infected trees to a standardised set of photographs and a corresponding disease rating. Although this visual method provides some indication of the spatial variability of PRR disease across orchards, the accuracy and repeatability of the ranking is influenced by the experience of the assessor, the visibility of tree canopies, and the timing of the assessment. This study evaluates two image analysis methods that may serve as surrogates to the visual assessment of canopy decline in large avocado orchards. A smartphone camera was used to collect red, green, and blue (RGB) colour images of individual trees with varying degrees of canopy decline, with the digital photographs then analysed to derive a canopy porosity percentage using a combination of ‘Canny edge detection’ and ‘Otsu’s’ methods. Coinciding with the on-ground measure of canopy porosity, the canopy reflectance characteristics of the sampled trees measured by high resolution Worldview-3 (WV-3) satellite imagery was also correlated against the observed disease severity rankings. Canopy porosity values (ranging from 20–70%) derived from RGB images were found to be significantly different for most disease rankings (p < 0.05) and correlated well (R2 = 0.89) with the differentiation of three disease severity levels identified to be optimal. From the WV-3 imagery, a multivariate stepwise regression of 18 structural and pigment-based vegetation indices found the simplified ratio vegetation index (SRVI) to be strongly correlated (R2 = 0.96) with the disease rankings of PRR disease severity, with the differentiation of four levels of severity found to be optimal. View Full-Text
Keywords: avocado; canopy porosity; RGB image gap analysis; phytophthora root rot disease (PRR); vegetation indices worldview-3; multispectral satellite imagery avocado; canopy porosity; RGB image gap analysis; phytophthora root rot disease (PRR); vegetation indices worldview-3; multispectral satellite imagery
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Salgadoe, A.S.A.; Robson, A.J.; Lamb, D.W.; Dann, E.K.; Searle, C. Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis. Remote Sens. 2018, 10, 226.

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