Fire Blight Disease Detection for Apple Trees: Hyperspectral Analysis of Healthy, Infected and Dry Leaves

Hubert Skoneczny,Artur Mikiciński,Marcin Spiralski,Katarzyna Kubiak,Joanna Puławska,Jan Kotlarz

doi:10.3390/rs12132101

Hubert Skoneczny, Artur Mikiciński + Show 4 more

Open Access

https://doi.org/10.3390/rs12132101

Copy DOI

Journal: Remote sensing	Publication Date: Jun 30, 2020
Citations: 27	License type: CC BY 4.0

Affiliation: Łukasiewicz Research Network, Instytut Lotnictwa

Abstract

The effective and rapid detection of Fire Blight, an important bacterial disease caused by the quarantine pest E.amylovora, is crucial for today’s horticulture. This study explored the application of non-invasive proximal hyperspectral remote sensing (RS) in order to differentiate the healthy (H), infected (I) and dry (D) leaves of apple trees. Analysis of variance was employed in order to determine which hyperspectral narrow spectral bands exhibited the most significant differences. Spectral signatures for the range of 400–2500 nm were acquired with Thermo Scientific Evolution 220 and iS50NIR spectrometers. The selected spectral bands were then used to evaluate several RS indices, including ARI (Anthocyanin Reflectance Index), RDVI (Renormalized Difference Vegetation Index), MSR (Modified Simple Ratio) and NRI (Nitrogen Reflectance Index), for Fire Blight detection in apple tree leaves. Furthermore, a new index was proposed, namely QFI. The spectral indices were tested on apple trees infected by Fire Blight in a quarantine greenhouse. Results indicated that the short-wavelength infrared (SWIR) band located at 1450 nm was able to distinguish (I) and (H) leaves, while the SWIR band at 1900 nm differentiated all three leaf types. Moreover, tests using the Pearson correlation indicated that ARI, MSR and QFI exhibited the highest correlations with the infection progress. Our results prove that our hyperspectral remote sensing technique is able to differentiate (H), (I) and (D) leaves of apple trees for the reliable and precise detection of Fire Blight.

Highlights

Poland ranks fourth in global apple production, with approximately 2.5 million tonnes produced annually, and over 800,000 tonnes of which are allocated for export
The different colorued curves refer to the spectral signatures of healthy (H), infected (I) and dry (D) leaves
The difference between the signatures of healthy (H) and infected (I) leaves increased with the disease progression, in the green band (500 nm), NIR region (900–1300 nm) (Figures 2 and 3) and at the short-wavelength infrared (SWIR) water absorption peaks located at 1400 nm and 1900 nm (Figures 4 and 5)

Summary

Introduction

Poland ranks fourth in global apple production, with approximately 2.5 million tonnes produced annually, and over 800,000 tonnes of which are allocated for export. Pome fruit Fire Blight poses one of the greatest threats for the horticulture industry across the globe. Institutions such as the Main Inspectorate of Plant Health and Seed Inspection (MIPHI) in Poland have undertaken firm action on plant disease control. In 2017, over 121,000 field inspections at agricultural entrepreneurs were performed on plant health and pathogen presence control throughout Poland. There is a great and indisputable need for research concerning Fire Blight detection on apple trees in order to develop rapid and precise methods that are able to reduce horticultural losses. Field inspectors are at present in need of an innovative approach

Results

Discussion

Conclusion