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Hyperspectral Imaging sees Xf Bacteria and Highlights the Business Impact of Crop Disease

November 4, 2021

PZT-Aircraft_UMelbourneThe incurable crop disease Xylella fastidiosa (Xf) affects a variety of important crops including olive, almond, avocado, coffee, grapevine, citrus and many herbaceous and forest species worldwide. New research is developing rapid and accurate detection using hyperspectral imaging from airborne platforms.Headwall customer Prof. Pablo J. Zarco-Tejada, Professor of Precision Agriculture and Remote Sensing, at the University of Melbourne recently published an article in the university magazine Pursuit, Tackling a Global Crop Pandemic - From the Air. The article references Prof. Zarco-Tejada's recently published work, Divergent Abiotic Spectral Pathways Unravel Pathogen Stress Signals Across Species in Nature Communications, 12, Article number: 6088 (2021).

The University of Melbourne’s Airborne Remote Sensing Facility aircraft is equipped with two hyperspectral imagers and one thermal camera and can scan thousands of hectares in the visible, near- and thermal-infrared spectrum. Picture from Pursuit article.

Distinguishing a Global-Scale Crop Disease from Other Plant Stress

According to Prof. Zarco-Tejada, Xf is arguably "the greatest disease threat to food security and agricultural productivity worldwide".


In Apulia, Italy, Xf could cost $22 billion USD to control the outbreak there over the next 50 years. Prof. Zarco-Tejada says that the key to containing Xf is early detection, which is challenging because some infections don’t cause visual symptoms for 8-10 months, and during this period, the asymptomatic plants continue to be infectious. His team's new research is a step closer to developing a rapid and more accurate large-scale screening process of at-risk crop species by enhancing the effectiveness of airborne scanning that uses hyperspectral imaging.

Hyperspectral image data from an Airborne Remote Sensing Facility – HyperSens Lab flight. Picture from Pursuit article.

The Nature article shows that hyperspectral imaging and a novel algorithm can distinguish the disease from water-induced stress and increase Xf detection to up to 92 percent accuracy. According to Prof. Zarco-Tejada, global warming and international trade are causing unprecedented risks to agriculture, particularly with emerging and re-emerging pathogens that cause yield losses exceeding 30 per cent in food-deficit regions with fast-growing populations. At the same time, we need to increase global food production by 50 per cent in the next 30 years to achieve food security.