Speeding Up Xf Bacteria Detection

Ernie NeffDiseases

Xylella fastidiosa (Xf) bacterium causes incurable diseases that make plants wither and possibly die, scorching and browning leaves and reducing the size of fruit in a wide variety of important crops. Citrus variegated chlorosis is among the diseases that Xf causes.

Pablo J. Zarco-Tejada and Tomas Poblete with the University of Melbourne describe the Xf bacterium as “the number one biological security threat to Australian agriculture.” They report on their research into early detection of Xf in the following excerpts from a University of Melbourne article they wrote.

Xf is arguably the greatest disease threat to food security and agricultural productivity worldwide. Already widely distributed in the Americas, it has been identified in Spain, France, Israel, Iran and Taiwan.

The key to containing Xf is early detection, which isn’t easy given that some infections don’t cause visual symptoms until eight to 10 months. And during this period, the asymptomatic plants continue to be infectious.

But new research takes us 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 images allow us to “see” in more fine-grained wavelengths. Our previous research has already demonstrated that we can use it to detect Xf in olive trees before symptoms were visible. But a common problem is that the remote sensing algorithms that scan the hyperspectral images can’t always distinguish the symptoms of Xf from the symptoms of other pathogens or environmental stress like lack of water or nutrients.

Published in Nature Communications, our research with international partners from the European Union, United Kingdom, and the United States demonstrates that hyperspectral imaging and a novel algorithm can distinguish the disease from water-induced stress and increase Xf detection to up to 92% accuracy while reducing uncertainty to below 6% across different hosts.

The technology used in this study is available in Australia as part of our Airborne Remote Sensing Facility – HyperSens Lab at the University of Melbourne.

In a trial in Victoria last year, we were able to scan several thousand hectares of healthy almond, citrus and olive trees with varying water and nutrient status levels as baselines to better adapt the Xf detection models developed in Europe for the particular varieties and management practices in Australian agriculture.

These methods enable the collection and delivery to the grower of water stress and nutrient maps for each tree in an orchard within 24 hours. And in the context of biosecurity, if an Xf outbreak occurs in Australia or elsewhere, our methods could potentially be used to rapidly detect and prevent the spread of the disease.

Source: University of Melbourne

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