Detecting Pathogenic Phytophthora Species Using Volatile Organic Compounds.

Area of Science:

• Plant Pathology
• Mycology
• Analytical Chemistry
• Forest Science

Background:

• Invasive Phytophthora species pose significant threats to forest ecosystems worldwide.
• Current detection methods for plant pathogens are often slow and not high-throughput.
• Early and rapid detection tools are crucial for preventing the spread of tree diseases.

Purpose of the Study:

• To investigate the potential of volatilomics for differentiating Phytophthora species.
• To discriminate between healthy and Phytophthora-inoculated forest trees (European beech and pedunculate oak).
• To identify volatile organic compounds (VOCs) indicative of specific Phytophthora species and infection.

Main Methods:

• Solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was employed.
• Volatile profiles of eight Phytophthora species were analyzed in vitro.
• Volatile profiles of healthy and inoculated European beech and pedunculate oak seedlings were compared.

Main Results:

• Fourteen VOCs were tentatively identified that differentiated between eight Phytophthora species in vitro.
• Most Phytophthora species produced unique compounds, with Phytophthora polonica showing the most distinct profile.
• Inoculated seedlings exhibited distinct volatile profiles from healthy controls, identifiable by isokaurene, anisole, and unknown compounds.

Conclusions:

• Volatilomics is a promising approach for the rapid screening of plant material for Phytophthora pathogens.
• VOC analysis can effectively differentiate between various Phytophthora species and healthy vs. diseased trees.
• This method supports the development of advanced tools for early detection and management of forest tree diseases.