Related Experiment Video
Updated: Jun 30, 2025

On-Site Molecular Detection of Soil-Borne Phytopathogens Using a Portable Real-Time PCR System
Published on: February 23, 2018
A nondestructive asymptomatic early disease prediction method employing ROS-induced differential volatile emissions
Rittika Ray1, Shiv Shakti Singh1, Shri Ram Yadav1
1Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India.
Abstract:
Potatoes are a staple crop with many health benefits. Postharvest storage of potatoes takes a considerable amount of time. Potato dry rot is one of the most serious postharvest storage diseases, caused primarily by the fungus Fusarium sambucinum. It is possible to minimize losses if disease is detected early, which allows it to be controlled promptly. A phytopathogen infection can alter the volatile profile of plants. Identifying unique volatile organic compounds (VOCs) as biomarkers for early disease detection is an area of considerable research interest. In this study, we compared the VOC profiles of healthy and dry rot inoculated potatoes (cv. "Kufri Pukhraj") over a time course using gas chromatography-mass spectrometry (GC-MS). There were 29 differentially emitting VOCs between healthy and dry rot inoculated potatoes. Nevertheless, only four of these compounds (linalool tetrahydride, γ-muurolene, alloaromadendrene, and α-isomethyl ionone) were exclusively found in dry rot inoculated potatoes, and hence they were considered biomarkers. Furthermore, reactive oxygen species (ROS) levels were altered in potatoes that were inoculated with dry rot, suggesting a role for ROS signaling in differential VOC emissions. In the early stages of dry rot infection, when symptoms were barely visible, these four biomarker VOCs were robustly useful in distinguishing healthy and dry rot-infected potatoes. These novel biomarkers associated with this disease are promising candidates for non-destructive detection of dry rot in stored potatoes at an early asymptomatic stage. These biomarkers can be used to develop an e-nose sensor to predict dry rot in the future.

