Volatile Biomarkers for the Early Stage Disease Diagnosis of Sweet Potato Rhizopus Soft Tissue Disease

Metabolomics is a powerful tool that
can be used to understand
disease progression in animals or plants. Early diagnosis allows for
control or prevention procedures to be implemented that can attenuate
damage. In this study, we used a headspace solid-phase microextraction
coupled GC-MS based metabolomics workflow to diagnose the early stage of fungal soft tissue disease in
sweet potatoes. We analyzed the volatile compounds emitted from the Rhizopus stolonifer infected and noninfected sweet potatoes.
A data set consisting of 96 spectra was analyzed using chemometrics
to investigate fungal soft tissue disease. A combination of 4 biomarkers
was able to diagnose R. stolonifer fungal soft tissue
disease (AUC = 0.980, 95% C.I. = 0.937–1) and the early stage
of the fungal soft rot disease (AUC = 0.999, 95% C.I. = 0.978–1).
We were able to detect the putative biomarkers, 1-propanol, ethyl
alcohol, ethyl propionate, and 3-methyl-3-buten-1-ol, during disease
progression in a simulated warehouse environment. Therefore, this
study shows the feasibility of early diagnosis of fungal soft tissue
disease by real-time screening of volatile profiles of sweet potato
in postharvest storage. The suggested putative biomarkers could be
used to train a sensory device (e.g., E-nose) for early disease diagnosis
of sweet potato fungal soft tissue disease.