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.