Abstract
Detecting volatile organic compounds (VOCs) in real-time can assist in monitoring and detection of potato rot pathogens in bulk storage facilities. Early detection of diseases allows the application of precise management strategies to reduce crop losses. In order to use the emission of VOCs from potato tubers to monitor storage conditions and extend the storage duration, which potentially can reduce losses and enhance growers' profit, it is critical to study the variability and distribution in volatile profile patterns within the potato pile in the storage building, prior to the detection of rot. Thus, a custom-built volatile sampling unit was developed for capturing VOCs from the storage environment. In addition, a thorough evaluation of the spatial variability and distribution of VOCs emitted by potato tubers was performed. Using the VOC sampling unit, 20 samples of air (potato pile headspace) were collected across an 81 x 14 m storage bay in Tedlar (R) bags with an approximately 10.5 m between sampling points, at two time points (tp1 and tp2, January and March 2024, respectively). The samples were analyzed using field asymmetric ion mobility spectrometer (FAIMS) and the FAIMS's ion current intensity data were evaluated. VOCs showed significant variability across the evaluated area in the storage facility, with coefficients of variation of about 82% and 78% at tp1 and tp2, respectively. Experimental semivariograms revealed spherical and Gaussian were the best-fitted models for data from tp1 and tp2, respectively. Among the interpolation techniques, it was also found that the ordinary kriging was better in capturing the spatial variability and the distribution of the VOC profile compared to the inverse distance weighting. The study describes the successful development of the sampling unit, and assessment of the spatial distribution of VOCs in a commercial storage facility. Continuous sampling across space and time is recommended to detect and identify the diseases in stored potato tubers. Such techniques are critical in improving storage facility management and minimizing post-harvest losses.