To control soil-borne disease, chemical fungicide and soil fumigation using methyl bromide were widely applied before. However, because of fungicide resistance development and environmental constraints, integrated management system including sanitation and legal methods is necessary for soil-borne disease management (Panth et al., 2020). One of the effective methods to prevent soil-borne disease is to use resistant cultivars. Resistance genes against soil-borne fungal pathogens have been discovered in cucurbitaceous crops, and increased resistance was successfully obtained by breeding and grafting (Ayala-Doñas et al., 2020). Biofumigation has been noticed as an eco-friendly control method for soil-borne disease. The control effects of biofumigation using plant-derived material have been confirmed in field (Ji et al., 2024).

In practice, disease detection in farms still depends largely on visible symptoms and signs. Since infections begin belowground, symptoms appear only at advanced stages, leading to severe losses and emphasizing the need for early diagnosis. Several detection techniques have been developed for plant pathogens (Venbrux et al., 2023). Among these, polymerase chain reaction (PCR)-based methods, including conventional PCR and quantitative PCR (qPCR), are widely applied for the detection of soil-borne pathogens (Chen et al., 2024). Reliable application of PCR assays requires effective genomic DNA (gDNA) extraction because inhibitors such as polysaccharides and humic acids are often co-extracted from soil (Venbrux et al., 2023). Although several extraction protocols and commercial kits have been evaluated (Wydro, 2022), most are time-consuming, laboratory-oriented, or costly, restricting their use for on-site diagnosis.

Previously, qPCR primers targeting eight soil-borne or apple-associated fungal pathogens—Alternaria tenuissima (At), Botryosphaeria dothidea (Bd), Fusarium oxysporum (Fo), Glomerella cingulata (Gc), Phytophthora cactorum (Pc), Rosellinia necatrix (Rn), Sclerotium rolfsii (Sr), and Sclerotinia sclerotiorum (Ss)—were developed (Kwon and Kim, 2025). In this study, a simple and rapid method for gDNA extraction from soil-mycelial mixtures of these pathogens was established, allowing direct application of the previously designed primer sets for field diagnostics (Fig. 1A).

We prepared a cetyltrimethylammonium bromide (CTAB)-based gDNA extraction buffer, as CTAB functions both as a detergent facilitating cell lysis and as a precipitant that removes polysaccharides and polyphenolic compounds. Polyvinylpolypyrrolidone was supplemented in the buffer to eliminate humic acids, which are major inhibitors in soil extracts (Cullen and Hirsch, 1998). To enhance cell lysis efficiency, sodium dodecyl sulfate (SDS) was also supplemented as an additive (Feng et al., 2010), however, since SDS tends to form insoluble complexes with CTAB, it was added separately to the sample prior to extraction (Table 1). Of the various methods reported for fungal cell lysis (Karakousis et al., 2006; Klimek-Ochab et al., 2011), bead beating and sonication are effective, but they are difficult to implement in the field. Thermolysis at 85°C has been shown to release gDNA from fungal cells (Zhang et al., 2010). Because portable heating blocks can be conveniently operated in the field, a brief heating step was adopted for cell lysis. However, thermolysis alone was insufficient for rapid extraction; therefore, one 5 mm steel bead and 0.05 g of glass beads were added to promote mechanical disruption.

For each extraction, 0.1 g of soil (approximately 500 μL) from pots of apple seedlings and 10 mg of fungal mycelia grown on complete medium (CM) agar (Molinari and Talbot, 2022) were combined in a 2 mL microtube containing the beads and 800 μL of extraction buffer. Samples were vortexed for 30 s, heated at 95°C for 1 min, and vortexed again for 30 s. Crude extracts were collected by brief centrifugation using a mini-centrifuge.

To remove PCR inhibitors, the crude extracts were treated with Q-Sepharose, which efficiently binds soil-derived contaminants (Sharma et al., 2007). Five hundred microliters of prewashed Q-Sepharose (Cytiva, Marlborough, MA, USA) were mixed with the extract, vortexed for 10 s, and centrifuged briefly. However, target pathogens were not detected within 40 cycles of qPCR under the conditions described in Supplementary Table 1, suggesting that additional purification was needed. The supernatant was therefore subjected to further purification using DaBead™ Magnetic Bead Si (Biofact, Daejeon, Korea). Twenty microliters of beads were added, vortexed, incubated for 30 s at room temperature, and separated with a magnetic stand. DNA-bound beads were washed with 500 μL of 80% ethanol, and ethanol was removed using the magnetic stand. Residual ethanol was eliminated by brief centrifugation and using magnetic stand, and DNA was eluted in 30 μL of distilled water after vortexing for 10 s and incubation for 30 s. The entire extraction procedure required approximately 20 min for 10 samples (Fig. 1B).

Detection of target pathogens was conducted by qPCR using soil-only samples as negative controls and recombinant plasmids as positive controls (Kwon and Kim, 2025). All target pathogens were detected within 30 cycles (Fig. 2A, Table 2). Among them, A. tenuissima and S. rolfsii showed the lowest Cq values (~22), while others ranged from 25 to 28. Negative controls consistently showed Cq over 30, indicating that 30 cycles can serve as a threshold for pathogen detection in soil. Mean Cq values of positive and test samples were significantly different from those of negative controls (Tukey’s test, P < 0.05). DNA purity was assessed by measuring A260/280 and A260/230 ratios at each purification step. The A260/230 ratio increased approximately threefold after purification (Supplementary Table 2), while the A260/280 ratio slightly decreased, possibly due to reduced DNA concentration.

The applicability of the extraction protocol without the Q-Sepharose purification step was evaluated using four pathogens: B. dothidea, F. oxysporum, G. cingulata, and P. cactorum which showed mean Cq over 27 in samples. gDNA was extracted and directly purified using magnetic beads, followed by qPCR detection. All target pathogens were successfully detected within 30 amplification cycles; however, the mean Cq values of B. dothidea and G. cingulata exceeded 28, and F. oxysporum reached nearly 30 (Supplementary Table 3). These results indicate that Q-Sepharose treatment is not essential but reduces soil-derived inhibitors that interfere with qPCR reactions. Therefore, a syringe filter packed with Q-Sepharose may be applied in soil-borne disease detection kits, or the step can be omitted depending on the target pathogen and cost considerations.

In addition to mycelia, other fungal structures can serve as inocula in soil-borne diseases. Sclerotia, the main overwintering structures of S. rolfsii, are primary inocula in soil (Kator et al., 2015). Sclerotia of S. rolfsii collected from 7-day-old CM agar cultures were processed using the same extraction protocol. qPCR results confirmed successful detection of sclerotial DNA with Cq approximately 25 (Fig. 2A, Table 2), suggesting that the developed method could be applied for early detection of overwintering sclerotia before disease onset. Conidia of F. oxysporum are important for disease dissemination and virulence (Uddin et al., 2023). Infection can be achieved experimentally with 10⁶ conidia mL⁻¹ (Choi and Ahsan, 2022; Shin et al., 2023). Conidia were harvested from 5-day-old cultures in carboxymethyl cellulose broth and diluted to 10⁴ cells μL⁻¹ using a hemocytometer. Then, 0.1 g of soil was mixed with 100 μL of suspension (10⁶ conidia per sample). gDNA extraction and qPCR detection were performed as described above, and gDNA of F. oxysporum from conidial samples was detected at approximately 31 cycles (Fig. 2A, Table 2). Given that the infection by F. oxysporum could be achieved by 10⁶ conidia per one milliliter, it would be difficult to apply this developed extraction method for conidia detection in field. Previous study showed that glass bead milling is effective for conidial cell lysis (Haugland et al., 1999). However, it is doubtful that same method is still effective for diagnosis using field soil sample. Taken together, gDNA extracted from mycelia of the eight pathogens using developed method was successfully amplified by qPCR and discriminatively detected compared to extracts from soil without mycelia (Fig. 2B).

To evaluate detection sensitivity, mycelial input was reduced to 1 mg for P. cactorum, R. necatrix, S. rolfsii, and S. sclerotiorum. gDNA extraction and qPCR detection were performed using the same protocol. The Cq values for P. cactorum, R. necatrix, and S. rolfsii were below 30, though higher variability was observed for P. cactorum and R. necatrix (Fig. 3, Supplementary Table 4). For S. sclerotiorum, Cq values were significantly different from those of negative controls but exceeded 30 on average.

Sensor-based approaches have recently been explored for plant disease detection. Wei et al. (2021) reported that sensors analyzing spectral signatures, thermal images, and volatile organic compounds can detect peanut stem rot caused by S. rolfsii. However, these approaches often face difficulty distinguishing responses to abiotic stress or non-target pathogens. Therefore, nucleic acid-based techniques remain reliable tools for soil-borne disease detection.

Various fungal gDNA extraction methods from soil have been proposed. However, most existing soil DNA extraction protocols are designed for microbiome studies, focusing on yield and purity rather than speed or portability. Fatima et al. (2014) used mannitol in the extraction buffer to obtain high-quality gDNA from rhizospheric soil, but their protocol required two days for completion. Cheng et al. (2016) achieved soil contaminant removal using multiple pre-washing and calcium flocculation steps, but the entire process also required several hours and organic solvents for purification, which is unsuitable for field use.

In this study, we developed a rapid and simple gDNA extraction method using only a heat block, vortex mixer, and mini-centrifuge. The method enables efficient gDNA extraction and reliable detection of soil-borne fungal pathogens, and it is expected to facilitate field-based diagnostics for soil-borne disease management.