Plant Pathology Journal最新文献

The soil-borne pathogen Rhizoctonia solani is one of the most devastating necrotrophic pathogens worldwide, responsible for causing rice sheath blight (RSB). This pathogen has a broad host range, affecting economically important monocots and dicots such as rice, wheat, potato, soybean, sugar beet, and cucumber. Despite extensive screening of rice germplasm, genes that confer full resistance to RSB have rarely been identified, leading to slow progress in breeding resistant varieties. To identify RSB-resistant rice cultivars in Korea, variations in quantitatively inherited resistance have been observed. We conducted a study to visually assess the RSB resistance phenotypes of 250 cultivated varieties under natural disease conditions in the field over several years. Notable candidates included P1401, which showed resistance, while Junam was susceptible. To identify the quantitative trait loci (QTLs) associated with resistance, we developed an F2 mapping population by crossing P1401 and Junam, followed by bulked segregant analysis. These QTLs were mapped to specific locations on seven of the 12 rice chromosomes. This mapping population and the resulting datasets provide valuable resources for advancing genomic research in rice, particularly for marker-assisted breeding strategies for enhancing resistance to R. solani and other important agronomic traits.

Chili pepper (Capsicum annuum L.), one of the most economically important vegetable crops globally, faces significant economic risks from anthracnose, leading to yield losses of 10% as well as decreasing marketability. Early and accurate detection is essential for mitigating these effects. Recent advancements in deep learning, particularly in image recognition, offer promising solutions for plant disease detection. This study applies deep learning models-MobileNet, ResNet50v2, and Xception-using transfer learning to diagnose anthracnose in chili peppers. A key challenge is the need for large, labeled datasets, which are costly to obtain. The study aims to identify the minimum dataset size required for accurate and efficient disease diagnosis using limited data. Performance metrics, including precision, recall, F1-score, and accuracy, were evaluated across different dataset sizes (500, 1,000, 2,000, 3,000, and 4,000 samples). Results indicated that model performance improves with larger datasets, with ResNet50v2 and Xception requiring more data to achieve optimal accuracy, while MobileNet showed strong generalization even with smaller datasets. These findings underscore the effectiveness of transfer learning-based models in plant disease detection, offering practical guidelines for balancing data availability and model performance in agricultural applications. Source code available at https://github.com/smart-able/Anthracnose.git.

Erwinia amylovora, first identified in 1793 in Hudson Valley (New York, USA), has a genome size of 3.7-4.0 Mb. E. amylovora bacterial strains are classified based on the infecting hosts: the Amygdaloideae-infecting (AI) group, targeting apple and pear trees, and the Rubus-infecting group, affecting berry trees. Since the AI-group strains display high genetic similarity (˃99.7%), it is challenging to characterize their genotypes. This study investigated the genetic diversity of E. amylovora isolates in Korea and the regional distribution patterns of genotypes using a multilocus variable number of tandem repeat analysis (MLVA). Four specific primers were used to amplify and sequence tandem repeats in the E. amylovora genome, and a distribution map of E. amylovora was created using MLVA genotypes. Thirty-two types of MLVA patterns were identified in Korean strains, and RV19 was the dominant type identified in all South Korean regions. According to the minimal spanning tree, genotypes were differentiated into RV7, RV14, RV20, RV22, and RV27 types, originating from the RV19 type. This finding suggests that the RV19 type, introduced to Korea for the first time, spread to other regions from Anseong-si, Cheonan-si, Chungju-si, and Jecheon-si, depending on the type. We determined the MLVA genotypes of E. amylovora isolates and distribution patterns by region from 2019 to 2023. The distribution of these genotypes by year and region provides basic information for the genetic diversity and spread of E. amylovora in Korea.

Xanthomonas arboricola pv. pruni (Xap) causes the shot hole disease of stone fruits and almonds. This bacterium is a damaging, widespread pathogen distributed across the major stone fruit producing regions of the world. To control shot hole disease, antibiotics such as streptomycin are mainly used. However, as concerns about antibiotic resistance increase, many restrictions are placed on the use of antibiotics. Additionally, it has been reported that the rise in temperature due to climate change affects disease occurrence and ecology. Therefore, in this study, we determined the minimum inhibitory concentration (MIC) of streptomycin for Xap at an optimal growth temperature of 28°C and investigated the changes in MIC and the occurrence frequency of resistant bacteria at 10°C, 25°C and 30°C. The results of this study showed that the MIC was 30 µg/ml at 28°C. In addition, when the change in streptomycin resistance concentration due to temperature was confirmed, we found that the resistance concentration decreased to 10 µg/ml at 30°C. When the occurrence of resistance according to concentration and temperature conditions was investigated, the occurrence frequency of resistant strains was found to be the highest at 50 µg/ml. In the case of temperature, the occurrence frequency of resistant strains was confirmed to be high at 30°C. These results provide basic data for further reducing the problem of antibiotic resistance by suggesting the possibility of changes in the occurrence of streptomycin-resistant strains depending on the antibiotic treatment environment.

Hop stunt viroid (HSVd) is a major pathogen that affects grapevine health and causes substantial economic losses in grape cultivation. Many studies have been conducted to control grapevine diseases, but effective control methods after plant infections remain lacking. This study aimed to assess the antiviral potential of garlic extract, a natural substance that inhibits HSVds in grapevine plants after micropropagation. Garlic extract was diluted 1,000-fold and applied to grapevine plants, and its effect on HSVd accumulation was evaluated using reverse transcription polymerase chain reaction and digital PCR. The results showed that HSVd accumulation was significantly reduced, with an inhibition rate of 74.45%; meanwhile, higher garlic extract concentrations resulted in contamination and plant damage. Nanopore sequencing confirmed that the integrity of the HSVd genome was compromised after treatment. Furthermore, garlic extract inhibited the HSVd and promoted plant growth by enhancing shoot and root development. Additionally, inhibition of the HSVd was sustained in regenerated grapevine plants. Moreover, the garlic extract showed inhibitory effects against HSVds in natural host cucumber plants. These results suggest that garlic extract could be a cost-effective and sustainable alternative for viroid control in grapevine cultivation, providing long-term protection and broader antiviral activity across plant species.

Begomoviruses have significantly threatened many important crops worldwide, causing substantial issues for years. New viruses from this genus are frequently identified, displaying increasingly harmful traits. Among the numerous species within this group, Tomato leaf curl New Delhi virus (ToLCNDV) stands out as a particularly dangerous member due to its notable pathogenic characteristics. This virus poses a serious threat to crops, leading to considerable economic losses. Although ToLCNDV has not been detected in Korea, there is no definitive assurance that it will not appear in the future. Thus, understanding the features and mechanisms of this virus, alongside extensive research on ToLCNDV characteristics and the development of effective preventive strategies, is essential. This review underscores key aspects of ToLCNDV, stressing the risks this virus poses to agriculture. Furthermore, recent advances in breeding natural resistance in key crops are discussed, offering a foundation for improved control methods and preparedness in regions currently unaffected, such as Korea, to mitigate potential agricultural impacts should the virus emerge.

Viral diseases have emerged as a serious threat to cherry trees production in Iran. To determine which virus(es) are present, three leaves from a sweet cherry tree (Qz5) with diffuse white blotch spots and deformation were subjected to high-throughput sequencing. After de novo assembly, blast analysis revealed that 12 contigs ranging from 360 to 7,433 nucleotides (nts) shared 78-96% nt identities with Capillovirus alphavii (cherry virus A, CVA) and seven contigs, ranging from 350 to 6,844 nts, shared 79-88% nt identities with Tepovirus tafpruni (prunus virus T, PrVT). During a survey, CVA, PrVT, and CVA + PrVT infections were detected in 12.6%, 5.1%, and 7.9% of 724 sour and sweet cherry samples. Phylogenetic analysis revealed that Iranian CVA was grouped into GIIIB, whereas PrVT fell into a distinct branch, which was confirmed by diversity plots. The within-population diversity was lower than the between-population diversity suggesting the contribution of a founder effect on diversification of CVA isolates. Host-specific codon adaptation analysis revealed the highest adaptation of CVA to sour cherry. This could suggest that sour cherry may be one of the closest Prunus species to wild progenitors. It raises the possibility that viruses such as CVA may have exerted evolutionary pressures influencing domestication processes. Additionally, the similarity index indicated that the common plum (Prunus domestica) may have exerted significant evolutionary pressure on CVA and PrVT. The association of CVA and PrVT was reported for the first time in the mid-Eurasian region, specifically in Iran, which represents an issue in phytosanitary certification of cherry plants.

Rice (Oryza sativa), a staple crop worldwide, is severely threatened by bacterial panicle blight caused by Burkholderia glumae, leading to substantial yield losses. The lack of effective chemical treatments and resistant rice cultivars highlights the urgent need for alternative solutions. In this study, 1,134 plant extracts were screened for antibacterial activity against B. glumae using agar disc diffusion and liquid broth assays. Thirty-three extracts exhibited significant growth inhibition on agar plates. These 33 extracts were further tested in Luria- Bertani broth, where five showed notable activity, and two extracts-Trapa japonica (FBCC-EP312) and Rumex crispus (FBCC-EP487)-were selected for detailed analysis. Both extracts significantly reduced bacterial motility and disease severity in rice, while having no effect on non-target bacteria such as Escherichia coli. These findings highlight the potential of these plant-derived compounds as effective biocontrol agents, offering an eco-friendly alternative to synthetic pesticides and promising applications in sustainable agriculture.

Xanthomonas euvesicatoria has become a serious problem in Physalis pubescens, leading to substantial crop losses. In our previous investigation, we used rapid molecular detection techniques to identify X. euvesicatoria; however, this pathogen's diversity and population structure remain poorly understood, despite their importance in disease management. To address this knowledge gap, we analyzed the diversity of X. euvesicatoria using BOX-PCR and ERIC-PCR fingerprinting techniques. A total of 103 isolates were collected from 13 counties across Heilongjiang province during the 2018 and 2019 growing seasons. Our findings revealed 635 unique genetic patterns from ERIC-PCR fingerprinting, compared to 360 patterns from BOX-PCR. BOX-PCR analysis identified 12 distinct genotypic clusters, whereas ERIC-PCR identified 14 clusters through unweighted pair group approach with arithmetic average analysis, demonstrating substantial genetic variability. STRUCTURE analysis further identified five distinct genetic clusters in the BOX-PCR data and two in the ERIC-PCR data. The Hailin isolates showed the highest level of diversification compared to other regional isolates. AMOVA results indicated that 85% of the genetic variation in BOX-PCR was attributable to within-population differences, while 78% of ERIC-PCR variation was due to differences across populations. In addition, a Mantel test demonstrated a tenuous correlation between BOX-PCR and ERIC-PCR genetic markers, indicating distinct genetic profiles. This extensive genetic information enhances our understanding of the epidemiology of bacterial leaf spot and its potential therapeutic prospects. These data can provide insights into Xanthomonas strains' diversity and geographical dissemination.

Plasmopara viticola causes grape downy mildew, one of the most notorious diseases of cultivated grapes that damage vineyards worldwide. The pathogen secretes various effector molecules to infect and modulate the host biological processes. In this study, we aimed to evaluate the roles of KPvRxLR27, an arginine-any amino acid-leucine-arginine (RxLR) effector isolated from P. viticola JN-9 from Jeonju (South Korea) with respect to the reported Bcl-2-associated X and inverted formin1in inducing cell death in non-host Nicotiana benthamiana and resistant grape host cultivars via Agrobacterium-mediated transient transformation. We found that, KPvRxLR27 induced programmed cell death in N. benthamiana and rapid hypersensitive response in resistant grape cultivars. Agroinfiltration assay revealed that putative N-glycosylation at the N186 amino acid sequence and nuclear localization signal motifs at the C-terminus were critical for the effector's cell death-inducing activity of KPvRxLR27. Overexpression assay revealed that KPvRxLR27 was abundantly expressed in the plasma membrane and nuclear regions and activated the accumulation of reactive oxygen species in N. benthamiana. Moreover, KPvRxLR27 expression was significantly delayed in the resistant cultivar than in the susceptible cultivar. Our results suggest KPvRxLR27 as a potential avirulence gene recognized by the host receptors to activate the host immune response-associated genes, providing valuable insights to enhance the pathogen resistance of commercial cultivars.