Search Results (50)

In November 2022, black-root and stem-rot symptoms were observed on the strawberry cultivar ‘Ssanta’ in Hohhot, Inner Mongolia Autonomous Region, China. In order to identify the causing agent of strawberry root rot, and select effective fungicides for controlling this disease, this study was carried out. The associated fungi were isolated from diseased strawberry plants, and the isolate that fulfilled Koch’s postulates was further identified based on morphological characteristics, together with the internal transcribed spacer regions and 28S rDNA sequences; then, the inhibitory activities of 11 commercial fungicides on the pathogenic strain were screened based on the mycelium growth method. Results showed that six candidate strains were isolated from diseased strawberry, and only the isolate CMGF-A caused typical root and stem rot on strawberry. The CMGF-A showed typical morphology of Acrostalagmus species, and sequence analyses revealed it as A. luteoalbus. The prochloraz was selected as the primary fungicide for effectively controlling CMGF-A, while tebuconazole, thiophanate-methyl, and difenoconazole·azoxystrobin could be used as alternatives. A. luteoalbus was previously reported to cause potato tuber disease, and red rust of needle mushroom, this work is the first report of A. luteoalbus causing strawberry root rot worldwide. This study provided helpful information for the diagnosis and management of strawberry root rot disease. Full article

Grapevine leaf rust (GLR) in temperate Asia is caused by Neophysopella meliosmae-myrianthae and N. montana; the former is commonly found on commercial grape cultivars (Vitis spp.) and the latter on a wild grape species, Vitis coignetiae. The two GLR fungi were found to co-occur in V. coignetiae at two survey sites in Japan. Under experimental conditions, both fungi parasitize and develop into uredinial and telial stages on commercial grape cultivars and wild species. Despite the assumed involvement of N. montana in GLR symptoms in commercial vineyards, there has been no confirmed report of its incidence, and it is not clear whether N. meliosmae-myrianthae commonly occurs on V. coignetiae under natural conditions. In this study, we aimed to disclose the occurrence and, in particular, the co-occurrence of the two species in a wide array of commercial grape cultivars and V. coignetiae in Japan based on the detection of targeted DNA markers with specific PCR primer pairs. This study confirmed the occurrence of only N. meliosmae-myrianthae infection in symptomatic samples of grape cultivars, while the co-occurrence was observed only in V. coignetiae. Neophysopella montana was widely detected in V. coignetiae specimens. Full article

Tan spot (Pyrenophora tritici-repentis) and stripe rust (Puccinia striiformis f. sp. tritici) are major foliar diseases of wheat, causing significant yield losses globally. This study evaluated the efficacy of fungicide seed treatments in managing these diseases during early growth stages under greenhouse, growth chamber, and field conditions in the Northern Great Plains. Winter and spring wheat cultivars were treated with pyraclostrobin or combinations of thiamethoxam, difenoconazole, mefenoxam, fludioxonil, and sedaxane, among others. Greenhouse and growth chamber plants were inoculated with the respective pathogens, while field trials relied on natural inoculum. Fungicide treatments significantly reduced stripe rust severity (up to 36%) (p ≤ 0.05) and moderately reduced tan spot severity during early growth stages (15–20%). Treated plants demonstrated a 30–40% improvement in plant vigor, and a 25–50% increase in winter survival. Additionally, grain yield in treated plots increased by 25–50% (p ≤ 0.05), with test weight and protein content improving by 10% and 15%, respectively. These findings demonstrate the potential of fungicide seed treatments as an integrated pest (or pathogen) management (IPM) strategy to enhance early foliar disease control and wheat productivity. Full article

The main diseases that affect coffee production worldwide are coffee leaf rust (CLR) and coffee berry disease (CBD), caused by fungi Hemileia vastatrix and Colletotrichum kahawae, respectively. The identification of cultivars with stacking resistance genes is of paramount importance for the control of these diseases. This work aimed to profile the phenotypic and genetic resistance of 160 genotypes belonging to 36 commercial coffee cultivars from five Central American countries regarding resistance to races II and XXXIII of H. vastatrix through phenotypic evaluation and evaluations associated with the genetic loci of resistance to CLR and CBD by molecular markers. Of the 160 genotypes from Central America evaluated, 26.25% presented genes stacked to the three loci of resistance to CLR and the locus of resistance to CBD, and resistance to races II and XXXIII when inoculated with urediniospores. In addition, 14 genotypes were identified with the presence of the S_H3 gene, whose resistance has not yet been broken. This work revealed errors in passport data or hybridizations in cultivars and even possible resistance breakdown in the Catimor genetic group. These results are essential to the search for strategies in coffee genetic breeding programs. Full article

A newly discovered rust fungus poses a significant threat to the survival and reproduction of the endangered plant Cystopteris chinensis in a forest in western Sichuan province, China. This study utilized both morphological analysis and molecular phylogenetic approaches to classify this fungal taxon. Artificial inoculation experiments, which involved sampling uredia from the field, were conducted to fulfill Koch’s postulates. Our results designate this rust fungus as a novel species within the Pucciniastraceae family, named Hyalopsora erlangensis A. Yu & X.H. Chen. Morphological features, including hyaline peridia cells, yellowish urediniospores, dark brown amphispores with three germ pores, and pigmented cytoplasm, differentiate this species from others in the genera Milesina, Uredinopsis, and Pucciniastrum. Phylogenetic analysis, based on internal transcribed spacer (ITS) sequences and 28S rDNA gene fragments, further confirms its distinctiveness from other Hyalopsora species, supported by high maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI) bootstrap values. Artificial inoculation both in the field and in tissue-cultured seedlings verified this fungus as the causative agent of C. chinensis rust disease. Our research not only identifies the pathogen but also offers fundamental insights for fern rust diversity, and the future management and conservation of this endangered fern, aiming to mitigate the impact of this devastating rust. Full article

Maize is one of the most widely grown crops in Ethiopia and is a staple crop around the globe; however, common rust maize disease (CRMD) is becoming a serious problem and severely impacts yields. Conventional CRMD detection and treatment methods are time-consuming, expensive, and ineffective. To address these challenges, we propose a real-time deep-learning model that provides disease detection and pesticide dosage recommendations. In the model development process, we collected 5000 maize leaf images experimentally, with permission from Haramaya University, and increased the size of the dataset to 8000 through augmentation. We applied image preprocessing techniques such as image equalization, noise removal, and enhancement to improve model performance. Additionally, during training, we utilized batch normalization, dropout, and early stopping to reduce overfitting, improve accuracy, and improve execution time. The optimal model recognizes CRMD and classifies it according to scientifically established severity levels. For pesticide recommendations, the model was integrated with the Gradio interface, which provides real-time recommendations based on the detected disease type and severity. We used a convolutional neural network (CNN), specifically the ResNet50 model, for this purpose. To evaluate its performance, ResNet50 was compared with other state-of-the-art algorithms, including VGG19, VGG16, and AlexNet, using similar parameters. ResNet50 outperformed the other CNN models in terms of accuracy, precision, recall, and F-score, achieving over 97% accuracy in CRMD classification—surpassing the other algorithms by more than 2.5% in both experimental and existing datasets. The agricultural experts verified the accuracy of the recommendation system across different stages of the disease, and the system demonstrated 100% accuracy. Additionally, ResNet50 exhibited lower time complexity during model development. This study demonstrates the potential of ResNet50 models for improving maize disease management. Full article

Rainfall, particularly in continental climates with a monsoonal tendency, impacts the microbial niches during the growth of mountain cultivated ginseng. With shifts in the microbial community, diseases in ginseng cultivated and protected under rain shelter conditions may ultimately be altered. Such cultivation may influence microflora dynamics through variations in meteorological parameters; however, this is not yet clear. The present study found that rain shelter cultivation affected the distribution of fungal communities within mountain cultivated ginseng. This led to an improved community structure in the ginseng rhizosphere, characterized by the proliferation of antagonistic fungi and a reduction in pathogenic fungi. A correlation analysis of meteorological factors found that soil temperature and humidity were the primary meteorological factors affecting mountain cultivated ginseng. It is evident that rain shelter cultivation regulated the microecological environment of the mountain cultivated ginseng’s rhizosphere and resulted in positive outcomes. A disease investigation supported this finding. The incidence of ginseng root diseases, such as rust and root rot, was reduced by 5–6%. The incidence of ginseng leaf diseases, including gray mold and black spot, was reduced by 5–10%. This research provides evidence to address the dynamics of microbial ecology under rain shelter cultivation and its benefits for sustainable mountain cultivated ginseng management. Full article

Coffee production worldwide is affected by the pathogen Hemileia vastatrix, which causes the “coffee rust” disease and may be associated with other fungi. Ecuador lacks studies on fungal diversity associated with coffee rust, which could potentially control or escalate pathogen activity. Using the ITS-5.8S nrDNA region, we randomly detected a small preliminary fungi diversity related to coffee rust in Ecuador, which we report here for the first time. Ten coffee farms (four in Loja, three in Calvas, and three in Quilanga) from the Loja Province were sampled to analyze the genetic diversity of the pathogen Hemileia vastatrix in rust lesions on coffee leaves. A high number of selected sequences (Sanger sequencing) showed the presence of 48 OTUs (Operational Taxonomic Units) or “hypothetical species” of Ascomycetes and Basidiomycetes distributed across all the sampled farms. The genera Akanthomyces, Ceramothyrium, Cladosporium, Didymella, Fusarium, Mycosphaerella, Neoceratosperma, and Trichothecium of Ascomycetes, as well as Bulleribasidium, Hannaella, and Meira of Basidiomycetes, were the most abundant. To avoid taxonomic conflict, some sequences were placed into Capnodiales (Ascomycetes) and Tremelalles (Basidiomycetes) without a genus definition. A new phylogenetic group of sequences is considered Incertae Sedis from Basidiomycetes. Additionally, morphospecies of Akanthomyces (synonymous with some Lecanicillium species) and Colletotrichum were observed macroscopically and microscopically growing closely with rust. Most of the OTUs probably correspond to rust mycoparasites, as previously reported in the literature. However, this study is limited by the number of sequences analyzed phylogenetically, which may hinder the discovery of significant insights. Future studies are needed to determine whether this preliminary fungal diversity is associated with the rust fungus or corresponds to ubiquitous airborne fungi. Furthermore, research into the function of these species may reveal whether they promote rust pathogenicity or enhance plant responses by activating resistance mechanisms. Full article

Plant disease identification is a crucial issue in agriculture, and with the advancement of deep learning techniques, early and accurate identification of plant diseases has become increasingly critical. In recent years, the rise of vision transformers has attracted significant attention from researchers in various vision-based application areas. We designed a model with an encoder–decoder architecture to efficiently classify plant diseases using a transfer learning approach, which effectively recognizes a large number of plant diseases in multiple crops. The model was tested on the “PlantVillage”, “FGVC8”, and “EMBRAPA” datasets, which contain leaf information from crops such as apples, soybeans, tomatoes, and potatoes. These datasets cover diseases caused by fungi, including rust, spot, and scab, as well as viral diseases such as leaf curl. The model’s performance was rigorously evaluated on datasets, and the results demonstrated its high accuracy. The model achieved 99.9% accuracy on the “PlantVillage” dataset, 97.4% on the “EMBRAPA” dataset, and 91.5% on the “FGVC8” dataset, showcasing its competitiveness with other state-of-the-art models. This study provides a robust and reliable solution for plant disease classification and contributes to the advancement of precision agriculture. Full article

Ravenelia is the third largest rust genus of the order Pucciniales with more than 200 described species. It is an important rust genus that has undergone tremendous taxonomic changes. This genus produces teliospores united into a head on a compound pedicel composed of two to several hyphae with autoecious, macro-, demi- to hemi-, and, more rarely, microcyclic modes of their life cycle which provide it a unique identity and have proved helpful in the identification of the genus. The current understanding of the taxonomy, history, diversity and distribution of this genus is discussed in this paper. Both online and offline resources were searched to gather data of the published literature. The data thus obtained were analyzed for numerical and graphical summaries to provide the diversity and distribution of the genus. In addition, a phylogenetic analysis based on the ITS and nLSU DNA sequence data available in GenBank and the published literature was performed to examine the taxonomic placement of different species within the genus. The genus was reported to be distributed over 53 countries of the world. Around 51 plant genera belonging to four plant families, viz., Fabaceae, Phyllanthaceae, Asphodelaceae and Zygophyllaceae were found to be infected with these rust fungi. The phylogenetic analysis based on LSU and ITS sequence data revealed the polyphyletic nature of the genus. A table of 248 species of this genus is also provided with all information of host, distribution and cited reference that can be helpful for mycologists to find all information at one place. Future perspectives for the advancement of this genus are also discussed. Full article

Between 2020 and 2023, rust fungus specimens were collected from the primary forested regions of the Sanjiangyuan area in Qinghai Province, resulting in over 300 samples. A taxonomic and phylogenetic study of the rust fungi from these forests was conducted using morphological and molecular biological techniques. The investigation identified rust fungi from 7 families, 12 genera, 56 species and varieties, including 10 new host records, 1 new record for China, and 2 novel species. The host plants involved belonged to 26 families, 48 genera, and 78 species. Pucciniaceae and Coleosporiaceae were the dominant families, with the genera Puccinia, Melampsora, and Gymnosporangium being prevalent. The rust fungi in the Sanjiangyuan forests showed a biogeographical affinity with the North Temperate Zone. Floristic comparisons revealed a higher similarity with rust fungi from Inner Mongolia, Gansu, and Tibet and a lower similarity with those from Hainan. An analysis of the life forms of rust fungus host plants indicated that herbaceous plants were the most common, followed by shrubs and trees. In different regions of Sanjiangyuan, rust fungi were found as follows: Golog Prefecture with 6 families, 9 genera, and 28 species; Yushu Prefecture with 5 families, 8 genera, and 31 species; Huangnan Prefecture with 5 families, 9 genera, and 26 species; and Hainan Prefecture with 4 families, 5 genera, and 10 species. The families Pucciniaceae, Melampsoraceae, and Coleosporiaceae were common across all four regions. Moreover, the families Rosaceae, Asteraceae, Ranunculaceae, Salicaceae, and Caprifoliaceae were shared among the host plants in these regions. Full article

Peru is one of the leading countries that produce and export specialty coffees, favorably positioned in the international markets for its physical and organoleptic cup qualities. In recent years, yellow coffee rust caused by the phytopathogenic fungus Hemileia vastatrix stands out as one of the main phytosanitary diseases that affect coffee culture yields. Many studies have demonstrated bacteria antagonistic activity against a number of phytopathogen fungi. In this context, the aim of this work was to select and characterize phyllospheric bacteria isolated from Coffea arabica with antagonistic features against coffee rust to obtain biocontrollers. For that purpose, a total of 82 phyllospheric bacteria were isolated from two coffee leaf rust-susceptible varieties, typica and caturra roja, and one tolerant variety, catimor. Of all the isolates, 15% were endophytic and 85% were epiphytes. Among all the isolates, 14 were capable of inhibiting the mycelial radial growth of Mycena citricolor, and Colletotrichum sp. 16S rRNA gene sequence-based analysis showed that 9 isolates were related to Achromobacter insuavis, 2 were related to Luteibacter anthropi and 1 was related to Rodococcus ceridiohylli, Achromobacter marplatensis and Pseudomonas parafulva. A total of 7 representative bacteria of each group were selected based on their antagonistic activity and tested in germination inhibition assays of coffee rust uredinospores. The CRRFLT7 and TRFLT8 isolates showed a high inhibition percentage of urediniospores germination (81% and 82%, respectively), similar to that obtained with the chemical control (91%). An experimental field assay showed a good performance of both strains against rust damage too, making them a promising alternative for coffee leaf rust biocontrol. Full article

Rust fungi cause significant damage to wheat production worldwide. In order to mitigate disease impact and improve food security via durable resistance, it is important to understand the molecular basis of host–pathogen interactions. Despite a long history of research and high agricultural importance, still little is known about the interactions between the stripe rust fungus and wheat host on the gene expression level. Here, we present analysis of the molecular interactions between a major wheat pathogen—Puccinia striiformis f. sp. tritici (Pst)—in resistant and susceptible host backgrounds. Using plants with durable nonrace-specific resistance along with fully susceptible ones allowed us to show how gene expression patterns shift in compatible versus incompatible interactions. The pathogen showed significantly greater number and fold changes of overexpressed genes on the resistant host than the susceptible host. Stress-related pathways including MAPK, oxidation–reduction, osmotic stress, and stress granule formation were, almost exclusively, upregulated in the resistant host background, suggesting the requirement of the resistance-countermeasure mechanism facilitated by Pst. In contrast, the susceptible host background allowed for broad overrepresentation of the nutrient uptake pathways. This is the first study focused on the stripe rust pathogen–wheat interactions, on the whole transcriptome level, from the pathogen side. It lays a foundation for the better understanding of the resistant/susceptible hosts versus pathogenic fungus interaction in a broader sense. Full article

Apple rust, caused by Gymnosporangium yamadae, poses a significant challenge to apple production. Prior studies have underscored the pivotal role played by endophytic microbial communities, intimately linked with the host, in influencing plant diseases and their pathogenic outcomes. The objective of this study is to scrutinize alternations in endophytic microbial communities within apple leaves at different stages of apple rust using high-throughput sequencing technology. The findings revealed a discernible pattern characterized by an initial increase and subsequent decrease in the alpha diversity of microbial communities in diseased leaves. A microbial co-occurrence network analysis revealed that the complexity of the bacterial community in diseased leaves diminished initially and then rebounded during the progression of the disease. Additionally, employing the PICRUSt2 platform, this study provided preliminary insights into the functions of microbial communities at specific disease timepoints. During the spermogonial stage, endophytic bacteria particularly exhibited heightened activity in genetic information processing, metabolism, and environmental information processing pathways. Endophytic fungi also significantly enriched a large number of metabolic pathways during the spermogonial stage and aecial stage, exhibiting abnormally active life activities. These findings establish a foundation for comprehending the role of host endophytes in the interaction between pathogens and hosts. Furthermore, they offer valuable insights for the development and exploitation of plant endophytic resources, thereby contributing to enhanced strategies for managing apple rust. Full article

(1) The fungal genus Simplicillium (Cordycipitaceae: Hypocreales) has an extensive distribution and a broad spectrum of hosts and substrates. The species Simplicillium lanosoniveum is a mycoparasite with potential for biological control of coffee leaf rust, Hemileia vastatrix. Morphologically, Simplicillium closely resembles mycoparasitic and entomopathogenic Lecanicillium fungi, often resulting in misidentification. A fungal isolate was obtained from leaf-rust-infested coffee plants from Cienfuegos Province, Cuba. (2) Combined analyses of morphology and molecular markers (ITS, LSU, EF-1alpha) were used for fungal identification. (3) In the NJ, ML, and BI phylogenies which were reconstructed, the isolate LBSim-01 was located in the Simplicillium lanosoniveum clade. This species-level identification was supported by morphological features. (4) The isolate LBSim-01 was assigned to the species Simplicillium lanosoniveum. This is the first description of a Simplicillium fungus associated with coffee leaf rust in Cuba. The presented results hold implications for the biological control of this economically relevant plant disease. Full article