Search Results (66)

Brown spot, caused by Alternaria alternata, is the most important leaf fungal disease threatening kiwifruit production in China, and it is typically controlled through the application of fungicides, such as procymidone and difenoconazole. To date, fungicide resistance development has not yet been systematically reported for the pathogen of kiwifruit. A total of 135 single-conidium A. alternata isolates were collected from different cities in Zhejiang Province, China. Alternaria alternata developed prevailing resistance to procymidone and initial resistance to difenoconazole, with resistance frequencies of 60.7 and 13.3%, respectively. Positive cross-resistance was observed between procymidone and iprodione but not between procymidone and difenoconazole, tebuconazole, prochloraz, pydiflumetofen, pyraclostrobin, or thiophanate-methyl. Moreover, no cross-resistance was observed between difenoconazole and all other tested fungicides, including the two other demethylation inhibitors, tebuconazole and prochloraz. A fitness penalty was not detected in procymidone-resistant (Pro^R) or difenoconazole-resistant (Dif^R) isolates. However, double-resistant (Pro^R Dif^R) isolates had a fitness penalty, showing significantly decreased sporulation, germination, and pathogenicity. The P894L single point mutation, caused by the change from CCA to CTA at the 894th codon of Os1, was detected in Pro^R isolates. Molecular dynamic simulation showed that the P894L mutation significantly decreased the inhibitory activity of procymidone against AaOs1 in A. alternata. These results provide insight into the development and characteristics of fungicide resistance, offering guidance for the study and management of kiwifruit diseases. Full article

Alternaria species produce diverse secondary metabolites that act as critical virulence factors during plant pathogenesis. In cultivation areas of Chrysanthemum morifolium ‘Fubai’—a key cultivar for herbal tea—black spot disease caused by A. alternata manifests as necrotic leaf lesions progressing to wilting. Despite this disease’s economic impact, information on its associated toxins is limited, and the types of toxins produced by the black spot pathogen of Chrysanthemum morifolium ‘Fubai’ in particular remain unclear. Furthermore, whether toxins are present in the flowers when the leaves show symptoms is uncertain, but their inflorescence is not visibly infected. Using two previously characterized A. alternata strains (F16/F20) isolated from ‘Fubai’ in earlier studies, we demonstrated the concomitant production of altenuene (ALT) and tenuazonic acid (TeA) in both strains, with strain-specific yield variations (F20 TeA: 342.16 µg/mL vs. F16: 21.84 µg/mL; ALT: 0.28 µg/mL vs. 0.90 µg/mL). Time-course monitoring revealed coordinated accumulation of both toxins in inoculated petals, reaching 18.07 μg/g ALT and 2.59 µg/g TeA by day 9. Notably, these two toxins were detected only in flower samples from black spot-infected plants, and their concentrations correlated closely with disease severity in the leaves. Moreover, although the inflorescences did not display symptoms, both fresh and dried flowers retained detectable toxin levels. We established a technical system for the extraction and quantitative detection of the toxins ALT and TeA produced by the black spot pathogen in tea chrysanthemum. This work provides the first confirmation of ALT/TeA co-contamination in Chrysanthemum morifolium ‘Fubai’, revealing substantial dietary exposure risks through tea consumption. Our findings suggest that, from a food safety risk reduction perspective, integrated management strategies should be developed to minimize toxin contamination in tea chrysanthemum, including improved disease prevention measures and potential regulatory considerations. Full article

Dehydroabietic acid (DHA) is a secondary metabolite isolated from rosin, which has certain antifungal activity, but its inhibitory effects against Alternaria alternata are unclear. In the present study, we found that DHA inhibited the mycelial growth of A. alternata, Botrytis cinerea, Valsa mali, Pestalotiopsis neglecta, and Fusarium oxysporum in a concentration-dependent manner, with the best inhibitory effect against A. alternata. Moreover, DHA can also inhibit the spore germination of A. alternata. Then, in vivo inoculation experiments showed that the leaf lesions of Populus alba gradually decreased with the increase in DHA concentration. The disease of P. alba leaves inoculated with A. alternata was not obvious after treatment with 800 mg/L DHA. The scanning electron microscopy showed that the mycelial morphology was abnormal, with crinkles and depressions. Meanwhile, the relative conductivity, soluble protein content, malondialdehyde content and hydrogen peroxide content of A. alternata were significantly increased after DHA treatment, which affected the integrity of the cell membrane and increased the permeability of A. alternata, resulting in a large leakage of intracellular substances, exacerbating the degree of lipid peroxidation of the cell membrane of A. alternata and causing oxidative damage to cells. The enzyme activity assay showed that treatment with 56.015 mg/L (EC₅₀) DHA significantly reduced the activities of antioxidant enzymes (superoxide dismutase, catalase, peroxidase) and cell-wall-degrading enzymes (endoglucanase, polygalacturonase, pectin lyase) in A. alternata (p < 0.05), resulting in a decrease in the activity of pathogenic fungi, as well as a reduction in the ability of the A. alternata to degrade the cell wall of the host plant, which led to a decrease in the ability of the A. alternata to infest the host plant. Moreover, the decrease in the relative expression of defense-related enzyme genes (AaSOD, AaPOD, AaCAT) and pathogenicity-related enzyme genes (AaPL, AaPG) was consistent with the enzyme activity results. Thus, the present study revealed the fungicidal activity and mechanism of DHA against A. alternata and the potential of DHA to be developed as a plant-derived antifungal agent was established. Full article

Difenoconazole, a broad-spectrum systemic fungicide, can effectively prevent and control plant diseases such as rice blast, leaf spot, and black spot caused by Colletotrichum godetiae, Alternaria alternata, and Neopestalotiopsis rosae. However, its residual accumulation in the environment may pose potential toxicity risks to non-target organisms. In this study, a highly efficient DIF-degrading microbial consortium TA01 was enriched from long-term pesticide-contaminated soil by a laboratory-based adaptive evolution strategy. The microbial consortium TA01 was able to degrade 83.87% of 50 mg/L of DIF within 3 days. In addition, three intermediate metabolites were identified using HPLC–MS/MS, and the results indicated that the degradation of DIF by microbial consortium TA01 may involve catalytic reactions such as hydrolysis, dehalogenation, and hydroxylation. High-throughput sequencing results showed that Pantoea, Serratia, Ochrobactrum, and Bacillus were the dominant microbial members involved in the degradation process. Finally, bioremediation capacity experiments showed that inoculation with microbial consortium TA01 was able to accelerate the degradation of DIF in the water–sediment system. The findings of this study not only enrich the microbial resources available for DIF degradation but also offer new potential strategies for in situ remediation of DIF contamination. Full article

The tree species Toona sinensis has been cultivated in China for over 2000 years for multiple purposes. In 2022, leaf spots were detected on the leaves of T. sinensis in a germplasm resource nursery in Zhejiang Province, China. Symptomatic leaves were collected, and fungal isolation was conducted. Four fungal isolates resembling Alternaria were isolated from the diseased leaves. These isolates were identified as Alternaria alternata according to a combination of morphological characteristics and multigene phylogenetic analysis. To fulfill Koch’s postulates, the pathogenicity of the selected isolate, YKHH, was tested on 2-year-old container seedlings of T. sinensis. Disease symptoms basically consistent with those observed in the field developed 12 days after inoculation (DAI) when either conidia or mycelia were used as the inoculum. Nevertheless, no visible symptoms developed on the leaves of the control groups. The fungi were reisolated from the diseased leaves, and both the morphological characteristics and three gene sequences (GAPDH, RPB2, and TEF1-α) of the reisolated fungi were consistent with those of the original YKHH isolate. Susceptibility trial results showed that family 55 of T. sinensis (F55) had the highest susceptibility to A. alternata, while family 28 of T. sinensis (F28), family 52 of T. sinensis (F52), and Toona ciliata var. pubescens (TCP) exhibited equal susceptibility to A. alternata. To the best of our knowledge, this is the first report of leaf spot disease caused by A. alternata on T. sinensis in China. Full article

The genus Alternaria, functioning as a saprobe, endophyte, and plant pathogen, is widely distributed across various natural and human-impacted environments. Leaf spot and black spot diseases, caused by Alternaria species, are the most prevalent plant diseases within this genus, leading to significant reductions in crop yields and substantial economic losses. To facilitate the timely detection of Alternaria species during the early stages of infection, enable targeted treatments, and mitigate associated damages, we employed a species identification method based on Analysis of whole-GEnome (AGE). We downloaded 148 genomes, including 31 Alternaria species, from the NCBI GenBank database. Through bioinformatics analysis, we constructed a specific-target sequence library and selected a representative sequence per species. The specific target sequences of the seven exemplary Alternaria species were subsequently used for validation and rapid detection, utilizing Sanger sequencing and CRISPR-Cas12a technology, respectively. The results demonstrated that our method accurately identified the target species. Additionally, by combining Enzymatic Recombinase Amplification (ERA) with CRISPR-Cas12a, we achieved rapid and precise identification of genomic DNA samples, with a detection limit as low as 0.01 ng/µL within 30 min. Therefore, AGE proves to be a highly robust and efficient method for the detection of Alternaria species, offering broad potential for various applications. Full article

Plant microbiomes play a major role in plant health, growth, and development, enhancing resistance to pathogen invasion. However, despite the extensive research on the phyllosphere microbiome, it remains unclear how the microbiome of leaves in proximity to diseased leaves responds to pathogen invasion. We investigate the response of the maize phyllosphere microbiome to maize white spot by assessing the microbiome dynamics associated with the white spot portion and the area in proximity using 16S and ITS high-throughput sequencing analysis. Our results showed that the bacterial diversities were higher in the diseased portion and area in proximity to the spot than those in healthy plants. At the same time, lower fungal diversity was recorded in the diseased portion compared to portions in proximity to it and healthy leaves. The spot portion had a significant influence on the microbial composition. The diseased portion, the area in proximity to it, and the healthy leaves were dominated by the bacterial genera Sphingomonas, Delftia, Chryseobacterium, Stenotrophomonas, Methylobacterium-methylorubrum, and Bacteroides. Still, the abundance of Sphingomonas decreased in the healthy leaves with a corresponding increase in Stenotrophomonas. Conversely, the fungal genus Setophoma dominated the diseased portion, while the fungal pathogens Cladosporium, Alternaria, and Exserohilum were highly abundant in the samples from the area in proximity to it. In addition, a co-occurrence network analysis revealed a complex fungal network in healthy leaves and those in proximity to leaves infected with white spot compared to the diseased portion. This study suggests that the area in proximity to the maize leaf infected with white spot disease is colonized by more harmful plant pathogenic fungi for disease progression. Full article

Plant diseases pose significant economic challenges and may lead to ecological consequences. Although plant pathologists have a significant ability to diagnose plant diseases, rapid, accurate, and early diagnosis of plant diseases by intelligent systems could improve disease control and management. This study evaluates six efficient classification models (classifiers) based on deep learning to detect common tomato diseases by analyzing symptomatic patterns on leaves. Additionally, group learning techniques, including simple and weighted majority voting methods, were employed to enhance classification performance further. Six tomato leaf diseases, including Pseudomonas syringae pv. syringae bacterial spot, Phytophthora infestance late blight, Cladosporium fulvum leaf mold, Septoria lycopersici Septoria leaf spot, Corynespora cassiicola target spot, and Alternaria solani early blight, as well as healthy leaves, resulting in a total of seven classes, were utilized for the classification. Deep learning models, such as convolutional neural networks (CNNs), GoogleNet, ResNet-50, AlexNet, Inception v3, and MobileNet, were utilized, achieving classification accuracies of 65.8%, 84.9%, 93.4%, 89.4%, 93.4%, and 96%, respectively. Furthermore, applying the group learning approaches significantly improved the results, with simple majority voting achieving a classification accuracy of 99.5% and weighted majority voting achieving 100%. These findings highlight the effectiveness of the proposed deep ensemble learning models in accurately identifying and classifying tomato diseases, featuring their potential for practical applications in tomato disease diagnosis and management. Full article

The Aloe barbadensis industry plays an important role in the economic development of Yuanjiang county of Yuxi city in Yunnan province, China. In order to reduce the harm of diseases and ensure the quality of products, the occurrence of A. barbadensis was investigated. The pathogenic fungi of wild and cultivated species of A. barbadensis were isolated by a tissue separation method, and DNA sequencing was carried out by using the sequence analysis of the ribosomal rDNA-ITS region, and the pathogenic fungi were classified and identified by finally combining morphological observations. The results showed that the main fungal diseases were root rot and leaf rot disease caused by Fusarium oxysporum, leaf spot disease caused by Curvularia lunata, anthracnose caused by Colletotrichum boninense, and brown spot disease caused by Alternaria alternata on A. barbadensis. Full article

Palm trees (Arecaceae) are among the most popular ornamental plants worldwide. Despite extensive research on the fungi associated with Arecaceae, the diversity and ecological dynamics of fungi affecting ornamental palms remain poorly studied, although they have significant impact on palm health and economic value. Furthermore, while research on palm fungal diversity has traditionally focused on tropical assemblages, ornamental palms in temperate climates offer a unique opportunity to explore the diversity of palm fungi in non-native habitats. The present study conducted a preliminary assessment of the diversity and ecology of potential phytopathogenic fungi associated with foliar lesions on various ornamental palm host species in Portugal, combining morphological examination, PCR-based genomic fingerprinting, and biodiversity data analysis. The examination of 134 foliar lesions sampled from 100 palm trees resulted in a collection of 2064 palm leaf spotting fungi (PLSF), representing a diverse fungal assemblage of 320 molecular operational taxonomic units (MOTUs) across 97 genera. The overall fungal community composition revealed a distinct assemblage dominated by Neosetophoma, Alternaria, Phoma, and Cladosporium, with a profusion of infrequent and rare taxa consistent with a logseries distribution. Significantly positive co-occurrence (CO) patterns among prevalent and uncommon taxa suggest potential synergistic interactions enhancing fungal colonisation, persistence, and pathogenicity. The taxonomic structures of the PLSF contrasted markedly from tropical palm fungi, especially in the prevalence of pleosporalean coelomycetes of the Didymellaceae and Phaeosphaeriaceae, including recently introduced or not previously documented genera on Arecaceae. This novel assemblage suggests that climatic constraints shape the structure of palm fungal communities, resulting in distinctive temperate and tropical assemblages. In addition, the fungal assemblages varied significantly across palm host species, with temperate-native palms hosting more diverse, coelomycete-enriched communities. The present findings highlight foliar lesions as hyperdiverse microhabitats harbouring fungal communities with intricate interactions and a complex interplay of climatic, host, and ecological factors. With climate change altering environmental conditions, the identification of fungi thriving in or inhabiting these microhabitats becomes crucial for predicting shifts in pathogen dynamics and mitigating future fungal disease outbreaks. Understanding these complex ecological dynamics is essential for identifying potential phytopathogenic threats and developing effective management strategies for the health and sustainability of ornamental plants. Full article

Okra (Abelmoschus esculentus) is an important agricultural crop of the Malvaceae family, cultivated across tropical, subtropical, and warm temperate regions. However, okra production faces numerous challenges from diverse pest species, including insects, nematodes, arachnids, and mites, that significantly reduce its yield. Major economic pests include the cotton aphid, cotton spotted bollworm, Egyptian bollworm, cotton mealybug, whitefly, cotton leafhopper, cotton bollworm, two-spotted spider mite, root-knot nematode, reniform nematode, cotton leaf roller, and flea beetle. Additionally, less prevalent pests such as the blister beetle, okra stem fly, red cotton bug, cotton seed bug, cotton looper, onion thrips, green plant bug, and lesion nematode are also described. This review also addresses fungal and oomycete diseases that present high risks to okra production, including damping-off, powdery mildew, Cercospora leaf spot, gray mold, Alternaria leaf spot and pod rot, Phyllosticta leaf spot, Fusarium wilt, Verticillium wilt, collar rot, stem canker, anthracnose, and fruit rot. In addition to these fungal diseases, okra is also severely affected by several viral diseases, with the most important being okra yellow vein mosaic disease, okra enation leaf curl disease, and okra mosaic disease, which can cause significant yield losses. Moreover, okra may also suffer from bacterial diseases, with bacterial leaf spot and blight, caused primarily by Pseudomonas syringae, being the most significant. This manuscript synthesizes the current knowledge on these pests. It outlines various management techniques and strategies to expand the knowledge base of farmers and researchers, highlighting the key role of integrated pest management (IPM). Full article

In this study, we carried out large-scale leaf spot symptom observation on vineyards in the Krasnodar Krai of Russia and determined their distribution. The incidence and severity of leaf spot were higher on the Euro-American grapevine hybrids (Bianka, Levokumskij, Avgustin, Moldova, Pervenets Magaracha, Dunavski lazur). A total of 433 isolates that belonged to the genus Alternaria were isolated from samples with leaf spot. Pathogenicity testing confirmed the ability of the representative isolates to cause necrosis on the grapevine. The isolates of Alternaria sp. were typed by the loci of internal transcribed spacer (ITS), glyceraldehyde-3-phosphate dehydrogenase (gapdh), Alternaria allergen a1 (Alt a1), β-tubulin (tub), and translation elongation factor (tef1). Isolates from grapevine causing leaf spot were shown to cluster with isolates of Alternaria. alternata (Fr.) Keissl. and Alternaria. arborescens E.G. Simmons species complex. Of the fungicides tested to inhibit Alternaria growth, the most effective were mixtures, such as pyrimethanil and fluopyram, cyprodinil and fludioxonil, and those that included difenoconazole. The results of the study expand our knowledge of the biodiversity of Alternaria sp. fungi and can be used to limit the spread of Alternaria leaf spot of the grapevine. Full article

Mikania micrantha is one of the most threatening invasive plant species in the world. Its invasion has greatly reduced the species diversity of the invaded areas. The development of fungal herbicides using phytopathogenic fungi has attracted considerable attention in recent years. In this study, a tissue isolation method was used to isolate and screen the strain SWFU-MM002 with strong pathogenicity to M. micrantha leaves from naturally occurring M. micrantha. Through morphological observation, ITS, GAPDH, and Alta-1 gene sequence homology, we compare and construct a phylogenetic tree to determine their taxonomic status. In addition, the biological characteristics of strain SWFU-MM002 were studied. The results showed that, combined with morphological and molecular biology identification, the strain was identified as Alternaria gossypina; biological characteristic research showed that the optimal medium for the growth of mycelium of this strain is PDA medium. At the optimal temperature of 27 °C and pH between 6 and 10, the mycelium can grow well. The best carbon and nitrogen sources are maltose and peptone, respectively. Analysing the infection process under a light microscope showed that SWFU-MM002 mycelia invaded the leaf tissue through stomata and colonized, eventually causing damage to the host. This is the first report of leaf spot of M. micrantha caused by A. gossypina. This study can lay a solid foundation for the development of A. gossypina as a control agent for M. micrantha. Full article

Apple canker disease, also named as apple Valsa canker, is one of the most destructive diseases for apples (Malus domestica Borkh.). Cytospora/Valsa spp. are the dominant causal agent of this disease, but many studies have revealed that fungi from some other genus can also cause typical apple canker symptoms. In this study, we performed fungal pathogen isolation from cankered ‘Fuji’ apple barks. Six representative morphologically different fungi (Strain 1–6) were further subjected to ITS sequencing and evolutionary analysis. Molecular identification results revealed that Strains 1–6 are Cytospora mali, Fusarium cf. solani, Alternaria alternata, C. mali, Diplodia seriata and F. proliferatum, respectively. All these fungi have been reported to be causal agents of apple diseases. By inoculating fungal plugs onto trunks of ‘Fuji’ apple trees, the pathogenicity of the six fungi were accessed. Only the inoculations of the two C. mali strains (Strain 1 and Strain 4) and the A. alternata strain (Strain 3) resulted in typical apple canker symptoms in trunks. It is worth noting that Strain 1 caused much more severe canker symptoms and higher pathogenicity incidence than the other two fungi. A. alternata has been identified as a pathogen causing diseases on apple fruits and leaves. By further assessing its pathogenicity on apple fruits and leaves, we verified that it can also cause typical fruit rot and leaf spot symptoms. To the best of our knowledge, this is the first report on apple canker disease caused by A. alternata in China. Our present study can provide a theoretical foundation for the prevention and control of apple canker disease. Full article

To mitigate problems concerning small-sized spots on apple leaves and the difficulties associated with the accurate detection of spot targets exacerbated by the complex backgrounds of orchards, this research used alternaria leaf spots, rust, brown spots, gray spots, and frog eye leaf spots on apple leaves as the research object and proposed the use of a high-accuracy detection model YOLOv5-Res (YOLOv5-Resblock) and lightweight detection model YOLOv5-Res4 (YOLOv5-Resblock-C4). Firstly, a multiscale feature extraction module, ResBlock (residual block), was designed by combining the Inception multi-branch structure and ResNet residual idea. Secondly, a lightweight feature fusion module C4 (CSP Bottleneck with four convolutions) was designed to reduce the number of model parameters while improving the detection ability of small targets. Finally, a parameter-streamlining strategy based on an optimized model architecture was proposed. The experimental results show that the performance of the YOLOv5-Res model and YOLOv5-Res4 model is significantly improved, with the mAP0.5 values increasing by 2.8% and 2.2% compared to the YOLOv5s model and YOLOv5n model, respectively. The sizes of the YOLOv5-Res model and YOLOv5-Res4 model are only 10.8 MB and 2.4 MB, and the model parameter counts are reduced by 22% and 38.3% compared to the YOLOv5s model and YOLOv5n model. Full article