Journal of Phytopathology最新文献

In apple leaf disease classification, the health of apple trees plays a crucial role in crop care and productivity. Since leaves are responsible for photosynthesis, they are essential for nutrient transport and overall plant vitality. Therefore, accurate disease identification enables timely intervention and effective disease management. This confirms the optimal yield and crop quality. This research introduces a novel parallel priority feature fusion and improved Butterfly Optimization network for apple leaf disease classification. This method uses PlantVillage, Apple Tree Leaf Disease and PlantPathology Apple as three benchmark datasets. Images undergo preprocessing, in which resizing, normalisation, contrast enhancement using the Top-Hat operation and data augmentation are used to improve strength and reduce data imbalance. High-level and complementary deep features by using transfer learning, EfficientNet-B3 and NasNetLarge are two pre-trained Convolutional Neural Networks are extracted. These features are fused by the parallel priority strategy, which reduces redundancy and enhances discriminability representation. Then, for optimal feature selection, overfitting is reduced and generalisation is improved using an improved Butterfly Optimization Algorithm with adaptive crossover strategies. The selected features are then classified using Light Gradient-Boosting Machine, which handles high-dimensional data efficiently, and more robust classification is ensured. The experimental results demonstrate that the proposed method achieves superior performance, attaining an accuracy of 98.97% and an F1-score of 97.57% confirming its effectiveness in feature representation and disease discrimination. The proposed method enables early and accurate detection of apple leaf diseases, providing an efficient and reliable solution. This contributes to sustainable agricultural management and enhanced productivity.

Biotic (root rot and wilt diseases) and abiotic (parawilt) stresses are the major constraints in cotton production. Microbe-based biological control offers an alternative to chemical control, leading to the ecologically sustainable management of both biotic and abiotic stresses. A total of 30 fluorescent pseudomonad strains were isolated from cotton rhizospheres and their biocontrol efficacy against Rhizoctonia solani and Fusarium oxysporum f. sp. vasinfectum was evaluated in vitro. The APKP4 and VPNP5 isolates were significantly superior in inhibiting the mycelial growth of wilt and root rot pathogens, respectively. Further, fluorescent pseudomonad strains APKP4, VPNP5 and KYIP5 showed greater performance in improving the plant growth parameters of cotton seedlings in vitro. These strains showed efficient production of growth hormones such as indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate deaminase (ACCD). The antifungal metabolites, 2,4-diacetylphloroglucinol and phenazine extracted from these isolates also showed higher antagonistic activity against F. oxysporum f. sp. vasinfectum and R. solani. Furthermore, the antagonistic fluorescent pseudomonads effectively produced lytic enzymes and antimicrobial traits such as chitinase, cellulase, protease, amylase, gelatinase, siderophore and hydrogen cyanide. The talc-based formulation of promising fluorescent pseudomonad strains was evaluated individually and in combination against root rot, wilt and parawilt of cotton under field conditions. Among the treatments, the bioformulation mixture (APKP4 + VPNP5 + KYIP5) containing both antibiotics and ACC-deaminase-producing fluorescent pseudomonad strains recorded the minimum incidence of root rot, wilt and parawilt, maximum plant growth and seed cotton yield. This study has the potential to be adopted for sustainable and environmentally friendly cotton production.

Colletotrichum siamense is an emerging plant pathogen with a broad host range and increasing global prevalence, yet its role in ornamental plant diseases remains underexplored. This study reports the first detailed characterisation of C. siamense associated with anthracnose symptoms on Ficus elastica. The fungus was isolated from symptomatic leaves exhibiting dark, necrotic lesions with yellow halos. Morphophysiological features were consistent with C. siamense and included fast-growing floccose colonies, globose conidiomata, cylindrical conidia, and melanized appressoria. Species identity was confirmed through multilocus sequencing of ITS and β-tubulin (BenA) regions, and phylogenetic analyses clustered the isolate with known C. siamense strains from diverse hosts. Additionally, physiological assays revealed enzymatic activity for amylase, hemicellulases, and laccases, whereas the activity of cellulases was absent. Finally, pathogenicity trials on healthy F. elastica leaves fulfilled Koch's postulates, with symptomatic lesions and successful re-isolation of the pathogen. An NCBI database search retrieved over 38,000 C. siamense sequences, with only two associated with F. elastica, underscoring the rarity of reported infections in this host. This study not only expands the known host range of C. siamense but also highlights its pathogenic potential in indoor ornamental settings. These findings emphasise the importance of accurate pathogen identification using a polyphasic approach and underscore the need for phytosanitary vigilance to manage emerging threats to ornamental horticulture.

Rhododendron latoucheae is a globally renowned ornamental plant valued for its aesthetic appeal and economic significance. In May 2023, a leaf blight disease was observed on R. latoucheae in Guizhou Province, China, with approximately 20% of 500 surveyed plants showing symptoms of irregular reddish-brown lesions bearing black conidial clusters. The causal agent was identified as Neopestalotiopsis cubana through morphological characterisation and multilocus phylogenetic analysis (ITS, tef1-α, tub2). Pathogenicity was confirmed in accordance with Koch's postulates. To our knowledge, this is the first report of N. cubana causing leaf blight on R. latoucheae. In vitro screening of nine fungicides revealed high efficacy of mancozeb, azoxystrobin, tebuconazole, oxime·tebuconazole, and osthole, with EC₅₀ values below 10 μg·mL⁻¹. These results provide key insights for diagnostic and chemical management strategies against this emerging disease.

Hot pepper is a vital crop in Ethiopia and worldwide, valued for its pungency and as a source of income for stallholder farmers. However, production is severely impacted by Fusarium wilt, leading to yield losses ranging from 10% to 80% and significant economic damage, estimated at $65.3 billion globally. In Ethiopia, Fusarium wilt is widespread, with an incidence rate of 86.6% and yield losses reaching up to 80%. The pathogen blooms in warm, humid conditions, with optimal growth at 25°C and pH 7.0. It infects plants through roots, colonising the xylem and leading to wilting and plant death. The disease spreads through contaminated soil, water, farming tools, and infected seeds, making it difficult to control. Timely and precise diagnosis using morphological features (such as colony colour, shape, and spore structure) and molecular techniques (like PCR targeting and sequencing EF-1α and rpb2 genes, and additional genetic markers acl1, tub2, CaM, and rpb1) are essential to design effective management options. The pathogen's virulence is driven by toxin production, cell wall-degrading enzymes, and effector proteins that suppress plant immunity. Management includes cultural practices, biocontrol, and fungicides, though resistance is a concern. Integrated disease management (IDM), combining these approaches, offers sustainable control of Fusarium wilt. Modern biotechnological tools such as gene editing (CRISPR-Cas9) and RNA interference (RNAi) offer promising solutions but remain underutilised. Although there are identified resistant genotypes, adoption remains limited. This review emphasises the importance of integrated management and multi-omics approaches to improve resistance breeding, along with advocating for farmer education and policy support to reduce crop losses.

Bai-ji (Bletilla striata), an economically important medicinal herb cultivated in Yunnan Province, China, was observed with severe anthracnose symptoms in July 2021. Through comprehensive morphological characterisation and multilocus phylogenetic analysis (ITS, ACT, TUB, and GAPDH gene regions), the causal agent was identified as Colletotrichum cymbidiicola. Initial symptoms manifested as brown necrotic lesions that progressively developed into elliptical or fusiform spots with light brown centers. Koch's postulates confirmed that C. cymbidiicola was the etiological agent. This study is the first documented case of C. cymbidiicola infecting B. striata in China, providing valuable phytopathological insights for the sustainable cultivation of this medicinal species.