Journal of Phytopathology最新文献

In 2022, potato plants exhibiting symptoms of stem canker were observed in commercial fields in northern Sinaloa, Mexico. Morphological characterisation of two isolates allowed the identification of Ceratobasidium sp., whereas molecular analysis using sequences of the ITS region and the rpb2 gene distinguished the isolates within the Anastomosis Group A (AG-A). Both isolates induced symptoms of stem canker on inoculated potato plants and exhibited median EC₅₀ values of 19.46, 5.20, 62.71 and 0.33 μg mL⁻¹ for the fungicides thiophanate methyl, pyraclostrobin, prochloraz and penflufen, respectively. However, the two isolates differed by > 65-fold in their EC₅₀ value relative to pyraclostrobin.

Kiwifruit (Actinidia deliciosa) production in northeastern Türkiye is facing an emerging threat from Armillaria root rot. Surveys conducted in August 2021 and 2022 revealed that 10.5%–17.5% of the 200–500 vines within each of 35 kiwifruit orchards in the Perşembe, Gülyalı and Altınordu districts of Ordu province exhibited symptoms of Armillaria root rot, including complete defoliation. Diseased plants exhibited diagnostic signs on their root collars and woody roots, including white mycelial fans, extensive wood rot and rhizomorphs. A single Armillaria isolate was obtained from each of the 35 symptomatic orchards. Molecular identification, employing DNA sequencing of the large subunit (LSU) region of rDNA, the translation elongation factor subunit 1-alpha (TEF1) gene and the second largest RNA polymerase II B-subunit (RPB2) gene, identified 20 isolates as Armillaria gallica and 15 as A. mellea. Phylogenetic analyses, based on TEF1 alignments, further supported the species identification with a 100% bootstrap value. To examine genetic diversity, start codon targeted (SCoT) marker 13 was used, successfully differentiating the two Armillaria species and revealing three distinct clades. Clades I and II comprised 15 and 5 isolates of A. gallica, respectively, while Clade III contained all 15 A. mellea isolates. Pathogenicity testing on kiwifruit seedlings (cv. Hayward) revealed the ability of both A. gallica and A. mellea isolates to induce disease. Rhizomorph-producing isolates in kiwifruit seedlings displayed high virulence, inducing severe leaf necrosis and seedling mortality, while isolates lacking these structures were non-pathogenic. This study identifies the first global instance of A. gallica causing kiwifruit root rot. This finding, along with the identification of A. mellea as a causal agent in the country, highlights the emerging threat of Armillaria root rot to kiwifruit production in the region.

The current study was carried out to assess the alkaloid-enriched constituents of Prosopis juliflora (Fabaceae) against bacterial blight of pomegranate. Utilising plant extracts for disease management offers an eco-friendly approach. In vitro assessment of the minimum inhibitory concentration (MIC) for alkaloid-enriched fractions from the leaves and inflorescence of P. juliflora revealed a 14 mm zone of inhibition, with the lowest MIC value being 30 mg/mL. Untargeted metabolomics analysis of alkaloid-rich fractions (ARF) from four different tissues of P. juliflora, subjected to LC–MS for alkaloid identification, detected a total of 1489 peaks in positive mode and 240 peaks in negative mode. The highest peaks were detected in the leaves, where 47 metabolites and 9 alkaloids were identified. Ellipticine and ormosanine were found in relatively high concentrations across all four tissues, as indicated by their peak areas. The inflorescence had significantly high concentrations of sparteine, solanidine-I and puberanidine compared with other parts. Additionally, acetylsolanine was more abundant in the inflorescence, while solasodine-I was more prevalent in the leaves. A substantial amount of strictosidine was also found in the inflorescence.

Alligator weed (Alternanthera philoxeroides), originally from South America, is a notorious semi-aquatic invasive species in many countries, including India. Due to its amphibious nature, it not only damages the aquatic environment but is also detrimental to the terrestrial ecosystem. To seek an environmentally sound control option for alligator weed, this study focused on selecting an appropriate mycoherbicidal agent. A series of steps from field survey-based collection, isolation and selection of promising fungal strains, followed by host range determination to biocontrol potential studies against the weed were undertaken. Twenty-three phytopathogenic fungi were isolated, and among these, the fungi with the highest herbicidal activity (> 90% disease severity) were subjected to morphological and molecular characterisation and identified as Alternaria alternantherae (= Nimbya alternanthera). The fungus and its crude metabolites were tested against 76 plant species, showing a relatively narrow host range. This fungal species is being reported from West Bengal, India, for the first time. Although the fungus has been considered as a potential biocontrol tool against alligator weed in countries such as Australia, Brazil and China, long-term, detailed research for A. alternantherae and its active metabolites to be developed as bioherbicides against alligator weed remains indispensable.

Modern technology is revolutionising traditional farming processes by introducing new and streamlined approaches. Despite these advancements, challenges such as disease identification, insect detection and weather forecasting persist. To address these issues, this work proposes a DHMPD-based IoT-UAV smart agriculture system focused on pest detection. The method involves several stages: data acquisition, preprocessing, data augmentation, segmentation, feature extraction and classification. During data acquisition, a ‘Pest data set’ is collected. Preprocessing includes Z-score normalisation to produce better-normalised images. Data augmentation involves rotating images to create different orientations. The segmentation stage uses an updated HDBSCAN process, which improves the distance calculation between pixels using hybridised Euclidean and Minkowski distances. Feature extraction retrieves various features from segmented images, including modified MBP features, colour-based features and shape-based features. After feature extraction, the classification phase is performed by a hybrid technique with DL approaches such as improved DBN and LSTM approaches. Finally, classification results are averaged to predict pest detection accurately. The approach's effectiveness is evaluated through various assessments, aiming to overcome current limitations and enhance smart agriculture systems. The proposed DHMPD method was compared with state-of-the-art approaches and traditional classifiers, achieving a maximum accuracy of 0.936, outperforming conventional methods in accurately detecting pests. Hence, the proposed work holds immense promise to advance the capabilities of smart agriculture systems, offering practical solutions that can benefit farmers, agricultural researchers and industries involved in crop management and food production.

Wheat stem rust (caused by Puccinia graminis f.sp. tritici) is a damaging disease widespread in all grain-producing regions of the world. In this work, the effectiveness of Sr genes was analysed under field conditions in the southern region of Russia (Krasnodar Krai, Stavropol Krai and Rostov Oblast) during 2016-2021. The data were obtained using a set of 46 isogenic lines and varieties with artificial inoculation. The Sr31 gene proved absolute effectiveness in the field. Effective (1R–10R) Sr genes were the following: 5, 12, 35 and 37; moderately effective (10MR–30MR) Sr genes: 1, 6, 9g, 10, 11, 13, 14, 15, 20, 22, 23, 24, 25, 32, 33, 38 and WLD. Lines with Sr genes 7a, 7b, 8a, 8b, 9a, 9b, 9d, 9e, 9f, 16, 17, 19, 21, 26, 27, 29, 30, 36, 39, 40, 44, Dp2, Gt and Tmp were ineffective in the adult plant phase (30MS–70S). Polymorphism of infection types and disease severity was noted for most of these lines in different years. Ongoing analysis of the efficiency of Sr genes in the region is important to prevent the risk of epidemics, and lines with stem rust resistance genes that have shown efficiency can be used as donors in breeding programmes.

Leaf blight was detected on potted blood lily (Scadoxus multiflorus) plants in a garden located in Andhra Pradesh, India. Pycnidia resembling a Lasiodiplodia species were consistently detected on the foliage of symptomatic plants. Based on morphology, cultural features and molecular analysis, the species was identified as Lasiodiplodia theobromae. Koch's postulates were fulfilled by pathogenicity tests carried out on potted blood lily plants. To the best of our knowledge, this is the first report of the occurrence of a disease caused by L. theobromae on S. multiflorus.

Banana (Musa acuminata Cavendish Subgroup) cultivation plays a pivotal role in Vietnam's economy. However, the presence of postharvest diseases poses significant challenges as they adversely affect the quality and market value of the crop. The objective of this study was to identify the microbial strains responsible for these diseases through phylogenetic analysis and morphological characterisation. Four fungal isolates including Colletotrichum musae, C. gloeosporioides, Fusarium musae and Lasiodiplodia theobromae were identified as the primary causal agents of fruit rot in postharvest bananas. Re-infection tests, which were conducted following Koch's postulates on banana samples, confirmed the isolates' significant pathogenicity, leading to weight loss, colour alteration, firmness reduction and acidity changes in the fungal-infected bananas. These findings hold profound implications for enhancing our understanding of banana diseases in the postharvest stage, which can contribute to the development of effective control measures and mitigation strategies in the future.