Journal of Phytopathology最新文献

{"title":"Plant Disease Detection: PyramidNet-ICNN Architecture With Modified BIRCH Segmentation","authors":"Aarti P. Pimpalkar,&nbsp;Arvind M. Jagtap","doi":"10.1111/jph.70068","DOIUrl":"https://doi.org/10.1111/jph.70068","url":null,"abstract":"<div>\u0000 \u0000 <p>Agriculture stands as the primary occupation in India, yet it faces a substantial annual loss of 35% in crop productivity due to plant diseases. These diseases pose a significant task in the sector of agriculture, emphasising the critical need for their automatic identification to efficiently monitor plant health. The conventional technique of analysis by specialists in laboratories is costly and time-consuming, even though the signs of the majority of diseases appear in plant leaves. Recognising the vital importance of early issue identification, this research proposes a novel hybrid Architecture, a hybrid of PyramidNet and ICNN models (Py-ICNN) for plant disease detection and classification with an Improved BIRCH (I-BIRCH) segmentation model, which uses an image as input. This framework follows a systematic approach, comprising preprocessing, segmentation, extraction of features and detection and classification of diseases. Using median and Contrast Limited Adaptive Histogram Equalisation (CLAHE) filtering, the input image first undergoes enhanced preprocessing. The preprocessed outcome is then subjected to I-Balanced Iterative Reducing and Clustering Using Hierarchies (BIRCH) segmentation. Then, features including IPHOG, multi-texton features and MBP-based features are extracted from the segmented image. These extracted features are then individually processed using PyramidNet and improved convolutional neural network (ICNN) to detect and classify the plant disease. Furthermore, the proposed Py-ICNN model is evaluated and compared with traditional methods. The findings demonstrate that the Py-ICNN framework obtained an accuracy of 93.70% and a specificity of 95.82%. These results demonstrate how well the Py-ICNN approach detects and classifies plant diseases.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rice Plant Disease Diagnosis Using SqueezeNet and Deep Transfer Learning","authors":"Santosh Kumar Upadhyay,&nbsp;Anshu Kumar Dwivedi","doi":"10.1111/jph.70092","DOIUrl":"https://doi.org/10.1111/jph.70092","url":null,"abstract":"<div>\u0000 \u0000 <p>Rice serves as a fundamental food source for around 50% of the world's population, mostly in Asia, where agriculturalists have difficulties due to several rice illnesses that may result in substantial crop losses. Timely identification of these illnesses is essential to avert such losses; yet swift and precise diagnosis continues to be challenging owing to constrained knowledge and resources. This research investigates the use of deep transfer learning for the automation of identifying and classifying rice leaf diseases, including blast, brown spot, blight, sheath blight and tungro. We have sourced dataset consisting of 2550 image samples divided into five categories from the Kaggle. Each category has 510 images of infected leaves. By using contrast stretching for image enhancement and data augmentation for data enrichment, we applied a modified SqueezeNet pre-trained deep network on processed dataset, achieved 99.30% accuracy in disease recognition. The final convolutional layer (conv. layer 10) of the pre-trained SqueezeNet is modified by applying multiscale feature aggregation (MFA) in place of 1 × 1 standard convolution. MFA consists of two parallel convolution paths with different kernel size to captures diverse features of the infected lesions. The model's proficiency is highlighted by precision values ranging from 0.972 to 1.000 and recall values between 0.980 and 1.000, whereas maintaining an extremely low error rate between 0.0% and 0.3%, highlighting its high effectiveness. In a comparison with state-of-the-art (SOTA) models under a similar experimental setup, the proposed model demonstrates superior performance in terms of precision, recall, F1-score and accuracy. The proposed method offers a fast, cost-effective and accurate solution to assist farmers in disease detection, even with small datasets and complex backgrounds.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physiological Responses of Maize Leaves Exposed to Ethylene and Infected by Exserohilum turcicum","authors":"Lillian Matias Oliveira,&nbsp;Andersom Milech Einhardt,&nbsp;Bianca Apolônio Fontes,&nbsp;Luiz Felipe Castro Carmo Pinto,&nbsp;Dimas Mendes Ribeiro,&nbsp;João Américo Wordell Filho,&nbsp;Fabrício Ávila Rodrigues","doi":"10.1111/jph.70086","DOIUrl":"https://doi.org/10.1111/jph.70086","url":null,"abstract":"<div>\u0000 \u0000 <p>The hormone ethylene (ET) plays multiple roles in plant growth and development. However, its involvement in the maize–<i>Exserohilum turcicum</i> interaction must be better elucidated. This study investigated the role of ET in the infection process of <i>E. turcicum</i> on maize leaves at the physiological (leaf gas exchange and chlorophyll <i>a</i> fluorescence parameters and concentrations of photosynthetic pigments) and biochemical [concentrations of malondialdehyde (MDA), hydrogen peroxide (H₂O₂) and superoxide anion radical] levels. Plants were sprayed with water (control), ET or aminooxyacetic acid (AOA) (an inhibitor of ET production) and challenged or not with <i>E. turcicum</i>. ET was not detected in the infected leaves of ET- or AOA-sprayed plants compared to noninfected leaves exposed to ET. The symptoms of northern corn leaf blight were very well developed in the leaves of ET-sprayed plants. Moreover, the greatest disease severity was closely associated with higher concentrations of MDA and H₂O₂ in the leaf tissues, indicating intense lipid peroxidation. On top of that, the photosynthetic apparatus was significantly impaired considering the lower values for net carbon assimilation rate, stomatal conductance, transpiration rate and maximal photosystem II quantum yield. In conclusion, the exogenous supply of ET to maize leaves was of pivotal importance in favouring the infection process of <i>E. turcicum</i> in maize leaves.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and Plant Disease Management: An Agro-Innovative Approach","authors":"Kritika Minhans,&nbsp;Sushma Sharma,&nbsp;Imran Sheikh,&nbsp;Saleh S. Alhewairini,&nbsp;Riyaz Sayyed","doi":"10.1111/jph.70084","DOIUrl":"https://doi.org/10.1111/jph.70084","url":null,"abstract":"<div>\u0000 \u0000 <p>The implementation of artificial intelligence (AI) systems in agriculture leads to intelligent operational systems for immediate field management needs. Modifications in AI, specifically regarding plant disease the detection have turned this technology into a revolutionary instrument that modern agriculture depends on. The growing human population requires smart farming technology for boosting efficiency in crop cultivation since conventional expansion of agricultural land is no longer feasible. The combination of constrained land sizes with labour scarcity and environmental issues affecting soil productivity along with limited production results lead to technology adoption becoming needed. Imported through AI, precision farming provides maximum efficiency in productivity by performing instantaneous property assessments to achieve superior crop protection and leadership decisions and disease management. Agricultural automation enables higher efficiency through IoT because it reduces human interaction. Disease diagnosis by AI-based systems with machine learning and computer vision facilitates early detection, enabling automated monitoring and decision systems that enable optimisation of the use of resources and losses in agricultural products. The implementation of AI technology faces drawbacks from limited availability of data, and difficulty in understanding models, and difficulties with technology deployment in basic facilities. The integration of AI-based tools also requires farmers to acquire technical expertise because existing farmer-centric systems do not exist for them to use. The complete agricultural transformation and global food security need the removal of these important barriers that limit AI application.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preconditioning Hormesis of the Fungicide Dimethachlone on Mycelial Growth and Aggressiveness of Sclerotinia sclerotiorum","authors":"Wanjun Chen,&nbsp;Pengju Wang,&nbsp;Fuxing Zhu","doi":"10.1111/jph.70090","DOIUrl":"https://doi.org/10.1111/jph.70090","url":null,"abstract":"<div>\u0000 \u0000 <p>Preconditioning hormesis refers to the phenomenon that early exposure (preconditioning) to low doses of a toxicant may reduce the potency of the subsequent high doses of the same toxicant. This paper investigated the preconditioning hormetic effects of the dicarboximide fungicide dimethachlone on mycelial growth and aggressiveness of the necrotrophic phytopathogen <i>Sclerotinia sclerotiorum</i>. <i>S. sclerotiorum</i> was cultured on potato dextrose agar (PDA) amended with different doses of dimethachlone. After the preconditioned mycelia were transferred onto PDA amended with a highly challenging concentration of dimethachlone, significant stimulation of mycelial growth was detected. The aggressiveness of the preconditioned mycelia to rapeseed leaves sprayed with a high concentration of dimethachlone was also enhanced, and the maximum stimulation magnitude for lesion size averaged 19.1% for the six isolates tested. Mycelia with the maximum stimulation in the preconditioning treatment were transferred onto PDA amended with challenging concentrations of dimethachlone, and mycelial growth of the second generation displayed a similar stimulation magnitude of around 10% for different challenging concentrations of dimethachlone. After dimethachlone-preconditioned mycelia were subjected to similar in vitro and in vivo tests with high concentrations of challenging iprodione, carbendazim, and boscalid, only iprodione induced significant growth and aggressiveness stimulations. These results indicate that preconditioning hormesis could occur for fungicides with the same mode of action. For <i>S. sclerotiorum</i> mycelia preconditioned with dimethachlone, control efficacies of dimethachlone and iprodione were reduced slightly, whereas no decreases in control efficacies were found for carbendazim and boscalid.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"First Report of Blast Disease on Hymenachne amplexicaulis Caused by Pyricularia oryzae in Argentina","authors":"Lisandro Martín Bastida,&nbsp;Susana Alejandra Gutiérrez,&nbsp;Gustavo Bich,&nbsp;María Lorena Castrillo,&nbsp;Marcelo Aníbal Carmona,&nbsp;Lourdes Cardozo Téllez,&nbsp;Alice Rocío Chávez","doi":"10.1111/jph.70093","DOIUrl":"https://doi.org/10.1111/jph.70093","url":null,"abstract":"<div>\u0000 \u0000 <p>In 2022, blast-like symptoms were observed on <i>Hymenachne amplexicaulis</i> plants in Argentina. The causal agent was identified as <i>Pyricularia oryzae</i> based on its cultural and morphometric characteristics, sequencing of the ITS1–5.8S–ITS2 region, phylogenetic analysis, and PCR amplification of the Pot2 transposon marker. Koch's postulates were fulfilled through pathogenicity tests on both <i>H. amplexicaulis</i> and <i>Oryza sativa</i> cv. Guri INTA CL, placing the isolate within a clade that includes <i>P. oryzae</i> strains known to infect <i>Oryza</i> spp. The ITS sequence was deposited in GenBank under accession number OR741771. To the best of our knowledge, this is the first report worldwide of <i>H. amplexicaulis</i> serving as a host for <i>P. oryzae</i>.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rhizospheric Bacteria: Promising Candidates for Biocontrol of Apple Trunk Pathogens","authors":"Khadija Goura,&nbsp;Nabila El Alami,&nbsp;Salah-Eddine Laasli,&nbsp;Rachid Lahlali,&nbsp;Abdessalem Tahiri","doi":"10.1111/jph.70083","DOIUrl":"https://doi.org/10.1111/jph.70083","url":null,"abstract":"<div>\u0000 \u0000 <p>Biocontrol provides a compelling alternative to fungicide applications for plant disease management. In the present study, bacteria from the rhizosphere of different fruit trees in Morocco were tested for their potential to inhibit causal agents of trunk diseases in apple trees, including <i>Lasiodiplodia theobromae</i>, <i>Diaporthe eres</i>, <i>Neopestalotiopsis rosae</i> and <i>Diplodia seriata.</i> These pathogens pose a considerable threat to worldwide apple production. Fifteen rhizobacterial isolates demonstrated notable antifungal activity against the tested fungal pathogens in vitro. Sequencing analysis classified these isolates into three bacterial genera: <i>Bacillus</i>, <i>Stenotrophomonas</i> and <i>Alcaligenes.</i> In vitro experiments demonstrated that <i>Bacillus</i> species were the most effective in inhibiting the mycelial growth of the aforementioned pathogens. For instance, <i>B. subtilis</i> PH31Z8 was highly effective against <i>D. seriata</i> (94.22% growth inhibition after 3 days), <i>B. amyloliquofaciens</i> PH34Z5 showed strong antagonistic activity against <i>L. theobromae</i> (94.12% inhibition) and <i>D. eres</i> (93.10%), whereas <i>B. tequilensis</i> AH31Z6 demonstrated notable efficacy against <i>N. rosae</i> (74.66%). Most of these bacterial strains secreted hydrolytic enzymes that can degrade fungal cell walls. In plant growth promotion assays with <i>Brassica napus</i> seedlings, the selected bacteria, particularly strains PH1Z8 and PM6Z12, enhanced plant growth compared with the negative controls. Experiments under glasshouse conditions revealed limited effectiveness of the antagonistic bacteria in reducing infections on apple plants, except for <i>D. seriata</i> treated with <i>B. amyloliquefaciens</i> PH34Z5, <i>B. subtilis</i> PH31Z8 and <i>B. siamensis</i> PC4Z9, which showed notable results. This study provides essential groundwork for advancing research on the biological control of apple canker diseases.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"First Report of Botryosphaeria dothidea Causing Leaf Blight on Aesculus chinensis in China","authors":"Cuicui Wang,&nbsp;Lina Liu,&nbsp;Yongguang Liu,&nbsp;Zihao Wu,&nbsp;Chao Li,&nbsp;Haoqin Pan","doi":"10.1111/jph.70085","DOIUrl":"https://doi.org/10.1111/jph.70085","url":null,"abstract":"<div>\u0000 \u0000 <p>In July 2024, a leaf blight disease was observed on <i>Aesculus chinensis</i> plants in Shandong Province, China. The disease presented as brown lesions progressing to light brown. The morphological features of colonies and conidia observed on PDA medium were consistent with those of <i>Botryosphaeria dothidea</i>. Pathogenicity tests were conducted on <i>A. chinensis</i> leaves using both greenhouse-grown seedlings and field-grown mature trees through a wound inoculation method. Brown lesions developed on the inoculated leaves of both seedlings and mature trees, whereas no symptoms appeared on the control leaves. The ITS, translation elongation factor 1-alpha (<i>TEF1</i>) and β-tubulin (<i>TUB</i>) regions from the isolates were amplified and sequenced. BLAST analysis of these three genes revealed 99.61%–100.00% identity with the corresponding sequences of <i>B. dothidea</i> ex-epitype strain (CBS 115476) available in GenBank. Phylogenetic analysis further confirmed the identification of the pathogen as <i>B. dothidea</i>. This study represents the first report of <i>B. dothidea</i> causing leaf blight disease on <i>A. chinensis</i> in China.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144197061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Strawberry Disease Associated With Leaf Spot, Crown Rot, and Root Rot Caused by Neopestalotiopsis rosae in Italy","authors":"Stefania Mirela Mang,&nbsp;Ippolito Camele,&nbsp;Carmine Palmieri,&nbsp;Carmine Marcone","doi":"10.1111/jph.70071","DOIUrl":"https://doi.org/10.1111/jph.70071","url":null,"abstract":"<p>In the spring of 2023 in Eboli and Caserta (Campania, southern Italy), strawberry plants (var. Marimbella) grown in organic open fields showed an outbreak of a severe and unprecedented decline (disease incidence reaching &gt; 80%) associated with root rot, crown rot, and leaf spot and closely resembling symptoms reported previously in other countries for <i>Neopestalotiopsis</i> spp. infection. Therefore, the present study was undertaken with the aim of determining the aetiology of this serious disease. Fungal isolates were obtained from symptomatic strawberry plants and investigated in detail for molecular identification. Phylogenetic analysis was conducted by amplifying and sequencing three DNA barcodes: the internal transcribed spacer (ITS) region of rDNA, the β-tubulin (<i>tub2</i>) partial gene, and the translation elongation factor 1α (<i>tef1</i>) partial gene. Symptoms observed in the field were replicated in pathogenicity tests, conducted by inoculating strawberry (var. Marimbella) leaves, fruits and plants, thus satisfying Koch's postulates. Phylogenetic analyses identified the causal agent as <i>Neopestalotiopsis rosae</i>. To our knowledge, this is the first report of the emerging and serious fungal pathogen <i>N</i>. <i>rosae</i> infecting strawberry in Italy.</p>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jph.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alternaria alternata Causing Leaf Spot on Sophora alopecuroides in China","authors":"Yufei Gou,&nbsp;Manmei Wu,&nbsp;Hong Zhang,&nbsp;Shuhua Wei,&nbsp;Jianli Liu","doi":"10.1111/jph.70082","DOIUrl":"https://doi.org/10.1111/jph.70082","url":null,"abstract":"<div>\u0000 \u0000 <p><i>Sophora alopecuroides</i> is a medicinal herb with high alkaloid content that is crucial in sand fixation in northwest China. In September 2023, a leaf spot disease was detected on wild <i>S. alopecuroides</i> growing in semi-arid steppe in Yanchi county (Ningxia, China). Based on morphological features and <i>tef1</i>, <i>gapdh</i> and <i>rpb2</i> sequence analysis, the representative isolates obtained from the leaf spots (H3 and H4) were identified as <i>Alternaria alternata</i>. Koch's postulates for pathogenicity tests were completed on <i>S. alopecuroides</i> seedlings. To our knowledge, this is the first report of <i>A. alternata</i> causing leaf spot on <i>S. alopecuroides</i> in China.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"173 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}