Journal of Phytopathology最新文献

{"title":"Biocontrol Potential of Bacillus velezensis ZF-10 Inhibiting Potato Virus Y and Promoting Growth of Tobacco Plant","authors":"Yufeng Ying,&nbsp;Nuoni Zhang,&nbsp;Bin Li,&nbsp;Dongyang Liu,&nbsp;Qiang Zhang,&nbsp;Zhao Yang,&nbsp;Derong An,&nbsp;Xingan Hao","doi":"10.1111/jph.70002","DOIUrl":"https://doi.org/10.1111/jph.70002","url":null,"abstract":"<div>\u0000 \u0000 <p>The viral disease caused by potato virus Y (PVY) poses a serious threat to tobacco plants worldwide. In this study, <i>Bacillus velezensis</i> ZF-10, isolated from Panzhihua, China, exhibited an effective inhibitory effect against PVY. The presence of <i>B. velezensis</i> ZF-10 significantly reduced the accumulation of PVY to 25.4% in plants and lowered the disease index to 15.23. Moreover, the infiltration of <i>B. velezensis</i> ZF-10 on leaves of tobacco resulted in an increase in reactive oxygen species (ROS) and enhanced defence enzyme activity, leading to a decrease in malondialdehyde (MDA) accumulation and ultimately improving the tolerance of tobacco plants to PVY infection. Additionally, in a greenhouse environment, <i>B. velezensis</i> ZF-10 promoted the growth of tobacco plants. Furthermore, <i>B. velezensis</i> ZF-10 was found to exhibit activities such as ammonia production, cellulase, protease and siderophore production, and the ability to solubilise insoluble phosphates in soil. As a novel plant growth-promoting bacterium (PGPB), <i>B. velezensis</i> ZF-10 not only effectively suppressed the occurrence of PVY disease and enhanced tobacco growth but also demonstrated potent antifungal properties against various phytopathogens that cause diseases in tobacco plants and other crops. In conclusion, <i>B. velezensis</i> ZF-10 is a potential biocontrol agent against PVY infection a supporter of plant growth for tobacco plant.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119013","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":"Skill-Honey Badger Optimisation Algorithm-Enabled Deep Convolutional Neural Network for Multiclass Leaf Disease Detection in Tomato Plant","authors":"Naresh Kumar Trivedi,&nbsp;Sachin Jain,&nbsp;Alok Misra,&nbsp;Raj Gaurang Tiwari,&nbsp;Shikha Maheshwari,&nbsp;Vinay Gautam","doi":"10.1111/jph.70001","DOIUrl":"https://doi.org/10.1111/jph.70001","url":null,"abstract":"<div>\u0000 \u0000 <p>In today's life, agriculture holds considerable importance in human life and the economy of a nation. Agriculture, including tomato farming, plays a vital role as one of the most extensively consumed vegetables worldwide. However, tomato crops are very prone to diseases, leading to reduced production and economic down in agricultural fields. To solve these issues, an effective method is proposed named Skill-Honey Badger Optimisation Algorithm-enabled deep convolutional neural network (CNN) (SHBOA_DeepCNN) for detecting leaf disease in tomato plants. In this method, the input is primarily preprocessed by utilising Savitzky–Golay (SG) filtering. Then, segmentation is performed by utilising Dense-Res-Inception Net (DRINet), which is trained by using devised SHBOA. The proposed SHBOA is designed by incorporating the Skill Optimisation Algorithm (SOA) and Honey Badger Algorithm (HBA). Subsequently, image augmentation is performed on segmented images by using two augmentation techniques, namely, colour augmentation and position augmentation. At last, multiclass leaf disease detection is performed using DeepCNN, which is trained by devised SHBOA. The experimental analysis of the devised SHBOA_DeepCNN method showed a high accuracy of 91.91% and a true positive rate (TPR) of 90.24%. Moreover, it achieved a minimum false positive rate (FPR) of 7.38%. The code of the article is available at “https://github.com/Amisra-98/SHBOA_DeepCNN.git”.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118633","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":"Potato Leaf Disease Detection and Classification With Weighted Ensembling of YOLOv8 Variants","authors":"Muthunayagam Muthulakshmi,&nbsp;Nagasubramanian Aishwarya,&nbsp;Rajes Kumar Vinesh Kumar,&nbsp;Babu Rakesh Thoppaen Suresh","doi":"10.1111/jph.13433","DOIUrl":"https://doi.org/10.1111/jph.13433","url":null,"abstract":"<div>\u0000 \u0000 <p>The identification and control of potato leaf diseases pose considerable difficulties for worldwide agriculture, affecting both the quality and yield of crops. Addressing this issue, we investigate the efficacy of the lightweight YOLOv8 variants, namely YOLOv8n, YOLOv8s and YOLOv8m, for the automated detection and classification of different potato leaf states. These conditions are categorised into three types: healthy, early blight disease and late blight disease. Our findings show that YOLOv8n achieves a mean average precision (mAP) of 94.2%, YOLOv8s achieves a mAP of 93.4%, and YOLOv8m achieves a mAP of 94%. Building on these results, we propose a novel weighted ensembling technique based on the confidence score (WECS) to combine the predictions of these YOLOv8 variants. The WECS technique efficiently leverages the advantages of each YOLOv8 variant by assigning weights based on the confidence scores of individual model predictions. These weighted forecasts are then combined to produce a final ensemble prediction for each sample. Achieving 99.9% precision and 89.6% recall, the WECS method attains a global mean Average Precision (mAP) of 96.3%, showcasing its robustness in real-world applications.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861744","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":"Increasing Soybean Resistance Against Rust Using a Product Containing Calcium and Nitrogen Complexed With Polyphenols","authors":"Bianca Apolônio Fontes,&nbsp;Leandro Castro Silva,&nbsp;Bruno Nascimento Silva,&nbsp;Luis Felipe Lata-Tenesaca,&nbsp;Verônica Vieira Brás,&nbsp;Fabrício Ávila Rodrigues","doi":"10.1111/jph.70004","DOIUrl":"https://doi.org/10.1111/jph.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>Among soybean diseases, rust, caused by <i>Phakopsora pachyrhizi</i>, stands out as one of the most destructive. Resistance inducers may be a great alternative to reduce the yield losses caused by this disease from the perspective of more sustainable agriculture. In this study, soybean plants were sprayed with water (control) or with Cautha [referred to as induced resistance (IR) stimulus after that] and inoculated or non-inoculated with <i>P</i>. <i>pachyrhizi</i>. The germination of urediniospores was significantly reduced by 22%, 26%, 19%, and 25% for the IR stimulus rates of 2.5, 5, 10, and 20 mL/L, respectively. Rust severity was significantly reduced by 27%, 19%, 23%, 25%, and 41% at 7, 9, 11, 13, and 15 days after inoculation, respectively, and the area under the disease progress curve significantly decreased by 27% for IR stimulus-sprayed plants compared to water-sprayed plants. For infected plants, foliar concentrations of Ca, N, chlorophyll <i>a</i> + <i>b</i>, and carotenoids were higher for IR-stimulus sprayed plants than for water-sprayed plants. Lower concentrations of malondialdehyde (less cellular damage) and reactive oxygen species (hydrogen peroxide and superoxide anion radical) along with great activities of antioxidative enzymes (ascorbate peroxidase, catalase, glutathione reductase, and superoxide dismutase) helped to reduce rust symptoms for IR-stimulus sprayed plants. On top of that, these plants also showed greater foliar concentrations of total soluble phenols and lignin as well as increased activities of defence-related enzymes (chitinase, <i>β</i>-1,3-glucanase, phenylalanine ammonia-lyase, peroxidase, polyphenoloxidase, and lipoxygenase). These results strongly support the potential of using this IR stimulus to increase soybean resistance against infection by <i>P</i>. <i>pachyrhizi</i> and, at the same time, to act directly against the germination of the urediniospores.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861743","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":"Enterobacter mori Causing Leaf Spot and Soft Rot in Three New Ornamental Hosts","authors":"Fatemeh Bolhasani,&nbsp;Nargues Falahi Charkhabi","doi":"10.1111/jph.13440","DOIUrl":"https://doi.org/10.1111/jph.13440","url":null,"abstract":"<div>\u0000 \u0000 <p>Leaf spot and soft rot of ornamental plants were observed in the Alborz and Markazi provinces during the summer and autumn of 2022. Eighteen samples were collected from symptomatic ornamental plants in Karaj and Arak cities. Necrotic leaf spots surrounded by a broad yellow halo were observed in the affected pothos (<i>Epipremnum aureum</i>) and compact dragon (<i>Dracaena compacta</i>) plants. On the severely affected, leaves of compact dragon with a yellow margin were observed. Soft rot symptoms which turned dark brown areas were observed on the diseased jade plants (<i>Crassula ovata</i>). The colonies of bacterial strains were cream-coloured, round, convex, smooth and with entire margins on nutrient agar. In the pathogenicity of 35 recovered strains, the five strains isolated from pothos caused water-soaking 2 days after inoculation, which finally turned into necrotic lesions surrounded by chlorotic halos. Eight strains isolated from compact dragon produced necrotic spots on the inoculated plants. Five strains originated from jade plants induced soft rot 4–5 days post-inoculation. All 18 pathogenic strains were negative in Gram and oxidase reactions. The <i>gyrB</i> and <i>infB</i> gene sequences of eight representative strains were partially amplified and sequenced. In the maximum-likelihood phylogenetic tree created based on the concatenated sequences of <i>gyrB</i> and <i>infB</i> genes, the strains clustered with <i>Enterobacter mori</i> LMG 25706^T supported with bootstrap value of 100%. To the best of our knowledge, this is the first report of pothos and compact dragon leaf spot and jade plant soft rot caused by <i>E. mori</i>.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851368","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":"Pathogenicity and Biological Characteristics of Botryosphaeria dothidea Causing Branch Blight of Salix babylonica","authors":"Yu Wan,&nbsp;Yue Ju,&nbsp;De-Wei Li,&nbsp;Li-Hua Zhu","doi":"10.1111/jph.70006","DOIUrl":"https://doi.org/10.1111/jph.70006","url":null,"abstract":"<div>\u0000 \u0000 <p><i>Salix babylonica</i> L. is a popular ornamental and ecological tree species. In this study, the results of pathogenicity tests showed that the <i>Botryosphaeria dothidea</i> isolates JXL1-3, JXL1-5, JXL1-11, L1-3, L2-2, NFS1, NFS2, NFS5 and WLS1 were pathogens causing branch blight on <i>S. babylonica</i>. Meanwhile, the <i>B. dothidea</i> isolates JXL1-11, L1-3, NFS1 and WLS1 were found to be pathogenic to two other willows, <i>S</i>. <i>chaenomeloides</i> and <i>S. suchowensis</i>. The biological characteristics of <i>B</i>. <i>dothidea</i> isolates JXL1-11, L1-3, NFS1 and WLS1 were investigated under different conditions, including culture media, pH, temperatures, carbon/nitrogen sources and light. It was found that potato dextrose agar (PDA) medium was the most optimal medium for the <i>B</i>. <i>dothidea</i> isolates JXL1-11, L1-3, NFS1 and WLS1 mycelial growth, the suitable pH was 4, and the optimal temperatures were 25°C–30°C. The optimal carbon sources were glucose and sucrose, and the optimal nitrogen sources were ammonium sulfate and peptone. The optimal light condition for inducing sporulation was dark + ultraviolet light. This study provides a fundamental basis for the prevention and control the branch blight on willows and further studies.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861554","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":"In Planta Inoculation of Trichoderma viridarium Reduces Seed Transmission of the Fungal Pathogen Alternaria brassicicola","authors":"Thomas Lerenard,&nbsp;Sophie Aligon,&nbsp;Pascal Poupard,&nbsp;Josiane Le Corff","doi":"10.1111/jph.70000","DOIUrl":"https://doi.org/10.1111/jph.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>Biological control by beneficial microorganisms is considered as one of the best alternatives to decrease the use of chemical fungicides. However, reliable and efficient solutions to manage crop diseases are still limited, and this is particularly true for seedborne fungal pathogens. As a first step towards identification of potential biological control agents (BCAs), a new methodological approach <i>in planta</i> was developed to control <i>Alternaria brassicicola</i>, a problematic fungal disease of <i>Brassica</i> crops. The method was used to evaluate the antagonistic activity of <i>Trichoderma viridarium</i> on transmission of the pathogen to seeds of <i>Capsella bursa-pastoris</i> (sheperd's purse). In vitro, inhibition of <i>A. brassicicola</i> and overgrowth by <i>T. viridarium</i> suggested mycoparasitism, which was confirmed by microscopical observations. <i>In planta</i>, siliques of <i>C. bursa pastoris</i> were co-inoculated with <i>T. viridarium</i> and <i>A. brassicicola</i> and seed transmission of each fungal species was evaluated. Pre-inoculation of <i>T. viridarium</i> 24 h before <i>A. brassicicola</i> significantly reduced the transmission of the pathogen to the seeds by almost 70%, compared with inoculation of <i>A. brassicicola</i> alone. The capacity of <i>T. viridarium</i> to reduce <i>A. brassicicola</i> seed transmission offers a promising alternative to conventional fungicides. However, in order to develop reliable biocontrol strategies, future research should focus on the underlying mechanisms involved in the interactions between <i>T. viridarium</i>, <i>A. brassicicola</i> and the host plant.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861505","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":"Germination and Viability of Albugo candida Oospores Infecting Indian Mustard (Brassica juncea)","authors":"Nitish Rattan Bhardwaj,&nbsp;Prashant Yadav,&nbsp;Bheeru Lal Meena,&nbsp;Hariom Kumar Sharma,&nbsp;Pramod Kumar Rai","doi":"10.1111/jph.70007","DOIUrl":"https://doi.org/10.1111/jph.70007","url":null,"abstract":"<div>\u0000 \u0000 <p><i>Albugo candida</i> causing white rust disease is a serious threat in cultivation of oilseed Brassicas particularly <i>Brassica juncea</i> when inflorescence infection (staghead) is high. Stagheads carry oospores which are the perpetuating structures and primary source of inoculum in white rust disease. However, two aspects that still needs to be addressed in <i>A. candida</i>-<i>B. juncea</i> pathosystem are determination of optimum oospore germination conditions and oospore viability assessment. Thus, here we have described a protocol for optimum oospore germination in samples derived from naturally infected stagheads of <i>B. juncea</i> on β-glucuronidase aryl sulfatase (a type of snail gut enzyme) treatment. The results indicates that 3% enzyme concentration induces ≥ 50% of oospores to germinate at 7°C, 10°C and 13°C after incubating for 24–48 hours. We also determined viability of staghead-derived and seed lot derived oospores through plasmolysis (using 4 M sodium chloride) and trypan blue staining. The results indicate the significant superiority of plasmolysis method in detecting viable oospores of <i>A. candida</i> than trypan blue staining. The techniques described here can be utilised for carrying out studies on oospore mating behaviour, sexual recombination and assessment of oosporic inoculum viability in <i>A. candida</i>-<i>B. juncea</i> pathosystem.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851501","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":"Modelling Citrus Huanglongbing Spread in Scenarios Involving Alternative Hosts, Vector Populations and Removal of Symptomatic Plants","authors":"Sônia Ternes,&nbsp;Raphael G. d' A. Vilamiu,&nbsp;Alécio Souza Moreira,&nbsp;Marcelo Rossi,&nbsp;Tâmara T. de C. Santos,&nbsp;Francisco Ferraz Laranjeira","doi":"10.1111/jph.13445","DOIUrl":"https://doi.org/10.1111/jph.13445","url":null,"abstract":"<div>\u0000 \u0000 <p>Huanglongbing (HLB) is the most devastating citrus disease around the world. We have modelled HLB spread in scenarios with different populational levels of the main alternative host (<i>Murraya paniculata</i>) and <i>Diaphorina citri</i> Kuwayama (Asian citrus psyllid—ACP) vector of HLB-associated bacteria and the removal of HLB-symptomatic plants. A compartmental deterministic mathematical model was built for representing the HLB dynamics in the Recôncavo Baiano, Bahia State, Brazil. The model encompasses delays on latency and incubation disease periods and on the ACP nymphal stages. The simulations indicated that presence of alternative hosts at a low proportion would not play a crucial role in HLB dynamics in situations of poor ACP management, regardless of HLB-symptomatic plant eradication. Symptomatic citrus plants contribute more to increase the HLB incidence than the alternative host in scenarios without a suitable ACP management.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861204","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":"Enhanced Segmentation and Ensemble Classification for Accurate Plant Disease Detection","authors":"P. Santhosh Kumar,&nbsp;K. Kalaivani,&nbsp;R. Balakrishna","doi":"10.1111/jph.13426","DOIUrl":"https://doi.org/10.1111/jph.13426","url":null,"abstract":"<div>\u0000 \u0000 <p>The majority of the crops are wasted owing to deficiency of transport, plant diseases and lack of storage facilities. Above 15% of crops are worn out in India owing to diseases and therefore it has turned out to be a main concern to be solved. This study introduces an advanced framework for plant disease detection by integrating enhanced image segmentation techniques with robust ensemble classification models. Our methodology begins with the pre-processing of plant leaf images using median filtering and Wiener denoising to reduce noise and enhance image quality. As the next step, the Improved Region Growing Algorithm (IRGA) is deployed for the segmentation of images. Then, features together with ‘Scale Invariant Feature Transform (SIFT), improved Binary Gabor Pattern (IBGP), Haralick features, color features like RGB Color Histogram, disease area and higher order statistical features (Entropy, Skewness, variance and kurtosis)’ are extracted. The improved independent component analysis (IICA) model is then used to choose the best attributes. Lastly, detection takes place using Ensemble classifiers (EC) including Neural Network (NN), modified effective squeeze and excitation block-based deep convolutional neural network (M-ESE-DCNN) and bi-directional gated recurrent unit (BI-GRU). Further, the DCNN weights are optimised via the Colliding Archimedes and Teamwork Algorithm (CA-TWA) model. For the best case with dataset 1, EC + CA-TWA got a high accuracy of 0.94, while EC + BOA, EC + DOX, EC + SSO, EC + TOA and EC + ArOA had lower accuracy. Furthermore, for all schemes, dataset 1 displays superior outputs to dataset 2 and dataset 3. Finally, an evaluation is done to validate this work.</p>\u0000 </div>","PeriodicalId":16843,"journal":{"name":"Journal of Phytopathology","volume":"172 6","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860973","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}