Plant Diseases Research Articles

Impacts of a Commercially Available Horticultural Oil Biopesticide (EF-400) on the Tomato-Phytophthora infestans Pathosystem.

Biopesticide fungicides are naturally derived compounds that offer protection from plant diseases through various modes of action, including antimicrobial activity and upregulation of defense responses in host plants. These plant protectants provide a sustainable and safe alternative to conventional pesticides in integrated disease management programs and are especially salient in the management of high-risk and economically important diseases such as late blight of tomato and potato, for which host resistance options are limited. In this study, a commercially available biopesticide, EF400 comprised of clove (8.2%), rosemary (8.1%), and peppermint oils (6.7%) (Anjon AG, Corcoran, CA), was investigated for its effects on the Phytophthora infestans-tomato pathosystem. Specifically, we evaluated the impact of EF400 on P. infestans growth in culture, disease symptoms in planta, and activation of host defenses through monitoring transcript accumulation of defense-related genes. The application timing and use rate of EF400 were further investigated for managing tomato late blight. EF400 delayed the onset of tomato late blight symptoms, although not as effectively as the copper hydroxide fungicide Champ WG (Nufarm Americas Inc., Alsip, IL). Pathogen mycelial growth and sporangial quantity on late blight-susceptible tomato leaves were significantly reduced with EF400. The biopesticide also had an enhancing or suppressing effect on the transcript accumulation of three defense-related genes: Pin2, PR1a, and PR1b. Our work in exploring a commercially available horticultural oil biopesticide meaningfully contributed to the essential knowledge base for optimizing recommendations for the management of tomato late blight.

Combined control of plant diseases by Bacillus subtilis SL44 and Enterobacter hormaechei Wu15

Co-incubation of plant growth promoting rhizobacteria (PGPRs) have been proposed as a potential alternative to pesticides for controlling fungal pathogens in crops, but their synergism mechanisms are not yet fully understood. In this study, combined use of Bacillus subtilis SL44 and Enterobacter hormaechei Wu15 could decrease the density of Colletotrichum gloeosporioides and Rhizoctonia solani and enhance the growth of beneficial bacteria on the mycelial surface, thereby mitigating disease severity. Meanwhile, PGPR application led to a reorganization of the rhizosphere microbial community through modulating its metabolites, such as extracellular polymeric substances and chitinase. These metabolites demonstrated positive effects on attracting and enhancing conventional periphery bacteria, inhibiting fungal pathogens and promoting soil health effectively. The improvement in the microbial community structure altered the trophic mode of soil fungal communities, effectively decreasing the proportion of saprotrophic soil and reducing fungal plant diseases. Certain combinations of PGPR have the potential to serve as precise instruments for managing plant pathogens.

Effector Cs02526 from Ciboria shiraiana induces cell death and modulates plant immunity.

Sclerotinia disease is one of the most devastating fungal diseases worldwide, as it reduces the yields of many economically important crops. Pathogen-secreted effectors play crucial roles in infection processes. However, key effectors of Ciboria shiraiana, the pathogen primarily responsible for sclerotinia disease in mulberry (Morus spp.), remain poorly understood. In this study, we identified and functionally characterized the effector Cs02526 in C. shiraiana and found that Cs02526 could induce cell deathin a variety of plants. Moreover, Cs02526-induced cell death was mediated by the central immune regulator BRASSINOSTEROID INSENSITIVE 1-associated receptor kinase 1 (BAK1), dependent on a 67-amino acid fragment. Notably, Cs02526 homologues were widely distributed in hemibiotrophic and necrotrophic phytopathogenic fungi, but the homologues failed to induce cell death in plants. Pre-treatment of plants with recombinant Cs02526 protein enhanced resistance against both C. shiraiana and Sclerotinia sclerotiorum. Furthermore, the pathogenicity of C. shiraiana was diminished upon spraying plants with synthetic dsRNA-Cs02526. In conclusion, our findings highlight the cell death-inducing effector Cs02526 as a potential target for future biological control strategies against plant diseases.

Eudistomins Y-Inspired Design and Divergent Optimization of Heteroaryl Ketones for New Antifungal Leads.

The discovery of structurally distinct leads is imperative in modern agrochemical science. Inspired by eudistomins Y and the framework-related pharmaceuticals, aryl heteroaryl ketone was drawn as a common model intriguing the design and divergent synthesis of 14 kinds of heteroaryl ketones aligned with their oxime derivatives. Antifungal function-oriented phenotypical screen protruded benzothiazolyl-phenyl oxime 5a as a promising model, and the concomitant modification led to benzothiazolyl oxime 5am (EC50 = 5.17 μM) as a superior lead than fluoxastrobin (EC50 = 7.54 μM) against Sclerotinia sclerotiorum. Scaffold hopping of the phenyl subunit identified benzothiazolyl-pyridyl oxime as a novel antifungal scaffold accompanied by acquiring oxime 5bm with remarkable activity (EC50 = 3.57 μM) against Pyricularia oryzae. Molecular docking showed that candidate 5am could form more hydrogen bonds with the amino acid residues of actin than metrafenone. This compound also demonstrated better curative efficacy than that of fluoxastrobin and metrafenone in controlling the plant disease caused by S. sclerotiorum. These results rationalize the discovery of antifungal candidates based on aryl heteroaryl ketone.

Characterization and evaluation of actinomycete from the Protaetia brevitarsis Larva Frass.

Protaetia brevitarsis larvae (PBL) are soil insects important for the soil organic carbon cycle, and PBL frass not only contains a large amount of humic acid but also affects the diversity, novelty, and potential functions of actinomycetes. Here, we characterized and assessed the actinomycete. The operational taxonomic unit (OTU) data showed that 90% of the actinomycetes cannot be annotated to species, and pure culture and genome analysis showed that 35% of the strains had the potential to be new species, indicating the novelty of PBL frass actinomycetes. Additionally, genome annotation showed that many gene clusters related to antifungal, antibacterial and insecticidal compound synthesis were identified, and confrontation culture confirmed the antifungal activities of the actinomycetes against soil-borne plant pathogenic fungi. The incubation experiment results showed that all isolates were able to thrive on media composed of straw powder and alkaline lignin. These results indicated that PBL hindgut-enriched actinomycetes could survive in soil by using the residual lignocellulose organic matter from plant residues, and the antibiotics produced not only give them a competitive advantage among soil microflora but also have a certain inhibitory effect on plant diseases and pests. This study suggests that the application of PBL frass can not only supplement soil humic acid but also potentially affect the soil microbiota of cultivated land, which is beneficial for the healthy growth of crops.

Boscalid + Pyraclotrobin Resistance and Expression of Succinate Dehyrogenase Genes (sdhA and sdhB) in Chestnut Blight Fungus Cryphonectria parasitica

Sweet chestnut, Castanea sativa Mill., is a significant species in Türkiye. The tree has been encountered with numerous diseases. Chestnut blight, caused by Cryphonectria parasitica (Murrill) M. E. Barr, is one of the most common diseases having spread to every chestnut-growing region. In this study, the effects of Bellis® (25.2% Boscalid + 12.8% Pyraclotrobin), a fungicide commonly used in plant disease control, were evaluated at different doses (10 ppm and 50 ppm) against the chestnut blight agent C. parasitica, which had not been previously studied for its effects in vitro. The isolates included two virulent strains (Cp1_2023, Cp2_2023) and two hypovirulent strains (Cp7_2023, Cp9_2023). The effects of Boscalid + Pyraclotrobin on the mycelial growth of the pathogenic fungus were determined for the first time in vitro, and these effects were detected at the sdhA and sdhB genes expression level. The results showed that the mycelial growth and pathogenicity of C. parasitica isolates in the fungicide-treated medium were consistent with the gene expression profile. Specifically, the virulent Cp1_2023 isolate exhibited higher mycelial growth, pathogenicity, and gene expression levels compared to the other isolate. In conclusion, it is recommended to conduct more detailed studies before using fungicides and to employ them in controlled environments.

A Mobile-Based System for Detecting Plant Leaf Diseases Using Deep Convolutional Neural Network

Plant diseases pose a significant challenge to agriculture in India, causing substantial losses in crop production each year. Limited-resource farmers often struggle with diagnosing these diseases accurately, especially when relying on visual observation of leaf symptoms. Hence, there is an urgent need to enhance the detection, monitoring, and prediction of crop diseases to mitigate agricultural losses effectively. To address this challenge, we propose a mobile-based system empowered by Machine Learning (ML) and computer vision tailored for the Indian context. Our system utilizes Convolutional Neural Networks (CNNs) as the core deep learning engine to classify 37 disease categories commonly found in Indian crops. We have curated a comprehensive dataset comprising 96,206 images of plant leaves, encompassing both healthy and infected, for training, validation, and testing purposes. The user interface of our system is designed as an Android mobile application, enabling farmers to capture images of diseased plant leaves effortlessly. Upon image capture, the system swiftly identifies the disease category and presents it to the user along with a confidence percentage. This functionality empowers farmers to take timely action to protect their crops, thereby reducing reliance on incorrect fertilizers that may exacerbate plant stress. Furthermore, we evaluated the performance of our system using various metrics, including classification accuracy and processing time. Our results indicate an impressive overall classification accuracy of 94% across the 37 disease classes prevalent in 14 different crop species commonly cultivated in India. In essence, our ML-powered mobile-based solution offers Indian farmers a robust tool for efficient crop disease diagnosis and management, ultimately contributing to the enhancement of agricultural productivity and sustainability in the country.

Unveiling Methods to Stimulate Plant Resistance against Pathogens.

Plant diseases caused by pathogens pose significant threats to agricultural productivity and food security worldwide. The traditional approach of relying on chemical pesticides for disease management has proven to be unsustainable, emphasizing the urgent need for sustainable and environmentally friendly alternatives. One promising strategy is to enhance plant resistance against pathogens through various methods. This review aims to unveil and explore effective methods for stimulating plant resistance, transforming vulnerable plants into vigilant defenders against pathogens. We discuss both conventional and innovative approaches, including genetic engineering, induced systemic resistance (ISR), priming, and the use of natural compounds. Furthermore, we analyze the underlying mechanisms involved in these methods, highlighting their potential advantages and limitations. Through an understanding of these methods, scientists and agronomists can develop novel strategies to combat plant diseases effectively while minimizing the environmental impact. Ultimately, this research offers valuable insights into harnessing the plant's innate defense mechanisms and paves the way for sustainable disease management practices in agriculture.

Estimation of Yield Loss Due to Striped Disease in Peanut Plants in Palopo City, South Sulawesi

Palopo City is one of the peanut production centres in South Sulawesi. However, from 2008 to 2020, groundnut production in Palopo City has decreased. Recently, in South Sulawesi, it was reported that peanut stripe virus infection has spread widely and evenly in peanut plants. Symptoms of stripe disease include dark green and light green leaf colour, chlorosis, and can cause stunting. This study aims to determine the estimation of yield loss caused by stripe disease in peanut plants in Polopo City, South Sulawesi. This research was conducted in a farmer-owned groundnut field located in Purangi Village, Sendana Subdistrict, Palopo City, South Sulawesi, from January to May 2023. Parameters observed were plant height, disease severity and incidence, and yield loss. Observations were made 6 times on plants aged 4 to 9 weeks after planting. The results showed that the symptoms of striped disease showed that the growth of peanut plant height was inhibited, and caused a decrease in the number of pods, pod weight, and pod number. Disease severity increased to 57.2% and disease incidence to 46.6%. Yield loss caused by stripe symptoms in peanut plants was 43.78%, indicating that high disease severity and incidence can reduce yield.

Nitric Oxide Mitigates the Deleterious Effects Caused by Infection of Pseudomonas syringae pv. syringae and Modulates the Carbon Assimilation Process in Sweet Cherry under Water Stress.

Bacterial canker is an important disease of sweet cherry plants mainly caused by Pseudomonas syringae pv. syringae (Pss). Water deficit profoundly impairs the yield of this crop. Nitric oxide (NO) is a molecule that plays an important role in the plant defense mechanisms. To evaluate the protection exerted by NO against Pss infection under normal or water-restricted conditions, sodium nitroprusside (SNP), a NO donor, was applied to sweet cherry plants cv. Lapins, before they were exposed to Pss infection under normal or water-restricted conditions throughout two seasons. Well-watered plants treated with exogenous NO presented a lower susceptibility to Pss. A lower susceptibility to Pss was also induced in plants by water stress and this effect was increased when water stress was accompanied by exogenous NO. The lower susceptibility to Pss induced either by exogenous NO or water stress was accompanied by a decrease in the internal bacterial population. In well-watered plants, exogenous NO increased the stomatal conductance and the net CO2 assimilation. In water-stressed plants, NO induced an increase in the leaf membranes stability and proline content, but not an increase in the CO2 assimilation or the stomatal conductance.

TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases

TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases

The effect of diversity on disease reverses from dilution to amplification in a 22-year biodiversity × N × CO2 experiment

Plant disease often increases with N, decreases with CO2, and increases as biodiversity is lost (i.e., the dilution effect). Additionally, all these factors can indirectly alter disease by changing host biomass and hence density-dependent disease transmission. Yet over long periods of time as communities undergo compositional changes, these biomass-mediated pathways might fade, intensify, or even reverse in direction. Using a field experiment that has manipulated N, CO2, and species richness for over 20 years, we compared severity of a specialist rust fungus (Puccinia andropogonis) on its grass host (Andropogon gerardii) shortly after the experiment began (1999) and twenty years later (2019). Between these two sampling periods, two decades apart, we found that disease severity consistently increased with N and decreased with CO2. However, the relationship between diversity and disease reversed from a dilution effect in 1999 (more severe disease in monocultures) to an amplification effect in 2019 (more severe disease in mixtures). The best explanation for this reversal centered on host density (i.e., aboveground biomass), which was initially highest in monoculture, but became highest in mixtures two decades later. Thus, the diversity-disease pattern reversed, but disease consistently increased with host biomass. These results highlight the consistency of N and CO2 as drivers of plant disease in the Anthropocene and emphasize the critical role of host biomass—despite potentially variable effects of diversity—for relationships between biodiversity and disease.

IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.

A circular single-stranded DNA mycovirus infects plants and confers broad-spectrum fungal resistance

Circular single-stranded DNA (ssDNA) viruses have been rarely found in fungi, and the evolutionary and ecological relationships among ssDNA viruses infecting fungi and other organisms remain unclear. In this study, a novel circular ssDNA virus, tentatively named Diaporthe sojae circular DNA virus 1 (DsCDV1), was identified in the phytopathogenic fungus Diaporthe sojae isolated from pear trees. DsCDV1 has a monopartite genome (3185 nt in size) encapsidated in isometric virions (21–26 nm in diameter). The genome comprises seven putative open reading frames encoding a discrete replicase (Rep) split by an intergenic region, a putative capsid protein (CP), several proteins of unknown function (P1–P4), and a long intergenic region. Notably, the two split parts of DsCDV1 Rep share high identities with the Reps of Geminiviridae and Genomoviridae, respectively, indicating an evolutionary linkage with both families. Phylogenetic analysis based on Rep or CP sequences placed DsCDV1 in a unique cluster, supporting the establishment of a new family, tentatively named Gegemycoviridae, intermediate to both families. DsCDV1 significantly attenuates fungal growth and nearly erases fungal virulence when transfected into the host fungus. Remarkably, DsCDV1 can systematically infect tobacco and pear seedlings, providing broad-spectrum resistance to fungal diseases. Subcellular localization analysis revealed that DsCDV1 P3 is systematically localized in the plasmodesmata, while its expression in trans-complementation experiments could restore systematic infection of a movement-deficient plant virus, suggesting that P3 is a movement protein. DsCDV1 exhibits unique molecular and biological traits not observed in other ssDNA viruses, serving as a link between fungal and plant ssDNA viruses and presenting an evolutionary connection between ssDNA viruses and fungi. These findings contribute to expanding our understanding of ssDNA virus diversity and evolution, offering potential biocontrol applications for managing crucial plant diseases.

Consumers’ Perceptions for an Outdoor Ornamental Plant: Exploring the Influence of Novel Plant Diseases Diagnostics and Sustainable Nurseries Cultivation Management

A discrete choice experiment was conducted to assess the perceptions and willingness-to-pay of Italian consumers regarding plant diagnosis and sustainable cultivation attributes in outdoor ornamental plants, specifically Abelia × grandiflora. The results revealed that most Italian consumers place great importance on the health of ornamental plants during the purchasing process, with a preference for obtaining them from nursery facilities. Additionally, they demonstrated a willingness to pay a price premium for innovative plant diagnosis and sustainable cultivation in the production of A. × grandiflora, amounting to EUR 1.10 and EUR 0.90, respectively. These findings have significant implications for (i) nursery growers, enabling them to shape their sustainable nursery management and marketing strategies, and (ii) policymakers, facilitating the enhancement of communication strategies and the implementation of awareness campaigns aimed at promoting the sale of healthy Italian ornamental species, following the current EU regulation 2020/1201.

Breeding for Resistance against Pest and Diseases in Tomatoes: A Review

Diseases and pests have a substantial effect on tomato production, greatly affecting both the quantity and quality of this crucial vegetable crop. Although fungicides and insecticides have been important in controlling plant diseases and pests, their excessive usage raises significant environmental issues. Vegetable breeders are increasingly concentrating on developing cultivars with natural tolerance to biotic stresses to promote sustainability and environmental friendliness. The change in focus is intended to cultivate tomato cultivars with inherent resistance to diseases and pests, hence decreasing the need for chemical treatments. Advancements in creating high-yielding genetically resistant tomato cultivars are a result of detailed study on the genetic basis of pest and disease resistance in tomato crops, as well as the complex interactions between the host plant and pathogens. For effective breeding programs and pre-breeding activities, scientists and breeders must have access to sources of resistance and a thorough grasp of the genetic complexities involved. This requires examining the genetic composition of both the tomato plants and the different infections that are impacting them. Breeders may generate tomato cultivars with strong resistance to common diseases and pests by using the inherent defensive mechanisms found in certain tomato types via selective crossing. Continuing to study how hosts and pathogens interact and the molecular processes involved in resistance is crucial. This information offers vital insights on how to improve and expand resistance, leading to the creation of cultivars with long-lasting and wide-ranging resistance. Currently, the emphasis on breeding is a proactive and sustainable strategy for transfer of resistances in high yielding tomato cultivars. Researchers aim to develop tomato cultivars that provide high yield and demonstrate tolerance to changing disease and pest stresses by integrating genetic knowledge with sophisticated breeding methods. This comprehensive method protects tomato crops and encourages environmental sustainability by decreasing the need on chemical inputs in agriculture.

Crop recommendation system and pest classification using weighted support vector machine on climate data

Introduction: The primary cause of the significant decline in crop productivity is farmers' poor crop selection. A number of pests, including weeds, insects, plant diseases, and the poisonous nature of the most current remedies, offer challenges to the current approach. Therefore, for the most effective and precise classification and recommendations, these factors should be considered together.Methods: Levy flight Grey Wolf Optimization (LGWO) and the WSVM (Weight-Support Vector Machine) method are recommended in this research for the intention of upgrading the efficiency of the system as well as resolving the above-mentioned issues. A CRS (Crop Recommendation System) utilizing the LGWO-WSVM algorithm is to be developed in order to increase crop productivity. This study's primary stages include crop suggestion, FS (Feature selection), and pre-processing. The KNN (K-Nearest Neighbour) technique is utilized for the pre-processing of the climatic dataset in order to accommodate incorrect values and missing variables. Results: The best fitness values are utilized to identify more pertinent weather features. These chosen qualities are then applied to the categorization phase. In order to create a system which integrates the predictions of the LGWO-WSVM model to recommend an appropriate crop depends on the kinds of the particular soil and features having greater accuracy.Conclusion: In order to get the best recommendation outcomes, it is also utilized to categorize the pest traits. The test outcomes indicate that the recommended LGWO-WSVM strategy overtakes the current methods by accuracy, precision, recall, and execution time.

PEMENUHAN GIZI DAN PENINGKATAN PENDAPATAN MASYARAKAT DENGAN BUDIDAYA SAYURAN DI LAHAN PEKARANGAN

Fulfilling people's food needs faces many obstacles, especially due to changes in environmental conditions, such as climate change, land conversion, and the increasing number of cases of pest attacks and plant diseases which cause a decrease in crop yields. The solution offered is to use yard land for cultivating plants. Apart from being able to be used for daily consumption, the harvest from the yard can also be sold as a side business for family members. The community service program aims to assist the target community in increasing their knowledge and skills in optimally utilizing yard land for cultivating vegetable crops. The method used is community empowerment with activities: counseling, training and participatory mentoring of target community groups. The results of the implementation of the community service program show an increase in community knowledge and skills in cultivating vegetable plants in their yards. Planting vegetable plants in the yard can be a source of food, medicine and environmental beauty, as well as increasing people's income.

First Report of Anthracnose Caused by Colletotrichum spaethianum on Zephyranthes candida in China.

Zephyranthes candida, an bulbous perennial plant, are planted in almost every park. In October 2023, anthracnose symptoms were observed on Z. candida leaves in Jiangxi Agricultural University (28.75° N, 115.83°E), Nanchang, Jiangxi Province, China, and the incidence of disease were up to 35% (140 of 400 plants). The lesions extended fromtheleafapextothebase, appearing as a dark brown color, and later changed to yellow and became dry. To isolate the pathogen, 20 symptomatic leaves were collected and cut into small pieces (4×4 mm, one pieces per leave), surface-sterilized with 70% ethanol for 10 s and 1% NaClO for 30 s, rinsed thrice with sterile water, placed onto potato dextrose agar (PDA) plates and incubated at 25℃ for 5 days. Fifteen isolates (15 out of 20) with similar morphological characteristics were obtained. The colonies on PDA presented effuse mycelium, initially white and later pale gray. Conidia were hyaline, curved or slightly curved, aseptate, with a truncate base and acute apex, measuring 17 to 23 × 3 to 6 μm (n = 50), and were matched to Colletotrichum species (Damm et al. 2009). To further confirm species, two representative isolates (JFRL 03-2873 and JFRL 03-2874) were selected for molecular identification. The internal transcribed spacer (ITS), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), chitin synthase (CHS), histone 3 (HIS3), actin (ACT) and β-tubulin 2 (TUB2) regions were amplified and sequenced by using primers sets ITS5/ITS4, Gpd1/Gpd2, CHS-79F/CHS354R, CYLH3F/CYLH3R, ACT-512F/ACT-783R and T1/Bt2b (Tan et al. 2022), respectively. These sequences were deposited into GenBank with accession number PP425890-PP425891 (ITS), PP437551-PP437552 (GAPDH), PP437549-PP437550 (CHS), PP480643-PP480644 (HIS3), PP437547-PP437548 (ACT) and PP437553-PP437554 (TUB2). A BLASTN search revealed high similarity of 99%-100% to ITS (GU227807, 518 nt/519 nt), GAPDH (GU228199, 525 nt/526 nt), CHS (GU228297, 251 nt/251 nt), HIS3 (GU228003, 372 nt/373 nt), ACT (GU227905, 236 nt/237 nt) and TUB2 (GU228101, 490 nt/490 nt) sequences of Colletotrichum spaethianum CBS 167.49. A maximum likelihood phylogenetic tree was constructed by combining ITS, GAPDH, CHS , HIS3, ACT and TUB2 sequences in IQtree web server (Ngugen et al. 2015). The result indicated that the two representative isolates were clustered together with Colletotrichum spaethianum in a clade with 100% bootstrap support. Based on morphologicalobservationandsequenceanalysis, the isolates were identified as C. spaethianum. To confirm pathogenicity, six surface-sterilized leaves of Z. candida were wounded and inoculated with 1 × 106 conidia/ml conidial suspension of JFRL 03-2873, and control leaves were inoculated with sterile water. They were incubated at 25 ℃ with 12 h photoperiod and 80% humidity, theexperimentwasrepeatedtwice. After five days, all leaves inoculated with JFRL 03-2873 displayed anthracnose symptom, whereas the control leaves remained unaffected. We re-isolated C. spaethianum from the symptomatic leaves and identified it based on morphological and molecular characteristics. Previous studies reported that C. spaethianum caused anthracnose on various common herbaceous plants in China (Vieira et al. 2014, Guo et al. 2013), but to our knowledge, this is the first report of C. spaethianum causing anthracnose on Z. candida in China. Anthracnose disease caused great economic loss to the cultivation of landscape plant Z. candida. Therefore, it is necessary to pay more attention to the anthracnose disease of herbaceous plants caused by C. spaethianum and develop appropriate control strategies.

InViTMixup: plant disease classification using convolutional vision transformer with Mixup augmentation

ABSTRACT Computer vision-based research is carried out to enhance the crop yield with automation solutions. In Tamil Nādu, tomato cultivation is carried out in many districts, including Coimbatore, and its contribution to the Indian economy, i.e. GDP growth, is significant. This paper proposes InViT Mixup, a novel approach toward image classification of diseased tomato leaves. The effectiveness of convolutional neural network (CNN) in obtaining spatial information and the attention mechanism of vision transformers, along with Mixup data augmentation, are combined, and the model’s generalization in predicting the diseased tomato based on leaf symptoms is evaluated. The proposed convolutional transformer model improvised the classification results of tomato disease in terms of accuracy and training speed compared to pure CNN or transformer-based models. In the proposed work, 10 tomato leaf disease classes from the PlantVillage dataset are used. Top-1 accuracy of 93.5% and Top-5 accuracy of 99.7% are achieved.