Plant Pathology Research Research Articles

Characterization of virus species associated with sweet potato virus disease in Costa Rica and riboprobe development for its rapid detection

AbstractSweet potato (Ipomoea batatas) is a crucial crop for food security and economic stability in many regions, including Costa Rica. This study aimed to assess the prevalence and genetic diversity of two major viruses associated with sweet potato virus disease (SPVD) in Costa Rica: sweet potato feathery mottle virus (SPFMV) and sweet potato chlorotic stunt virus (SPCSV). A total of 50 leaf samples displaying typical viral disease symptoms were collected from major sweet potato‐growing regions. Using multiplex reverse transcription (RT)‐PCR, SPFMV was detected in 82% of the samples and SPCSV in 52%, with a coinfection rate of 48%. Genetic analysis revealed that SPFMV isolates belonged predominantly to phylogenetic group B, while SPCSV isolates clustered with the West African (WA) strain. The low genetic diversity within these viral populations suggests a limited number of initial infection events followed by local spread. Riboprobe technology was evaluated as an alternative to RT‐PCR for virus detection. While the riboprobes for SPFMV demonstrated sensitivity comparable to RT‐PCR, the SPCSV riboprobes showed slightly lower sensitivity, particularly when using crude leaf extracts. Despite this, riboprobes offer significant advantages in terms of cost and ease of use for large‐scale screening. Our findings underscore the need for robust diagnostic and management strategies to control SPVD and highlight the importance of continuous monitoring and research to mitigate the impact of viral diseases on sweet potato production in Costa Rica. These insights contribute to the global understanding of SPVD and support collaborative efforts in plant pathology research.

Stress induced factor 2 is a dual regulator for defense and seed germination in Arabidopsis

Receptor-like kinases (RLKs) constitute a diverse superfamily of proteins pivotal for various plant physiological processes, including responses to pathogens, hormone perception, growth, and development. Their ability to recognize conserved epitopes for general elicitors and specific pathogens marked significant advancements in plant pathology research. Emerging evidence suggests that RLKs and associated components also act as modulators in hormone signaling and cellular trafficking, showcasing their multifunctional roles in growth and development. Notably, STRESS INDUCED FACTOR 2 (SIF2) stands out as a representative with distinct expression patterns in different Arabidopsis organs. Our prior work highlighted the specific induction of SIF2 expression in guard cells, emphasizing its positive contribution to stomatal immunity. Expanding on these findings, our present study delves into the diverse functions of SIF2 expression in root tissues. Utilizing comprehensive physiology, molecular biology, protein biochemistry, and genetic analyses, we reveal that SIF2 modulates abscisic acid (ABA) signaling in Arabidopsis roots. SIF2 is epistatic with key regulators in the ABA signaling pathway, thereby governing the expression of genes crucial for dormancy release and, consequently, Arabidopsis seed germination. This study sheds light on the intricate roles of SIF2 as a multi-functional RLK, underscoring its organ-specific contributions to plant immunity, hormonal regulation, and seed germination.

It's a Trap! Part I: Exploring the Applications of Rotating-Arm Impaction Samplers in Plant Pathology.

Although improved knowledge on the movement of airborne plant pathogens is likely to benefit plant health management, generating this knowledge is often far more complicated than anticipated. This complexity is driven by the dynamic nature of environmental variables, diversity among pathosystems that are targeted, and the unique needs of each research group. When using a rotating-arm impaction sampler, particle collection is dependent on the pathogen, environment, research objectives, and limitations (monetary, environmental, or labor). Consequently, no design will result in 100% collection efficiency. Fortunately, it is likely that multiple approaches can succeed despite these constraints. Choices made during design and implementation of samplers can influence the results, and recognizing this influence is crucial for researchers. This article is for beginners in the art and science of using rotating-arm impaction samplers; it provides a foundation for designing a project, from planning the experiment to processing samples. We present a relatively nontechnical discussion of the factors influencing pathogen dispersal and how placement of the rotating-arm air samplers alters propagule capture. We include a discussion of applications of rotating-arm air samplers to demonstrate their versatility and potential in plant pathology research as well as their limitations.

Unveiling the draft genome of the seed gall nematode, Anguina tritici: Insights and analysis

Anguina tritici, a plant parasitic nematode (PPN) from clade IV of the phylum Nematoda, causes earcockle and tundu diseases in wheat. It stands out from other PPNs due to its ability to parasitize wheat plant seeds and its long-term survival capability under anhydrobiosis conditions within the seeds. Therefore, the genome of A. tritici provides an opportunity to understand the genomic basis for its adaptation to parasitize the aerial parts of the plant. The Illumina MiSeq sequencing strategy yielded a total of 11,065,381,294 bases, with a read count of 40,210,848. The genome, with a size of 164 MB and 39,965 protein-coding genes, was sequenced at 60-fold coverage. Key statistics include a GC content of 39.1 %, Q20 % of 92.73, and Q30 % of 84.08. KEGG analysis identified the involvement of genes in 375 different pathways, highlighting significant pathways related to parasitism, anhydrobiosis, and stress responses. Comparative genomic analysis yielded insightful results regarding the orthologous relationships among the six analyzed species, including A. tritici, Aphelenchoides besseyi, Bursaphelenchus xylophilus, Ditylenchus destructor, Globodera pallida, and Meloidogyne incognita. Sixty-one overlaps were identified, indicating shared orthologous clusters among these species. A single-copy orthologue-based phylogenetic tree showed A. tritici and D. destructor in a monophyletic group. Expert functional annotations revealed the occurrence of several gene homologues involved in developmental processes, neuropeptide signaling, aging, anhydrobiosis, parasitism, RNA interference (RNAi), chemosensory mechanisms, and sex determination processes in A. tritici. These findings offer a comprehensive genetic framework for understanding the parasitism and survival strategies of A. tritici, with significant implications for developing novel control methods and advancing research in plant pathology and Nematology.

A Hybrid Deep Learning Architecture for Apple Foliar Disease Detection

Incorrectly diagnosing plant diseases can lead to various undesirable outcomes. This includes the potential for the misuse of unsuitable herbicides, resulting in harm to both plants and the environment. Examining plant diseases visually is a complex and challenging procedure that demands considerable time and resources. Moreover, it necessitates keen observational skills from agronomists and plant pathologists. Precise identification of plant diseases is crucial to enhance crop yields, ultimately guaranteeing the quality and quantity of production. The latest progress in deep learning (DL) models has demonstrated encouraging outcomes in the identification and classification of plant diseases. In the context of this study, we introduce a novel hybrid deep learning architecture named “CTPlantNet”. This architecture employs convolutional neural network (CNN) models and a vision transformer model to efficiently classify plant foliar diseases, contributing to the advancement of disease classification methods in the field of plant pathology research. This study utilizes two open-access datasets. The first one is the Plant Pathology 2020-FGVC-7 dataset, comprising a total of 3526 images depicting apple leaves and divided into four distinct classes: healthy, scab, rust, and multiple. The second dataset is Plant Pathology 2021-FGVC-8, containing 18,632 images classified into six categories: healthy, scab, rust, powdery mildew, frog eye spot, and complex. The proposed architecture demonstrated remarkable performance across both datasets, outperforming state-of-the-art models with an accuracy (ACC) of 98.28% for Plant Pathology 2020-FGVC-7 and 95.96% for Plant Pathology 2021-FGVC-8.

Why a strategic shift in action is needed to recognise and empower Indigenous plant pathology knowledge and research

Plant pathology researchers play a pivotal role in thought leadership and its translation to action regarding the recognition and demonstration of the value of Indigenous knowledge and science. For many scientists, navigating the space of Indigenous rights and perspectives is challenging. In pursuit of a cultural shift in research and development within the field of plant pathology, the 2019–2021 Management Committee of the Australasian Plant Pathology Society (APPS) undertook a review and modernization of the Society’s Constitution. The aim was to ensure its alignment with principles that foster inclusivity of Indigenous peoples in the development and implementation of relevant research projects impacting their communities. Additionally, a dynamic repository of guidelines and resources was compiled. These resources are designed to assist plant pathologists, while respecting and not superseding the guidance provided by local Indigenous researchers, practitioners, and advisors. The collective efforts of plant pathologists hold immense potential in championing Indigenous Peoples and their rights, steering the field toward a more inclusive and equitable future. This paper builds upon the thesis presented in the APPS Presidential Address at the Biennial APPS Conference in 2021, held virtually in lutruwita (Tasmania) on the unceded lands of the Palawa people. It underscores the potential impact when plant pathologists unite in advocating for Indigenous Peoples and their rightful place within the field.

Exogenous application of different antagonists and their secretory metabolites to manage root-knot nematodes in pea

Pea (Pisum sativum L.) is a grain legume, a member of the Leguminosae family. Root-knot nematodes cause severe losses ranging from 15 to 85%. Different species of nematodes including root-knot nematodes reduce the yield of pea significantly. To control root-knot nematodes biological control is a more environment-friendly approach. The main objective of the study is to assess the effect of different antagonistic microbes and their secretory metabolites to manage root-knot nematodes in peas. Through this research, we aim to identify potential biological control agents that can be used as eco-friendly alternatives to chemical nematicides, contributing to sustainable pest management practices in agriculture. For this purpose, firstly, a brinjal seedling was transplanted for inoculum development which was inoculated with infective 2nd stage juveniles of root-knot nematodes (Meloidogyne spp.) in Department of Plant Pathology research area, University of Agriculture Faisalabad (UAF). Then two pea varieties viz. Matar sabaz and Pea-2009 were sown in pots and inoculated with nematode larvae after four weeks of sowing. Moreover, the management of nematodes was done by using the antagonists and their secretory metabolites application. The data of different plant growth and nematode-related parameters was taken and subsequently analyzed using analysis of variance and least significant difference test (LSD). Results showed that the antagonist’s treatment subsequently controlled root-knot nematodes (RKNs). Maximum plant/shoot length (47 cm), root length (25.25 cm), shoot weight (22.25 g) pod length (8.50 cm), No. of secondary shoots (8) and minimum number of galls (2.5 cluster), was observed in plants treated with Bacillus spp. (T1) while maximum No. of fruits (5.75) was observed in plants treated with Pseudomonas spp. (T2). Similarly, the number of nodules (7.50 clusters) primary shoots (5) Root weight (4.6 g) was observed in plants treated with Enterobacter spp. (T3).

Open Access and Reproducibility in Plant Pathology Research: Guidelines and Best Practices.

The landscape of scientific publishing is experiencing a transformative shift toward open access, a paradigm that mandates the availability of research outputs such as data, code, materials, and publications. Open access provides increased reproducibility and allows for reuse of these resources. This article provides guidance for best publishing practices of scientific research, data, and associated resources, including code, in The American Phytopathological Society journals. Key areas such as diagnostic assays, experimental design, data sharing, and code deposition are explored in detail. This guidance aligns with that observed by other leading journals. We hope the information assembled in this paper will raise awareness of best practices and enable greater appraisal of the true effects of biological phenomena in plant pathology.

An optimized capsule neural networks for tomato leaf disease classification

Plant diseases have a significant impact on leaves, with each disease exhibiting specific spots characterized by unique colors and locations. Therefore, it is crucial to develop a method for detecting these diseases based on spot shape, color, and location within the leaves. While Convolutional Neural Networks (CNNs) have been widely used in deep learning applications, they suffer from limitations in capturing relative spatial and orientation relationships. This paper presents a computer vision methodology that utilizes an optimized capsule neural network (CapsNet) to detect and classify ten tomato leaf diseases using standard dataset images. To mitigate overfitting, data augmentation, and preprocessing techniques were employed during the training phase. CapsNet was chosen over CNNs due to its superior ability to capture spatial positioning within the image. The proposed CapsNet approach achieved an accuracy of 96.39% with minimal loss, relying on a 0.00001 Adam optimizer. By comparing the results with existing state-of-the-art approaches, the study demonstrates the effectiveness of CapsNet in accurately identifying and classifying tomato leaf diseases based on spot shape, color, and location. The findings highlight the potential of CapsNet as an alternative to CNNs for improving disease detection and classification in plant pathology research.

Conventional and Biopesticide Fungicides for Cucurbit Downy Mildew Control on Cucumber in Michigan

Michigan ranks first in the nation in cucumber production for processing (pickling), contributing over $45 million to the state's economy in 2019. Cucurbit downy mildew, caused by the oomycete Pseudoperonospora cubensis, is the most important disease of cucumber and an annual threat to yields. Fungicides are the most important means to control P. cubensis. Our goal was to monitor currently labelled conventional fungicides and biopesticides for efficacy over the course of an entire cropping period under high pathogen pressure. Field trials were conducted at the Michigan State University Plant Pathology Research Farm in 2021 and 2022. Fungicides were applied weekly, and disease severity was evaluated by visually assessing the percentage of foliar area showing downy mildew symptoms. At the end of the season, the relative area under the disease progress curve (rAUDPC) was calculated using the disease severity data. Based on rAUDPC results, oxathiapiprolin premixed with chlorothalonil was the most effective fungicide at controlling P. cubensis and was significantly better than all other conventional fungicides in both years tested. In both years, all conventional treatments had a significantly lower rAUDPC than the untreated control except pyraclostrobin, dimethomorph, and fluopicolide. No biopesticide fungicide reduced the rAUDPC compared with the untreated control in either year evaluated.

Evaluation of Okra (Abelmoschus esculentus L.) Pest Control Strategies and Cost-Benefit Analysis

A field study on integrated pest management of okra insect pests was conducted at the Plant Pathology Research Institute, Ayub Agriculture Research Institute, in collaboration with the Department of Entomology, University of Agriculture Faisalabad, during the 2022 crop season. Rama Krishma, a variety of okra, was sown using the Randomized Complete Block Design with four replications and employing the drilling technique and agronomical practices. Significant differences (P0.05) in insect pest populations, namely whitefly, jassid, thrips, aphids, Helicoverpa, and spotted bollworm, were observed across various treatments. The pest populations of all these insects progressively decreased with treatment applications, and post-treatment measurements were taken 48 hours after each spray. The minimum mean populations of aphids (2.01/leaf), thrips (0.15/leaf), jassids (1.86/leaf), and spotted bollworm (2.41/plant) were recorded with the application of the biosal treatment, followed by Helicoverpa (1.25/plant) and whitefly (0.13/leaf) populations, which were observed in plots treated with tobacco extract and Chrysoperla + Trichogramma, respectively. The maximum mean populations of Formicomus antiqumus (0.55), Laius malleifer (0.17), Orius bugs (0.56), Trichogramma chilonis (Ishii) (20.41), Chrysoperla carnea (0.31), ladybird beetles (0.69), ants (0.79), and spiders (0.89) were recorded in the Chrysoperla + Trichogramma treated plots, indicating the safety of this bio-pesticide for predatory populations. Analysis of yield attributing parameters revealed that biosal-treated plots exhibited the highest values for several factors, including the maximum number of fruits per plant (19.57), number of flowers (8.75), squares (18.34), plant height (42.36 cm), and number of branches per plant (3.73). Furthermore, the cost-benefit ratios for okra plants were highest for treatments involving tobacco extract and natural enemies, with ratios of 1:16.3 and 1:10.6, respectively. The application of biosal after treatment demonstrated superior efficacy as a control approach compared to alternative treatments

EVALUATION OF FUNGICIDES AGAINST TURCIUM LEAF BLIGHT OF MAIZE CAUSED BY EXSEROHILUM TURCICUM

Northern Leaf Blight of Maize (NLBM) is a serious disease of Maize crop in Pakistan. The disease causes heavy losses in maize crop every year. To avoid this loss, a research experiment was conducted to check the efficacy of four fungicides and one control against Turcicum Leaf Blight of maize. The experiment was tested against the maize variety Malka-2016. The trial was conducted at Research Area of Plant Pathology Research Institute, Faisalabad, from 2021 to 22. The result of experiment showed that DithaneM-45 (Mancozeb), Tilt 25%EC (propiconazole), Score 25% EC (Difenaconazole), and Topsin-M70%WP (Thiophenate Methyl) significantly reduced the northern leaf blight disease of Maize and increase the yield. Dithane M45(Mancozeb) controlled the disease by 86% over control ,followed by Tilt (Propiconazole) by 79%, Score (Difenaconazole) by 71 %, and the least effective fungicide was Topsin-M 70% WP (Thiophenate Methyal) which control the disease by 68%.

Developing a microscope image dataset for fungal spore classification in grapevine using deep learning

Grapevine trunk diseases (GTD) result from various fungi invading grapevine wood, leading to a decline in quality and yield. Accurate identification of fungal species is vital for effective disease management. Visual inspection through microscopy is a commonly used method, but distinguishing similar microorganisms within the same genus can be challenging. For precise identification, molecular methods are often required, despite being relatively costly and time-consuming. In this paper, we present a novel method for classifying four species of grapevine wood fungi using deep learning algorithms. We evaluate the performance of four different deep learning architectures, ResNet-50, VGG-16, MobileNet, and InceptionV3, in the classification of grapevine fungal spores from our microscope image dataset. During our tests, the proposed classification methodology achieved an accuracy of up to 97.40 %. Our approach can facilitate the development of more efficient and accurate methods for fungal species identification and has potential applications in viticulture and plant pathology research.

In vitro Evaluation of Different Chemical Fungicides for the Control of Rhizoctonia solani Kuhn

An in vitro experiment was conducted for an evaluation of different chemical fungicides against Rhizoctonia solani using poisoned food technique at National Plant Pathology Research Centre, Nepal Agricultural Research Council (NARC) Khumaltar, Lalitpur. Pathogen was isolated from infected broad leaf mustard. The experiment was conducted in Completely Randomized Design (CRD) with three replications for each treatment. Seven fungicides as treatments, namely, Saaf (carbendazim 12% + mancozeb 63%), Bavistin (carbendazim 50%), Vacomil Plus (metalaxyl 15% + copper oxychloride 35%), Nativo (tebuconazole 50% + trifloxystrobin 25%), Sectin (fenamidone 10% + mancozeb 50%), Kingstival (dimethomorph 50%) and Topcare (azoxystrobin 50%) were taken for the evaluation. Two levels of concentrations (100 ppm and 200 ppm) were used for each fungicide and concentration was calculated based on active ingredients (a.i.) of the fungicides. All fungicides were used individually to study the rate of inhibition of R. solani on PDA media. At higher concentration 200 ppm, Bavistin, Nativo and Saaf showed complete inhibition of the mycelial growth of the pathogen whereas at lower concentration 100 ppm, Bavistin was only completely effective against the pathogen. Sectin and Topcare were also highly effective in inhibiting the growth of R. solani. The efficaces of Kingstival and Vacomil Plus against the pathogen were much lesser than others. The active ingredients carbendazim, tebuconazole, mancozeb and trifloxystrobin showed the highest degree of mycelial growth inhibitions compared to others. The fungicides that found to be effective for inhibition of mycelial growth of R. solani in this study should be further tested in the field conditions in order to verify their efficacies as well as to determine their optimum application doses.

First Report of Tobacco Ringspot Virus Infecting Pawpaw Orchard (Asimina triloba (L.) Dunal) in North America.

Pawpaw (Asimina triloba (L.) Dunal, Annonaceae) is a fruit tree native to eastern North America, increasingly grown for commercial production in the United States (Callaway, 1992; Layne, 1996), Europe, and Western Asia (Brannan and Coyle, 2021; Lolletti et al., 2021). In 2012, virus-like symptoms were noticed in a 0.3 ha pawpaw orchard at Michigan State University Plant Pathology Research Station; ~30% of the trees presented symptoms which included foliar mosaic, vein yellowing, and necrosis, and were first mistaken for nutrient (magnesium/zinc) deficiency. Trees were treated for magnesium/zinc deficiency but continued to decline in fruit yield and overall vigor, and typically died within 3─4years after symptoms were first observed (Fig. S1). Preliminary testing using Agdia ImmunoStrips for cucumber mosaic virus, impatiens necrotic spot virus, tobacco mosaic virus, tomato spotted wilt virus and the genus Potyvirus were negative. However, icosahedral virus particles were observed by TEM (Fig. S2). To establish virus identity, we deep-sequenced tissue from a symptomatic pawpaw obtained from same site in summer 2021. Virus particles were purified , and virion-associated nucleic acids (VANA) were extracted using the Purelink viral RNA/DNA kit (Invitrogen) (Maclot et al., 2021). Both viral RNA and DNA were subjected to high-throughput sequencing (HTS) on the Illumina NextSeq 500 platform (GIGA, University of Liege, Belgium). A total of 574,274 trimmed reads (150 nt read length) were de novo assembled using Geneious Prime 2022.2.2 software (https://www.geneious.com) and subjected to BLASTn analysis. Two contigs of 7511 bp (average coverage: 1048) and 3924 bp (average coverage: 3012) showed 94% and 95% nt identities with tobacco ringspot virus (TRSV) RNA1 isolate YW (MT042825) and RNA2 isolate OH19 (MT561435) respectively. These two contigs (Accession no. OP589177 and OP589178) covered the complete TRSV genome for each segment. HTS found no other plant-associated viral / virus-like sequences in this symptomatic pawpaw sample. To further confirm TRSV infection, leaf extract from this sample was tested with RT-PCR using primers specific to the RdRp gene of TRSV RNA1 (Forward, 5'-TAACCTCATTGCAGTTGATCCTT-3'; Reverse, 5'-TAATTCAAGCTCAGGTCTCTTCT-3'; 739 bp amplicon) and the coat protein of TRSV RNA2 (Forward, 5'-TCATGCTTAAAGATGCAGATGTG-3'; Reverse, 5'-TATAAAGCTCCGCACTAGAAAACA-3'; 753 bp amplicon). Sanger sequence analysis showed 99.5% and 99.8% nt identity between the amplicons and the HTS contigs (RNA1 and RNA2 respectively) assembled from the pawpaw sample, and the amplicons likewise matched GenBank TRSV sequences (91.7% and 95.6% nt identities respectively with TRSV RNA1 isolate CmTX-H (MN504766) and TRSV RNA2 isolate IA-1-2017 (MT563079)). We further screened for TRSV infection in leaves from four symptomatic and three non-symptomatic pawpaw trees collected from the same site in 2022. RT-PCR revealed positive infection in all four symptomatic samples and one of the three (33%) non-symptomatic samples. Our results confirm the presence of TRSV infection in symptomatic pawpaw trees and emphasize the importance of also monitoring non-symptomatic trees. We confirmed graft transmission with 100% transmission rate observed in 200 trees grafted from a TRSV-infected pawpaw (Shenandoah cultivar), and investigation of other transmission vectors is on going. Because of TRSV's wide host range (Tolin, 2008), its broad transmission profile in other crops (via nematodes, thrips, seeds, sap inoculation, and grafting) (Hill and Whitham, 2014), and the notable decline observed in infected pawpaws from different cultivars (10-35, NC-1, Overleese, Pennsylvania-Golden, Shenandoah, Sunflower, Wabash), TRSV appears to pose a new threat to pawpaw orchards. To the best of our knowledge, this is the first report of TRSV infecting pawpaw in North America and the world.

Management of damping off disease in tomato (Solanum lycopersicum) using potential biocontrol agent Pseudomonas fluorescens

Biocontrol is a potential strategy adapted to control the fungal plant pathogens thus bio-prospecting to find novel native siderophore and enzyme producing Pseudomonas isolate for the management of tomato (Solanum lycopersicum L.) damping off disease under the prevailing conditions of Punjab state. In the present study, a total of 15 isolates of Pseudomonas fluorescens isolated from rhizospheric soils of tomato growing areas of Punjab and evaluated by dual culture plate confrontation assay, of which, two isolates (Pf10 and Pf6) showed maximum antagonistic activity against damping off pathogen (Rhizoctonia solani) with a zone of inhibition 14.30 mm and 11.53 mm respectively. These Pseudomonas isolates (Pf10 and Pf6) were also analyzed for their siderophore production and enzymatic activity. They were found to effectively produce siderophore and cell wall degrading enzymes such as chitinase and β-1,3 glucanase with higher antagonistic activity against Rhizoctonia solani. The present study was carried out at the Plant Pathology Research Farm, Punjab Agricultural University, Ludhiana, Punjab during 2017 and 2018 to confirm the bio-efficacy of these Pseudomonas isolates. Amongst the isolates, talc-based bioformulation of Pf10 isolate when applied as the seed+soil treatment had exerted strong inhibition against Rhizoctonia solani in tomato. Therefore, based on the findings, it was concluded that Pseudomonas fluorescens played a significant role as a potential biocontrol agent against damping off disease in tomato.

Use of Trained Convolutional Neural Networks for Analysis of Symptoms Caused by Botrytis fabae Sard

This study evaluated the use of convolutional neural networks (CNN) in agricultural disease recognition, specifically for Botrytis fabae symptoms. An experimental bean culture was used to capture images of healthy and affected leaflets, which were then used to perform binary classification and severity classification tests using several CNN models. The results showed that CNN models achieved high accuracy in binary classification, but performance decreased in severity classification due to the complexity of the task. InceptionResNet and ResNet101 were the models that performed best in this task. The study also utilized the Grad-CAM algorithm to identify the most significant B. fabae symptoms recognized by the CNNs. Overall, these findings can be used to develop a smart farming tool for crop production support and plant pathology research.

Alteration in Biochemical Responses in Leaves of Potato due to Common Scab Disease

The current study was designed at the research area of Plant Pathology Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan during 2017– 2020. Fresh leaves of inoculated and un-inoculated potato varieties highly susceptible (FD 76-36), moderately susceptible (FD 73-110), and resistant (Esmee)/ test lines were collected during 2017-18 and 2018-19, at 35, 65 and 95 days after sowing for biochemical analysis. Superoxide dismutase activity, Catalase activity, Per-oxidase activity, Protein and Total phenolics contents were quantified. FD 76-36 exhibited minimum SOD activity (67.733, 45.637, 24.910) %, followed by FD 73-110 (70.303,57.893, 42.513) % and Esmee (84.567, 65.167, 45.873) % after 35, 65 and 95 days of inoculation respectively as compared to control. FD 76-36 expressed minimum CAT activity (10.990, 7.473, 3.413) %, followed by Esmee (13.537, 9.630, 8.147) % and FD 73-110 (19.277, 8.147, 6.170) % after 35, 65 and 95 days of inoculation respectively as compared to control. FD 76-36 exhibited minimum POD activity (0.2133, 0.2767, 0.3600) %, followed by FD 73-110 (0.2900, 0.5567, 0.6300) % and Esmee (0.8800, 1.2733, 1.5433) % after 35, 65 and 95 days of inoculation respectively as compared to control. FD 76-36 expressed minimum protein contents (3.097, 2.873, 1.260) %, followed by FD 73-110 (7.907, 5.423, 4.267) % and Esmee (12.163, 8.633, 5.127) % after 35, 65 and 95 days of inoculation respectively as compared to control. FD 76-36 expressed minimum TPC (136.31, 115.58, 70.77) %, followed by FD 73-110 (165.85, 136.75, 86.89) % and Esmee (188.42, 158.38, 109.00) % after 35, 65 and 95 days of inoculation respectively as compared to control. The experiment was conducted with a randomized complete block design (RCBD) and three replications. The experimental data were analyzed using Fisher’s analysis of variance technique and treatment means were compared by the least significance difference (LSD) test at a 5% probability level.

Let Emerging Plant Diseases Be Predictable

A prevalent concept for colonization and evolution among plant pathogens and their hosts stems from a post-Darwinian paradigm rooted in the formalized assumption of “specialized parasitism.” Seminal studies on rust fungi of socioeconomic importance integrated such an evolutionary perspective driven by the assumption of strict coevolution among pathogens and their plant hosts. Following this fundamentally unfalsifiable assumption, theories regarding host-switching for parasites were dismissed. If colonization occurred, this process would depend upon the origin of specific and novel mutations that allow infections of previously unexploited hosts or host groups, the acquisition of a broader host range. After a specific mutation arose, parasites and hosts would be locked into an eventual evolutionary dead end (e.g., codified under Dietel’s Law). Accordingly, if the parasites are highly specialized (one parasite, one plant), then new associations are rare or otherwise unpredictable. Similar schools of thought became dominant for animal pathogens and were established during the same period (i.e., Müller’s rule, Fuhrmann’s rule, and Fahrenholz’s rule). Other studies that focused on plant pathogens took the one host–one parasite idea for granted and only tentatively included evolutionary insights in subsequent development of plant pathogen scientific frameworks. Later, emerging from neo-Darwinian views, the paradigm of strict cospeciation was conflated with the gene-for-gene rule postulated in 1956 and which has persisted among phytopathologists even to the present day. In a parallel history, conceptual development among plant pathologists and parasitologists has assumed that colonization is rare and cannot be predicted, given the dependence on the origin of the elusive special mutation. In contrast, current impacts and increasing frequency of emerging pathogens and epidemics across the globe, which influence health and food security, suggest that this historical approach fails in describing a complex biosphere in dynamic change. The Stockholm paradigm (SP) provides a powerful alternative to what may be regarded as the standard model of coevolutionary diversification. The SP creates a theoretical workbench from which emergence of new associations can be evaluated and predicted. The SP provides a new perspective in exploring the dynamics among the phytoplasmas, an emergent group of plant pathogens with substantial risk for food security. New insights are examined, pushing for resolution of the internal conflicts generated by assumptions of the standard coevolutionary model, which has dominated the scientific reasoning for more than a century of plant pathology research.

Field Response of Brassica Germplasm against Alternaria Leaf Spot Disease and its Management

Brassica is an edible oilseed crop and world’s third most important oilseed source. Alternaria leaf spot disease of Brassica, caused by Alternaria brassicae (Berk) is major limiting factor for its yield loss. In current study forty-two Brassica germplasm (B. napus = 17, B. juncea = 25) were evaluated against Alternaria leaf spot disease at research area of Plant Pathology Research Institute (PPRI), Ayub Agricultural Research Institute (AARI), Faisalabad, Pakistan. These germplasms were sown in augmented design with 10 cm plant x plant and 60 cm row x row distance in single replication. A susceptible check KJ-159 was sown after every two entries. Data were recorded on 0-9 disease severity rating scale. Out of 17 germplasm of B. napus no germplasm was found to be immune. Two germplasm exhibited highly resistant while eight germplasm showed resistance response against the disease. Six germplasm were moderately resistant and only one showed moderately susceptible response. Similarly, out of 25 germplasm of B. junceas even were found moderately resistant and ten showed moderately susceptible response. Seven were susceptible while only one germplasm was highly susceptible. Then in-vitro efficacy of different fungicides was evaluated against A. brassicae. For evaluation of fungicides Potato Dextrose Agar (PDA) amended with five different fungicides at different concentrations (10, 50, 100 and 200 ppm) was used. Experiment was conducted in completely randomized design with ten replications. Data were recorded on mycelial growth (mm) of fungus. Mancozeb (Ethylene bisdithiocarbamate) and Nativo (Tebuconazole) significantly inhibited the growth at all concentrations while Antracol (Propineb) was significantly least effective against A. brassicae. The current research provided the new resistance source of Brassica germplasm to the breeders against Alternaria leaf spot disease and its management.