Leaf Spot Research Articles

In vitro, in planta, and comparative genomic analyses of Pseudomonas syringae pv. syringae strains of pepper (Capsicum annuum var. annuum).

Pseudomonas leaf spot (PLS) caused by Pseudomonas syringae pv. syringae (Pss) causes significant losses to the pepper industry. Highly virulent Pss strains under optimal environmental conditions (cool-moderate temperatures, high moisture) can cause severe necrotic lesions on pepper leaves that consequently can decrease pepper yield if the disease persists. Hence, it is important to understand the virulence mechanisms of Pss to be able to effectively control PLS in peppers. In our study, in vitro, in planta, and whole-genome sequence analyses were conducted to better understand the virulence and pathogenicity characteristics of Pss strains in peppers. Our findings fill a knowledge gap regarding potential virulence and pathogenicity characteristics of Pss in peppers, including virulence and antimicrobial gene content. Our study helps pave a path to further identify the role of specific virulence genes in causing disease in peppers, which can have implications in developing strategies to effectively control PLS in peppers.

Assessing the efficiency of UAV for pesticide application in disease management of peanut crop.

Effective utilization of plant protection UAVs in peanut cultivation management necessitates a comprehensive grasp of how application volume rates and pesticides influence peanut leaf spot and rust control. This study aimed to compare the effects of application volume rates and pesticides on droplet deposition, disease, leaf retention rate, and peanut yield. A T20 plant protection UAV sprayer was used to apply four various pesticide doses. In comparison, a knapsack sprayer was used to spray with an application volume rate of 450 L/ha. The results showed a significant difference in droplet deposition between the plant protection UAVs and the electric knapsack sprayer. In the pesticide treatment with an application volume rate of 15.0 L/ha, there was no significant difference in the deposition on the peanut canopy of each pesticide treatment, but there was a significant difference in the deposition on the ground in the treatment with adding vegetable oil adjuvant. The treatment with added vegetable oil additives showed the worst performance. The treatment with a spray volume of 22.5 L/ha showed the best performance, with only the leaf spot control effect being 0.3 percentage points lower than that of the electric knapsack sprayer. Plant protection UAV spraying is feasible to control peanut diseases. Considering the operational effectiveness of the plant protection UAV and application volume rate, it is recommended to use a spray volume of 22.5 L/ha without adding vegetable oil adjuvants for field operations. This article is protected by copyright. All rights reserved.

Cultural, Morphological and Pathogenic Variability in the Colletotrichum capsici Isolates, Inciting Anthracnose and Fruit rot of Chilli (Capsicum annuum L.) in different Agro-Climatic Zones of Kerala, India

Aims: To study the cultural, morphological and pathogenic variability existing among the pathogen isolates of Colletotrichum capsici, inciting anthracnose and fruit rot of chilli in Kerala. Study Design: Completely randomized design (CRD). Place and Duration of Study: Department of Plant Pathology, College of Agriculture (Kerala Agricultural University), Vellayani, Thiruvananthapuram during 2018-2019. Methodology: A survey was conducted in the five agro-climatic zones (ACZs) of Kerala viz., Northern zone, Central zone, Special problem zone, High range zone and Southern zone to assess the incidence and severity of anthracnose disease. The various symptoms in the surveyed locations were also noted. Pathogen isolates were grown in PDA medium in the laboratory and colony characters (colour and mycelial growth rate of pathogen colonies) were observed. Also, the morphological characters viz., mycelial width, shape and size of conidia, acervular diameter, number and size of setae, appressorial size were recorded. Results: Maximum anthracnose incidence of 90 per cent and severity of 52.60 per cent were noticed at Regional Agricultural Research Station (RARS), Pilicode (Northern zone). Characteristic leaf spot, fruit rot and die-back symptoms were observed in the survey locations. Pathogen colonies showed different shades of white, off-white to grey turning brown or black with regular or irregular margins and concentric rings of black acervuli in the potato dextrose agar (PDA) medium. The diameter of growth of C. capsici isolates ranged from 7.20 to 8.60 cm at 7 days after incubation. All the C. capsici isolates initiated hyaline mycelium having a width of 1.73 - 2.36 µm and produced numerous sickle shaped conidia with a size range of 19.42 - 20.46 µm × 2.16 - 3.09 µm. Black coloured, circular or ellipsoidal acervuli (122.14 - 189.08 µm dia.) had 20 – 46 setae of length 74.13 to 107.30 µm. Also, brown or black appressoria of size 8.64 - 12.64 µm × 5.54 - 7.84 µm were formed in slide culture. Cc3 from College of Agriculture, Vellanikkara was obtained as the most virulent isolate producing a lesion size of 1.13 cm and PDI of 45.33 in the artificially inoculated chilli fruits (var. Vellayani Athulya) at 5 days after inoculation. Conclusion: All the nine C. capsici isolates exhibited variability in their cultural, morphological and pathogenic characteristics. Variability in phytopathogenic fungi helps in identifying novel and sustainable control methods to tackle the diseases incited by them. Understanding pathogen variability provides new insights for developing effective disease management methods. This will help in promoting sustainable agriculture and preventing severe crop losses.

In-vitro Efficacy of Different Chemical Fungicides and Plant Extracts Against Alternaria alternata Causing Alternaria Leaf Spot Disease in Brinjal

Five different chemical fungicides and three plant extracts were evaluated against Alternaria alternate causing Alternaria leaf spot disease in brinjal. The experiment was carried out in the laboratory of plant pathology at Chaudhary Charan Singh University Meerut, during kharif season 2021-22. During survey the maximum disease incidence was recorded (37.8%) Rajpura in Meerut and minimum (10.9%) incidence was recorded in Lakhaoti, survey and metrological data presented in the (Tables 2 & 3). The incidence of the disease varied from 10.9 to 37.8 percent due to difference in environmental condition. The concentration of all fungicides and Plant-extracts was kept at 500, 1000 and 2000 ppm.  Mycelial growth was measured to continue zero to ten days. Mainly four chemical fungicides (Thaiophinate Methyl 70%WP, Propineb 70% WP, Carbendazim 50%WP and Chlorothalonil 75% WP) and Neem extract significantly inhibited the mycelial growth of the pathogen (Alternaria alternata). Among all those, four fungicides and Neem extract giving the better results. Maximum 100% mycelial growth inhibition was recorded in Thaiophinate Methyl 70%WP, 94.45% mycelial growth inhibition was recorded in Propineb 70% WP, 86.09% mycelial growth inhibition was recorded in Carbendazim 50%WP and 84.80 growth inhibition was recorded in Chlorothalonil 75% WP and in plant extract 18.53% inhibition was observed in Neem and 14.33% inhibition was observed in garlic. However, Azoxystrobin 23% SC and Onion also had some effect, which is mentioned in the result of the paper.

Maize leaf disease recognition using PRF-SVM integration: a breakthrough technique

The difficulty of collecting maize leaf lesion characteristics in an environment that undergoes frequent changes, suffers varying illumination from lighting sources, and is influenced by a variety of other factors makes detecting diseases in maize leaves difficult. It is critical to monitor and identify plant leaf diseases during the initial growing period to take suitable preventative measures. In this work, we propose an automated maize leaf disease recognition system constructed using the PRF-SVM model. The PRFSVM model was constructed by combining three powerful components: PSPNet, ResNet50, and Fuzzy Support Vector Machine (Fuzzy SVM). The combination of PSPNet and ResNet50 not only assures that the model can capture delicate visual features but also allows for end-to-end training for smooth integration. Fuzzy SVM is included as a final classification layer to accommodate the inherent fuzziness and uncertainty in real-world image data. Five different maize crop diseases (common rust, southern rust, grey leaf spot, maydis leaf blight, and turcicum leaf blight along with healthy leaves) are selected from the Plant Village dataset for the algorithm’s evaluation. The average accuracy achieved using the proposed method is approximately 96.67%. The PRFSVM model achieves an average accuracy rating of 96.67% and a mAP value of 0.81, demonstrating the efficacy of our approach for detecting and classifying various forms of maize leaf diseases.

First Report of Pseudopestalotiopsis ixorae Causing Leaf Spot of Photinia × fraseri in China.

Photinia × fraseri is a well-known ornamental shrub in southern China. In December 2021, we observed leaf spots that were circular to irregular, gray with dark red margins and violet brown with brownish violet edges on the leaves of Photinia × fraseri shrubs in the scenic area of Shenlongtan (28°46'10″N, 115°42'93″E), Jiangxi Province, China. Almost 15% of the leaves in the 1300 m2 Photinia × fraseri planting area were symptomatic. Thirty symptomatic leaves were randomly collected from different plants, and sectioned into 5-mm2 pieces, which were surface-sterilized using 1% NaOCl for 30 s. After rinsing thrice in sterile distilled water and drying, the pieces were transferred onto potato dextrose agar (PDA) and incubated at 28 ℃ for 5-7 days. A total of sixteen morphologically similar isolates were obtained. After incubation on PDA for 20 days, the fungi had irregular edges, were white to pale brown, and had spare aerial mycelium on the surface with irregularly distributed black, gregarious conidiomata. Conidia were fusoid, subcylindrical, straight to slightly curved, 4-septated, slightly constricted at the septa, and 23 to 36 × 6 to 10 μm (mean: 27.6 × 7.7 μm). The morphological characteristics were consistent with the features of Pseudopestalotiopsis species (Maharachchikumbura et al. 2014). The genomic DNA of two representative isolates (JFRL032 and JFRL033) was extracted for further identification. The internal transcribed spacer (ITS) region, translation elongation factor 1-ɑ (tef1-ɑ) and β-tubulin (tub2) genes were amplified and sequenced using primers ITS5/ITS4, EF1-526F/EF1-1567R, and Bt2A/Bt2B, respectively (Maharachchikumbura et al. 2012). The sequences of the two representative isolates were 100% identical to each other. These nucleotide sequences were deposited in GenBank with accession numbers, ON342794 and ON342795 (ITS); ON375851 and ON375852 (tef1-ɑ); ON375853 and ON375854 (tub2). BLASTn searches of the obtained sequences revealed 99%-100% to ITS (MG816316, 478/478 nucleotides), tef1-ɑ (MG816336, 924/926 nucleotides), tub2 (MG816326, 441/442 nucleotides) sequences of the ex-type strain of Pseudopestalotiopsis ixorae (NTUCC17-001.1). Phylogenetic analysis was conducted using the concatenation of multiple sequences (ITS, tef1-ɑ and tub2) with the Maximum likelihood statistics in PhyloSuite v1.2.2 (Zhang et al.2020). The phylogenetic tree showed the two isolates clustered with P. ixorae in a clade with 100% bootstrap support. The isolates were identified as P. ixorae based on morphological and molecular data. To confirm pathogenicity, eight healthy leaves of 3-year-old Photinia × fraseri were surface sterilized, scratched with a pair of sterilized tweezers, and ten µl of conidial suspension (106 conidia/ml) was sprayed on the injured leaves and the control was sprayed with sterile distilled water. Then, All plants were potted in a climate chamber at 25℃ and 85% relative humidity. After 3 days, leaf spot symptoms similar to those described above were observed on inoculated leaves, while the non-inoculated leaves remained symptomless. The pathogen was reisolated from the inoculated leaves to fulfill Koch's postulates and confirmed as P. ixorae by morphological and molecular analysis. It has been reported that P. ixorae can infect the Ixora plant (Tsai et al., 2018). To the best of our knowledge, this is the first report of P. ixorae causing leaf spot on Photinia × fraseri in China. The study provides valuable information for identifying and controlling the leaf spot on Photinia × fraseri.

Development and validation of a standard area diagram set to assess corn grey leaf spot severity and foliar fungicide control efficacy

AbstractGrey leaf spot (GLS), caused by Cercospora spp., has become a very important foliar disease for second‐crop corn season, mainly in South America. Therefore, this study aimed to develop and validate a standard area diagram set (SADs) to estimate the severity of GLS and to apply the SADs established in this study to evaluate the efficacy of fungicides for GLS control in field trials. The SADs with nine levels of severity (0.5; 2; 5; 10; 20; 30; 40; 50 and 60%) improved accuracy, precision and reliability. To evaluate the control of GLS in corn, two experiments spraying chemical fungicides were conducted, one in Rio Verde (GO) (experiment A) and another in Chapadão do Sul (MS) (experiment B). Both experiments were conducted in randomized block design, with 10 treatments and four replicates. For the severity assessment, the SADs elaborated in this study was used. From this severity data over time, disease progress curves, area under the disease progress curve (AUDPC), and yield were obtained. Based on the AUDPC and yield values, all treatments differed from the control. The fungicide fluxapyroxad + pyraclostrobin + mefentrifluconazole had the highest value, giving 72.8% control efficacy and the highest yield maintenance of 43.5%. The other treatments had an intermediate control efficacy and yield. The SADs proposed here is a useful tool for improving visual assessments of GLS severity on corn leaves and fungicides can be used for integrated disease management.

Endophytic Fungi Residing within Cornus florida L. in Mid-Tennessee: Phylogenetic Diversity, Enzymatic Properties, and Potential Role in Plant Health

Endophytic fungi that reside internally in healthy, asymptomatic plants often benefit their hosts by promoting plant growth and/or providing plant protection against abiotic and biotic stresses. However, only a small fraction of the estimated 1.5 million fungal endophytes have been identified. In this study, a total of 369 isolates of fungal endophytes in 59 distinct taxa were isolated from stem samples of Cornus florida (flowering dogwood). All isolates belonged to species of phyla Ascomycota and Basidiomycota distributed across five orders and 11 genera. Isolates belonging to the same family clustered together in a phylogenetic tree generated from a cluster analysis using MEGA 7 software. Diversity indices of the fungi revealed a rich and diverse community that included several species associated with leaf spots, blight, cankers, and/or dieback diseases. Pathogenicity tests confirmed 16 fungal endophytes as C. florida pathogens, including some well-known destructive pathogens Botryosphaera dothidea, Colletotrichum acutatum, and C. gleosporoides. Isolates of the fungal endophytes possess the capacity to produce extracellular hydrolytic enzymes (cellulase, amylase, pectinase, laccase, chitinase, and protease) that are known to function in tissue penetration, plant colonization, nutrient acquisition, and disease suppression in both plant pathogens and endophytes These results support the interchangeable pathogenic–endophytic roles for some taxa.

Comparing Regression and Classification Models to Estimate Leaf Spot Disease in Peanut (Arachis hypogaea L.) for Implementation in Breeding Selection

Late leaf spot (LLS) is an important disease of peanut, causing global yield losses. Developing resistant varieties through breeding is crucial for yield stability, especially for smallholder farmers. However, traditional phenotyping methods used for resistance selection are laborious and subjective. Remote sensing offers an accurate, objective, and efficient alternative for phenotyping for resistance. The objectives of this study were to compare between regression and classification for breeding, and to identify the best models and indices to be used for selection. We evaluated 223 genotypes in three environments: Serere in 2020, and Nakabango and Nyankpala in 2021. Phenotypic data were collected using visual scores and two handheld sensors: a red–green–blue (RGB) camera and GreenSeeker. RGB indices derived from the images, along with the normalized difference vegetation index (NDVI), were used to model LLS resistance using statistical and machine learning methods. Both regression and classification methods were also evaluated for selection. Random Forest (RF), the artificial neural network (ANN), and k-nearest neighbors (KNNs) were the top-performing algorithms for both regression and classification. The ANN (R2: 0.81, RMSE: 22%) was the best regression algorithm, while the RF was the best classification algorithm for both binary (90%) and multiclass (78% and 73% accuracy) classification. The classification accuracy of the models decreased with the increase in classification classes. NDVI, crop senescence index (CSI), hue, and greenness index were strongly associated with LLS and useful for selection. Our study demonstrates that the integration of remote sensing and machine learning can enhance selection for LLS-resistant genotypes, aiding plant breeders in managing large populations effectively.

The MdVQ37-MdWRKY100 complex regulates salicylic acid content and MdRPM1 expression to modulate resistance to Glomerella leaf spot in apples.

Glomerella leaf spot (GLS), caused by the fungus Colletotrichum fructicola, is considered one of the most destructive diseases affecting apples. The VQ-WRKY complex plays a crucial role in the response of plants to biotic stresses. However, our understanding of the defensive role of the VQ-WRKY complex on woody plants, particularly apples, under biotic stress, remains limited. In this study, we elucidated the molecular mechanisms underlying the defensive role of the apple MdVQ37-MdWRKY100 module in response to GLS infection. The overexpression of MdWRKY100 enhanced resistance to C. fructicola, whereas MdWRKY100 RNA interference in apple plants reduced resistance to C. fructicola by affecting salicylic acid (SA) content and the expression level of the CC-NBS-LRR resistance gene MdRPM1. DAP-seq, Y1H, EMSA, and RT-qPCR assays indicated that MdWRKY100 inhibited the expression of MdWRKY17, a positive regulatory factor gene of SA degradation, upregulated the expression of MdPAL1, a key enzyme gene of SA biosynthesis, and promoted MdRPM1 expression by directly binding to their promotors. Transient overexpression and silencing experiments showed that MdPAL1 and MdRPM1 positively regulated GLS resistance in apples. Furthermore, the overexpression of MdVQ37 increased the susceptibility to C. fructicola by reducing the SA content and expression level of MdRPM1. Additionally, MdVQ37 interacted with MdWRKY100, which repressed the transcriptional activity of MdWRKY100. In summary, these results revealed the molecular mechanism through which the apple MdVQ37-MdWRKY100 module responds to GLS infection by regulating SA content and MdRPM1 expression, providing novel insights into the involvement of the VQ-WRKY complex in plant pathogen defence responses.

First Report of Phyllosticta capitalensis Causing Leaf spot in Hymenocallis littoralis in China.

Hymenocallis littoralis (Jacq.) Salisb. is a common ornamental plant in China. In November 2021, leaf spots were observed on H. littoralis in a public garden in Zhanjiang, Guangdong Province, China (21°17'25″N, 110°18'12″E). Disease incidence was around 60% (n = 100 investigated plants from about 1 ha). Leaf symptoms were round spots with collapse centers, surrounded by yellow halos. Ten symptomatic leaves from 10 plants were sampled. The margins of the samples were cut into 2 mm × 2 mm pieces. The surfaces were disinfected with 75% ethanol for 30 s and 2% sodium hypochlorite for 60 s. Thereafter, the samples were rinsed thrice in sterile water, placed on PDA, and incubated at 28 °C in dark. Pure cultures were obtained by transferring hyphal tips to new PDA plates. Twenty pure cultures were obtained. Single-spore isolation method (Liu et al. 2021) was used to recover the cultures of three isolates (HPC-1, HPC-2, and HPC-3). Colonies of the isolates were dark green with a granular surface, and irregular white (later turning black) edge. Pycnidia were black, globose and 96 -140 μm in diameter. Conidia were single-celled, oval, 7.5 to 13.5 × 4.0 to 7.5 µm (n= 40), with a single apical appendage. Morphological characteristics of the isolates were consistent with the description ofPhyllostictacapitalensis(Wikee et al. 2013). Molecular identification was performed using PCR method with MightyAmp DNA Polymerase (Takara-Bio, Dalian, China) (Lu et al. 2012). The internal transcribed spacer (ITS) region, translation elongation factor (TEF1), actin (ACT), and glyceradehyde-3-phosphate dehydrogenase (GAPDH) were amplified using primers ITS1/ITS4, EF1-728F/EF1-986R (Druzhinina et al. 2005), ACT-512F/ACT-783R, and Gpd1-LM/Gpd2-LM (Wikee et al. 2013), respectively. Sequences were deposited in GenBank with accession numbers OM654570 - OM654572 forITS, OM831376 - OM831378 fortef1-α, OM831346 - OM831348 forACT, and OM831364 - OM831366 for GAPDH. BLASTn analysis showed that these sequences were 99 to 100% similarity with those of P.capitalensis(ITS, FJ538339; TEF1, FJ538397; ACT, FJ538455; and GAPDH, JF343723). Besides, a phylogenetic tree was generated on the basis of the concatenated data from the sequences of ITS, TEF1, ACT, and GAPDH that nested within the clade containing P.capitalensis (CBS 117118, CPC20510,CPC20267, and CPC18848). From the combination of the morphological and molecular characteristics, the isolates were determined to beP.capitalensis. Pathogenicity testing was performed in a greenhouse with 80% relative humidity at 25 to 30°C. Ten healthy plants of H. littoralis (2 month old with 4 leaves) were grown in pots with one plant in each pot. Three leaves on one plant per isolate were inoculated with three mycelial plugs obtained from 7-day cultures, totaling five plants. Five plants treated with PDA plugs served as the controls. Wet cotton balls were fixed on the leaves with transparent tape for five days to keep it from drying out. The test was conducted three times. After 15 days, similar symptoms were observed in the inoculated leaves as in the garden, whereas control leaves remained asymptomatic and P.capitalensiswas successfully re-isolated from the inoculated leaves. Previously, P.capitalensishas been reported to cause leaf spot disease of various host plants around the world (Wikee et al. 2013). However, to our knowledge, this is the first report of leaf spot caused by P.capitalensison H. littoralis in China. This study provides an important reference for the control of the disease.

First report of Colletotrichum incanum causing leaf spots on common bean in Europe (Slovenia).

A Phaseolus vulgaris L. leaf showing necrotic spots was collected in an experimental bean field in central Slovenia in August 2021. The field contained diverse common bean lines sourced from genebank collections, with each line represented by 10 plants. While symptomatic leaves were seen across various lines, the reported species derived exclusively from a Huasca Huallaga Colorado plant (single-seed descent, USDA accession PI153714, doi: 10.18730/H7P9N), a Peruvian landrace. After incubating the leaf for 2 d at ambient temperature in a moist chamber, setose acervuli developed producing curved, distally tapering and proximately truncated conidia. Single-spore cultures developed equally-shaped conidia measuring 14.5-21.5 (avg. 18.5) × 3-4 (avg. 3.5) μm (n=60) on corn meal agar when mounted in lactic acid. Obtained morphological characters and sequences of the partial actin (GenBank accession, OR208162), beta-tubulin (OR208164), and histone 3 (OR208165) gene identified the isolate as Colletotrichum incanum H.-C. Yang, J.S. Haudenshield & G.L. Hartman. Sequences were identical to those from CBS 133485 (= NRRL 62592, IL6A), ex-type strain of C. incanum (KC110823, KC110814, and KC110796). Partial sequences of the chitin synthase (CHS) gene (OR208163), not available for the ex-type strain, was identical to sequences of other C. incanum strains reported from China (KP145539, ON189040, and OQ613679-OQ613686) or differed in two nucleotide positions (OL471268 and OL471269). The strain from Slovenia was deposited in the CBS biobanks of the Westerdijk Fungal Biodiversity Institute (Utrecht, The Netherlands) as CBS 150848. Pathogenicity of the strain was tested by spraying ca. 3×105 conidia as a watery spore suspension onto each leaf of 6 greenhouse-grown and 3 wk-old common bean plantlets (cv. KIS Amand). Nonsterile commercial substrate (Potgrond H, AGRO-FertiCrop) was used and natural light conditions at ambient temperatures (18-23°C) applied. Sterile water was sprayed on 6, equally grown negative control plants. Treated plants showed small brownish spots after 3 wks similar to those described by Yang et al. (2014) on soybean. Setose acervuli formed within 5 days after detached leaves were incubated in moist chambers. No acervuli formed on negative control plants. Conidia re-isolated from these acervuli and obtained cultures were morphologically identical to originally obtained conidia and cultures and those used for performing the pathogenicity test. Anthracnose is an important disease of common bean attributed to various races of C. lindemuthianum (Sacc. & Magnus) Briosi & Cavara (Nunes et al. 2021). Reporting an additional agent potentially able to cause diseases in common bean and so far not known to occur in Europe is of high relevance as the various genetic bean lines used in Europe may show alternative susceptibility levels to it. However, symptoms caused by C. incanum seem to be less severe as those caused by C. lindemuthianum and the species belongs to the C. spaethianum species complex, whose members have so far not been considered as pathogens of economic importance (Talhinhas & Baroncelli 2021). Yang et al. (2014) based C. incanum on isolates from soybean petioles (USA) and associated it with common bean by re-identifying strain ATCC 64682 obtained by Tu (1990) in Canada. Database queries revealed that it was encountered also on sugar beet (USA; Hanson et al. 2023) and on various crop hosts in China (e.g., chili; Diao et al. 2017), but not in Europe. The work was funded by the Ministry of Agriculture, Forestry and Food and conducted as part of research programs P4-0072 and P4-0431, financed by the Slovenian Research and Innovation Agency ARIS, and the Horizon 2020 project INCREASE funded by the European Union.

First report of leaf blight caused by Nigrospora hainanensis on Euonymus japonicus in China.

Euonymus japonicus Thunb., belonging to the family Celastreace and native to East Asia, is a widely cultivated evergreen ornamental woody plant with important ecological and economic values. In May 2023, serious leaf blight of E. japonicus occurred in the campus green space at Guiyang University, Guizhou Province, China (26°55'85"N, 106°78'04"E). Early symptom appeared as small, circular light brown spots on the edges or tips of the leaves. Then, the spot developed visible necrosis, initially light brown to dark brown halos with clear margins. Subsequently, severely infected leaves appear totally wilt, and significantly decrease their ornamental values. In a 0.07-ha field, the disease incidence reached to 40-55%. To identify the pathogen, ten typical symptomatic E. japonicus leaves were collected. They were initially immersed in 75% ethanol for 3 min, and by sodium hypochlorite (4% NaClO) solution for 45 s, and ultimately rinsed with sterile distilled water (dH2O) five times for not less than 1 min each time, then, placed the leaves on potato dextrose agar (PDA) medium and cultured for 5 days at 25°C in constant temperature incubator. Cultures were purified to yield eight isolates. Early colonies are white and regularly rounded, gradually turning dark brown to black with fluffy mycelium. Conidia were single celled, smooth, black, spherical or ellipsoidal. The conidia size of the representative strain, GY-2 and GY-3, was averagely 12.3-17.3 µm × 10.8-17 µm (n = 50). The conidiogenous cells were monoblastic, hyaline, globose or ampulliform. Morphology-based identification revealed the strain as Nigrospora spp. (Wang et al., 2017). For further confirmation, PCR of GY-2 and GY-3 DNA was performed with the primers ITS1/ITS4 (White et al., 1990), Bt2a-F/Bt2b-R (Glass and Don-aldson 1995), and TEF1-728F/TEF1-986R (Carbone and Kohn 1999). Sequences of the ITS region, TUB and TEF1 genes from the strain GY-2 and GY-3 were deposited in GenBank. (GY-2: OR999377, PP112221 and PP150467; GY-3: PP406871, PP421045 and PP421046, respectively). BLAST analysis showed GY-2 100%, 100%, and 98.36%; GY-3 99.43%, 98.21% and 100% (ITS region, TEF1, and TUB) identity to N. hainanensis sequences (accession numbers. NR_153480.1, KY019415.1, and KY019464.1; KX986094.1, OP611475.1, and KY019597.1). Additionally, tandem sequences of ITS, TUB and TEF1 constructed by MEGA 7.0 confimed the homology through the phylogenetic tree. Pathogenicity tests were conducted on healthy plants grown, each 5 mm diameter of active growing mycelium plug of isolate GY-2 was attached to 15 leaves from five healthy 2-year-old E. japonicu plants. The same number of leaves in the control group were treated with non-inoculated plugs only. All the plants were incubated at 25°C and 75% relative humidity with a 16-h/8-h photoperiod. After 10 days, no symptoms appeared on the leaves of the control group. In contrast, symptomatic blight appeared on all leaves inoculated with GY-2. Pathogenicity tests were performed five times. Pure strains were re-isolated from diseased leaves and, confirmed to be N. hainanensis based on the above methods. Recently, Nigrospora oryzae was reported as causal agent of leaf spots on Euonymus japonicus in China (Xu et al., 2023). To our knowledge, this study is the first report of N. hainanensis causing leaf blight on E. japonicu. Identification of the etiological agent may provide assistance for sustainable management in the future.

Linkage-Mapping and Genome-wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using a Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping (NAM) population has been genotyped with the peanut 58 K SNP array and phenotyped for LLS severity in the field for three years. Joint linkage-based QTL mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained (PVE) up to 47.7%. A genome-wide association study (GWAS) identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 Kb to 1,520 Kb (184 Kb) on chromosome B02 and from 1,026.9 Kb to 1,793.2 Kb (767 Kb) on chromosome B03, designated as peanut late leaf spot resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 NBS-LRR disease resistant genes. An NBS-LRR disease resistance gene Arahy.VKVT6A was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat (PPR), acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as NAM for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Corn Leaf Spot Disease Recognition Based on Improved YOLOv8

Leaf spot disease is an extremely common disease in the growth process of maize in Northern China and its degree of harm is quite significant. Therefore, the rapid and accurate identification of maize leaf spot disease is crucial for reducing economic losses in maize. In complex field environments, traditional identification methods are susceptible to subjective interference and cannot quickly and accurately identify leaf spot disease through color or shape features. We present an advanced disease identification method utilizing YOLOv8. This method utilizes actual field images of diseased corn leaves to construct a dataset and accurately labels the diseased leaves in these images, thereby achieving rapid and accurate identification of target diseases in complex field environments. We have improved the model based on YOLOv8 by adding Slim-neck modules and GAM attention modules and introducing them to enhance the model’s ability to identify maize leaf spot disease. The enhanced YOLOv8 model achieved a precision (P) of 95.18%, a recall (R) of 89.11%, an average recognition accuracy (mAP50) of 94.65%, and an mAP50-95 of 71.62%, respectively. Compared to the original YOLOv8 model, the enhanced model showcased enhancements of 3.79%, 4.65%, 3.56%, and 7.3% in precision (P), recall (R), average recognition accuracy (mAP50), and mAP50-95, respectively. The model can effectively identify leaf spot disease and accurately calibrate its location. Under the same experimental conditions, we compared the improved model with the YOLOv3, YOLOv5, YOLOv6, Faster R-CNN, and SSD models. The results show that the improved model not only enhances performance, but also reduces parameter complexity and simplifies the network structure. The results indicated that the improved model enhanced performance, while reducing experimental time. Hence, the enhanced method proposed in this study, based on YOLOv8, exhibits the capability to identify maize leaf spot disease in intricate field environments, offering robust technical support for agricultural production.

Phenotypic Variability in Resistance to Anthracnose, White, Brown, and Blight Leaf Spot in Cassava Germplasm

Despite fungal diseases affecting the aerial parts of cassava (Manihot esculenta Crantz) and causing significant yield losses, there is a lack of comprehensive studies assessing resistance in the species’ germplasm. This study aimed to evaluate the phenotypic diversity for resistance to anthracnose disease (CAD), blight leaf spot (BliLS), brown leaf spot (BLS), and white leaf spot (WLS) in cassava germplasm and to identify genotypes suitable for breeding purposes. A total of 837 genotypes were evaluated under field conditions across two production cycles (2021 and 2022). Artificial inoculations were carried out in the field, and data on yield and disease severity were collected using a standardized rating scale. The top 25 cassava genotypes were selected based on a selection index for disease resistance and agronomic traits. High environmental variability resulted in low heritabilities (h2) for CAD, WLS, and BLS (h2 = 0.42, 0.34, 0.29, respectively) and moderate heritability for BliLS (h2 = 0.51). While the range of data for disease resistance was narrow, it was considerably wider for yield traits. Cluster analysis revealed that increased yield traits and disease severity were associated with higher scores of the first and second discriminant functions, respectively. Thus, most clusters comprised genotypes with hybrid characteristics for both traits. Overall, there was a strong correlation among aerial diseases, particularly between BLS and BliLS (r = 0.96), while the correlation between CAD and other diseases ranged from r = 0.53 to 0.58. Yield traits showed no significant correlations with disease resistance. Although the mean selection differential for disease resistance was modest (between −2.31% and −3.61%), selection based on yield traits showed promising results, particularly for fresh root yield (82%), dry root yield (39%), shoot yield (49%), and plant vigor (26%). This study contributes to enhancing genetic gains for resistance to major aerial part diseases and improving yield traits in cassava breeding programs.

Characterization and pathogenicity of Alternaria species associated with leaf spot on Plantago lanceolata in Sichuan Province, China

AbstractPlantago lanceolata has been increasingly cultivated in recent years as a forage crop due to its high feeding quality, good adaptability and medicinal benefits. Between 2015 and 2023, Alternaria leaf spot (ALS), appearing as reddish‐brown necrotic spots with a greyish white to pale brown centre, was commonly observed in two forage germplasm nurseries of P. lanceolata of Sichuan Province, China. Initially, 139 Alternaria strains were isolated from leaf lesions, and then identified using the identity of rDNA internal transcribed spacer (ITS) sequences in the NCBI database and the similarity of morphological characteristics. By pure culture technique, six representative isolates were finally obtained for the present study. Based on both multilocus phylogeny (SSU, LSU, ITS, gapdh, rpb2, tef1, endoPG, OPA10‐2, alt a 1, KOG1058 and KOG1077) and morphology, four Alternaria species were identified: three new records of A. alternata, A. arborescens species complex and A. gossypina on this host in China, belonging to section Alternaria, and a new species of section Porri, namely, A. lanceolatae sp. nov. Pathogenicity tests by inoculation on both detached leaves and whole plants revealed that A. lanceolatae was the most important causal agent of ALS, while the other three species were nonpathogenic to P. lanceolata. This study characterized a novel pathogenic Alternaria species of section Porri from P. lanceolata in China and could contribute as useful research for possible ALS management.

An Improved CNN model for Identifying Tomato Leaf Diseases

A major loss in gross domestic product, quantity and quality of products produced, as well as tomato production, is caused by diseases in tomato leaves due to  which farmers have a difficult time in controlling and monitoring the health of tomato leaves, one of which is leaf disease. In our  project, we developed an Enhanced CNN by using data augmentation techniques to identify the seven classes(blight ,leaf curl, leaf miner ,Alteneria, leaf spot,  cutwork infected) of  tomato leaf diseases. Using 27807 trainable parameters, the enhanced CNN obtains the maximum training accuracy of ninety nine point nine eight percent(99.98%) and validating accuracy of ninety eight point four percent(98.4%) .With fewer parameters, The Enhanced CNN can more accurately determine the type of illness of tomato leaf. Our Enhanced CNN model also determine the type of illness of tomato leaf when tested with the images of diseased tomato leaf collected from the internet sources.Using 152850 trainable parameters the enhanced CNN obtain the maximum training accuracy of 99.68% and validation accuracy of 89%.

Evaluation of Biocontrol-based Formulations against Late Leaf Spot and Rust in Groundnut

This study investigated the efficacy of various biocontrol-based formulations against late leaf spot (LLS) (Phaeoisariopsis personata) and rust (Puccinia arachidis) in groundnut. Pot culture and field experiments were conducted during the Kharif season (June-September) of 2022. Disease incidence of both late leaf spot and rust was significantly lower in groundnut plants treated with a combination of biocontrol-based formulations compared to control. The most effective eco-friendly treatment included a combination of Trichoderma asperellum, Pseudomonas fluorescens, fortified lignite fly ash and Annamalai mixture. This combination significantly reduced lesion frequency and Percent Disease Index (PDI) for both diseases at 50, 70 and 90 DAS, compared to other treatments. The combination of biocontrol-based formulations also significantly increased the pod yield. Furthermore, the same treatment increased the induction of defense enzymes peroxidase (2.22 fold), polyphenol oxidase (1.28 fold) and phenylalanine ammonia-lyase (6.25 fold). While Carbendazim effectively reduced disease incidence, it was surpassed by the biocontrol-based module in terms of both disease control and yield. These findings suggest that biocontrol-based formulations can be a sustainable approach for managing LLS and rust diseases in groundnut cultivation.

Efficacy of Using Chemical Inducers and Biological Agents to Control Strawberry Leaf Spot Disease on Chemical Components and Enzyme Activity

Strawberry plants are subjected to many pathogens. Fungal diseases of strawberries are important worldwide and occur in all parts of the plant, including leaves, crowns, and fruits. The results of the bio-agent experiment indicated that Trichoderma harzianum was the most effective in reducing the growth of Alternaria alternata and Botrytis cinerea in vitro, the main causes of leaf spots in strawberry plants. The inhibition zone was observed and mycelium of T. harzianum invaded the colony of the tested pathogens. The importance of the biochemical study of defense reaction in the physiology of disease resistance was accepted. The activity of total, free, and conjugated phenols as well as peroxidase, polyphenol oxidase, and catalase enzyme activities were determined in resistant and susceptible strawberry cultivars. All the total, free, and conjugated phenols increased in resistant cultivars (Fortuna and Winter Star) and decreased in susceptible cultivar (Festival). Oxidative enzymes, like the increased activity of enzymes that appear mince of new polypeptide protein, have become models in the study of plant disease resistance. The higher content of peroxidase, polyphenol oxidase, and catalase enzymes in resistant cultivars, were noticed compared with those in susceptible ones. It was found also that, the chemical inducers increased total phenols in resistant and susceptible cultivars i.e., potassium di-phosphate, ferrous sulphate, and oxalic acid. Inducer resistance also caused an increase of free phenols than the control. However, conjugated phenols accumulated faster after using chemical inducers in the leaves of the resistant cultivars, than the susceptible ones.