Brown Spot Disease Research Articles

Alternaria alternata Causing Brown Spot Disease on Walnut in Xinjiang, China.

Walnut is one of the Xinjiang's characteristic dried fruits and the main source of income for farmers in walnut growing areas. In September 2019, Juglans regia leaves with brown spots were observed in a 10 hm2 orchard in Hotan area, the diseased leaf rate reached more than 25%. The leaf lesions were suborbicular to irregular, black-brown, 3 to 8 mm in diameter, with distinct dark borders. Colonies were isolated from 10 diseased leaves collected from two trees in the orchard. Leaf sections (4 × 4 mm) from diseased leaves were surface disinfested with 75% ethyl alcohol for 30 s and 2% NaClO for 3 min, washed with sterile water three times and then plated on potato dextrose agar (PDA) and incubated at 27℃ with a 12h/12h light/dark photoperiod for 4 days. A total of 7 fungal isolates were obtained by single-spore isolation. All the colonies were dark olivaceous on the PDA plates, with loose, cottony mycelium. On potato carrot agar (PCA), all fungal isolates produced conidial chains with numerous secondary chains. The conidia were ellipsoid or obpyriform with 0-3 longitudinal septa and 2-4 transverse septa, measuring 20.6 to 35.8 × 6.8 to 11.2 μm (25.5 ± 0.4 × 8.7 ± 0.2 μm, n=50). The morphological characteristics of the seven fungal isolates were consistent with the A. alternata descriptions of Simmons (2007). DNA was extracted from 50 mg of mycelia for the representative isolate HLP17-7. The internal transcribed spacer (ITS) region was PCR amplified using the universal primers ITS1 / ITS4 (White et al.1990), the partial coding sequence of endopolygalacturonase (endoPG) and the partial region of the histone 3 (H3) were amplified using primers PG2b / PG3 (Andrew et al. 2009) and H3-1a / H3-1b (Glass and Donaldson 1995) respectively. The products were sequenced and deposited in GenBank database under the accession numbers MW514319 [ITS], ON806938 endoPG, MW489301 [H3]. ITS, endoPG and H3 sequences had 99.81% (1/535 nt difference), 99.78% (1/448 nt difference) and 100% (0/417 nt difference) homology with homologous sequences of A. alternata strains (KP124306 [ITS], KP124006 [endoPG], MK085979 [H3]), respectively. During the early autumn, pathogenicity tests were carried out on the healthy mature leaves of seven-year-old Juglans regia plants in the field. Thirty leaves (five leaves per plant) were wounded with a sterile needle and then sprayed with a spore suspension prepared from 10-day-old PDA culture. Five wounded leaves per plant were sprayed with sterile water as control. All the treated leaves were covered with clear plastic bags for 3 days, and the experiment was replicated three times. On the 8th day after inoculation, brown spots appeared on the inoculated leaves, but no spots were observed in the control. Morphological observation and gene sequencing confirmed that the original fungal pathogen was re-isolated from the inoculated leaves. No colony was isolated from the control leaves. The pathogen causing the brown spot was identified as A. alternata based on morphological features and sequence analysis. A. alternata has been reported previously in Sichuan (Yang et al., 2017) causing brown spot in walnut. Xinjiang is dry with little rain and abundant sunshine, so there are few diseases on walnuts. However, the occurrence of brown spot disease has alarmed fruit farmers, walnuts are still at the risk of A. alternata infections even in dry environment with little rain. To our knowledge, this is the first report of A. alternata causing brown spot in walnut in Xinjiang, China.

Antagonistic activities of Trichoderma spp. isolates against Neoscytalidium dimidiatum causing brown spot disease on dragon fruit Hylocereus undatus

Antagonistic activities of Trichoderma spp. isolates against Neoscytalidium dimidiatum causing brown spot disease on dragon fruit Hylocereus undatus

Phytochemical characterization and antifungal ability of three meliaceae species against Bipolaris oryzae

Phytochemical characterization and antifungal ability of three meliaceae species against Bipolaris oryzae

Effects of slope aspect and age class on diseases of Juglans regia in Wild Walnut Nature Conservation Area of Xinjiang, China.

To understand the disease situation of vulnerable plant Juglans regia, we investigated the proportions of four diseases of J. regia with different age classes in different slope aspects in the Wild Walnut Nature Conservation Area of Xinjiang. We analyzed the correlation of disease types and disease grades with the diameter at breast height (DBH) of J. regia and slope aspects. The results showed that the main diseases of J. regia in the reserve were walnut brown spot disease (95.8%), walnut deadwood disease (90.5%), walnut black spot disease (74.4%), and walnut rot disease (7.7%). J. regia was susceptible to walnut brown spot disease in all the four slope aspects, with walnut deadwood disease on shady and semi-shady slopes, walnut black spot disease on sunny and shady slopes, and walnut rot disease on semi-sunny and semi-shady slopes. The proportion of diseased plants with the four diseases decreased with the increases of disease grades (1-4 grades) in the four slope aspects. Across the four slope aspects, the middle-aged trees had the largest proportion of walnut deadwood disease, walnut black spot disease and walnut brown spot disease, followed by old trees and young trees. No diseased seedlings were found. Walnut rot disease only occurred in old trees. There was significant positive correlation between DBH of J. regia and the four diseases. Walnut black spot disease had significant negative correlation with slope aspect. There was correlation between different disease grades of walnut deadwood disease, walnut rot disease and walnut black spot disease with DBH and slope aspects.

Fluorescent detection of brown spot of tobacco caused by Alternaria alternata based on lambda exonuclease-induced DNAzyme amplification.

A rapid, simple, and sensitive fluorescent detection method for brown spot of tobacco is established by lambda exonuclease-induced Mg2+-dependent DNAzyme amplification. It contains hybridization of the Alternaria alternata genome and HP1, digestion of the 5'-phosphorylated strand of the hybrid dsDNA by lambda exonuclease, acquisition of complete Mg2+-dependent DNAzyme, cleavage of the substrate modified with FAM and BHQ-1, and fluorescent detection. The proposed assay exhibits good sensitivity (10 pg L-1), selectivity and reproducibility. The method does not require pure DNA and expensive instruments, and can be performed within 2.5 hours. To the best of our knowledge, this is the first report of fluorescent detection of Alternaria alternata and its tobacco field samples. This method can be applied to the rapid and sensitive detection of Alternaria alternata in tobacco and its seedlings, and is particularly important for the green prevention and control of tobacco brown spot disease.

First Report of Stem brown spot on 'Thai Gold' Selenicereus megalanthus in Malaysia caused by Nigrospora sphaerica.

'Thai Gold' yellow pitahaya (family Cactaceae, Selenicereus megalanthus) is a new crop being planted commercially in Malaysia. In May 2021, reddish-brown necrotic lesions were observed on the stems of approximately 60% of 'yellow pitahaya' plants in the field (~8 ha) located in the district Keningau of Sabah, Malaysia (5°20'53.1"N 116°06'23.0"E). As the disease progressed, the smaller lesions merged into larger irregularly shaped areas that formed dark brown in color. Stems with reddish-brown spot symptoms from ten plants were collected from the field and brought to the laboratory in sterilized paper bags. The symptom margin was excised into small blocks (5 x 5 x 5 mm). The blocks were surface sterilized based on Khoo et al. (2022), and placed on potato dextrose agar (PDA). The pathogens were isolated (three isolates were obtained) and cultured on potato dextrose agar (PDA) at 25°C for 5 days in the dark. The isolates developed floccose, white colony that darkened with age in PDA. Conidia (n = 30) were single celled, black, smooth, globose to subglobose, 13.9 to 18.7 μm in diameter, and borne singly on a hyaline vesicle at the tip of each conidiophore. Genomic DNA was extracted from fresh mycelia based on Khoo et al. (2021) and Khoo et al. (2022). Amplification of the internal transcribed spacer (ITS) region of rDNA, translation elongation factor 1-α (tef1-a) region and β-tubulin (tub2) genes were performed using ITS1/ITS4 (White et al. 1990), EF1-728F/EF2 (O'Donnell et al. 1998; Carbone and Kohn, 1999) and T10/Bt2b (Glass and Donaldson, 1995; O'Donnell and Cigelnik, 1997) primer sets, respectively. The products were sent to Apical Scientific Sdn. Bhd. for purification and sequencing. BLASTn analysis of the newly generated ITS (OK448496, OM832586, OM832589) were 100% identical to Nigrospora sphaerica isolate 1SS (MN339998) (507/507 bp), tef1-a (OM223859, OM826971, OM826972) were 100% identical to Nigrospora sphaerica isolate F (MT708197) (497/497 bp) and tub2 (OL697400, OM826973, OM826974) were 100% identical to Nigrospora sphaerica isolate SN180517 (MN719407) (434/434 bp). The isolates established a supported clade to the related N. sphaerica type sequences, according to phylogenetic analysis using maximum likelihood based on the concatenated ITS, tef1-a and tub2 sequences. Morphological and molecular characterization matched the description of N. sphaerica (Kee et al. 2019). Koch's postulates were performed by spray inoculation (106 spores/ml) of isolate Keningau on the stem of three 'Thai Gold' yellow pitahaya plants in growth stage 4 (BBCH code: 419) (Kishore, 2016), while water was sprayed on three mock controls. The experiment was repeated using isolate Keningau02 and Keningau03 as inoculants. The inoculated stems on yellow pitahaya plants were covered with plastics for 48 h, and the plants were maintained in a greenhouse at room temperature 25 to 28°C with a relative humidity of 80 to 90%. All the inoculated stems developed symptoms 5 days post-inoculation, whereas no symptoms occurred on mock controls, thus fulfilling the Koch's postulates. No pathogen was isolated from the mock controls. The experiments were repeated two more times for each isolate. The reisolated fungi were identical to N. sphaerica morphologically and molecularly. Previously, N. sphaerica has been reported to cause stem brown spot disease on S. megalanthus in the Philippines (Taguiam et al. 2020). To our knowledge, this is the first report of N. sphaerica causing stem brown spot on 'Thai Gold' S. megalanthus in Malaysia. Our findings serve as a warning for the authorities and farmers that the disease threat has appeared for the Malaysian yellow pitahaya production.

Field efficacy of aqueous extracts of Artemisia annua, Commelina benghalensis and Euphorbia hirta on rice growth, yield and brown spot disease incidence

Field efficacy of aqueous extracts of Artemisia annua, Commelina benghalensis and Euphorbia hirta on rice growth, yield and brown spot disease incidence

Stability analysis and optimal control for leaf brown spot disease of rice

<abstract> <p>Leaf brown spot, caused by fungi, is a terrible plant disease, and it can significantly reduce the quality and quantity of rice. In this paper, we developed the model based on leaf brown spot disease development and considered a preventive treatment using botanical fungicide. In addition, we develop a model with suitable optimal control strategies. The result shows disease-free equilibrium is asymptotically stable when $R_0>1$. In contrast, the endemic equilibrium is asymptotically stable when $R_0 > 1$. The obtained optimal control to can reduce the number of infected plants compared to that without control. In addition, the analytical results were confirmed by numerical simulations of the occurrence of the theoretical results.</p> </abstract>

Identification of Paddy Rice Diseases Using Deep Convolutional Neural Networks

In modern digital agricultural applications, automatic identification and diagnosis of plant diseases using artificial intelligence is becoming popular and widespread. Deep learning is a promising tool in pattern recognition and machine learning and it can be used to identify and classify diseases in paddy rice. In this study, 2 different paddy rice diseases, including rice blast and brown spot, were investigated in the district of İpsala in the province of Edirne between the 2020 and 2021 production seasons by collecting 1569 images. These diseases are very common and important in Edirne province and surrounding rice production areas. Therefore, practical methods are needed to identify and classify these two diseases. A Convolutional Neural Network (CNN) model was created by applying pre-processing techniques such as rescaling, rotation, and data augmentation to the paddy rice disease images. The classification model was created in Google Colab, which is a web-based Python editor using Tensorflow and Keras libraries. The CNN model was able to classify rice blast and brown spot diseases with high accuracy of 91.70%.

A Morphological Change in Leaves-Based Image Processing Approach for Detecting Plant Diseases

In recent years, rice production is mostly affected by rice plant leaf diseases due to the unawareness of suitable management strategies. The paddy leaves are regularly impacted by Brown spot and Bacterial blight diseases, which result in creating major loss to the farm owners. The naked-eye observation is used by the farmer to analyse the condition of paddy leaves, but, it takes more time and the accuracy of it is based on the observer. The naked-eye observation is generally difficult and it has a high possibility of human error. To overcome these drawbacks, a fast and suitable recognition system is required. Thus, appropriate methodologies are required for the determination of diseases in paddy leaf. The use of image processing is seen as a non-intrusive method that offers farmers a precise, economical, and trustworthy solution. Therefore, this research work, focused to provide the fast recognition system to detect leaf diseases in paddy crops.

Effect of Sowing Times and Rice Varietal Resistance on the Severity of Narrow Brown Leaf Spot Disease in Relation to Environmental Conditions

The objective of this study was to investigate the effects of sowing times and genetic resistance of 10 commercially important rice varieties on the percent disease severity (PDS) of narrow brown leaf spot (NBLS) caused by Cercospora oryzae. Two sowing time treatments (mid-May and mid-June) each year were evaluated for this 2-year study. Rice varieties were drill seeded and arranged in randomized complete block designed plots with four replications for each variety. The effects of environmental factors (high and low temperature, relative humidity and precipitation) on the NBLS severity of the rice varieties at both sowing times were also evaluated. Disease data was analyzed using computer software GenStat 10th edition. Results: By changing cultivation timing of rice varieties, B-Chenab, KSK-434, PK-386, B-Kissan, and KSK-133 from mid-May to mid-June, their resistance levels were also changed from a higher to a lower. Weather conditions during the mid-June cultivation of 2019 induced a higher level of disease severity than did the mid-May weather conditions of 2018. The variation in temperatures affected the percent disease severity more as compared to relative humidity and precipitation. High temperature of 31-33˚C and low temperature of 18-21˚C were found to be most effective in enhancing the NBLS development. Minimum NBLS severity 4.75% and 8.25% was noted on variety B-515 in mid-May and mid-June sowings respectively. Thus, its rating changed from resistant to mildly susceptible by changing sowing timing. Rice variety PK-1121 depicted maximum NBLS severity 60.25 % in mid-May sowings, rated as very highly susceptible, while severity increased to 79.25% in mid-June sowings, and rated as completely susceptible. It is concluded that the severity of NBLS was affected by genetic resistance level of rice varieties, sowing times and weather conditions thus consideration of these factors is the key to the integrated management of the NBLS in rice.

Effectiveness of new fungicides and neem plant aqueous extract against brown spot disease of rice

Effectiveness of new fungicides and neem plant aqueous extract against brown spot disease of rice

ACT-Toxin, the Key Effector for the Virulence of Alternaria alternata Tangerine Pathotype to Specific Citrus Species

Alternaria brown spot disease is caused by the Alternaria alternata tangerine pathotype, which relies on ACT-toxin for infection. At present, all identified ACT-toxin biosynthesis-related genes are multi-copy genes. In this study, we summarized the advances in important host-specific toxins (HSTs), and listed key genes required for the pathogenicity of the A. alternata tangerine pathotype. Toxin virulence test results revealed that different citrus species displayed distinctly different tolerances to ACT-toxin. The extraction method of ACT-toxin crude extract was described in schematic form to make the method easier to understand. In addition, target gene disruption of two copies of ACTT5 (∆∆ACTT5) displayed significantly reduced virulence, indicating that ACTT5 is essential for the pathogenicity of the A. alternata tangerine pathotype.

Occurrence of citrus brown and black spot diseases and their control using pre-harvest approaches

Mild brown and black spot diseases symptoms were detected on citrus varieties, Valencia and Navel fruits during season 2018 in some citrus orchards at North Egypt. Collected diseased fruit samples revealed isolation of Alternaria alternata and Phyllosticta citricarpa (McAlpine) van der Aa. Some organic acids, salts and Saccharomyces cerevisiae were evaluated against the diseases incidents in vitro and in vivo. Complete growth inhibition was recorded for fungi tested at 2g/L of salicylic acid, Potassium dihydrogen phosphate, Tri-Sodium polyphosphate and 2.5 g/L of S. cerevisiae. All pre-harvest treated Valencia trees, inoculated fruits revealed no diseases symptoms up to 10 days of storage period. Meanwhile, S. cerevisiae and salicylic acid treatments had extended protective effect up to 20 days. Control strategy through spraying Valencia orange trees with yeast or some organic acids and salts as pre-harvest approaches should be taken in consideration especially these diseases began to occur in North region of Egypt.

Benchmarking of different microbes for their biosurfactants antifungal action against plant pathogens

The biotic stress caused by phytopathogens (bacteria, fungus, yeast and insect pests) is a primary factor in yield loss of plants. Biocontrol agents and their active compounds are used to manage such plant pathogens. Here, in our study, we screened four bacterial isolates identified as Bacillus cereus, B. anthracis, B. velezensis and Serratia marcescens after morphological, biochemical and molecular characterization (16s rDNA sequencing) for production of biosurfactant by foam forming activity, oil spreading tests and emulsification activity. Highest foam stability (75 min) and maximum emulsification activity E24% (75%) was observed by B. velezensis strain. Among all the four isolates, Bacillus velezensis strain produced maximum biosurfactant (0.349±0.004 g/50 mL). Biosurfactant of all the four bacterial isolates were checked for fungal inhibiton on PDA plate(s). Bacillus velezensis showed comparatively the highest percent inhibition 58.82, 88.15, 78.45,72.68, 83.96, 75.47, 68.07 and 88.44% against Colletotrichum falcatum, Fusarium oxysporum f sp. ciceri, Helminthosporium maydis, F. oxysporum f. sp. lycopersici, Aspergillus niger, Mucor sp., Helminthosporium oryzae and Rhizoctonia solani, respectively. Bacillus velezensis biosurfactant among all the four bacterial isolates was found to be most effective against the tested phytopathogens.

Chitin-induced systemic disease resistance in rice requires both OsCERK1 and OsCEBiP and is mediated via perturbation of cell-wall biogenesis in leaves.

Chitin is a well-known elicitor of disease resistance and its recognition by plants is crucial to perceive fungal infections. Chitin can induce both a local immune response and a systemic disease resistance when provided as a supplement in soils. Unlike local immune responses, it is poorly explored how chitin-induced systemic disease resistance is developed. In this study, we report the systemic induction of disease resistance against the fungal pathogen Bipolaris oryzae by chitin supplementation of soils in rice. The transcriptome analysis uncovered genes related to cell-wall biogenesis, cytokinin signaling, regulation of phosphorylation, and defence priming in the development of chitin-induced systemic response. Alterations of cell-wall composition were observed in leaves of rice plants grown in chitin-supplemented soils, and the disease resistance against B. oryzae was increased in rice leaves treated with a cellulose biosynthesis inhibitor. The disruption of genes for lysin motif (LysM)-containing chitin receptors, OsCERK1 (Chitin elicitor receptor kinase 1) and OsCEBiP (Chitin elicitor-binding protein), compromised chitin-induced systemic disease resistance against B. oryzae and differential expression of chitin-induced genes found in wild-type rice plants. These findings suggest that chitin-induced systemic disease resistance in rice is caused by a perturbation of cell-wall biogenesis in leaves through long-distance signalling after local recognition of chitins by OsCERK1 and OsCEBiP.

Micro-farming specific morpho-molecular characterization of Trichoderma isolates and its bio-control potential against foliar fungal plant pathogens

In order to understand the use of micro farming specific local bio-control agents against the foliar pathogens, twenty-one Trichoderma isolates were collected from different cropping locations of Karnataka. In morphological characterization: all colonies were appeared dark green with flat, even/uneven growth with 2–4 concentric rings and sporulation was observed after 2–4 days after inoculation on potato dextrose agar medium. The length × width of conidia and phialides varied from 2.5–4.6 μm × 2.5–4.6 μm and 6–11.3 μm × 2–3.5 μm respectively. In Basic Local Alignment Search Tool analysis of 5.8S-ITS region was amplified using ITS-4 and 5. These results assisted in species identification and classified into five clades (T. harzianum: 11, T. asperellum; 5, T. virde; 2, T. virens; 2 and T. longibrachiatum; 1). Further, in antagonistic activity, RMlO exhibited highest growth inhibition of Asperisporium caricae (96.30%), Pyricularia oryzae (97.03%) and Bipolaris oryzae (100%)) significantly over the commercial isolate (A. caricae (85.93%); P. oryzae (89.38%) and B. oryzae (91.92%)).

Genetic diversity and structure of Bipolaris oryzae and Exserohilum rostratum populations causing brown spot of rice in Burkina Faso based on genotyping-by-sequencing.

In recent years, Brown spot disease of rice (BSR) has been observed on leaves and seeds of rice in all rice-growing areas of Burkina Faso. Bipolaris oryzae and Exserohilum rostratum are the main fungal species isolated from BSR infected tissues and they are frequently observed in the same field. However, we are lacking information on the genetic diversity and population structure of these fungi in Burkina Faso. The mode of reproduction is also unknown. The genetic diversity of isolates of B. oryzae (n=61) and E. rostratum (n=151), collected from major rice-growing areas of Burkina Faso, was estimated using genotyping-by-sequencing (GBS). The mean values for nucleotide diversity (π) were 1.9 x10-4 for B. oryzae and 4.8 x10-4 for E. rostratum. There is no genetic differentiation between the geographical populations of each species. The analysis of molecular variance revealed that 89% and 94% of the genetic variances were within the populations of B. oryzae and E. rostratum, respectively. For each species, four genetic clusters were identified by two clustering methods (DAPC and sNMF). The distribution of these genetic groups was independent of the geographical origin of the isolates. Evidence of recombination was detected in the populations of B. oryzae and E. rostratum. For B. oryzae balanced mating type ratios were supporting sexual reproduction. For E. rostratum overrepresentation of MAT1-2 isolates (79%) suggested a predominant asexual reproduction. This study provides important information on the biology and genetics of the two major fungi causing brown spot disease of rice in Burkina Faso.

Accurate cotton diseases and pests detection in complex background based on an improved YOLOX model

Cotton diseases and pests are essential factors affecting the quality and yield of cotton in agricultural production. To meet the needs of intelligent agriculture development and solve the problems of low efficiency and poor reliability of cotton diseases and pests detection, this study proposed a real-time high-performance detection model based on improved YOLOX. The model introduced Efficient Channel Attention (ECA), hard-Swish activation function, and Focal Loss function into YOLOX, which improved the ability of the model to extract image features, solved the problem of sample imbalance, improved the detection speed and accuracy, and enhanced the detection effect of cotton diseases and pests. A total of 5760 manually labeled cotton diseases and pests images (including five kinds of red leaf blight, verticillium wilt, cotton spider mite damage, double-spotted leaf beetle damage, and brown spot disease) were used to fine-tune and test the model. The mean Average Precision (mAP) of cotton diseases and pests detection reached 94.60%, the precision was 94.04%, the F1-score was 0.90, and the FPS was 74.21. Furthermore, the results were compared with five classical object detection algorithms (Faster R-CNN, SSD, YOLOv3, YOLOv4, and YOLOv5). The comparative results showed that the mAP of the improved model was 11.50%, 21.17%, 9.34%, 10.22%, and 8.33% higher than the other five algorithms, and the detection speed can meet the real-time requirements. Finally, a cotton diseases and pests detection software was designed and developed based on the improved model, deployed on the smartphone to complete the real-time detection of cotton diseases and pests in the field environment. The improved model can effectively detect the infected area of cotton leaves in the field and provide theoretical reference and technical support for controlling cotton diseases and pests.

Aerobiological dynamics of Bipolaris oryzae in the rice agroecosystem and its impact on rice brown spot disease severity

Rice brown spot disease (RBS), caused by seed-borne and air-borne pathogen Bipolaris oryzae, appears throughout the rice growing season. Considering its polycyclic nature and its significance in yield loss, a one-year (2019) aerobiological study was carried out at Thiruthani (13°11′N 79°38′E) village in Thiruvallur district during two seasons viz., kharif (April 2019 to July 2019) and rabi (August 2019-December 2019). B. oryzae airspora contributed to an average of 20.7% annually. Amongst the barren land conditions, it contributed 11.83%, whereas during rabi 32.52% and kharif 18.04%. The average length (range 40.0-129.8) and average breadth (range 13.17-23.92) of B. oryzae spores were used to calculate dvolume (range 20.54-42.03) and aspect ratio (2.29-6.85). The intra-diurnal behaviour pattern indicated that B. oryzae airspora percentage contribution was highest at 12 noon-1 p.m. (55.64%) in rabi crop and two peaks at 10-11 a.m. (19.56%) and at 12 noon-1 p.m. (19.09%) in kharif crop. The calculated correlation coefficient R value revealed that relative humidity (kharif R=0.9879, rabi R=0.9977) and precipitation in kharif (0.9279) were positively correlated, while the temperature in rabi was negatively correlated with the RBS pathogen airspora percentage. Both the airspora percentage contributions of the RBS pathogen and the PDI were highly correlated (R=0.9002 in kharif, R=0.9874 in rabi). In the Step-Down regression analysis, R2 value (regression coefficient) unveiled that relative humidity (R2 value=0.99760 in kharif, 0.9954 in rabi), precipitation (R2=0.8480) and wind speed (R2=0.7319) in kharif, and temperature in rabi (R2=0.8862) had a greater impact on the RBS pathogen airspora per cent contribution. The airspora B. oryzae per cent contribution aggravated disease occurrence and reflected in the PDI (R2 = 0.8103 in kharif, R2=0.9748 in rabi). The calculated P value and OD ratio supported the significance of the experimental results.