Yellow Mosaic Virus Research Articles

Detection of yellow mosaic virus resistance in Soybean (Glycine max L.) genotypes for yield and related traits

Background Twenty soybean genotypes were screened for Soybean yellow mosaic virus (YMV) identification which were collected from the Genetics and plant breeding farm laboratory. Methods To evaluate genetic studies of the chosen materials, the use of a net house assay upon sap inoculation made it easier to determine the trend of the Area Under Disease Progress Curve (AUDPC) in a controlled environment. Younger leaves from these plants were gathered and used for molecular analysis. Results Six genotypes were identified with semi-resistant disease reactions. Yellow mosaic virus-resistant and susceptible soybean genotypes were distinguished using a soybean “Rsv1-h” gene-based primer pair. To discover the existence of the Rsv-1-h gene responsible for YMV resistance, a genetic diversity panel of 15 soybean genotypes was investigated with two simple sequence repeat (SSR) markers. The BARCSOYSSR_13_1115 and BARCSOYSSR_13_1173 primer sets were employed to validate the desired genes in these genotypes. Conclusion The genotypes HIHS-WIHS, MINA-HAI, Shohag, G-2120, BRAGG, and BS-3 presented the major gene Rsv1-h, which is said to be essential for yellow mosaic virus resistance and can provide better yield also than other genotypes. The six soybean genotypes with the Rsv1-h gene may be resistant to mosaic virus and could be exploited as a source of improved breeding material in the future.

Abiotic and Biotic Stresses in Green Gram (Vigna radiata L. Wilczek): A Comprehensive Review

Green gram (Vigna radiata L. Wilczek), a vital legume crop widely cultivated across Asia, is a rich source of minerals and plant-based protein. Despite its nutritional and agricultural importance, green gram production is significantly affected by various biotic and abiotic stress factors. Biotic stresses include diseases caused by bacteria, viruses, fungi, and insect pests. Major fungal diseases impacting green gram are anthracnose, cercospora leaf spot, and dry root rot, while viral infections are predominantly caused by the yellow mosaic virus. Insect pests such as bruchids, aphids, jassids, and whiteflies also pose serious threats to crop health. Abiotic stresses, particularly salinity, high temperatures, and drought, are equally detrimental and are becoming increasingly prominent due to climate change. These stressors adversely affect plant growth, development, and yield, posing a significant challenge to sustainable green gram production. Understanding the physiological, biochemical, and molecular mechanisms of stress tolerance is essential for developing resilient green gram cultivars. To mitigate the adverse effects of these stressors and ensure sustainable production, integrated crop management strategies are crucial. These strategies should encompass genetic engineering, traditional breeding, marker-assisted selection, and improved agronomic practices. Genetic approaches can help develop green gram varieties with enhanced resistance to both biotic and abiotic stresses. Additionally, agronomic practices such as optimal irrigation, soil management, and the use of bio pesticides can further support stress management. This comprehensive review highlights the critical need for a multifaceted approach to manage biotic and abiotic stresses in green gram. By integrating advanced genetic techniques with sustainable agronomic practices, it is possible to enhance the resilience and productivity of green gram, ensuring its continued contribution to global food security.

Selection efficiency of molecular markers associated to Yellow Mosaic Virus (YMV) tolerance and identification of donors for earliness, yield and YMV tolerance in blackgram (Vigna mungo (L.) Hepper) using GT Biplot analysis

Selection efficiency of molecular markers associated to Yellow Mosaic Virus (YMV) tolerance and identification of donors for earliness, yield and YMV tolerance in blackgram (Vigna mungo (L.) Hepper) using GT Biplot analysis

Selection efficiency of molecular markers associated to Yellow Mosaic Virus (YMV) tolerance and identification of donors for earliness, yield and YMV tolerance in blackgram (Vigna mungo (L.) Hepper) using GT Biplot analysis

Selection efficiency of molecular markers associated to Yellow Mosaic Virus (YMV) tolerance and identification of donors for earliness, yield and YMV tolerance in blackgram (Vigna mungo (L.) Hepper) using GT Biplot analysis

Unveiling resistant sources and characterizing germplasm for effective management of yellow mosaic virus (YMV) disease in blackgram [Vigna mungo (L.) Hepper

Unveiling resistant sources and characterizing germplasm for effective management of yellow mosaic virus (YMV) disease in blackgram [Vigna mungo (L.) Hepper

Multivariate Analysis and Screening of Moth Bean Accessions for Biotic Stresses in the Arid Region of Western India

The present investigation assesses the genetic diversity and resilience of moth bean (Vigna aconitifolia) against the biotic stresses in the arid zones of India. This research was carried out at the ICAR-Indian Institute of Pulses Research, Regional Research Centre, Bikaner, and employed an augmented design to analyze 300 accessions for morphological and agronomic traits. The study integrated Pearson’s correlation, hierarchical clustering, and principal component analysis to understand trait interrelationships and genetic variance. The number of clusters per plant, number of pods per plant, plant height and test weight showed a highly significant and positive correlation, whereas days to 50% flowering and number of branches per plant showed a negative correlation with seed yield per plant. Hierarchical clustering subdivided accessions into fourteen clusters, and cluster1 best suited to arid conditions with 21 accessions. Principal component analysis with eigenvalues classified the accessions into eight principal components. PC1 contributed the maximum variation that is 32.21 percent, followed by other clusters. Cercospora leaf spot had the highest disease incidence among the three diseases (yellow mosaic virus, cercospora leaf spot and leaf curl virus diseases). The findings underscore the potential of exploiting genetic variability in moth beans for breeding programs aimed at enhancing yield and stress tolerance, crucial for sustainable production in resource-poor arid ecosystems.

Evaluation of indigenous and exotic soybean accessions for yield, resistance to frog-eye leaf spot and yellow mosaic virus diseases

AbstractSoybean is a major source of vegetable oil and protein worldwide. Globally, India is among the top five producers where soybean is a major oilseed grown under diverse agro-climatic conditions by small and marginal farmers. The present study aims to identify soybean varieties with higher yield levels, resistance to pestdiseases and adaptability to climatic fluctuations. One hundred and twenty-five (125) indigenous and exotic soybean germplasm accessions and five checks were evaluated and characterized for eight agro-morphological traits at five testing locations and also screened for frog-eye leaf spot (FLS) and yellow mosaic virus (YMV) diseases under hot-spot locations during the rainy season. A wide range of variability was observed among accessions for days to 50% flowering (39–59), plant height (41–111 cm), number of nodes/plant (10–30), pod clusters/plant (14–39), number of pods/plant (40–102), days to maturity (96–115), grain yield/plant (4.89–16.54 g) and 100-seed weight (6.02–13.72 g). Among various traits, 100-seed weight (0.45), number of pods/plant (0.60) and number of pod clusters/plant (0.38) were found to be major yield-contributing traits as they exhibited highly significant correlation with grain yield/plant. Principal components PCI and PCII with eigen value >1 accounted for 42.66 and 27.08% of the total variation, respectively. Accessions G24 (EC 393222) from Taiwan and G40 (IMP-1) from the USA belonging to cluster IV were found promising for multiple yield traits and JS 20–38 from cluster III for earliness as per cluster analysis. GGE biplot average environment coordination (AEC) view revealed that the accessions viz., G11 (EC 333872), G2 (EC 251506) and G47 (TNAU-S-55) were the best performing stable genotypes in terms of grain yield/plant across locations. Twelve accessions had a high level of resistance against both FLS and YMV diseases under natural hot-spot conditions which can be utilized as promising donors in the soybean breeding programme.

Molecular Detection of Yellow Mosaic Virus Infecting Black Gram and Green Gram in Coimbatore District

Yellow mosaic virus (YMV) is indeed one of the most destructive diseases of mungbean (Vigna radiata (l.) wilczek) and urdbean (Vigna mungo l. Hepper). Mungbean Yellow Mosaic Virus infecting green gram and black gram cause great yield loss.The virus belongs to the genus begomovirus of the family geminiviridae transmitted by white fly. Infected samples were collected and scored according to disease scale. Diseased samples were collected from infected plants from the field of Coimbatore district and percent disease index was calculated. The symptoms of yellow mosaic virus ranges from small yellow spots which develop as mosaic yellow patterns. Later the disease leads to complete yellowing of the leaf samples. Percent Disease Index impart the severity of virus in black gram and green gram field.The DNA was isolated from both black gram and green gram samples through CTAB method. Both the quality and quantity of the DNA was evaluated through gel electrophoresis and nanodrop reading and found to be appreciably good. The DNA was molecularly confirmed with universal primer which show amplification around 1200 bp through Polymerase Chain Reaction (PCR). Polymerase chain reaction of Yellow Mosaic Virus infecting black gram and green gram samples using MYMV-CP-f/MYMV-cp-r primers of DNA A component were amplified and the expected product of size 1000 bp from the obtained infected samples.

Yellow Mosaic Virus (YMV) in Green Gram: Impacts, Management, and Future Perspectives

Yellow mosaic virus (YMV) is a destructive viral pathogen that affects green gram (Vigna radiata) crops, leading to significant yield losses and economic repercussions. This review paper provides a comprehensive analysis of the impacts of YMV on green gram cultivation, explores the current management strategies employed to combat the disease, and discusses future perspectives for effective YMV control and prevention. YMV is primarily transmitted through whiteflies and infects green gram plants at various stages of growth, causing severe symptoms such as leaf yellowing, stunted growth, and mosaic patterns. These symptoms ultimately lead to reduced crop yield and quality. The virus poses a major threat to green gram production globally, demanding urgent attention and effective management practices. Various management approaches have been employed to mitigate the impact of YMV. Cultural practices, including proper field sanitation, weed control, and crop rotation, play a vital role in disease management. Insecticide application, use of yellow sticky traps, and whitefly population monitoring are important components of integrated pest management strategies aimed at reducing virus transmission. Additionally, the development and deployment of resistant cultivars through conventional breeding and biotechnological approaches have shown promise in minimizing YMV infection and its associated losses. Despite these efforts, YMV continues to pose significant challenges to green gram production, necessitating further research and innovative approaches. Future perspectives for YMV management involve the integration of advanced technologies such as molecular diagnostics, genome editing, and RNA interference to enhance disease resistance in green gram varieties. Additionally, promoting awareness among farmers about YMV symptoms, preventive measures, and adoption of integrated disease management strategies will contribute to sustainable green gram production. In conclusion, YMV represents a major threat to green gram cultivation, affecting crop productivity and economic sustainability. This review emphasizes the need for concerted efforts to develop comprehensive YMV management strategies. By combining conventional and modern techniques, effective disease control measures can be implemented to mitigate the impact of YMV and secure the future of green gram production.

Improved Spectral Detection of Nitrogen Deficiency and Yellow Mosaic Disease Stresses in Wheat Using a Soil Effect Removal Algorithm and Machine Learning

Wheat yellow mosaic disease is a low-temperature and soil-borne disease. Crop infection by the yellow mosaic virus can lead to severe yield and economic losses. It is easily confused with nitrogen deficiency based on the plant’s morphological characteristics. Timely disease detection and crop management in the field require the precise identification of crop stress types. However, the detection of crop stress is often underappreciated. Wheat nitrogen deficiency and yellow mosaic disease were investigated in the field and wheat physiological and biochemical experiments were conducted to collect agronomic indicators, four years of reflectance spectral data at green-up and jointing were collected, and then studies for the detection of nitrogen deficiency and yellow mosaic disease stresses were carried out. The continuous removal (CR), first-order derivative (FD), standard normal variate (SNV), and spectral separation of soil and vegetation (3SV) preprocessing methods and 96 spectral indices were evaluated. The threshold method and variance inflation factor (TVIF) were used as feature selection methods combined with machine learning to develop a crop stress detection method. The results show that the most sensitive wavelengths are found in the 725–1000 nm region, while the sensitivity of the spectrum in the 400–725 nm region is lower. The PRI670,570, B, and RARSa spectral indices can detect nitrogen deficiency and yellow leaf disease stress, and the OA and Kappa values are 93.87% and 0.873, respectively, for PRI670,570, which is the best index. A 3SV-TVIF-SVM stress detection method was then proposed, using OA and Kappa values of 96.97% and 0.931, respectively, for field data validation. The results of the study can provide technical support and a theoretical basis for the accurate control of yellow mosaic disease and nitrogen fertilizer management in the field.

Soybean Disease Detection and Segmentation Based on Mask-RCNN Algorithm

Anthracnose, frogeye leaf spot (FLS), rhizoctonia aerial blight (RAB), soybean mosaic virus (SMV), and yellow mosaic virus (YMV) of soybean are major common soybean leaf diseases that seriously affect soybean yield in India. However, the existing system needs a real-time detection method for soybean leaf diseases, which will help to take appropriate action for disease cure with minimum losses. This study studied a real-time detector for soybean leaf diseases based on deep convolutional neural networks. The 3,127 RGB images of disease-free leaves, anthracnose, FLS, RAB, SMV, and YMV-affected leaves of soybean were collected from the agriculture fields. The Mask R-CNN detection algorithm was used for the detection of soybean leaf diseases by introducing the Res Net 50 module. The pre-processed images (512×512 pixels) were used as input in Mask R-CNN. The model was trained at a number of epochs, training step per epoch training & validation, and learning rate were 80, 500, 50, 8, and 0.001, respectively. The detection accuracy was calculated at three levels of minimum detection confidence i.e. 0.80, 0.85, and 0.90. The results indicate that the maximum detection accuracy i.e. greater than 85% at 0.90 level of minimum detection confidence. This research indicates that the real-time detector based on deep learning provides a feasible solution for diagnosing soybean leaf diseases and provides guidance for the detection of other plant diseases. In addition to that the application of pesticide in the early stage reduce the use of pesticide resulting in less environmental pollution.

Laboratory Evaluation Of Different Botanicals And Bioagents Against Rhizoctonia Bataticola Causing Root Rot Of Soybean

Soybean (Glycine max (L.) Merill) is the world’s most important oilseed crop, accounting for nearly half of total oilseed acreage and production. It is susceptible to diseases such as anthracnose, charcoal rot, bacterial blight, yellow mosaic virus, and others that pose a threat to soybean production. Root rot caused by Rhizoctonia bataticola is an important and major limiting factor for seed yield. Evaluation of four bioagents and seven different botanicals against Rhizoctonia bataticola were carried out in laboratory to determine their efficacy. Among the botanicals tested in laboratory at a concentration of 10% using the poisoned food technique, Azadirachta indica recorded the highest inhibition (62.96%) of R. bataticola mycelial growth and was significantly superior to the other treatments. This was followed by Oscimum sanctum (58.88%) and Milletia pinnata (58.88%). The dual culture technique was used to test the in vitro efficacy of bioagents against R. bataticola. Trichoderma asperellum inhibited growth the most (87.50%), followed by Trichoderma harzianum (81.38%).

Screening of Mung Bean Genotypes against Yellow Mosaic Virus (YMV) Resistance

Experiment was conducted to identify the resistant Mung bean varieties against MYMV in Kharif during 2017. Ten Indian mung bean genotypes obtained from AICRP on Arid legumes, RARI, Durgapura, Jaipur, were used in the screening experiment and the obtained results revealed that there was significant variation among the genotypes for resistance against MYMV. Based on the average MYMV score, only two genotypes (IPM 02-3 and IPM 0205-7) were found completely free from the disease and the plants had maximum chlorophyll content whereas IPM-409-4 and RMG 991 were found resistant and chlorophyll content was low as compared to the highly resistant genotypes. The rest of six genotypes observed moderately resistant, moderately susceptible, susceptible and highly susceptible to the disease.

Detection of Resistance against Leaf Spot, Yellow Mosaic and Urdbean Leaf Crinkle Viruses in Mash Bean (Vigna mungo)

Among foliar diseases Leaf spot, yellow mosaic virus (YMV) and Urd bean leaf crinkle virus (ULCV) are destructive diseases of mash bean (Vigna mungo) in Pakistan. Incorporation of resistance against biotic stress in plants is traditional strategy of crop improvement through breeding. Effective breeding for biotic stresses entails readily accessible resistant germplasm. 67 genotypes were evaluated for multi disease resistance was tested for two consecutive years (2019 and 2020) at Barani Agricultural Research Institute, Chakwal. Experiment was repeated with an idea to decrease the effect of environment and those material was selected which performed same in both years. Out of 67 genotypes 12 were resistant against leaf spot infection and 19 genotypes were found highly resistant against yellow mosaic virus during both years. In case of ULCV disease did not appear during 2020. However, 19 genotypes showed resistance against ULCV during first year of experiment. Two genotypes namely 3CM-703 and 4CM-720 exhibited resistance response to all foliar diseases under study. Three genotypes viz. 4CM-716, 4CM-720, 5CM-708 demonstrated resistance against YMV as well as leaf spot. 4CM716, 4CM720, 5CM708, 7CM701, 7CM702, 7CM704, 7CM705, 7CM706 expressed resistance against leaf spot and ULCV simultaneously. The data generated is useful for improvement of mash bean through breeding.

Genetic diversity and marker trait association for yellow mosaic virus disease ingreen gram, Vigna radiata (L.) Wilczek

Yellow mosaic virus (YMV) disease is known to cause severe damage in green gram in terms of yield loss. As the resistance is often governed by recessive genes, introgression of such resistance faces some difficulty. DNA molecular markers are reported to be effective in this process. However, validation of such markers is important. Here, we have made an attempt to validate DNA markers associated with YMV disease resistance gene from a diverse group of 26 green gram genotypes. A total of 19 molecular markers were used to assess the susceptibility or resistance against YMV disease. Results show that among the amplified 31 alleles, 21 were polymorphic, with a mean of 1.1.0 per locus. The polymorphism information content (PIC) values ranged from 0.32 to 0.80. Only five markers exhibited higher PIC value (>6.0) and were revealed to be polymorphic, suggesting its utility in marker assisted selection for breeding YMV resistant genotypes in greengram. Dice dissimilarity coefficient among the genotypes exhibited a range of 0.07 to 1.0 which show a wide genetic variation among the genotypes for YMV tolerance. Neighbor-joining cluster analysis has grouped 26 green gram genotypes into 4 main clusters which revealed the existence of genetic dissimilarities among the genotypes. The genotypes AUGG 6, VBN (Gg) 2 and CO (Gg) 8 carried the positive alleles for YMV disease resistance and the allele for susceptibility were found in the genotypes AUGG 12, AUGG 15, AUGG 17 and AUGG 19. Single marker analysis indicated that there was correlation between the markers and the disease reaction in the field with exceptions. The findings revealed that the SSR markers CEDG180 and YR4 could be used to screen germplasm in order to discriminate the YMV resistant genotypes from the susceptible genotypes in marker assisted selection.

Molecular characterization and identification of bhendi yellow vein mosaic virus with satellite DNAs infecting okra plants of district Mardan, Pakistan

Abstract Background Bhendi or okra (Abelmoschus esculentus) is an important crop widely cultivated in the Indian subcontinent. The production of okra in tropical regions is constrained by several abiotic and biotic factors. Among biotic stresses, yellow vein mosaic disease (YVMD), transmitted by the whitefly (Bemisia tabaci Genn.), causes significant production losses. Results Leaves showing symptoms of YVMD were collected from okra plants in the district of Mardan, Pakistan, from which the total nucleic acid was extracted. It was found that the viral genome was 2739 bp in the length and had seven conserved open reading frames, comparable to those of monopartite begomovirus species from the Old World. Nucleotide sequence comparison revealed that the genome has 97.7% identity with bhendi yellow vein mosaic virus (BYVMV). Additionally, alpha- and betasatellite DNA components were amplified and sequenced. The alpha- and betasatellite DNA sequences were 1367 and 1346 nt in length, respectively. Sequence analysis revealed that the alpha- and betasatellite sequences shared 97.9 and 98.7% similarity with cotton leaf curl Multan alphasatellite DNA (CLCuMuA) and croton yellow vein mosaic betasatellite DNA (CroYVMB), respectively. Conclusions Based on the prevailing classification system, the isolate was identified as a variant of BYVMV, CLCuMuA, and CroYVB. Alphasatellite presence in the begomovirus betasatellite complex detected in the present study indicated a recent mobilization into the viral complex infecting okra in this region. The study findings may facilitate the design of new management strategies to protect this valuable crop against begomovirus infection.

Genetic Variability Studies of Yellow Mosaic Virus Infecting Blackgram [Vigna mungo (L.) Hepper] from Andhra Pradesh, India

Background: The productivity of blackgram is affected by many biotic and abiotic stresses. Among the biotic stresses, yellow mosaic disease (YMD) cause severe yield loss and it is caused by four distinct viruses (belongs to genus begomovirus) collectively known as yellow mosaic virus (YMV). Hence there is need to characterize various YMV isolates associated with blackgram in Andhra Pradesh. Methods: YMV infected blackgram samples were collected from East Godavari, Kurnool and Prakasam districts of Andhra Pradesh. The Rolling Circle Amplification (RCA) based full length MYMIV DNA-A and MYMV DNA-B of three isolates were cloned and sequenced. Result: Nucleotide sequence of full length DNA-A of MYMIV-East Godavari isolate showed greater than 96% similarity at nucleotide and greater than 90% at amino acid level with other MYMIV isolates in NCBI database. The complete DNA-A nucleotide sequence of MYMIV-Kurnool and MYMIV-Prakasam isolates shared greater than 99% similarity at nucleotide and greater than 98% at amino acid level with other MYMIV isolates. The complete nucleotide sequence of MYMV DNA-B of three isolates (East Godavari, Kurnool and Prakasam) had greater than 97% homology with other MYMV DNA-B isolates from database. The predicted amino acid sequence of MYMV DNA-B of three isolates shared greater than 96% homology with other MYMV-B isolates. The common region (CR) sequence similarity between MYMIV-As and MYMV-Bs of East Godavari and Kurnool isolates was 76.4% and 78.3% with Prakasam isolate. The divergence between the MYMIV-A and MYMV-B of present three isolates (East Godavari, Kurnool and Prakasam) under study were ranged from 22.2 to 22.6%.

Genetic diversity analysis in blackgram (Vigna mungo) genotypes using microsatellite markers for resistance to Yellow mosaic virus

One hundred and two blackgram genotypes were evaluated for Yellow mosaic virus (YMV) resistance based on disease scoring, molecular characterisation, yield and morphological observation. An analysis of variance and a correlation analysis were performed on nine biometric traits. The genotypes showed the highest genetic variation for a single plant yield (genotypic coefficient variation 42.72%). The genotypes were grouped into 18 clusters based on the morphological data. The genetic divergence among the blackgram genotypes was differentiated by 60 alleles using 14 polymorphic simple sequence repeat markers. The polymorphism information content value varied from 0.37 to 0.79. The multivariate analyses of the simple sequence repeat marker scorings divided the germplasm into five divergent clusters wherein, clusters viz., II, III and V accommodated 61 genotypes and all these genotypes were resistant to moderately resistant for YMV. The tolerant accessions identified from this present investigation can be directly used for further crop improvement programmes.

Identification of Elite Parental Lines in Cultivated and Wild Okra (Abelmoschus esculentus L. Moench) Accessions for Yellow Vein Mosaic Virus Disease Resistance Using Multivariate Analysis

Yellow vein mosaic virus (YVMV) is the most destructive viral disease of okra, has become a limiting factor in the successful cultivation and production of okra in India, resulting in yield losses ranging from 17.09 to 96.49 per cent. As a result, it is critical that breeders continue to develop superior varieties or hybrids with long-lasting resistance to overcome this major devastating disease. In this context present investigation was carried with 74 elite okra lines to discover potential parents for a resistance breeding programme. On the basis of D2 values the 74 genotypes were divided into seven groups. Cluster I constituted the highest number of genotypes followed by cluster II, III, IV, V, VI and VII. The traits per cent disease index of YVMV contributed maximum towards divergence followed by total phenolic content, peroxidase activity, fruit yield per plant, number of primary branches and number of fruit per plant. PCA showed four principal components with Eigen values more than one viz., 3.87, 3.21, 1.89 and 1.64 and accounted 81.56 per cent of the total genetic variation. Principal component analysis revealed that PC1 captured potential traits viz., total phenolic content, peroxidase activity, polyphenol oxidase, number of fruits per plant, number of primary branches per plant and fruit yield per plant, which could be used in future breeding programmes for high yield and YVMV resistance. The present study it was revealed that, eleven accessions viz., AE-65, AE-66, AE-CBE-921, Pusa Bhendi-5, SB-2, IC112449, AE-CBE-94, AE-CBE-943, AE-CBE-934, AE-CBE-92 and AE-CBE-93 appeared to be very promising lines for future use in resistant breeding programmes

Survey for Yellow Mosaic Disease Occurring on Blackgram [Vigna mungo (L.) Hepper] and Weed Hosts in Four Major Blackgram Growing Districts of Andhra Pradesh and Characterization of Associated Viruses using Coat Protein Gene

Background: Yellow mosaic disease (YMD) caused by Yellow mosaic virus is one of the major constraints in the pulse production in Andhra Pradesh (A.P.) due to fast evolution of strains, like Mungbean yellow mosaic India virus (MYMIV). Keeping this in view, a survey was undertaken in the major blackgram growing districts of A.P. to know the YMD incidence in blackgram and weed hosts and were characterized based on genetic features by comparing with other YMV isolates from different hosts and locations across the world. Methods: Roving survey was conducted during rabi 2019-20 in major blackgram growing districts of A.P. viz., Krishna, Guntur, West Godavari and Prakasam districts for YMD incidence. Blackgram plants showing characteristic symptoms were collected as representative samples from each mandal along with the suspected weed plants and were subjected to amplification using coat protein (CP) specific primers followed by molecular characterization. Phylogenetic tree for coat protein (CP) gene was constructed using aligned sequences with 1000 bootstrap replicates following neighbor-joining phylogeny. Result: Out of the four districts surveyed, the highest disease incidence was recorded at Machavaram village of Prakasam district (43.22%), whereas least disease incidence was recorded at Chinaganjam village of Praksam district (2.4%). Six weeds viz., Ageratum conyzoides, Amaranthus viridis, Parthenium hysterophporus, Vigna trilobata, Abelmoscus moschatus, Desmodium laxiflorum have showed positive result in PCR amplification with MYMIV specific coat protein primers. Four isolates from blackgram samples and two from weed plants shared 94.85 to 99.58% nucleotide identity among themselves.