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Legume Research, volume 47 issue 12 (december 2024) : 2147-2157

Distribution of Charcoal Rot of Soybean, its Influencing Factors and Pathogenic Variabilities in Different Regions of Madhya Pradesh

Pawan K. Amrate1,*, Kailash Chaukika2, Sanjay Kharte3, Dinesh K. Pancheshwar3, R.S. Marabi2, M.K. Shrivastav1, M.S. Bhale3
1Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur-482 004, Madhya Pradesh, India.
2Department of Entomology, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur-482 004, Madhya Pradesh, India.
3Department of Plant Pathology, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur-482 004, Madhya Pradesh, India.

  • Submitted20-10-2023|

  • Accepted19-03-2024|

  • First Online 11-04-2024|

  • doi 10.18805/LR-5262

Cite article:- Amrate K. Pawan, Chaukika Kailash, Kharte Sanjay, Pancheshwar K. Dinesh, Marabi R.S., Shrivastav M.K., Bhale M.S. (2024). Distribution of Charcoal Rot of Soybean, its Influencing Factors and Pathogenic Variabilities in Different Regions of Madhya Pradesh . Legume Research. 47(12): 2147-2157. doi: 10.18805/LR-5262.

ABSTRACT

Background: Macrophomina phaseolina (Tassi) Goid is a necrotrophic soil-inhabiting fungus that causes disease in several economic plants worldwide and has now become a serious threat to soybean cultivation in central India.

Methods: The random surveys were done during 2018 and 2019 to determine the present status of charcoal rot (M. phaseolina) in key soybean growing districts of Madhya Pradesh. Sixteen isolates of pathogen were characterized based on morpho-cultural and pathogenic variability by using cut stem inoculation techniques at J.N.K.V.V., Jabalpur. 

Result: Charcoal rot was prevalent in all surveyed sixteen districts of Madhya Pradesh. Out of six, Kymore plateau and Satpura hills (44.5%), Satpura plateau (42.5%), Central Narmada Valley (42.0%) and Vindhyan plateau agroclimatic zones (35.0%) were identified as favouable zones for charcoal rot. Malwa plateau (16.25%) and Northern hill region (24.5%) had low incidences of charcoal rot. Among varieties, JS 95-60, JS 93-05 and JS 20-29 were highly affected, whereas, JS 20-34, JS 20-98 and JS 20-69 were least affected. Incidence of charcoal rot was comparatively higher in the fields that had Maize-Chickpea (26.32%), Maize-Wheat, Soybean- Pea and Soybean - Chickpea cropping patterns in the previous year and lowest in Rice-Chickpea (12.00%) and Rice - Wheat (12.45%) cropping patterns. The incidence of charcoal rot was partially higher in the fields with light soil (21.3%) than in heavy soil (19.0%). Isolates investigation revealed that isolates from Jabalpur, Hoshangabad, Chhindwara and Sagar were fast-growing variables and highly aggressive in developing necrotic lesions on the cut stem of soybean. This investigation could be instrumental in forewarning sensitive areas of charcoal rot, varietal options and crop rotation to be followed to minimize the incidence of charcoal rot. Moreover, identified variable aggressive isolates could be utilized in genotype resistance screening programs.

INTRODUCTION

Soybean [Glycine max (L.) Merrill] is a seed legume cultivated as a leading oilseed crop worldwide. It is one of the richest vegetarian sources of proteins (36.1-42.8%) and edible oil (16.8-20.2%), along with several beneficial contents, including amino acids, unsaturated fatty acids, minerals (Ca and P), vitamins (e.g. A, B, C and D), antioxidants which make it one of the best food and feed for human and other animals (Kumar et al., 2020; Mehra et al., 2020; Banerjee et al., 2023). India is among the top fifth producers of soybean in the world. Nevertheless, it is simultaneously the largest soybean oil importer, accounting for about $5.6B (OEC, 2023). The central part of the country that includes Madhya Pradesh (45%), Maharashtra (38%) and Rajasthan (8%) are major soybean growing regions. The soybean productivity in India is far lower (about 0.9 tons) compared to other countries like USA, Brazil and Argentina (3.0 to 3.5 tons) (SOPA, 2023). In India, soybean is a Kharif season crop cultivated in rainfed conditions during which the crop succumbed to various abiotic and biotic stresses (Dupare et al., 2014; Amrate et al., 2021; Amrate et al., 2023a). In this concern, sustainable soybean production in the central part of the country has suffered due to the attack of many diseases such as yellow mosaic, charcoal rot, aerial blight, anthracnose, bacterial pustule, frog eye leaf spot etc (Amrate et al., 2020a; Amrate and Shrivastava, 2021; Rajput et al., 2021; Uikey et al., 2022; Amrate et al., 2023b).

In this, charcoal rot caused by a necrotrophic soil-borne fungus Macrophomina phaseolina (Tassi) Goid is a devastating disease of soybean responsible for significant yield reduction in the top eight soybean-producing nations (Wrather et al., 2010; Amrate et al., 2023c). It occurs yearly and affects most genotypes, varieties and advanced soybean lines under Madhya Pradesh agro conditions (Amrate et al., 2019; Amrate and Shrivastava, 2021; Amrate et al., 2023c). Sudden wilting of plants and greyish-black appearance of lower stems and roots are common symptoms of charcoal rot (Gupta et al., 2012; Amrate et al., 2020b; Sagarika et al., 2023). Macrophomina phaseolina has a wide host range (about 500), including field crops, vegetables, fruit, ornamental, medicinal and forest plants (Marquez et al., 2021; Amrate et al., 2023c). Charcoal rot is challenging to manage due to its complex pathogenesis and sudden onset of wilting symptoms (Sagarika et al., 2023; Singh et al., 2024). This particular pathogen can cause significant economic losses in crop plants. Recent reports from several parts of Madhya Pradesh indicated that soybean crops had been facing the problem of sudden wilting during reproductive stages and, thereby, significant yield loss in those fields. However, more information was needed on the extent of severity and distribution of charcoal rot and pathogens behaviour in the critical soybean-producing state of the country. Because of this, a comprehensive survey was conducted to record the prevalence and distribution of charcoal rot and possible factors associated with it in the state. Furthermore, the cultural and pathogenic nature of isolates belonging to surveyed regions was also determined. The study could be helpful for farmers and researchers in providing better varietal options and other preventive measures for minimizing charcoal rot incidence. The most pathogenic isolate could also be used in an artificial resistance screening programme for charcoal rot. 

MATERIALS AND METHODS

Survey locations and methodology 
 
A comprehensive disease survey was conducted to record the incidence and distribution of soybean charcoal rot at farmers’ fields in twenty-two blocks of sixteen districts representing six agro-climatic zones of Madhya Pradesh during kharif 2018 and 2019. A random survey was conducted at the reproductive stages of soybean (R5-R7), coinciding with the second fortnight of September. Roadside, easily approachable farmer’s fields were selected and 400 plants were observed at four randomly selected points from each field. Charcoal rot-affected plants were identified based on the typical symptoms of charcoal rot (Amrate et al., 2020b) (Fig 1) and the association of the pathogen was confirmed in the lab (Fig 2). The information on soybean varieties, soil types and the previous year’s cropping pattern of the same piece of land was also obtained by interacting with farmers. The diseased samples were collected and brought to the lab for further studies. After the survey, blocks, districts and variety wise per disease incidence of charcoal rot were calculated by using the formula given below:
 
To interpret the influence of cropping patterns on charcoal rot, fields with similar cropping patterns during the previous year were averaged for two years for charcoal rot incidence across the zones. Similarly, the fields were grouped mainly as heavy soil (dark to medium black) and light soil (Sandy and sandy loam soil) and the average incidence of charcoal rot on those fields was also computed.

Fig 1: A field of view of charcoal rot affected plants.



Fig 2: Cultural characteristic of M. phaseolina: ten days old culture (A), right angle branching of hyphae (B), presence of abundance microsclerotia (C) and close up view of round shaped microsclerotia (D), respectively.


 
Cultural and morphological variability among different isolates
 
The pathogenic fungus was isolated, purified and identified using standard techniques on potato dextrose medium (Marquez et al., 2021) (Fig 2). The isolates from districts were assigned a unique code name. The radial growth of isolates on PDA was measured four days after inoculation at 26±1°C. Isolates were classified as fast (>85 mm), medium (75-85 mm) and slow (<75 mm) based on the growth, respectively. The growth pattern and colour of the colony were recorded on the 7th and 10th day after inoculation, respectively. Five mm five mycelium mats of ten days old culture from all corners, including the centre, were suspended in 5 ml of sterile distilled water. After that, one drop of the suspension was examined under a stereo binocular microscope for microslcerotial shape and their numbers. The number of sclerotia per microscopic (10X) field was counted from five microscopic fields for three replications (three culture plates) for each isolate.
 
Testing of pathogenic variability by using cut stem inoculation technique
 
Eighteen days old seedlings of JS 20-29 were inoculated by the actively growing culture of isolates of M. phaseolina by using the cut stem inoculation technique (Twizeyimana et al., 2012; Amrate et al., 2019). Initially, plants were cut at 3.0 cm above the unifoliolate node and cut end, then inoculated by three days actively growing culture on PDA (Fig 3). For inoculation, the open end of the sterile micropipette tip (10 to 200 μl) was inserted into the medium. A circular disc of fungal mycelium was cut, picked up and immediately placed over the cut stem. After the 3rd, 6th, 9th and 12th days of inoculation, downward linear stem necrosis was measured. Four plants of each variety were inoculated for this purpose. The experiment was conducted under polyhouse conditions (temperature 30°C±3 and RH >75%). 

Fig 3: Cut stem inoculation technique: picking actively growing M. phaseolina culture (A), placing at cut end of stem (B), necrotic lesion in 2 days after inoculation (C) and Progression of lesion continued (D), respectively.


 
Calculation of Area under lesion progression curve (AULPC)
 
By using linear stem necrosis length at 3rd, 6th, 9th and 12th days, area under lesion progression curve (AULPC) was calculated as given by Shaner and Finney (1977).
 
AULPC = n-1∑i=1 [(yi + yi+1)/2][ti+1-ti]
 
Where,
yi= Necrotic lesion at ith observation.
ti= Time (days) at ith observation.
n= Number of observations.

RESULTS AND DISCUSSION

Incidence of charcoal rot across the zones 
 
The charcoal rot was found in all the major soybean growing areas of Madhya Pradesh (Table 1). In Kymore Plateau and Satpura hills agroclimatic zones, the incidence of charcoal rot ranged between 1.75-44.50 (in 2018) and 10.75-34.25% (in 2019), with the maximum average of 39.38% in JS 95-60 at Seoni block, Seoni. In Satpura plateau agroclimatic zone, it was distributed from 1.25-42.50 and 0.50-32.00% during 2018 and 2019, respectively. Variety JS 20-29 (34.50%) was highly affected at Mohkhed, Chhindwara. In Central Narmada Valley, it ranged between 0.75-42.0 and 0.50-32.25% during 2018 and 2019, respectively, with the highest average (37.13%) in JS 95-60 at Hoshangabad. In the Vindhyan plateau, charcoal rot incidence varied from 2.25-35.0 and 0.75-31.0% during 2018 and 2019, respectively, with the maximum average (30.75%) in JS 95-60 at Vidisha. In the case of the Malwa plateau, charcoal rot was very low and ranged from 4.5-10.5 and 1.5-16.25% during 2018 and 2019, respectively. The JS 20-98 fields were free from charcoal rot infection. In the Northern hill region, it was also comparatively low and ranged between 13.0-24.5 and 1.75-19.25% in 2018 and 2019, respectively. 

Table 1: Incidence of charcoal rot of soybean at different locations covering sixteen districts of six Agroclimatic zones of Madhya Pradesh during 2018 and 2019.



Zone-wise average incidence was higher in Satpura Plateau (19.07%), followed by Kymore Plateau and Satpura Hills (18.81%) and central Narmada Valley (15.60%). At the same time, it was lowest in the Malwa Plateau (5.94%), i.e. Rajgarh and Ujjain district. Incidence was higher in 2018 (16.48 %) than in 2019 (12.26%). Across the zones, JS 95-60 was found to be the most affected (27.76 %), followed JS 93-05 (25.38%) and JS 20-29 (23.96%). At the same time, JS 20-34 (0.77%), JS 20-98 (0.83%) and JS 20-69 (1.70%) were least affected by charcoal rot. Our results have been corroborated with the findings of some recent investigations. Mishra and Dantre (2017) indicated that charcoal rot (30-60%) have also been infecting soybean varieties to varying extent in different districts of Chhattisgarh. High severity of charcoal rot (up to 100 %) in most presently growing varieties and germplasm at the experimental area in Jabalpur has also indicated its prevalence in the state (Amrate et al., 2018; Amrate et al., 2019). Charcoal rot is severe under high temperatures and erratic rainfall during reproductive stages in Indian conditions (Wrather et al., 2010; Gupta et al., 2012). The high incidence of charcoal in 2018 might be attributed to low rainfall and dry spells in most of the region of Madhya Pradesh, whereas in 2019, the conditions were not favourable. 
 
Influence of cropping pattern and soil type
 
Through cropping pattern revealed that the incidence of charcoal rot was highest in the fields that had maize-chickpea (26.32%) cropping pattern in the previous year, followed by Maize-Wheat (23.75 %), Soybean - Pea (23.63%) and Soybean - Chickpea (18.87%) in the same land (Fig 4). The lowest average incidence of charcoal rot was recorded in the cropping pattern of rice-chickpea (12.00%) and Rice - Wheat (12.45%). The charcoal rot incidence was comparatively higher in the field with single/both crops (kharif and rabi) as hosts of charcoal rot pathogen. Maize and chickpea are the prominent host of M. phaseolina, which causes considerable losses in Indian conditions (Kaur et al., 2022; Bankoliya et al., 2022). Hence, it might be possible that these cropping patterns enhanced the pathogen load in soil, resulting in high disease. In contrast, a low incidence of charcoal rot in the Rice - Wheat system might reduce the microsclerotial of M. phaseolina, which could result in low infection in other hosts. Previous reports also indicate that crop rotation with non-host crops or less susceptible varieties have been influential in reducing inoculums of M. phaseolina  (Gupta et al., 2012). Besides this, charcoal rot was partially higher in the field with light soil (6.5 - 21.3%) than in heavy soil (6.6 - 19.0%) across the agroclimatic zones and years (Fig 5). However, some fields with heavy soil also had a higher incidence than light soil in the same zone. Therefore, it could not be concluded that soil types influenced the incidence of charcoal rot disease in soybean.

Fig 4: Influence of previous year cropping pattern on incidence of charcoal rot in soybean across the zones and years (2018 and 2019).



Fig 5: Influence of soil type on incidence of charcoal rot across the years (2018 and 2019).


 
Cultural and morphological characteristics of isolates
 
Mycelial growth among all isolates (16) was significantly varied from 76.33 (MP-13(SHD)) to 90.00 (MP-9(SGR)) mm (Table 2). Seven isolates i.e. MP-1(JBP), MP-2(NAR), MP-4(CWA), MP-6(HBD), MP-3(SEO), MP-9(SGR) and MP-14(SHR) were designated as Fast-Growing Isolates (FGI). Colony elevation patterns of most of the isolates were partially fluffy to fluffy (Fig 6). The colony colour of the isolates varied from dark black or black [MP-1(JBP), MP-3(SEO), MP-4(CWA), Mp-11(VDS) and Mp-13(SHD)] to greyish [Mp-5(BET) and Mp-10(RSN)] (Fig 6). Most of the isolates had oblong shape microsclerotia, except some had round. The number of sclerotia /microscopic fields (10x) varied significantly in most of the isolates and ranged from 41.07 [Mp-10(RSN)] to 77.20 [Mp-4(CWA)]. Four isolates, i.e. Mp-4(CWA), Mp-1(JBP), Mp-2(NAR) and Mp-14(SHR), had more than 70.0 sclerotia per microscopic field. Our findings revealed that isolates were variable concerning growth pattern, colony appearance and morphological traits, which are in agreement with the previous finding that also depicted variabilities in M. phaseolina isolated from different areas (Aghakhani and Dubey, 2009; Iqbal and Mukhtar, 2014; Gade et al., 2018).  

Table 2: Cultural, morphological and pathogenic variability in the isolates of M. phaseolina.



Fig 6: Variation in colony color and pattern of elevation of mycelium among M. phaseolina isolates (Mp - 1 to Mp - 16).


 
Pathogenic variability
 
Progression of downward necrotic lesion through cut stem inoculation of all isolates differed at 3, 6, 9 and 12 days after inoculation in the variety JS 20-29. The Jabalpur isolates Mp-1(JBP) was found to be highly aggressive as recorded high length necrotic lesion of 15.30 cm, followed by Hoshangabad Mp-6(HBD) and Sagar Mp-9(SGR) isolates (12.80 cm) at 12 days after inoculation (Table 2). The isolates from Damoh Mp-8(DMH), Raisen Mp-10(RSN) and Umaria Mp-12(UMR) were the least aggressive, with the most downward, about 3.00 mm lesion. Similar trends were also depicted in the area under the lesion progression curve (AULPC). Through this, it was concluded that isolates from Jabalpur and Hoshangabad were the most aggressive among all sixteen. Previous to this, significant difference in necrotic lesion development and relative area under the disease progress curve by isolates of M. phaseolina from soybean was well described by Twizeyimana et al. (2012). Varieties also differed in necrotic lesion development after cut stem inoculation by M. phaseolina (Amrate et al., 2019). 

CONCLUSION

It concluded that charcoal rot has been affecting soybean cultivation badly in most of the soybean growing districts of the state and could be one of the reasons for low yield. Varieties such as JS 95-60, JS 93-05 and JS 20-29 should be replaced with tolerant varieties in charcoal rot-sensitive zones. Continuous cultivation of Maize/Soybean - Chickpea may enhance M. phaseolina inoculum in soil and this may be avoided in charcoal rot prone districts. Variability was detected in isolates that could be utilized in further research programmes. 

ACKNOWLEDGEMENT

We are highly thankful to Head, Department of plant pathology and Head, Department of plant breeding and genetics for their valuable cooperation, support and facility.

CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.

REFERENCES


  1. Aghakhani, M. and Dubey, S.C. (2009). Determination of genetic diversity among Indian isolates of Rhizoctonia bataticola causing dry root rot of chickpea. Journal of Mycology and Plant Pathology. 96: 607-619.

  2. Amrate, P. K., Pancheshwar, D.K., Shrivastava, M.K. (2018). Evaluation of soybean germplasm against charcoal rot, aerial blight and yellow mosaic virus disease in Madhya Pradesh. Plant Disease Research. 33(2): 185-190. 

  3. Amrate, P.K., Shrivastava, M.K., Bhale, M.S. (2019). Resistance in soybean varieties against charcoal rot disease caused by Macrophomina phaseolina. Plant Disease Research. 34(2): 124-128. doi: 10.5958/2249-8788.2019.00021.0.

  4. Amrate, P.K., Shrivastava, M.K., Singh G. (2020a). Screening of genotypes to identify the resistance source against major diseases of soybean under high disease pressure conditions. International Journal of Current Microbiology and Applied Sciences. 9(5): 1739-1745. https://doi.org/ 10.20546/ijcmas.2020.905.195.

  5. Amrate, P.K., Shrivastava, M.K., Pancheshwar, D.K., Stuti, S. (2020b). Charcoal rot and yellow mosaic virus disease of soybean under hot spot condition: Symptoms, incidence and resistance characterization. International Journal of Bio-resource and Stress Management. 11(3): 268-273. doi: HTTPS://DOI.ORG/10.23910/1.2020.2104.

  6. Amrate, P.K. and Shrivastava, M.K. (2021). Yield response and pathological characterization of promising genotypes of soybean against major diseases in Madhya Pradesh. Journal of Oilseeds Research. 38(4): 380-384.

  7. Amrate, P.K., Shrivastava, M.K., Pancheshwar, D.K. (2021) Crop- weather based relation and severity prediction of Aerial blight incited by Rhizoctonia solani Kuhn in soybean. Journal of Agrometeorology. 23(1): 66-73.

  8. Amrate, P.K., Shrivastava, M.K., Borah, M., Routhu, G.K., Sharma, S., Nataraj, V., Pancheshwar, D.K., Singh, G. (2023a). Molecular characterization of soybean yellow mosaic virus isolates and identification of stable resistance sources in central India. Australasian Plant Pathology. 52: 165- 179. https://doi.org/10.1007/s13313-022-00902-8.

  9. Amrate, P.K., Shrivastava, M.K. and Singh, G. (2023b). Identification of sources of resistance and yield loss assessment for aerial blight and anthracnose/pod blight diseases in soybean. Legume Research. 46(11): 1534-1540. doi: 10.18805/LR-4452.

  10. Amrate, P.K., Shrivastava, M.K., Bhale, M.S., Agrawal, N., Kumawat, G., Shivakumar, M. Nataraj, V. (2023c). Identification and genetic diversity analysis of high-yielding charcoal rot resistant soybean genotypes. Scientific Reports. 13: 8905. https://doi.org/10.1038/s41598-023-35688-2.

  11. Banerjee, J., Shrivastava, M.K., Singh, Y. Amrate, P.K. (2023). Estimation of genetic divergence and proximate composition in advanced breeding lines of soybean [Glycine max (L.) Merrill]. Environment and Ecology. 41(3C): 1960-1968.  https://doi.org/10.60151/envec/VYWE5744.

  12. Bankoliya, M.K., Yadav, V.K., Khare, U.K., Amrate, P.K., Kumar, A., Sharma, R.C. (2022). Survey for dry root rot of chickpea caused by Rhizoctonia bataticolain different region of Madhya Pradesh, India. The Pharma Innovation Journal. 11(6): 100-103.

  13. Dupare, B.U, Billore, S.D., Sharma, A.N. and Joshi O.P. (2014). Contribution of area, productivity and their interaction towards changing oilseeds and soybean production scenario in India. Legume Research. 37(6): 635-640. doi: 10.5958/0976-0571.2014.00688.2. 

  14. Gade, R.M., Belkar, Y.K., Ingle, Y.V. (2018). Morphological and pathogenic variability among Rhizoctonia bataticola Isolates associated with soybean (Glycine max L.) from India. International Journal of Current Microbiology and Applied Sciences. 7(1): 2575-2588.

  15. Gupta, G.K., Sharma, S.K., Ramteke, R. (2012). Biology, epidemiology and management of the pathogenic fungus Macrophomina phaseolina (Tassi) goid with special reference to charcoal rot of soybean [Glycine max (L.) Merrill]. Journal of Phytopathology. 160: 167-180. HTTPS://DOI.ORG/ 10.23910/1.2022.2478.

  16. Iqbal, U. and Mukhtar, T. (2014). Morphological and pathogenic variability among macrophomina phaseolina isolates associated with mungbean (Vigna radiata L.) wilczek from Pakistan. The Scientific World Journal. 10: 1-9.

  17. Kaur, H., Ahmadi, K., Kumar, S.  (2022). Associations between charcoal rot disease and grain yield in different sowing dates in spring maize (Zea mays L.). Indian Phytopathology.  75: 741-747. https://doi.org/10.1007/s42360-022-00493-w.

  18. Kumar, S., Kumari, V., Kumar, V., (2020). Genetic variability and character association studies for seed yield and component  characters in soybean [Glycine max (L.) Merrill] under North-western Himalayas. Legume Research. 43(4): 507- 511. doi: 10.18805/LR-4006.

  19. Marquez, N., Giachero, M.L., Declerck, S., Ducasse, D.A. (2021). Macrophomina phaseolina: General characteristics of pathogenicity and methods of control. Frontiers of Plant Science. 12: 634397. doi: 10.3389/fpls.2021.634397.

  20. Mehra, S., Shrivastava, M.K., Amrate, P.K., Yadav, R.B. (2020). Studies on variability, correlation coefficient and path analysis for yield associated traits in soybean [Glycine max (L.) Merrill]. Journal of Oilseeds Research. 37(1): 56-59.

  21. Mishra, P.K. and Dantre, R.K. (2017). Survey to record the disease incidence of charcoal rot of soybean caused by Macrophomina phaseolina from Chhattisgarh. Trends in Biosciences. 10(15): 2780-2783.

  22. OEC, (2023). The observatory of economic complexity.https:// oec.world/en/profile/bilateral-product/soybean-oil/reporter/ ind.

  23. Rajput, L., Nataraj, V., Kumar, S., Amrate, P.K., Jahagirdar, S., Huilgol, S.N., Chakruno, P., Singh, A., Maranna, S., Ratnaparkhe, M. B., Borah, M., Singh, K. P., Gupta, S., Khandekar, N. (2021). WAASB index revealed stable resistance sources for soybean anthracnose in India. Journal of Agricultural Science. 159(9-10): 710-720. doi:10.1017/S0021859622000016.

  24. Sagarika, M., Amrate, P.K., Yadav, V.K., Shrivastava, M.K. (2023). Exploring potential of new generation fungicides as seed dresser in combating early infection of Macrophomina phaseolina in soybean. Indian Phytopathology. 76: 1045-1053. https://doi.org/10.1007/s42360-023-00680-3.

  25. Shaner, G. and Finney, R. (1977). The effect of nitrogen fertilization on the expression of slow mildewing resistance in knox wheat. Phytopathology. 67: 1051-1056. http://dx.doi. org/ 10.1094/Phyto-67-1051.

  26. Singh, M., Singh, J., Maurya, S., Kumar, S., Meena, A.K., Sharma, P. and Lakhran, L. (2024). Root rot disease incited by Macrophomina phaseolina in Arid legumes and their management: A review. Legume Research. 47(1): 1-7. doi: 10.18805/LR-4714.

  27. SOPA, (2023). The Soybean Processors Association of India (SOPA) report http://www.sopa.org/statistics/world- soybeanproduction/. 

  28. Twizeyimana, M., Hill, C.B., Pawlowski, M., Paul, C., Hartman, G.L. (2012). A cut-stem inoculation technique to evaluate soybean for resistance to Macrophomina phaseolina. Plant Disease. 96: 1210-1215.

  29. Uikey, S., Sharma, S., Amrate, P.K., Shrivastava, M.K. (2022). Identification of rich oil-protein and disease resistance genotypes in soybean [Glycine max (L.) Merrill]. International  Journal of Bio-resource and Stress Management. 13(5): 497-506. doi: HTTPS://DOI.ORG/10.23910/1.2022.2478.

  30. Wrather, A., Shannon, G., Balardin, R. (2010). Effect of diseases on soybean yield in the top eight producing countries in 2006. Plant Health Progress. 11:1. https://doi.org/10.1094/ PHP-2010-0102-01-RS.
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