Exploring genetic diversity coupled with multiple disease resistance in soybean

Introduction

Soybean (Glycine max (L.) Merrill) is the most valuable eco-friendly leguminous oilseed crop globally. The soybean seed is rich in protein (40 percent) and oil (20 percent). India is among the top five soybean producer nations where soybean is mainly grown under rainfed conditions, significantly affected by several biotic and abiotic stresses. Madhya Pradesh alone contributes more than fifty percent of the area and production of the country's soybean. The diversity present in the genotypes is an essential tool for crop improvement as diverse parents produce high heterotic effects (Tiwari et al. 1982; Mian and Bahl 1989, Burton and Brownie 2006) [14,11,6] . Genetic diversity can be revealed with different agro morphological traits and molecular markers (Kachare et al., 2020; Tiwari et al. 2019) [7,15] . Principal Component Analysis (PC) divides the total variance into several factors. Classification of genotypes according to agronomic characteristics made using multi-factor techniques can shorten the period and the cost of improving the yield. Presently, soybean diseases like charcoal rot (CR), Yellow Mosaic Virus (YMV), and Rhizoctonia aerial blight (RAB) are severely affecting the soybean crop with considerable yield losses in major soybean growing regions of India. RAB (Rhizoctonia solani) causes significant yield loss (Wrather et al., 2010) [17] under humid fields (Yang et al., 1990) [18] . It can be recognised by grey to reddish brown irregular water-soaked lesions coupled with web of mycelium (aerial hyphae) and small dark brown Sclerotia of fungus on affected trifoliate (Amrate et al., 2021) [4] . Charcoal rot (Macrophomina phaseolina) is very severe disease causes plant mortality and significant high yield reduction under dry field conditions (Luna et al. 2017; Wrather et al., 2010) [9,17] . It is usually affects soybean crops at reproductive stages and can be recognized by the greyish black appearance of lower stem and root tissue due to formation of numerous black microsclerotia of pathogenic fungus (Luna et al. 2017) [9] . Most Indian soybean varieties are entirely susceptible to charcoal rot disease and can cause as high as 92.6 % yield reduction (Amrate et al., 2019) [2] . Yellow mosaic is a begomovirus disease (Mungbean yellow mosaic India virus) transmitted by Bemisia tabaci (Usharani et al., 2004; Kumar et al., 2014) [16,8] . YMV disease is characterized with the presence of contrast yellow mottles on leaves and can cause heavy yield losses(>80.0 percent) in soybean upon severe infection at early stage of growth (Amrate et al., 2020) [3] . The present soybean varieties in India have a narrow genetic base. The deployment of multiple disease resistance under high yielding background is an effective strategy for enhancing soybean productivity and sustainability. Therefore, realizing the importance of the problem, an investigation was undertaken to assess genetic divergence for resistance for multiple diseases (YMV, CR and RAB) along with crucial traits in a panel of diverse soybean germplasm.

Materials and Methods

An experiment comprising one hundred sixty-five diverse soybean germplasm was carried out at the All India Coordinated Research Project on soybean, JN Agriculture University, Jabalpur, India (Latitude: 23º14 N, Longitude: 79º56 E, Altitude: 411.5 m) during Kharif 2019. The experiment was laid down in augmented plot design in 4 m rows with 50 cm row to row and 6-8 cm plant to plant distance. Five released varieties (JS 20-34, JS 335, JS 20-98, JS 95-60 and NRC 86) were used as check. The present experimental location is designated as a hotspot for charcoal rot (CR), Yellow mosaic virus (YMV) and Rhizoctonia aerial blight (RAB) diseases by the AICRP on Soybean. Genetic divergence analysis was undertaken for eleven significant yield attributing traits of soybean. The observations were recorded for days to flower initiation, days to maturity, plant height (cm), number of primary branches/plant, number of nodes/plant, number of pods/plant, number of seeds/pod, seed yield/plant (g), 100 seeds weight (g), biological yield per plant (g) and harvest index (%) from five randomly selected healthy plants from each genotype and the principal component analysis was worked out.

Diseases scoring and resistant reaction

Each genotype was critically observed for appearance, incidence and severity of diseases throughout the cropping season, and final reactions were given based on the highest disease severity. Disease/resistance reaction was assigned to each genotype for RAB, CR and YMV based on percent disease index (PDI), percentage mortality and Coefficient of infection, respectively (Table 1) (Amrate et al., 2018) [1] .

Results and discussion

Genetic divergence

As some genotypes were ultimately killed due to complex and high disease pressure, only 100 genotypes were included in the genetic divergence analysis of eleven traits. PCA provides a roadmap for reducing complex data set to a lower dimension to sometimes hidden, simplified structures that often underlies it. In the present investigation, out of twelve, only six principal components (PCs) exhibited more than 0.5 Eigenvalue (Table 2) and showed about 87.78% variability among the traits studied. The first principal component recorded the highest variation (40.380 %). Semi curve line obtained after the sixth PC with slight variation observed in each PC indicated that maximum variation was found in the first PC; therefore, selection for characters under the first PC may be desirable. The dispersion of genotypes in biplot indicated the presence of fair amount of genetic diversity (Figure 1). The genotypes closer to each other had little or no differences with respect to seed yield. Therefore, based on the homogeneity existing in the groups, it was possible to make a second selection focusing on seed yield. [12] reported three principal components in his investigation. Smith et al. (1995) [13] conducted average linkage cluster and principal component analysis and reported the utility of these results in preserving and utilising germplasm. Broschat (1979) [5] considered PCA as a powerful technique for data reduction which removes interrelationships among components.

Resistance to YMV, RAB and CR disease

The severe symptoms of YMV, RAB and CR appeared during the second fortnight of July, August and September, respectively (Figure 3, A-D). Incidence and severity of CR and RAB were wildly higher than YMV disease in all the genotypes. The screening result also revealed that different genotypes were reacted differently for all three diseases (Table 4). Out of one hundred sixty-five, only eleven were found to be highly resistant to RAB, forty-eight for CR and ninety-three genotypes were highly resistant for YMV disease, respectively. Others genotypes have shown moderate resistance to susceptible reactions for all three diseases. Ten genotypes were found to be highly resistant against charcoal rot plus aerial blight, fifteen for charcoal rot plus YMV and four for aerial blight plus YMV. Only four genotypes, namely UPSL 152, DCB 137, JSM 232, EC 350664, were identified as high resistance to all three diseases (Table 5). Different levels of disease resistance in soybean genotypes were also reported by Mengistu et al.

(2013) [10] against charcoal rot using root and stem severity index and identified four genotypes with higher resistance levels. Kumar et al. (2014) [8] identified resistant and susceptible genotypes for YMV under field conditions. In contrast, Amrate et al. (2018) [1] identified seventeen genotypes with higher-level resistance to charcoal rot, aerial blight and YMV under Madhya Pradesh conditions.

Conclusion

The principal components analysis detected the vast genetic diversity among the studied genotypes for seed yield. These results indicate an excellent opportunity to improve soybean yield through wide hybridization by crossing genotypes in the farthest clusters. Field screening for multiple disease resistance revealed that the genotypes UPSL 152, DCB 137, JSM 232, EC 350664 were highly resistant against biotic stresses and, thus, can be further utilized as superior parents/donors in future breeding programmes. The diverse genotypes coupled with multiple disease resistance may be helpful in further varietal improvement.

Acknowledgement

AcknowledgementAuthors are thankful to the ICAR-IISR, Indore for providing the valuable germplasm.

References

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