Legume Research

  • Chief EditorJ. S. Sandhu

  • Print ISSN 0250-5371

  • Online ISSN 0976-0571

  • NAAS Rating 6.59

  • SJR .349 (2022) Q2

  • Impact Factor .669 (2022)

Frequency :
Monthly (January, February, March, April, May, June, July, August, September, October, November and December)
Indexing Services :
BIOSIS Preview, ISI Citation Index, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus

​Physiological and Biochemical Characters of Blackgram as Influenced by Liquid Rhizobium with Organic Biostimulants

R. Ajaykumar1,*, K. Harishankar2, P. Chandrasekaran3, P. Kumaresan4, K. Sivasabari5, P. Rajeshkumar6, S. Kumaresan7
1Vanavarayar Institute of Agriculture, Pollachi-642 103, Tamil Nadu, India.
2S. Thangapazham Agricultural College, Tenkasi-627 758, Tamil Nadu, India
3SRM College of Agricultural Sciences, Chengalpattu-603 201, Tamil Nadu, India.
4Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India.
5Department of Soil Science and Agricultural Chemistry, Amrita School of Agricultural Sciences, Coimbatore-642 109, Tamil Nadu, India.
6Department of Plant Pathology, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India.
7Department of Horticulture, Amrita School of Agricultural Sciences, Coimbatore-642 109, Tamil Nadu, India.
  • Submitted18-07-2022|

  • Accepted12-09-2022|

  • First Online 29-09-2022|

  • doi 10.18805/LR-5012

Cite article:- Ajaykumar R., Harishankar K., Chandrasekaran P., Kumaresan P., Sivasabari K., Rajeshkumar P., Kumaresan S. (2023). ​Physiological and Biochemical Characters of Blackgram as Influenced by Liquid Rhizobium with Organic Biostimulants . Legume Research. 46(2): 160-165. doi: 10.18805/LR-5012.
Background: The productivity of blackgram is not adequate to meet the domestic demand of the growing Indian population. Consequently, there is an urgent need for enhancement of productivity through proper management practices. With this background, a research experiment was conducted to investigate the effect of liquid rhizobium with organic bio-stimulants on physiological and biochemical characters, antioxidant enzymes and yield of blackgram.

Methods: A field experiment was laid out in randomized block design with three replications during 2021 (Kharif and Rabi) season. The treatments include 100% recommended dose of NPK along with foliar application of dasagavya, liquid rhizobium, fish amino acid, panchagavya, pink pigmented facultative methylotrophs (PPFM) and Sea weed extract with different concentration (1% and 3%, respectively) in addition to control. Organic bio stimulants were sprayed at 30 and 45 days after the sowing of blackgram.

Result: The experiment results revealed that the application of 100% RDF+Liquid Rhizobium @ 1% registered maximum physiological and biochemical characters viz., CGR, total chlorophyll content, soluble protein content, nitrate reductase activity, catalase activity, peroxidase activity and number of root nodules plant-1, yield attributes viz., number of pods plant-1, number of seeds pod-1, grain yield (kg ha-1), haulm yield (kg ha-1). Correlation and Regression analysis also indicated that the yield attributes had a positive impact on the grain yield. 
Pulses are important crops in India because of its low cost and high quality protein. They play a major role in providing a balanced protein component in the diet of the people. Among pulses, blackgram [Vigna mungo (L.) Hepper], occupies a unique place for its use as vegetable and it is grown both as a pure and mixed crop along with maize, cotton, sorghum and other millets (Ajaykumar et al., 2022).

The yield of blackgram is low due to various reasons includes poor management practices, various physiological, biochemical as well as inherent factors associated with the crop. Organic  substances are known to influence a wide array of physiological parameters like alteration of plant architecture, assimilate partitioning, promotion of photosynthesis, uptake of nutrients (mineral ions), enhancing nitrogen metabolism, promotion of flowering, uniform pod formation, increased mobilization of assimilates to defined sinks, improved seed quality, induction of synchrony in flowering and delayed senescence of leaves (Pradeep and Elamathy, 2007).

Role of foliar applied panchagavya and dhasagavya in production of many plantation crops had been well documented in India (Selvaraj, 2003). The use of fermented, liquid organic fertilizers, effective microorganisms (EM) as foliar fertilizers have been introduced to modern agriculture in recent years to produce food with good quality and safety (Galindo et al., 2007).

Fish amino acid (FAA) is a liquid and great value to both plants and microorganisms in their growth, because it contains and abundant amount of nutrients and various types of amino acids (will constitute a source of nitrogen (N) for plants). Seaweed concentrates are beneficial effects on plants as they contain growth promoting hormones (IAA, IBA and Cytokinins) and different trace elements, vitamins and amino acids (Khan et al., 2009). In green gram, foliar application of liquid bio fertilizers during vegetative and flower bud initiation stages increased the number of flowers, pods and seeds per plant and seed yield. Foliar application of organic substance increased the chlorophyll content and promoted epicotyls elongation of soybean, mungbean and pea (Senthil et al., 2003).

Exogenous application of PPFM (Methylobacterium species are a group of bacteria known as pink-pigmented facultative methylotrophs) produces some benefit in alleviating the adverse effects of drought stress and also improves germination, growth, development, quality and yield of crop plants (Hayat et al., 2010).

Based on the available background knowledge, the present investigation was carried out to develop suitable nutrient management technology involving liquid rhizobium and organic bio stimulants to enhance the productivity of irrigated black gram.
A field experiment was conducted during the year of 2021 (kharif and rabi season) in a Vanavarayar Institute of Agriculture, Pollachi. The experiment was laid out in randomized block design with seven treatments and three replications. The treatments were T1 - 100% RDF along with foliar application of dhasagavya at 3 %, T2 - 100% RDF along with foliar application of liquid rhizobium at 1%. T3- 100% RDF along with foliar application of Fish amino acid at 1%, T4 - 100% RDF along with foliar application of Panchagavya at 3%, T5 - 100% RDF along with foliar application of PPFM at 1%, T6- 100% RDF along with foliar application of Sea weed extract at 3%, T7 - control. Liquid bio fertilizers and organic bio stimulants were purchased from Tamil Nadu Agricultural University, Coimbatore. Blackgram variety VBN 8 was used for the study.
        The recommended doses of N, P2O5, K2O were 25, 50, 25 kg ha-1, respectively. Full dose of nitrogen, phosphorus, potassium in the form of urea, SSP, MOP were applied basal as per treatments. Liquid bio fertilizers and organic bio stimulants were given as foliar spray at 30 and 45 days after sowing of blackgram. All other agronomic practices were adopted as per the need of the crop.
        The physiological biochemical characters viz., crop growth rate, chlorophyll content and soluble protein were estimated. The CGR was computed using the formula suggested by Watson (1958). Chlorophyll content of leaves was recorded as described by Yoshida et al., (1976). Soluble protein content of the leaf was estimated at by using folinciocalteau reagent by adopting the procedure described by Lowry et al., (1950). Nitrate reductase activity (NRase activity) (Nicholas et al., 1976), Catalase activity (Gopalachari, 1963), Peroxidase activity (Gurumurthy et al., 2019) were also estimated. Yield attributes viz., number of pods plant-1, number of seeds pod-1, grain and haulm yield were recorded during harvest stage. The data on the different parameters was analyzed statistically by adopting Fisher’s method of ANOVA suggested by Gomez and Gomez (1984).
Quantitative variables analysis
Correlation and multiple linear regressions were employed to study the value of money or profitability, the relationship between the various parameters (variables) and grain yield. The Pearson Correlation Coefficient (PCC) is the most prevalent sort of correlation coefficient and it creates a relationship between expected and observed values after a statistical investigation. In this article, the correlation was employed to identify the relations among grain yield (kg ha-1), Crop growth rate (g. m-2 day-1), Total chlorophyll content (mg g-1), Soluble protein content (mg g-1), Nitrate Reductase activity (μg NO2 g-1 h-1), number of pods plant-1 and number of seeds pod-1 (Ajaykumar et al., 2022). It was computed using the equation:

Rxy = Coefficient of the linear relationship between the variables x and y;
Sx and Sy= Sample standard deviation.
Sxy = Sample covariance.
xi and yi = Values of x and y variables in the sample of the population.
xand yi = Sample mean.

Another econometric tool used in this study was regression which examines the relationship between a dependent variable and a collection of independent variables (Pillai et al., 2010). Regression was estimated by:

Yi = Dependent variable (grain yield).
Xi =  Independent variables grain yield (kg ha-1), crop growth rate (g. m-2 day-1), total chlorophyll content (mg g-1), soluble protein content (mg g-1), nitrate reductase activity (μg NO2 g-1 h-1), number of pods plant-1 and number of seeds pod-1).
β =  Slope coefficient of the respective independent variable.
α =  Constant or intercept term.
ui =  The error term.

This formal model of regression equation could be rewritten as,
Grain yield (kg ha-1) = α+ β1 crop growth rate (g. m-2 day-1) +β2 total chlorophyll content (mg g-1) + β3 soluble protein content (mg g-1) + β4 nitrate reductase activity (μg NOg-1 h-1) +β5 number of pods plant-1 + β6 number of seeds pod-1+ ui.
Physiological and biochemical characters

Liquid bio fertilizer and organic bio stimulants influenced the crop growth rate, total chlorophyll content and soluble protein content during vegetative and flowering stages. Maximum crop growth rate was registered at 1% liquid rhizobium (4.75 and 6.33 g.m-2 day-1) at 60 DAS. Which was followed by 3% panchagavya and 3% seaweed extract. Liquid bio fertilizer are excellent source of  macro and micro nutrients, trace elements, amino acid, Plant growth promoting hormones, vitamins, antibiotics, carbohydrates, proteins and other organic matters exhibits plant growth stimulating property under diluted condition (Moshe et al., 2015) which increased the crop growth. Total chlorophyll content was significantly improved with 1% liquid rhizobium application with value of 3.02 mg g-1 (vegetative stage) and 3.60 mg g-1 (flowering stage). Furthermore, it was followed by foliar application of 3% panchagavya (Fig 1). The increased chlorophyll content in PGPR sprayed plants may be due to the fact that nitrogen is a constituent of chlorophyll molecule (Teotia et al., 2000).

Fig 1: Effect of liquid rhizobium and organic bio stimulants on total chlorophyll content and soluble protein content (mg g-1) in irrigated blackgram (pooled data).

Soluble protein content of the leaf, being a measure of RuBP carboxylase activity, was considered as an index for photosynthetic efficiency. Rubisco enzyme forms nearly 80 per cent of the soluble protein in leaves of many plants (Joseph et al., 1981). In the present study, higher soluble protein content (12.51 mg g-1 at vegetative stage and 12.74 mg g-1 at flowering stage) was observed under application 100% RDF + 1% liquid rhizobium followed by foliar spray of 3% panchagavya. 100% RDF + sea weed extract 3% noticed higher soluble protein content with value 12.34 mg g-1 and 12.52 mg g-1 (vegetative stage and flowering stage) over than rest of the treatments (Fig 1). The positive effect of liquid bio fertilizers on soluble protein content might be due to its involvement in the expression and activation of genes responsible for synthesis of rubisco and rubiscoactivate (Xia et al., 2009), thereby increasing the capacity of CO2 assimilation in the Calvin cycle. The rubisco content per unit leaf area was positively correlated with that of soluble protein content of the leaf (Balachandar et al., 2003).

Antioxidant enzymes

Antioxidant enzymes activities are significantly influenced by application of liquid rhizobium and organic bio stimulants. The data on antioxidant enzymes are presented Table 1. Nitrate reductase (NR) is an important enzyme for nitrogen assimilation and is a key point of metabolic regulation in crop plants. Thus, NRase is intimately associated with the plant growth and development (Sinha and Nicholas, 1981). Peroxidases, one of the key antioxidant enzymes, are widely distributed in nature and catalyze oxidation of various electron donor substrates concomitant with the decomposition of H2O2. Catalase was a main enzyme to eliminate H2O2 in the mitochondrion and microbody (Shigeoka et al., 2002). The reduction trend of H2O2 content revealed that, gradual increase of catalase enzyme activity during vegetative and flowering stage of the investigation. In the present study, high NRase activity, POD and catalase enzymes activity were observed with application of 1% liquid rhizobium and it was followed by 3% panchagavya. The absolute control recorded the minimum catalase activity and control recorded the maximum value (16.87 and 17.91 μg of H2O2 g-1 min-1). Catalases also played an important role in the fine regulation of reactive oxygen speciesin the cell through activation and deactivation of several apoplastic enzymes might also generate reactive oxygen species under normal conditions (Sairam et al., 1996).

Table 1: Effect of liquid rhizobium and organic bio stimulants on antioxidant enzymes of irrigated blackgram (Pooled data).

Effect on nodulation

Number of completely developed nodules in all the treatments was calculated manually. 100% RDF along with foliar application of 1% liquid rhizobium noticed significantly increased number of nodules plant-1 (22.67 and 23.05) during kharif and rabi. This was followed by 100% RDF + 3% panchagavya (Fig 2). Being, a leguminous crop, blackgram fulfills major part of nitrogen requirement by symbiotic nitrogen fixation with the help of bacterium called Rhizobia. Rhizobium involve in symbiotic biological nitrogen fixation; survival in soil, Rhizosphere colonization, infection and nodule development and energy transformation during Nitrogen fixation in root nodules (O’ Hara​ et al., 1988). Symbiotic nitrogen fixation is well known process exclusively driven by bacterial nitrogenase enzyme which specifically reduces atmospheric nitrogen to ammonia in the symbiotic root nodules (Leigh, 2002).

Fig 2: Effect of liquid rhizobium and organic bio stimulants on crop growth rate (g m-2 day-1) and no. of nodules/plant in irrigated blackgram (pooled data).

Yield attributes and yield

A perusal of data revealed that yield attributes and the yield increased significantly with the foliar application of Liquid rhizobium and organic bio stimulants in blackgram over control (Table 2). 100% RDF along with foliar application of 1% liquid rhizobium noticed significantly increased number of pods plant-1 (37.5 and 37.7), number of  seeds pod-1  (9.0 and 9.2), grain yield (1004 and 1063 kg ha-1 during kharif and rabi, respectively) and haulm yield (1936 and 2108 kg ha-1) and which was followed by 100% RDF + 3% panchagavya. This was due to the enhanced root and shoot development, solar radiation interception and nutrients uptake. Further, the translocation and accumulation of photosynthates in the economic sinks resulted in increased yield attributes and biological yield of blackgram.

Table 2: Effect of liquid rhizobium and organic bio stimulants on yield attributes and yield of irrigated blackgram.

In addition to that, the effect of 3% Seaweed extract was on par with 3% dhasagavya. The least grain and haulm yield was observed in control plot. The overall effect of rhizobium in increasing the grain yield of this crop was primarily due to the enhanced availability of nutrients, through nitrogen fixation by bacteria production of plant growth promoting (PGP) substances and vitamins, especially B12 produced in the rhizosphere soils (Vardhini and Rao, 1998).

Correlation and regression analysis

The correlation results revealed that all the variables included in the model were positively significant at a one percent level of significance (Table 3). The correlation coefficients of the grain yield with crop growth rate (0.93), total chlorophyll content (0.94), soluble protein content (0.79), nitrate reductase activity (0.52), number of pods plant-1 (0.89) and number of seeds pod-1 (0.29) showed that all the attributes were positively related and that strongly proves when there is an increment in these variables, there would be an increase in the yield of the black gram. The multiple linear regressions were estimated to measure the relationship and the change in magnitude of the grain yield due to the other prescribed parameters (Table 4). The multiple linear regression equation could be written as,
Grain yield = -174.97 + 7.46 crop growth rate (gm-2 day-1) + 1.91 otal chlorophyll content (mg g-1) + 0.63 soluble protein content (mg g-1) + 3.11 nitrate reductase activity (ug NO2 g-1 h-1) + 1.51 number of pods plant-1 + 1.02 number of seeds pod-1. 

The R2 (0.77) depicts a good model fit, implying that the independent variables caused 77 per cent of the grain yield. All the variables except nitrate reductase activity and number of seeds pod-1 were found statistically significant (Table 4). The slope coefficient of the crop growth rate has shown that when there is one per cent increase incrop growth rate, there would be a significant increase in the grain yield by 7.46 per cent, other variables being held constant. Likewise, when there is a one per cent increase in the variables viz., total chlorophyll index, soluble protein content and number of pods plant-1, there would an increase in the yield by 1.91, 0.63 and 1.51 per cent, respectively. There is strong econometric evidence that the crop growth rate, total chlorophyl content and number of pods plant-1 significantly impact the grain yield of blackgram.

Table 3: Correlation between physio-biochemical parameters and yield attributes (Pooled data).

Table 4: Multiple linear regression estimates the blackgram yield.

Both the seasons of experiments concluded that the application of 100% RDF along with foliar spraying of 1% liquid rhizobium significantly increased physiological and biochemical characters and yield compared to all other treatments. Subsequently, it was followed by the application of 100% RDF along with 3% panchagavya. The correlation and regression results showed that all the parameters had a positive relation on the grain yield and thus variables should be focused to enhance the productivity of the blackgram.

  1. Ajaykumar, R., Selvakumar, S., Harishankar, K. and Sivasabari, K. (2022). Effect of pink-pigmented facultative methylotrophs,  PGRs and nutrients on growth, yield and economics of irrigated blackgram [Vigna mungo (L.) Hepper]. Legume Research. 1(6): 52-57.

  2. Ajaykumar, R., Prabakaran, P. and Sivasabari, K. (2022). Growth and yield performance of black gram [Vigna mungo (L.) Hepper] under malabar neem (Melia dubia) plantations in western zone of Tamil Nadu. Legume Research. 1(8): 182-188.

  3. Balachandar, D., Nagarajan, P., Gunasekaran, S. (2003). Effect of organic amendments and micronutrients on nodulation and yield of blackgram in acid soil. Legume Research. 26: 192-195.

  4. Galindo, A., Jeronimo, C., Spaans, E. and Weil, M. (2007). An introduction to modern agriculture. Tierra Tropica. 13(1): 91- 96.

  5. Gopalachari, N.C. (1963). Changes in the activities of certain oxidizing enzymes during germination and seedling development of Phaseolus mungo and sorghum. India Journal of Experimental Biology. 1: 98-100.

  6. Gomez, K.A. and Gomez, A.A. (1984). Statistical Procedures for Agricultural Research. John Wiley and Sons.

  7. Gurumurthy, S., Sarkar, B., Vanaja, M., Lakshmi, J., Yadav, S.K. and Maheswari, M. (2019). Morpho-physiological and biochemical changes in black gram [Vigna mungo (L.) Hepper] genotypes under drought stress at flowering stage. Acta Physiologiae Plantarum. 41(3): 1-14.

  8. Hayat, Q., Hayat, S. Irfan, M. and Ahmad, A. (2010). Effect of exogenous salicylic acid under changing environment: A review. Environmental and Experimental Botany. 68: 14-25.

  9. Joseph, M.C., Randall, D.D. and Nelson, C.J. (1981). Photosynthesis and RUBP-case of polyploidy tall fescue. Plant Physiology.  68: 894-898.

  10. Khan, W., Rayirath, U.P., Subramanian, S., Jithesh, M.N., Rayorath, P., Hodges, D.M. (2009). Seaweed extracts as biostimulants of plant growth and development. Journal of Plant Growth Regulator. 28: 386-399. 

  11. Leigh, G.J. (2002). Nitrogen Fixation at the Millennium. Elsevier Science, London.

  12. Lowry, O.H., Rosebrough, N.J. Farr, A.L. Randall, R.J. (1950). Protein measurement with the folin phenol reagent. Journal of Biological Chemistry. 193: 265-275.

  13. Madhaiyan, M., Poonguzhali, S., Senthilkumar, M., Sundaram, S., Heekyung, C., Jinchul, Y., Subbiah, S. and Tongmin, S.A. (2004). Growth promotion and induction of systemic resistance in rice cultivar Co-47 (Oryza sativa L.) by Methylobacterium spp. Botanical Bulletin of Academia Sinica. 45: 315-324.

  14. Moshé, S.L., Perucca, E., Ryvlin, P. and Tomson, T. (2015). Epilepsy: New advances. The Lancet. 385(9971): 884-898.

  15. Nicholas, J.C., Harper, J.S. and Hageman, R.H. (1976). Nitrate reductase activity in soybean. Effect of light and temperature. Plant Physiology. 58: 731-735.

  16. O’ Hara, G.W., Bookerd, N. and Dilworth, M.J. (1988). Mineral constraints to nitrogen fixation. Plant and Soil. 198: 93- 110. 

  17. Pillai, M.A., Anandhi, K. and Selvi, B. (2010). Stability analysis of yield in blackgram. Legume Research. 33(2): 152-153.

  18. Pradeep, M.D.S and Elamathi, S. (2007). Effect of foliar application of DAP and micronutrients and NAA in mungbean. Legume Research. 30: 305-307.

  19. Sairam, R.K., Shukla, D.S. and Deshmukh, P.S. (1996). Effect of homo-brassinolide seed treatment on germination, amylase activity and yield of wheat under moisture stress condition. Indian Journal of Plant Physiology. 1(3): 141- 144.

  20. Selvaraj, N. (2003). Report on Organic Farming at Horticulture Research Station, Tamil Nadu Agricultural University, Ooty. 2003-04. pp. 2-5.

  21. Senthil, A., Pathmanaban, G. and Srinivasan, P.S. (2003). Effect of bioregulator of some physiological and biochemical parameters of soybean (G. max L.). Legume Research. 28: 54-56.

  22. Shigeoka, S., Ishikawa, T., Tamoi, M., Miyagawa, Y., Takeda, T., Yabuta, Y. and Yoshimura, K. (2002). Regulation and function of ascorbate peroxidase isoenzymes. Journal of Experimental Botany. 53: 1305-1319.

  23. Sinha, S.K. and Nicholas, D.J.D. (1981). Nitrate reductase. The Physiology and Biochemistry of Drought Resistance in Plants. 145-169.

  24. Teotia, U.S., Mehta, V.S., Srivastava, P.C. (2000). Phosphorus- sulphur interaction in moongbean [Vigna radiate (L.) Wilczek]: I. Yield, phosphorus and Sulphur contents. Legume Research. 23: 106-109.

  25. Vardhini, B.V. and Rao, S.R. (1998). Effect of 28-Homobrassinolide on growth, metabolite content and yield of groundnut (Arachis hypogea L.). Indian Journal of Plant Physiology. 3: 58-66. 

  26. Watson, D.J. (1958). The dependence of crop growth rate on plant dry weight. Annals of Botany. 23: 37-54.

  27. Xia, X.J., Huang, L.F., Zhou, Y.H., Mao, W.H., Shi, K., Wu, J.X., Asami, T., Chen, Z.  and Yu, J.Q. (2009). Brassinosteroids promote photosynthesis and growth by enhancing activation  of Rubisco and expression of photosynthetic genes in Cucumis sativus. Planta. 230: 1185-1196.

  28. Yoshida, S., Forno, D.A., Cock, J.H. and Gomez, K.A. (1976). Laboratory Manual for Physiological Studies of Rice. International Rice Research Institute, Philippines.

Editorial Board

View all (0)