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Impacts of Bioinoculants Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 on Chickpea (Cicer arietinum L.) Yield and Soil Nitrogen Status
Pedosphere 29(3): 388–399, 2019 doi:10.1016/S1002-0160(19)60807-6 ISSN 1002-0160/CN 32-1315/P c 2019 Soil Science Society of China ⃝ Published by Elsevier B.V. and Science Press
Impacts of Bioinoculants Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 on Chickpea (Cicer arietinum L.) Yield and Soil Nitrogen Status Divya JOSHI1 , Ramesh CHANDRA2 , Deep Chandra SUYAL1 , Saurabh KUMAR1 and Reeta GOEL1,∗ 1 Department
of Microbiology, College of Basic Sciences and Humanities, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar-263145, Uttarakhand (India) 2 Department of Soil Science, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar263145, Uttarakhand (India) (Received November 12, 2018; revised April 2, 2019)
ABSTRACT Cold-adapted bioinoculants are considered as harbingers of sustainable hill agriculture. Therefore, two previously characterized psychrotolerant diazotrophs, Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107, were evaluated for their plant growthpromoting potential for chickpea (Cicer arietinum L.) grown under natural field conditions. Comparative analysis of agronomical and biochemical crop parameters revealed the irrelevance of chemical fertilizers for chickpea production; the diazotrophs alone were sufficient to fulfil the crop’s nutritional requirement. However, the integrated use of bacterial strains in combination with urea at 20 kg N ha−1 as urea was being recommended for higher crop yield and better soil nitrogen status. Quantitative polymerase chain reaction (qPCR) and denaturing gradient gel electrophoresis (DGGE)-based soil bacterial dynamics unveiled the persistence of both diazotrophs until the end of the crop maturation period without affecting the native micro-flora. Therefore, these bioinoculants can be explored as natural nitrogen resource, and an additional incentive in their bio-formulation will be a step towards agricultural sustainability. Key Words: agricultural sustainability, denaturing gradient gel electrophoresis (DGGE), hill agriculture, psychrotolerance, N fertilizer, N fixation, N uptake, quantitative polymerase chain reaction (qPCR) Citation: Joshi D, Chandra R, Suyal D C, Kumar S, Goel R. 2019. Impacts of bioinoculants Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 on chickpea (Cicer arietinum L.) yield and soil nitrogen status. Pedosphere. 29(3): 388–399.
INTRODUCTION Himalayan agro-ecosystems are facing continuous pressures from anthropogenic activities, habitat degradation, fragmentation and/or conversion, pollution, and climate change. Consequently, microbial niches are under risk of extinction, as indicated by declining species richness and population sizes in different agro-climatic zones of the Himalaya (Stres et al., 2013; Joshi et al., 2017). Agriculture is thought to be a difficult task in such traditionally maintained agricultural lands where production of crops suffers from various climate- and nutrient-related drawbacks, especially nitrogen (N) deficiency. With a focus on organic alternatives, chemical fertilizers are not recommended for healthy food production. Hence, the application of bioinoculants mainly comprising cold-adapted diazotrophs would be a long-standing alternative for sustainable agriculture practices. ∗ Corresponding
author. E-mail: rg55@rediffmail.com.
Chickpea is widely grown in the northern parts of India (Bimbraw, 2016). Initially, it was confined to only the Himalayan foothills as it required cold temperature and a prolonged winter season. However, due to the scarcity of available N in the Himalayan soils and the emergence of new, warm adapted varieties, there has been a significant shift in the chickpea-growing area from northern India (cold environment) to central and southern India (warm environment) (Pathak et al., 2017). The availability of N is very crucial for the growth and development of chickpea. Moreover, it is also considered as a limiting factor for optimum grain yield in this crop. Although, synthetic N fertilizers are an easy and effective source of crop nourishment, their unintended use has brought ruins to our doors. In this perspective, microorganisms could play an important role in managing soil nutrient status, plant productivity, and adaptation, the key elements of sustainability in traditional agro-ecosystems.
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
Our previous studies have unraveled the immense microbial diversity of the Himalayan regions (Latha et al., 2009; Soni and Goel, 2010; Suyal et al., 2015a, b). Moreover, the proteomes of four Himalayan cold-dapted diazotrophs, viz., Pseudomonas migulae S10724, P. palleroniana N26, Dyadobacter psychrophilus B2, and P. jesenii MP1 have also been analyzed and documented (Suyal et al., 2014, 2017; Soni et al., 2015). Preliminary pot trial studies from the author group revealed that the Himalayan psychrotrophic diazotrophs P. jesenii MP1 and Rhodococcus qingshengii S10107 were significantly effective in promoting chickpea crop growth (Kumar et al., 2014). However, successful implementation and adoption of the bioinoculants needs proper investigation across environments. Therefore, in this study, the aim of this study was to evaluate both these diazotroph strains for their plant growth promoting efficacy in the chickpea crop under natural field condition. MATERIALS AND METHODS Bacterial strains and growth condition Psychrotolerant diazotrophs R. qingshengii S10107 (JX173283) and P. jesenii MP1 (JX310329) were originally isolated from the crop field of Munsyari, India (30.07◦ N, 80.23◦ E; 2 200 m above the sea level) (Table I). Both were grown aerobically in Burk medium (Soni et al., 2015) at 28 ◦ C. Both strains were able to grow on N-deficient medium at 10 ◦ C, and the nifH gene was amplified as described previously (Suyal et al., 2014, 2017). Amplification of nifH with degenerate primers yielded a single band of the expected size of approximately 360 bp (Poly et al., 2001). Experimental site, soil, and field experiment A field experiment was conducted during the winter season from November 2016 to April 2017 at Norman E. Borlogue Crop Research Centre (NEBCRC) of Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. The experimental site lies in the Terai plains, about 30 km south of the foothills of the “Shivalik” range of the Himalayas (29◦ N, 79◦ 29′ E; 243.8 m above the mean sea
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level). It is characterized by a humid and subtropical climate with summer being hot and dry, and winter being cold, with fog. Summer is extremely hot, with the maximum temperature exceeding even 42 ◦ C (May and June), whereas the minimum temperature sometimes reaches 0 ◦ C during winter (December–January). The relative humidity recorded was the highest in July– August and the lowest in April–May. Moderate rainfall often occurs during the winter months. The rainfall distribution, relative humidity, and thermal regimes during the cropping season, recorded at the meteorological observatory at NEBCRC of the University, are given in Fig. 1. During the experimental period, a total of 11.2 mm of rainfall occurred during December 2016. The maximum rainfall was recorded during the month of January. The experimental soil was classified under the subgroup Aquic Hapludoll in the order Mollisols (Deshpande et al., 1971). The soil belongs to the textural class sandy loam (sand 58.4%, silt 25.2%, clay 16.4%), with pH 6.9 and electrical conductivity 0.24 dS m−1 (in a soil:water ratio of 1:2.5, weight:volume), soil organic carbon 6.7 g kg−1 , available N (alkaline KMnO4 -extractable N) 180.2 kg ha−1 (Subbiah and Asija, 1956), NaHCO3 -extractable P 20.1 kg ha−1 (Olson et al., 1954) and ammonium acetate-extractable K 261.4 kg ha−1 (Jackson, 1973). The experiment was laid out in randomized block design: 4 treatments inoculated with P. jesenii MP1 or R. qingshengii S10107, i.e., alone (treatments MP1A and S10A) and in combination with 20 kg N ha−1 (treatments MP1N and S10N), and the remaining 2 treatments, one applied with 20 kg N ha−1 alone (NA) and an uninoculated control with no N. There were four replications of each treatment and the plot size was 7.2 m2 . Seed bacterization and sowing Seeds of chickpea (Cicer arietinum L. var. PG-186) were surface sterilized by soaking in 0.1% HgCl2 for 2 min and then thoroughly washed with autoclaved distilled water. After this, 0.1% carboxy methyl cellulose was added to the overnight grown cultures (optical density at 600 nm = 0.6). The seeds were soaked in cu-
TABLE I Characterization of the bacterial strains used in this study Strain name
NCBIa) accession No.
Isolation site
Latitude, longitude
Elevation
Climate
Pseudomonas jesenii MP1 Rhodococcus qingshengii S10107
JX310329 JX173283
Munsyari Munsyari
30.07◦ N, 80.23◦ E 30.07◦ N, 80.23◦ E
m 2 200 2 200
Temperate Temperate
a) National
center for Biotechnology Information.
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Fig. 1 Weekly weather conditions at the experimental site during the crop-growing season (from November 2016 to April 2017). Min. = minnum; max. = maxnum; R. = relative.
lture medium for 10 min, dried at room temperature and finally sown in tractor-opened furrows 30 cm apart in a field under natural conditions. Nitrogen was applied, as per treatments, in the form of urea at the time of sowing. A dose of 40 kg P2 O5 ha−1 from single super phosphate and 20 kg K2 O ha−1 from muriate of potash was given uniformly in all the treatments as basal applications. The crop was grown and protected from diseases and pests as per the recommended agronomic practices (Singh et al., 2003). Bioinoculants were inoculated by seed bacterization at 1.9 × 108 ± 1.1 × 102 colony forming units seed−1 at the time of sowing. Soil and plant sampling and analysis Five plants from each plot were taken for the study of agronomical parameters, such as root length, shoot length, fresh and dry weight of plant, nodule number, and fresh as well as dry weight of nodules. Plants were removed from side rows along with a soil block of about 25 cm diameter at 45, 60, and 75 days after sowing (DAS). The soil adhered to the roots was carefully washed off with tap water; the nodules were removed from the roots, counted, and their fresh and dry weights were recorded after drying in a hot air oven to a constant weight at 65 ◦ C. The root and shoot length and fresh weight of the uprooted plants were also recorded at each time interval. The dry weight of the plants at each interval was recorded by drying in a hot air oven to a constant weight at 65 ◦ C. Biochemical parameters, such as chlorophyll content and nitrate reductase activity of the plants, were estimated using standard protocols by Hiscox and Israelstam (1979) and Hageman and Hicklesley (1971), respectively. The grain and straw yields were recorded after harvesting the crop and expressed in kg ha−1 and there-
after, used in calculating the harvest index. The N content of plants at different time intervals, and in grain and straw, was estimated as described by Page et al. (1982), and N uptake by plants, grain, and straw was computed by multiplying with plant dry weight, grain, and straw yield, respectively (A.O.A.C., 1970). Soil samples (0–15 cm) from each plot were collected before and after sowing at time intervals of 45, 60, and 75 DAS and at the time of harvesting, and available N in soil was estimated using the alkaline permanganate method described by Subbiah and Asija (1956), in which the four replicates were pooled and analyzed. The soil N content following the treatments was compared with that at the initiation of the study to exclusively study soil health. Dynamics of 16S rRNA and nifH genes were analyzed in all soil samples using iCycleriQTM Multicolor (Bio-Rad Lab, Hercules, USA) real-time quantitative polymerase chain reaction (qPCR) and PCR-DGGE (Dcode system; Bio-Rad Lab, Hercules, USA) techniques as per our previous study (Kumar et al., 2014). Statistical analysis The statistical analysis of the above-mentioned parameters was carried out using analysis of variance (ANOVA), using a general linear model procedure (SPSS, ver. 16.0) to test the significance of the effects of different treatments. Duncan’s multiple range test was applied to determine significant differences between treatments at P < 0.05 level. RESULTS Plant agronomical parameters Fresh and dry weights. Both the bioinoculants, alone (MP1A and S10A) or in combination with che-
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
mical fertilizer N (MP1N and S10N), resulted in significantly higher plant fresh and dry weights compared to the control. Treatments MP1A and MP1N resulted in significantly higher plant fresh and dry weights than the control and other treatments at 45, 60, and 75 DAS. Although both these treatments were statistically comparable, treatment MP1N resulted in an increase of 7.7%, 2.70%, and 3.8% in fresh weight, when compared with MP1A at 45, 60, and 75 DAS, respectively. Similarly, in terms of fresh and dry weights, treatments S10A and S10N were statistically at par. The latter treatment resulted in 8.6%, 3.6%, and 1.5% higher plant fresh weights than treatment S10A at 45, 60, and 75 DAS, respectively. Both these treatments were also comparable with treatment NA for fresh and dry weights (Fig. 2). The dry weight of the plants in treatment MP1N was significantly higher than that of the uninoculated control at all sampling intervals. At 45 and 65 DAS, treatment MP1N resulted in significantly higher plant dry weights than treatments S10A and NA and uninoculated control, and was statistically comparable to S10N and MP1A. Similarly, treatment MP1N resulted in significantly higher plant dry weights than all
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the other treatments at 75 DAS and was at par with treatment MP1A in this regard (Fig. 2). Shoot and root length. The shoot length of chickpea plants was the highest in treatment MP1N at all crop ages. It was significantly higher than that in the uninoculated control, but was similar to those in treatments S10A, S10N, and MP1A up to 65 DAS. At 75 DAS, treatment S10A was at par with all the other treatments, whereas treatment S10N resulted in significantly higher shoot lengths than the uninoculated control. Treatment MP1N showed the highest increase, of 35.8%, in shoot length at 75 DAS, when compared with the uninoculated control (Fig. 2). Similarly, the root length recorded in treatment MP1N was numerically higher than those of all the other treatments and significantly higher than that of the uninoculated control at all crop growth stages. Treatments S10A, S10N, and MP1A also resulted in significantly higher root lengths than the uninoculated control at different time intervals (Fig. 2). Nodule number, fresh weight, and dry weight. Nodule number and fresh and dry weights numerically increased with crop stage in all treatments. Both the bioinoculants, alone and in combination with N fertili-
Fig. 2 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on agronomical parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments at a specific time interval. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A= MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
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zer, induced significantly higher nodule numbers and fresh and dry weights than the uninoculated control at all intervals (Fig. 3). The highest nodule number was recorded in treatment MP1A, followed by MP1N, S10A, and S10N. Treatment MP1A was significantly better than the uninoculated control and at par with all the other treatments for nodule number at 45 DAS. At 65 DAS, treatment MP1A resulted in a significantly higher nodule number than treatments of uninoculated control, S10N and NA, but was at par with MP1N as well as S10A. This bioinoculant at 75 DAS also resulted in a significantly higher nodule number than treatment NA and the uninoculated control. Nodule fresh weight was the highest in treatment MP1A at all sampling intervals. This treatment was better than all other treatments for increasing nodule fresh weight at 45 DAS (547.75 mg plant−1 ). However, at 65 and 75 DAS, treatment MP1A was statistically comparable to MP1N, S10A, and S10N and was significantly better than the uninoculated control and NA for increasing nodule fresh weight. Inoculation of MP1 and S10107 alone and with N (MP1A, MP1N, S10A, and S10N), which were statistically comparable in increasing nodule dry weight, resulted in significantly higher nodule dry weights than
the uninoculated control at 45 DAS. At 65 DAS, all these treatments with bioinoculant resulted in significantly higher nodule dry weights than treatment NA and the uninoculated control; however, they were at par among themselves. Treatment MP1A also resulted in a significantly higher nodule dry weight than all the other treatments, except MP1N at 75 DAS. Treatment S10A was at par with S10N, NA and MP1N for nodule dry weight at this time interval. Plant biochemical parameters Chlorophyll content and nitrate reductase activity. Both the bioinoculants, alone and with 20 kg N −1 ha , resulted in significantly higher chlorophyll contents in the leaves than the uninoculated control at all crop growth stages. The leaf chlorophyll content recorded was the highest in treatment MP1N at all sampling intervals. This treatment resulted in significantly more chlorophyll in the leaves than the uninoculated control, NA and S10A treatments, whereas it was statistically comparable to S10N and MP1A at 45 DAS. Also at 65 DAS, leaf chlorophyll content was significantly higher in treatment MP1N than all the other treatments. Treatment S10N was at par with MP1A and S10A in terms of leaf chlorophyll content. All the
Fig. 3 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on nodule parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments at a specific time interval. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
treatments resulted in a significant higher chlorophyll content in the leaves than the uninoculated control and were at par among themselves at 75 DAS (Fig. 4). The nitrate reductase (NR) activity in chickpea was the highest in treatment MP1A at all sampling intervals. Treatment MP1A was significantly better than the uninoculated control and at par with all the other treatments for NR activity at 45 DAS. Treatments NA, S10A, and S10N were found to be statistically comparable to the uninoculated control for NR activity at this time interval. Also at 65 DAS, MP1A resulted in significantly higher NR activity than the uninoculated control, although it was at par with all the other treatments. However, at 75 DAS, it was statistically comparable to MP1N, S10A, and S10N and better than other treatments, with respect to NR activity (Fig. 4). N uptake. Nitrogen uptake by plants at different time intervals, seeds, and straw was the highest in treatment MP1N. Both the bioinoculants, alone and in combination with 20 kg N ha−1 , resulted in significantly more N accumulation in the pant, seeds, and straw than the uninoculated control (Fig. 5). Treatment MP1N was found to be significantly better than the uninoculated control and treatment NA for N uptake by plants at 45 DAS; it was at par with S10A, S10N and MP1A at this crop stage, in terms of N uptake. Also at 65 DAS, treatment MP1N resulted in significantly more N uptake by plants than the treatments of uninoculated control, NA, and S10A, but was statistically comparable to treatments S10N and MP1A. At 75 DAS, treatment MP1N was statistically comparable to S10A, S10N, and MP1A for plant N accumulation. However, it resulted in a significant increase, of 138.4% and 78.5%, in N uptake by plants, when
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compared with the uninoculated control and NA, respectively. Treatment MP1N also proved better for N uptake by seeds and straw after crop harvesting. This treatment was statistically comparable with S10N and MP1A, and significantly better than the uninoculated control, NA, and S10A for N uptake by seeds. Treatment MP1N also resulted in the highest N accumulation in straw (38.21 kg ha−1 ), followed by MP1A, S10N, S10A, and NA. This treatment was significantly better than the uninoculated control and was at par with NA, S10A, S10N and MP1A for straw N accumulation. Yield and harvest index. Grain and straw yields of chickpea and the harvest index were the highest in treatment MP1N, followed by MP1A, S10N, S10A, NA, and the uninoculated control (Fig. 6). Treatment MP1N resulted in a significantly higher grain yield, by 46.2%, and straw yield, by 27.0%, than the uninoculated control. It also resulted in a significantly higher grain yield than treatment NA and was at par with S10A, S10N, and MP1A. Similarly, it was statistically comparable to treatments MP1A, S10A, S10N, and NA for straw yield. The different treatments did not differ significantly in terms of harvest index. Soil biochemical properties Available N in soil. Different inoculation treatments resulted in remarkable increases in available N in the soil after harvesting, when compared with soil N levels before sowing (180.2 kg ha−1 ). Treatment MP1N resulted in the highest available N in soil after harvesting, with an increase of 235.6 kg ha−1 above the initial soil N level. This was followed by treatments MP1A,
Fig. 4 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on biochemical parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for a specific time interval at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 ; FW = fresh weight.
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Fig. 5 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on the accumulation of N in plants at different time intervals, seeds, and straw of chickpea (Cicer arietinum L. var. PG-186). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for a specific plant growth or agronomical parameter at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 ; DAS = days after sowing.
Fig. 6 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on grain and straw yields at the time of harvesting chickpea (Cicer arietinum L. var. PG-186). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for grain or straw yield at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
S10N, S10A, and NA and the uninoculated control.
These treatments resulted in 189.4, 150.9, 143.2, 120.1, and 104.7 kg ha−1 more available N in soil than the initially value (pre-sowing soil), respectively. Treatment MP1N resulted in significantly more available N in soil than S10N, S10A, and NA, and was statistically comparable to MP1A in terms of available N (Fig. 7). 16S rRNA and nifH gene abundances in the soil. Total bacterial (16S rRNA) and diazotrophic (nifH) abundances were calculated for all the experimental samples (Table II) and were expressed in copy numbers. The gradual increase in 16S rRNA abundance was observed until 75 DAS, with the highest in treatment MP1A, followed by S10107. After the last sampling, the total bacterial gene abundance was: MP1A > MP1N > S10A > S10N > NA > uninoculated control. The soil in treatment MP1A had the maximum abundance of 16S rDNA (4.63 × 1011 copies g−1 soil), which was much higher than that of the pre-sowing soil (8.67 × 108 copies g−1 soil). Similarly, nifH abundance ranged from 1.26 × 102 (pre-sowing) to 7.29 × 106 (MP1A) copies g−1 soil at 75 DAS. The quantification reveals the comparative effects of the treatments with respect to the soil before
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
Fig. 7 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on available N content in soil. Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
sowing. The treatment with only MP1 and S10107 (MP1A and S10A) had respective abundances of 7.29 × 106 and 4.45 × 105 copies g−1 soil in the last sampling, whereas, in combination with 20 kg N ha−1 (MP1N and S10N), the nifH abundance was 5.93 × 105 and 2.18 × 104 copies g−1 soil, respectively. However, in the treatment with only urea (NA), the nifH abundance declined from 3.61 × 102 to 1.56 × 102 copies g−1 soil. Soil bacterial and diazotrophic community structures. Rhizospheric bacterial and diazotrophic community structures of each experimental sample were compared using 16S rDNA and nifH amplified genes, respectively. The DGGE patterns revealed the persistence of MP1 and S10107 throughout the experiment. In fact, the band pattern at 45 DAS depicted that MP1 was more dominant than S10107 during the cropping period. The intensity of the bands was prevalent until 60 DAS, and later decreased until 75 DAS. Six prominent bands were visible at 60 DAS, a few of which were persistent until 75 DAS (Fig. 8). This suggested an increase in soil microflora as an added effect of the bacterial inoculation in the field. Furthermore, the soil nifH diversity revealed a similar band pattern with prominent and intense bands at 45 and 75 DAS. The bands corresponding to the strain MP1 were abundant and intense at 45 and 75 DAS, whereas the bands corresponding to S10107 persisted but with less intensity (Fig. 9). This is in direct correlation with their respective copy numbers in soil, as discussed earlier.
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Fig. 8 Denaturing gradient gel electrophoresis (DGGE) image depicting the bacterial diversity (16S rRNA) in the soil under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS). Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . a = MP1 genomic DNA; b = S10107 genomic DNA; c = pre-sowing soil.
Fig. 9 Denaturing gradient gel electrophoresis (DGGE) image depicting the soil diazotrophic (nifH) diversity under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS). Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . a = MP1 genomic DNA; b = S10107 genomic DNA; c = pre-sowing soil.
DISCUSSION Plant growth and agronomical parameters are influenced by a variety of biotic and abiotic factors. This study revealed that the strain MP1, in combination with the chemical fertilizer, helped the plant growth under field conditions. This is due to the fact that N from symbiotic N2 fixation is not always adequate to maximize growth and yield in legumes. For instance, low soil temperature at the time of planting can limit soil microbial activity, and, therefore, potentially de-
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TABLE II Comparative 16S rDNA and nifH gene abundances in the soil under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS), as revealed by quantitative polymerase chain reaction (qPCR) analysis Treat- 45 DAS menta) 16S rDNA × × × × × ×
× × × × × ×
103 103 103 103 103 102
copies g−1 soil 108 ± 2.50 × 103 1.21 × 102 ± 1.67 × 108 ± 1.09 × 103 1.11 × 102 ± 1.45 × 1010 ± 1.28 × 103 4.13 × 105 ± 2.09 × 109 ± 2.11 × 103 1.32 × 104 ± 2.57 × 1010 ± 1.33 × 103 3.28 × 106 ± 1.22 × 109 ± 1.27 × 103 5.31 × 105 ± 1.33 ×
103 103 103 103 103 103
Control NA S10A S10N MP1A MP1N
3.40 1.10 1.80 2.80 4.19 2.27
Treatment
60 DAS 16S rDNA × × × × × ×
Control NA S10A S10N MP1A MP1N
1.47 4.50 3.57 4.03 7.17 5.50
Treatment
75 DAS 16S rDNA
Control NA S10A S10N MP1A MP1N
1.27 1.51 1.59 2.69 4.63 2.96
× × × × × ×
nifH
copies g−1 soil 109 ± 2.51 × 103b) 1.97 × 1010 ± 1.20 × 103 3.61 × 1010 ± 2.23 × 103 2.07 × 109 ± 1.54 × 103 2.72 × 1011 ± 1.69 × 103 3.74 × 1010 ± 2.15 × 103 3.15 ×
copies 109 ± 1.50 × 103 109 ± 1.02 × 103 1011 ± 1.36 × 103 1010 ± 1.31 × 103 1011 ± 1.31 × 103 1010 ± 1.21× 103
102 102 105 104 106 105
± ± ± ± ± ±
2.35 1.59 1.22 1.11 1.89 1.24
nifH
nifH g−1
soil 2.12 × 1.56 × 4.45 × 2.18 × 7.29 × 5.93 ×
103 102 105 104 106 105
± ± ± ± ± ±
1.29 1.33 2.11 1.09 2.13 1.55
× × × × × ×
103 103 103 103 103 103
= no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . b) Mean ± standard error (n = 3). a) Control
lay N fixation and possibly the vegetative growth at the early stage (Gai et al., 2017). The stimulation of plant growth using the combination of bioinoculants and a lower concentration of chemical fertilizers has also been reported earlier (Maheshwari et al., 2010; Shashidhar et al., 2018). However, in terms of nodule parameters, viz., nodule number, fresh weight, and dry weight, individual applications of bacterial strains were observed to be better than the combinations and control used. This can be explained by the fact that a high concentration of soil N inhibits the production of nodules in legumes, reduces nodule mass, and N2 fixing activity, along with increasing senescence of the existing ones (Saito et al., 2014). However, an initial starter dose of mineral fertilizer helps in nodule initiation as well as acting as a N source until the biologi-
cal N fixation begins (Gai et al., 2017). Therefore, the fertilizer dose must be optimized before the cropping season to gain maximum output. Growth and development of chickpea tends to be slow in acidic and saline soils as the rate of nutrient uptake is negatively affected (Atieno et al., 2017; Burns et al., 2017; McCauley et al., 2017), which can be seen in the treatment with only 20 kg N ha−1 (urea). However, it can be successfully alleviated by the application of bioinoculants (Ilangumaran and Smith, 2017). Furthermore, urea, being an ammonia-based fertilizer, shows much less of an inhibitory effect on biological N fixation than nitrates, as it is readily metabolized to ammonium with the help of the urease enzyme, which is less harmful for diazotrophs. High chlorophyll content is beneficial in achieving high photosynthetic rates at low light intensities, which ultimately result in a healthy plant and higher yield (Shukla et al., 2015; Gu et al., 2017), whereas NR activity acts as a biochemical marker for predicting yield and protein concentration (Wang et al., 2017). In addition, N is a constituent of chlorophyll, photosynthetic enzymes (including Rubisco, PEPc, and PPDK), and thylakoid membranes. These cellular features are located in chloroplasts. The increased chlorophyll content with N addition indicates that more N is allocated to the light-harvesting complex (Mu et al., 2017). Plants cannot completely depend on biological N2 fixation and for optimum yield, it is necessary to use both biological N2 fixation and N uptake by roots from soil. Even in legumes, N fertilizer dose is based on the plant’s N needs during early plant development prior to nodule formation, and is crucial to growth and development (Gai et al., 2017). The chlorophyll and N content was higher in treatment MP1N, whereas the NR activity was the highest in treatment MP1A. These results suggest the integrated use of chemical and biofertilizers for better plant health and nutrient uptake. In nutshell, simultaneous use of biofertilizers and an optimum dose of mineral fertilizers can improve nutrient use efficiency of plants (Kakraliya et al., 2017). The crop yield was also higher in the combination treatments. In conclusion, the maximum grain yield of 2 698 kg ha−1 and harvesting index of 55.63% were observed for treatment MP1N. The high N content in soil is an indicator of good soil health, which in turn results in healthy plants. The integrated use of biofertilizers and mineral fertilizers results in higher residual soil N than does their individual application (Mukhongo et al., 2017). In addition, the higher N level after harvesting might be caused by rhizodeposition due to high leaf fall in chickpea. Treat-
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
ment MP1N resulted in the highest plant growth, and thus, had a high nutrient status. The fallen leaves act as excellent source of carbon and N after mineralization. To summarize, the bioinoculants had a positive effect on soil health by increasing N in the soil, which is not only beneficial for the standing crop, but also on any subsequent crop grown in that field. The 16S rRNA and nifH gene abundance in soil did not reveal vast differences among the treatments; however, both were increased significantly after treatment with bioinoculants. Thus, the bioinoculants have not affected soil microbial communities but boosted the soil micro-biota. Only MP1 or S10107 performed better than when applied in combination. The dose of chemical fertilizers in fields must be regulated as it showed consistent effects on the richness, diversity, and composition of soil bacterial communities. Though a basal dose of fertilizers will help in the establishment of the bacterial genera (Tang et al., 2017), prolonged use of chemical N in soil may decrease soil pH and bacterial 16S rRNA copy number while increasing soil N and crop yield (Zhou et al., 2015; Wang et al., 2017). The DGGE analysis for 16S rRNA revealed some bands observed exclusively at 60 DAS, a few of which persisted till the last sampling. Whereas, for nifH, some bands were prominent at 45 DAS, reduced on the second sampling (60 DAS), and again increased at 75 DAS. The bands corresponding to MP1 were more intense and persistent than those corresponding to S10107, which might be due to the rapid adaptability and metabolic versatility of this particular genus, as revealed by its plant growth-promoting activities including P solubilization (Tomer et al., 2017), N fixation, siderophore production, IAA production, etc. (Suyal et al., 2014; Uzair et al., 2018). The increased band numbers could be correlated with the change in nutrient content of the soil, which enriched new species. However, these data cannot reveal the complete or accurate diversity of soil microbes, as two bacterial genera with the same guanine plus cytosine (GC) content cannot be resolved by DGGE (Tabit, 2016). Furthermore, this also explains the existence of multiple bands in all the treatments, indicating the presence of some other bacterial strains with nearly same GC content as the bioinoculants (Kumar et al., 2014). On the contrary, the nifH diversity in soil is greatly influenced by the presence of chemical fertilizers. A similar study was conducted by Liao et al. (2018) on free living diazotrophs in rice fields and reported that the long-term use of chemical NPK fertilizers led to decreased nifH community diversity in soil, whereas the combination of chemical fertilizers with chicken ma-
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nure (organic manure) significantly improved the activity of diazotrophic communities. This suggests that adopting an integrated approach is more beneficial than reliance on a single factor for ensuring soil fertility, health, and a better crop yield (Bhardwaj et al., 2014; Bageshwar et al., 2017). In addition to this, environmental factors such as temperature, pH, soil texture, moisture content, organic matter, and humic acid play a decisive role in shaping the soil microbiota (Kumar et al., 2014; Zhou et al., 2017). Our study clearly indicated that the integrated use of bioinoculants and chemical fertilizer (MP1N and S10N) performed better in increasing crop yield and improving soil health. CONCLUSIONS In conclusion, the rhizosphere provides a peculiar environment where a huge variety of positive, negative, and neutral interactions between roots and microorganisms occur. Such interactions can significantly influence plant growth as well as the microbial activities. The present study demonstrated that application of bacterial strains in combination with 20 kg N ha−1 were better than the at par with application of the strains alone as well as their respective controls in terms of promoting plant growth and improving soil health. The chemical fertilizers, when supplied in appropriate amounts, can be beneficial not only for the plants and soil, but also for indigenous microbial diversity. ACKNOWLEDGEMENT The author (Dr. Deep Chandra SUYAL) acknowledges support from the Science and Engineering Research Board (SERB) young scientist scheme (No. YSS/2015/001214). Also, Senior Research Fellowship (Council of Scientific and Industrial Research Award No. 09/171(0126)/2015-EMR-I) to Mr. Saurabh Kumar is duly acknowledged. REFERENCES Association of Official Agricultural Chemistry (A.O.A.C.) 1970. Official Methods of Analysis. 11th Edn. Washington, D.C. Atieno J, Li Y L, Langridge P, Dowling K, Brien C, Berger B, Varshney R K, Sutton T. 2017. Exploring genetic variation for salinity tolerance in chickpea using image-based phenotyping. Sci Rep. 7: 1300. Bageshwar U K, Srivastava M, Pardha-Saradhi P, Paul S, Gothandapani S, Jaat R S, Shankar P, Yadav R, Biswas D R, Kumar P A, Padaria J C, Mandal P K, Annapurna K, Das H K. 2017. An environment friendly engineered Azotobacter can replace substantial amount of urea fertilizer and yet sustain same wheat yield. Appl Environ Microbiol. 83: e00590-17. Bhardwaj D, Ansari M W, Sahoo R K, Tuteja N. 2014. Biofertilizers function as key player in sustainable agriculture by
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Impacts of Bioinoculants Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 on Chickpea (Cicer arietinum L.) Yield and Soil Nitrogen Status Divya JOSHI1 , Ramesh CHANDRA2 , Deep Chandra SUYAL1 , Saurabh KUMAR1 and Reeta GOEL1,∗ 1 Department
of Microbiology, College of Basic Sciences and Humanities, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar-263145, Uttarakhand (India) 2 Department of Soil Science, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar263145, Uttarakhand (India) (Received November 12, 2018; revised April 2, 2019)
ABSTRACT Cold-adapted bioinoculants are considered as harbingers of sustainable hill agriculture. Therefore, two previously characterized psychrotolerant diazotrophs, Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107, were evaluated for their plant growthpromoting potential for chickpea (Cicer arietinum L.) grown under natural field conditions. Comparative analysis of agronomical and biochemical crop parameters revealed the irrelevance of chemical fertilizers for chickpea production; the diazotrophs alone were sufficient to fulfil the crop’s nutritional requirement. However, the integrated use of bacterial strains in combination with urea at 20 kg N ha−1 as urea was being recommended for higher crop yield and better soil nitrogen status. Quantitative polymerase chain reaction (qPCR) and denaturing gradient gel electrophoresis (DGGE)-based soil bacterial dynamics unveiled the persistence of both diazotrophs until the end of the crop maturation period without affecting the native micro-flora. Therefore, these bioinoculants can be explored as natural nitrogen resource, and an additional incentive in their bio-formulation will be a step towards agricultural sustainability. Key Words: agricultural sustainability, denaturing gradient gel electrophoresis (DGGE), hill agriculture, psychrotolerance, N fertilizer, N fixation, N uptake, quantitative polymerase chain reaction (qPCR) Citation: Joshi D, Chandra R, Suyal D C, Kumar S, Goel R. 2019. Impacts of bioinoculants Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 on chickpea (Cicer arietinum L.) yield and soil nitrogen status. Pedosphere. 29(3): 388–399.
INTRODUCTION Himalayan agro-ecosystems are facing continuous pressures from anthropogenic activities, habitat degradation, fragmentation and/or conversion, pollution, and climate change. Consequently, microbial niches are under risk of extinction, as indicated by declining species richness and population sizes in different agro-climatic zones of the Himalaya (Stres et al., 2013; Joshi et al., 2017). Agriculture is thought to be a difficult task in such traditionally maintained agricultural lands where production of crops suffers from various climate- and nutrient-related drawbacks, especially nitrogen (N) deficiency. With a focus on organic alternatives, chemical fertilizers are not recommended for healthy food production. Hence, the application of bioinoculants mainly comprising cold-adapted diazotrophs would be a long-standing alternative for sustainable agriculture practices. ∗ Corresponding
author. E-mail: rg55@rediffmail.com.
Chickpea is widely grown in the northern parts of India (Bimbraw, 2016). Initially, it was confined to only the Himalayan foothills as it required cold temperature and a prolonged winter season. However, due to the scarcity of available N in the Himalayan soils and the emergence of new, warm adapted varieties, there has been a significant shift in the chickpea-growing area from northern India (cold environment) to central and southern India (warm environment) (Pathak et al., 2017). The availability of N is very crucial for the growth and development of chickpea. Moreover, it is also considered as a limiting factor for optimum grain yield in this crop. Although, synthetic N fertilizers are an easy and effective source of crop nourishment, their unintended use has brought ruins to our doors. In this perspective, microorganisms could play an important role in managing soil nutrient status, plant productivity, and adaptation, the key elements of sustainability in traditional agro-ecosystems.
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Our previous studies have unraveled the immense microbial diversity of the Himalayan regions (Latha et al., 2009; Soni and Goel, 2010; Suyal et al., 2015a, b). Moreover, the proteomes of four Himalayan cold-dapted diazotrophs, viz., Pseudomonas migulae S10724, P. palleroniana N26, Dyadobacter psychrophilus B2, and P. jesenii MP1 have also been analyzed and documented (Suyal et al., 2014, 2017; Soni et al., 2015). Preliminary pot trial studies from the author group revealed that the Himalayan psychrotrophic diazotrophs P. jesenii MP1 and Rhodococcus qingshengii S10107 were significantly effective in promoting chickpea crop growth (Kumar et al., 2014). However, successful implementation and adoption of the bioinoculants needs proper investigation across environments. Therefore, in this study, the aim of this study was to evaluate both these diazotroph strains for their plant growth promoting efficacy in the chickpea crop under natural field condition. MATERIALS AND METHODS Bacterial strains and growth condition Psychrotolerant diazotrophs R. qingshengii S10107 (JX173283) and P. jesenii MP1 (JX310329) were originally isolated from the crop field of Munsyari, India (30.07◦ N, 80.23◦ E; 2 200 m above the sea level) (Table I). Both were grown aerobically in Burk medium (Soni et al., 2015) at 28 ◦ C. Both strains were able to grow on N-deficient medium at 10 ◦ C, and the nifH gene was amplified as described previously (Suyal et al., 2014, 2017). Amplification of nifH with degenerate primers yielded a single band of the expected size of approximately 360 bp (Poly et al., 2001). Experimental site, soil, and field experiment A field experiment was conducted during the winter season from November 2016 to April 2017 at Norman E. Borlogue Crop Research Centre (NEBCRC) of Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. The experimental site lies in the Terai plains, about 30 km south of the foothills of the “Shivalik” range of the Himalayas (29◦ N, 79◦ 29′ E; 243.8 m above the mean sea
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level). It is characterized by a humid and subtropical climate with summer being hot and dry, and winter being cold, with fog. Summer is extremely hot, with the maximum temperature exceeding even 42 ◦ C (May and June), whereas the minimum temperature sometimes reaches 0 ◦ C during winter (December–January). The relative humidity recorded was the highest in July– August and the lowest in April–May. Moderate rainfall often occurs during the winter months. The rainfall distribution, relative humidity, and thermal regimes during the cropping season, recorded at the meteorological observatory at NEBCRC of the University, are given in Fig. 1. During the experimental period, a total of 11.2 mm of rainfall occurred during December 2016. The maximum rainfall was recorded during the month of January. The experimental soil was classified under the subgroup Aquic Hapludoll in the order Mollisols (Deshpande et al., 1971). The soil belongs to the textural class sandy loam (sand 58.4%, silt 25.2%, clay 16.4%), with pH 6.9 and electrical conductivity 0.24 dS m−1 (in a soil:water ratio of 1:2.5, weight:volume), soil organic carbon 6.7 g kg−1 , available N (alkaline KMnO4 -extractable N) 180.2 kg ha−1 (Subbiah and Asija, 1956), NaHCO3 -extractable P 20.1 kg ha−1 (Olson et al., 1954) and ammonium acetate-extractable K 261.4 kg ha−1 (Jackson, 1973). The experiment was laid out in randomized block design: 4 treatments inoculated with P. jesenii MP1 or R. qingshengii S10107, i.e., alone (treatments MP1A and S10A) and in combination with 20 kg N ha−1 (treatments MP1N and S10N), and the remaining 2 treatments, one applied with 20 kg N ha−1 alone (NA) and an uninoculated control with no N. There were four replications of each treatment and the plot size was 7.2 m2 . Seed bacterization and sowing Seeds of chickpea (Cicer arietinum L. var. PG-186) were surface sterilized by soaking in 0.1% HgCl2 for 2 min and then thoroughly washed with autoclaved distilled water. After this, 0.1% carboxy methyl cellulose was added to the overnight grown cultures (optical density at 600 nm = 0.6). The seeds were soaked in cu-
TABLE I Characterization of the bacterial strains used in this study Strain name
NCBIa) accession No.
Isolation site
Latitude, longitude
Elevation
Climate
Pseudomonas jesenii MP1 Rhodococcus qingshengii S10107
JX310329 JX173283
Munsyari Munsyari
30.07◦ N, 80.23◦ E 30.07◦ N, 80.23◦ E
m 2 200 2 200
Temperate Temperate
a) National
center for Biotechnology Information.
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Fig. 1 Weekly weather conditions at the experimental site during the crop-growing season (from November 2016 to April 2017). Min. = minnum; max. = maxnum; R. = relative.
lture medium for 10 min, dried at room temperature and finally sown in tractor-opened furrows 30 cm apart in a field under natural conditions. Nitrogen was applied, as per treatments, in the form of urea at the time of sowing. A dose of 40 kg P2 O5 ha−1 from single super phosphate and 20 kg K2 O ha−1 from muriate of potash was given uniformly in all the treatments as basal applications. The crop was grown and protected from diseases and pests as per the recommended agronomic practices (Singh et al., 2003). Bioinoculants were inoculated by seed bacterization at 1.9 × 108 ± 1.1 × 102 colony forming units seed−1 at the time of sowing. Soil and plant sampling and analysis Five plants from each plot were taken for the study of agronomical parameters, such as root length, shoot length, fresh and dry weight of plant, nodule number, and fresh as well as dry weight of nodules. Plants were removed from side rows along with a soil block of about 25 cm diameter at 45, 60, and 75 days after sowing (DAS). The soil adhered to the roots was carefully washed off with tap water; the nodules were removed from the roots, counted, and their fresh and dry weights were recorded after drying in a hot air oven to a constant weight at 65 ◦ C. The root and shoot length and fresh weight of the uprooted plants were also recorded at each time interval. The dry weight of the plants at each interval was recorded by drying in a hot air oven to a constant weight at 65 ◦ C. Biochemical parameters, such as chlorophyll content and nitrate reductase activity of the plants, were estimated using standard protocols by Hiscox and Israelstam (1979) and Hageman and Hicklesley (1971), respectively. The grain and straw yields were recorded after harvesting the crop and expressed in kg ha−1 and there-
after, used in calculating the harvest index. The N content of plants at different time intervals, and in grain and straw, was estimated as described by Page et al. (1982), and N uptake by plants, grain, and straw was computed by multiplying with plant dry weight, grain, and straw yield, respectively (A.O.A.C., 1970). Soil samples (0–15 cm) from each plot were collected before and after sowing at time intervals of 45, 60, and 75 DAS and at the time of harvesting, and available N in soil was estimated using the alkaline permanganate method described by Subbiah and Asija (1956), in which the four replicates were pooled and analyzed. The soil N content following the treatments was compared with that at the initiation of the study to exclusively study soil health. Dynamics of 16S rRNA and nifH genes were analyzed in all soil samples using iCycleriQTM Multicolor (Bio-Rad Lab, Hercules, USA) real-time quantitative polymerase chain reaction (qPCR) and PCR-DGGE (Dcode system; Bio-Rad Lab, Hercules, USA) techniques as per our previous study (Kumar et al., 2014). Statistical analysis The statistical analysis of the above-mentioned parameters was carried out using analysis of variance (ANOVA), using a general linear model procedure (SPSS, ver. 16.0) to test the significance of the effects of different treatments. Duncan’s multiple range test was applied to determine significant differences between treatments at P < 0.05 level. RESULTS Plant agronomical parameters Fresh and dry weights. Both the bioinoculants, alone (MP1A and S10A) or in combination with che-
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mical fertilizer N (MP1N and S10N), resulted in significantly higher plant fresh and dry weights compared to the control. Treatments MP1A and MP1N resulted in significantly higher plant fresh and dry weights than the control and other treatments at 45, 60, and 75 DAS. Although both these treatments were statistically comparable, treatment MP1N resulted in an increase of 7.7%, 2.70%, and 3.8% in fresh weight, when compared with MP1A at 45, 60, and 75 DAS, respectively. Similarly, in terms of fresh and dry weights, treatments S10A and S10N were statistically at par. The latter treatment resulted in 8.6%, 3.6%, and 1.5% higher plant fresh weights than treatment S10A at 45, 60, and 75 DAS, respectively. Both these treatments were also comparable with treatment NA for fresh and dry weights (Fig. 2). The dry weight of the plants in treatment MP1N was significantly higher than that of the uninoculated control at all sampling intervals. At 45 and 65 DAS, treatment MP1N resulted in significantly higher plant dry weights than treatments S10A and NA and uninoculated control, and was statistically comparable to S10N and MP1A. Similarly, treatment MP1N resulted in significantly higher plant dry weights than all
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the other treatments at 75 DAS and was at par with treatment MP1A in this regard (Fig. 2). Shoot and root length. The shoot length of chickpea plants was the highest in treatment MP1N at all crop ages. It was significantly higher than that in the uninoculated control, but was similar to those in treatments S10A, S10N, and MP1A up to 65 DAS. At 75 DAS, treatment S10A was at par with all the other treatments, whereas treatment S10N resulted in significantly higher shoot lengths than the uninoculated control. Treatment MP1N showed the highest increase, of 35.8%, in shoot length at 75 DAS, when compared with the uninoculated control (Fig. 2). Similarly, the root length recorded in treatment MP1N was numerically higher than those of all the other treatments and significantly higher than that of the uninoculated control at all crop growth stages. Treatments S10A, S10N, and MP1A also resulted in significantly higher root lengths than the uninoculated control at different time intervals (Fig. 2). Nodule number, fresh weight, and dry weight. Nodule number and fresh and dry weights numerically increased with crop stage in all treatments. Both the bioinoculants, alone and in combination with N fertili-
Fig. 2 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on agronomical parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments at a specific time interval. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A= MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
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zer, induced significantly higher nodule numbers and fresh and dry weights than the uninoculated control at all intervals (Fig. 3). The highest nodule number was recorded in treatment MP1A, followed by MP1N, S10A, and S10N. Treatment MP1A was significantly better than the uninoculated control and at par with all the other treatments for nodule number at 45 DAS. At 65 DAS, treatment MP1A resulted in a significantly higher nodule number than treatments of uninoculated control, S10N and NA, but was at par with MP1N as well as S10A. This bioinoculant at 75 DAS also resulted in a significantly higher nodule number than treatment NA and the uninoculated control. Nodule fresh weight was the highest in treatment MP1A at all sampling intervals. This treatment was better than all other treatments for increasing nodule fresh weight at 45 DAS (547.75 mg plant−1 ). However, at 65 and 75 DAS, treatment MP1A was statistically comparable to MP1N, S10A, and S10N and was significantly better than the uninoculated control and NA for increasing nodule fresh weight. Inoculation of MP1 and S10107 alone and with N (MP1A, MP1N, S10A, and S10N), which were statistically comparable in increasing nodule dry weight, resulted in significantly higher nodule dry weights than
the uninoculated control at 45 DAS. At 65 DAS, all these treatments with bioinoculant resulted in significantly higher nodule dry weights than treatment NA and the uninoculated control; however, they were at par among themselves. Treatment MP1A also resulted in a significantly higher nodule dry weight than all the other treatments, except MP1N at 75 DAS. Treatment S10A was at par with S10N, NA and MP1N for nodule dry weight at this time interval. Plant biochemical parameters Chlorophyll content and nitrate reductase activity. Both the bioinoculants, alone and with 20 kg N −1 ha , resulted in significantly higher chlorophyll contents in the leaves than the uninoculated control at all crop growth stages. The leaf chlorophyll content recorded was the highest in treatment MP1N at all sampling intervals. This treatment resulted in significantly more chlorophyll in the leaves than the uninoculated control, NA and S10A treatments, whereas it was statistically comparable to S10N and MP1A at 45 DAS. Also at 65 DAS, leaf chlorophyll content was significantly higher in treatment MP1N than all the other treatments. Treatment S10N was at par with MP1A and S10A in terms of leaf chlorophyll content. All the
Fig. 3 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on nodule parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments at a specific time interval. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
treatments resulted in a significant higher chlorophyll content in the leaves than the uninoculated control and were at par among themselves at 75 DAS (Fig. 4). The nitrate reductase (NR) activity in chickpea was the highest in treatment MP1A at all sampling intervals. Treatment MP1A was significantly better than the uninoculated control and at par with all the other treatments for NR activity at 45 DAS. Treatments NA, S10A, and S10N were found to be statistically comparable to the uninoculated control for NR activity at this time interval. Also at 65 DAS, MP1A resulted in significantly higher NR activity than the uninoculated control, although it was at par with all the other treatments. However, at 75 DAS, it was statistically comparable to MP1N, S10A, and S10N and better than other treatments, with respect to NR activity (Fig. 4). N uptake. Nitrogen uptake by plants at different time intervals, seeds, and straw was the highest in treatment MP1N. Both the bioinoculants, alone and in combination with 20 kg N ha−1 , resulted in significantly more N accumulation in the pant, seeds, and straw than the uninoculated control (Fig. 5). Treatment MP1N was found to be significantly better than the uninoculated control and treatment NA for N uptake by plants at 45 DAS; it was at par with S10A, S10N and MP1A at this crop stage, in terms of N uptake. Also at 65 DAS, treatment MP1N resulted in significantly more N uptake by plants than the treatments of uninoculated control, NA, and S10A, but was statistically comparable to treatments S10N and MP1A. At 75 DAS, treatment MP1N was statistically comparable to S10A, S10N, and MP1A for plant N accumulation. However, it resulted in a significant increase, of 138.4% and 78.5%, in N uptake by plants, when
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compared with the uninoculated control and NA, respectively. Treatment MP1N also proved better for N uptake by seeds and straw after crop harvesting. This treatment was statistically comparable with S10N and MP1A, and significantly better than the uninoculated control, NA, and S10A for N uptake by seeds. Treatment MP1N also resulted in the highest N accumulation in straw (38.21 kg ha−1 ), followed by MP1A, S10N, S10A, and NA. This treatment was significantly better than the uninoculated control and was at par with NA, S10A, S10N and MP1A for straw N accumulation. Yield and harvest index. Grain and straw yields of chickpea and the harvest index were the highest in treatment MP1N, followed by MP1A, S10N, S10A, NA, and the uninoculated control (Fig. 6). Treatment MP1N resulted in a significantly higher grain yield, by 46.2%, and straw yield, by 27.0%, than the uninoculated control. It also resulted in a significantly higher grain yield than treatment NA and was at par with S10A, S10N, and MP1A. Similarly, it was statistically comparable to treatments MP1A, S10A, S10N, and NA for straw yield. The different treatments did not differ significantly in terms of harvest index. Soil biochemical properties Available N in soil. Different inoculation treatments resulted in remarkable increases in available N in the soil after harvesting, when compared with soil N levels before sowing (180.2 kg ha−1 ). Treatment MP1N resulted in the highest available N in soil after harvesting, with an increase of 235.6 kg ha−1 above the initial soil N level. This was followed by treatments MP1A,
Fig. 4 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on biochemical parameters of chickpea (Cicer arietinum L. var. PG-186) at 45, 60, and 75 days after sowing (DAS). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for a specific time interval at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 ; FW = fresh weight.
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Fig. 5 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on the accumulation of N in plants at different time intervals, seeds, and straw of chickpea (Cicer arietinum L. var. PG-186). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for a specific plant growth or agronomical parameter at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 ; DAS = days after sowing.
Fig. 6 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on grain and straw yields at the time of harvesting chickpea (Cicer arietinum L. var. PG-186). Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences between treatments for grain or straw yield at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
S10N, S10A, and NA and the uninoculated control.
These treatments resulted in 189.4, 150.9, 143.2, 120.1, and 104.7 kg ha−1 more available N in soil than the initially value (pre-sowing soil), respectively. Treatment MP1N resulted in significantly more available N in soil than S10N, S10A, and NA, and was statistically comparable to MP1A in terms of available N (Fig. 7). 16S rRNA and nifH gene abundances in the soil. Total bacterial (16S rRNA) and diazotrophic (nifH) abundances were calculated for all the experimental samples (Table II) and were expressed in copy numbers. The gradual increase in 16S rRNA abundance was observed until 75 DAS, with the highest in treatment MP1A, followed by S10107. After the last sampling, the total bacterial gene abundance was: MP1A > MP1N > S10A > S10N > NA > uninoculated control. The soil in treatment MP1A had the maximum abundance of 16S rDNA (4.63 × 1011 copies g−1 soil), which was much higher than that of the pre-sowing soil (8.67 × 108 copies g−1 soil). Similarly, nifH abundance ranged from 1.26 × 102 (pre-sowing) to 7.29 × 106 (MP1A) copies g−1 soil at 75 DAS. The quantification reveals the comparative effects of the treatments with respect to the soil before
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
Fig. 7 Effects of diazotrophs Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107 inoculation on available N content in soil. Bars are standard errors of means (n = 4). Different letter(s) above error bars indicate significant differences at P < 0.05. Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 .
sowing. The treatment with only MP1 and S10107 (MP1A and S10A) had respective abundances of 7.29 × 106 and 4.45 × 105 copies g−1 soil in the last sampling, whereas, in combination with 20 kg N ha−1 (MP1N and S10N), the nifH abundance was 5.93 × 105 and 2.18 × 104 copies g−1 soil, respectively. However, in the treatment with only urea (NA), the nifH abundance declined from 3.61 × 102 to 1.56 × 102 copies g−1 soil. Soil bacterial and diazotrophic community structures. Rhizospheric bacterial and diazotrophic community structures of each experimental sample were compared using 16S rDNA and nifH amplified genes, respectively. The DGGE patterns revealed the persistence of MP1 and S10107 throughout the experiment. In fact, the band pattern at 45 DAS depicted that MP1 was more dominant than S10107 during the cropping period. The intensity of the bands was prevalent until 60 DAS, and later decreased until 75 DAS. Six prominent bands were visible at 60 DAS, a few of which were persistent until 75 DAS (Fig. 8). This suggested an increase in soil microflora as an added effect of the bacterial inoculation in the field. Furthermore, the soil nifH diversity revealed a similar band pattern with prominent and intense bands at 45 and 75 DAS. The bands corresponding to the strain MP1 were abundant and intense at 45 and 75 DAS, whereas the bands corresponding to S10107 persisted but with less intensity (Fig. 9). This is in direct correlation with their respective copy numbers in soil, as discussed earlier.
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Fig. 8 Denaturing gradient gel electrophoresis (DGGE) image depicting the bacterial diversity (16S rRNA) in the soil under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS). Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . a = MP1 genomic DNA; b = S10107 genomic DNA; c = pre-sowing soil.
Fig. 9 Denaturing gradient gel electrophoresis (DGGE) image depicting the soil diazotrophic (nifH) diversity under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS). Control = no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . a = MP1 genomic DNA; b = S10107 genomic DNA; c = pre-sowing soil.
DISCUSSION Plant growth and agronomical parameters are influenced by a variety of biotic and abiotic factors. This study revealed that the strain MP1, in combination with the chemical fertilizer, helped the plant growth under field conditions. This is due to the fact that N from symbiotic N2 fixation is not always adequate to maximize growth and yield in legumes. For instance, low soil temperature at the time of planting can limit soil microbial activity, and, therefore, potentially de-
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TABLE II Comparative 16S rDNA and nifH gene abundances in the soil under different inoculation (Pseudomonas jesenii MP1 and Rhodococcus qingshengii S10107) and fertilizer (20 kg N ha−1 ) treatments at different days after sowing (DAS), as revealed by quantitative polymerase chain reaction (qPCR) analysis Treat- 45 DAS menta) 16S rDNA × × × × × ×
× × × × × ×
103 103 103 103 103 102
copies g−1 soil 108 ± 2.50 × 103 1.21 × 102 ± 1.67 × 108 ± 1.09 × 103 1.11 × 102 ± 1.45 × 1010 ± 1.28 × 103 4.13 × 105 ± 2.09 × 109 ± 2.11 × 103 1.32 × 104 ± 2.57 × 1010 ± 1.33 × 103 3.28 × 106 ± 1.22 × 109 ± 1.27 × 103 5.31 × 105 ± 1.33 ×
103 103 103 103 103 103
Control NA S10A S10N MP1A MP1N
3.40 1.10 1.80 2.80 4.19 2.27
Treatment
60 DAS 16S rDNA × × × × × ×
Control NA S10A S10N MP1A MP1N
1.47 4.50 3.57 4.03 7.17 5.50
Treatment
75 DAS 16S rDNA
Control NA S10A S10N MP1A MP1N
1.27 1.51 1.59 2.69 4.63 2.96
× × × × × ×
nifH
copies g−1 soil 109 ± 2.51 × 103b) 1.97 × 1010 ± 1.20 × 103 3.61 × 1010 ± 2.23 × 103 2.07 × 109 ± 1.54 × 103 2.72 × 1011 ± 1.69 × 103 3.74 × 1010 ± 2.15 × 103 3.15 ×
copies 109 ± 1.50 × 103 109 ± 1.02 × 103 1011 ± 1.36 × 103 1010 ± 1.31 × 103 1011 ± 1.31 × 103 1010 ± 1.21× 103
102 102 105 104 106 105
± ± ± ± ± ±
2.35 1.59 1.22 1.11 1.89 1.24
nifH
nifH g−1
soil 2.12 × 1.56 × 4.45 × 2.18 × 7.29 × 5.93 ×
103 102 105 104 106 105
± ± ± ± ± ±
1.29 1.33 2.11 1.09 2.13 1.55
× × × × × ×
103 103 103 103 103 103
= no N or bioinoculants; NA = 20 kg N ha−1 applied alone; S10A = S10107 inoculated alone; S10N = S10107 inoculated with 20 kg N ha−1 ; MP1A = MP1 inoculated alone; MP1N = MP1 inoculated with 20 kg N ha−1 . b) Mean ± standard error (n = 3). a) Control
lay N fixation and possibly the vegetative growth at the early stage (Gai et al., 2017). The stimulation of plant growth using the combination of bioinoculants and a lower concentration of chemical fertilizers has also been reported earlier (Maheshwari et al., 2010; Shashidhar et al., 2018). However, in terms of nodule parameters, viz., nodule number, fresh weight, and dry weight, individual applications of bacterial strains were observed to be better than the combinations and control used. This can be explained by the fact that a high concentration of soil N inhibits the production of nodules in legumes, reduces nodule mass, and N2 fixing activity, along with increasing senescence of the existing ones (Saito et al., 2014). However, an initial starter dose of mineral fertilizer helps in nodule initiation as well as acting as a N source until the biologi-
cal N fixation begins (Gai et al., 2017). Therefore, the fertilizer dose must be optimized before the cropping season to gain maximum output. Growth and development of chickpea tends to be slow in acidic and saline soils as the rate of nutrient uptake is negatively affected (Atieno et al., 2017; Burns et al., 2017; McCauley et al., 2017), which can be seen in the treatment with only 20 kg N ha−1 (urea). However, it can be successfully alleviated by the application of bioinoculants (Ilangumaran and Smith, 2017). Furthermore, urea, being an ammonia-based fertilizer, shows much less of an inhibitory effect on biological N fixation than nitrates, as it is readily metabolized to ammonium with the help of the urease enzyme, which is less harmful for diazotrophs. High chlorophyll content is beneficial in achieving high photosynthetic rates at low light intensities, which ultimately result in a healthy plant and higher yield (Shukla et al., 2015; Gu et al., 2017), whereas NR activity acts as a biochemical marker for predicting yield and protein concentration (Wang et al., 2017). In addition, N is a constituent of chlorophyll, photosynthetic enzymes (including Rubisco, PEPc, and PPDK), and thylakoid membranes. These cellular features are located in chloroplasts. The increased chlorophyll content with N addition indicates that more N is allocated to the light-harvesting complex (Mu et al., 2017). Plants cannot completely depend on biological N2 fixation and for optimum yield, it is necessary to use both biological N2 fixation and N uptake by roots from soil. Even in legumes, N fertilizer dose is based on the plant’s N needs during early plant development prior to nodule formation, and is crucial to growth and development (Gai et al., 2017). The chlorophyll and N content was higher in treatment MP1N, whereas the NR activity was the highest in treatment MP1A. These results suggest the integrated use of chemical and biofertilizers for better plant health and nutrient uptake. In nutshell, simultaneous use of biofertilizers and an optimum dose of mineral fertilizers can improve nutrient use efficiency of plants (Kakraliya et al., 2017). The crop yield was also higher in the combination treatments. In conclusion, the maximum grain yield of 2 698 kg ha−1 and harvesting index of 55.63% were observed for treatment MP1N. The high N content in soil is an indicator of good soil health, which in turn results in healthy plants. The integrated use of biofertilizers and mineral fertilizers results in higher residual soil N than does their individual application (Mukhongo et al., 2017). In addition, the higher N level after harvesting might be caused by rhizodeposition due to high leaf fall in chickpea. Treat-
IMPACTS OF BIOINOCULANTS ON CHICKPEA YIELD AND SOIL
ment MP1N resulted in the highest plant growth, and thus, had a high nutrient status. The fallen leaves act as excellent source of carbon and N after mineralization. To summarize, the bioinoculants had a positive effect on soil health by increasing N in the soil, which is not only beneficial for the standing crop, but also on any subsequent crop grown in that field. The 16S rRNA and nifH gene abundance in soil did not reveal vast differences among the treatments; however, both were increased significantly after treatment with bioinoculants. Thus, the bioinoculants have not affected soil microbial communities but boosted the soil micro-biota. Only MP1 or S10107 performed better than when applied in combination. The dose of chemical fertilizers in fields must be regulated as it showed consistent effects on the richness, diversity, and composition of soil bacterial communities. Though a basal dose of fertilizers will help in the establishment of the bacterial genera (Tang et al., 2017), prolonged use of chemical N in soil may decrease soil pH and bacterial 16S rRNA copy number while increasing soil N and crop yield (Zhou et al., 2015; Wang et al., 2017). The DGGE analysis for 16S rRNA revealed some bands observed exclusively at 60 DAS, a few of which persisted till the last sampling. Whereas, for nifH, some bands were prominent at 45 DAS, reduced on the second sampling (60 DAS), and again increased at 75 DAS. The bands corresponding to MP1 were more intense and persistent than those corresponding to S10107, which might be due to the rapid adaptability and metabolic versatility of this particular genus, as revealed by its plant growth-promoting activities including P solubilization (Tomer et al., 2017), N fixation, siderophore production, IAA production, etc. (Suyal et al., 2014; Uzair et al., 2018). The increased band numbers could be correlated with the change in nutrient content of the soil, which enriched new species. However, these data cannot reveal the complete or accurate diversity of soil microbes, as two bacterial genera with the same guanine plus cytosine (GC) content cannot be resolved by DGGE (Tabit, 2016). Furthermore, this also explains the existence of multiple bands in all the treatments, indicating the presence of some other bacterial strains with nearly same GC content as the bioinoculants (Kumar et al., 2014). On the contrary, the nifH diversity in soil is greatly influenced by the presence of chemical fertilizers. A similar study was conducted by Liao et al. (2018) on free living diazotrophs in rice fields and reported that the long-term use of chemical NPK fertilizers led to decreased nifH community diversity in soil, whereas the combination of chemical fertilizers with chicken ma-
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nure (organic manure) significantly improved the activity of diazotrophic communities. This suggests that adopting an integrated approach is more beneficial than reliance on a single factor for ensuring soil fertility, health, and a better crop yield (Bhardwaj et al., 2014; Bageshwar et al., 2017). In addition to this, environmental factors such as temperature, pH, soil texture, moisture content, organic matter, and humic acid play a decisive role in shaping the soil microbiota (Kumar et al., 2014; Zhou et al., 2017). Our study clearly indicated that the integrated use of bioinoculants and chemical fertilizer (MP1N and S10N) performed better in increasing crop yield and improving soil health. CONCLUSIONS In conclusion, the rhizosphere provides a peculiar environment where a huge variety of positive, negative, and neutral interactions between roots and microorganisms occur. Such interactions can significantly influence plant growth as well as the microbial activities. The present study demonstrated that application of bacterial strains in combination with 20 kg N ha−1 were better than the at par with application of the strains alone as well as their respective controls in terms of promoting plant growth and improving soil health. The chemical fertilizers, when supplied in appropriate amounts, can be beneficial not only for the plants and soil, but also for indigenous microbial diversity. ACKNOWLEDGEMENT The author (Dr. Deep Chandra SUYAL) acknowledges support from the Science and Engineering Research Board (SERB) young scientist scheme (No. YSS/2015/001214). Also, Senior Research Fellowship (Council of Scientific and Industrial Research Award No. 09/171(0126)/2015-EMR-I) to Mr. Saurabh Kumar is duly acknowledged. REFERENCES Association of Official Agricultural Chemistry (A.O.A.C.) 1970. Official Methods of Analysis. 11th Edn. Washington, D.C. Atieno J, Li Y L, Langridge P, Dowling K, Brien C, Berger B, Varshney R K, Sutton T. 2017. Exploring genetic variation for salinity tolerance in chickpea using image-based phenotyping. Sci Rep. 7: 1300. Bageshwar U K, Srivastava M, Pardha-Saradhi P, Paul S, Gothandapani S, Jaat R S, Shankar P, Yadav R, Biswas D R, Kumar P A, Padaria J C, Mandal P K, Annapurna K, Das H K. 2017. An environment friendly engineered Azotobacter can replace substantial amount of urea fertilizer and yet sustain same wheat yield. Appl Environ Microbiol. 83: e00590-17. Bhardwaj D, Ansari M W, Sahoo R K, Tuteja N. 2014. Biofertilizers function as key player in sustainable agriculture by
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