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Diversity of cultivable Azotobacter in the semi-arid alfisol receiving long-term organic and inorganic nutrient amendments

Diversity of cultivable Azotobacter in the semi-arid alfisol receiving long-term organic and... Ann Microbiol (2013) 63:1397–1404 DOI 10.1007/s13213-013-0600-6 ORIGINAL ARTICLE Diversity of cultivable Azotobacter in the semi-arid alfisol receiving long-term organic and inorganic nutrient amendments Chinnappan Cinnadurai & Ganesan Gopalaswamy & Dananjeyan Balachandar Received: 26 September 2012 /Accepted: 2 January 2013 /Published online: 17 January 2013 Springer-Verlag Berlin Heidelberg and the University of Milan 2013 Abstract Monitoring the biological processes and microbial Introduction diversity is essential for sustaining the soil health for long-term productivity. In the present study, the impact of long-term Most Indian agricultural soils are representative of semi-arid nutrient management systems on changes in Azotobacter di- tropical arable soils and characterized by low levels of soil versity of Indian semi-arid alfisol was assessed. Three organic carbon (SOC), macro- and micro-nutrients. The soils, i.e., unfertilized control, soils amended with organic agricultural system is typically a low-input farming with manures (OM), and with inorganic chemical fertilizers (IC) limited use of organic amendments for soil enrichment. from century-old experimental fields were evaluated Given the tropical climate (long hours of sun), the added for Azotobacter diversity by Amplified Ribosomal DNA organic amendments and inorganic fertilizers quickly oxi- Restriction Analysis (ARDRA). Bray–Curtis’s similarity index dize and this causes slow SOC development. The SOC is the of the ARDRA data of the isolates was analyzed by non-metric source and sink for macro- and micro-nutrients and is im- multi-dimensional scaling and hierarchical cluster analysis. portant for soil tilth, aeration and water-holding capacity The results revealed that the long-term organically managed (Gregorich et al. 1994). The microbial communities in- soil recorded significantly higher soil organic carbon, micro- volved in soil processes affect the production levels and bial biomass carbon, and total culturable bacterial counts, sustainability of an agro-system (Stark et al. 2008). whereas the chemical fertilized and control soils remained However, in order to sustain the productivity and increase unaffected. Though the Azotobacter population was signifi- yield, the soil is supplemented with inorganic chemical cantly higher in OM soil than IC and control soils, the genetic fertilizers. These fertilizers are directly taken up by the crop diversity was unaffected due to long-term addition of either plants with minimal transformation in soil. organic manures or inorganic chemical fertilizers. This result The addition of exogenous organic manures and chemi- implies the importance of continuous addition of organic man- cal fertilizers affects the microbial population, composition, ures and also the optimal use of inorganic chemical fertilizers and functioning (Marschner et al. 2003). Organic manures without disturbing the biological properties of the soil. usually increase the soil microbial biomass (Peacock et al. 2001), soil respiration (Ajwa and Tabatabai 1994), and . . Keywords Azotobacter Conventional farming Long-term enzymes (Crecchio et al. 2001), along with SOC and con- . . . fertilization Microbial biomass Organic farming Soil centration of other nutrients (Crecchio et al. 2001). It fertility Soil quality appears that the inorganic fertilizers have relatively less impact on soil microbiological properties, including soil enzymes, nutrient transformation rates except nitrification : : C. Cinnadurai G. Gopalaswamy D. Balachandar (*) (Chu et al. 2007a), and diversity of bacterial communities Department of Agricultural Microbiology, Tamil Nadu (Liu et al. 2007; Chu et al. 2007b), compared to organic Agricultural University, Coimbatore 641 003, India amendments (Plaza et al. 2004). Hence, monitoring the e-mail: dbalu2000@yahoo.com changes in the biological properties of the soil due to any C. Cinnadurai disturbances like nutrient managements and agronomical e-mail: chinna515@yahoo.com practices is essential as these may affect the productivity G. Gopalaswamy and sustainability of soil. e-mail: ggswamy@gmail.com 1398 Ann Microbiol (2013) 63:1397–1404 Azotobacter, a gamma-Proteobacteria (Tchan 1984)and an and immediately subjected to biological analyses. The obligate aerobe, is the predominant free-living diazotroph in physico-chemical properties were analysed later on the soil agricultural soils. Positive interactions of Azotobacter with samples stored at 4 °C. field crops are well documented (Aquilanti et al. 2004a, b). The physico-chemical properties of the soils including The ecological distribution of Azotobacter spp. is dictated by pH, electrical conductivity (EC), SOC, available N, P, K, soil characteristics (Martyniuk and Martyniuk 2003) and cli- and micronutrients including copper, manganese, iron, and mate conditions (Dobereiner and Pedrosa 1987), including zinc were analyzed following the standard protocols (Sparks organic matter content, moisture, C/N ratio, and pH. Hence, 1996). The fumigation extraction method (Jenkinson and the occurrence and functionality of Azotobacter have been Ladd 1981) was used to estimate the microbial biomass widely used as an indicator for physical and chemical distur- carbon (MBC) of the soil. The number of total heterotrophic bances of soil (Gonzalez-Lopez et al. 1992). The occurrence bacteria was quantified by serial dilution and plating in soil of Azotobacter in soil is affected by the toxicity of herbicides extract agar medium (James 1958). The cultivable (Murica et al. 1997), industrial pollutants (Pozo et al. 2000), Azotobacter population present in the soil samples was and choice of crop (Bhatia et al. 2009). However, no study has counted using Waksman 77 medium as described by Fred so far been undertaken to assess the impact of long-term and Waksman (1928). Biochemical tests were used to au- nutrient management on the fate of Azotobacter, which may thenticate the Azotobacter isolates, according to Bergey’s be useful for assessing the soil fertility. In the present study, Manual of Systematic Bacteriology (Tchan 1984). the influence of long-term application of chemical fertilizers and organic manures on the diversity of Azotobacter,as Azotobacter diversity assessed by Amplified Ribosomal DNA Restriction Analysis (ARDRA), was investigated. From each soil sample, 20 Azotobacter isolates showing typical growth pattern in N-free Waksman 77 medium were further purified and maintained in the same medium. These Materials and methods were designated as C1-C20, OM1-OM20, and IC1-IC20 for control, organic manure amended and inorganic chemical Soil sampling fertilized soil isolates, respectively. Genomic DNA from all the 60 Azotobacter isolates along with the standard strain The long-term permanent manurial experiment being con- (Azotobacter chroococcum AC1; authenticated by ducted in alfisol (Typic Haplustalf) since 1909 at Tamil Department of Agricultural Microbiology, Tamil Nadu Nadu Agricultural University, Coimbatore, India (11°N, Agricultural University, Coimbatore 641 003, India) cul- 77°E, and 426 m altitude), was selected for this study. The tured in Tryptic soy broth at 30 °C were extracted by permanent manurial experiment area is characterized by hexadecyl cetyltrimethyl ammonium bromide (CTAB) semi-arid sub-tropical climate with a mean annual precipi- method (Melody 1997). tation of about 670 mm and mean annual maximum and Nearly full-length 16S rRNA gene was amplified from minimum air temperature of 34.2 and 20 °C respectively. the genomic DNA from each isolate using FD1 and RP2 The soil is characterized by red sandy loam, arable, enriched primers (Weisburg et al. 1991). A total of 20 μL of reaction with aluminium and iron minerals and low in humus. It has volume contained 50 ng of the genomic DNA, 0.2 mM of high content of available Ca, Mg, K, and Na and is low in N each dNTP, 1 μM of each primer, 2.5 mM of MgCl , and 1 and P. Maize followed by sunflower is the crop rotation U of Taq DNA polymerase (all from Bangalore Genei, adopted in the experimental field. India) and the buffer supplied with the enzyme. PCR am- For the present study, the long-term nutrient treatment plification was performed in a thermocycler (Eppendorf plots, viz., inorganic chemical fertilizers (IC), organic man- Master Cycler, Germany) using conditions as follows: initial ures (OM), and unfertilized control (control), were chosen denaturation at 95 °C for 10 min; 35 cycles consisting of from the long-term permanent manurial experiment. IC 94 °C for 1 min (denaturation); 55 °C for 1 min (annealing); plots were applied with 60:20:10 kg/ha of N, P O , and 72 °C for 1 min (primer extension); and final extension at 2 5 K O as urea, superphosphate, and muriate of potash, respec- 72 °C for 10 min. tively, irrespective of the crop tested. OM plots received Approximately 1 μg of PCR-amplified 16S rRNA gene composted cattle manure at N equivalent of IC during last fragments was restricted with endonuclease HaeIII ploughing, and control plots were unfertilized. (Fermentas, USA) at 37 °C for 3 h and resolved using 2 % Undisturbed soil samples were collected in triplicate at a metaphor agarose gels. Banding patterns were visualized by depth of 0–15 cm during fallow period (April 2011) from ethidium bromide staining and documented in the Alpha each treatment plot. After removing stones and stubbles, soil Imager TM1200 documentation and analysis system. In samples were homogenized, passed through a 2-mm sieve, order to determine the similarity between the isolates among Ann Microbiol (2013) 63:1397–1404 1399 the soil samples, a binary matrix was established recording randomization to generate significance levels (P values). the presence or absence of bands in the ARDRA profile. ANOSIM tests the null hypothesis, where similar samples show a test statistic R of 0. As R approaches 1, the null- hypothesis is rejected; this indicates that members of a group Statistical analyses are similar each other and differ significantly from members of other groups. Data from the presence/absence of bands in the ARDRA profile of all the 60 Azotobacter isolates were imported into PRIMER 6 (Plymouth Routines in Multivariate Ecological Research, v.6.1.13; PRIMER-E, Plymouth, UK). A similarity Results matrix was constructed by calculating similarities between each pair of samples using the Bray–Curtis coefficient The long-term addition of nutrient amendments apparently (Clarke 1993). Non-metric Multi-Dimensional Scaling influenced the physico-chemical properties of alfisol soil (MDS) was used to ordinate the similarity data. MDS uses with semi-arid tropical climate (Table 1). Between the two an iterative algorithm that takes the multidimensional data of a long-term nutritionally managed soils, OM soil had signif- similarity matrix and presents it in minimal dimensional space, icantly higher SOC (190 % more than control) followed by typically two-dimensional and three-dimensional plots can be IC soil (65 % than control). Apart from this, the levels of N, employed to visualize group differences. The result of MDS P, and Mn available to plants did not significantly differ ordination is a map where the position of each sample is between OM and IC soils. The potassium and copper con- determined by its distance from all other points in the analysis. tents of IC soil were statistically higher than OM and least in The stress of the plot is a measure of how much distortion was the control soil. The Fe concentration of IC and control soils introduced to allow the representation of the data in the spec- was significantly higher than OM soil. ified dimensions. A stress value greater than 0.2 indicates that The significant effect exerted by different nutrient man- the plot is close to random, stress less than 0.2 indicates a agements accounted for the differences (p≤0.05) in total useful two-dimensional picture, and less than 0.1 corresponds heterotrophic bacterial count of soil samples. The bacterial to an ideal ordination with no real prospect of misinterpretation population was higher in OM soil than IC and control soils (Clarke 1993). In the present analysis, stress was calculated as (Fig. 1). Likewise, the mean Azotobacter count was statisti- described by Kruskal (1964)within PRIMER6. cally higher (p≤0.05) in OM soil than in IC and control To visualize the relationship among the Azotobacter iso- soils. There was no significant difference in the Azotobacter lates derived from different soil samples, the similarity matrix count between the IC and control soils. With regards to soil using the Bray–Curtis coefficient was also analyzed by MBC, the OM plot was significantly higher than the other Hierarchical Cluster Analysis (HCA), a classification method two and the trend observed was OM>IC>control. that aims to group samples into discrete clusters based on The ARDRA profiling of Azotobacter isolates showed similarity. HCA was performed by a weighted, group- few dominating isolates appearing in any of the three dif- average linkage agglomerative method and dendrogram was ferently managed soils (Fig. 2). HaeIII restriction digestion constructed from the ranked similarities using PRIMER 6 of the full-length 16S rRNA gene amplicon (1,500 bp) software. Significance testing of sample data was done with resulted in a clear and strong banding pattern with fragment the non-parametric permutation procedure ANOSIM (analysis range 100–700 bp. However, the banding patterns of of similarity). This test ranks the similarity matrix used in Azotobacter isolates from three different nutritionally man- MDS and combines this ranking with Monte Carlo aged soils were similar among all the samples (Fig. 2a–c). Table 1 Physico-chemical Soil properties Control OM IC properties of soil influenced by long-term organic manures and pH 8.45 (±0.03) a 8.45 (±0.04) a 8.42 (±0.03) a chemical fertilizers application Ec (dS/m) 0.19 (±0.10) a 0.09 (±0.01) b 0.10 (±0.00) b SOC (%) 0.20 (±0.05) c 0.58 (±0.05) a 0.33 (±0.06) b Available N (kg/ha) 184.23 (±3.11) b 286.37 (±2.71) a 278.83 (±5.87) a Values are mean (±standard er- ror) (n=6) and values followed Available P (kg/ha) 8.08 (±0.72) b 17.27 (±0.79) a 16.73 (±0.91) a by the same letter in each row Available K (kg/ha) 319.50 (±6.01) c 644.17 (±4.50) b 663.50 (±4.46) a are not significantly different Copper (μg/g) 0.45 (±0.01) c 0.58 (±0.02) b 0.61 (±0.02) a from each other as determined Manganese (μg/g) 8.15 (±0.33) b 9.12 (±0.37) a 9.17 (±0.25) a by Duncan’s Multiple Range Test (p≤0.05) Iron (μg/g) 1.39 (±0.09) a 1.18 (±0.05) b 1.39 (±0.05) a OM Organically managed soil, IC Zinc (μg/g) 0.20 (±0.02) c 0.40 (±0.01) a 0.28 (±0.01) b Inorganic chemical fertilized soil 1400 Ann Microbiol (2013) 63:1397–1404 Fig. 1 Impact of long-term ad- dition of organic manures (OM) and inorganic chemical fertil- izers (IC) on changes in soil microbial biomass-C, total cul- turable bacteria, and Azotobac- ter populations. For each histogram, different letters in- dicate significantly different at p≤0.05 according to Duncan’s Multiple Range Test The banding patterns of the isolates also revealed that a ordination. The HCA dendrogram based on Bray–Curtis single isolate was predominantly present in all the three coefficient matrix showed about 40–100 % similarity soils (Fig. 2a lanes 2, 6, 7, 8, 13, 14; b lanes 1, 2, 5, 6, 7, among the isolates (Fig. 3). The HCA dendrogram showed 8, 17, 18, 19, 20; c lanes 1, 2, 3, 4, 7, 9, 10, 11, 18). The that 35, 45, and 50 % of Azotobacter isolates of control, IC, relationships among the Azotobacter isolates from control, and OM, respectively, formed a major cluster with 100 % IC andOMsoils were assessedbyHCA andMDS similarity (Fig. 3). There were three IC isolates (IC5, IC15, Fig. 2 ARDRA profiling of Azotobacter isolates from differently managed soils. a Control soil; b organically managed soil; c inorganic chemical fertilized soil; Lanes 1–20 of each profile refers to the Azotobacter isolates from respective soil samples; S standard strain (Azotobacter chroococcum Ac1); M 100 bp DNA marker Ann Microbiol (2013) 63:1397–1404 1401 Fig. 3 HCA dendrogram constructed from ARDRA data of Azotobacter isolates from soils amended with organic manures and chemical fertilizers. C Control soil; OM organically managed soil; IC inorganic chemical fertilized soil; lanes 1–20 refer to the Azotobacter isolates from respective soil samples and IC19) that fell as outliers in the dendrogram suggesting soils (Fig. 4). Most of the Azotobacter isolates of the three that these were different from other isolates. soils clustered tightly (stress of 0.1) and clustering of the MDS ordination of ARDRA profiles of Azotobacter iso- isolates based on soil nutrient management was not pro- lates showed a similar community structure in all the three nounced. ANOSIM test of Bray–Curtis similarity matrix 1402 Ann Microbiol (2013) 63:1397–1404 Fig. 4 PCA plot constructed from ARDRA data of Azotobacter isolates from soils amended with organic manures and chemical fertilizers. OM organically managed soil; IC inorganic chemical fertilized soil gave a global R statistic of 0.005 (p=0.01) which revealed sensitive indicators of sustainability of management systems that the overall difference between soil types was small and (Gregorich et al. 1997). In our present investigation, both the statistically towards the null hypothesis, i.e., the samples are inorganic chemical fertilizers and organic amendments had not different. The pairwise R statistic values were also much higher MBC than that of unfertilized controls indicating that lower and insignificant. R values for control/OM, control/IC nutrient management practice was a vital key for improvement and OM/IC were 0.007 (p<0.01), 0.002 (p=0.05), and 0.02 of SOC and MBC (Gu et al. 2009). In the present study, the (p<0.05), respectively. Azotobacter population was positively correlated with the SOC and MBC. Azotobacter uses a variety of carbohydrates, alcohols, and salts of organic acids as sources of carbon and Discussion hence depends on the SOC for its survival and activity. Hence, in the present study, the OM soil recorded the maximum Long-term addition of both organic manures and inorganic Azotobacter population compared to IC and control soil. fertilizers equally enhanced the available nutrients status of However, the continuous addition of chemical fertilizers at the soil except SOC compared to control, which is in accor- the recommended dosage did not cause any reduction in the dance with the earlier reports from long-term field experi- Azotobacter population of the soil. ments (Meng et al. 2005; Chu et al. 2007b). In the IC soil, In the present investigation, the genetic diversity of the free- the enhanced crop residues including roots and stubbles due living diazotroph, Azotobacter, as influenced by long-term to chemical fertilization contributed to the build-up of SOC addition of organic manures and chemical fertilizers in the which was significantly higher than in control soil (Meng et semi-arid alfisol was assessed. Azotobacter as a bioinoculant al. 2005; Paustian et al. 1997). The macronutrients level in has been reported to improve the yields of both annual and OM and IC was higher than the unfertilized control indicat- perennial crops (Lakshminaryana 1993; Narula et al. 2005). Its ing that nutrients, released either from organic manure or survival in the soil and establishment in the rhizosphere of crop from chemical fertilizers applied for the long-term, were plants are known to be affected by climatic conditions, plant efficiently deposited and maintained in the tested soil. species, and the organic matter content of the soil (Dart and The increased bacterial count recorded in OM soil com- SubbaRao 1981; Rajakumar and Lakshmanan 1995). Hence, pared to IC and control soils is mainly due to the addition of assessing the population and diversity of Azotobacter in an diversified carbon-rich organic manures, which in turn signif- alfisol-type soil due to long-term nutrient management is es- icantly enhanced the microbial counts, whereas the chemical sential in the sense of fertility sustainment. Further, soil char- fertilizers did not have much influence on the microbial pop- acteristics including available nitrogen, moisture, and ulations (Govaerts et al. 2008; Janvier et al. 2007). The MBC temperature also affect the various physiological properties of of soil, an agent of labile nutrients, is critically important for Azotobacter. In the present investigation, the common molec- the establishment of soil quality and thus one of the most ular diversity fingerprinting for culturable bacterial diversity, Ann Microbiol (2013) 63:1397–1404 1403 Agricultural Chemistry, Tamil Nadu Agricultural University, Coimba- ARDRA, has been employed to assess the diversity of tore, India, is acknowledged for his help and support in collecting the Azotobacter in soil. In the past, this technique had been used soil samples from the century-old permanent manurial experimental successfully to discriminate the diversity of Methylobacterium fields. We also thank Dr. Kalai Mathee, Florida International Univer- in the phyllosphere of plant species (Raja et al. 2008; sity, Miami, USA, for reviewing, valuable suggestions, and also En- glish corrections. Our acknowledgments to Dr. R. Krishnamachary, Balachandar et al. 2008). In the present study, the similarity Department of Linguistics, Bharathiyar University, Coimbatore, India, of ARDRA profiling of Azotobacter isolates calculated by the for language improvement. Bray–Curtis coefficient, grouped by HCA and ordinated using an MDS plot, showed that there was not much difference (ANOSIM global R statistic near 0) in the diversity of Azotobacter in soil influenced by even 100 years of continuous References application of either organic manures or chemical fertilizers. These sequential multivariate statistical analyses have effec- Ajwa HA, Tabatabai MA (1994) Decomposition of different organic tively resolved the soil samples based on the bacterial commu- materials in soils. Biol Fertil Soils 18(3):175–182. doi:10.1007/ bf00647664 nity profiles (Micallef et al. 2009), and the present result was Aleem A, Isar J, Malik A (2003) Impact of long-term application of also in agreement. Bhatia et al. 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Polish J Environ Studies 12:371–374 ture and short-term nitrogen mineralisation resulting from farm Melody SC (1997) Plant Molecular Biology - A laboratory manual. management history and organic matter amendments. Soil Biol Springer, New York Biochem 40(6):1352–1363. doi:10.1016/j.soilbio.2007.09.025 Meng L, Ding W, Cai Z (2005) Long-term application of organic Tchan YT (1984) Family II Azotobacteraceae Pribram 1933, 5AL. In: manure and nitrogen fertilizer on NO emissions, soil quality and Krieg NR, Holt JG (eds) Bergey’s Manual of Systematic crop production in a sandy loam soil. Soil Biol Biochem 37 Bacteriology, vol 1. Williams & Wilkins, Baltimore, pp 219–220 (11):2037–2045. doi:10.1016/j.soilbio.2005.03.007 Weisburg WG, Barns SM, Pelletier DA, Lane DJ (1991) 16S ribosomal Micallef SA, Shiaris MP, Colón-Carmona A (2009) Influence of DNA amplification for phylogenetic study. J Bacteriol 173 Arabidopsis thaliana accessions on rhizobacterial communities (2):697–703 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Microbiology Springer Journals

Diversity of cultivable Azotobacter in the semi-arid alfisol receiving long-term organic and inorganic nutrient amendments

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Life Sciences; Microbiology; Microbial Genetics and Genomics; Microbial Ecology; Fungus Genetics; Medical Microbiology; Applied Microbiology
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Ann Microbiol (2013) 63:1397–1404 DOI 10.1007/s13213-013-0600-6 ORIGINAL ARTICLE Diversity of cultivable Azotobacter in the semi-arid alfisol receiving long-term organic and inorganic nutrient amendments Chinnappan Cinnadurai & Ganesan Gopalaswamy & Dananjeyan Balachandar Received: 26 September 2012 /Accepted: 2 January 2013 /Published online: 17 January 2013 Springer-Verlag Berlin Heidelberg and the University of Milan 2013 Abstract Monitoring the biological processes and microbial Introduction diversity is essential for sustaining the soil health for long-term productivity. In the present study, the impact of long-term Most Indian agricultural soils are representative of semi-arid nutrient management systems on changes in Azotobacter di- tropical arable soils and characterized by low levels of soil versity of Indian semi-arid alfisol was assessed. Three organic carbon (SOC), macro- and micro-nutrients. The soils, i.e., unfertilized control, soils amended with organic agricultural system is typically a low-input farming with manures (OM), and with inorganic chemical fertilizers (IC) limited use of organic amendments for soil enrichment. from century-old experimental fields were evaluated Given the tropical climate (long hours of sun), the added for Azotobacter diversity by Amplified Ribosomal DNA organic amendments and inorganic fertilizers quickly oxi- Restriction Analysis (ARDRA). Bray–Curtis’s similarity index dize and this causes slow SOC development. The SOC is the of the ARDRA data of the isolates was analyzed by non-metric source and sink for macro- and micro-nutrients and is im- multi-dimensional scaling and hierarchical cluster analysis. portant for soil tilth, aeration and water-holding capacity The results revealed that the long-term organically managed (Gregorich et al. 1994). The microbial communities in- soil recorded significantly higher soil organic carbon, micro- volved in soil processes affect the production levels and bial biomass carbon, and total culturable bacterial counts, sustainability of an agro-system (Stark et al. 2008). whereas the chemical fertilized and control soils remained However, in order to sustain the productivity and increase unaffected. Though the Azotobacter population was signifi- yield, the soil is supplemented with inorganic chemical cantly higher in OM soil than IC and control soils, the genetic fertilizers. These fertilizers are directly taken up by the crop diversity was unaffected due to long-term addition of either plants with minimal transformation in soil. organic manures or inorganic chemical fertilizers. This result The addition of exogenous organic manures and chemi- implies the importance of continuous addition of organic man- cal fertilizers affects the microbial population, composition, ures and also the optimal use of inorganic chemical fertilizers and functioning (Marschner et al. 2003). Organic manures without disturbing the biological properties of the soil. usually increase the soil microbial biomass (Peacock et al. 2001), soil respiration (Ajwa and Tabatabai 1994), and . . Keywords Azotobacter Conventional farming Long-term enzymes (Crecchio et al. 2001), along with SOC and con- . . . fertilization Microbial biomass Organic farming Soil centration of other nutrients (Crecchio et al. 2001). It fertility Soil quality appears that the inorganic fertilizers have relatively less impact on soil microbiological properties, including soil enzymes, nutrient transformation rates except nitrification : : C. Cinnadurai G. Gopalaswamy D. Balachandar (*) (Chu et al. 2007a), and diversity of bacterial communities Department of Agricultural Microbiology, Tamil Nadu (Liu et al. 2007; Chu et al. 2007b), compared to organic Agricultural University, Coimbatore 641 003, India amendments (Plaza et al. 2004). Hence, monitoring the e-mail: dbalu2000@yahoo.com changes in the biological properties of the soil due to any C. Cinnadurai disturbances like nutrient managements and agronomical e-mail: chinna515@yahoo.com practices is essential as these may affect the productivity G. Gopalaswamy and sustainability of soil. e-mail: ggswamy@gmail.com 1398 Ann Microbiol (2013) 63:1397–1404 Azotobacter, a gamma-Proteobacteria (Tchan 1984)and an and immediately subjected to biological analyses. The obligate aerobe, is the predominant free-living diazotroph in physico-chemical properties were analysed later on the soil agricultural soils. Positive interactions of Azotobacter with samples stored at 4 °C. field crops are well documented (Aquilanti et al. 2004a, b). The physico-chemical properties of the soils including The ecological distribution of Azotobacter spp. is dictated by pH, electrical conductivity (EC), SOC, available N, P, K, soil characteristics (Martyniuk and Martyniuk 2003) and cli- and micronutrients including copper, manganese, iron, and mate conditions (Dobereiner and Pedrosa 1987), including zinc were analyzed following the standard protocols (Sparks organic matter content, moisture, C/N ratio, and pH. Hence, 1996). The fumigation extraction method (Jenkinson and the occurrence and functionality of Azotobacter have been Ladd 1981) was used to estimate the microbial biomass widely used as an indicator for physical and chemical distur- carbon (MBC) of the soil. The number of total heterotrophic bances of soil (Gonzalez-Lopez et al. 1992). The occurrence bacteria was quantified by serial dilution and plating in soil of Azotobacter in soil is affected by the toxicity of herbicides extract agar medium (James 1958). The cultivable (Murica et al. 1997), industrial pollutants (Pozo et al. 2000), Azotobacter population present in the soil samples was and choice of crop (Bhatia et al. 2009). However, no study has counted using Waksman 77 medium as described by Fred so far been undertaken to assess the impact of long-term and Waksman (1928). Biochemical tests were used to au- nutrient management on the fate of Azotobacter, which may thenticate the Azotobacter isolates, according to Bergey’s be useful for assessing the soil fertility. In the present study, Manual of Systematic Bacteriology (Tchan 1984). the influence of long-term application of chemical fertilizers and organic manures on the diversity of Azotobacter,as Azotobacter diversity assessed by Amplified Ribosomal DNA Restriction Analysis (ARDRA), was investigated. From each soil sample, 20 Azotobacter isolates showing typical growth pattern in N-free Waksman 77 medium were further purified and maintained in the same medium. These Materials and methods were designated as C1-C20, OM1-OM20, and IC1-IC20 for control, organic manure amended and inorganic chemical Soil sampling fertilized soil isolates, respectively. Genomic DNA from all the 60 Azotobacter isolates along with the standard strain The long-term permanent manurial experiment being con- (Azotobacter chroococcum AC1; authenticated by ducted in alfisol (Typic Haplustalf) since 1909 at Tamil Department of Agricultural Microbiology, Tamil Nadu Nadu Agricultural University, Coimbatore, India (11°N, Agricultural University, Coimbatore 641 003, India) cul- 77°E, and 426 m altitude), was selected for this study. The tured in Tryptic soy broth at 30 °C were extracted by permanent manurial experiment area is characterized by hexadecyl cetyltrimethyl ammonium bromide (CTAB) semi-arid sub-tropical climate with a mean annual precipi- method (Melody 1997). tation of about 670 mm and mean annual maximum and Nearly full-length 16S rRNA gene was amplified from minimum air temperature of 34.2 and 20 °C respectively. the genomic DNA from each isolate using FD1 and RP2 The soil is characterized by red sandy loam, arable, enriched primers (Weisburg et al. 1991). A total of 20 μL of reaction with aluminium and iron minerals and low in humus. It has volume contained 50 ng of the genomic DNA, 0.2 mM of high content of available Ca, Mg, K, and Na and is low in N each dNTP, 1 μM of each primer, 2.5 mM of MgCl , and 1 and P. Maize followed by sunflower is the crop rotation U of Taq DNA polymerase (all from Bangalore Genei, adopted in the experimental field. India) and the buffer supplied with the enzyme. PCR am- For the present study, the long-term nutrient treatment plification was performed in a thermocycler (Eppendorf plots, viz., inorganic chemical fertilizers (IC), organic man- Master Cycler, Germany) using conditions as follows: initial ures (OM), and unfertilized control (control), were chosen denaturation at 95 °C for 10 min; 35 cycles consisting of from the long-term permanent manurial experiment. IC 94 °C for 1 min (denaturation); 55 °C for 1 min (annealing); plots were applied with 60:20:10 kg/ha of N, P O , and 72 °C for 1 min (primer extension); and final extension at 2 5 K O as urea, superphosphate, and muriate of potash, respec- 72 °C for 10 min. tively, irrespective of the crop tested. OM plots received Approximately 1 μg of PCR-amplified 16S rRNA gene composted cattle manure at N equivalent of IC during last fragments was restricted with endonuclease HaeIII ploughing, and control plots were unfertilized. (Fermentas, USA) at 37 °C for 3 h and resolved using 2 % Undisturbed soil samples were collected in triplicate at a metaphor agarose gels. Banding patterns were visualized by depth of 0–15 cm during fallow period (April 2011) from ethidium bromide staining and documented in the Alpha each treatment plot. After removing stones and stubbles, soil Imager TM1200 documentation and analysis system. In samples were homogenized, passed through a 2-mm sieve, order to determine the similarity between the isolates among Ann Microbiol (2013) 63:1397–1404 1399 the soil samples, a binary matrix was established recording randomization to generate significance levels (P values). the presence or absence of bands in the ARDRA profile. ANOSIM tests the null hypothesis, where similar samples show a test statistic R of 0. As R approaches 1, the null- hypothesis is rejected; this indicates that members of a group Statistical analyses are similar each other and differ significantly from members of other groups. Data from the presence/absence of bands in the ARDRA profile of all the 60 Azotobacter isolates were imported into PRIMER 6 (Plymouth Routines in Multivariate Ecological Research, v.6.1.13; PRIMER-E, Plymouth, UK). A similarity Results matrix was constructed by calculating similarities between each pair of samples using the Bray–Curtis coefficient The long-term addition of nutrient amendments apparently (Clarke 1993). Non-metric Multi-Dimensional Scaling influenced the physico-chemical properties of alfisol soil (MDS) was used to ordinate the similarity data. MDS uses with semi-arid tropical climate (Table 1). Between the two an iterative algorithm that takes the multidimensional data of a long-term nutritionally managed soils, OM soil had signif- similarity matrix and presents it in minimal dimensional space, icantly higher SOC (190 % more than control) followed by typically two-dimensional and three-dimensional plots can be IC soil (65 % than control). Apart from this, the levels of N, employed to visualize group differences. The result of MDS P, and Mn available to plants did not significantly differ ordination is a map where the position of each sample is between OM and IC soils. The potassium and copper con- determined by its distance from all other points in the analysis. tents of IC soil were statistically higher than OM and least in The stress of the plot is a measure of how much distortion was the control soil. The Fe concentration of IC and control soils introduced to allow the representation of the data in the spec- was significantly higher than OM soil. ified dimensions. A stress value greater than 0.2 indicates that The significant effect exerted by different nutrient man- the plot is close to random, stress less than 0.2 indicates a agements accounted for the differences (p≤0.05) in total useful two-dimensional picture, and less than 0.1 corresponds heterotrophic bacterial count of soil samples. The bacterial to an ideal ordination with no real prospect of misinterpretation population was higher in OM soil than IC and control soils (Clarke 1993). In the present analysis, stress was calculated as (Fig. 1). Likewise, the mean Azotobacter count was statisti- described by Kruskal (1964)within PRIMER6. cally higher (p≤0.05) in OM soil than in IC and control To visualize the relationship among the Azotobacter iso- soils. There was no significant difference in the Azotobacter lates derived from different soil samples, the similarity matrix count between the IC and control soils. With regards to soil using the Bray–Curtis coefficient was also analyzed by MBC, the OM plot was significantly higher than the other Hierarchical Cluster Analysis (HCA), a classification method two and the trend observed was OM>IC>control. that aims to group samples into discrete clusters based on The ARDRA profiling of Azotobacter isolates showed similarity. HCA was performed by a weighted, group- few dominating isolates appearing in any of the three dif- average linkage agglomerative method and dendrogram was ferently managed soils (Fig. 2). HaeIII restriction digestion constructed from the ranked similarities using PRIMER 6 of the full-length 16S rRNA gene amplicon (1,500 bp) software. Significance testing of sample data was done with resulted in a clear and strong banding pattern with fragment the non-parametric permutation procedure ANOSIM (analysis range 100–700 bp. However, the banding patterns of of similarity). This test ranks the similarity matrix used in Azotobacter isolates from three different nutritionally man- MDS and combines this ranking with Monte Carlo aged soils were similar among all the samples (Fig. 2a–c). Table 1 Physico-chemical Soil properties Control OM IC properties of soil influenced by long-term organic manures and pH 8.45 (±0.03) a 8.45 (±0.04) a 8.42 (±0.03) a chemical fertilizers application Ec (dS/m) 0.19 (±0.10) a 0.09 (±0.01) b 0.10 (±0.00) b SOC (%) 0.20 (±0.05) c 0.58 (±0.05) a 0.33 (±0.06) b Available N (kg/ha) 184.23 (±3.11) b 286.37 (±2.71) a 278.83 (±5.87) a Values are mean (±standard er- ror) (n=6) and values followed Available P (kg/ha) 8.08 (±0.72) b 17.27 (±0.79) a 16.73 (±0.91) a by the same letter in each row Available K (kg/ha) 319.50 (±6.01) c 644.17 (±4.50) b 663.50 (±4.46) a are not significantly different Copper (μg/g) 0.45 (±0.01) c 0.58 (±0.02) b 0.61 (±0.02) a from each other as determined Manganese (μg/g) 8.15 (±0.33) b 9.12 (±0.37) a 9.17 (±0.25) a by Duncan’s Multiple Range Test (p≤0.05) Iron (μg/g) 1.39 (±0.09) a 1.18 (±0.05) b 1.39 (±0.05) a OM Organically managed soil, IC Zinc (μg/g) 0.20 (±0.02) c 0.40 (±0.01) a 0.28 (±0.01) b Inorganic chemical fertilized soil 1400 Ann Microbiol (2013) 63:1397–1404 Fig. 1 Impact of long-term ad- dition of organic manures (OM) and inorganic chemical fertil- izers (IC) on changes in soil microbial biomass-C, total cul- turable bacteria, and Azotobac- ter populations. For each histogram, different letters in- dicate significantly different at p≤0.05 according to Duncan’s Multiple Range Test The banding patterns of the isolates also revealed that a ordination. The HCA dendrogram based on Bray–Curtis single isolate was predominantly present in all the three coefficient matrix showed about 40–100 % similarity soils (Fig. 2a lanes 2, 6, 7, 8, 13, 14; b lanes 1, 2, 5, 6, 7, among the isolates (Fig. 3). The HCA dendrogram showed 8, 17, 18, 19, 20; c lanes 1, 2, 3, 4, 7, 9, 10, 11, 18). The that 35, 45, and 50 % of Azotobacter isolates of control, IC, relationships among the Azotobacter isolates from control, and OM, respectively, formed a major cluster with 100 % IC andOMsoils were assessedbyHCA andMDS similarity (Fig. 3). There were three IC isolates (IC5, IC15, Fig. 2 ARDRA profiling of Azotobacter isolates from differently managed soils. a Control soil; b organically managed soil; c inorganic chemical fertilized soil; Lanes 1–20 of each profile refers to the Azotobacter isolates from respective soil samples; S standard strain (Azotobacter chroococcum Ac1); M 100 bp DNA marker Ann Microbiol (2013) 63:1397–1404 1401 Fig. 3 HCA dendrogram constructed from ARDRA data of Azotobacter isolates from soils amended with organic manures and chemical fertilizers. C Control soil; OM organically managed soil; IC inorganic chemical fertilized soil; lanes 1–20 refer to the Azotobacter isolates from respective soil samples and IC19) that fell as outliers in the dendrogram suggesting soils (Fig. 4). Most of the Azotobacter isolates of the three that these were different from other isolates. soils clustered tightly (stress of 0.1) and clustering of the MDS ordination of ARDRA profiles of Azotobacter iso- isolates based on soil nutrient management was not pro- lates showed a similar community structure in all the three nounced. ANOSIM test of Bray–Curtis similarity matrix 1402 Ann Microbiol (2013) 63:1397–1404 Fig. 4 PCA plot constructed from ARDRA data of Azotobacter isolates from soils amended with organic manures and chemical fertilizers. OM organically managed soil; IC inorganic chemical fertilized soil gave a global R statistic of 0.005 (p=0.01) which revealed sensitive indicators of sustainability of management systems that the overall difference between soil types was small and (Gregorich et al. 1997). In our present investigation, both the statistically towards the null hypothesis, i.e., the samples are inorganic chemical fertilizers and organic amendments had not different. The pairwise R statistic values were also much higher MBC than that of unfertilized controls indicating that lower and insignificant. R values for control/OM, control/IC nutrient management practice was a vital key for improvement and OM/IC were 0.007 (p<0.01), 0.002 (p=0.05), and 0.02 of SOC and MBC (Gu et al. 2009). In the present study, the (p<0.05), respectively. Azotobacter population was positively correlated with the SOC and MBC. Azotobacter uses a variety of carbohydrates, alcohols, and salts of organic acids as sources of carbon and Discussion hence depends on the SOC for its survival and activity. Hence, in the present study, the OM soil recorded the maximum Long-term addition of both organic manures and inorganic Azotobacter population compared to IC and control soil. fertilizers equally enhanced the available nutrients status of However, the continuous addition of chemical fertilizers at the soil except SOC compared to control, which is in accor- the recommended dosage did not cause any reduction in the dance with the earlier reports from long-term field experi- Azotobacter population of the soil. ments (Meng et al. 2005; Chu et al. 2007b). In the IC soil, In the present investigation, the genetic diversity of the free- the enhanced crop residues including roots and stubbles due living diazotroph, Azotobacter, as influenced by long-term to chemical fertilization contributed to the build-up of SOC addition of organic manures and chemical fertilizers in the which was significantly higher than in control soil (Meng et semi-arid alfisol was assessed. Azotobacter as a bioinoculant al. 2005; Paustian et al. 1997). The macronutrients level in has been reported to improve the yields of both annual and OM and IC was higher than the unfertilized control indicat- perennial crops (Lakshminaryana 1993; Narula et al. 2005). Its ing that nutrients, released either from organic manure or survival in the soil and establishment in the rhizosphere of crop from chemical fertilizers applied for the long-term, were plants are known to be affected by climatic conditions, plant efficiently deposited and maintained in the tested soil. species, and the organic matter content of the soil (Dart and The increased bacterial count recorded in OM soil com- SubbaRao 1981; Rajakumar and Lakshmanan 1995). Hence, pared to IC and control soils is mainly due to the addition of assessing the population and diversity of Azotobacter in an diversified carbon-rich organic manures, which in turn signif- alfisol-type soil due to long-term nutrient management is es- icantly enhanced the microbial counts, whereas the chemical sential in the sense of fertility sustainment. Further, soil char- fertilizers did not have much influence on the microbial pop- acteristics including available nitrogen, moisture, and ulations (Govaerts et al. 2008; Janvier et al. 2007). The MBC temperature also affect the various physiological properties of of soil, an agent of labile nutrients, is critically important for Azotobacter. In the present investigation, the common molec- the establishment of soil quality and thus one of the most ular diversity fingerprinting for culturable bacterial diversity, Ann Microbiol (2013) 63:1397–1404 1403 Agricultural Chemistry, Tamil Nadu Agricultural University, Coimba- ARDRA, has been employed to assess the diversity of tore, India, is acknowledged for his help and support in collecting the Azotobacter in soil. In the past, this technique had been used soil samples from the century-old permanent manurial experimental successfully to discriminate the diversity of Methylobacterium fields. We also thank Dr. Kalai Mathee, Florida International Univer- in the phyllosphere of plant species (Raja et al. 2008; sity, Miami, USA, for reviewing, valuable suggestions, and also En- glish corrections. Our acknowledgments to Dr. R. Krishnamachary, Balachandar et al. 2008). 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Annals of Microbiology – Springer Journals

Published: Jan 17, 2013

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