Meta QTL analysis for dissecting abiotic stress tolerance in chickpea.

BACKGROUND: Chickpea is prone to many abiotic stresses such as heat, drought, salinity, etc. which cause severe loss in yield. Tolerance towards these stresses is quantitative in nature and many studies have been done to map the loci influencing these traits in different populations using different markers. This study is an attempt to meta-analyse those reported loci projected over a high-density consensus map to provide a more accurate information on the regions influencing heat, drought, cold and salinity tolerance in chickpea. RESULTS: A meta-analysis of QTL reported to be responsible for tolerance to drought, heat, cold and salinity stress tolerance in chickpeas was done. A total of 1512 QTL responsible for the concerned abiotic stress tolerance were collected from literature, of which 1189 were projected on a chickpea consensus genetic map. The QTL meta-analysis predicted 59 MQTL spread over all 8 chromosomes, responsible for these 4 kinds of abiotic stress tolerance in chickpea. The physical locations of 23 MQTL were validated by various marker-trait associations and genome-wide association studies. Out of these reported MQTL, CaMQAST1.1, CaMQAST4.1, CaMQAST4.4, CaMQAST7.8, and CaMQAST8.2 were suggested to be useful for different breeding approaches as they were responsible for high per cent variance explained (PVE), had small intervals and encompassed a large number of originally reported QTL. Many putative candidate genes that might be responsible for directly or indirectly conferring abiotic stress tolerance were identified in the region covered by 4 major MQTL- CaMQAST1.1, CaMQAST4.4, CaMQAST7.7, and CaMQAST6.4, such as heat shock proteins, auxin and gibberellin response factors, etc. CONCLUSION: The results of this study should be useful for the breeders and researchers to develop new chickpea varieties which are tolerant to drought, heat, cold, and salinity stresses.

Nitrate reduction to ammonium: a phylogenetic, physiological, and genetic aspects in Prokaryotes and eukaryotes.

The microbe-mediated conversion of nitrate (NO3-) to ammonium (NH4+) in the nitrogen cycle has strong implications for soil health and crop productivity. The role of prokaryotes, eukaryotes and their phylogeny, physiology, and genetic regulations are essential for understanding the ecological significance of this empirical process. Several prokaryotes (bacteria and archaea), and a few eukaryotes (fungi and algae) are reported as NO3- reducers under certain conditions. This process involves enzymatic reactions which has been catalysed by nitrate reductases, nitrite reductases, and NH4+-assimilating enzymes. Earlier reports emphasised that single-cell prokaryotic or eukaryotic organisms are responsible for this process, which portrayed a prominent gap. Therefore, this study revisits the similarities and uniqueness of mechanism behind NO3- -reduction to NH4+ in both prokaryotes and eukaryotes. Moreover, phylogenetic, physiological, and genetic regulation also shed light on the evolutionary connections between two systems which could help us to better explain the NO3--reduction mechanisms over time. Reports also revealed that certain transcription factors like NtrC/NtrB and Nit2 have shown a major role in coordinating the expression of NO3- assimilation genes in response to NO3- availability. Overall, this review provides a comprehensive information about the complex fermentative and respiratory dissimilatory nitrate reduction to ammonium (DNRA) processes. Uncovering the complexity of this process across various organisms may further give insight into sustainable nitrogen management practices and might contribute to addressing global environmental challenges.

Structural, microstructure, dielectric relaxation, and AC conduction studies of perovskite SrSnO3 and Ruddlesden-Popper oxide Sr2SnO4.

Here, we report a comparison study on the synthesis and characterization of perovskite SrSnO3 (SSO) and Sr2SnO4 (S2SO). Rietveld refinement studies were performed on both prepared samples and suggest that they crystallized in cubic (SSO) and tetragonal (S2SO) structures. Fourier-transform infrared (FTIR) and Raman spectroscopy studies supported the XRD observations. Improved dielectric parameters were observed for S2SO over SSO due to differences in dislocation density, larger crystallite size, and denser microstructure. The electrical conduction and relaxation processes followed the Arrhenius type in both samples through the migration of oxygen vacancies via the Sn-site and the transfer of electrons between the Sn sites in two different temperature regions. These processes in the samples occurred via correlated barrier hopping (CBH) in SSO and the non-overlapping of small-polaron tunnelling (NSPT) in S2SO. The conduction and relaxation processes had similar sources of charge carriers but differed in the concentration and mobility of charge carriers. The presented materials can be utilized for dielectric capacitors, sensors, and mixed ionic and electronic conductor-based electrodes in IT-SOFC applications.

Enhancing soil quality and yield through microbial assisted in-situ residue management in rice-rice cropping system in Odisha, Eastern India.

Crop residue management has become more challenging with intensive agricultural operations. Zero tillage and crop residue returns, along with the enhancement of in-situ residue decomposition through microbial intervention, are essential measures for preserving and enhancing soil quality. To address this problem in view of stubble burning, field experiments were conducted in rice-rice (variety Swarna) cropping systems under lowland conditions, wherein the following different residue management practices were adopted viz., conventional cultivation (CC), residue incorporation (RI @ 6 t paddy straw ha-1), residue retention (RR @6 t paddy straw ha-1), and zero tillage (ZT). In this experiment, two microbial products i.e. solid microbial consortium (SMC) at 2.0 kg ha-1) and capsule (10 numbers ha-1), were evaluated in both Rabi (dry) and Kharif (wet) seasons under different residue management practices. The results on soil microbial properties showed that application of either SMC or capsule based formulation could significantly improve the soil organic carbon (SOC) content in ZT (9.51 g/kg), followed by RI (9.36 g/kg), and RR (9.34 g/kg) as compared to CC (7.61 g/kg). There were significant differences in the soil functional properties (AcP, AkP, FDA, and DHA) with microbial interventions across all residue management practices. SOC was significantly positive correlated with cellulase (R2 = 0.64, p < 0.001), ß-glucosidase (R2 = 0.61, p < 0.001), and laccase (R2 = 0.66, p < 0.001) activity; however, the regression coefficients varied significantly with microbial intervention. Moreover, the availability of N, P, and K in soil was significantly (p < 0.05) improved under microbial treatments with either RR or RI practices. Among the different methods of residues management practices, RI with microbial intervention registered a consistent yield improvement (8.4-17.8%) compared to conventional practices with microbial intervention. The present findings prove that the application of decomposing microbial consortia for in-situ rice residue management under field conditions significantly enhances soil quality and crop yield compared to conventional practices.

Impacts of conservation agriculture on crop yield and soil carbon sequestration: a meta-analysis in the Indian subcontinent.

In the quest of achieving sustainable crop productivity, improved soil health, and increased carbon (C) sequestration in the soil, conservation agriculture (CA) is increasingly being promoted and adopted in the Indian subcontinent. However, because some researchers from different regions of the world have reported reduced crop yield under CA relative to agriculture based on conventional tillage (CT), a meta-analysis has been conducted based on published research from India to evaluate the effects of CA on the yield of crops, accumulation of soil organic C as an index of soil health, and C sequestration in the soil in different regions and soil textural groups in the country. The meta-analysis is based on 544 paired observations under CA and CT from 35 publications from India was carried out using Meta Win 2.1 software. The results showed an overall significant (p < 0.05) reduction of 1.15% crop yield under CA compared to CT. Yearwise data showed a reduction of yields under CA from 2009 to 2016, but an increase from 2017 to 2020. Yield reduction was observed in the eastern, north-eastern, and southern regions of India but in western, northern, and north-western regions of the country, an increase was observed under CA rather than CT. Sandy loam and clayey soils exhibited higher crop yield under CA than under CT. Compared to CT, soil organic C content and soil C sequestration under CA increased by 8.9% and 7.3%, respectively. Also, in all the regions and soil textural groups both soil organic C accumulation and soil C sequestration were higher under CA than under CT. Factors such as rainfall, soil depth, available nitrogen (N), and total N significantly influenced the extent of yield increase/decrease and soil organic C accumulation under CA. Overall, results of the meta-analysis suggest that the promotion of CA in India will have to be location-specific taking into consideration the crops, soil attributes, and climatic conditions.

Rice-based integrated farming system improves the soil quality, bacterial community structure and system productivity under sub-humid tropical condition.

Rice-based integrated farming system improves the productivity and profitability by recycling resources efficiently. In the sub-humid tropics, rice production without sufficient nutrient replenishment often leads to soil health and fertility degradation. There has been very limited research on soil health and fertility after adopting a multi-enterprising rice-based integrated farming system (IFS), notably in the rice-fish-livestock and agroforestry system, when compared to a conventional farming system (CS). Therefore, the present study analyzed the dynamics of soil properties, soil bacterial community structure and their possible interaction mechanisms, as well as their effect on regulating soil quality and production in IFS, IFSw (water stagnant area of IFS) and CS. The results indicated that soil nutrient dynamics, bacterial diversity indices (Shannon index, Simpson index, Chao 1, ACE and Fisher index) and system productivity were higher in IFSw and IFS compared to CS. Moreover, relative operational taxonomic units of dominant bacterial genera (Chloroflexi, Acidobacteria, Verrucomicrobia, Planctomycetes, Cyanobacteria, Crenarchaeota and Gemmatimonadetes) were also higher in IFSw and IFS compared to CS. Mean soil quality index (SQI) was highest in IFSw (0.780 ± 0.201) followed by IFS (0.770 ± 0.080) and CS (0.595 ± 0.244). Moreover, rice equivalent yields (REY) and rice yields were well correlated with the higher levels of soil biological indices (SQIBiol) in IFS. Overall, our results revealed that rice-based IFS improved the soil health and fertility and ensuing crop productivity through positive interaction with soil bacterial communities and nutrient stoichiometry leading to agroecosystem sustainability.

Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat.

BACKGROUND: Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. RESULTS: Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker-trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development. CONCLUSION: The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.

ASmiR: a machine learning framework for prediction of abiotic stress-specific miRNAs in plants.

Abiotic stresses have become a major challenge in recent years due to their pervasive nature and shocking impacts on plant growth, development, and quality. MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of specific abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational model for prediction of miRNAs associated with four specific abiotic stresses such as cold, drought, heat and salt. The pseudo K-tuple nucleotide compositional features of Kmer size 1 to 5 were used to represent miRNAs in numeric form. Feature selection strategy was employed to select important features. With the selected feature sets, support vector machine (SVM) achieved the highest cross-validation accuracy in all four abiotic stress conditions. The highest cross-validated prediction accuracies in terms of area under precision-recall curve were found to be 90.15, 90.09, 87.71, and 89.25% for cold, drought, heat and salt respectively. Overall prediction accuracies for the independent dataset were respectively observed 84.57, 80.62, 80.38 and 82.78%, for the abiotic stresses. The SVM was also seen to outperform different deep learning models for prediction of abiotic stress-responsive miRNAs. To implement our method with ease, an online prediction server "ASmiR" has been established at https://iasri-sg.icar.gov.in/asmir/ . The proposed computational model and the developed prediction tool are believed to supplement the existing effort for identification of specific abiotic stress-responsive miRNAs in plants.

Multicomponent Reaction of CS2, Amines, and Sulfoxonium Ylides in Water: Straightforward Access to ß-Keto Dithiocarbamates, Thiazolidine-2-thiones, and Thiazole-2-thiones.

Simple, versatile, and catalyst-free synthetic methods for ß-keto dithiocarbamates, thiazolidine-2-thiones, and thiazole-2-thiones via the multicomponent reaction of CS2, amines, and sulfoxonium ylides have been described. The ß-keto sulfoxonium ylides furnished ß-keto dithiocarbamates in the presence of CS2 and secondary amines, whereas primary amines afforded thiazolidine-2-thiones or thiazole-2-thiones after dehydration in an acidic environment. With simple procedures, the reaction has a wide substrate scope and excellent functional group tolerance.

Physiological traits and expression profile of genes associated with nitrogen and phosphorous use efficiency in wheat.

BACKGROUND: Nitrogen (N) and phosphorous (P) play a very important role in the growth and development of wheat as well as major constituents of biological membranes. To meet the plant's nutritional demand these nutrients are applied in the form of fertilizers. But the plant can utilize only half of the applied fertilizer whereas the rest is lost through surface runoff, leaching and volatilization. Thus, to overcome the N/P loss we need to elucidate the molecular mechanism behind the N/P uptake. METHODS: In our study, we used DBW16 (low NUE), and WH147 (high NUE) wheat genotypes under different doses of N, whereas HD2967 (low PUE) and WH1100 (high PUE) genotypes were studied under different doses of P. To check the effect of different doses of N/P, the physiological parameters like total chlorophyll content, net photosynthetic rate, N/P content, and N/PUE of these genotypes were calculated. In addition, gene expression of various genes involved in N uptake, utilization, and acquisition such as Nitrite reductase (NiR), Nitrate transporter 1/Peptide transporter family (NPF2.4/2.5), Nitrate transporter (NRT1) and NIN Like Protein (NLP) and induced phosphate starvation (IPS), Phosphate Transporter (PHT1.7) and Phosphate 2 (PHO2) acquisition was studied by quantitative real-time PCR. RESULTS: Statistical analysis revealed a lower percent reduction in TCC, NPR, and N/P content in N/P efficient wheat genotypes (WH147 & WH1100). A significant increase in relative fold expression of genes under low N/P concentration was observed in N/P efficient genotypes as compared to N/P deficient genotypes. CONCLUSION: Significant differences in physiological data and gene expression among N/ P efficient and deficient wheat genotypes could be useful for future improvement of N/P use efficiency.

Delineating Marker-Trait Associations for Fusarium Wilt in Chickpea Using the Axiom® CicerSNP Array.

Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at the seedling and reproductive stages under field conditions and controlled conditions in the greenhouse. Our results revealed that at the seedling stage, most of the genotypes were resistant, whereas at the reproductive stage, most of the genotypes were susceptible. Genotyping using a 50K Axiom® CicerSNP Array and trait data of FW together led to the identification of 26 significant (P ≤ E-05) marker-trait associations (MTAs) for FW resistance. Among the 26 MTAs, 12 were identified using trait data recorded in the field (three at the seedling and nine at the reproductive stage), and 14 were identified using trait data recorded under controlled conditions in the greenhouse (six at the seedling and eight at the reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86%, with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% of the phenotypic variation for FW, and two were declared stable, being identified in two environments. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at the reproductive stage was also detected in greenhouse conditions at the seedling and reproductive stages. The stable and major (>15% PVE) MTAs can be used in chickpea breeding programs.

Development and characterization of nitrogen and phosphorus use efficiency responsive genic and miRNA derived SSR markers in wheat.

Among all the nutrients, nitrogen (N) and phosphorous (P) are the most limiting factors reducing wheat production and productivity world-wide. These macronutrients are directly applied to soil in the form of fertilizers. However, only 30-40% of these applied fertilizers are utilized by crop plants, while the rest is lost through volatilization, leaching, and surface run off. Therefore, to overcome the deficiency of N and P, it becomes necessary to improve their use efficiency. Marker-assisted selection (MAS) combined with traditional plant breeding approaches is considered best to improve the N and P use efficiency (N/PUE) of wheat varieties. In this study, we developed and evaluated a total of 98 simple sequence repeat (SSR) markers including 66 microRNAs and 32 gene-specific SSRs on a panel of 10 (N and P efficient/deficient) wheat genotypes. Out of these, 35 SSRs were found polymorphic and have been used for the study of genetic diversity and population differentiation. A set of two SSRs, namely miR171a and miR167a were found candidate markers able to discriminate contrasting genotypes for N/PUE, respectively. Therefore, these two markers could be used as functional markers for characterization of wheat germplasm for N and P use efficiency. Target genes of these miRNAs were found to be highly associated with biological processes (24 GO terms) as compared to molecular function and cellular component and shows differential expression under various P starving conditions and abiotic stresses.

ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo K-Tuple Nucleotide Compositional Features.

MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set were 62.33, 64.85, 69.21 percentages, respectively, for the three datasets. The SVM also achieved higher accuracy than other learning methods such as random forest, extreme gradient boosting, and adaptive boosting. To implement our method with ease, an online prediction server "ASRmiRNA" has been developed. The proposed approach is believed to supplement the existing effort for identification of abiotic stress-responsive miRNAs and Pre-miRNAs.

Homology modeling and virtual characterization of cytochrome c nitrite reductase (NrfA) in three model bacteria responsible for short-circuit pathway, DNRA in the terrestrial nitrogen cycle.

NrfA is the molecular marker for dissimilatory nitrate reduction to ammonium (DNRA) activity, catalysing cytochrome c nitrite reductase enzyme. However, the limited study has been made so far to understand the structural homology modeling of NrfA protein in DNRA bacteria. Therefore, three model DNRA bacteria (Escherechia coli, Wolinella succinogenes and Shewanella oneidensis) were chosen in this study for in-silico protein modeling of NrfA which roughly consists of similar length of amino acids and molecular weight and they belong to two contrasting taxonomic families (γ-proteobacteria with nrfABCDEFG and ε-proteobacteria with nrfHAIJ operon). Multiple bioinformatic tools were used to examine the primary, secondary, and tertiary structure of NrfA protein using three distinct homology modeling pipelines viz., Phyre2, Swiss model and Modeller. The results indicated that NrfA protein in E. coli, W. succinogenes and S. oneidensis was mostly periplasmic and hydrophilic. Four conserved Cys-X1-X2-Cys-His motifs, one Cys-X1-X2-Cys-Lys haem-binding motif and Ca ligand were also identified in NrfA protein irrespective of three model bacteria. Moreover, 11 identical conserved amino acids sequence was observed for the first time between serine and proline in NrfA protein. Secondary structure of NrfA revealed that α-helices were observed in 77.9%, 73.4%, and 77.4% in E. coli, W. succinogenes and S. oneidensis, respectively. Ramachandran plot showed that number of residue in favored region in E. coli, W. succinogenes and S. oneidensis was 97.03%, 97.01% and 97.25%, respectively. Our findings also revealed that among three pipelines, Modeller was considered the best in-silico tool for prediction of NrfA protein. Overall, significant findings of this study may aid in the identification of future unexplored DNRA bacteria containing cytochrome c nitrite reductase. The NrfA system, which is linked to respiratory nitrite ammonification, provides an analogous target for monitoring less studied N-retention processes, particularly in agricultural ecosystems. Furthermore, one of the challenging research tasks for the future is to determine how the NrfA protein responds to redox status in the microbial cells.

Non-target effect of bispyribac sodium on soil microbial community in paddy soil.

Bispyribac sodium is frequently used herbicide in the rice field. Though, it has been targeted to kill rice weeds, but its non-target effect on soil microbes in paddy soil was largely unknown. Therefore, in the present study, an attempt was made to assess the non-target effect of bispyribac sodium on alteration of functional variation of soil microbial community and their correlation with microbial biomass carbon (MBC) and soil enzymes. A microcosm experiment set up was made comprising three treatments viz., control (CON) (without application of bispyribac sodium), recommended dose of bispyribac sodium (35 g ha-1) (BS), and double the dose of BS (70 g ha-1) (DBS). Results indicated that the MBC and soil enzyme activities (dehydrogenase, alkaline phosphatase and urease) in BS and DBS-treated soil were significantly (p < 0.05) declined from 1st to 30th day after application as compared to CON. Counts of heterotrophic bacteria, actinomycetes and fungal population were also decreased in BS and DBS-treated soil. The average well color development (AWCD) values derived from Biolog®ecoplates followed the order of DBS ˂ BS ˂ CON. Shannon index value was high (p ≤ 0.05) in CON compared to soil-treated with BS and DBS. Principal component analysis (PCA) showed a clear distinction of the cluster of treatments between CON, BS and DBS. Biplot analysis and heatmap suggested that carboxylic compounds and amino acids showed positive response towards BS-treated soil, whereas phenolic compounds had positive correlation with DBS-treated soil. PCA analysis indicated that oligotrophs was rich in BS-treated paddy soil, whereas copiotrophs and asymbiotic nitrogen fixers were richer in DBS treatment. Overall, the present study revealed that application of recommended dose of BS and its double dose alter the soil microbial population, enzyme activities and functional microbial diversity in paddy soil.

Functional diversity and metabolic profile of microbial community of mine soils with different levels of chromium contamination.

Microbial communities provide useful information about any chemical and physical changes in the environment and play an essential role in maintaining soil fertility. Biolog® eco-plates method was used to study the functional diversity of microbial communities, and their correlation with soil organic carbon (OC), microbial biomass and activities, under three different soil conditions of Sukinda chromite mining area of Odisha, India during August 2016. The OC, available nitrogen, available phosphorus and available potash were significantly (p < 0.05) lower in in situ and overburden soils as compared to forest soil. The average development rate of average well color development values decreased with incubation time in all soil conditions. The utilization of six categories of carbon sources by soil microbes decreased with the increase in chromium load and biplot analysis suggested that carbohydrate, polymer and amino acid utilizing microbes were dominant in mining soils. The ecotoxicological status of chromite mine soil would be useful for formulating strategies of possible bioremediation program.

Cyanobiont diversity in six Azolla spp. and relation to Azolla-nutrient profiling.

MAIN CONCLUSION: Illumina-Miseq®-based cyanobiont diversity and biomass were analyzed in six Azolla spp. Results revealed that 93-98% of total operational taxonomic units (OTUs) belong to Nostacaceae followed by Cylindrospermopsis with about 1-6% OTUs. The taxonomy of Azolla-cyanobiont is a long-term debate within the scientific community. Morphological and biochemical-based reports indicated the presence of Anabaena, Nostoc and/or Trichormus azollae as abundant Azolla-cyanobionts, however, molecular data did not support the abundance of Anabaena and/or Nostoc. To understand furthermore, the cyanobiont diversity in six species of Azolla (A. microphylla, A. mexicana, A. filiculoides, A. caroliniana, A. pinnata and A. rubra) was analyzed based on 16S rRNA Illumina-MiSeq sequencing. Additionally, biomass and nutrient profiling of Azolla spp. were analyzed and correlated with cyanobiont diversity. Illumina-MiSeq data revealed that 99.6-99.9% of total operational taxonomic units (OTUs) belonged to Nostocophycideae (class), Nostocales (order) and Nostacaceae (family). At genus level, the unassigned affiliation (93.4-97.9%) under Nostacaceae family was abundant followed by Cylindrospermopsis OTUs (1.1-6.0%). Interestingly, A. pinnata harboured maximum Cylindrospermopsis OTUs and also recorded higher biomass (40.67 g m-2 day-1), whereas crude protein (25.9%) and antioxidants (76.9%) were recorded to be higher in A. microphylla. Biplot analysis revealed that A. pinnata and its cyanobiont abundance were positively correlated with neutral and acid detergent fibers. Overall, the present findings deepened the understanding about cyanobiont in Azolla and its relations with Azolla nutrient profiling.

Understanding interaction effect of arbuscular mycorrhizal fungi in rice under elevated carbon dioxide conditions.

Arbuscular mycorrhizal fungi (AMF), particularly the Glomerales group, play a paramount role in plant nutrient uptake, and abiotic and biotic stress management in rice, but recent evidence revealed that elevated CO2 concentration considerably reduces the Glomerales group in soil. In view of this, the present study was initiated to understand the interaction effect of native Glomerales species application in rice plants (cv. Naveen) under elevated CO2 concentrations (400 ± 10, 550 ± 20, and 700 ± 20 ppm) in open-top chambers. Three different modes of application of the AMF inoculum were evaluated, of which, combined application of AMF at the seedling production and transplanting stages showed increased AMF colonization, which significantly improved grain yield by 25.08% and also increased uptake of phosphorus by 18.2% and nitrogen by 49.5%, as observed at 700-ppm CO2 concentration. Organic acids secretion in rice root increased in AMF-inoculated plants exposed to 700-ppm CO2 concentration. To understand the overall effect of CO2 elevation on AMF interaction with the rice plant, principal component and partial least square regression analysis were performed, which found both positive and negative responses under elevated CO2 concentration.

Structural diversity and efficacy of culturable cellulose decomposing bacteria isolated from rice-pulse resource conservation practices.

The diversity of cellulolytic bacteria from the rice-pulse system can be sourced for identification of efficient cellulose decomposing microbial strains. In the present study, the abundance, structural diversity, and cellulolytic potential of the culturable bacterial community were studied in 5-year old rice-pulse system under different resource conservation technologies. Higher cellulose (68% more) and xylanase (35% more) activities were observed under zero tilled soil. The populations of cellulolytic bacteria were significantly higher (44%) in zero tillage (ZT) treatment than those of conventional practice. Results revealed that the cellulolytic bacterial diversity was found to be significantly higher under ZT practice, but the present population may not be sufficient for effective recycling of organic wastes in this system. Out of 290 bacterial isolates, 20 isolates had significantly higher cellulolytic activities, of which the top three superior isolates were received from ZT practice. The cellulolytic bacterial diversity based on 16S rDNA sequencing data revealed that the Firmicutes was the most dominant phyla and the Bacillus spp. were the common genus, the observation also showed that there were 17 different haplotypes were recorded among 20 isolates of cellulolytic bacteria. The present findings indicated that long-term ZT in the rice-pulse system could be a unique source for efficient cellulose decomposing bacteria and further the efficient bacterial strains isolated from this system can be used as efficient bioinoculants for in situ as well as ex-situ decomposition of rice straw particularly in conservation agriculture.

Thermodynamic spectral and kinetic analysis of the removal of Cu(II) from aqueous solution by sodium carbonate treated rice husk.

A new adsorbent for removing copper ions from aqueous solutions has been developed and characterized. The present study deals with the sorption of Cu(II) from aqueous solution on chemically pretreated sodium carbonate-treated rice husk (SCRH). The physico-chemical characteristics of rice husks were investigated to analyze their suitability to adsorb Cu(II) ions from water and wastewater. The raw rice husk (RRH), SCRH and Cu(II) adsorbed rice husk were analyzed by SEM-EDAX analysis. FTIR spectroscopy was also applied to identify functional groups, capable of adsorbing metal ions. Batch kinetic studies were conducted for the adsorption of Cu(II) on SCRH. It has been observed that 92.9-96.0% removal of Cu(II) is achieved at 4.8 mg of Cu(II)/g of adsorbent, adsorbent dose of 10 g L-1 and initial Cu(II) concentration of 10 mg L-1 in a temperature range of 15-50 °C. It was observed that the adsorption of Cu(II) on SCRH followed pseudo second-order kinetic and time to achieve equilibrium was found to be 60 min. The maximum uptake (97%) of Cu (II) was observed at pH 6. In this paper, an attempt has also been made to develop simple and readily understandable thermodynamic parameters related to sorption process at the equilibrium for understanding the adsorption mechanism. The Gibbs free energy ΔG° values for the adsorption processes of Cu(II) at 15, 30, 40 and 50 °C were calculated as -6.16, -6.84, -8.01 and -8.53 kJ mol-1, respectively. The negative value of ΔG° indicates spontaneity of adsorption. The values of ΔH° and ΔS° for Cu(II) adsorption were calculated as 14.37 kJ mol-1 and 70.92 J K-1 mol-1, respectively. The activation energy for the adsorption of Cu(II) was found to be 9 kJ mol-1 which is a characteristic for diffusion limited processes.