Microbiomics and cloud-based analytics advance sustainable soil management

Das, Anupam; Ravinath, Renuka; Shilpa, Budiyal Ramesh; Rohith, Bilgi Sampgod; Goyal, Arvind Kumar; Shilpa, Nijalingappa Ramesh; Prasannakumar, M. K.; Prasannakumar, Hemavathy Ekambaram; Ekambaram, Hemavathy; Usha, Talambedu; Middha, Sushil Kumar

doi:10.2741/4903

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…The advanced Illumina Novaseq 6000 (Illumina) offers a unique possibility to perform soil microbial characterization [38,39]. Despite the large data outputs from these platforms, bioinformatics analysis of the data employing server and cloud-based analytics services have enhanced the speed and efficiency of analysis [40]. There are limited studies on the phytopathogen Fusarium oxysporum prevalence and associated genomic information with respect to Fusarium wilt in pomegranate.…”

Section: Introductionmentioning

confidence: 99%

Microbiome Analysis of the Rhizosphere from Wilt Infected Pomegranate Reveals Complex Adaptations in Fusarium—A Preliminary Study

Das

Ravinath

Usha³

et al. 2021

Agriculture

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Wilt disease affecting pomegranate crops results in rapid soil-nutrient depletion, reduced or complete loss in yield, and crop destruction. There are limited studies on the phytopathogen Fusarium oxysporum prevalence and associated genomic information with respect to Fusarium wilt in pomegranate. In this study, soil samples from the rhizosphere of different pomegranate plants showing early stage symptoms of wilt infection to an advanced stage were collected from an orchard situated in Karnataka, India. A whole metagenome sequencing approach was employed to gain insights into the adaptations of the causative pathogen F. oxysporum. Physicochemical results showed a drop in the pH levels, N, Fe, and Mn, and increase in electrical conductivity, B, Zn, Cl, Cu was observed in the early and intermediate stage samples. Comparative abundance analysis of the experimental samples ESI and ISI revealed an abundance of Proteobacteria phyla Achromobacter sp. 2789STDY5608625, Achromobacter sp. K91, and Achromobacter aegrifaciens and Eukaryota namely Aspergillus arachidicola, Aspergillus candidus, and Aspergillus campestris. Functional pathway predictions implied carbohydrate binding to be significant (p < 0.05) among the three experimental samples. Microbiological examination and whole microbiome analysis confirmed the prevalence of F. oxysporum in the soil samples. Variant analysis of F. oxysporum revealed multiple mutations in the 3IPD gene with high impact effects. 3-Isopropylmalate dehydratase and carbohydrate-active enzymes could be good targets for the development of antifungals that could aid in biocontrol of F. oxysporum. The present study demonstrates the capabilities of the whole metagenome sequencing approach for rapid identification of potential key players of wilt disease pathogenesis wherein the symptomatology is complex.

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Section: Introductionmentioning

confidence: 99%

Microbiome Analysis of the Rhizosphere from Wilt Infected Pomegranate Reveals Complex Adaptations in Fusarium—A Preliminary Study

Das

Ravinath

Usha³

et al. 2021

Agriculture

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“…Suppose that the dataset is observations on n variables and the variable G is a directed acyclic graph. Given the topology G, the variable G ϑ is the value of the parameter corresponding to the variable G. Therefore, the prior knowledge about G can be represented by the probability distribution P (G) [9] . When the value of G is a certain value, G ϑ is represented by another probability distribution.…”

Section: Network Security Posture Indicator Fusionmentioning

confidence: 99%

A cloud-based approach to network security situational awareness

Yang

Chen

2023

International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022)

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The traditional network security situational awareness method obtains the clustering results of network behavior analysis by using adaptive weight clustering algorithm, which leads to poor perception due to the lack of fusion of situational indicators. In this regard, a cloud computing-based network security situational awareness approach is proposed. By using Hadoop cloud computing network platform to collect security posture information and establish Bayesian network to fuse network security posture indicators and construct a posture perception model. In the experiments, the proposed method is verified for the perception effect. The analysis of the experimental results shows that the proposed method is used for network security situational awareness of network data, and the perception is less time-consuming and has a more excellent performance of network security situational awareness.

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