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Microbiota Characterization of Agricultural Green Waste-Based Suppressive Composts Using Omics and Classic Approaches

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CREA Research Centre for Vegetable and Ornamental Crops, 84098 Pontecagnano Faiano (Salerno), Italy
2
Quadram Institute Bioscience, Norwich Research Park, Norwich NR4 7UQ, UK
3
EMBL-EBI European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
*
Author to whom correspondence should be addressed.
Agriculture 2020, 10(3), 61; https://doi.org/10.3390/agriculture10030061
Received: 30 December 2019 / Revised: 18 February 2020 / Accepted: 28 February 2020 / Published: 4 March 2020
(This article belongs to the Special Issue Composting and Organic Soil Amendments)
While the control of soil-borne phytopathogenic fungi becomes increasingly difficult without using chemicals, concern over the intensive use of pesticides in agriculture is driving more environmentally sound crop protection managements. Among these approaches, the use of compost to suppress fungal diseases could have great potential. In this study, a multidisciplinary approach has been applied to characterize microbiota composition of two on-farm composts and assess their suppress and biostimulant activities. The on-farm composting system used in this study was able to produce two composts characterized by an antagonistic microbiota community able to suppress plant pathogens and biostimulate plant growth. Our results suggest a potential role for Nocardiopsis and Pseudomonas genera in suppression, while Flavobacterium and Streptomyces genera seem to be potentially involved in plant biostimulation. In conclusion, this study combines different techniques to characterize composts, giving a unique overview on the microbial communities and their role in suppressiveness, helping to unravel their complexity. View Full-Text
Keywords: metagenomics; 16S rDNA; 18S rDNA; Whole genome shotgun sequencing; microbiome; sustainable agriculture metagenomics; 16S rDNA; 18S rDNA; Whole genome shotgun sequencing; microbiome; sustainable agriculture
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Scotti, R.; Mitchell, A.L.; Pane, C.; Finn, R.D.; Zaccardelli, M. Microbiota Characterization of Agricultural Green Waste-Based Suppressive Composts Using Omics and Classic Approaches. Agriculture 2020, 10, 61.

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