EconPapers    
Economics at your fingertips  
 

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

Riccardo Scotti, Alex L. Mitchell, Catello Pane, Rob D. Finn and Massimo Zaccardelli
Additional contact information
Riccardo Scotti: CREA Research Centre for Vegetable and Ornamental Crops, 84098 Pontecagnano Faiano (Salerno), Italy
Alex L. Mitchell: EMBL-EBI European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
Catello Pane: CREA Research Centre for Vegetable and Ornamental Crops, 84098 Pontecagnano Faiano (Salerno), Italy
Rob D. Finn: EMBL-EBI European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
Massimo Zaccardelli: CREA Research Centre for Vegetable and Ornamental Crops, 84098 Pontecagnano Faiano (Salerno), Italy

Agriculture, 2020, vol. 10, issue 3, 1-17

Abstract: 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.

Keywords: metagenomics; 16S rDNA; 18S rDNA; Whole genome shotgun sequencing; microbiome; sustainable agriculture (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/10/3/61/pdf (application/pdf)
https://www.mdpi.com/2077-0472/10/3/61/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:10:y:2020:i:3:p:61-:d:328053

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jagris:v:10:y:2020:i:3:p:61-:d:328053