%0 Generic
%A Mayerhofer, Johanna
%A Thuerig, Barbara
%A Oberhänsli, Thomas
%A Enderle, Eileen
%A Lutz, Stefanie
%A Ahrens, Christian H.
%A Fuchs, Jacques G.
%A Widmer, Franco
%D 2021
%F orgprints:42578
%K compost microbiome, amplicon sequencing, sequence variant, soil-borne pathogen, targeted strain isolation, suppressiveness, disease suppression, soil-borne diseases, Abacus, FiBL20068, diagnostics, Kompost, Düngung, Pflanzenschutz
%N 10
%P 1-15
%T Indicative bacterial communities and taxa of disease-suppressing and growth-promoting composts and their associations to the rhizoplane
%U https://orgprints.org/id/eprint/42578/
%V 97
%X Compost applications vary in their plant growth promotion and plant disease suppression, likely due to differences in physico-chemical and biological parameters. Our hypothesis was that bacteria are important for plant growth promotion and disease suppression of composts and, therefore, composts having these traits would contain similar sets of indicative bacterial taxa. Seventeen composts prepared from five different commercial providers and different starting materials were classified accordingly with bioassays using cress plants and the pathogen Pythium ultimum. Using a metabarcoding approach, bacterial communities were assessed in bulk composts and cress rhizoplanes. Six and nine composts showed significant disease suppression or growth promotion, respectively, but these traits did not correlate. Growth promotion correlated positively with nitrate content of composts, whereas disease suppression correlated negatively with factors representing compost age.  Growth promotion and disease suppression explained significant portions of variation in bacterial community structures, i.e. 11.5% and 14.7%, respectively. Among the sequence variants (SVs) associated with growth promotion, Microvirga, Acinetobacter, Streptomyces, Bradyrhizobium and Bacillus were highly promising, while in suppressive composts, Ureibacillus, Thermogutta and Sphingopyxis were most promising. Associated SVs represent the basis for developing prediction tools for growth promotion and disease suppression, a highly desired goal for targeted compost production and application.