The use of specific parameters such as general (dehydrogenase activity) and specific enzymatic activities (protease, NAGase and chitinase activities) may be useful to predict compost suppressiveness against both pathogens. The selection of raw materials for agro-industrial composts is important in controlling Fusarium wilt and Phytophthora root rot.

Phytophthora root rot caused by Phytophthora nicotianae is an economically important disease in pepper crops. The use of suppressive composts is a low environmental impact method for its control. Although attempts have been made to reveal the relationship between microbiota and compost suppressiveness, little is known about the microorganisms associated with disease suppression. Here, an Ion Torrent platform was used to assess the microbial composition of composts made of different agro-industrial waste and with different levels of suppressiveness against P. nicotianae. Both bacterial and fungal populations responded differently depending on the chemical heterogeneity of materials used during the composting process. High proportions (67–75%) of vineyard pruning waste were used in the most suppressive composts, COM-A and COM-B. This material may have promoted the presence of higher relative abundance of Ascomycota as well as higher microbial activity, which have proved to be essential for controlling the disease. Although no unique fungi or bacteria have been detected in neither suppressive nor conducive composts, relatively high abundance of Fusarium and Zopfiella were found in compost COM-B and COM-A, respectively. To the best of our knowledge, this is the first work that studies compost metabolome. Surprisingly, composts and peat clustered together in principal component analysis of the metabolic data according to their levels of suppressiveness achieved. This study demonstrated the need for combining the information provided by different techniques, including metagenomics and metametabolomics, to better understand the ability of compost to control plant diseases.

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These results suggest that dPCR is a promising alternative for quantifying soil-borne pathogens in environmental samples, even in early stages of the disease.

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