Biocontrol and ecophysiological characterization of bacterial and yeast BCA candidates isolated from two different environments to control postharvest diseases

Abstract

Biocontrol agents are a sustainable alternative to chemical fungicides in postharvest protection. Part of their success depends on using strains able to persistently colonize the host and maintain a broad activity from the field to the storage facilities. In this report, we evaluated 213 potential biocontrol agents (124 bacteria, 78 yeasts, and 11 filamentous fungi) isolated from two contrasting environments, the Pyrenees Mountains and the Ebro Valley (Catalonia, Spain). Their efficacy was tested against the three main postharvest pathogens of apples: Penicillium expansum, Botrytis cinerea, and Rhizopus stolonifer. The results showed that 4 bacteria and 25 yeast strains were effective against these pathogens, reducing their incidence by more than 75 %. From these results, two Pantoea agglomerans and two Vishniacozyma carnescens were further studied in terms of growth at different temperatures and water availability in vitro and their persistence on apple surfaces. The ecophysiological characterization showed that the valley P. agglomerans strain tolerated lower water activities better than the mountain strain, suggesting adaptation to the region’s hot and dry climate. In contrast, the mountain V. carnescens performed better at low temperatures, while the valley strain showed superior growth at 30 ºC, consistent with their respective environmental origins. In conclusion, these results indicated the need to consider the environmental adaptability of potential biocontrol agents when searching for new BCA strains.

This work has been financially supported by the Spanish ‘Agencia Estatal de Investigación’ (AEI) and the European Regional Development Fund (ERDF) through the national project PID2020–117607RR-I00 (ENVIRONAPPLE). This work has been also supported by the 2021 SGR 01477 grant and the CERCA Programme from the ‘Generalitat de Catalunya’. Thanks, are also given to the University of Lleida and IRTA for the predoctoral UdL-IRTA Sponsored Fellowship 2021 awarded to A.M. Sánchez Ruiz. We are grateful to Cèlia Sánchez for their logistic and technical support and Maribel Abadias for its support in the use of DMFIT.