Title
Diversity and pathogenicity of Lasiodiplodia and Neopestalotiopsis species associated with stem blight and dieback of blueberry plants in Peru
Date Issued
01 May 2020
Access level
metadata only access
Resource Type
journal article
Author(s)
Universidad Nacional de Piura
Publisher(s)
Springer
Abstract
The production of blueberry in Peru has been increasing over the last years. Dieback and stem blight of plants are the most prominent disease symptoms observed in blueberry orchards. This study evaluated the diversity and pathogenicity of Lasiodiplodia and Neopestalotiopsis species associated with dieback of blueberry plants in Peru. A collection of isolates was initially subjected to Microsatellite-primed PCR (MSP-PCR) fingerprinting and further characterised by sequence analyses of the rDNA internal transcribed spacer region (ITS), translation elongation factor 1-alpha (tef1-α) and β-tubulin (tub2). The phylogenetic analyses revealed the presence of Lasiodiplodia theobromae, L. laeliocattleyae and Neopestalotiopsis rosae. Lasiodiplodia laeliocattleyae and N. rosae are reported for the first time in blueberry plants associated with dieback and stem blight symptoms. Additionally, N. rosae is newly reported from Peru. Inoculation trials of blueberry plants confirmed the pathogenicity of Lasiodiplodia and Neopestalotiopsis species and revealed differences in aggressiveness among species and isolates.
Start page
89
End page
102
Volume
157
Issue
1
Language
English
OCDE Knowledge area
Protección y nutrición de las plantas
Ciencias de las plantas, Botánica
Biotecnología agrícola, Biotecnología alimentaria
Subjects
Scopus EID
2-s2.0-85084505985
Source
European Journal of Plant Pathology
ISSN of the container
09291873
Sponsor(s)
The authors are thankful to the Portuguese Foundation for Science and Technology (FCT/MCTES) for financing CESAM (UIDB/50017/2020 + UIDP/50017/2020) through national funds, and the PhD grant of Sandra Hilário (SFRH/BD/137394/2018). We wish to acknowledge Cátia Fidalgo (University of Aveiro, Portugal) for her valuable help with R Statistical Software.
The authors are thankful to the Portuguese Foundation for Science and Technology (FCT/MCTES) for financing CESAM (UIDB/50017/2020 + UIDP/50017/2020) through national funds, and the PhD grant of Sandra Hilário (SFRH/BD/137394/2018). We wish to acknowledge Cátia Fidalgo (University of Aveiro, Portugal) for her valuable help with R Statistical Software.
Sources of information:
Directorio de Producción Científica
Scopus