Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 553961
Title Mapping European canker spatial pattern and disease progression in apples using GIS, Tasman, New Zealand
Author(s) Iorio, Diletta Di; Walter, Monika; Lantinga, Egbert; Kerckhoffs, Huub; Campbell, Rebecca E.
Source New Zealand Plant Protection 72 (2019). - ISSN 1175-9003 - p. 176 - 184.
DOI https://doi.org/10.30843/nzpp.2019.72.305
Department(s) BBF Team Randwijk
OT Team Fruit-Bomen
PE&RC
Farming Systems Ecology
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) Apple - Disease progression - European canker - Geographical Information Systems - GIS - Hot-spots - Neonectria ditissima - Spatial - Temporal
Abstract

European canker (EC), caused by Neonectria ditissima, is an important disease in apple-producing regions in New Zealand. In order to improve plant protection, Geographic Information Systems (GIS) can be used to map plant disease location and severity in agricultural settings. Data were compiled from apple growers in Tasman, New Zealand, to investigate EC distribution over 4 years, for the period 2015–2018. ArcGIS software, including the Spatial Analyst, Interpolation and Geospatial statistics toolboxes, was used to map EC incidence at the spatial scale of orchard blocks, which allowed the identification of disease hot-spots. A clustered spatial pattern of disease was detected every year and areas with higher risk of EC were identified within the region. The spatial patterns detected were related to disease pressure over time for different apple cultivars. The use of GIS provides a platform for analysing and visually communicating disease patterns over time. Investigating disease spatial pattern allows the inference of spatial processes and further hypothesis generation to understand the pathogen.

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