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Elsevier, Computers and Electronics in Agriculture, (85), p. 112-122

DOI: 10.1016/j.compag.2012.02.011

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A knowledge-based prediction model of Verticillium wilt on potato and its use for rational crop rotation

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Verticillium dahliae is the major causal agent of potato early dying (PED) syndrome, characterized by stunting, chlorosis and wilting, premature senescence and early plant dying. It is a common practice to reduce the risk of Verticillium wilt (VW) by applying a rational crop rotation. A knowledge based prediction model for VW was developed and validated. It was based on experimental data and practical management experience, and utilized a knowledge-based approach to acquire the expert knowledge. The potential contribution of this approach was demonstrated in the process of knowledge acquisition and in the model development. The experts identified eight major factors that affect disease development (in descending order of importance): inoculum level in the soil, cultivar susceptibility, fumigation history, frequency of susceptible crops within a crop rotation, growing season, fallow seasons within a crop rotation, infection level in the tubers and soil type. The procedure used for selecting the factors