Combining an initial risk assessment process with DNA assays to improve prediction of soilborne diseases caused by root-knot nematode (Meloidogyne spp.) and Fusarium oxysporum f. sp. lycopersici in the Queensland tomato industry

G. R. Stirling, D. Griffin, K. Ophel-Keller, A. McKay, D. Hartley, J. Curran, A. M. Stirling, C. Monsour, J. Winch and B. Hardie

Abstract

A two-step process was used to assess the risk of losses from root-knot nematode and Fusarium wilt in fields to be planted to tomatoes. The first step involved deciding well before planting whether the risk of disease was high enough to justify collecting soil samples to determine pathogen inoculum density. This interim assessment was done using information on the major factors likely to affect disease risk (i.e. cropping history, disease history, soil texture and expected temperature during the growing season), in order to calculate a hazard index (score between 0 and 50). Its value as a predictive tool was validated by relating the hazard index to actual disease incidence and severity in representative tomato fields. The usefulness of the hazard index was often found to be limited by a lack of reliable information on disease history. Nevertheless, it had some predictive value, as all sites with moderate infestations of root-knot nematode had hazard indexes greater than 40, and most sites with more than 3% Fusarium wilt had hazard indexes greater than 35. The second step in the prediction process involved using DNA tests to estimate inoculum densities of Fusarium oxysporum f. sp. lycopersici and root-knot nematode in soil collected before planting. Experiments in pots and in the field confirmed that the incidence and severity of both diseases was related to pre-plant inoculum density. The DNA test for root-knot nematode was useful from a practical point of view as it detected nematode populations capable of causing economically damaging levels of galling at harvest. However, the test for F. oxysporum f. sp. lycopersici was not sensitive enough to always detect the pathogen in soils where 4–10% of plants were diseased.

Keywords: disease management, IPM.

Australasian Plant Pathology 33(2) 285 - 293 (2004) doi:10.1071/AP04004