Quantitative evaluation of Heterodera avenae females in soil and root extracts by digital image analysis

Abstract

Heterodera avenae and other cyst-producing nematode species are traditionally counted manually by visual inspection, a laborious and time consuming process. A method to detect and count cereal cyst nematodes based on image analysis techniques and statistical identification was designed and tested on H. avenae white females. Nematodes at the white female stage and free of soil particles were isolated from a contaminated wheat field. Known quantities of white females were mixed with different pre-treated background soil samples from non infested fields. Pre-treatment consisted of typical sieving and centrifugation procedures for white female extraction. Image analysis techniques were then used to detect, count and characterize white females in the mixtures. Over 96% of the H. avenae white females and substrate particles were correctly identified showing that a clear distinction can be drawn between the two groups. The results confirmed the validity of the proposed method to identify and count H. avenae females in backgrounds of different origins. This study establishes the basis for the design of a standardized method that is easily incorporated into a stand-alone system to facilitate the detection and quantification of nematode inoculum. This method can be applied to evaluate infestation level in crop fields and also to detect resistance/tolerance in breeding lines.