SOIL BIOASSAY AS A DIAGNOSTIC TOOL IN THE DETECTION OF SOIL- BORNE PATHOGENS OF COMMON BEAN (Phaseolus vulgaris) IN WESTERN KENYA

Abstract

Lack of accurate and precise diagnostic tools and methods for detecting soil pathogens and their impacts on crop yields hinders the productivity of various crops, including beans. This highlights the need to link field disease severities to bioassay results to ease not only the accuracy in detection but also ensure the reliability of the predictions of crop performance. The study was set to evaluate the effectiveness of existing soil bioassays for screening,

detecting, and quantifying soil-borne pathogens (Fusarium spp., Pythium spp., and root- knot nematode) and predicting impacts on grain yields and severity levels in smallholder

fields. The study was conducted in 50 farmer fields in five counties across Western Kenya. Field demonstration trials consisting of four bean varieties planted on the 4 by 4 m treatment plots were established in each of the five sites. At planting, soil samples were collected for physical and biochemical analysis. A subset of the soil samples was bulked at the field level and assessed for bioassays targeting Fusarium, Pythium, and plant parasitic nematodes. The bean varieties were assessed for disease severities, and agronomic indicators recorded. The study employed descriptive statistics, correlation analysis, and stepwise linear regression using R software. Pearson’s correlation coefficient (r) indicated a significant but weak negative relationship between the Fusarium stem assay and vascular browning (r= -0.27, p = 0.0091). In addition, Pythium seed assay had no association with field root rot severity, while the root knot nematode assay showed a marginally significant but weak positive relationship with field galling infestation (r = 0.14, p = 0.05). Also, a strong negative correlation between vascular browning and bean yield (r = -0.28, p< 0.001), and between disease pressure and yield (r = -0.22, p < 0.001) was observed. A stepwise linear regression model revealed that the interaction between Fusarium stem assay infestation and pH influenced vascular browning (p< 0.001) and stand count (p< 0.01). Similarly, the interaction of Pythium seed assay infestation with POXC significantly affected stand count (p< 0.001), and the association between Root knot nematode assay infestation and stand count was influenced by soil clay content (p< 0.001). Apart from the Root knot nematode assay, the soil pathogen bioassays tested here were not effective in predicting the field incidence. However, our findings revealed the ability of the fusarium stem assay to predict other symptoms associated with disease pressure, suggesting that the bioassays result together with soil fertility assessment can led to a more effective prediction of early disease pressure and yield.