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Probability Models Based on Soil Properties for Predicting Presence-Absence of Pythium in Soybean Roots

  • Fungal Microbiology
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Abstract

Associations between soil properties and Pythium groups on soybean roots were investigated in 83 commercial soybean fields in North Dakota. A data set containing 2877 isolates of Pythium which included 26 known spp. and 1 unknown spp. and 13 soil properties from each field were analyzed. A Pearson correlation analysis was performed with all soil properties to observe any significant correlation between properties. Hierarchical clustering, indicator spp., and multi-response permutation procedures were used to identify groups of Pythium. Logistic regression analysis using stepwise selection was employed to calculate probability models for presence of groups based on soil properties. Three major Pythium groups were identified and three soil properties were associated with these groups. Group 1, characterized by P. ultimum, was associated with zinc levels; as zinc increased, the probability of group 1 being present increased (α = 0.05). Pythium group 2, characterized by Pythium kashmirense and an unknown Pythium sp., was associated with cation exchange capacity (CEC) (α < 0.05); as CEC increased, these spp. increased. Group 3, characterized by Pythium heterothallicum and Pythium irregulare, were associated with CEC and calcium carbonate exchange (CCE); as CCE increased and CEC decreased, these spp. increased (α = 0.05). The regression models may have value in predicting pathogenic Pythium spp. in soybean fields in North Dakota and adjacent states.

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Acknowledgements

This research was funded by the North Dakota Soybean Council. This work was supported by the USDA National Institute of Food and Agriculture, Hatch projects ND02223 and ND02226.

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Authors and Affiliations

  1. Department of Plant Pathology, North Dakota State University, Fargo, ND, USA

    Kimberly K. Zitnick-Anderson, Luis E. del Río Mendoza & Berlin D. Nelson Jr

  2. Natural Resources Management, North Dakota State University, Fargo, ND, USA

    Jack E. Norland

  3. Department of Soil Science, North Dakota State University, Fargo, ND, USA

    Ann-Marie Fortuna

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  1. Kimberly K. Zitnick-Anderson
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  2. Jack E. Norland
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  3. Luis E. del Río Mendoza
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  5. Berlin D. Nelson Jr
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Correspondence to Berlin D. Nelson Jr.

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Zitnick-Anderson, K.K., Norland, J.E., del Río Mendoza, L.E. et al. Probability Models Based on Soil Properties for Predicting Presence-Absence of Pythium in Soybean Roots. Microb Ecol 74, 550–560 (2017). https://doi.org/10.1007/s00248-017-0958-2

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