67-13 Quantification of Soybean-Associated Rhizobia with Quantitative Real-Time Polymerase Chain Reaction.

Poster Number 162

See more from this Division: C03 Crop Ecology, Management & Quality
See more from this Session: C03 Graduate Student Poster Competition
Monday, November 1, 2010
Long Beach Convention Center, Exhibit Hall BC, Lower Level
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Branden Furseth, Shawn Conley and Jean-Michel Ané, University of Wisconsin-Madison, Madison, WI
The symbiotic relationship between soybean [Glycine max (L.) Merr.] and rhizobial bacteria such as Bradyrhizobium japonicum allows biological nitrogen fixation (BNF), which along with residual soil N, can meet the seasonal needs of a soybean crop. The widespread use of rhizobia inoculants to encourage BNF is not strongly supported by previous research. A high throughput, efficient method for quantifying rhizobia would be a valuable tool for assessing the need of inoculation on a case by case basis. Such a method is also needed for large-scale research on rhizobia populations in various environments and cropping systems. The objective of this study was to create a new method for quantifying soybean-specific rhizobia in the soil using quantitative (real-time) polymerase chain reaction (qPCR). Soil from 12 plots with presumably different rhizobia populations was collected from a long-term corn (Zea mays L.) -soybean rotation study near Arlington, WI and the most probable number (MPN) of rhizobia in the soil was determined. DNA from the soil was analyzed with qPCR using primers targeting the nodZ specificity gene for nodulation. The qPCR quantification was correlated to the MPN with a simple regression model. The relationship between MPN and qPCR was described by the equation CT =33.43-0.85(ln(MPN)), with an adjusted R2 of 0.88. These data allow for the prediction of soybean-associated rhizobia populations in the soil based on the qPCR analysis of extracted DNA.
See more from this Division: C03 Crop Ecology, Management & Quality
See more from this Session: C03 Graduate Student Poster Competition