Quantification of belowground plant response via rhizotron root image analysis is difficult and time-consuming, yet a plant's root response is of great interest to many researchers. Here, we present an automated, time efficient method for examining digital rhizotron images. A total of 285 digital images (218 mm by 300 mm) were collected using a flatbed scanner from 16 rhizotron boxes from an experiment designed to evaluate the root response of Dalmatian toadflax, Linaria dalmatica (L.) Miller to herbivory by the Dalmatian toadflax stem mining weevil, Mecinus janthinus Germar, a widely used biological control agent. Images were quantified for root length and area using two methods: manually digitizing images using Root Measurement System (RMS) software, and semi-automated analysis using Feature Analyst^TM, an extension for a geographic information system. Feature Analyst length and area values were highly positively correlated with RMS area values, but were not correlated with RMS length measurements. The semi-automated Feature Analyst approach required one-eighth of the time required to analyze images using the manual RMS method. Feature Analyst for digital image analysis warrants more investigation, but appears to be a promising method for quantifying belowground plant characteristics.