Automatic discrimination of fine roots in minirhizotron images.
Minirhizotrons provide detailed information on the production, life history and mortality of fine roots. However, manual processing of minirhizotron images is time-consuming, limiting the number and size of experiments that can reasonably be analysed. Previously, an algorithm was developed to automatically detect and measure individual roots in minirhizotron images. Here, species-specific root classifiers were developed to discriminate detected roots from bright background artifacts. Classifiers were developed from training images of peach (Prunus persica), freeman maple (Acer x freemanii) and sweetbay magnolia (Magnolia virginiana) using the Adaboost algorithm. True- and false-positive rates for classifiers were estimated using receiver operating characteristic curves. Classifiers gave true positive rates of 89-94% and false positive rates of 3-7% when applied to nontraining images of the species for which they were developed. The application of a classifier trained on one species to images from another species resulted in little or no reduction in accuracy. These results suggest that a single root classifier can be used to distinguish roots from background objects across multiple minirhizotron experiments. By incorporating root detection and discrimination algorithms into an open-source minirhizotron image analysis application, many analysis tasks that are currently performed by hand can be automated.
Department of Electrical and Computer Engineering, Clemson University, Clemson SC 29634, USA.
Guang
G
Zeng
Department of Electrical and Computer Engineering, Clemson University, Clemson SC 29634, USA.
Stanley T
ST
Birchfield
Department of Horticulture, Clemson University, Clemson SC 29634, USA.
Christina E
CE
Wells
D031002:Acer / Q000033:anatomy & histology*; D000465:Algorithms; D031566:Magnolia / Q000033:anatomy & histology*; D018517:Plant Roots / Q000033:anatomy & histology* / Q000254:growth & development; D027861:Prunus / Q000033:anatomy & histology*; D012984:Software