93-6 Automated X-Ray Image Analysis Methods for Investigating Root Architecture of Corn Rootworm Resistant and Susceptible Maize Varieties.



Monday, October 17, 2011: 2:15 PM
Henry Gonzalez Convention Center, Ballroom C-1, Ballroom Level

Kenton E. Dashiell1, Deirdre A. Prischmann-Voldseth2, Daniel W. McDonald3, Ronald B. Michaels3, Robert J. Kodrzycki4, Nancy L. West3, Jeremy R. Allbright3 and David J. Schneider5, (1)Tropical Soil Biology and Fertility (TSBF) Institute of the International Center for Tropical Agriculture, Nairobi, Kenya
(2)Entomology, North Dakota State University, Fargo, ND
(3)Phenotype Screening Corporation, Knoxville, TN
(4)Encompass Biotech LLC, Summerville, SC
(5)North Central Agricultural Research Laboratory, Brookings, SD
Six replicates of four varieties of maize were grown and their root systems non-destructively imaged over a seven week period using low-energy X-ray technology.  The resulting X-ray images were analyzed with novel image processing techniques to characterize each plant’s root architecture as it developed over time.  Two of the varieties are known to be susceptible to western corn rootworm (Diabrotica virgifera virgifera) larval feeding while the other two are considered resistant to this subterranean insect pest. Because of the unique nature of X-ray imaging the entire root volume can be captured in one picture. X-ray imaging also allows additional information to be extracted from the images which would be hidden with standard reflective imaging techniques.  The number of roots, root depth, density, complexity, diameters and root mass distribution were traits automatically extracted from the X-ray images.  Inter- and intra-variations in root architecture were determined among the varieties studied.  Special emphasis was placed upon the distribution of fine roots (< 2 mm) throughout the root volume over time as these are suspected to be the preferred feeding sites of the corn rootworm larvae.  The results of the automated analysis are presented and the challenges of using automated methods for capturing and quantifying root traits in situ are discussed.
See more from this Division: C02 Crop Physiology and Metabolism
See more from this Session: General Crop Physiology & Metabolism: I