Root phenotypic detection of different vigorous maize seeds based on Progressive Corrosion Joining algorithm of image

BACKGROUND: The root phenotypes of different vigorous maize seeds vary a lot. Imaging roots of growing maize is a non-invasive, affordable and high throughput approach. However, it’s difficult to get integral root images because of the block of the soil. The paper proposed an algorithm to repair incomplete root images for maize root fast non-invasive phenotyping detection. RESULTS: A two-layer transparent stress growth device with two concentric cylinders was developed as mesocosms and the maize seeds were planted in the annulus of it. The maize roots grow in soil against two acrylic plastic surfaces due to the press of the small growing area to acquire more root details during roots visualization and imaging. Even though, parts of the roots are occluded which means that it’s tough to extract the information of root general physical construction. For recovering gaps from disconnected root segments, Progressive Corrosion Joining (PCJ) algorithm was proposed based on the physiological characteristics of hydrotropism, geostrophic and continuity with three steps which are root image thinning, progressive corrosion and joining processing respectively. The experiments indicate that maize phenotyping parameters are negative correlation with seed aging days. And specifically, Root Number (RTN), Root Length (RTL), Root Width (RTW) and Root Extension Length (REL) of unaged and 14-day-aged maize seeds are decreased from 15.40, 82.40 mm, 1.53 mm and 82.20 mm to 4.58, 38.6 mm, 1.35 mm and 55.20 mm, and the growing speed of them are changed from 1.68 per day, 8.80 mm/d, 0.06 mm/d, 9.0 mm/d to 0.70 per day, 4.3 mm/d, 0.05 mm/d and 5.70 mm/d respectively. Whereas Root Extension Angle (REA) is basically irrelevant with the level of maize seed aging. CONCLUSION: The developed double-layer Annular Root Phenotyping Container (ARPC) can satisfy the general physical construction of maize as well as push each root growing along the inner wall of the container which help to acquire more root information. The presented novel PCJ algorithm can recover the missing parts, even for big gaps, of maize roots effectively according to root morphological properties. The experiments show that the proposed method can be applied to evaluate the vigor of maize seeds which has vast application prospect in high throughput root phenotyping area.