Analysis of Maize (Zea mays L.) Seedling Roots with the High-Throughput Image Analysis Tool ARIA (Automatic Root Image Analysis)

Abstract

The maize root system is crucial for plant establishment as well as water and nutrient uptake. There is substantial genetic and phenotypic variation for root architecture, which gives opportunity for selection. Root traits, however, have not been used as selection criterion mainly due to the difficulty in measuring them, as well as their quantitative mode of inheritance. Seedling root traits offer an opportunity to study multiple individuals and to enable repeated measurements per year as compared to adult root phenotyping. We developed a new software framework to capture various traits from a single image of seedling roots. This framework is based on the mathematical notion of converting images of roots into an equivalent graph. This allows automated querying of multiple traits simply as graph operations. This framework is furthermore extendable to 3D tomography image data. In order to evaluate this tool, a subset of the 384 inbred lines from the Ames panel, for which extensive genotype by sequencing data are available, was investigated. A genome wide association study was applied to this panel for two traits, Total Root Length and Total Surface Area, captured from seedling root images from WinRhizo Pro 9.0 and the current framework (called ARIA) for comparison using 135,311 single nucleotide polymorphism markers. The trait Total Root Length was found to have significant SNPs in similar regions of the genome when analyzed by both programs. This high-throughput trait capture software system allows for large phenotyping experiments and can help to establish relationships between developmental stages between seedling and adult traits in the future.

Genome-wide association studies of doubled haploid exotic introgression lines for root system architecture traits in maize (Zea mays L.)

“…Roots were scanned using a flatbed scanner (EPSON Expression 10000 XL, Copyright © 2000-2014 Epson America, Inc.). Seedling root traits were measured using ARIA image analysis software [20]. If data collection could not be completed in a single day, seedlings were preserved by submerging the roots in 30% ethanol and storing them in a cold room (4°C) to prevent further growth.…”

“…Evaluation of root traits from seedlings grown in paper rolls, allows screening for a large number of lines quickly and more precisely, especially with the availability of root imaging software (e.g., ARIA [20], WinRhizo (Regent Instruments), or DIRT [40]). We found a moderate to strong positive (r between 0.42-0.63) and significant correlation (P < .0001) between root (length, area, dry weight) and shoot (length, dry weight) traits (Table 3).…”

Deploying Fourier Coefficients to Unravel Soybean Canopy Diversity

“…Once segmentation was done, the connected components labeling method (Suzuki et al, 2003; Gonzales and Woods, 2008; Wodo et al, 2012; Samudrala et al, 2013; Pace et al, 2014) was used on the processed image to remove spurious outliers and noise from the image (e.g., plant debris on soil). This was accomplished by identifying clusters of pixels that connected to one another, followed by labeling them, and identifying the largest connected component (i.e., plants in a plot).…”

Combining Ability and Heterosis of Maize Genotypes under Water Stress during Seed Germination and Seedling Emergence

“…The study of heterosis and the estimation of GCA and SCA related to seeds quality requires little time and space, is easy and quick to evaluate, and may be repeated as many times as needed to assist breeding programs (Meeks et al, 2013;Pace et al, 2014). The study of heterosis and the estimation of GCA and SCA related to seeds quality requires little time and space, is easy and quick to evaluate, and may be repeated as many times as needed to assist breeding programs (Meeks et al, 2013;Pace et al, 2014).…”