SmartGrain: High-Throughput Phenotyping Software for Measuring Seed Shape through Image Analysis      

Abstract

Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.

phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds

“…Projected area is measured either by microscopic analyses (Alonso-Blanco et al, 1999) or quite often by scanning methods (de Jong et al, 2011;Tanabata et al, 2012;Moore et al, 2013). For 11 natural accessions of Arabidopsis, a quite good correlation (r 2 = 0.8879) of A with average seed weight has been reported (Herridge et al, 2011).…”

“…Seed mass can be measured individually (Stanton, 1984), but it is generally collected as an average value of batches of 50 to 1,000 seeds (Jako et al, 2001;Jofuku et al, 2005;Montesinos-Navarro et al, 2011;Tanabata et al, 2012). Alternatively, 2D scans are analyzed to determine parameters such as seed length, width, area, and perimeter length as a measure for seed size (Tanabata et al, 2012).…”

“…Alternatively, 2D scans are analyzed to determine parameters such as seed length, width, area, and perimeter length as a measure for seed size (Tanabata et al, 2012). This approach can be implemented in high-throughput facilities to obtain projected areas of seed grains combined with genome-wide association studies (Yang et al, 2014).…”

“…This approach can be implemented in high-throughput facilities to obtain projected areas of seed grains combined with genome-wide association studies (Yang et al, 2014). Although projected seed area can easily be measured with a common office scanner (Herridge et al, 2011;Tanabata et al, 2012;Moore et al, 2013), it is not necessarily a precise or reliable measure of the true seed size because it may depend on the shape (Alonso-Blanco et al, 1999) and the orientation of a seed at scan (see "Results"). These issues also apply when using 2D projections to calculate length-to-width ratios as a simple shape factor (Tanabata et al, 2012).…”

“…Although projected seed area can easily be measured with a common office scanner (Herridge et al, 2011;Tanabata et al, 2012;Moore et al, 2013), it is not necessarily a precise or reliable measure of the true seed size because it may depend on the shape (Alonso-Blanco et al, 1999) and the orientation of a seed at scan (see "Results"). These issues also apply when using 2D projections to calculate length-to-width ratios as a simple shape factor (Tanabata et al, 2012). Projected seed area also has been used to calculate seed mass, assuming a fixed relationship between these parameters (de Jong et al, 2011;Herridge et al, 2011).…”