However, it does not extract seed color information ( Tanabata et al., 2012). For example, SmartGrain determines seed morphometrics such as area, perimeter, length, and width, as well as seed shape. Keeping in view the importance of seed size and color, several seed image analysis applications have been developed. Furthermore, the red pigmented wheat, which is resistant to pre-harvest sprouting, has been extensively targeted in wheat breeding programs ( Groos et al., 2002). In addition to their medicinal properties, colored rice varieties hold cultural significance for certain regions and are consequentially valued in the respective local markets ( Finocchiaro et al., 2007). Similarly, pigmented maize seeds offer several beneficial effects on human health due to their antioxidant properties ( Casas et al., 2014 Petroni et al., 2014). For instance, colored rice varieties carry antioxidant properties, which are known to decrease the risks involved with developing cardiovascular diseases ( Ling et al., 2001). Within this framework, seed color can be associated with enhanced nutrition ( Shao et al., 2011 and references therein). Qualitative assessment of the yield-related traits can also be important to ensure optimal nutritional values of seeds ( Zhao et al., 2020). Moreover, high-throughput image analysis provides a powerful tool for trait discovery that facilities a more rapid input into downstream analysis such as genome-wide association studies (GWAS) for performing genetic mapping of yield-related traits.
#Matlab 2009 random seed manual
In contrast, imaging-based automated platforms that are tailored to accurately measure seed parameters offer an efficient solution to mitigate time constraints, seed amount issues, and circumvent manual errors ( Furbank and Tester, 2011 Fiorani and Schurr, 2013 Sandhu et al., 2019 Yang et al., 2020). Mechanized seed size measuring equipment is expensive, requires regular calibration, and often needs large amounts of seeds to run through the system. Manual measurements of seed size provide evidence of restricted parameters such as length and width at a low resolution, which can be error-prone and time-consuming. In this context, obtaining precise measurements of seed size and seed shape is critical to both breeding programs aimed at enhancing crop yields and facilitating fundamental research that is focused on discovering genetic components that regulate seed size. Thus, a large proportion of resources in crop improvement programs are invested toward better seeds. Most of the plant-based food that we eat is either seed or seed-derived products. In summary, we present a publicly available application that can be used to determine key yield-related traits in crops. We identified known loci for regulating seed length ( GS3) and width ( qSW5/GW5) in rice, which demonstrates the accuracy of this application to extract seed phenotypes and accelerate trait discovery. The derived seed-size traits, such as seed length, width, were used for genome-wide association analysis. We further validated the utility of this application by analyzing mature-rice seeds from 231 accessions in Rice Diversity Panel 1. The adaptability of SeedExtractor was demonstrated by analyzing scanned seeds from multiple crops.
#Matlab 2009 random seed software
As this software is open-source, it can be modified by users to serve more specific needs. In this context, our application takes ∼2 s for analyzing an image, i.e., significantly less compared to the other tools. To address this need, we have developed an open-source graphical user interface (GUI) software, SeedExtractor that determines seed size and shape (including area, perimeter, length, width, circularity, and centroid), and seed color with capability to process a large number of images in a time-efficient manner. Accurate measurement of seed size parameters is essential for both breeding efforts aimed at enhancing yields and basic research focused on discovering genetic components that regulate seed size.