Updated Methods for Seed Shape Analysis

Cervantés, Emilio; Martín, José Javier; Saadaoui, Ezzeddine

doi:10.1155/2016/5691825

Cited by 95 publications

(99 citation statements)

References 33 publications

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“…Furthermore, we opened new window for the seed color data collection which was very difficult to measure in an objective manner. These results could be applied to various analysis for shapes which are well addressed by Bianco et al [23] and Cervantes et al [24] for seed traits. Eventually, the accurate phenotypic data produced using the method of analysis presented in this research will produce would help to search the gene locus for the target through Genome Wide Association Study (GWAS).…”

Section: Discussionmentioning

confidence: 81%

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Baek

Lee

Kim

et al. 2020

Sensors

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Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits.

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Section: Discussionmentioning

confidence: 81%

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Baek

Lee

Kim

et al. 2020

Sensors

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“…This study support the utility of seed surface characteristics as distinctive character for species identification. According to Cervantes, Martín, and Saadaoui (), the procedure of digital techniques, along with the advance of quantification and modeling methods, suggests methods for an improved account about seeds morphology. Our results by consistency with the results by Kanwal et al () and Sadeghian et al () in family Caryophyllaceae.…”

Section: Discussionmentioning

confidence: 99%

Seed micromorphology and its taxonomic evidence in subfamily Alsinoideae (Caryophyllaceae)

Ullah

Papini

Shah

et al. 2018

Microscopy Res & Technique

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Seed micromorphology of 13 species, belonging to four genera of subfamily Alsinoideae (Caryophyllaceae) were investigated with scanning electron microscopy (SEM), in order to assess their diagnostic significance at generic level and provide additional evidence on species delimitation, as well as correct identification and phylogenetic position. Genera and species of subfamily Alsinoideae exhibit great variation in ultrastructure and a high diversity of novel micromorphological characters were observed. Variation in seed shape, color, hilum, anticlinal wall, epidermal cell, cell surface, margins, and quantitative characters as length and width were studied in detail, compared, illustrated, and their taxonomic significant were discussed. Seed shapes of the species were classified as reniform, round, angular, subcircular, subreniform, and elliptical pyriform, with sub‐central, central, basal, and nearly basal hilum. Wavy, irregular, tetragonal, and elongated epidermal cells structure has been observed as an exomorphological character. The present findings show that the micromorphology of subfamily Alsinoideae provides taxonomic information and is helpful to distinguish different species. The results also explained that SEM morphology of seeds provide important data about affinity among taxa and give potential characters in delimitation of members of subfamily Alsinoideae at generic and species level. A principal component analysis allowed to highlight the most outsiders among seed micromorphology with a possible explanation. Taxonomic keys were developed based on micromorphological characters to delimit the species and useful for their quick identification within subfamily Alsinoideae.

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“…Updates of these methods appear constantly, including in recent years (Smykalova et al, 2013; Whan et al, 2014; Miller et al, 2016; Sankaran et al, 2016). New methods use various optical sensing techniques to estimate seed quality and safety (Huang et al, 2015), describe complex seed shapes using 2D images (Williams et al, 2013; Cervantes et al, 2016). Breakthrough 3D imaging technology and robotics (Jahnke et al, 2016; Roussel et al, 2016) or X-ray computed tomography (Strange et al, 2015) implemented for evaluating seed shape in fine detail.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping

2017

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Grain morphometry in cereals is an important step in selecting new high-yielding plants. Manual assessment of parameters such as the number of grains per ear and grain size is laborious. One solution to this problem is image-based analysis that can be performed using a desktop PC. Furthermore, the effectiveness of analysis performed in the field can be improved through the use of mobile devices. In this paper, we propose a method for the automated evaluation of phenotypic parameters of grains using mobile devices running the Android operational system. The experimental results show that this approach is efficient and sufficiently accurate for the large-scale analysis of phenotypic characteristics in wheat grains. Evaluation of our application under six different lighting conditions and three mobile devices demonstrated that the lighting of the paper has significant influence on the accuracy of our method, unlike the smartphone type.

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Updated Methods for Seed Shape Analysis

Cited by 95 publications

References 33 publications

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Seed micromorphology and its taxonomic evidence in subfamily Alsinoideae (Caryophyllaceae)

Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping

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