Original leaf images are deposited into https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZPGVPP ; https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QLXGBG ; and https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/29PJR1 for public access.
Open resource ↗dataverse.harvard.edu · doi:10.7910/DVN/ZPGVPP · lines:40-52Unverified paper record
LeafletAnalyzer, an Automated Software for Quantifying, Comparing and Classifying Blade and Serration Features of Compound Leaves during Development, and among Induced Mutants and Natural Variants in the Legume Medicago truncatula .
Frontiers in plant science · 31 May 2017 · 10.3389/fpls.2017.00915
Abstract
Diverse leaf forms ranging from simple to compound leaves are found in plants. It is known that the final leaf size and shape vary greatly in response to developmental and environmental changes. However, changes in leaf size and shape have been quantitatively characterized only in a limited number of species. Here, we report development of LeafletAnalyzer, an automated image analysis and classification software to analyze and classify blade and serration characteristics of trifoliate leaves in Medicago truncatula . The software processes high quality leaf images in an automated or manual fashion to generate size and shape parameters for both blades and serrations. In addition, it generates spectral components for each leaflets using elliptic Fourier transformation. Reconstruction studies show that the spectral components can be reliably used to rebuild the original leaflet images, with low, and middle and high frequency spectral components corresponding to the outline and serration of leaflets, respectively. The software uses artificial neutral network or k -means classification method to classify leaflet groups that are developed either on successive nodes of stems within a genotype or among genotypes such as natural variants and developmental mutants. The automated feature of the software allows analysis of thousands of leaf samples within a short period of time, thus facilitating identification, comparison and classification of leaf groups based on leaflet size, shape and tooth features during leaf development, and among induced mutants and natural variants.
Plant phenotyping relevance
葉の画像からサイズ・形状・鋸歯などの表現型を自動抽出・分類するソフトウェアの開発が中心であり、植物フェノタイピング手法に該当する。
abstractHere, we report development of LeafletAnalyzer, an automated image analysis and classification software to analyze and classify blade and serration characteristics of trifoliate leaves in Medicago truncatula .
abstractThe software processes high quality leaf images in an automated or manual fashion to generate size and shape parameters for both blades and serrations.
Code and data availability
The paper deposits original M. truncatula leaf images used for LeafletAnalyzer phenotyping in three public Harvard Dataverse datasets, and raw measured data are in Supplementary Files 1–3. No public code deposit for the LeafletAnalyzer software is stated.
Original leaf images are deposited into https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZPGVPP ; https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QLXGBG ; and https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/29PJR1 for public access.
Open resource ↗dataverse.harvard.edu · doi:10.7910/DVN/QLXGBG · lines:40-52Original leaf images are deposited into https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZPGVPP ; https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QLXGBG ; and https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/29PJR1 for public access.
Open resource ↗dataverse.harvard.edu · doi:10.7910/DVN/29PJR1 · lines:40-52Raw data are listed in Supplementary Files 1 – 3 .
Open resource ↗lines:40-52This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.