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

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.

Morphometric and colourimetric tools to dissect morphological diversity: an application in sweet potato [Ipomoea batatas (L.) Lam.]

“…The potential use of phenomics in fruit shape description in tomato and eggplant has also been demonstrated (Brewer et al 2006;Plazas et al 2014), and its subsequent use in plant breeding (Kaushik et al 2016). In accordance with our results, quantification of leaf shape in barley (Chitwood et al 2013(Chitwood et al , 2014Lockhart 2013), olive leaves and fruits (Blazakis et al 2017), and legume leaves (Liao et al 2017), using geometric estimations allowed comparing and classifying differences among organ shapes that are not perceptible using conventional descriptors, and improving then the accuracy of plant descriptions. In sweet potato, the results showed that morphometric parameters should be included in morphological characterizations, and its potential is promising in physiological and genetic association studies.…”

Dissecting the Molecular Function of Triticum aestivum STI Family Members Under Heat Stress

“…Chlorophyll content (i.e., total chlorophyll content) was found to be higher in transgenics than in WT after stress ( Figure 11C ). Similarly, membrane stability, which is a measure of ion leakage from the tissue, was used to analyze the damage caused to the members due to HS ( Niu and Xiang, 2018 ). However, no significant difference was found in membrane stability between the WT and transgenic plants ( Figure 11B ).…”

Morphometrics of complex cell shapes: lobe contribution elliptic Fourier analysis (LOCO-EFA)

“…Our method is also well-suited for studying organ shape development, specifically when landmarks are difficult to assign. It could, therefore, be used to improve quantification and biological meaningfulness of previous EFA-based studies that, for example, decomposed entire leaf shapes ( Liao et al, 2017 ), insect wings ( Yang et al, 2015 ), jaw shape and sizes ( Rose et al, 2015 ) and pinniped whisker morphologies ( Ginter et al, 2012 ). LOCO-EFA can even be employed at different levels within the same organism, for example to quantify leaf shape and serrations as well as root morphology ( Li et al, 2017 preprint ).…”