Abstract
Many species of plants produce leaves with distinct teeth around their margins. The presence and nature of these teeth can often help botanists to identify species. Moreover, it has long been known that more species native to colder regions have teeth than species native to warmer regions. It has therefore been suggested that fossilized remains of leaves can be used as a proxy for ancient climate reconstruction. Similar studies on living plants can help our understanding of the relationships. The required analysis of leaves typically involves considerable manual effort, which in practice limits the number of leaves that are analyzed, potentially reducing the power of the results. In this work, we describe a novel algorithm to automate the marginal tooth analysis of leaves found in digital images. We demonstrate our methods on a large set of images of whole herbarium specimens collected from Tilia trees (also known as lime, linden or basswood). We chose the genus Tilia as its constituent species have toothed leaves of varied size and shape. In a previous study we extracted leaves automatically from a set of images. Our new algorithm locates teeth on the margins of such leaves and extracts features such as each tooth’s area, perimeter and internal angles, as well as counting them. We evaluate an implementation of our algorithm’s performance against a manually analyzed subset of the images. We found that the algorithm achieves an accuracy of 85% for counting teeth and 75% for estimating tooth area. We also demonstrate that the automatically extracted features are sufficient to identify different species of Tilia using a simple linear discriminant analysis, and that the features relating to teeth are the most useful.
Highlights
Characterizing the margin of leaves, including their teeth, is important for several areas of botanical research. These include modeling the climate and identifying species, both of which we discuss here. It was observed by Bailey and Sinnott in 1915–16 [1,2] that in warm climates a greater proportion of plant species produce leaves with entire margins and fewer produce dentate or serrate leaves
Species Identification Having established the basic accuracy of our system, we demonstrate the potential value of automated leaf margin character extraction, with some experiments in species identification (Table 4)
We have demonstrated that it is possible to automatically locate and measure leaf margin teeth from images of herbarium specimens, extending our previous work in this area [13]
Summary
Characterizing the margin of leaves, including their teeth, is important for several areas of botanical research These include modeling the climate and identifying species, both of which we discuss here. Due to the presence of a large number of well-preserved leaves in the fossil record, it has been proposed that the morphology of fossilized leaves can be used as a ‘‘paleothermometer’’ to aid in modeling past climates [3,4,5,6,7,8] This estimation of temperature by calculating the proportion of toothed species at a site is called ‘‘leaf margin analysis’’ (LMA) [3,5]. In its standard form, this is a very simple univariate model predicting mean annual temperature from the proportion of species with entire (toothless) margins. Note that the term ‘‘blade’’ refers strictly to the flat part of a leaf, while ‘‘leaf’’ refers to both the blade and the petiole (stalk); in this work, we are only interested in the blade and its margin [9]
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