A New Method for Morphometric Analysis of Opal Phytoliths from Plants

Out, Welmoed A.; Grau, José; Madella, Marco

doi:10.1017/s1431927614013270

Cited by 16 publications

(7 citation statements)

References 24 publications

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“…We sampled calculus from 24 individual chimpanzees using established methods 18 29 , and built a random forest model in R 30 to allow us to identify the microremains based on multivariate comparison to reference material 31 32 33 34 35 (see detailed methods below). We predict that if microremains reflect diet, they are accumulative in calculus and should increase with age of the individual.…”

mentioning

confidence: 99%

Dental calculus evidence of Taï Forest Chimpanzee plant consumption and life history transitions

Power

Salazar‐García

Wittig

et al. 2015

Sci Rep

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Dental calculus (calcified dental plaque) is a source of multiple types of data on life history. Recent research has targeted the plant microremains preserved in this mineralised deposit as a source of dietary and health information for recent and past populations. However, it is unclear to what extent we can interpret behaviour from microremains. Few studies to date have directly compared the microremain record from dental calculus to dietary records, and none with long-term observation dietary records, thus limiting how we can interpret diet, food acquisition and behaviour. Here we present a high-resolution analysis of calculus microremains from wild chimpanzees (Pan troglodytes verus) of Taï National Park, Côte d’Ivoire. We test microremain assemblages against more than two decades of field behavioural observations to establish the ability of calculus to capture the composition of diet. Our results show that some microremain classes accumulate as long-lived dietary markers. Phytolith abundance in calculus can reflect the proportions of plants in the diet, yet this pattern is not true for starches. We also report microremains can record information about other dietary behaviours, such as the age of weaning and learned food processing techniques like nut-cracking.

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mentioning

confidence: 99%

Dental calculus evidence of Taï Forest Chimpanzee plant consumption and life history transitions

Power

Salazar‐García

Wittig

et al. 2015

Sci Rep

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“…Current protocols for phytolith morphometrics require either direct measurement of distance parameters with an eyepiece micrometer or a ruler on a phytolith image, or manually digitizing phytolith boundaries on an image to enable more sophisticated quantitative shape analysis using macros in image processing software such as ImageJ (Ball et al 2015;Out et al 2014). In order to make rapid phytolith measurement practical for routine use, methods must be developed that will allow software to automatically define, or segment, object boundaries on slide images containing many phytolith and non-phytolith particles.…”

Section: Image Segmentation and Automated Object Measurementmentioning

confidence: 99%

“…After a phytolith boundary has been segmented, the next step required to build a semi-automated phytolith analysis procedure is to transfer the data into an automated shape feature extraction program. The current cutting edge in phytolith research are macros in ImageJ or other digital image analysis software that process manually or automatically defined boundary data and output geometric size and shape data (Ball et al 2015;Cuthrell 2013;Out et al 2014). SHERPA has progressed considerably further than this with diatom analysis, allowing researchers to automatically input boundary data from the segmentation process into a module that manipulates the data to produce a much wider range of shape descriptors than ImageJ; this module could potentially be applied to phytolith analysis after extensive testing on a range of morphotypes.…”

Section: Image Segmentation and Automated Object Measurementmentioning

confidence: 99%

A conceptual framework for a computer-assisted, morphometric-based phytolith analysis and classification system

Evett

Cuthrell

2016

Journal of Archaeological Science

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Although automated approaches to shape analysis and object classification have been widely applied in the biological sciences, technical and time considerations have limited their use in phytolith research. As advanced microscopy systems become more affordable and accessible and digital imaging software provides a wider range of sophisticated analytical tools, there is increased potential for effective use of machinevision and automation in phytolith research. In this paper, we describe technical limitations of phytolith imaging and identify several techniques that might improve results. Drawing on examples of software developed for related disciplines, we then describe a conceptual framework for development and integration of automated phytolith analysis software for: separating phytoliths from non-phytolith material in digital images; segmentation of phytolith boundaries; quantitative phytolith feature extraction, including a discussion of potentially more powerful, non-traditional parameters of phytolith shape and texture; phytolith classification and identification; and phytolith database image retrieval. While recognizing the difficulty of implementing this framework and the need for extensive empirical testing of suggested approaches on phytoliths, we examine the possibility of aggregating quantitative phytolith data collected in studies worldwide to construct a cloud-based database of phytolith images with associated morphotype data.

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“…Phytolith studies have been utilized both for characterization of individual Setaria species (Rovner, 1971 ; Hodson et al, 1982 ) as also for taxonomic demarcation among species within the genus (Zhang et al, 2011 ; Layton and Kellogg, 2014 ; Wang et al, 2014 ; Madella et al, 2016 ) and from related genera (Hunt et al, 2008 ; Lu et al, 2009 ; Out et al, 2014 ; Wang et al, 2014 ; García-Granero et al, 2016 ; Madella et al, 2016 ). The ever increasing role of phytoliths in the resolution of intrageneric and intergeneric taxonomy of the genus can be ascribed to the simple fact that even among grasses, Setaria spp.…”

Section: Introductionmentioning

confidence: 99%

Taxonomic Demarcation of Setaria pumila (Poir.) Roem. & Schult., S. verticillata (L.) P. Beauv., and S. viridis (L.) P. Beauv. (Cenchrinae, Paniceae, Panicoideae, Poaceae) From Phytolith Signatures

et al. 2018

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Background and Aims: The role and significance of phytoliths in taxonomic diagnosis of grass species has been well documented with a focus on the types found in foliar epidermis and the synflorescence. The present paper is an attempt to broaden the scope of phytoliths in species diagnosis of grasses by developing phytolith signatures of some species of the foxtail genus Setaria P. Beauv. through in situ location and physico-chemical analysis of various phytolith morphotypes in different parts of the plant body.Methods: Clearing solution and dry ashing extraction methods were employed for in situ location and isolation of phytolith morphotypes respectively. Ultrastructural details were worked out by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy. Morphometric and frequency data of phytolith morphotypes were also recorded. Biochemical architecture of various phytolith types was worked out through SEM-EDX, XRD, and FTIR analysis. Data were analyzed through Principal Component Analysis and Cluster Analysis.Key Results: In situ location of phytoliths revealed species specific epidermal patterns. The presence of cystoliths (calcium oxalate crystals) in the costal regions of adaxial leaf surface of S. verticillata (L.) P. Beauv. is the first report for the genus Setaria. Our results revealed marked variations in epidermal ornamentation and undulation patterns with a novel “Λ” (Lamda) type of undulated ornamentation reported in S. verticillata. Dry ashing method revealed species specific clusters of phytolith morphotypes.Conclusions: The study revealed that phytoliths can play a significant role in resolution of taxonomic identity of three species of Setaria. Each species was marked out by a unique assemblage of phytolith morphotypes from various parts of the plant body. Apart from in situ location and epidermal patterning, diagnostic shapes, frequency distribution, size dimensions, and biochemical architecture emerged as complementary traits that help in developing robust phytolith signatures for plant species.

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A New Method for Morphometric Analysis of Opal Phytoliths from Plants

Cited by 16 publications

References 24 publications

Dental calculus evidence of Taï Forest Chimpanzee plant consumption and life history transitions

Dental calculus evidence of Taï Forest Chimpanzee plant consumption and life history transitions

A conceptual framework for a computer-assisted, morphometric-based phytolith analysis and classification system

Taxonomic Demarcation of Setaria pumila (Poir.) Roem. & Schult., S. verticillata (L.) P. Beauv., and S. viridis (L.) P. Beauv. (Cenchrinae, Paniceae, Panicoideae, Poaceae) From Phytolith Signatures

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