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V. Blagoderov et al. (2012): No specimen left behind: industrial scale digitization of natural history collections. In PDF, Zookeys, 209: 133-146.
!
M.J.M. Brown and G.J. Jordan (2023):
No
cell is an island: characterising the leaf epidermis using
EPIDERMALMORPH, a new R package. Open access,
New Phytologist, 237: 354–366.
"... we present a method to characterise individual cell size, shape (including the effect of
neighbouring cells) and arrangement from light microscope images. We provide the first automated
characterisation of cell arrangement ..."
Download the R package
(quantifying and analysing epidermal cell shape, size and spatial arrangement),
and
the manual.
!
Chip (in German):
Vollversion: Photoshop CS2.
Photoshop CS2 free of charge!
!
J.S. Cope et al. (2012):
Plant
species identification using digital morphometrics: A review. In PDF,
Expert Systems with Applications, 39: 7562-7573.
See also
here.
"... We review the main computational, morphometric and image processing methods
[...] We discuss the measurement of leaf outlines, flower shape, vein structures and leaf textures, and
describe a wide range of analytical methods in use.
Chris Creevey & James O. McInerney, Bioinformatics Laboratory, Department of Biology, National University of Ireland, Maynooth: Clann. Construction of Supertrees and exploration of phylogenomic information from partially overlapping datasets. This software program is free and it implements the greatest number of phylogenetic supertree methods.
Joe Felsenstein, Department of Genetics, University of Washington, Seattle, Washington: Phylogeny Programs. List of packages arranged by methods available, cross-referenced by method and by computer systems. The programs listed here include both free and non-free ones.
K.C. Fetter et al. (2018): StomataCounter: a deep learning method applied to automatic stomatal identification and counting. In PDF, bioRxiv. See also here! FSF/UNESCO Free Software Directory (a project of the Free Software Foundation, Inc.(FSF), Boston, MA, and United Nations Education, Scientific and Cultural Organization, UNESCO). Useful free software that runs under free operating systems - particularly the GNU operating system and its GNU/Linux variants. There are 4,386 packages indexed. Go to: Biology
B.A. Lloyd et al. (2023): CuticleTrace: A toolkit for capturing cell outlines of leaf cuticle with implications for paleoecology and paleoclimatology. Free access, bioRxiv.
NOAA Paleoclimatology Program, National Geophysical Data Center, National Oceanic and Atmospheric Administration (NOAA), Boulder, Colorado: Free Software. A link list.
Rod Page, Division of Ecology and Evolutionary Biology, Faculty of Biomedical and Life Sciences, University of Glasgow: COMPONENT 2.0. Now free of charge! This is a computer program for analysing evolutionary trees.
M.P. Pound et al. (2017): Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience. See also here (in PDF).
K.M. Pryer et al. (2020): Using computer vision on herbarium specimen images to discriminate among closely related horsetails (Equisetum). Open access, Applications in Plant Sciences, 8: e11372. See also here (in PDF).
! J. Schindelin et al. (2012): Fiji - an Open Source platform for biological image analysis. Open access, Nat Methods, 9: 10.1038/nmeth.2019.
Robert A. Spicer, The Warm Earth Environmental Systems Research Group: Plant Fossils as Climatic Indicators. Go to: Climate Leaf Analysis Multivariate Programe (CLAMP). An introduction to the use of leaf architecture for determining past climatic conditions.
SPSS Inc.: Today, more than 250,000 organizations use SPSS, a software for desktop analysis, to create and distribute information for better decision making. Fully functional demos of SIGMAPLOT and DELTAGRAPH.
!
C.G. Willis et al. (2017):
Old
Plants, New Tricks: Phenological Research Using Herbarium Specimens. In PDF,
Trends in Ecology & Evolution, 32: 531-546.
See also
here.
"... Herbarium specimens provide a
window into the past that increases our temporal, geographic – and taxonomic vision of how
phenology – and potentially plant success and ecosystem processes, have changed and will
continue to be affected as the climate changes. With a thorough and growing understanding of
the potential and limitations of this rich historical data source, combined with the modern tools
of digitization, data sharing, and integration, researchers will increasingly be able to address
critical questions about plant biology ..."
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