TY - JOUR
T1 - Bioinformatic and biometric methods in plant morphology
AU - Punyasena, Surangi W.
AU - Smith, Selena Y.
N1 - Publisher Copyright:
© 2014 Crawford and Belcher. Published by the Botanical Society of America.
PY - 2014/8
Y1 - 2014/8
N2 - Recent advances in microscopy, imaging, and data analyses have permitted both the greater application of quantitative methods and the collection of large data sets that can be used to investigate plant morphology. This special issue, the fi rst for Applications in Plant Sciences , presents a collection of papers highlighting recent methods in the quantitative study of plant form. These emerging biometric and bioinformatic approaches to plant sciences are critical for better understanding how morphology relates to ecology, physiology, genotype, and evolutionary and phylogenetic history. From microscopic pollen grains and charcoal particles, to macroscopic leaves and whole root systems, the methods presented include automated classifi cation and identifi cation, geometric morphometrics, and skeleton networks, as well as tests of the limits of human assessment. All demonstrate a clear need for these computational and morphometric approaches in order to increase the consistency, objectivity, and throughput of plant morphological studies.
AB - Recent advances in microscopy, imaging, and data analyses have permitted both the greater application of quantitative methods and the collection of large data sets that can be used to investigate plant morphology. This special issue, the fi rst for Applications in Plant Sciences , presents a collection of papers highlighting recent methods in the quantitative study of plant form. These emerging biometric and bioinformatic approaches to plant sciences are critical for better understanding how morphology relates to ecology, physiology, genotype, and evolutionary and phylogenetic history. From microscopic pollen grains and charcoal particles, to macroscopic leaves and whole root systems, the methods presented include automated classifi cation and identifi cation, geometric morphometrics, and skeleton networks, as well as tests of the limits of human assessment. All demonstrate a clear need for these computational and morphometric approaches in order to increase the consistency, objectivity, and throughput of plant morphological studies.
KW - automation
KW - charcoal shape
KW - leaf shape
KW - leaf venation
KW - morphometrics
KW - plant morphology
KW - pollen classifi cation
KW - root networks.
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U2 - 10.3732/apps.1400071
DO - 10.3732/apps.1400071
M3 - Article
AN - SCOPUS:84946595349
SN - 2168-0450
VL - 2
JO - Applications in Plant Sciences
JF - Applications in Plant Sciences
IS - 8
M1 - 1400071
ER -