Simple but long-lasting: A specimen imaging method applicable for small- and medium-sized herbaria

Takano, Atsuko; Horiuchi, Yasuhiko; Yu, Fei; Aoki, Kouta; Mitsuhashi, Hiromune; Takahashi, Akira

doi:10.3897/phytokeys.118.29434

Cited by 20 publications

(20 citation statements)

References 13 publications

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“…The previous research states that herbarium can make it easier for students to observe and identity plants (Syamsiah, Nurhayati, & Hiola, 2020). A good herbarium should feature well-preserved plant structures, to provide a representative model over a long period (Takano et al, 2019). Therefore, the researchers compiled the herbarium design according to the criteria and carried out a good herbarium-making procedure.…”

Section: Discussionmentioning

confidence: 99%

The feasibility of herbarium based local wisdom on plant structure and development subject

Ami

Yuliana

2021

BIO

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The development of herbarium based on local wisdom as a learning media for the subject of plant structure and development, especially traditional food, is still very rare. This is very unfortunate because local wisdom contains pedagogical values that play an important role in improving the quality of learning. This study aims to determine the feasibility of the herbarium developed according to the validation results of the instructional media expert and herbarium expert. The development model used is ADDIE and the stages carried out in this research are up to the development stage. The results showed that the herbarium based on local wisdom developed was suitable as a learning media for the subject of plant structure and development, with an average score of the validation results of the two validators was 81,25. Both validators suggest using plant specimens that display complete organs, consisting of roots, stems, leaves, flowers, fruits, and seeds in making herbariums.Keywords: Local wisdom, herbarium, learning media

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Section: Discussionmentioning

confidence: 99%

The feasibility of herbarium based local wisdom on plant structure and development subject

Ami

Yuliana

2021

BIO

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“…Image resolution may not be a problem for high‐quality images (e.g. JStor Global Plants; https://plants.jstor.org/), but as digitization methods vary (Sweeney et al., 2018; Takano et al., 2019; Tulig, Tarnowsky, Bevans, Kirchgessner, & Thiers, 2012), databases will differ in how they are prone to measurement errors.…”

Section: Discussionmentioning

confidence: 99%

“…When compiling morphological data from specimen images, measurement noise is not a problem, particularly if variables are outside the size range affected by resolution. Hence, even though resolution may vary among digitization methods (Sweeney et al., 2018; Takano et al., 2019; Tulig et al., 2012), measuring them instead of specimens is an effective, less expensive (no need for traveling or loans), and, more important, reliable method for data acquisition.…”

Section: Discussionmentioning

confidence: 99%

Schrödinger's phenotypes: Herbarium specimens show two‐dimensional images are both good and (not so) bad sources of morphological data

2020

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1. Museum specimens are the main source of information on organisms' morphological features. Although access to this information was commonly limited to researchers able to visit collections, it is now becoming freely available thanks to the digitization of museum specimens. With these images, we will be able to collectively build large-scale morphological datasets, but these will only be useful if the limits to this approach are well-known. To establish these limits, we used two-dimensional images of plant specimens to test the precision and accuracy of image-based data and analyses. 2. To test measurement precision and accuracy, we compared leaf measurements taken from specimens and images of the same specimens. Then, we used legacy morphometric datasets to establish differences in the quality of datasets and multivariate analyses between specimens and images. To do so, we compared the multivariate space based on original legacy data to spaces built with datasets simulating image-based data. 3. We found that trait measurements made from images are as precise as those obtained directly from specimens, but as traits diminish in size, the accuracy drops as well. This decrease in accuracy, however, has a very low impact on dataset and analysis quality. The main problem with image-based datasets comes from missing observations due to image resolution or organ overlapping. Missing data lowers the accuracy of datasets and multivariate analyses. Although the effect is not strong, this decrease in accuracy suggests caution is needed when designing morphological research that will rely on digitized specimens. 4. As highlighted by images of plant specimens, 2D images are reliable measurement sources, even though resolution issues lower accuracy for small traits. At the same time, the impossibility of observing particular traits affects the quality of image-based datasets and, thus, of derived analyses. Despite these issues, gathering phenotypic data from two-dimensional images is valid and may support largescale studies on the morphology and evolution of a wide diversity of organisms.

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“…Image resolution may not be a problem for high quality images (e.g. JStor Global Plants; https://plants.jstor.org/), but as digitization methods vary (Tulig et al, 2012; Takano et al, 2019; Sweeney et al, 2018), databases will differ in how they are prone to measurement errors.…”

Section: Discussionmentioning

confidence: 99%

“…When compiling morphological data from images of herbarium specimens, measurement noise is not a problem, particularly if variables are outside the size range affected by resolution. Hence, even though resolution may vary among digitization methods (Tulig et al, 2012; Takano et al, 2019; Sweeney et al, 2018), measuring them instead of specimens is an effective, less expensive (no need for traveling or loans), and, more important, reliable method for data acquisition.…”

Section: Discussionmentioning

confidence: 99%

Schrödinger’s phenotypes: herbarium specimens show two-dimensional images are both good and (not so) bad sources of morphological data

Borges

Reis

Izbicki

2020

Preprint

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AbstractMuseum specimens are the main source of information on organisms’ morphological features. Although access to this information was commonly limited to researchers able to visit collections, it is now becoming freely available thanks to the digitization of museum specimens. With these images, we will be able to collectively build large-scale morphological datasets, but these will only be useful if the limits to this approach are well-known. To establish these limits, we used two-dimensional images of plant specimens to test the precision and accuracy of image-based data and analyses.To test measurement precision and accuracy, we compared leaf measurements taken from specimens and images of the same specimens. Then we used legacy morphometric datasets to establish differences in the quality of datasets and multivariate analyses between specimens and images. To do so, we compared the multivariate space based on original legacy data to spaces built with datasets simulating image-based data.We found that trait measurements made from images are as precise as those obtained directly from specimens, but as traits diminish in size, the accuracy drops as well. This decrease in accuracy, however, has a very low impact on dataset and analysis quality. The main problem with image-based datasets comes from missing observations due to image resolution or organ overlapping. Missing data lowers the accuracy of datasets and multivariate analyses. Although the effect is not strong, this decrease in accuracy suggests caution is needed when designing morphological research that will rely on digitized specimens.As highlighted by images of plant specimens, 2D images are reliable measurement sources, even though resolution issues lower accuracy for small traits. At the same time, the impossibility of observing particular traits affects the quality of image-based datasets and, thus, of derived analyses. Despite these issues, gathering phenotypic data from two-dimensional images is valid and may support large-scale studies on the morphology and evolution of a wide diversity of organisms.

show abstract

Simple but long-lasting: A specimen imaging method applicable for small- and medium-sized herbaria

Cited by 20 publications

References 13 publications

The feasibility of herbarium based local wisdom on plant structure and development subject

The feasibility of herbarium based local wisdom on plant structure and development subject

Schrödinger's phenotypes: Herbarium specimens show two‐dimensional images are both good and (not so) bad sources of morphological data

Schrödinger’s phenotypes: herbarium specimens show two-dimensional images are both good and (not so) bad sources of morphological data

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