A high-throughput multispectral imaging system for museum specimens

被引:0
|
作者
Wei-Ping Chan
Richard Rabideau Childers
Sorcha Ashe
Cheng-Chia Tsai
Caroline Elson
Kirsten J. Keleher
Rachel L. Hawkins Sipe
Crystal A. Maier
Andrei Sourakov
Lawrence F. Gall
Gary D. Bernard
Edward R. Soucy
Nanfang Yu
Naomi E. Pierce
机构
[1] Harvard University,Department of Organismic and Evolutionary Biology
[2] Harvard University,Museum of Comparative Zoology
[3] Columbia University,Department of Applied Physics and Applied Mathematics
[4] North Carolina State University,Department of Forestry and Environmental Resources
[5] Cornell University,Department of Neurobiology and Behavior
[6] University of Florida,McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History
[7] Yale University,Computer Systems Office & Division of Entomology, Peabody Museum of Natural History
[8] University of Washington,Department of Electrical and Computer Engineering
[9] Harvard University,Center for Brain Science
来源
Communications Biology | / 5卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
We present an economical imaging system with integrated hardware and software to capture multispectral images of Lepidoptera with high efficiency. This method facilitates the comparison of colors and shapes among species at fine and broad taxonomic scales and may be adapted for other insect orders with greater three-dimensionality. Our system can image both the dorsal and ventral sides of pinned specimens. Together with our processing pipeline, the descriptive data can be used to systematically investigate multispectral colors and shapes based on full-wing reconstruction and a universally applicable ground plan that objectively quantifies wing patterns for species with different wing shapes (including tails) and venation systems. Basic morphological measurements, such as body length, thorax width, and antenna size are automatically generated. This system can increase exponentially the amount and quality of trait data extracted from museum specimens.
引用
收藏
相关论文
共 50 条
  • [21] High-Throughput Stool Metaproteomics: Method and Application to Human Specimens
    Gonzalez, Carlos G.
    Wastyk, Hannah C.
    Topf, Madeline
    Gardner, Christopher D.
    Sonnenburg, Justin L.
    Elias, Joshua E.
    MSYSTEMS, 2020, 5 (03)
  • [22] Depth-multiplexed ptychographic microscopy for high-throughput imaging of stacked bio-specimens on a chip
    Guo, Chengfei
    Jiang, Shaowei
    Yang, Liming
    Song, Pengming
    Pirhanov, Azady
    Wang, Ruihai
    Wang, Tianbo
    Shao, Xiaopeng
    Wu, Qian
    Cho, Yong Ku
    Zheng, Guoan
    BIOSENSORS & BIOELECTRONICS, 2023, 224
  • [23] High-throughput terahertz imaging: progress and challenges
    Li, Xurong
    Li, Jingxi
    Li, Yuhang
    Ozcan, Aydogan
    Jarrahi, Mona
    LIGHT-SCIENCE & APPLICATIONS, 2023, 12 (01)
  • [24] High-throughput terahertz imaging: progress and challenges
    Xurong Li
    Jingxi Li
    Yuhang Li
    Aydogan Ozcan
    Mona Jarrahi
    Light: Science & Applications, 12
  • [25] High-throughput imaging of brain gene expression
    Brown, VM
    Ossadtchi, A
    Khan, AH
    Cherry, SR
    Leahy, RM
    Smith, DJ
    GENOME RESEARCH, 2002, 12 (02) : 244 - 254
  • [26] Imaging for High-Throughput Phenotyping in Energy Sorghum
    Batz, Jose
    Mendez-Dorado, Mario A.
    Thomasson, J. Alex
    JOURNAL OF IMAGING, 2016, 2 (01)
  • [27] High-throughput microfluidic imaging flow cytometry
    Stavrakis, Stavros
    Holzner, Gregor
    Choo, Jaebum
    DeMello, Andrew
    CURRENT OPINION IN BIOTECHNOLOGY, 2019, 55 : 36 - 43
  • [28] JALA Special Issue: High-Throughput Imaging
    Chow, Edward Kai-Hua
    JALA, 2016, 21 (02): : 234 - 237
  • [29] High-throughput neuro-imaging informatics
    Miller, Michael I.
    Faria, Andrei V.
    Oishi, Kenichi
    Mori, Susumu
    FRONTIERS IN NEUROINFORMATICS, 2013, 7
  • [30] HIGH-THROUGHPUT DNA PREPARATION SYSTEM
    GARNER, HR
    ARMSTRONG, B
    KRAMARSKY, DA
    GENETIC ANALYSIS-BIOMOLECULAR ENGINEERING, 1992, 9 (5-6): : 134 - 139