Low-cost, high-volume imaging for entomological digitization
Authors/Creators
- 1. University of Guelph, Guelph, Canada
Description
Large-scale digitization of natural history collections requires automation of image acquisition and processing. Reflecting this fact, various approaches, some highly sophisticated, have been developed to support imaging of museum specimens. However, most of these systems are complex and expensive, restricting their deployment. Here we describe a simple, inexpensive technique for imaging arthropods larger than 5 mm. By mounting a digital SLR camera on a CNC (computer numerical control) motor-drive rig, we created a system that captures high-resolution z-axis stacked images (6960 × 4640 pixels) of 95 specimens in 30 minutes. This system can be assembled inexpensively ($1000 USD without a camera) and it is easy to set-up and maintain. By coupling low cost with high production capacity, it represents a solution for digitizing any natural history collection.
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References
- Ärje J, Melvad C, Rosenhøj Jeppesen M, Agerskov Madsen S, Raitoharju J, Strandgård Rasmussen M, Iosifidis A, Tirronen V, Gabbouj M, Meissner K, Høye TT (2020) Automatic image-based identification and biomass estimation of invertebrates. Methods in Ecology and Evolution 11(8): 922–931. https://doi.org/10.1111/2041-210X.13428
- Beaman RS, Cellinese N (2012) Mass digitization of scientific collections: New opportunities to transform the use of biological specimens and underwrite biodiversity science. ZooKeys 209: 7–17. https://doi.org/10.3897/zookeys.209.3313
- Berents P, Hamer M, Chavan V (2010) Towards demand-driven publishing: Approaches to the prioritization of digitization of natural history collection data. Biodiversity Informatics 7: 113–119. https://doi.org/10.17161/bi.v7i2.3990
- Blagoderov V, Kitching IJ, Livermore L, Simonsen TJ, Smith VS (2012) No specimen left behind: Industrial scale digitization of natural history collections. ZooKeys 209: 133–146. https://doi.org/10.3897/zookeys.209.3178
- Chapman A (2005) Principles of Data Quality. Global Biodiversity Information Facility. https://doi.org/10.15468/doc.jrgg-a190
- deWaard JR, Ratnasingham S, Zakharov EV, Borisenko AV, Steinke D, Telfer AC, Perez KHJ, Sones JE, Young MR, Levesque-Beaudin V, Sobel CN, Abrahamyan A, Bessonov K, Blagoev G, deWaard SL, Ho C, Ivanova NV, Layton KKS, Lu L, Manjunath R, McKeown JTA, Milton MA, Miskie R, Monkhouse N, Naik S, Nikolova N, Pentinsaari M, Prosser SWJ, Radulovici AE, Steinke C, Warne CP, Hebert PDN (2019) A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples. Scientific Data 6(1): 308. https://doi.org/10.1038/s41597-019-0320-2
- Gharaee Z, Gong Z, Pellegrino N, Zarubiieva I, Haurum JB, Lowe SC, McKeown JTA, Ho CCY, McLeod J, Wei YC, Agda J, Ratnasingham S, Steinke D, Chang AX, Taylor GW, Fieguth P (2023) A step towards worldwide biodiversity assessment: The BIOSCAN-1M insect dataset. Advances in Neural Information Processing Systems 37.
- Hedrick BP, Heberling JM, Meineke EK, Turner KG, Grassa CJ, Park DS, Kennedy J, Clarke JA, Cook JA, Blackburn DC, Edwards SV, Davis CC (2020) Digitization and the future of natural history collections. Bioscience 70(3): 243–251. https://doi.org/10.1093/biosci/biz163
- Heerlien M, van Leusen J, Schnörr S, de Jong-Kole S, Raes R, van Hulsen K (2015) The natural history production line: An industrial approach to the digitization of scientific collections. ACM Journal on Computing and Cultural Heritage 8(1): 1–11. https://doi.org/10.1145/2644822
- Holovachov O, Zatushevsky A, Shydlovsky I (2014) Whole-drawer imaging of entomological collections: Benefits, limitations and alternative applications. Journal of Conservation & Museum Studies 12(1): 9. https://doi.org/10.5334/jcms.1021218
- Hudson LN, Blagoderov V, Heaton A, Holtzhausen P, Livermore L, Price BW, van der Walt S, Smith VS (2015) Inselect: Automating the digitization of natural history collections. PLoS one 10: e0143402. https://doi.org/10.1371/journal.pone.0143402
- Ahl LI, Bellucci L, Brewer P, Gagnier P-Y, Hardy HM, Haston EM, Livermore L, De Smedt S, Enghoff H (2023) Digitisation of natural history collections: criteria for prioritization. Research Ideas and Outcomes 9: e114548. https://doi.org/10.3897/rio.9.e114548
- Mantle BL, Salle JL, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147–163. https://doi.org/10.3897/zookeys.209.3169
- Mathys A, Brecko J, Semal P (2013) Comparing 3D digitizing technologies: What are the differences? Digital Heritage International Congress. Marseille, 201–204. https://doi.org/10.1109/DigitalHeritage.2013.6743733
- Mendez PK, Lee S, Venter CE (2018) Imaging natural history museum collections from the bottom up: 3D print technology facilitates imaging of fluid-stored arthropods with flatbed scanners. ZooKeys 795: 49–65. https://doi.org/10.3897/zookeys.795.28416
- Mertens JEJ, Roie MV, Merckx J, Dekoninck W (2017) The use of low-cost compact cameras with focus stocking functionality in entomological digitization projects. ZooKeys 712: 141–154. https://doi.org/10.3897/zookeys.712.205055
- Moore W (2011) Biology needs cyber-infrastructure to facilitate specimen-level data acquisition for insect and other hyperdiverse groups. ZooKeys 147: 479–486. https://doi.org/10.3897/zookeys.147.1944
- Ratnasingham S, Hebert PDN (2007) BOLD: the barcode of life data system (http://www.barcodinglife.org). Molecular Ecology Notes 7(3): 355–364. https://doi.org/10.1111/j.1471-8286.2007.01678.x
- Ströbel B, Schmelzle S, Blüthgen N, Heethoff M (2018) An automated device for the digitization and 3D modelling of insects, combining extended-depth-of-field and all-side multi-view imaging. ZooKeys 759: 1–27. https://doi.org/10.3897/zookeys.759.24584
- Tegelberg R, Mononen T, Saarenmaa H (2014) High-performance digitization of natural history collections: Automated imaging lines for herbarium and insect specimens. Taxon 63(6): 1307–1313. https://doi.org/10.12705/636.13
- Tegelberg R, Kahanpää J, Karppinen J, Mononen T, Wu Z, Saarenmaa H (2017) Mass digitization of individual pinned insects using conveyor-driven imaging. 2017 IEEE 13th International Conference on e-Science (e-Science): 523–527. https://doi.org/10.1109/eScience.2017.85
- Vollmar A, Macklin JA, Ford LS (2010) Natural history specimen digitization: Challenges and concerns. Biodiversity Informatics 7(2): 93–113. https://doi.org/10.17161/bi.v7i2.3992
- Wührl L, Pylatiuk C, Giersch M, Lapp F, von Rintelen T, Balke M, Schmidt S, Cerretti P, Meier R (2021) DiversityScanner: Robotic discovery of small invertebrates with machine learning methods. BioRxiv preprint. https://doi.org/10.1101/2021.05.17.444523