Mostrar el registro sencillo del ítem

dc.contributor.authorCardona L
dc.contributor.authorArroyave C
dc.contributor.authorAristizábal A.
dc.date.accessioned2023-10-24T19:24:15Z
dc.date.available2023-10-24T19:24:15Z
dc.date.created2023
dc.identifier.issn15375110
dc.identifier.urihttp://hdl.handle.net/11407/7927
dc.description.abstractThe morphological features of Spirulina can be related to environmental conditions and can affect biomass harvesting; thus, monitoring these parameters is desirable to assess the state of the culture and to establish favourable conditions for achieving easy-to-harvest filaments, improving biomass productivity. However, obtaining significant measurements of these morphological features can be slow and laborious since it is normally manually. This work presents a new methodology for automatically measuring the morphological features of Spirulina filaments on microscopy images. A novel algorithm is presented that uses the variance of the distances between pixels on each half of the contour to identify filament ends. Unlike previous methods, this approach does not assume that filaments are coiled around a straight axis. Once the endpoints are identified, the filaments' morphological features (length, width, helix angle, and diameter) can be estimated through the fitting of lines and Bezier curves, as explained in sections 3.4–3.6. The addition of editable objects to represent the fitted parameters is presented, allowing for manual adjustment of the results. To evaluate the proposed methodology, the morphological parameters of some Spirulina filaments were estimated and compared to manual measurements. The results of the proposed algorithm had close agreement with the manual measurements with variations below 4% in filament length; a noticeable result considering that this feature is the most time-consuming to measure manually. Overall, the results indicated that the proposed methodology can automatically and reliably estimate the morphological parameters of Spirulina filaments. © 2023 IAgrEeng
dc.language.isoeng
dc.publisherAcademic Press
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85150796711&doi=10.1016%2fj.biosystemseng.2023.03.004&partnerID=40&md5=e7b2253ea24e0adf262d9dd8a80c1ec6
dc.sourceBiosyst. Eng.
dc.sourceBiosystems Engineeringeng
dc.subjectBezier curveeng
dc.subjectFilamenteng
dc.subjectImage processingeng
dc.subjectMorphological featureseng
dc.subjectSpirulinaeng
dc.titleImage processing algorithm for automatically measuring morphological features of spirulina filaments in microscopy imageseng
dc.typeArticle
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería Ambientalspa
dc.type.spaArtículo
dc.identifier.doi10.1016/j.biosystemseng.2023.03.004
dc.relation.citationvolume228
dc.relation.citationstartpage166
dc.relation.citationendpage177
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationCardona, L., Department of Mechanics, Institución Universitaria Pascual Bravo, Calle 73 # 73A – 226, Medellín, 050034, Colombia
dc.affiliationArroyave, C., Department of Environmental Engineering, Universidad de Medellín, Carrera 87 # 30-65, Medellín, 050026, Colombia
dc.affiliationAristizábal, A., Department of Process Engineering, Universidad EAFIT, Carrera 49 # 7 Sur-50, Medellín, 050022, Colombia
dc.relation.referencesAbuBaker, A., Qahwaji, R., Ipson, S., Saleh, M., One scan connected component labeling technique (2007) ICSPC 2007 proceedings - 2007 IEEE international conference on signal processing and communications, (november), pp. 1283-1286
dc.relation.referencesCheng, J., Guo, W., Ameer Ali, K., Ye, Q., Jin, G., Qiao, Z., Promoting helix pitch and trichome length to improve biomass harvesting efficiency and carbon dioxide fixation rate by Spirulina sp. in 660 m2 raceway ponds under purified carbon dioxide from a coal chemical flue gas (2018) Bioresource Technology, 261 (February), pp. 76-85
dc.relation.referencesFloater, M.S., Rasmussen, A.F., Point-based methods for estimating the length of a parametric curve (2006) Journal of Computational and Applied Mathematics, 196 (2), pp. 512-522
dc.relation.referencesGao, K., Li, P., Watanabe, T., Walter Helbling, E., Combined effects of ultraviolet radiation and temperature on morphology, photosynthesis, and DNA of Arthrospira (Spirulina) platensis (cyanophyta) (2008) Journal of Phycology, 44 (3), pp. 777-786
dc.relation.referencesGüneş, A., Kalkan, H., Durmuş, E., Optimizing the color-to-grayscale conversion for image classification (2016) Signal, Image and Video Processing, 10 (5), pp. 853-860
dc.relation.referencesH, J., Splines: Generation of curves and surfaces (2001) Computer graphics through key mathematics, pp. 259-294. , Springer London
dc.relation.referencesJiménez, C., Cossío, B.R., Niell, F.X., Relationship between physicochemical variables and productivity in open ponds for the production of Spirulina: A predictive model of algal yield (2003) Aquaculture, 221 (1-4), pp. 331-345
dc.relation.referencesS.Z., L., A, J., Local adaptive thresholding (2009) Encyclopedia of biometrics, p. 939. , Springer US Boston, MA 939
dc.relation.referencesMa, Z., Gao, K., Photoregulation of morphological structure and its physiological relevance in the cyanobacterium Arthrospira (Spirulina) platensis (2009) Planta, 230 (2), pp. 329-337
dc.relation.referencesMaini, R., Aggarwal, H., Study and comparison of various image edge detection techniques (2012) International Journal of Image Processing, 3 (1), pp. 1-11. , https://www.academia.edu/3345358/Study_and_comparison_of_various_image_edge_detection_techniques?auto=citations&from=cover_page, Retrieved from
dc.relation.referencesPierobon, S.C., Cheng, X., Graham, P.J., Nguyen, B., Karakolis, E.G., Sinton, D., Emerging microalgae technology: A review (2018) Sustainable Energy Fuels, 2 (1), pp. 13-38
dc.relation.referencesVonshak, A., (2002) Spirulina platensis (arthrospira): Physiology, cell-biology and biotechnology, , Taylor & Francis London
dc.relation.referencesWatson, P.F., Petrie, A., Method agreement analysis: A review of correct methodology (2010) Theriogenology, 73 (9), pp. 1167-1179
dc.relation.referencesWhitton, B.A., Ecology of cyanobacteria II: Their diversity in space and time (2012) Ecology of Cyanobacteria II: Their Diversity in Space and Time, pp. 1-760. , 9789400738
dc.relation.referencesWu, D., Wang, S., Liu, K., Yu, X., He, Y., Wang, Z., Rapid measurement of morphological features of Spirulina microalgae filaments using microscopy and image processing algorithms (2012) Biosystems Engineering, 112 (1), pp. 35-41
dc.relation.referencesZapata, D., Arroyave, C., Cardona, L., Aristizábal, A., Poschenrieder, C., Llugany, M., Phytohormone production and morphology of Spirulina platensis grown in dairy wastewaters (2021) Algal Research, 59
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem