Näytä suppeat kuvailutiedot

dc.contributor.authorSalmi, Pauliina
dc.contributor.authorEskelinen, Matti A.
dc.contributor.authorLeppänen, Matti T.
dc.contributor.authorPölönen, Ilkka
dc.date.accessioned2021-02-15T14:07:48Z
dc.date.available2021-02-15T14:07:48Z
dc.date.issued2021
dc.identifier.citationSalmi, P., Eskelinen, M. A., Leppänen, M. T., & Pölönen, I. (2021). Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices. <i>Plants</i>, <i>10</i>(2), Article 341. <a href="https://doi.org/10.3390/plants10020341" target="_blank">https://doi.org/10.3390/plants10020341</a>
dc.identifier.otherCONVID_51484116
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/74237
dc.description.abstractSpectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherMDPI AG
dc.relation.ispartofseriesPlants
dc.rightsCC BY 4.0
dc.subject.othermobile spectral camera
dc.subject.othervegetation indices
dc.subject.othermonitoring
dc.subject.othertransmission imaging
dc.titleRapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202102151658
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineAkvaattiset tieteetfi
dc.contributor.oppiaineMathematical Information Technologyen
dc.contributor.oppiaineAquatic Sciencesen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn2223-7747
dc.relation.numberinseries2
dc.relation.volume10
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 the Authors
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber321780
dc.subject.ysospektrikuvaus
dc.subject.ysomikrolevät
dc.subject.ysokasvillisuus
dc.subject.ysomonitorointi
dc.subject.ysokaukokartoitus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p26364
jyx.subject.urihttp://www.yso.fi/onto/yso/p26977
jyx.subject.urihttp://www.yso.fi/onto/yso/p1756
jyx.subject.urihttp://www.yso.fi/onto/yso/p3628
jyx.subject.urihttp://www.yso.fi/onto/yso/p2521
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.datasethttps://jyx.jyu.fi/handle/123456789/71623
dc.relation.doi10.3390/plants10020341
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundinginformationThis research was funded by The Academy of Finland, grant number 321780.
dc.type.okmA1


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