0000000001333018
AUTHOR
Salmi, Pauliina
Original data for study: Rapid quantification of microalgae with hyperspectral camera and vegetation indices
Spectral 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 in…
Plastid 23S rRNA gene sequence data for several algae strains
The dataset consists of plastid 23S rRNA gene sequence data for several algae strains. For more information about the collection and analysis of the data, see the attached documentation.
Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network
Artikkeliin "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network" liittyvä aineisto koostuu seuraavista osista: 1.Transmittanssi-hyperspektrikuvat levänäytteistä kuvattuina 24-kuoppalevyllä 2.Biomassamääritykset elektronisella solulaskurilla 3.Opetus- ja validointiaineisto konvoluutioneuroverkolle 4.Testiaineisto konvoluutioneuroverkolle 5.Opetus-, validointi- ja testiaineiston käsittelyyn käytetty Python koodi 6.Seitsemään eri malliin käytetty Python koodi ja mallit itsessään The data and code related to the article "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural netwo…
Metabolic plasticity of mixotrophic algae is key for their persistence in browning environments
The dataset consists of phenotypic and transcriptomic data of Cryptomonas sp. when submitted to different concentrations of dissolved organic carbon (DOC), fully phototrophic conditions and glucose supplemented phototrophic conditions. In addition, scripts of processing of transcriptomic data together with input and output files are given. For more detailed description, see the attached documentation.