2020
DOI: 10.3390/rs12030567
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Determination of Phycocyanin from Space—A Bibliometric Analysis

Abstract: Over the past few decades, there has been an increase in the number of studies about the estimation of phycocyanin derived from remote sensing techniques. Since phycocyanin is a unique pigment of inland water cyanobacteria, the quantification of its concentration from earth observation data is important for water quality monitoring -once some species can produce toxins. Because of the growth of this field in the past decade, several reviews and studies comparing algorithms have been published. Thus, instead of… Show more

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Cited by 28 publications
(26 citation statements)
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“…Recent advancements in sensor technology and algorithm development have allowed for improved measurements of coastal and inland waters (Hu, 2009;Matthews et al, 2012;Palmer et al, 2015b;Smith et al, 2018;Pahlevan et al, 2020). Given the increased attention placed on retrieving eutrophication metrics for inland water bodies, numerous studies have attempted radiometric retrieval of chlorophyll-a (chl-a) or phycocyanin (PC), the diagnostic pigment within cyanobacteria, with varying degrees of success (see reviews by Ogashawara, 2020;Odermatt et al, 2012;Blondeau-Patissier et al, 2014;Matthews, 2011;Gholizadeh et al, 2016). Retrieval of chl-a concentration has been significantly developed, and is generally more robust for trophic delineation; however, PC is highly specific to cyanobacteria and is thus a better indicator of potential water toxicity (Stumpf et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Recent advancements in sensor technology and algorithm development have allowed for improved measurements of coastal and inland waters (Hu, 2009;Matthews et al, 2012;Palmer et al, 2015b;Smith et al, 2018;Pahlevan et al, 2020). Given the increased attention placed on retrieving eutrophication metrics for inland water bodies, numerous studies have attempted radiometric retrieval of chlorophyll-a (chl-a) or phycocyanin (PC), the diagnostic pigment within cyanobacteria, with varying degrees of success (see reviews by Ogashawara, 2020;Odermatt et al, 2012;Blondeau-Patissier et al, 2014;Matthews, 2011;Gholizadeh et al, 2016). Retrieval of chl-a concentration has been significantly developed, and is generally more robust for trophic delineation; however, PC is highly specific to cyanobacteria and is thus a better indicator of potential water toxicity (Stumpf et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Advance variability profile was selected as ‘auto’ and sequences below 90% identity were rejected. The phylogenetic tree of the OTUs was bootstrapped with RAxML 59 with 20 maximum likelihood (ML) and 100 bootstrapped searches. Annotation was performed in R-studio (1.4.1106) with package ggtree (2.2.4) and Adobe Illustrator (25.2.1).…”
Section: Supplementary Methodologymentioning
confidence: 99%
“…CTD profiles from the whole water column (0-20 m, Day 1 and 2) were used to identify the distribution of the mixolimnion, chemocline and monimolimnion and guided water sampling strategy. The CTD was equipped with an Underwater Quantum Sensor (Li-Cor Biosciences; NE, USA) that continuously recorded photosynthetically active radiation (PAR-w/m 2 ;) and a TriLux multi-parameter algae sensor (Chelsea Technologies Ltd; Surrey, UK) that measured in-vivo Chl a (Chl a, µg/L), an indicator of phytoplankton (including eukaryotic autotrophs and cyanobacteria) biomass 58 , and phycocyanin (µg/L), a pigment characteristic of cyanobacteria 59 . 475 476…”
Section: Methodology Water-sample Collection and Physicochemical Profilingmentioning
confidence: 99%
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“…The error in oxygen profiles for day two was manually adjusted by referring to day 1 measurements which indicated approximately zero oxygen within and below chemocline.CTD profiles from the whole water column (0-20 m, Day 1 and 2) were used to idenbmission Template ASM Journals Submission Template ASM Journals Submission Template ASM Journals Submission Template ASM Journals Submission Template ASM Journals Subm tify the distribution of the mixolimnion, chemocline and monimolimnion and guided water sampling strategy. The CTD was equipped with an LI-192 Underwater Quantum Sensor (Li-Cor Biosciences; NE, USA) that continuously recorded photosynthetically active radiation (PAR-w/m2;) and a TriLux multi-parameter algae sensor (Chelsea Technologies Ltd; Surrey, UK) that measured in-vivo Chl a (Chl a, µg/L), an indicator of phytoplankton (including eukaryotic autotrophs and cyanobacteria) biomass(55), and phycocyanin (µg/L), a pigment characteristic of cyanobacteria(56).Chemical parameters. Dissolved compounds.…”
mentioning
confidence: 99%