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Optimization of sensors based on encapsulated algae for pesticide detection in water
- Source :
- Analytical Methods, Analytical Methods, Royal Society of Chemistry, 2019, 11 (48), pp.6193-6203. ⟨10.1039/C9AY02145K⟩
- Publication Year :
- 2019
- Publisher :
- Royal Society of Chemistry (RSC), 2019.
-
Abstract
- International audience; Pesticides represent a significant source of contamination for urban and suburban surface, ground and seawaters. Whole-cell algal biosensors are sensitive, cheap and adaptable early-warning systems, which are capable of detecting pesticides both in situ and continuously in discharges and receiving ecosystems. Here we designed and optimized a new biosensor with a microalgae immobilization method based on double encapsulation in alginate beads/silica gel, which has been proven safe for algae in previous studies. Pesticide detection was assessed by chlorophyll fluorescence disturbance using the two algae strains Chlorella vulgaris and Pseudokirchneriella subcapitata. Three pesticides (diuron, atrazine and isoproturon) were used to optimize and assess the sensor's performance. The first step was to select the optimal silica hydrogel (based on porosity and optical properties) to design the sensor. Two parameters were adjusted to obtain the best contact between microalgae and pesticides, optimizing pesticide detection: algal concentrations in the alginate beads and thickness of the silica gel around the algal beads. Finally, the biosensor's performance was assessed with pesticide solutions and the lowest detection limit was obtained with C. vulgaris exposed to diuron (10 μg L−1)
- Subjects :
- General Chemical Engineering
Chlorella vulgaris
02 engineering and technology
01 natural sciences
Analytical Chemistry
chemistry.chemical_compound
Algae
Atrazine
Detection limit
biology
[SDE.IE]Environmental Sciences/Environmental Engineering
Chemistry
Silica gel
010401 analytical chemistry
General Engineering
Pesticide
Contamination
021001 nanoscience & nanotechnology
biology.organism_classification
6. Clean water
0104 chemical sciences
13. Climate action
Environmental chemistry
[SDE]Environmental Sciences
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
0210 nano-technology
Biosensor
Subjects
Details
- ISSN :
- 17599679 and 17599660
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Analytical Methods
- Accession number :
- edsair.doi.dedup.....a86aeed8d273002e88c2ab5f5570c1f7
- Full Text :
- https://doi.org/10.1039/c9ay02145k