A Bioelectric Active Hydrogel Sensor for Trace Detection of Heavy Metal Ions in Livestock and Poultry Farm Wastewater
Heavy metal contamination in livestock and poultry farm wastewater poses significant risks to both the environment and human health, so it is critical to accurately and rapidly quantify heavy metal ion concentrations in water. This research develops a bioelectric active hydrogel sensor for detecting...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Biosensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-6374/15/6/341 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Heavy metal contamination in livestock and poultry farm wastewater poses significant risks to both the environment and human health, so it is critical to accurately and rapidly quantify heavy metal ion concentrations in water. This research develops a bioelectric active hydrogel sensor for detecting heavy metal ions in livestock wastewater. The sensor integrates microbial surface display technology with graphene hydrogel, displaying glucose oxidase (GOx) on the surface of yeast cells, and covalently incorporating it into the graphene hydrogel through the bio-reduction activity of metal-reducing bacteria, enhancing its electrochemical performance. The sensor demonstrates excellent sensitivity and stability in detecting Cu<sup>2+</sup>, with a detection limit for Cu<sup>2+</sup> of 17.0 µM. This sensor is also applicable for detecting Zn<sup>2+</sup> in wastewater. When various heavy metal ions coexist in the solution, they exert a more pronounced inhibitory effect on enzyme activity. Consequently, the sensor can be employed to assess the overall heavy metal content in water samples. In the detection of Cu<sup>2+</sup> in real livestock and poultry wastewater, the recovery rate of the graphene hydrogel electrode ranged from 88% to 106.5%, indicating that the sensor holds significant potential for application in actual sample analysis. |
|---|---|
| ISSN: | 2079-6374 |