Detection of 3-monochloropropane-1, 2-diol (3-MCPD) using molecularly imprinted Poly(3-aminophenylboronic acid)
- Pathum Thani, Thailand : Asian Institute of Technology, 2018
- 74 leaves : ill. + 1 online resource
- Thesis ; no.FB-18-05 .
- Asian Institute of Technology. Thesis ; no.FB-18-05 .
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Food Engineering & Bioprocess Technology, School of Environment, Resources and Development
Thesis (M. Sc.) - Asian Institute of Technology, 2018
Screen printed sensor development is a remarkable sector of present - day electroanalysis. Molecularly imprinted polymers (MIP) enable highly selective and sensitive sensing approaches. Combining these two applications, a selective sensor was developed for t he detection of 3 - monochloropropane - 1,2 - diol (3 - MCPD) which is a process induced food contaminant. A screen printed carbon electrode (SPCE) modified with multiwalled carbon nanotubes (MWCNT), gold nanoparticles (AuNP) and molecularly imprinted poly(3 - amino phenylboronic acid) was used as the sensing platform. Morphological and electrochemical characterizations of the sensor were done using FE - SEM/EDX and potentiometry respectively. In comparison to the non - imprinted sensor, the MIP sensor demonstrated a stat istically significant ( p < .05 ) response towards 3 - MCPD. Fabrication and measurement conditions were optimized for selected parameters. The optimized sensor showed a linear range at 300 to 1500 oM and the sensitivity was 0.011 mV/oM. The LOD and LOQ of the sensor were ascertained to be 192.53 oM and 583.42 oM respectively. The sensor exhibited rather a good selectivity against 1,3 - DCP, 1,2 - propanediol, glycerol , and D - glucose. The pot entiometric response of the sensor was moderately reproducible with a n RSD of <15%. High stability of the sensor was depicted by the non - significant change ( p > .05) in response over 20 days of storage at room temperature. Applicability of the developed sen sor for soy sauce analysis was occluded by the complexities of the food matrix. Further studies are necessary to accomplish real sample application and to ameliorate the sensitivity of the developed sensor.