Journal article
Odorant binding protein based biomimetic sensors for detection of alcohols associated with Salmonella contamination in packaged beef
Biosensors & bioelectronics, Vol.26(7), pp.3103-3109
2011
Handle:
https://hdl.handle.net/2376/105327
PMID: 21227678
Abstract
Detection of food-borne bacteria present in the food products is critical to prevent the spread of infectious diseases. Intelligent quality sensors are being developed for detecting bacterial pathogens such as
Salmonella in beef. One of our research thrusts was to develop novel sensing materials sensitive to specific indicator alcohols at low concentrations. Present work focuses on developing olfactory sensors mimicking insect odorant binding protein to detect alcohols in low concentrations at room temperature. A quartz crystal microbalance (QCM) based sensor in conjunction with synthetic peptide was developed to detect volatile organic compounds indicative to
Salmonella contamination in packaged beef. The peptide sequence used as sensing materials was derived from the amino acids sequence of
Drosophila odorant binding protein, LUSH. The sensors were used to detect alcohols: 3-methyl-1-butanol and 1-hexanol. The sensors were sensitive to alcohols with estimated lower detection limits of <5
ppm. Thus, the LUSH-derived QCM sensors exhibited potential to detect alcohols at low ppm concentrations.
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Details
- Title
- Odorant binding protein based biomimetic sensors for detection of alcohols associated with Salmonella contamination in packaged beef
- Creators
- Sindhuja Sankaran - Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58108, USASuranjan Panigrahi - Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58108, USASanku Mallik - Pharmaceutical Sciences, North Dakota State University, Fargo, ND 58108, USA
- Publication Details
- Biosensors & bioelectronics, Vol.26(7), pp.3103-3109
- Academic Unit
- Biological Systems Engineering, Department of
- Publisher
- Elsevier B.V
- Identifiers
- 99900546877001842
- Language
- English
- Resource Type
- Journal article