Application of Xanthan-Gum-Based Edible Coating Incorporated with Litsea cubeba Essential Oil Nanoliposomes in Salmon Preservation.
Haiying CuiMei YangCe ShiChangzhu LiLin LinPublished in: Foods (Basel, Switzerland) (2022)
Salmon is prone to be contaminated by Vibrio parahaemolyticus ( V. parahaemolyticus ), leading to the deterioration of salmon quality and the occurrence of food-borne diseases. In this study, we aimed to develop a novel xanthan-gum-based edible coating embedded with nano-encapsulated Litsea cubeba essential oil (LC-EO) for salmon preservation at 4 °C. First, the results of the growth curves and scanning electron microscopy (SEM) showed that LC-EO displayed potent antibacterial activity against V. parahaemolyticus ; the optimal concentration of LC-EO in the liposomes was 5 mg/mL, and the maximal encapsulation efficiency (EE) was 37.8%. The particle size, polydispersity coefficient (PDI), and zeta potential of the liposomes were 168.10 nm, 0.250, and -32.14 mV, respectively. The rheological test results of xanthan-gum-based edible coatings incorporating liposomes showed that the prepared coating was suitable for applying on food surfaces. The results in the challenge test at 4 °C demonstrated that the treatment of 1:3 (liposome: xanthan gum, v / v ) coating performed the best preservative properties, the coating treatment delayed the oxidation of salmon, and controlled the growth of V. parahaemolyticus . These findings suggest that the coatings formulated in this study could be used as a promising approach to control V. parahaemolyticus contamination and maintain salmon quality.
Keyphrases
- essential oil
- electron microscopy
- drug delivery
- risk assessment
- human health
- drinking water
- drug release
- mass spectrometry
- blood pressure
- staphylococcus aureus
- combination therapy
- escherichia coli
- magnetic resonance imaging
- hydrogen peroxide
- pseudomonas aeruginosa
- biofilm formation
- cystic fibrosis
- body composition
- heart rate
- high intensity
- tandem mass spectrometry
- diffusion weighted imaging