Spoilage Potential of Pseudomonas (P. fragi, P. putida) and LAB (Leuconostoc mesenteroides, Lactobacillus sakei) Strains and Their Volatilome Profile During Storage of Sterile Pork Meat Using GC/MS and Data Analytics.
Olga S PapadopoulouVasilis IliopoulosGeorge-John E NychasEfstathios Z PanagouNikos G ChorianopoulosChrysoula C TassouGeorge-John E NychasPublished in: Foods (Basel, Switzerland) (2020)
The aim of the present study was to investigate the evolution of the volatile compounds of aerobically stored sterile pork meat as a consequence of the metabolic activities of inoculated specific spoilage microorganisms. Thus, Pseudomonas fragi, Pseudomonas putida, Lactobacillus sakei and Leuconostoc mesenteroides were inoculated in monocultures, dual cultures and a cocktail culture of all strains on sterile pork meat stored aerobically at 4 and 10 °C. Microbiological and sensory analyses, as well as pH measurements, were performed, along with headspace solid-phase microextraction gas chromatography/mass spectroscopy (headspace SPME-GC/MS) analysis. Data analytics were used to correlate the volatile compounds with the spoilage potential of each stain using multivariate data analysis. The results for the sensory discrimination showed that the volatiles that dominated in spoiled samples consisted mostly of alcohols, ketones and two esters (butyl acetate and ethyl acetate), while at fresh samples, dimethyl sulfide, furans, acetoin and ethyl lactate were detected. On the other hand, 2-butanone, diacetyl and acetaldehyde were among the volatile compounds that were mainly correlated with the inoculated meat during storage. In addition, P. fragi was positively correlated with a higher number of volatiles compared to the other strains, strengthening the hypothesis that volatile compound production is strain-dependent.
Keyphrases
- gas chromatography
- data analysis
- gas chromatography mass spectrometry
- mass spectrometry
- tandem mass spectrometry
- big data
- high resolution mass spectrometry
- escherichia coli
- solid phase extraction
- biofilm formation
- liquid chromatography
- high resolution
- electronic health record
- room temperature
- ionic liquid
- risk assessment
- human health
- machine learning
- simultaneous determination
- plant growth
- staphylococcus aureus
- cystic fibrosis
- climate change
- deep learning