Quantifying meat spoilage with an array of biochemical indicators

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. It is crucial to validate and establish new rapid methods for the accurate detection of microbial spoilage of meats. In the current thesis, the microbial association of meat was monitored in parallel with the chemical changes, pH measurements and sensory analysis. Several chemical analytical techniques were applied to explore their dynamics on quantifying spoilage indicators and evaluate the shelf life of meat products. The applied analytical methods used were Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, image analysis, high performance liquid chromatography (HPLC) and gas chromatography/mass spectroscopy (GC/MS). The first component of the study was designed to evaluate the potential of FTIR spectroscopy as a rapid, reagent-less and non-destructive analytical technique in estimating the freshness and shelf life of beef. For this reason, minced beef samples survey from the Greek market), beef fillet samples stored aerobically (0, 5, 10, 15 and 20ºC) and minced beef samples stored aerobically, under modified atmosphere packaging (MAP) and active packaging (0, 5, 10, and 15ºC), were analysed with FTIR. The statistical analysis from the survey revealed that the impact of the market type, the packaging type, the day and the season of purchase had a significant effect on the microbial association of mince. Furthermore, the Principal Components Analysis (PCA) and Factorial Discriminant Analysis (FDA), applied to the FTIR spectral data, showed discrimination of the samples based on freshness, packaging type, the day and season of purchase. The validated overall classification accuracies VCA) were 61.7% for the freshness, 79.2% for the packaging 80.5% for the season and 61.7% for the day of purchase. The shelf life of beef fillets and minced beef was evaluated and correlated with FTIR spectral data. This analysis revealed discrimination of the samples regarding their freshness (VCA 81.6% for the fillets, 76.34% for the mince), their storage temperature (VCA 55.3% and 88.1% for the fillets and mince, respectively) and the packaging type (VCA 92.5% for the mince). Moreover, estimations of the different microbial populations using Partial Least Squares Regression (PLS-R) were demonstrated (e.g. Total viable counts-TVC: RMSE 1.34 for the beef fillets and 0.72 for the mince). Cont/d.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Quantifying meat spoilage with an array of biochemical indicators

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. It is crucial to validate and establish new rapid methods for the accurate detection of microbial spoilage of meats. In the current thesis, the microbial association of meat was monitored in parallel with the chemical changes, pH measurements and sensory analysis. Several chemical analytical techniques were applied to explore their dynamics on quantifying spoilage indicators and evaluate the shelf life of meat products. The applied analytical methods used were Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, image analysis, high performance liquid chromatography (HPLC) and gas chromatography/mass spectroscopy (GC/MS). The first component of the study was designed to evaluate the potential of FTIR spectroscopy as a rapid, reagent-less and non-destructive analytical technique in estimating the freshness and shelf life of beef. For this reason, minced beef samples survey from the Greek market), beef fillet samples stored aerobically (0, 5, 10, 15 and 20ºC) and minced beef samples stored aerobically, under modified atmosphere packaging (MAP) and active packaging (0, 5, 10, and 15ºC), were analysed with FTIR. The statistical analysis from the survey revealed that the impact of the market type, the packaging type, the day and the season of purchase had a significant effect on the microbial association of mince. Furthermore, the Principal Components Analysis (PCA) and Factorial Discriminant Analysis (FDA), applied to the FTIR spectral data, showed discrimination of the samples based on freshness, packaging type, the day and season of purchase. The validated overall classification accuracies VCA) were 61.7% for the freshness, 79.2% for the packaging 80.5% for the season and 61.7% for the day of purchase. The shelf life of beef fillets and minced beef was evaluated and correlated with FTIR spectral data. This analysis revealed discrimination of the samples regarding their freshness (VCA 81.6% for the fillets, 76.34% for the mince), their storage temperature (VCA 55.3% and 88.1% for the fillets and mince, respectively) and the packaging type (VCA 92.5% for the mince). Moreover, estimations of the different microbial populations using Partial Least Squares Regression (PLS-R) were demonstrated (e.g. Total viable counts-TVC: RMSE 1.34 for the beef fillets and 0.72 for the mince). Cont/d

Rapid qualitative and quantitative detection of beef fillets spoilage based on Fourier transform infrared spectroscopy data and artificial neural networks

A machine learning strategy in the form of a multilayer perceptron (MLP) neural network was employed to correlate Fourier transform infrared (FTIR) spectral data with beef spoilage during aerobic storage at chill and abuse temperatures. Fresh beef fillets were packaged under aerobic conditions and left to spoil at 0, 5, 10, 15, and 20 °C for up to 350 hours. FTIR spectra were collected directly from the surface of meat samples, whereas total viable counts of bacteria were obtained with standard plating methods. Sensory evaluation was performed during storage and samples were attributed into three quality classes namely fresh, semi-fresh, and spoiled. A neural network was designed to classify beef samples to one of the three quality classes based on the biochemical profile provided by the FTIR spectra, and in parallel to predict the microbial load (as total viable counts) on meat surface. The results obtained demonstrated that the developed neural network was able to classify with high accuracy the beef samples in the corresponding quality class using their FTIR spectra. The network was able to classify correctly 22 out of 24 fresh samples (91.7%), 32 out of 34 spoiled samples (94.1%), and 13 out of 16 semi-fresh samples (81.2%). No fresh sample was misclassified as spoiled and vice versa. The performance of the network in the prediction of microbial counts was based on graphical plots and statistical indices (bias and accuracy factors, standard error of prediction, mean relative and mean absolute percentage residuals). Results demonstrated good correlation of microbial load on beef surface with spectral data. The results of this work indicated that the biochemical fingerprints during beef spoilage obtained by FTIR spectroscopy in combination with the appropriate machine learning strategy have significant potential for rapid assessment of meat spoilage

A comparison of artificial neural networks and partial least squares modelling for the rapid detection of the microbial spoilage of beef fillets based on Fourier transform infrared spectral fingerprints

A series of partial least squares (PLS) models were employed to correlate spectral data from FTIR analysis with beef fillet spoilage during aerobic storage at different temperatures (0, 5, 10, 15, and 20°C) using the dataset presented by Argyri etal. (2010). The performance of the PLS models was compared with a three-layer feed-forward artificial neural network (ANN) developed using the same dataset. FTIR spectra were collected from the surface of meat samples in parallel with microbiological analyses to enumerate total viable counts. Sensory evaluation was based on a three-point hedonic scale classifying meat samples as fresh, semi-fresh, and spoiled. The purpose of the modelling approach employed in this work was to classify beef samples in the respective quality class as well as to predict their total viable counts directly from FTIR spectra. The results obtained demonstrated that both approaches showed good performance in discriminating meat samples in one of the three predefined sensory classes. The PLS classification models showed performances ranging from 72.0 to 98.2% using the training dataset, and from 63.1 to 94.7% using independent testing dataset. The ANN classification model performed equally well in discriminating meat samples, with correct classification rates from 98.2 to 100% and 63.1 to 73.7% in the train and test sessions, respectively. PLS and ANN approaches were also applied to create models for the prediction of microbial counts. The performance of these was based on graphical plots and statistical indices (bias factor, accuracy factor, root mean square error). Furthermore, results demonstrated reasonably good correlation of total viable counts on meat surface with FTIR spectral data with PLS models presenting better performance indices compared to ANN

Microbial Diversity of Fermented Greek Table Olives of Halkidiki and Konservolia Varieties from Different Regions as Revealed by Metagenomic Analysis

Current information from conventional microbiological methods on the microbial diversity of table olives is insufficient. Next-generation sequencing (NGS) technologies allow comprehensive analysis of their microbial community, providing microbial identity of table olive varieties and their designation of origin. The purpose of this study was to evaluate the bacterial and yeast diversity of fermented olives of two main Greek varieties collected from different regions—green olives, cv. Halkidiki, from Kavala and Halkidiki and black olives, cv. Konservolia, from Magnesia and Fthiotida—via conventional microbiological methods and NGS. Total viable counts (TVC), lactic acid bacteria (LAB), yeast and molds, and Enterobacteriaceae were enumerated. Microbial genomic DNA was directly extracted from the olives’ surface and subjected to NGS for the identification of bacteria and yeast communities. Lactobacillaceae was the most abundant family in all samples. In relation to yeast diversity, Phaffomycetaceae was the most abundant yeast family in Konservolia olives from the Magnesia region, while Pichiaceae dominated the yeast microbiota in Konservolia olives from Fthiotida and in Halkidiki olives from both regions. Further analysis of the data employing multivariate analysis allowed for the first time the discrimination of cv. Konservolia and cv. Halkidiki table olives according to their geographical origin

Evaluating the Quality of Cheese Slices Packaged with Na-Alginate Edible Films Supplemented with Functional Lactic Acid Bacteria Cultures after High-Pressure Processing

The aim of the current study was to assess the efficacy of Na-alginate edible films as vehicles for delivering lactic acid bacteria (LAB) with functional properties to sliced cheeses, with or without high-pressure processing (HPP). A three-strain LAB cocktail (Lactococcus lactis Τ4, Leuconostoc mesenteroides Τ25 and Lacticaseibacillus paracasei Τ26) was incorporated into Na-alginate solution in a final population of 9 log CFU/mL. The cheese slices (without or with HPP treatment at 500 MPa for 2 min) were packaged in contact with the LAB edible films (LEFs), and subsequently vacuum packed and stored at 4 °C. Cheese slices without the addition of films, with or without HPP treatment, were used as controls. In all cases, microbiological, pH and sensory analyses were performed, while the presence and the relative abundance of each strain during storage was evaluated using Random Amplified Polymorphic DNA-PCR (RAPD-PCR). In addition, organic acid determination and peptide analysis were performed using high-performance liquid chromatography. The results showed that in cheeses without HPP treatment, the microbiota consisted mostly of mesophilic LAB and lactococci (>7.0 log CFU/g), while HPP caused a reduction in the indigenous microbiota population of approximately 1–1.5 log CFU/g. In the LEF samples, the populations of mesophilic LAB and lactococci were maintained at levels of >6.35 log CFU/g during storage, regardless of the HPP treatment. Sensory evaluation revealed that the LEF samples without HPP had a slightly more acidic taste compared to the control, whereas the HPP-LEF samples exhibited the best organoleptic characteristics. RAPD-PCR confirmed that the recovered strains were attributed to the three strains that had been entrapped in the films, while the strain distribution during storage was random. Overall, the results of the study are promising since the functional LAB strains were successfully delivered to the products by the edible films until the end of storage

Nonthermal Pasteurization of Fermented Green Table Olives by means of High Hydrostatic Pressure Processing

Green fermented olives cv. Halkidiki were subjected to different treatments of high hydrostatic pressure (HHP) processing (400, 450, and 500 MPa for 15 or 30 min). Total viable counts, lactic acid bacteria and yeasts/moulds, and the physicochemical characteristics of the product (pH, colour, and firmness) were monitored right after the treatment and after 7 days of storage at 20°C to allow for recovery of injured cells. The treatments at 400 MPa for 15 and 30 min, 450 MPa for 15 and 30 min, and 500 MPa for 15 min were found insufficient as a recovery of the microbiota was observed. The treatment at 500 MPa for 30 min was effective in reducing the olive microbiota below the detection limit of the enumeration method after the treatment and after 1 week of storage and was chosen as being more appropriate for storing olives for an extended time period (5 months). After 5 months of storage at 20°C, no microbiota was detected in treated samples, while significant changes for both HHP treated and untreated olives were observed for colour parameters only (minor degradation). In conclusion, HHP treatment may introduce a reliable nonthermal pasteurization method to extend the microbiological shelf-life of fermented table olives

Quality and Safety of Fresh Chicken Fillets after High Pressure Processing: Survival of Indigenous Brochothrix thermosphacta and Inoculated Listeria monocytogenes

The effect of high-pressure processing (HPP) on Listeria monocytogenes, the indigenous microbiota and the shelf-life of chicken fillets was evaluated. Chicken fillets were inoculated with different inocula (2, 4, and 6 log CFU/g) of a 4-strain cocktail of L. monocytogenes, vacuum-packed, processed or not with HPP (500 MPa/10 min) and stored at 4 °C and 12 °C. Total viable counts (TVC), L. monocytogenes, Pseudomonas spp., Brochothrix thermosphacta, lactic acid bacteria (LAB), Enterobacteriaceae and yeasts/molds were determined along with the pH and sensory analysis. Pulsed-field gel electrophoresis (PFGE) was used to monitor the succession of indigenous Brochothrix isolates and inoculated Listeria strains. The main spoilage microorganism of HPP-treated samples was B. thermosphacta detected after 3 days of storage. HPP decreased the inoculated Listeria population. For the low and medium inoculum case it was detected throughout the shelf-life at both temperatures in populations near to the detection limit or after enrichment. In the high inoculum case, the pathogen decreased ≥5-log cycles after HPP, while increased subsequently to 1.6 and 4.5 log CFU/g at 4 °C and 12 °C, respectively, by the end of the shelf-life. PFGE showed that Brochothrix isolates exhibited a significant diversity among control samples, whereas this was limited for the HPP-treated samples. The survival and distribution of different Listeria strains depended on the initial inoculum and storage temperature. In conclusion, HPP increased the shelf-life (for 5 and 4 days, at 4 °C and 12 °C, respectively) and enhanced the safety of chicken meat

Recent Advances and Applications of Rapid Microbial Assessment from a Food Safety Perspective

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to “translate” measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses

Antimicrobial Activity of Oregano Essential Oil Incorporated in Sodium Alginate Edible Films: Control of Listeria monocytogenes and Spoilage in Ham Slices Treated with High Pressure Processing

The aim of the study was to evaluate the efficacy of oregano essential oil (OEO) incorporated in Na-alginate edible films when applied to sliced ham inoculated with a cocktail of Listeria monocytogenes strains, with or without pretreatment by high pressure processing (HPP). Microbiological, physicochemical and sensory analyses (in Listeria-free slices) were performed, while, the presence/absence and the relative abundance of each Listeria strain, was monitored by pulsed field gel electrophoresis (PFGE). The OEO incorporation in the films, caused approximately 1.5 log reduction in Listeria population at 8 and 12 °C at the end of the storage period, and almost 2.5 log reduction at 4 °C. The HPP treatment caused 1 log reduction to the initial Listeria population, while levels kept on decreasing throughout the storage for all the tested temperatures. The pH of the samples was higher in the cases where HPP was involved, and the samples were evaluated as less spoiled. Furthermore, the presence of OEO in the films resulted in color differences compared to the control samples, whilst the aroma of these samples was improved. In conclusion, the combined application of HPP and OEO edible films on the slices, led to a significant reduction or absence of the pathogen