Investigation of spoilage in saveloy samples inoculated with four potential spoilage bacteria

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning

Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns during storage. On this basis, machine learning would help to process complex volatolomic data and predict pork microbial quality efficiently. This study focused on (1) investigating model generalizability based on different nested cross-validation settings, and (2) comparing the predictive power and feature importance of nine algorithms, including Artificial Neural Network (ANN), k-Nearest Neighbors, Support Vector Regression, Decision Tree, Partial Least Squares Regression, and four ensemble learning models. The datasets used contain 37 VOCs' concentrations (input) and total plate counts (TPC, output) of 350 pork samples with different storage times, including 225 pork loin samples stored under three high-O2 and three low-O2 conditions, and 125 commercially packaged products. An appropriate choice of cross-validation strategies resulted in trustworthy and relevant predictions. When trained on all possible selections of two high-O2 and two low-O2 conditions, ANNs produced satisfactory TPC predictions of unseen test scenarios (one high-O2 condition, one low-O2 condition, and the commercial products). ANN-based bagging outperformed other employed models, when TPC exceeded ca. 6 log CFU/g. VOCs including benzaldehyde, 3-methyl-1-butanol, ethanol and methyl mercaptan were identified with high feature importance. This elaborated case study illustrates great prospects of real-time detection techniques and machine learning in meat quality prediction. Further investigations on handling low VOC levels would enhance the model performance and decision making in commercial meat quality control.

Microbial volatile organic compounds as novel indicators of anaerobic digestion instability: Potential and challenges

The wide application of anaerobic digestion (AD) technology is limited by process fluctuations. Thus, process monitoring based on screening state parameters as early warning indicators (EWI) is a top priority for AD facilities. However, predicting anaerobic digester stability based on such indicators is difficult, and their threshold values are uncertain, case-specific, and sometimes produce conflicting results. Thus, new EWI should be proposed to integrate microbial and metabolic information. These microbial volatile organic compounds (mVOCs) including alkanes, alkenes, alkynes, aromatic compounds are produced by microorganisms (bacteria, archaea and fungi), which might serve as a promising diagnostic tool for environmental monitoring. Moreover, mVOCs diffuse in both gas and liquid phases and are considered the language of intra kingdom microbial interactions. Herein, we highlight the potential of mVOCs as EWI for AD process instability, including discussions regarding characteristics and sources of mVOCs as well as sampling and determination methods. Furthermore, existing challenges must be addressed, before mVOCs profiling can be used as an early warning system for diagnosing AD process instability, such as mVOCs sampling, analysis and identification. Finally, we discuss the potential biotechnology applications of mVOCs and approaches to overcome the challenges regarding their application.

Selected-ion flow-tube mass spectrometry for the identification of volatile spoilage markers for fresh pork packaged under modified atmospheres

Microbial behavior during meat storage leads to the generation of volatile organic compounds (VOCs) and unpleasant off-odors. This study focused on a novel real-time analytical method, selected-ion flow-tube mass spectrometry (SIFT-MS), to monitor VOC quality and identify spoilage indicators for fresh pork stored under different packaging atmospheres (air, 70/0/30, 70/30/0, 5/30/65, 0/30/70 - v/v% O₂/CO₂/N₂) at 4 °C. A comprehensive selection methodology was used to identify compounds with good instrumental data quality as well as a strong relationship with microbial growth and olfactory rejection. Based on the volatolome quantified by SIFT-MS, storage periods and conditions can be discriminated using multivariate statistics. Acetoin (or ethyl acetate) represented a significant pork quality marker for high-O₂ conditions, whereas ethanol, 3-methylbutanal and sulfur compounds can indicate the anaerobic storage progress. Considering the applicability in monitoring different VOC profiles, SIFT-MS is expected to be promising in many storage scenarios to improve analytical efficiency and ensure reliability.

Analysis of Microbial Diversity and Dynamics During Bacon Storage Inoculated With Potential Spoilage Bacteria by High-Throughput Sequencing

Staphylococcus xylosus, Leuconostoc mesenteroides, Carnobacterium maltaromaticum, Leuconostoc gelidum, and Serratia liquefaciens were investigated for their roles in in the spoilage of sterilized smoked bacon. These five strains, individually and in combination, were applied as starters on sliced bacon at 4–5 log₁₀ CFU/g using a hand-operated spraying bottle and stored for 45 days at 0–4°C. Dynamics, diversity, and succession of microbial community during storage of samples were studied by high-throughput sequencing (HTS) of the V3–V4 region of the 16S rRNA gene. A total of 367 bacterial genera belonging to 21 phyla were identified. Bacterial counts in all the inoculated specimens increased significantly within the first 15 days while the microbiota developed into more similar communities with increasing storage time. At the end of the storage time, the highest abundance of Serratia (96.46%) was found in samples inoculated with S. liquefaciens. Similarly, for samples inoculated with C. maltaromaticum and L. mesenteroides, a sharp increase in Carnobacterium and Leuconostoc abundance was observed as they reached a maximum relative abundance of 97.95 and 81.6%, respectively. Hence, these species were not only the predominant ones but could also have been the more competitive ones, potentially inhibiting the growth of other microorganisms. By analyzing the bacterial load of meat products using the SSO model, the relationships between the microbial communities involved in spoilage can be understood to assist further research.

Application of a path-modelling approach for deciphering causality relationships between microbiota, volatile organic compounds and off-odour profiles during meat spoilage

Microbiological spoilage of meat is considered as a process which involves mainly bacterial metabolism leading to degradation of meat sensory qualities. Studying spoilage requires the collection of different types of experimental data encompassing microbiological, physicochemical and sensorial measurements. Within this framework, the objective herein was to carry out a multiblock path modelling workflow to decipher causality relationships between different types of spoilage-related responses: composition of microbiota, volatilome and off-odour profiles. Analyses were performed with the Path-ComDim approach on a large-scale dataset collected on fresh turkey sausages. This approach enabled to quantify the importance of causality relationships determined a priori between each type of responses as well as to identify important responses involved in spoilage, then to validate causality assumptions. Results were very promising: the data integration confirmed and quantified the causality between data blocks, exhibiting the dynamical nature of spoilage, mainly characterized by the evolution of off-odour profiles caused by the production of volatile organic compounds such as ethanol or ethyl acetate. This production was possibly associated with several bacterial species like Lactococcus piscium, Leuconostoc gelidum, Psychrobacter sp. or Latilactobacillus fuchuensis. Likewise, the production of acetoin and diacetyl in meat spoilage was highlighted. The Path-ComDim approach illustrated here with meat spoilage can be applied to other large-scale and heterogeneous datasets associated with pathway scenarios and represents a promising key tool for deciphering causality in complex biological phenomena.

Spoilage of Chilled Fresh Meat Products during Storage: A Quantitative Analysis of Literature Data

A literature search was performed on spoilage of fresh meat products by combining keyword query, text mining and expert elicitation. From the 258 collected studies, a quantitative analysis was first performed to identify the methods which are the most used to evaluate spoilage beside the preservation strategies suggested. In a second step focusing on a subset of 24 publications providing quantitative data on spoilage occurrence time, associations between spoilage occurrence time of meat products and specific spoilage indicators were investigated. The analysis especially focused on factors well represented in the 24 publications, i.e., gas packaging (O2 and CO2) and storage temperature. Relationships between spoilage occurrence and several microbiological indicators were also sought. The results point out possible advantages of removing dioxygen in packaging to delay spoilage occurrence, whereas, in the presence of dioxygen, the carbon dioxide proportion in the gas mixtures was shown to influence spoilage occurrence. The collected data clearly reveal a potentially protective role of lactic acid bacteria. Besides, while a spoilage role could be attributed to Pseudomonas spp., the growth of mesophilic aerobic microbes, Brochothrix spp. and Enterobacteriaceae seemed independent of spoilage occurrence time.

Assessment of Spoilage Bacterial Communities in Food Wrap and Modified Atmospheres-Packed Minced Pork Meat Samples by 16S rDNA Metagenetic Analysis

Although several studies have focused on the dynamics of bacterial food community, little is known about the variability of batch production and microbial changes that occur during storage. The aim of the study was to characterize the microbial spoilage community of minced pork meat samples, among different food production and storage, using both 16S rRNA gene sequencing and classical microbiology. Three batches of samples were obtained from four local Belgian facilities (A–D) and stored until shelf life under food wrap (FW) and modified atmosphere packaging (MAP, CO₂ 30%/O₂ 70%), at constant and dynamic temperature. Analysis of 288 samples were performed by 16S rRNA gene sequencing in combination with counts of psychrotrophic and lactic acid bacteria at 22°C. At the first day of storage, different psychrotrophic counts were observed between the four food companies (Kruskal-Wallist test, p-value < 0.05). Results shown that lowest microbial counts were observed at the first day for industries D and A (4.2 ± 0.4 and 5.6 ± 0.1 log CFU/g, respectively), whereas industries B and C showed the highest results (7.5 ± 0.4 and 7.2 ± 0.4 log CFU/g). At the end of the shelf life, psychrotrophic counts for all food companies was over 7.0 log CFU/g. With metagenetics, 48 OTUs were assigned. At the first day, the genus Photobacterium (86.7 and 19.9% for food industries A and C, respectively) and Pseudomonas (38.7 and 25.7% for food companies B and D, respectively) were dominant. During the storage, a total of 12 dominant genera (>5% in relative abundance) were identified in MAP and 7 in FW. Pseudomonas was more present in FW and this genus was potentially replaced by Brochothrix in MAP (two-sided Welch’s t-test, p-value < 0.05). Also, a high Bray-Curtis dissimilarity in genus relative abundance was observed between food companies and batches. Although the bacteria consistently dominated the microbiota in our samples are known, results indicated that bacterial diversity needs to be addressed on the level of food companies, batches variation and food storage conditions. Present data illustrate that the combined approach provides complementary results on microbial dynamics in minced pork meat samples, considering batches and packaging variations.

Understanding spoilage microbial community and spoilage mechanisms in foods of animal origin

The increasing global population has resulted in increased demand for food. Goods quality and safe food is required for healthy living. However, food spoilage has resulted in food insecurity in different regions of the world. Spoilage of food occurs when the quality of food deteriorates from its original organoleptic properties observed at the time of processing. Food spoilage results in huge economic losses to both producers (farmers) and consumers. Factors such as storage temperature, pH, water availability, presence of spoilage microorganisms including bacteria and fungi, initial microbial load (total viable count-TVC), and processing influence the rate of food spoilage. This article reviews the spoilage microbiota and spoilage mechanisms in meat and dairy products and seafood. Understanding food spoilage mechanisms will assist in the development of robust technologies for the prevention of food spoilage and waste.

Bacterial diversity analysis of pork longissimus lumborum following long term ohmic cooking and water bath cooking by amplicon sequencing of 16S rRNA gene

The bacterial ecology of long term ohmic- (LTOH) and water bath- (WB) cooked pork longissimus lumborum during refrigerated storage was investigated by culture-dependent and amplicon sequencing of 16S rRNA gene. High bacterial diversity was observed in both LTOH- and WB-cooked meat, and the diversity decreased with prolonged storage, however, it was more complex in LTOH-cooked meat compared with WB treated ones. Bacillus, Pseudomonas, Enterococcus and Lactococcus were the most prevalent genera in the first two weeks and were replaced by Carnobacterium by the end of storage. Brevundimonas, Bacteroidaceae, Lactobacillaceae, uncultured Clostridiales Family_XIII, Alcaligenaceae and Micrococcales were more abundant in LTOH-cooked meat, while only Moraxellaceae were more abundant in WB-cooked samples. The different abundances may have resulted from the reaction of bacteria to different heating mechanisms. Overall, LTOH-cooked meat has a similar shelf-life with shorter processing time compared to WB treated ones.

Volatile organic compounds and Photobacterium phosphoreum associated with spoilage of modified-atmosphere-packaged raw pork

Accumulation of volatile organic compounds was monitored in association with sensory quality, bacterial concentrations and culture-independent microbial community analyses in raw pork loin and pork collar during storage under high-oxygen modified atmosphere at +4 °C. Of the 48 volatile compounds detected in the pork samples, the levels of acetoin, diacetyl and 3-methyl-1-butanol had the highest correlations with the sensory scores and bacterial concentrations. These compounds accumulated in all of the four monitored lots of non-sterile pork but not in the sterilized pork during chilled storage. According to the culture-dependent and culture-independent characterization of bacterial communities, Brochothrix thermosphacta, lactic acid bacteria (Carnobacterium, Lactobacillus, Lactococcus, Leuconostoc, Weissella) and Photobacterium spp. predominated in pork samples. Photobacterium spp., typically not associated with spoilage of meat, were detected also in 8 of the 11 retail packages of pork investigated subsequently. Eleven isolates from the pork samples were shown to belong to Photobacterium phosphoreum by phenotypic tests and sequencing of the 16S rRNA and gyrB gene fragments. Off-odors in pork samples with high proportion of Photobacterium spp. were associated with accumulation of acetoin, diacetyl and 3-methyl-1-butanol in meat, but these compounds did not explain all the off-odors reported in sensory analyses.