Application of an Electronic Nose and HS-SPME/GC-MS to Determine Volatile Organic Compounds in Fresh Mexican Cheese

Microbial food spoilage: impact, causative agents and control strategies

Microbial food spoilage is a major contributor to food waste and, hence, to the negative environmental sustainability impacts of food production and processing. Globally, it is estimated that 15-20% of food is wasted, with waste, by definition, occurring after primary production and harvesting (for example, in households and food service establishments). Although the causative agents of food spoilage are diverse, many microorganisms are major contributors across different types of foods. For example, the genus Pseudomonas causes spoilage in various raw and ready-to-eat foods. Aerobic sporeformers (for example, members of the genera Bacillus, Paenibacillus and Alicyclobacillus) cause spoilage across various foods and beverages, whereas anaerobic sporeformers (for example, Clostridiales) cause spoilage in a range of products that present low-oxygen environments. Fungi are also important spoilage microorganisms, including in products that are not susceptible to bacterial spoilage due to their low water activity or low pH. Strategies that can reduce spoilage include improved control of spoilage microorganisms in raw material and environmental sources as well as application of microbicidal or microbiostatic strategies (for example, to products and packaging). Emerging tools (for example, systems models and improved genomic tools) represent an opportunity for rational design of systems, processes and products that minimize microbial food spoilage.

Preserving the Aromatic Profile of Aged Toma Piemontese PDO Cheese with Gaseous Ozone Technology: A Quality Assessment via SPME-GC-MS/E-Nose

The efficacy of low gaseous ozone concentrations (300 ppb and 400 ppb) in controlling spoilage microflora and preserving the quality of the aged Toma Piemontese PDO cheese was explored. The research integrates consumer tests, Gas Chromatography-Mass Spectrometry (GC-MS) with Solid phase Microextraction (SPME) fiber and Electronic Nose (e-nose) analysis to conduct a detailed assessment of the cheese's aromatic composition. Results indicate that low ozone concentrations significantly affected spoilage microflora, preserving the overall quality. Through GC-FID (Flame Ionization Detection) analysis, 22 of all identified compounds by GC-MS were quantified, including ethyl acetate (sweety), diacetyl and acetoin (buttery). Compared with the untreated sample, ozone treatments maintained the distinctive characteristics of Toma Piemontese PDO cheese, reducing the formation of off-flavors-related compounds (i.e., ethanol). Moreover, ozone-treated samples correlated with positive aroma scores given by consumers. However, sensory perception involves complex interactions among aroma compounds, highlighting the importance of advanced approaches. The utilization of a 12-sensor Quartz Microbalance (QMB) e-nose played a crucial role in identifying subtle differences in aroma, contributing to a more nuanced understanding of ozone treatments on the cheese's sensory profile. In conclusion, this research demonstrates the potential of ozone technology as a viable and effective method for improving the quality of aged Toma Piemontese PDO cheese.

Portable and miniature sensors in supply chain for food authentication: a review

Food fraud, a pervasive issue in the global food industry, poses significant challenges to consumer health, trust, and economic stability, costing an estimated $10-15 billion annually. Therefore, there is a rising demand for developing portable and miniature sensors that facilitate food authentication throughout the supply chain. This review explores the recent advancements and applications of portable and miniature sensors, including portable/miniature near-infrared (NIR) spectroscopy, e-nose and colorimetric sensors based on nanozyme for food authentication within the supply chain. After briefly presenting the architecture and mechanism, this review discusses the application of these portable and miniature sensors in food authentication, addressing the challenges and opportunities in integrating and deploying these sensors to ensure authenticity. This review reveals the enhanced utility of portable/miniature NIR spectroscopy, e-nose, and nanozyme-based colorimetric sensors in ensuring food authenticity and enabling informed decision-making throughout the food supply chain.

Dung Beetle Optimizer Algorithm and Machine Learning-Based Genome Analysis of Lactococcus lactis: Predicting Electronic Sensory Properties of Fermented Milk

In the global food industry, fermented dairy products are valued for their unique flavors and nutrients. Lactococcus lactis is crucial in developing these flavors during fermentation. Meeting diverse consumer flavor preferences requires the careful selection of fermentation agents. Traditional assessment methods are slow, costly, and subjective. Although electronic-nose and -tongue technologies provide objective assessments, they are mostly limited to laboratory environments. Therefore, this study developed a model to predict the electronic sensory characteristics of fermented milk. This model is based on the genomic data of Lactococcus lactis, using the DBO (Dung Beetle Optimizer) optimization algorithm combined with 10 different machine learning methods. The research results show that the combination of the DBO optimization algorithm and multi-round feature selection with a ridge regression model significantly improved the performance of the model. In the 10-fold cross-validation, the R2 values of all the electronic sensory phenotypes exceeded 0.895, indicating an excellent performance. In addition, a deep analysis of the electronic sensory data revealed an important phenomenon: the correlation between the electronic sensory phenotypes is positively related to the number of features jointly selected. Generally, a higher correlation among the electronic sensory phenotypes corresponds to a greater number of features being jointly selected. Specifically, phenotypes with high correlations exhibit from 2 to 60 times more jointly selected features than those with low correlations. This suggests that our feature selection strategy effectively identifies the key features impacting multiple phenotypes, likely originating from their regulation by similar biological pathways or metabolic processes. Overall, this study proposes a more efficient and cost-effective method for predicting the electronic sensory characteristics of milk fermented by Lactococcus lactis. It helps to screen and optimize fermenting agents with desirable flavor characteristics, thereby driving innovation and development in the dairy industry and enhancing the product quality and market competitiveness.

Flavor profiling and gene expression studies of indigenous aromatic rice variety (Mushk Budiji) grown at different altitudes of Highland Himalayan regions

Mushk Budiji-an indigenous aromatic rice variety is usually grown at an altitude ranging from 5000 to 7000 ft above mean sea level in Highland Himalayas. This study was conducted to investigate the effects of altitude, soil nitrogen content and climatic conditions (temperature) of the selected locations on the flavor profile of Mushk Budiji using gas chromatography-mass spectroscopy (GC-MS) and electronic nose (E-nose). E-nose being rapid and non-destructive method was used to validate the results of volatile aromatic compounds obtained using GC-MS in Mushk Budiji. Around 35 aromatic compounds were identified in Mushk Budiji rice samples. Highest volatile peak area percentage (105.41%) was recorded for Mushk Budji grown at an altitude of 5216.53 ft. Highest E-nose score (2.52) was obtained at an altitude of 6299.21 ft. Over-expression of fatty acid degradation and linoleic acid metabolism genes was observed at higher altitudes, whereas lipid biosynthesis was negatively influenced by higher altitude. Fatty acid degradation and linoleic acid metabolism is responsible for the synthesis of volatile aromatic compounds in Mushk Budiji. This study will therefore be the path finder for investigating the intricate mechanism behind the role of altitude on aroma development in Mushk Budiji rice for future studies.

The Aroma Composition of Koryciński Cheese Ripened in Different Temperatures

As a regional product, Koryciński cheese is one of the most important cheeses in the Podlasie region of Poland. In this study, the influence of technological processes, such as ripening, on shaping the organoleptic characteristics of cheese was determined. Korycin-type cheeses are produced from cow's milk according to traditional technology. The ripening process lasted 466 h at 5 °C, 10 °C, and 15 °C. The aging temperature had a decisive influence on the number of esters and organic acids formed, which were analyzed by gas chromatography-mass spectrometry (GC/MS). The organoleptic properties of the cheeses were also related to the ripening temperature.

Aromatic Characteristics of Passion Fruit Wines Measured by E-Nose, GC-Quadrupole MS, GC-Orbitrap-MS and Sensory Evaluation

This study investigated the volatile composition and aromatic features of passion fruit wines using a combination of gas chromatography-quadrupole mass spectrometry (GC-qMS), gas chromatography-Orbitrap-mass spectrometry (GC-Orbitrap-MS), electronic nose (E-nose) and sensory evaluation. The results showed that these passion fruit wines possessed different aromatic features confirmed by E-nose. Seventeen sulfur compounds and seventy-eight volatiles were detected in these passion fruit wines using GC-Orbitrap-MS and GC-qMS, respectively. Forty-four volatiles significantly contributed to the overall wine aroma. These wines possessed passion fruit, mango, green apple, lemon and floral aromas confirmed by sensory evaluation. The partial least squares regression analysis indicated that sulfides, esters and terpenes, and terpenes mainly correlated to the passion fruit, mango and green apple aroma, respectively. Sulfur compounds significantly affected the aroma of passion fruit wine. The findings in this study could provide useful insight toward the quality control of passion fruit wine.

Honeycomb, a New Food Resource with Health Care Functions: The Difference of Volatile Compounds found in Apis cerana and A. mellifera Honeycombs

The honeycomb composition is very complex, containing honey, royal jelly, pollen, and propolis, and thus contains a large number of bioactive ingredients, such as polyphenols and flavonoids. In recent years, honeycomb as a new functional food resource has been favored by many bee product companies, but the basic research on honeycomb is lacking. The aim of this study is to reveal the chemical differences between A. cerana honeycombs (ACC) and A. mellifera honeycombs (AMC). In this paper, we studied the volatile organic components (VOCs) of ACC and AMC by solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME/GC-MS). A total of 114 VOCs were identified in 10 honeycombs. Furthermore, principal component analysis (PCA) revealed that the chemical composition of ACC and AMC were different. Additionally, orthogonal partial least squares discrimination analysis (OPLS-DA) revealed that benzaldehyde, octanal, limonene, ocimene, linalool, α-terpineol, and decanal are the significant VOCs in AMC extracts, which are mainly derived from propolis. OPLS-DA model also identified 2-phenylethanol, phenethyl acetate, isophorone, 4-oxoisophorone, betula, ethyl phenylacetate, ethyl palmitate, and dihydrooxophorone as potential discriminatory markers of ACC, which likely contribute to protecting the hive against microorganisms and keep it clean.