In recent years, there has been a growing interest in identifying and applying new, naturally occurring molecules that promote health. Probiotics are defined as “live microorganisms which, when administered in adequate amounts, confer health benefits on the host”. Quite a few fermented products serve as the source of probiotic strains, with many factors influencing the effectiveness of probiotics, including interactions of probiotic bacteria with the host’s microbiome. Prebiotics contain no microorganisms, only substances which stimulate their growth. Prebiotics can be obtained from various sources, including breast milk, soybeans, and raw oats, however, the most popular prebiotics are the oligosaccharides contained in plants. Recent research increasingly claims that probiotics and prebiotics alleviate many disorders related to the immune system, cancer metastasis, type 2 diabetes, and obesity. However, little is known about the role of these supplements as important dietary components in preventing or treating cardiovascular disease. Still, some reports and clinical studies were conducted, offering new ways of treatment. Therefore, the aim of this review is to discuss the roles of gut microbiota, probiotics, and prebiotics interventions in the prevention and treatment of cardiovascular disease.

This paper describes the possibility of electronic nose-based detection and discrimination of volatile compound profiles of coffee from different countries roasted in a Gothot roaster under identical time and thermal regimes. The material used in the study was roasted Arabica coffee beans from Brazil, Ethiopia, Guatemala, Costa Rica, and Peru. The analyses were carried out with the use of the Agrinose electronic nose designed and constructed at the Institute of Agrophysics of the Polish Academy of Sciences in Lublin. The results of the volatile compound profile analysis provided by the Agrinose device were verified with the GC-MS technique. Chemometric tests demonstrated a dominant role of alcohols, acids, aldehydes, azines, and hydrazides in the coffee volatile compound profile. The differences in their content had an impact on the odor profile of the coffees originating from the different countries. High content of pyridine from the group of azines was detected in the coffee from Peru and Brazil despite the same roasting conditions. The results of the Agrinose analysis of volatile substances were consistent and correlated with the GC-MS results. This suggests that the Agrinose is a promising tool for selection of coffees based on their volatile compound profile.

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A b s t r a c t. Investigations were performed to examine the possibility of using an electronic nose to monitor development of fungal microflora during the first eighteen days of rapeseed storage. The Cyranose 320 device manufactured by Sensigent was used to analyse volatile organic compounds. Each sample of infected material was divided into three parts and the degree of spoilage was measured in three ways: analysis of colony forming units, determination of ergosterol content, and measurement of volatile organic compounds with the e-nose. Principal component analysis was performed on the generated patterns of signals and six groups of different spoilage levels were isolated. An analysis of sensorgrams for a few sensors with a strong signal for each group of rapeseed spoilage was performed. The ratio of the association time to the steady state was calculated. This ratio was different for the low level and the highest level of ergosterol and colony forming units. The results have shown that the e-nose can be a useful tool for quick estimation of the degree of rapeseed spoilage.

The paper presents application of a new three‐parameter method for identification of volatile organic compounds (VOCs) and creation of fingerprints based on the impregnation time (tIM), cleaning time (tCL), and maximum response ([ΔR/R]max) of chemically sensing sensors for detecting spoilage of agricultural commodities. The novelty of this method consists in the use of two additional parameters: an impregnation time and a cleaning time for the first time. An Agrinose built of eight metal oxide semiconductors was used for identification of loss in the rapeseed quality during a short period of storage after harvest. Principal component analysis was applied as a method of data analysis to verify the suitability of the new three‐parameter method and visualization of groups of different quality of raw materials. Fourier transform infrared spectroscopy spectra for identification of the infrared bands of fungal polysaccharides and gas chromatography‐mass spectrometry analysis of the headspace was applied to describe volatile metabolite contents in reference to the electronic nose technique. The investigations and analyses have demonstrated that the new three‐parameter method for determination of volatile compounds ([ΔR/R]max, tIM, tCL) describes the changes in VOCs more efficiently than the single‐parameter approach based only on the maximum sensor response ([ΔR/R]max). The proposed method for generation of electronic fingerprints clearly discriminated between rapeseed samples infected with field and storage microflora. Three‐parameters method can be useful for quality control in food microbiology and safety, as a rapid method of analysis and detection, including electronic nose sensor technology. Practical Application The use of the proposed method for generation of fingerprints requires no interference with the hardware of the electronic nose but necessitates modification of the software only. This facilitates implementation of the three‐parameter method in available devices. This kind of methods and devices can be useful for example in storage process with active ventilation.

Volatile organic compounds (VOCs) are natural markers useful in rapid assessment of adverse changes occurring in biological material. The use of an electronic nose seems to be a good, fast, and cheap method to determine particular VOCs. This paper presents a new method determination for VOCs and their concentration based on three sensorgram parameters: maximum of normalized sensor response, reaction time, and cleaning time measured from the end of the test to the half value of the maximum of normalized sensor response. The novelty of the method consists in the use for the first time of two parameters: reaction time and cleaning time measured from the end of the test to the half value of the maximum of normalized sensor response. The VOC sensorgrams at different VOC concentrations (26 to 3,842 ppm) were measured by an electronic nose Food Volatile Compound Analyzer (Agrinose) equipped with eight metal oxide semiconductor sensors dedicated to detect different gases. In the present studies, only six sensors that best respond to the VOCs were used. The highest responses to VOCs were obtained for two sensors—TGS2602 and AS‐MLV‐P2. The results showed that the dependence between the sensorgram parameters on VOC concentration was well described by a logarithmic curve in the whole range of concentrations. Detailed analysis revealed that the cleaning time increases with an increase in the number of carbon atoms in aliphatic molecules. The principal component analysis (PCA) was used to verify the utility of the new three parameters method in VOCs differentiation. The PCA analysis of these parameters showed that maximum of the normalized sensor response alone, which has been used for identification of particular VOCs so far, could not be regarded as a good parameter used for this purpose. Application of all the three parameters gave the best results in VOC identification. The research indicates that the use of three parameters of a volatile compound instead of only one parameter can allow precise determination of substances. Moreover, the results indicate that the analyzed parameters depend on the chemical structure of VOCs.

The article presents an attempt to use an electronic nose together with a new three-parameter method for generation of a digital smellprint in order to specify the mode of processing of rapeseed based on the analysis of volatile compounds contained in cold-pressed rapeseed oil. Prior to the pressing process, the seeds were roasted or improperly stored to obtain oil samples with varied technological quality. The quality of pressed oils was evaluated by determination of the acid value. Furthermore, changes in oil colour were assessed with the use of an imaging colorimeter. Volatile compounds were determined with the use of gas chromatography and an electronic nose with a metal oxide semiconductor (MOS) sensor matrix. It was found that the mode of seed pre-treatment before pressing did not change the colour of the oil significantly. However, it influenced the profile of volatile organic compounds and changed their proportions. Ketones represented the largest proportion of volatile compounds determined for roasted samples and those pressed from seeds moistened up to 25% (w.b.). Alcohols dominated in samples moistened up to 10 and 12%, terpenes were the dominant volatile compounds in samples roasted at 140°C, and other volatile compounds dominated in samples moistened up to 10 and 20% (w.b.). In turn, esters and aromatic compounds accounted for the lowest proportion in the analysed samples. The results shown by the electronic nose were correlated with the presence of particular groups of volatile compounds in rapeseed oil.An enose for analysis of rapeseed oil R. Rusinek et al. 2162

The frequent occurrence of adulterated or counterfeit plant products sold in worldwide commercial markets has created the necessity to validate the authenticity of natural plant-derived palatable products, based on product-label composition, to certify pricing values and for regulatory quality control (QC). The necessity to confirm product authenticity before marketing has required the need for rapid-sensing, electronic devices capable of quickly evaluating plant product quality by easily measurable volatile (aroma) emissions. An experimental MAU-9 electronic nose (e-nose) system, containing a sensor array with 9 metal oxide semiconductor (MOS) gas sensors, was developed with capabilities to quickly identify and classify volatile essential oils derived from fruit and herbal edible-plant sources. The e-nose instrument was tested for efficacy to discriminate between different volatile essential oils present in gaseous emissions from purified sources of these natural food products. Several chemometric data-analysis methods, including pattern recognition algorithms, principal component analysis (PCA), and support vector machine (SVM) were utilized and compared. The classification accuracy of essential oils using PCA, LDA and QDA, and SVM methods was at or near 100%. The MAU-9 e-nose effectively distinguished between different purified essential oil aromas from herbal and fruit plant sources, based on unique e-nose sensor array responses to distinct, essential-oil specific mixtures of volatile organic compounds (VOCs).