Recent developments of e-sensing devices coupled to data processing techniques in food quality evaluation: a critical review

A greater demand for high-quality food is being driven by the growth of economic and technological advancements. In this context, consumers are currently paying special attention to organoleptic characteristics such as smell, taste, and appearance. Motivated to mimic human senses, scientists developed electronic devices such as e-noses, e-tongues, and e-eyes, to spot signals relative to different chemical substances prevalent in food systems. To interpret the information provided by the sensors' responses, multiple chemometric approaches are used depending on the aim of the study. This review based on the Web of Science database, endeavored to scrutinize three e-sensing systems coupled to chemometric approaches for food quality evaluation. A total of 122 eligible articles pertaining to the e-nose, e-tongue and e-eye devices were selected to conduct this review. Most of the performed studies used exploratory analysis based on linear factorial methods, while classification and regression techniques came in the second position. Although their applications have been less common in food science, it is to be noted that nonlinear approaches based on artificial intelligence and machine learning deployed in a big-data context have generally yielded better results for classification and regression purposes, providing new perspectives for future studies.

Pipecolate and Taurine are Rat Urinary Biomarkers for Lysine and Threonine Deficiencies

BACKGROUND

The consumption of poor-quality protein increases the risk of essential amino acid (EAA) deficiency, particularly for lysine and threonine. Thus, it is necessary to be able to detect easily EAA deficiency.

OBJECTIVES

The purpose of this study was to develop metabolomic approaches to identify specific biomarkers for an EAA deficiency, such as lysine and threonine.

METHODS

Three experiments were performed on growing rats. In experiment 1, rats were fed for 3 weeks with lysine (L30), or threonine (T53)-deficient gluten diets, or nondeficient gluten diet (LT100) in comparison with the control diet (milk protein, PLT). In experiments 2a and 2b, rats were fed at different concentrations of lysine (L) or threonine (T) deficiency: L/T15, L/T25, L/T40, L/T60, L/T75, P20, L/T100 and L/T170. Twenty-four-hour urine and blood samples from portal vein and vena cava were analyzed using LC-MS. Data from experiment 1 were analyzed by untargeted metabolomic and Independent Component - Discriminant Analysis (ICDA) and data from experiments 2a and 2b by targeted metabolomic and a quantitative Partial Least- Squares (PLS) regression model. Each metabolite identified as significant by PLS or ICDA was then tested by 1-way ANOVA to evaluate the diet effect. A two-phase linear regression analysis was used to determine lysine and threonine requirements.

RESULTS

ICDA and PLS found molecules that discriminated between the different diets. A common metabolite, the pipecolate, was identified in experiments 1 and 2a, confirming that it could be specific to lysine deficiency. Another metabolite, taurine, was found in experiments 1 and 2b, so probably specific to threonine deficiency. Pipecolate or taurine breakpoints obtained give a value closed to the values obtained by growth indicators.

CONCLUSIONS

Our results showed that the EAA deficiencies influenced the metabolome. Specific urinary biomarkers identified could be easily applied to detect EAA deficiency and to determine which AA is deficient.

Consumption of Boiled, but Not Grilled, Roasted, or Barbecued Beef Modifies the Urinary Metabolite Profiles in Rats

SCOPE

The consumption of processed meat is associated with increased risk of chronic diseases, but determining how the exposure to specific cooking processes alters the metabolome is an analytical challenge. This study aims to evaluate the impact of four typical cooking methods for beef (boiling, barbecuing, grilling, and roasting) on the urinary metabolite profiles in rats, using a non-targeted approach.

METHODS AND RESULTS

Male Wistar rats (n  =  48) are fed for 3 weeks with experimental diets containing either raw or cooked (boiled, barbecued, grilled, and roasted) beef. A control group is fed with milk proteins. The 24 h-urines are analyzed using LC-MS. The consumption of boiled meat leads to the specific excretion of di- and tri-peptides (aspartyl-leucine, glycyl-aspartate, and aspartyl-prolyl-threonine) and a cyclo-prolyl-proline (p < 0.001). No singular metabolite specifically associated with the groups "grilled," "roasted," and "barbecued" meat is observed.

CONCLUSION

Urinary metabolite profiles of rats fed boiled beef are clearly distinct from those of rats fed with raw, grilled, roasted, or barbecued beef. The specific metabolites include the products of non-digested proteins and may be useful as potential intake biomarkers of this meat cooking method.

Metataxonomics, metagenomics and metabolomics analysis of the influence of temperature modification in full-scale anaerobic digesters

Full-scale anaerobic digesters' performance is regulated by modifying their operational conditions, but little is known about how these modifications affect their microbiome. In this work, we monitored two originally mesophilic (35 °C) full-scale anaerobic digesters during 476 days. One digester was submitted to sub-mesophilic (25 °C) conditions between days 123 and 373. We characterized the effect of temperature modification using a multi-omics (metataxonomics, metagenomics, and metabolomics) approach. The metataxonomics and metagenomics results revealed that the lower temperature allowed a substantial increase of the sub-dominant bacterial population, destabilizing the microbial community equilibrium and reducing the biogas production. After restoring the initial mesophilic temperature, the bacterial community manifested resilience in terms of microbial structure and functional activity. The metabolomic signature of the sub-mesophilic acclimation was characterized by a rise of amino acids and short peptides, suggesting a protein degradation activity not directed towards biogas production.

Plasma and Urinary Amino Acid-Derived Catabolites as Potential Biomarkers of Protein and Amino Acid Deficiency in Rats

OBJECTIVE

Dietary intakes must cover protein and essential amino acid (EAA) requirements. For this purpose, different methods have been developed such as the nitrogen balance method, factorial method, or AA tracer studies. However, these methods are either invasive or imprecise, and the Food and Agriculture Organization of the United Nations (FAO, 2013) recommends new methods and, in particular, metabolomics. The aim of this study is to determine total protein/EAA requirement in the plasma and urine of growing rats.

METHODS

36 weanling rats were fed with diets containing 3, 5, 8, 12, 15, and 20% protein for 3 weeks. During experimentation, urine was collected using metabolic cages, and blood from the portal vein and vena was taken at the end of the experiment. Metabolomics analyses were performed using LC-MS, and the data were analyzed with a multivariate analysis model, partial least Squares (PLS) regression, and independent component-discriminant analysis (ICDA). Each discriminant metabolite identified by PLS or ICDA was tested by one-way ANOVA to evaluate the effect of diet.

RESULTS

PLS and ICDA allowed us to identify discriminating metabolites between different diet groups. Protein deficiency led to an increase in the AA catabolism enzyme systems inducing the production of breakdown metabolites in the plasma and urine.

CONCLUSION

These results indicate that metabolites are specific for the state of EAA deficiency and sufficiency. Some types of biomarkers such as AA degradation metabolites appear to be specific candidates for protein/EAA requirement.

Assessment of substrate biodegradability improvement in anaerobic Co-digestion using a chemometrics-based metabolomic approach

Anaerobic co-digestion (AcoD) can increase methane production of anaerobic digesters in plants treating wastewater sludge by improving the nutrient balance needed for the microorganisms to grow in the digesters, resulting in a faster process stabilization. Substrate mixture proportions are usually optimized in terms of biogas production, while the metabolic biodegradability of the whole mixture is neglected in this optimisation. In this aim, we developed a strategy to assess AcoD using metabolomics data. This strategy was explored in two different systems. Specifically, we investigated the co-digestion of wastewater sludge with different proportions of either grass or fish waste using untargeted High Performance Liquid Chromatography coupled to Mass Spectrometry (HPLC-MS) metabolomics and chemometrics methods. The analysis of these data revealed that adding grass waste did not improve the metabolic biodegradability of wastewater sludge. Conversely, a synergistic effect in the metabolic biodegradability was observed when fish waste was used, this effect being the highest for 25% of fish waste. In conclusion, metabolomics can be regarded as a promising tool both for characterizing the biochemical processes occurring during anaerobic digestion, and for providing a better understanding of the anaerobic digestion processes.

Exploratory study on the possibility to link gasoline samples sharing a common source after alteration by evaporation or combustion

The source inference of ignitable liquids in forensic science is still a challenging and ongoing research area. In real case applications, specimens of different natures, which may have been exposed to fire or not, may have to be compared. These comparisons are difficult since specimens may have been altered by evaporation, combustion or both. Plus, the extent of the alteration is often difficult to evaluate. Most studies concerning source inference of ignitable liquids worked on neat samples or samples altered by evaporation. However, there is a lack of studies comparing the influence of evaporation and combustion within a source inference framework. In this study, the same collection of gasoline samples was altered by both evaporation under a nitrogen stream and combustion of the gasoline adsorbed on a matrix. The possibility to link gasoline samples sharing a common source was then explored using an adaptive untargeted chemometrics workflow from feature detection to feature selection. This data treatment approach was successfully applied to the data and it was shown that the possibility to link samples with a common source was not compromised despite evaporation or combustion for degrees of alteration from 0% to 99%.

Molecular Markers of Dietary Essential Amino Acid-deficiency (P08-059-19)

Objectives

The quality of dietary protein sources became a particularly sensitive issue in the current debates on a rebalancing between animal and vegetable food sources.

The ability of a protein to meet the nutritional requirements of essential amino acid (EAA) is the basis for assessing the quality of protein.

The objective of this study was to characterize the impact of lysine- and threonine-deficient gluten-based diets on the metabolism of growing rats and to identify molecular markers of these diets.

Methods

Growing rats were fed for 3 weeks with a threonine-supplemented and 70% lysine-deficient gluten diet; a lysine-supplemented and 47% threonine-deficient gluten diet; a gluten diet supplemented in lysine and threonine to meet all the AA requirements, and a control diet with milk protein to meet all the AA requirements.

Body weight and food intake were measured daily. At the end of the experiment, tissues and biological fluids were removed. The body composition was analyzed, gene expression measurements involved in protein and lipid metabolism were performed and the urinary metabolome was analyzed by LC-MS. Statistical analysis was done by variance analysis and metabolome analysis by discriminant analysis of independent components.

Results

These EAA deficiency does not modify the food intake. Lysine deficiency induces a decrease in body weight gain, and lean body mass, associated with an increased in proteolysis and a decreased in proteosynthesis, a decreased in bone mineral density, and no effect on lipid metabolism.

Threonine deficiency induces a decrease in body weight gain, and liver and skin weight, without changes in protein metabolism, bone mineral density, and lipid metabolism. After approval of the deficiency model, the metabolomic analysis performed on urine samples revealed the presence of specific discriminating molecules of the diets and types of proteins.

Conclusions

EAA deficiency has an impact on the growth, and bone and protein metabolism of growing rats. These deficiency states have resulted in different metabolome profiles that could lead to the identification of specific molecular markers of protein sources and related to EAA deficiencies.

Funding Sources

This study was funded by the UMR Nutrition Physiology and Ingestive Behavior.

Supporting Tables, Images and/or Graphs

Using pH variations to improve the discrimination of wines by 3D front face fluorescence spectroscopy associated to Independent Components Analysis

Wine composition in polyphenols is related to the variety of grape that it contains. These polyphenols play an essential role in its quality as well as a possible protective effect on human health. Their conjugated aromatic structure renders them fluorescent, which means that 3D front-face fluorescence spectroscopy could be a useful tool to differentiate among the grape varieties that characterize each wine. However, fluorescence spectra acquired simply at the natural pH of wine are not always sufficient to discriminate the wines. The structural changes in the polyphenols resulting from modifications in the pH induce significant changes in their fluorescence spectra, making it possible to more clearly separate different wines. 9 wines belonging to three different grape varieties (Shiraz, Cabernet Sauvignon and Pinot Noir) and from 9 different producers, were analyzed over a range of pHs. Independent Components Analysis (ICA) was used to extract characteristic signals from the matrix of unfolded 3D front-face fluorescence spectra and showed that the introduction of pH as an additional parameter in the study of wine fluorescence improved the discrimination of wines.

Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.

Independent component analysis as a pretreatment method for parallel factor analysis to eliminate artefacts from multiway data

Parallel factor analysis (PARAFAC) has successfully been used in many applications for the analysis of excitation-emission fluorescence data. However, some measurement "artefacts", such as Rayleigh or Raman scattering, can pose a problem for the extraction of the PARAFAC components and their interpretation. Replacing the spectral zones corresponding to these signals by missing values in the data is not necessarily a method of choice in the cases where informative signals lie in the same wavelength regions. In this article, independent component analysis (ICA) is used on the unfolded cubic array, and the independent components related to the Rayleigh and Raman scattering are identified and removed prior to the reconstruction of the excitation-emission fluorescence data cube. PARAFAC is then applied on these data reconstructed after selective artefact removal, and satisfactory models can be obtained. This procedure, although particularly useful for 3D fluorescence data, may be applied to other types of data as well.

Fluorescence spectroscopy for monitoring deterioration of extra virgin olive oil during heating

The potential of fluorescence spectroscopy for characterizing the deterioration of extra virgin olive oil (EVOO) during heating was investigated. Two commercial EVOO were analysed by HPLC to determine changes in EVOO vitamin E and polyphenols as a result of heating at 170 degrees C for 3 h. This thermal oxidation of EVOO caused an exponential decrease in hydroxytyrosol and vitamin E (R(2)=0.90 and 0.93, respectively) whereas the tyrosol content was relatively stable. At the same time, amounts of preformed hydroperoxides (ROOH), analysed by an indirect colorimetric method, decreased exponentially during the heating process (R(2)=0.94), as a result of their degradation into secondary peroxidation products. Fluorescence excitation spectra with emission at 330 and 450 nm were recorded to monitor polyphenols and vitamin E evolution and ROOH degradation, respectively. Partial least-squares calibration models were built to predict these indicators of EVOO quality from oil fluorescence spectra. A global approach was then proposed to monitor the heat charge from the overall fluorescence fingerprint. Different data pretreatment methods were tested. This study indicates that fluorescence spectroscopy is a promising, rapid, and cost-effective approach for evaluating the quality of heat-treated EVOO, and is an alternative to time-consuming conventional analyses. In future work, calibration models will be developed using a wide range of EVOO samples.