Odor Fingerprint Research Articles

Effects of electron-beam irradiation on volatile flavor compounds of salmon fillets by the molecular sensory science technique.

Vacuum-packed salmon was treated by electron beam irradiation preservation technology, to study the effects of electron-beam irradiation on odor active compounds of salmon by two types of methods for extraction: headspace-solid phase micro extraction (HS-SPME) and solvent assisted flavor evaporation (SAFE). Volatile flavor compounds examined by gas chromatography-mass spectrometry (GC-MS) and gas chromatography-olfactometry (GC-O), combined with aroma extract dilution method (AEDA) and odor activity value (OAV) for identification of important odorants. In addition, the correlation between sensory attributes and volatile compounds of salmon irradiated at different doses was analyzed by partial least squares regression (PLSR). The results showed that after SPME and SAFE extraction, a total of 49 and 70 volatile flavor compounds were detected in salmon before and after electron beam irradiation. AEDA and OAV were further identified, among which 10 odorants were considered as important volatile flavor compounds and played an important role in the formation of aroma contours such as meaty, fatty, and grassy in salmon. In addition, methanethiol, 3-methyl butyraldehyde, 3-methyl propyl aldehyde, dimethyl disulfide, dimethyl trisulfide, and 2-pentyl furan were identified as the important volatile flavor compounds in salmon irradiated with 4 kGy, and were also the unique compounds that constituted irradiation off-odor. In general, salmon irradiated with 1 kGy showed the best aroma profile. PRACTICAL APPLICATION: SPME and SAFE were used as two types of extraction methods for volatile compounds of salmon, which complemented each other. Additionally, combined with AEDA and OAV, characteristic flavor compounds were identified. Furthermore, the odor fingerprint of salmon with E-beam irradiation was established for the first time.

The type of microorganism and substrate determines the odor fingerprint of dried bacteria targeting microbial protein production.

The rapidly increasing demand for protein has led to the pursuit of new protein sources, among which microbial protein (MP) is one of the most promising. Although the nutritional properties of MP are important and often well-studied, the sensory properties of the microbial cells will in part determine the commercial success of the product and are much less investigated. Here we assessed the odor fingerprint of dried bacteria originating from pure cultures and enriched mixed microbial communities using an electronic nose (e-nose). The e-nose discriminated between the different MP sources, while the choice of culture and substrate substantially affected their volatile organic compound (VOC) profile. The most dominant odor descriptors (>20% of VOC peak area) were sweet, fruity and fishy, while the mixed cultures presented higher peak areas indicating potentially more intense aromas than the pure cultures. The e-nose can detect the suitability of new MP sources and determine their best end-use.

Identification of curcumin content in raw and vinegar-processed rhizomes of Curcuma kwangsiensis based on electronic nose combined with back propagation neural network

This study aimed to establish a rapid and accurate method for identification of raw and vinegar-processed rhizomes of Curcuma kwangsiensis, in order to predict the content of curcumin compounds for scientific evaluation. A complete set of bionics recognition mode was adopted. The digital odor signal of raw and vinegar-processed rhizomes of Curcuma kwangsiensis were obtained by e-nose, and analyzed by back propagation(BP) neural network algorithm, with the accuracy, the sensitivity and specificity in discriminant model, correlation coefficient as well as the mean square error in regression model as the evaluation indexes. The experimental results showed that the three indexes of the e-nose signal discrimination model established by the neural network algorithm were 100% in training set, correction set and prediction set, which were obviously better than the traditional decision tree, naive bayes, support vector machine, K nearest neighbor and boost classification, and could accurately differentiate the raw and vinegar products. Correlation coefficient and mean square error of the regression model in prediction set were 0.974 8 and 0.117 5 respectively, and could well predict curcumin compounds content in Curcuma kwangsiensis, and demonstrate the superiority of the simulation biometrics model in the analysis of traditional Chinese medicine. By BP neural network algorithm, e-nose odor fingerprint could quickly, conveniently and accurately realize the discrimination and regression, which suggested that more bionics information acquisition and identification patterns could be combined in the field of traditional Chinese medicine, so as to provide ideas and methods for the rapid evaluation and stan-dardization of the quality of traditional Chinese medicine.

Storage effects on the quality quartet of orange juice submitted to moderate thermosonication: Predictive modeling and odor fingerprinting approach.

The effects of moderate thermosonication (MTS) on the quality quartet: physico-chemical, microbial, nutritional and sensory qualities of orange juice (OJ) inoculated with Alicyclobacillus acidoterrestris (AAT) were studied during 24days of storage at ambient and refrigerated temperatures. The bioactive compounds and antioxidant activity of OJ decreased with storage, while the pectin methyl esterase (PME) increased. Nonetheless, noticeable changes were observed from the 12th day of storage. There was no obvious (p>0.05) variation in pH and total soluble solids. To determine the nutritional and microbial quality characteristics of OJ during storage, non-linear kinetic curves were successfully fitted with least square fitting polynomial and four-parameter log-logistic distribution models. The E-nose sensors succeeded in discriminating between the aroma of non-treated and treated OJ based on linear discriminant analysis (LDA). Furthermore, terpenes, alcohol and partially aromatic compounds were the main spoilage indicators of OJ during storage based on E-nose analysis and confirmed by HS-SPME-GC/MS analysis. Thus, MTS significantly extended the shelf life of the quality quartet of natural OJ at 4°C. E-nose-GC/MS fusion offered odor fingerprints to AAT microorganisms that can be used as spoilage index without using traditional food analysis techniques. The proposed approach can be used as an alternative tool for rapid detection of spoilage microorganisms in OJ.

Analyzing changes of volatile components in dried pork slice by gas chromatography-ion mobility spectroscopy

ABSTRACT The volatile organic compounds (VOCs) in different processing stages of dried pork slices (DPS) were analyzed by gas chromatography-ion mobility spectrometry (GC-IMS), which was used to construct the GC-IMS odor fingerprint spectrometry. The VOCs of raw meat, mixed meat, cured meat, semi-finished meat and finished meat were detected and analyzed by GC-IMS. The result shows that the main VOC species in DPS include alcohols and aldehydes, acids, ketones, heterocyclic compounds, aromatic hydrocarbons and esters. Except that the VOCs of mixed meat and cured meat were very similar, the odor component characteristics of DPS in other processing stages were significantly different. GC-IMS technology can effectively distinguish the volatile component differences of preserved meat samples at different processing stages. It is of profound significance to regulate and ensure the consistency of the VOCs in the processing of DPS.

Identification of Curcuma herbs using XGBoost algorithm in electronic nose odor fingerprint

This article aims to identify four commonly applied herbs from Curcuma genus of Zingiberaceae family,namely Curcumae Radix( Yujin),Curcumae Rhizoma( Ezhu),Curcumae Longae Rhizoma( Jianghuang) and Wenyujin Rhizoma Concisum( Pianjianghuang). The odor fingerprints of those four herbal medicines were collected by electronic nose,respectively. Meanwhile,XGBoost algorithm was introduced to data analysis and discriminant model establishment,with four indexes for performance evaluation,including accuracy,precision,recall,and F-measure. The discriminant model was established by XGBoost with positive rate of returning to 166 samples in the training set and 69 samples in the test set were 99. 39% and 95. 65%,respectively. The top four of the contribution to the discriminant model were LY2/g CT,P40/1,LY2/Gh and LY2/LG,the least contributing sensor was T70/2. Compared with support vector machine,random forest and artificial neural network,XGBoost algorithms shows better identification capacity with higher recognition efficiency. The accuracy,precision,recall and F-measure of the XGBoost discriminant model forecast set were 95. 65%,95. 25%,93. 07%,93. 75%,respectively. The superiority of XGBoost in the identification of Curcuma herbs was verified. Obviously,this new method could not only be suitable for digitization and objectification of traditional Chinese medicine( TCM) odor indicators,but also achieve the identification of different TCM based on their odor fingerprint in electronic nose system. The introduction of XGBoost algorithm and more excellent algorithms provide more ideas for the application of electronic nose in data mining for TCM studies.

Chemical characterisation of potential pheromones from the shoulder gland of the Northern yellow-shouldered-bat, Sturnira parvidens (Phyllostomidae: Stenodermatinae).

Bats of the genus Sturnira (Family Phyllostomidae) are characterised by shoulder glands that are more developed in reproductively mature adult males. The glands produce a waxy secretion that accumulates on the fur around the gland, dyeing the fur a dark colour and giving off a pungent odour. These shoulder glands are thought to play a role in their reproductive behaviour. Using gas chromatography–mass spectrometry, we analysed solvent extracts of fur surrounding the shoulder gland in the northern-shouldered bat, Sturnira parvidens to (i) characterise the chemical composition of shoulder gland secretions for the first time, and (ii) look for differences in chemical composition among and between adult males, sub-adult/juvenile males and adult females. Fur solvent extracts were analysed as liquids and also further extracted using headspace solid-phase microextraction to identify volatile components in the odour itself. Odour fingerprint analysis using non-metric multidimensional scaling plots and multivariate analysis revealed clear and significant differences (P < 0.001) between adult males vs both juvenile males and adult females. The chemical components of the shoulder gland secretion included terpenes and phenolics, together with alcohols and esters, most likely derived from the frugivorous diet of the bat. Many of the compounds identified were found exclusively or in elevated quantities among adult (reproductive) males compared with adult females and non-reproductive (juvenile) males. This strongly suggests a specific role in male–female attraction although a function in male–male competition and/or species recognition is also possible.

A multipronged flavor comparison of Ecuadorian CCN51 and Nacional cocoa cultivars

Two cocoa types are predominantly being cultivated in Ecuador, the highly appreciated fine Nacional and the high-yielding and disease-resistant CCN51, classified as bulk. With the introduction of foreign germplasm in Ecuador and the international demand for high-quality Nacional cocoa, the present study aims to characterize and compare the flavor profile of Nacional hybrids (EET103, EET559, EET576 and EET577) and CCN51, and to assess the effect of the genotype. The fermented dried beans were processed into liquor and their sensory properties, volatile composition and odor fingerprint were analyzed by trained panelists, headspace–solid phase microextraction gas chromatography–mass spectrometry (HS–SPME–GC–MS), and GC electronic nose (e-nose), respectively, combined with multivariate statistics. Seventy volatiles were identified and semi-quantified, among them, 16 and 14 volatiles conferring fruity and floral aroma notes, respectively. CCN51 was mainly characterized by undesirable odor-active volatiles, whereas the EET cultivars contained the highest concentration of most fruity and floral volatiles, with differences in between EET cultivars. Sensory data highlighted organoleptic differences between the fine and bulk liquors, i.e. the fruity and acid EET flavor strongly differed from the bitter, astringent and off-flavor attributes of CCN51. Principal component analysis (PCA) discriminated firstly between fine and bulk, and secondly between EET identity. Partial least squares analysis identified possible correlations between sensory attributes and volatile compounds. Besides, e-nose proved its usefulness for rapid assessment of the liquors’ sensory profile. The results provide a foundation for understanding the genotype’s contribution to and the compositional basis of Ecuadorian fine and bulk cocoa flavor.

Origin identification of Chinese Maca using electronic nose coupled with GC-MS

Maca (Lepidium meyenii Walp.), originated in the high Andes of Peru, is rich in nutrients and phytochemicals. As a new resource food in China, Maca suffers marketing disorders due to the limitation of basic research. Due to the close relationship of Maca quality and origin of place, it’s of scientific, economic and social importance to set up a rapid, reliable and efficient method to identify Maca origin. In the present study, 303 Maca samples were collected from 101 villages of the main producing area in China. Using electronic nose and BP neutral network algorithm, a Maca odor database was set up to trace the origin. GC-MS was then employed to analyze the characteristic components qualitatively and semi-quantitatively. As a result, very significant differences (p < 0.01) were detected in the volatile components of Maca from different areas. This study not only constructs a network model to forecast the Maca origin, but also reveals the relationship between Maca odor fingerprints and origins.

Gas Chromatography-Ion Mobility Spectrometry Detection of Odor Fingerprint as Markers of Rapeseed Oil Refined Grade.

In this work, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyze the volatile organic compound changes of rapeseed oil with different refined grades, the odor fingerprints of refined rapeseed oil were constructed, and a nonlinear model was built to realize rapid and accurate discrimination of rapeseed oil with different refined grades. 124 rapeseed oil samples with different refined grades were collected and analyzed by GC-IMS and chemometric tools, and 34 characteristic peaks were selected by the colorized difference method as variables to characterize the internal quality in rapeseed oil of different refined grades. The principal component analysis algorithm was used to further reduce dimensionality and extract the most relevant information. The k-nearest neighbor algorithm was applied to build a discriminant model. All the samples were recognized accurately without errors, and the results show the potential of this method to discriminate different refined grades of vegetable oil.

Odor Fingerprint Analysis Using Feature Mining Method Based on Olfactory Sensory Evaluation.

In this paper, we aim to use odor fingerprint analysis to identify and detect various odors. We obtained the olfactory sensory evaluation of eight different brands of Chinese liquor by a lab-developed intelligent nose. From the respective combination of the time domain and frequency domain, we extract features to reflect the samples comprehensively. However, the extracted feature combined time domain and frequency domain will bring redundant information that affects performance. Therefore, we proposed data by Principal Component Analysis (PCA) and Variable Importance Projection (VIP) to delete redundant information to construct a more precise odor fingerprint. Then, Random Forest (RF) and Probabilistic Neural Network (PNN) were built based on the above. Results showed that the VIP-based models achieved better classification performance than PCA-based models. In addition, the peak performance (92.5%) of the VIP-RF model had a higher classification rate than the VIP-PNN model (90%). In conclusion, odor fingerprint analysis using a feature mining method based on the olfactory sensory evaluation can be applied to monitor product quality in the actual process of industrialization.

Discrimination of Cocoa Liquors Based on Their Odor Fingerprint: a Fast GC Electronic Nose Suitability Study

With the rising interest by consumers for high-quality cocoa products from a clear geographical origin, a rapid analytical method for quality control, authenticity and traceability assessment is of paramount importance. However, the complex mixture of volatiles present in cocoa liquor, the main ingredient for the chocolate production, complicates reaching this purpose. Hence, an analytical fingerprint approach using advanced electronic nose (E-nose) technology may offer a suitable technique. This study aimed to verify the suitability of an E-nose based on ultra-fast gas chromatography (GC) for the rapid discrimination between cocoa liquors from different origins. Fourteen cocoa liquors, produced of cocoa beans from ten different geographical origins, were analyzed. The obtained odor fingerprints were investigated using principal component analysis (PCA) which successfully discriminated most cocoa liquors, within one continent, according to their geographical origin. Besides, discriminant factor analysis (DFA) showed the possibility to differentiate between bulk and fine cocoa. Further tentative identification of predominant volatile compounds allowed the detection of compounds within a wide range of chemical classes occurring in cocoa products, such as acids, alcohols, aldehydes, ketones, esters, pyrazines, pyrones, and pyrroles. Most odorant compounds were previously described in literature as key volatiles in cocoa flavor, notable examples are acetic acid, 2-heptanol, 2/3-methylbutanal, acetophenone, isoamyl acetate, tetramethylpyrazine, maltol, and 2-acetyl-1-pyrroline. This study proves for the first time the usefulness of the GC E-nose for effective and rapid aroma profiling and discrimination between single origin cocoa liquors, which can be easily applied in the cocoa industry.

Influence of chemical additives and wax modifiers on odor emissions of road asphalt

The use of a broad range of asphalt additives is a well-established practice in road pavement engineering for the production of high-performance hot-mix and warm-mix asphalt mixtures. The study aimed to verify and to assess, though an analytical-sensory approach based on artificial olfactory system (AOS), the effects of five different asphalt additives (chemical additives, odor suppressant agent and wax modifiers) on the odorous patterns of asphalt emissions at typical mixing and laying temperatures. The AOS has made possible to identify a specific odor fingerprint of each additive. However, once added to asphalt, these agents did not establish with binder effects of synergy, additivity or antagonism, but appear to be as neutral elements by an odorous point of view. The odorous patterns of emissions generated by heating neat asphalt at various temperatures in laboratory scale tend to coincide with those of asphalt/additive mixtures, underlining how the bituminous binder odor resulted to be hiding or masking compared to that of only-additives.

Innovative Diagnostic Methods for Early Prostate Cancer Detection through Urine Analysis: A Review.

Prostate cancer is the second most common cause of cancer death among men. It is an asymptomatic and slow growing tumour, which starts occurring in young men, but can be detected only around the age of 40–50. Although its long latency period and potential curability make prostate cancer a perfect candidate for screening programs, the current procedure lacks in specificity. Researchers are rising to the challenge of developing innovative tools able of detecting the disease during its early stage that is the most curable. In recent years, the interest in characterisation of biological fluids aimed at the identification of tumour-specific compounds has increased significantly, since cell neoplastic transformation causes metabolic alterations leading to volatile organic compounds release. In the scientific literature, different approaches have been proposed. Many studies focus on the identification of a cancer-characteristic “odour fingerprint” emanated from biological samples through the application of sensorial or senso-instrumental analyses, others suggest a chemical characterisation of biological fluids with the aim of identifying prostate cancer (PCa)-specific biomarkers. This paper focuses on the review of literary studies in the field of prostate cancer diagnosis, in order to provide an overview of innovative methods based on the analysis of urine, thereby comparing them with the traditional diagnostic procedures.

Anaerobic digestion coupled with digestate injection reduced odour emissions from soil during manure distribution

This work aimed to measure the odour impact of untreated cow and pig slurries and treated (digestate and liquid fraction of digestate) manures when they were used on soil at a field scale, while also testing different spreading methods, i.e. surface vs. injection. Five experiments were performed in 2012–2016 on different farms. Odours were quantitatively (specific odour emission rate – SOER) (OUEm−2h−1) measured by using dynamic olfactometry and qualitatively, i.e. to obtain an “odour fingerprint”, by using an electronic nose (EN).Anaerobic digestion was effective in allowing the reduction of potential odour emission from digestates, so that when they were dosed on soil, odours emitted were much lower than those from soils on which untreated slurries were used. Slurries/digestate injection reduced much more odour emitted by soils so that SOER tended to become more similar to that of the control (untreated soil) although the odours were slightly greater.Odour fingerprint data indicated that there was a direct correlation between SOER and odour fingerprints. This was due to the ability of EN to detect ammonia, S-compounds and methane that were (the first two mainly), also, responsible for odours. Very good regression was found for Log SOER and EN by using a Partial Least Square (PLS) approach (R2=0.73; R2cv=0.66; P<0.01) for matrices used to fertilize soils in lab tests. Unfortunately, regression was not so good when odour data from field experiments on soil were used, so that EN cannot be proposed to replace olfactometry. EN fingerprints for control (Blank) and injected organic matrices were virtually identical, due to the creation of cavities in the soil during the injection that decreased the treated surface. Anaerobic digestion and subsequent digestate injection allowed us to reduce odour impact, avoiding annoyance to local inhabitants.

Analytical assessment of asphalt odor patterns in hot mix asphalt production

During the various stages of asphalt paving mixtures production and placement, as a result of binder heating, a complex mixtures of hydrocarbons and volatile organic compounds (VOCs) is released into the atmosphere. As far as hot mix asphalt plants is concerned, several standards and directives were drawn up for limiting the emissions of certain specific substances, without setting any specific limit on the odorous perspective. But, odor is increasingly considered an atmospheric pollutant that can have a significant negative impact on both quality of life and economic activity. The odorous flows of HMA emitted in plants or during the paving operations and hot-in-place recycling processes in the worksites can severely limit the usability of the territory. Advances in sensor technology have made possible the development of artificial olfactory systems (AOS), which are devices designed to mimic the human olfactory system capable of characterizing osmogene mixtures. However, their potentialities have not been explored until now at any stages of asphalt and asphalt mixtures production chain. Thus, the main purpose of this study was an analytical-sensory characterization, mainly based on AOS approach, of asphalt emissions generated during the various stages of road pavement construction. The analytical and sensory analyses have firstly demonstrated the effective application of these instruments in the pavement engineering sector: an odor fingerprint of asphalt emissions, specific for each type of binder and temperature class, was determined. Thanks to the photoionization, a technique which allow the detection of organic compounds in gaseous mixtures, a pseudo-hyperbolic relationship between the release of airborne substances in asphalt emissions and the heating temperature was identified; whereas the AOS demonstrated that this increase of VOCs corresponded contextually to a change in their odorous patterns. Moreover, the existence of variations in the odor fingerprints of different asphalt binders heated at the same temperature was assessed. Through a specific statistical approach for the treatment and post-processing of data and the following elaboration of a geometric based procedure for the determination of the numerical inter-class separation, a quantitative value to the purely qualitative response of the AOS was assigned.

The Equine Volatilome: Volatile Organic Compounds as Discriminatory Markers

Animals rely on subtle signals perceived between individuals that convey information such as sex, reproductive status, individual identity, ownership, competitive ability, and health status. These cues have important influences on behaviors that are vital for reproductive success, such as parent–offspring attachment, recognition of relatedness, mate choice, and territorial marking. This study investigates individual odor profiles as discriminatory markers possibly affecting equine behavior. This study investigated the volatile compounds in horses using solid phase microextraction gas chromatography-mass spectrometry and hair samples. Two horse breeds, Appaloosa (n = 6) and Quarter Horses (n = 17), were used as a model to assess the volatilome that may be used to identify individuals and kin recognition. A total of 187 volatiles were identified and demonstrated that the volatilome carries information on genetic relatedness. Interestingly, apart from individualization and kinship, the volatiles detected were also able to discriminate between breeds. The study is limited exclusively to two horse breeds and should be expanded to include other domestic and wild horses. In addition, compounds were identified based on NIST 98 mass spectral library. The results of this study support the individual odor hypothesis suggesting that each individual possesses a unique scent that acts as a characteristic or odor fingerprint. Such qualitative and quantitative patterns have not been explored in domestic or wild animals and there is a need to understand more about the influence of odor on behavior and interactions.

Odor fingerprinting of Listeria monocytogenes recognized by SPME-GC-MS and E-nose.

Microorganisms can produce species-specific microbial volatile organic compounds (MVOCs), or odor compounds, which can be characterized by odor fingerprinting. The objective of this study was to characterize the odor fingerprint of Listeria monocytogenes. Solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) and electronic nose (E-nose) were used to recognize the MVOCs of L. monocytogenes in pure culture medium. The main MVOCs of L. monocytogenes were identified by SPME-GC-MS analysis as alcohols, aldehydes, ketones, alkanes, and heterocyclics, among which the relative peak area of one compound, 3-hydroxy-2-butanone, increased along with the growth of L. monocytogenes. The odor fingerprint of L. monocytogenes at different growth stages could be clearly discriminated by E-nose. In addition, E-nose signals had a very good linear relationship with the concentration of this bacterium (R(2) = 0.9937). Our study may help to establish the analysis of the odor fingerprint of microorganisms as a potential routine method in microbiology.

Differences in olfactory species recognition in the females of two Australian songbird species

Although birds have recently been shown to possess olfactory abilities and to use chemical cues in communication, limited effort has been made to demonstrate the use of odorants in social contexts. Even less is known regarding the use of odorants in species recognition. The ability to recognize conspecifics should be more pronounced in social species. This study investigated the importance of olfactory cues in species recognition in females of two estrildid finch species with different levels of sociality. Combining odor preference tests with chemical analyses, we surveyed whether female zebra finches and diamond firetails are able to distinguish between the species based on volatile traits and whether individuals exhibit species-specific differences in body odorants. Zebra finches are more social than diamond firetails; nevertheless, both species have an overlapping distribution area. Applying an experimental Y-maze paradigm, we showed that zebra finches can use differences in their species odor fingerprints and displayed a significant preference for the odor of conspecifics over that of heterospecifics, whereas diamond firetails did not reveal a preference. Using gas chromatography and mass spectrometry, we demonstrated that body odorants of the two species were significantly different in relative composition. This finding demonstrates the potential importance of olfactory cues in species recognition, at least in social bird species. Even these two closely related species displayed remarkable differences in their responsiveness to similar chemical cues, which might be caused by species-specific differences in ecology, physiology, or evolution.

The Scent of Colorectal Cancer: Detection by Volatile Organic Compound Analysis

The overall metabolic state of an individual is reflected by emitted volatile organic compounds (VOCs), which are gaseous carbon-based chemicals. In this review, we will describe the potential of VOCs as fully noninvasive markers for the detection of neoplastic lesions of the colon. VOCs are detected by our sensory olfactory nerves and form the molecular basis for our sense of smell. As such, we emit our own individual odor fingerprint or so-called smellprint. This may change over time in response to any alteration in metabolism such as modifications caused by gastrointestinal infection, inflammation, external factors such as medication and diet, or development of neoplastic disease such as colorectal cancer. This means that analysis of VOCs can provide a fully noninvasive metabolomics biomarker profile that could be used as a diagnostic tool. Thus far, canine scent detection, gas chromatography-mass spectrometry, and electronic nose technologies allow for discrimination between patients with and without colorectal cancer and also its precursor (advanced adenoma) with promising accuracy. The challenge for future research is to identify specific biomarkers driving these signals. This enables the development of primed sensors tailored toward accurate identification of volatiles specific to colorectal cancer and adenomas. Such a technique may allow noninvasive monitoring of response to therapy and could revolutionize screening practices for colorectal cancer and potentially many other gastrointestinal diseases.