Colorimetric sensor array for volatile organic compound analysis

Abstract

The invention discloses a colorimetric sensor array for detecting volatile organic compounds (VOCs), and a system comprising the colorimetric sensor array. Methods of using the colorimetric sensor array and / or the system are also disclosed. According to the method, the odor in the sample can be visualized into colorimetric fingerprints, so that quick, accurate, simple, convenient and low-cost qualitative identification and semi-quantitative analysis on the VOCs in the sample can be realized.

Description

Cross-references

[0001] This application claims priority to Singapore Patent Application No. 10202302228Q filed on August 4, 2023, which is expressly incorporated herein by reference in its entirety. Field of the Invention

[0002] The present invention generally relates to the field of analytical chemistry. In particular, the present invention relates to a colorimetric array of sensors with chemical indicators and / or dyes. Background Art

[0003] Aroma is an important quality indicator for a wide range of products, including food, beverages, and other everyday consumer goods. The aroma of these products is determined by the volatile organic compounds (VOCs) present in them, which are organic molecules with high vapor pressure at room temperature. In many industries, including the food and beverage industry, aroma evaluation is often performed through sensory evaluation, a discipline that uses scientific methods to measure human perception of various products. Sensory evaluation is superior to other analytical techniques because it better reflects consumer response, making it essential for quality control and product development.

[0004] Despite its importance, sensory evaluation has significant disadvantages and limitations. The process requires a team of well-trained and experienced personnel, and the training process is time-consuming and less cost-effective. Training a sensory evaluator can take anywhere from several months to half a year. Furthermore, even for well-trained panelists, the results are susceptible to interference from various factors, such as exposure duration, fatigue, and mental health. The evaluation of unpleasant odors further complicates the process, making it challenging to find panelists willing to conduct the evaluation.

[0005] Laboratory-based methods have been adopted to assist humans in aroma analysis, with gas chromatography (GC) being the most commonly used tool. However, there are inconsistencies between GC-based techniques and human olfaction in terms of signal interpretation. Unlike human olfaction, where the electrochemical signals generated by olfactory receptors are integrated into an odor "fingerprint," GC-based techniques are analytical in nature and, therefore, the information about the aroma is broken down into its molecular components.

[0006] These limitations highlight the need for a more efficient, cost-effective, and reliable method to analyze VOCs in a wide range of samples. Summary of the invention

[0007] In one aspect, a colorimetric sensor array for detecting volatile organic compounds (VOCs) is provided, comprising: one or more pH-sensitive dyes selected from the group consisting of litmus, bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, rhodamine, phenol red and nitrazine yellow; one or more carbonyl-sensitive indicators selected from the group consisting of parafuchsin or parafuchsin base, salts of hydroxylamine and Schiff's reagent; and one or more solvatochromic dyes selected from the group consisting of Reichardt's dyes, Brooker's merocyanine, chrome azuro S, Nile Red, Nile Blue, acridine orange, merocyanine 540 and disperse orange 25; wherein each of the indicators or dyes is deposited on a substrate, and wherein the indicators and / or dyes are arranged in a predetermined linear or two-dimensional pattern.

[0008] On the other hand, a system for detecting volatile organic compounds (VOCs) in a sample is provided, comprising: the colorimetric sensor array as disclosed herein, a sensor chamber for accommodating the colorimetric sensor array, and a sample chamber for accommodating the sample; wherein the sensor chamber is fluidically connected to the sample chamber.

[0009] On the other hand, a method for detecting and analyzing volatile organic compounds (VOCs) in a sample is provided, comprising the following steps: (i) providing the colorimetric sensor array or the system as disclosed herein, (ii) acquiring a first image of the colorimetric sensor array, (iii) providing the sample and exposing the colorimetric sensor array to the sample for a period of time, (iv) acquiring a second image of the colorimetric sensor array, and (v) analyzing the difference between the first image and the second image.

[0010] In another aspect, a method for detecting adulteration or counterfeiting in a sample, assessing the freshness of a sample, assessing the general quality of a sample, or determining the geographic origin of a sample is provided, which comprises the method for detecting and analyzing VOCs as disclosed herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The invention will be better understood with reference to the detailed description when considered in conjunction with the non-limiting examples and accompanying drawings, in which:

[0012] Figure 1 A schematic diagram showing the structure, size and arrangement of colorimetric sensors of an exemplary colorimetric sensor array described in the present disclosure (the colorimetric sensor array includes 14 colorimetric sensors);

[0013] Figure 2A schematic diagram showing an exemplary system disclosed in the present application (the system includes a colorimetric sensor array as described in the present disclosure, and further includes 1-a sample chamber, 2-a sensor chamber, 3-a micro vacuum pump, and 4-a power supply);

[0014] Figure 3 shows the color difference graphs generated by an exemplary colorimetric sensor array after exposure to various chemical standards (1-pentanal; 2-heptanal; 3-benzaldehyde; 4-phenylacetaldehyde; 5-acetic acid; 6-hexanoic acid);

[0015] Figure 4a The concentrations of the main VOCs identified in the two sesame oil standards are shown;

[0016] Figure 4b The average color difference graph of HP-S standards is shown;

[0017] Figure 4c The average color difference graph of the XM-S standard is shown;

[0018] Figure 4d The results of principal component analysis (PCA) using the Euclidean distance of RGB value changes are shown;

[0019] Figure 5a shows typical scan images of the colorimetric sensor after exposure to HP and XM samples;

[0020] Figure 5b The average color difference graph of 28 commercial HP samples and 25 commercial XM samples is shown;

[0021] Figure 5c The color difference graph of HP and XM samples from three different brands A, C, and O is shown;

[0022] Figure 5d shows a bar graph of the Euclidean distances calculated for the 14 sensors after exposure to commercial HP and XM samples;

[0023] Figure 5e The results of PCA analysis of all 53 commercial samples are shown;

[0024] Figure 6 is a bar graph showing the lignan content of representative commercial HP samples;

[0025] Figure 7a A color difference graph of blended sesame oils containing 0% to 100% hot pressed sesame oil is shown;

[0026] Figure 7b The PCA results of the adulteration experiments conducted are shown;

[0027] Figure 8Partial least squares (PLS) regression analysis results are shown, where the fitted response (predicted refined oil concentration) is plotted against the observed response (reference refined oil concentration);

[0028] Figure 9a A schematic diagram showing the colorimetric sensor array (the colorimetric sensor array includes 23 colorimetric sensors);

[0029] Figure 9b The scanned image and color difference map of the consumer product (apple vinegar, sensing duration 5 minutes) are shown;

[0030] Fig.9c The scanned image and color difference diagram of the consumer product (balsamic vinegar, sensing duration 5 minutes) are shown;

[0031] Figure 9d The scanned image and color difference diagram of the consumer product (soy sauce, sensing duration 30 min) are shown;

[0032] Fig.9e The scanned image and color difference diagram of the consumer product (black coffee, sensing duration 30 minutes) are shown;

[0033] Figure 9f The scanned image and color difference map of a consumer product (nail polish remover, sensing duration 30 minutes) are shown;

[0034] Fig.10a Two sensors (with methyl orange and trace Na 2 CO 3 A mixture of hydroxylamine sulfate (A1) and bromophenol blue and trace amounts of Na 2 CO 3 Schematic diagram of mixed hydroxylamine sulfate (A2);

[0035] Fig.10b Scanning images of two sensors (A1 and A2) are shown;

[0036] Fig.10c The scanned images and color difference diagrams of two sensors (A1 and A2) after exposure to soy sauce samples for 30 minutes are shown;

[0037] Fig.11a A schematic diagram showing the colorimetric sensor array (the colorimetric sensor array includes 26 colorimetric sensors);

[0038] Fig.11b Scanned images and color difference diagrams of chemical standards (furfural) are shown;

[0039] Fig.11c Scanned images and color difference diagrams of a chemical standard (phenylacetaldehyde) are shown;

[0040] Fig.11d The scanned image and color difference diagram of the chemical standard (acetic acid) are shown;

[0041] Fig.11e The scanned image and color difference diagram of the chemical standard (hexanoic acid) are shown;

[0042] Fig.11f Scanned images and color difference diagrams of a chemical standard (acetone) are shown;

[0043] Figure 11g Scanned images and color difference diagrams of chemical standards (ethanol) are shown;

[0044] Fig.12a shows a scanned image and a color difference diagram of the tested roasted coffee bean sample A1;

[0045] Figure 12b shows a scanned image and a color difference diagram of the tested roasted coffee bean sample A2;

[0046] Fig.12c shows a scanned image and a color difference diagram of the tested roasted coffee bean sample A3;

[0047] Fig.12d Shows a scanned image and color difference diagram of the roasted coffee bean sample A4 tested;

[0048] Fig.12e shows a scanned image and a color difference diagram of the tested roasted coffee bean sample A5;

[0049] Fig.12f shows a scanned image and a color difference diagram of the tested roasted coffee bean sample A6;

[0050] Figure 12g shows a scanned image and a color difference diagram of the tested roasted coffee bean sample R1;

[0051] Figure 12h shows a scanned image and a color difference diagram of the tested roasted coffee bean sample R2;

[0052] Fig.12i shows a scanned image and a color difference diagram of the tested roasted coffee bean sample R3;

[0053] Fig.12j shows a scanned image and a color difference diagram of the tested roasted coffee bean sample R4;

[0054] Figure 12k shows a scanned image and a color difference diagram of the tested roasted coffee bean sample R5;

[0055] Figure 12lshows a scanned image and a color difference diagram of a tested roasted coffee bean sample U;

[0056] Fig.13a The scanned image and color difference diagram of the tested in-package strawberry sample RT-1 are shown;

[0057] Fig.13b The scanned image and color difference diagram of the tested in-package strawberry sample RT-2 are shown;

[0058] Fig.13c The scanned image and color difference diagram of the tested in-package strawberry sample RT-3 are shown;

[0059] Fig.13d The scanned image and color difference diagram of the tested in-package strawberry sample F-1 are shown;

[0060] Fig.13e The scanned image and color difference diagram of the tested in-package strawberry sample F-2 are shown;

[0061] Fig.13f Shown are the scanned images and color difference graphs of the tested in-package strawberry sample F-3.

[0062] in: Figure 2 The system shown can be used to detect volatile organic compounds (VOCs) in a sample. Figure 3 The results showed that the colorimetric sensors in the colorimetric sensor array exhibited cross-reactivity because many indicators or dyes used in the colorimetric sensors could exhibit color changes to a variety of VOCs (1-pentanal; 2-heptanal; 3-benzaldehyde; 4-phenylacetaldehyde; 5-acetic acid; 6-hexanoic acid). Figures 4a to 4d (collectively referred to as Figure 4) shows the analysis results of VOCs present in two sesame oil standards, hot pressed sesame oil (HP-S) and small milled sesame oil (XM-S); Figure 4d The results in Figure 4 show that HP-S and XM-S standards can be easily distinguished by their PC1 values. Figure 5a to Figure 5e (collectively referred to as FIG5 ) shows the results of the analysis of VOCs present in 53 commercial sesame oil samples—28 hot pressed (HP) samples and 25 small milled (XM) samples. Figures 9a to 9f (collectively, FIG. 9 ) show the results of analyzing VOCs in various consumer products using another exemplary colorimetric sensor array described in the present disclosure. Figures 10a to 10c (collectively, FIG. 10 ) shows the results of experiments performed showing that the pH-sensitive dye in sensor No. 13 (hydroxylamine sulfate with Congo red) can be replaced with methyl orange or bromophenol blue. Figures 11a to 11g (collectively, FIG. 11 ) show the results of analyzing various chemical standards using another exemplary colorimetric sensor array described in the present disclosure. Figures 12a to 12l (collectively referred to as Figure 12) shows the use of Fig.11a Result of analyzing various roasted coffee bean samples using the exemplary colorimetric sensor array shown in FIG. Figures 13a to 13f (collectively referred to as Figure 13) shows the use of Fig.11a The results of analyzing various in-package strawberry samples using the exemplary colorimetric sensor array shown in FIG. DETAILED DESCRIPTION

[0063] The present invention provides a colorimetric sensor array that addresses the limitations of sensory evaluation and existing laboratory-based methods for analyzing VOCs.

[0064] In one aspect, a colorimetric sensor array for detecting VOCs is provided, wherein the colorimetric sensor array comprises: one or more pH-sensitive dyes, one or more carbonyl-sensitive indicators, and one or more solvatochromic dyes.

[0065] pH sensitive dyes include pH indicators or acid-base indicator dyes that may change color when exposed to an acid or base. Examples of pH sensitive dyes include, but are not limited to, litmus, bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, rhodamine, phenol red, and nitrazine yellow.

[0066] Carbonyl-sensitive indicators are indicators / dyes that are sensitive to carbonyl groups. Carbonyl is a functional group with the molecular formula C=O. Carbonyl is common to several classes of organic compounds, including but not limited to: aldehydes, ketones, and carboxylic acids. Examples of carbonyl-sensitive indicators include but are not limited to: para-fuchsin or para-fuchsin base, salts of hydroxylamine, and Schiff's reagent. In some specific embodiments, the carbonyl-sensitive indicator is particularly sensitive to aldehydes.

[0067] Solvatochromic dyes are dyes that change color in response to a general change in polarity of the environment. Examples of solvatochromic dyes include, but are not limited to, Reichardt's dyes, Brooker's merocyanine, chrome azure S, Nile Red, Nile Blue, Acridine Orange, Merocyanine 540, and Disperse Orange 25.

[0068] The colorimetric sensor array may further include one or more redox indicators, and / or one or more phenolic compound-sensitive indicators.

[0069] A redox indicator is an indicator that changes color depending on its oxidation state. An exemplary redox indicator is indigo carmine.

[0070] Phenolic compound sensitive indicators are indicators / dyes that are sensitive to phenolic compounds. Phenolic compounds are a class of compounds consisting of one or more hydroxyl groups directly bonded to an aromatic hydrocarbon group. Phenolic compounds can be synthesized industrially or produced by plants and microorganisms. In fact, phenolic compounds are one of the largest chemical classes of compounds biosynthesized in plants. Examples of phenolic compound sensitive indicators include, but are not limited to: ferric chloride and 4-nitrobenzene diazonium tetrafluoroborate.

[0071] In some embodiments, the colorimetric sensor array comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten pH-sensitive dyes; at least one, at least two, or at least three carbonyl-sensitive indicators; and at least one, at least two, at least three, at least four, at least five, at least six, at least seven, or at least eight solvatochromic dyes. In some embodiments, the colorimetric sensor array further comprises at least one redox indicator; and at least one or at least two phenolic compound-sensitive indicators.

[0072] The use of more than one type of indicator and / or dye may expand the range of analytes to which the colorimetric sensor array is sensitive, may improve sensitivity to some analytes, and / or may increase the ability to distinguish analytes. In some embodiments, the colorimetric array includes 3 to 50 sensors, 5 to 45 sensors, 10 to 40 sensors, 15 to 35 sensors, 20 to 25 sensors, or 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 or 50 sensors. In some embodiments, the colorimetric array includes 9, 14, 23, or 26 sensors. The terms "sensor," "sensing unit," and "unit" are used interchangeably in this disclosure.

[0073] In some embodiments, the colorimetric sensor array includes the following indicators and / or dyes: bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, Reichardt's dye, Brooker's merocyanine, and Schiff's reagent.

[0074] In some other embodiments, the colorimetric sensor array includes the following indicators and / or dyes: bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, Reichardt's dye, Brooker's merocyanine, Schiff's reagent, paracyanine, litmus, chrome azurol S and salts of hydroxylamine.

[0075] In some other embodiments, the colorimetric sensor array includes the following indicators and / or dyes: bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, Reichardt's dye, Brooker's merocyanine, Schiff's reagent, paracyanine, litmus, chrome azuro blue S, salts of hydroxylamine, Nile blue, merocyanine 540, acridine orange, Nile red, rhodamine, nitrazine yellow and phenol red.

[0076] In some other embodiments, the colorimetric sensor array includes the following indicators and / or dyes: bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, Reichardt's dye, Brooker's merocyanine, Schiff's reagent, paracyanine, litmus, chrome azuro blue S, salts of hydroxylamine, nitrazine yellow, phenol red, indigo carmine, iron chloride, 4-nitrobenzene diazonium tetrafluoroborate, Nile red, merocyanine 540 and disperse orange 25.

[0077] In some embodiments, the salt of bromocresol green is bromocresol green sodium salt.

[0078] In some embodiments, the resazurin salt is resazurin sodium salt.

[0079] In some embodiments, the salt of xylenol orange is xylenol orange tetrasodium salt.

[0080] In some embodiments, the salt of hydroxylamine is hydroxylamine sulfate or hydroxylamine hydrochloride, preferably hydroxylamine sulfate.

[0081] In some embodiments, the methyl red, bromothymol blue, bromocresol purple, rhodamine, phenol red and / or nitrazine yellow used in the colorimetric sensor array are mixed with a base. The base can be an inorganic base, including but not limited to sodium carbonate (Na 2 CO 3 ), sodium hydroxide (NaOH), potassium hydroxide (KOH), calcium hydroxide (Ca(OH) 2 ) and sodium bicarbonate (NaHCO 3 In some specific embodiments, the inorganic base is sodium carbonate (Na 2 CO 3), sodium hydroxide (NaOH) or potassium hydroxide (KOH). The base can also be a basic amino acid, including but not limited to: arginine, histidine and lysine. In some specific embodiments, the basic amino acid is arginine or histidine.

[0082] In some embodiments, methyl red and sodium carbonate (Na 2 CO 3 In some other specific embodiments, bromothymol blue and sodium carbonate (Na 2 CO 3 ), potassium hydroxide (KOH) or arginine. In some other embodiments, bromocresol purple is mixed with potassium hydroxide (KOH). In some other embodiments, rhodic acid is mixed with arginine. In some other embodiments, nitrazine yellow is mixed with sodium carbonate (Na 2 CO 3 In some other specific embodiments, phenol red is mixed with potassium hydroxide (KOH).

[0083] In some embodiments, the salt of hydroxylamine is mixed with a pH-sensitive dye, such as Congo red, methyl orange or bromophenol blue. In some specific embodiments, the salt of hydroxylamine mixed with a pH-sensitive dye is further mixed with a base, preferably an inorganic base, such as sodium carbonate (Na 2 CO 3 ).

[0084] In some specific embodiments, the colorimetric sensor array includes the following indicators and / or dyes: bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, and sodium carbonate (Na 2 CO 3 ) mixed with methyl red and sodium carbonate (Na 2 CO 3 ) mixed with bromothymol blue, bromocresol purple mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine, and Schiff's reagent.

[0085] In some other specific embodiments, the colorimetric sensor array includes the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, and sodium carbonate (Na 2 CO 3 ) mixed with methyl red and sodium carbonate (Na 2 CO 3 ), bromothymol blue mixed with potassium hydroxide (KOH), bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine, chrome azuro blue S, hydroxylamine sulfate mixed with Congo red, and Schiff's reagent.

[0086] In some specific embodiments, the colorimetric sensor array includes the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, and sodium carbonate (Na 2 CO 3 ) mixed with methyl red and sodium carbonate (Na 2 CO 3 ), bromothymol blue mixed with potassium hydroxide (KOH), bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine, chrome azuro blue S, hydroxylamine sulfate mixed with Congo red, Schiff's reagent, Nile blue, merocyanine 540, acridine orange, Nile red (dissolved in acetone), Nile red (dissolved in ethanol), rhodamine mixed with arginine, bromothymol blue mixed with arginine, sodium carbonate (Na 2 CO 3 ) and phenol red mixed with potassium hydroxide (KOH).

[0087] In some specific embodiments, the colorimetric sensor array includes the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, and sodium carbonate (Na 2 CO 3 ) mixed with methyl red and sodium carbonate (Na 2 CO 3 ) mixed with bromothymol blue, bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), bromothymol blue mixed with arginine, and bromothymol blue mixed with sodium carbonate (Na 2 CO 3 ), nitrazine yellow mixed with potassium hydroxide (KOH), phenol red mixed with potassium hydroxide (KOH), indigo carmine, ferric chloride, 4-nitrobenzenediazonium tetrafluoroborate, Nile Red (dissolved in acetone), Nile Red (dissolved in ethanol), merocyanine 540, disperse orange 25, Reichardt's dye, Brooker's merocyanine, chrome azuro blue S, hydroxylamine sulfate mixed with Congo red, hydroxylamine sulfate mixed with methyl orange, hydroxylamine sulfate mixed with bromophenol blue, and Schiff's reagent.

[0088] Each indicator and / or dye used in the colorimetric sensor array is dissolved in a suitable solvent. Examples of suitable solvents include, but are not limited to, methanol, ethanol, deionized water, and acetone.

[0089] In some specific embodiments, for the following indicators / dyes, the suitable solvent used is ethanol: paramerin or paramerin base; bromocresol green or its salt, in particular bromocresol green sodium salt; resazurin or its salt, in particular resazurin sodium salt; methyl red; bromothymol blue; bromocresol purple; Brooker's merocyanine; chrome azurol S; merocyanine 540; acridine orange; rhodamine; nitrazine yellow; phenol red and Nile red. In some embodiments, for the following indicators / dyes, the suitable solvent used is deionized water: xylenol orange or its salt, in particular xylenol orange tetrasodium salt; and Congo red. In some embodiments, for the following indicators / dyes, the suitable solvent used is acetone: Reichardt's dye; Nile blue; Nile red, and 4-nitrobenzene tetrafluoroborate diazonium salt. In specific embodiments, the suitable solvent for 4-nitrobenzene tetrafluoroborate diazonium salt is a mixture of acetone and deionized water. In some other specific embodiments, the suitable solvent for Nile red is preferably a hydrophilic solvent, such as ethanol. The suitable concentration of the indicator / dye used can be determined according to the common knowledge available in the relevant field without undue experimentation. In some embodiments, the final concentration of the indicator / dye used in the sensor is about 0.1 to about 10, or about 0.2 to about 9.5, or about 0.3 to about 9, or about 0.4 to about 8.5, or about 0.5 to about 8, or about 0.6 to about 7.5, or about 0.7 to about 7, or about 0.8 to about 6.5, or about 0.9 to about 6, or about 1 to about 5.5, or about 1.2 to about 5, or about 1.4 to about 4.5, or about 1.6 to about 4, or about 1.8 to about 3.5, or about 2 to about 3 mg / mL, or about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 , 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5, 5.2, 5.4, 5.6, 5.8, 6, 6.2, 6.4, 6.6, 6.8, 7, 7.2, 7.4, 7.6, 7.8, 8, 8.2, 8.4, 8.6, 8.8, 9, 9.2, 9.4, 9.6, 9.8 or 10 mg / mL. The indicator or dye can be prepared according to the working examples shown in the disclosure or prepared using any other method or process available in the art or commercially available.

[0090] The indicators or dyes in the colorimetric sensor array are arranged in a predetermined pattern, which can be linear, two-dimensional, or three-dimensional. The predetermined pattern can be a combination of rows, columns, spirals, etc. After interacting with one or more analytes (i.e., VOCs), the distinctive color and intensity response of each indicator or dye in the colorimetric sensor array reflects the signature of the one or more analytes.

[0091] Each of the indicators or dyes in the colorimetric sensor array is deposited on a substrate. The substrate may be any material capable of retaining an indicator or dye on its surface. The example of a substrate includes a polymer film, such as a cellulose-based material. The example of a suitable substrate material includes, but is not limited to, filter paper, paper, and a porous membrane. In a specific embodiment, the substrate material is a filter paper. The indicator / dye can be non-covalently attached (affixed) in or on a substrate by direct deposition, including but not limited to pin-printing, airbrushing, ink-jet printing, screen printing, stamping, micropipette spotting, or nanoliter dispensing.

[0092] In some embodiments, the colorimetric sensor array further comprises a patterned mask for positioning the substrate. The mask is typically made of a non-porous and non-absorbent material, such as a flexible polymer. Examples of flexible polymers include, but are not limited to, polyimide, polyethylene naphthalate (PEN), polytetrafluoroethylene (PTFE), polyethylene terephthalate (PET), and combinations thereof. The pattern of the mask corresponds to the predetermined pattern of the indicator or dye in the colorimetric sensor array. The mask should contain openings or holes that match the shape and size of the substrate used.

[0093] The suitable shape and / or size of the substrate can be determined according to the character of the indicator / dye used in the array and / or the tested sample. Operable common shapes include but are not limited to circle, oval, square, rectangle, triangle, pentagon, hexagon and rhombus. The diameter of the substrate or every side can be about 1,2,3,4,5,6,7,8,9 or 10mm. In a specific embodiment, the substrate is circular, and the diameter is about 3mm.

[0094] In some embodiments, the colorimetric sensor array further comprises a support for supporting the substrate and / or the patterned mask. The support can be made of a polymer (e.g., polyvinyl chloride (PVC), polyvinylidene fluoride (PVDF), poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), polysulfone (PSF), or polyacrylonitrile (PAN)), or made of a cellulose-based material (e.g., filter paper or paper).

[0095] The size of the support generally corresponds to the size of the colorimetric sensor array and is generally determined by the number of sensors contained in the colorimetric sensor array. The support can be any common shape, including but not limited to: rectangular, circular, oval, square, triangle, pentagon, hexagon and diamond. The diameter or each side of the support can be about 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 mm. In a specific embodiment, the support is rectangular and the size of the support is 15 mm×25 mm.

[0096] The colorimetric sensor array described herein is capable of detecting VOCs at low concentrations and with high accuracy. The colorimetric sensor array can be used to achieve higher sample throughput and faster response. Most importantly, the sensor readout can be observed with the naked eye and does not require complex data processing.

[0097] Many indicators / dyes used in the colorimetric sensor array of the present invention have not been fully studied, and therefore, the properties of such indicators / dyes are still unknown. The inventors of the present invention have selected suitable indicators / dyes that can respond to the VOCs emitted by most food and beverage products from a large number of chemicals that may be used for colorimetric reactions through experiments. In addition, although some of the indicators / dyes have been used to detect liquid samples, the possibility of different performances of such indicators / dyes in wet and dry states makes them less suitable for the detection of VOCs without further modification. In addition, each available pH indicator / dye can only respond to a specific pH range. However, the pH value of the VOCs emitted by actual commercial products (particularly food and beverage products) is difficult to determine. In the present invention, all pH-sensitive indicators / dyes used have been selected through experiments to detect the VOCs emitted by most food and beverage products.

[0098] In one aspect, a system for detecting volatile organic compounds (VOCs) in a sample is provided. The system includes a colorimetric sensor array as described above, a sensor chamber for accommodating the colorimetric sensor array, and a sample chamber for accommodating the sample. The sensor chamber is in fluid communication with the sample chamber. In some embodiments, more than one colorimetric sensor array may be used in the sensor chamber. In some other embodiments, more than one sensor chamber may be used in the system.

[0099] In some embodiments, the system further comprises a flow facilitator. The flow facilitator is in fluid communication with the sample chamber and the sensor chamber. The flow facilitator promotes the circulation of the VOCs in the system, thereby shortening the sensing duration. In some embodiments, the flow facilitator is a pump, preferably a vacuum pump, and more preferably a micro vacuum pump.

[0100] In some embodiments, the system further comprises an imaging device or image sensor. The imaging device or image sensor is used to detect and / or capture the color changes of the colorimetric sensors in the array. Any suitable optical or other detector can be used, including but not limited to: scanners and cameras.

[0101] In some other embodiments, the system further includes a processing device and / or a storage device to process and store any acquired data.

[0102] In one aspect, a method for detecting and analyzing VOCs in a sample is provided, the method comprising the following steps: (i) providing the colorimetric sensor as described above, or the system as described above, (ii) acquiring a first image of the colorimetric sensor array, (iii) providing the sample and exposing the colorimetric sensor array to the sample for a period of time, (iv) acquiring a second image of the colorimetric sensor array, and (v) analyzing the difference between the first image and the second image.

[0103] The first image acquired in step (ii) is a control image of the colorimetric sensor array before being exposed to the sample. The second image acquired in step (iv) is a test image of the colorimetric sensor array after being exposed to the sample. Accordingly, performing steps (ii) to (iv) will allow the system to measure color changes based on changes in the initial color spectrum of a specific array. Steps (iv) and (v) can be modified to acquire and analyze a series of images at various time intervals after the array is exposed to the sample. In some embodiments, images can be acquired every minute, every 2, 3, 4, 5, 6, 7, 8, 9 or 10 minutes, or at intervals of any length therebetween, or at intervals of 20 or 30 minutes, or other suitable intervals. In some other embodiments, images within one hour, 2, 3, 4, 5, 6 hours, or other suitable time frames selected based on the color change rate can be acquired continuously.

[0104] In some embodiments, the exposure time in step (iii) above is from about 10 minutes to about 48 hours, or from about 20 minutes to about 46 hours, or from about 30 minutes to about 44 hours, or from about 40 minutes to about 42 hours, or from about 50 minutes to about 40 hours, or from about 1 hour to about 38 hours, or from about 2 hours to about 36 hours, or from about 3 hours to about 34 hours, or from about 4 hours to about 32 hours, or from about 5 hours to about 30 hours, or from about 6 hours to about 28 hours, or from about 7 hours to about 26 hours, or from about 8 hours to about 24 hours, or from about 9 hours to about 22 hours, or from about 10 hours to about 28 hours. In some embodiments, the exposure time is as short as possible, for example, about 30 minutes or less.

[0105] The step (iii) of the method should be carried out at a temperature suitable for the analysis of the sample. The suitable temperature can be determined according to the properties of the sample. For example, a suitable temperature can be a temperature at which the sample is usually consumed, stored and / or transported, such as room temperature, common cooking temperature, common refrigeration temperature and / or common freezing temperature. In some specific embodiments, a suitable temperature is in the range of about -20°C to about 40°C, or about -15°C to about 35°C, or about -10°C to about 30°C, or about -5°C to about 25°C, or about 0°C to about 20°C, or about 5°C to about 15°C, or about -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38 or 40°C. In a specific embodiment, the suitable temperature is room temperature of about 25°C.

[0106] In some embodiments, analyzing the difference between the first image and the second image includes measuring the first image (R 1 , G1, B 1 ) and the second image (R 2 , G 2 , B 2 ), calculate the RGB (red, green, blue) values ​​of each indicator and / or dye in the colorimetric sensor array, calculate the differences ΔR, ΔG and ΔB, calculate the total Euclidean distance of the RGB value changes, and analyze the total Euclidean distance. The following formula is used in the calculation: ΔR = |R 2 –R 1 |, ΔG=|G 2 –G 1 |, ΔB=|B 2 –B 1 |. The acquired data can then be analyzed using common statistical methods such as principal component analysis (PCA) and partial least squares (PLS) analysis, etc.

[0107] The colorimetric sensor array, system, and method described above have a variety of applications, including but not limited to: detecting adulteration or imitation in a sample, assessing the freshness of a sample, assessing the general quality of a sample, and determining the geographic origin of a sample. The colorimetric sensor array, system, and method can be used alone or as an alternative or supplemental analysis to existing VOCs assessment methods (i.e., gas chromatography and human sensory analysis). The following lists exemplary scenarios in which the colorimetric sensor array, system, and method can be used.

[0108] As a quick and easy quality control tool, it is used to monitor the quality of aromatic edible vegetable oil products. Since the VOCs profile can be affected by various factors such as oilseeds and processing technology, any changes in these factors may affect the aroma of the final product. Therefore, the analysis results generated by the colorimetric sensor array can be compared with a standard reference to ensure the consistency of the VOCs profile in the product.

[0109] As a fast and easy VOCs analysis tool to assist product development. The colorimetric sensor array can be used to first evaluate a new formulation. The analysis results generated by the sensor array can be compared with a standard reference to evaluate whether the VOCs profile of the new formulation meets the desired composition.

[0110] As a quick and easy screening tool for studying competitive products. Samples of competitive products can be first evaluated using the colorimetric sensor array. Only samples with abnormal results need to be further evaluated by other methods, saving time and cost.

[0111] As a quick and easy analytical tool, it is used to assess the freshness of a given product (e.g., edible vegetable oil products). The degradation of edible vegetable oils can lead to changes in the VOCs spectrum therein, for example, as the oil deteriorates, the content of acidic VOCs and aldehyde VOCs may increase. The presence of such VOCs can be detected by the colorimetric sensor array.

[0112] The data acquired using the colorimetric sensor array, the system, and the method described above can be stored in a storage device and processed by a processing device. In this way, a unique colorimetric fingerprint can be generated for each sample, which can be used for qualitative identification and semi-quantitative analysis of VOCs in the sample. In addition, a database containing such unique colorimetric fingerprints can be established and used to detect adulteration or imitation in samples, evaluate the freshness of samples, evaluate the general quality of samples, and determine the geographical origin of samples.

[0113] The sample may be solid, liquid, semi-solid and / or semi-liquid (eg gel, paste) or gas, as long as the sample contains or can release VOCs.

[0114] In some embodiments, the sample is a crop or product thereof, an oil, a liquid dressing (eg, soy sauce, vinegar, or cider), a spread, a paste, an extract, or a beverage.

[0115] Examples of crops include, but are not limited to, rice, wheat, corn, soybeans, cocoa, coffee beans, tea, spices, rubber, tobacco, and fruits, preferably coffee beans and fruits. Examples of fruits include, but are not limited to, strawberries, bananas, apples, pears, oranges, mangoes, grapes, pineapples, durian, guava, kiwis, papayas, cherries, etc., preferably strawberries.

[0116] In some embodiments, the oil is a vegetable oil, preferably an edible vegetable oil, examples of which include, but are not limited to, sesame oil, peanut oil, sunflower oil, rice bran oil, olive oil, avocado oil, canola oil, coconut oil, corn oil, cottonseed oil, mustard oil, palm oil, rapeseed oil, safflower oil, and soybean oil. In some specific embodiments, the oil is sesame oil.

[0117] VOCs that can be analyzed using the colorimetric sensor array, system or method described above include, but are not limited to, acids, aldehydes, alcohols and polar VOCs, such as acetic acid, propionic acid, formic acid, butyric acid, valeric acid, hexanoic acid, heptanoic acid, butyraldehyde, valeraldehyde, hexanal, heptaldehyde, furfural, benzaldehyde, formaldehyde, acetaldehyde and acetone. Example

[0118] Example 1 - Exemplary 14-sensor colorimetric sensor array

[0119] Array Structure

[0120] Figure 1 A schematic diagram of the colorimetric sensor array of the 14 sensors is shown. The sensor array has 14 paper-based sensors arranged in a specific manner. The sensor array adopts a layered structure. A polyvinyl chloride (PVC) microporous membrane (pore size: 0.22 μm) is used as a support for easy handling. A patterned polyethylene terephthalate (PET) mask is used to position the sensors. The sensors and the PET mask are attached to the PVC support using commercially available double-sided tape.

[0121] Indicators used in arrays

[0122] The 14 sensors were loaded with colorimetric indicators that were carefully selected for fragrance oil VOCs. Table 1 summarizes the active chemical components in each sensor and the corresponding target VOCs. All chemicals used were commercially available. Table 1. List of active ingredients in the 14 sensor arrays. Sensor No. Active chemical ingredients Target VOCs 1 Pararubine Carbonyl compounds 2 Litmus acid 3 Bromocresol green sodium salt acid 4 Resazurin Sodium Salt acid 5 Xylenol Orange Tetrasodium Salt acid 6 <![CDATA[Methyl Red + Sodium Carbonate (Na 2 CO 3 )]]> Acid, aldehyde 7 <![CDATA[Bromothymol Blue + Sodium Carbonate (Na 2 CO 3 )]]> Acid, aldehyde 8 Bromocresol purple + potassium hydroxide (KOH) Acid, aldehyde 9 Bromothymol blue + potassium hydroxide (KOH) Acid, aldehyde 10 Reichardt's dye Polar VOCs 11 Brooker's merocyanine Polar VOCs 12 Chrome Azure S Polar VOCs 13 Hydroxylamine sulfate + Congo red Aldehydes, Ketones 14 Schiff's reagent aldehyde

[0123] Example 2 - Exemplary Experimental Setup

[0124] The experimental device consists of three main components: (1) sample chamber, (2) sensor chamber and (3) micro vacuum pump. The three components are connected by flexible tubes. Figure 2A schematic diagram of the experimental setup is shown. By introducing the sensor chamber, contamination of the sensor by liquid samples can be prevented. Gas circulation can be promoted by adding a micro vacuum pump to shorten the time required for sensing. The micro vacuum pump is powered by an external power supply.

[0125] Fabrication of sensor arrays

[0126] Prepare the indicator solutions as summarized in Table 2. Table 2. Summary of preparation of indicator solutions.

[0127] Filter paper is chosen as the substrate material for loading the indicator dye because of its hydrophilicity - adsorbed water molecules can promote reactions such as intermolecular proton transfer between the immobilized dye molecules and the gaseous analyte, which is necessary for pH-sensitive dyes to change color in some embodiments. In addition, filter paper is porous and readily available, making it ideal for disposable sensors. Cut the first-grade qualitative filter paper into circular pieces The filter paper was immersed in the corresponding indicator solution and dried. For sensors No. 2-9 and 13, drying was performed in a 60°C oven; for sensors No. 1, 10-12 and 14, drying was performed in the environment under standard laboratory conditions (sensor No. 14 was dried in the environment overnight). The dried sensors were sealed in a sealed bag and stored in the dark before use.

[0128] The polyvinyl chloride (PVC) microporous membrane was cut into 25 mm × 15 mm. A microporous film with 14 circular holes was cut from the polyethylene terephthalate (PET) film using a benchtop cutter. The same size mask.

[0129] The sensor array was assembled by attaching the PET mask and sensors to a PVC support film using commercially available double-sided tape. The tape used had little odor.

[0130] Sensing and data acquisition using edible oil samples

[0131] Weigh 5 mL of oil sample and transfer it to the sample chamber, and use the desktop scanner to obtain an image of the sensor array. After scanning, place the sensor array in the sensor chamber. Turn on the micro vacuum pump to start the sensing process. After 30 minutes, turn off the micro vacuum pump. Take out the sensor array from the sensor chamber, and then use the desktop scanner to obtain an image of the sensor array.

[0132] Data analysis

[0133] The RGB values ​​of each sensor can be obtained using any image analysis software. The color difference of each sensor can be calculated as follows: ΔR=|R 之后 -R 之前 | ΔG=|G 之后 -G 之前 | ΔB=|B 之后 -B 之前 |

[0134] The obtained ΔR, ΔG, and ΔB values ​​can be used to construct a color difference map. The Euclidean distance can be calculated using the following formula:

[0135] The obtained Euclidean distance can be used for data analysis, such as principal component analysis (PCA) and partial least squares (PLS) regression.

[0136] Example 3 - Analysis of sesame oil samples using an exemplary colorimetric sensor array

[0137] Sesame oil produced by different processing techniques has different aromas. Hot pressing and small milling are two common processes for producing aromatic sesame oil. In both processes, roasted sesame seeds are pressed for oil by mechanical force. The small milling process uses hot water to remove impurities from the oil; due to the difference in density and solubility, impurities can be easily removed. Therefore, small milled sesame oil tends to have a better aroma. The aroma of sesame oil is caused by the volatile organic compounds (VOCs) present in it. Since VOCs only constitute a small part of the mass and tend to evaporate from the oil due to their high vapor pressure, the VOCs of a given sesame oil sample can be analyzed by analyzing the headspace gas when the sample is placed in a closed container. In this example, the VOC spectrum of commercial sesame oil samples produced by hot pressing and small milling was analyzed using the sensors described in Examples 1 and 2.

[0138] The sensor array was validated using chemical standards and sesame oil samples produced by two different processes (hot pressing and small milling). The sensor array readings were compared with GC data and classified using principal component analysis (PCA). Preliminary results suggest that the sensor array can be a simple and fast way to visualize the VOCs spectrum of aromatic sesame oil. On the one hand, the sensor array can generate a colorimetric fingerprint for each sample; on the other hand, it can provide some chemical information about the VOCs composition without the need for complex analytical tools.

[0139] Material

[0140] Reagents

[0141] The indicator solution described in Example 2 was prepared using bromocresol green sodium salt, bromocresol purple sodium salt (dye content 90%), bromothymol blue (analytical grade), Brooker's merocyanine, chrome azuroin S (dye content 50%), Congo red, hydroxylamine sulfate, methyl red (analytical grade), parasmin (dye content 95%), Reichardt's dye (dye content 90%), resazurin sodium salt, xylenol orange tetrasodium salt, litmus indicator solution (1.0% ± 0.05%) and Schiff's reagent. Potassium hydroxide (KOH) and sodium carbonate (Na 2 CO 3 ) was used to adjust the pH of the indicator solution. Acetic acid, hexanoic acid, valeraldehyde, heptanal, benzaldehyde, and phenylacetaldehyde were used to represent volatile acids and aldehydes commonly found in food.

[0142] Sesame oil sample

[0143] Fifty-five commercial aromatic sesame oil samples were collected in China. One hot-pressed sample (labeled as "HP-S") and one small-milled sample (labeled as "XM-S") were used as standards for both techniques. The remaining 53 samples were from 21 brands (labeled with English letters A to U), including 28 hot-pressed (HP) samples and 25 small-milled (XM) samples.

[0144] method

[0145] A 14-unit paper-based colorimetric sensor array was prepared according to Example 1 above.

[0146] Verification with chemical standards

[0147] 2 μL of liquid chemical (the liquid chemical can be acetic acid, hexanoic acid, valeraldehyde, heptanal, benzaldehyde or phenylacetaldehyde) was dropped on the bottom of a 5-liter chamber. The chamber was then covered and sealed with parafilm. The liquid chemical was allowed to evaporate for 30 minutes. Before reacting with the chemical, a scanned image of the sensor was acquired. The colorimetric sensor was then placed in the chamber to react with the gas. After 30 minutes, the sensor was removed and a scanned image was acquired.

[0148] Gas chromatography (GC)-mass spectrometry (MS) analysis

[0149] The VOC spectra of 39 sesame oil samples (including HP-S, XM-S, 19 randomly selected HP commercial samples and 18 randomly selected XM commercial samples) were analyzed by solid phase microextraction (SPME)-GC-MS. The sample analysis was conducted at Wilmar (Shanghai) Biotechnology Research and Development Center Co., Ltd.

[0150] VOCs Sensing of Sesame Oil

[0151] According to the process described in Example 2, a homemade device ( Figure 2 ) was used to sense sesame oil. For each sample, three identical sensor arrays were tested in parallel. The experiments were performed at room temperature, and each test lasted for 30 minutes.

[0152] Data analysis

[0153] The software was used to determine the RGB values ​​of each sensor before and after exposure to the sample VOCs. The color difference and Euclidean distance were calculated as described in Example 2 above.

[0154] Therefore, a color difference map can be constructed using the ΔR, ΔG, ΔB values. For visualization, the color range of 0–167 (i.e., 167 is the maximum color difference achieved in all experiments) is expanded to an 8-bit color range. In addition, the Euclidean distance is analyzed using principal component analysis (PCA).

[0155] Results and Discussion

[0156] Reactions with chemical standards

[0157] The sensor can respond to all 6 chemical standards ( Figure 3 ).

[0158] Sensor No. 1 (pararubin) can change color in response to acetic acid, hexanoic acid, and valeraldehyde. The color change is due to the amino group -NH 2 Reaction with the carbonyl -(C=O)- group in acids / aldehydes.

[0159] Sensors 2-5 (pH indicators) can change color in response to acetic acid and hexanoic acid. Sensor 5 also shows a slight color change in response to valeraldehyde.

[0160] Sensors 6-9 (pH indicator + base) can change color in response to acetic acid, hexanoic acid, and valeraldehyde. Sensor 9 also shows a slight color change in response to heptanal. The color change is due to the reaction between the alkaline chemical and the acid / aldehyde. As the alkaline chemical is consumed during the reaction, the pH will change; the pH indicator will change color accordingly.

[0161] Sensors No. 10-12 (solvatochromic dyes) were more sensitive to acids, especially the highly polar acetic acid; sensors No. 11 and 12 also showed observable color changes in response to valeraldehyde.

[0162] Sensor No. 13 (hydroxylamine sulfate + Congo red) can change color in response to all tested aldehydes. The color change is due to the reaction between hydroxylamine sulfate and aldehyde; the sulfuric acid generated by the reaction can change the color of Congo red.

[0163] Sensor No. 14 (Schiff's reagent) can change color in response to phenylacetaldehyde. The color change is due to the reaction between the colorless para-fuchsin in the Schiff's reagent and phenylacetaldehyde, which will form a colored compound.

[0164] Sesame Oil Standard

[0165] The same types of VOCs were detected in both HP-S and XM-S, including alcohols, aldehydes, furans, phenols, pyrazines, other heterocyclic compounds (pyridine, pyrrole, thiazole, thiophene, etc.) and organic molecules ( Figure 4a HP-S contains more acids and aldehydes. The sensor array detected stronger signals from HP-S, especially in sensors No. 5, 7, 8 and 11 (compare Figure 4b and Figure 4c ). Based on the response of the sensor array to chemical standards, the stronger signal can be attributed to the higher content of acids and aldehydes in the VOCs of HP-S.

[0166] Commercial samples

[0167] The average VOC concentrations of the commercial HP and XM samples were 551.92 mg / kg and 522.47 mg / kg, respectively (Table 3). The major VOCs types identified in the commercial samples were the same as those in HP-S and XM-S. In general, the HP samples contained significantly higher concentrations of acids and aldehydes than the XM samples. The lower concentrations of volatile acids and aldehydes in the XM samples may be due to the hot water extraction step in the small mill process, which is not performed in hot pressing. Table 3. Concentrations of major VOCs identified in commercial sesame oil samples. SD: standard deviation.

[0168] The HP samples generally contained more types of acids and aldehydes than the XM samples, especially lower molecular weight acids and aldehydes such as acetic acid, hexanoic acid, and hexanal (Table 4). Table 4 Average concentrations of acids and aldehydes identified in commercial sesame oil samples. ND: Not Detected.

[0169] The sensor array detected stronger signals from most HP samples, especially sensors No. 5, 7, 8, and 11, because of the higher concentrations of acids and aldehydes in the HP samples. Figure 5a and Figure 5b Typical scanned images and average color difference graphs of commercial HP and XM samples are shown, respectively. There are significant differences in the sensing results that can be directly observed by the naked eye. This trend can also be observed in HP and XM samples from the same brand ( Figure 5c ).

[0170] By calculating the Euclidean distance, the difference in color changes can be presented more intuitively ( Figure 5d ). HP samples generally have larger Euclidean distances (except for sensor 14). HP and XM samples have larger differences (i.e., the difference between the means is greater than 5) in sensors 3-8, 10, 11, and 14. Therefore, only the data collected by these 9 sensors were used for PCA.

[0171] The PCA results are as follows Figure 5e As shown. The first three principal components can explain 84.5% of the total variance. HP samples and XM samples are largely distinguished by the first principal component (PC1). Despite the differences between brands, the PCA results show that the sensing results achieved by the sensor array depend on the processing technology used to produce the samples.

[0172] The analysis results of 55 commercial samples show that the colorimetric sensor array can effectively combine sample VOCs information into a single "color fingerprint". The color changes exhibited by the sensor are clearly observable to the naked eye, so minimal data processing is required. Compared with GC-based technologies, the results obtained by the colorimetric sensor array are more intuitive and can be interpreted without even complex data analysis. In addition, the colorimetric sensor array has demonstrated the ability to reflect the differences between fresh sesame oils produced by different technologies, making a step forward from simple deterioration monitoring to processing technology classification. In addition, the study showed that the colorimetric sensor array can exhibit obvious color changes within 30 minutes, which greatly improves the timeliness compared to many existing studies that require longer reaction times.

[0173] Example 4 - Detection of Refined Oil in Blended Sesame Oil Using an Exemplary Colorimetric Sensor Array

[0174] Refined oils are sometimes added to aromatic sesame oils. Blended sesame oil products can be sold legally when the ingredients are clearly labeled in the product information. However, if the product does not state that refined oils have been added, it can be considered adulterated. Since refined oils have a lower aroma (because VOCs are removed during the oil refining process), the addition of refined oils to aromatic oils dilutes the aroma of the final product. The refined oils can also be obtained from sesame seeds, making them challenging to detect using established methods such as fatty acid profiling.

[0175] Commercial samples

[0176] In Example 3, it was found that 10 HP samples (from brands B, D, G, H, I, J) produced less color variation than the other HP samples. These samples were distinguished from the other HP samples by the second principal component (PC2) ( Figure 5e Since it was known (based on the product label) that the sample from Brand I was a blended sesame oil product containing refined oil and aromatic sesame oil, the remaining 9 samples were also suspected to contain refined oil.

[0177] The authenticity of sesame oil can be assessed by its lignan content. Sesame lignans are found only in sesame seeds and are generally present in higher concentrations in hot-pressed sesame oil compared to sesame oil produced using other techniques. Therefore, products from brands B, D, G, H, and J were analyzed for lignan concentrations using reversed-phase liquid chromatography (RP-LC).

[0178] Compared with the reference group (100% hot-pressed sesame oil), the products from brands D, G, H, and J had significantly lower lignan contents, indicating the possibility of refined oils ( Figure 6 ). The product from Brand B had a higher concentration of lignans. Given the weaker signal collected by the sensor array, Brand B may have used a processing technique other than hot pressing or micro-milling.

[0179] Laboratory samples

[0180] Blended sesame oil was prepared using pure refined oil and pure hot pressed sesame oil. Refined oil and hot pressed sesame oil were mixed in various proportions: 80% v / v refined oil-20% v / v sesame oil, 50% v / v refined oil-50% v / v sesame oil, 20% v / v refined oil-80% v / v sesame oil, 10% v / v refined oil-90% v / v sesame oil. VOC sensing and data analysis were performed as described in Examples 1-3 above. For each blended oil formulation, colorimetric sensing was repeated five times by analyzing 5 samples (5 mL / sample); three sensor arrays were tested in parallel each time.

[0181] The color difference of pure refined oil, various blended sesame oil samples and pure hot-pressed sesame oil is shown in the figure below. Figure 7a As shown in the figure, the signal of pure refined oil is weak. As the volume percentage of sesame oil increases, the signal becomes stronger; the signal of pure hot-pressed sesame oil is the strongest.

[0182] PCA analysis was performed using the Euclidean distance of all 14 sensors. The clusters of pure refined oil and pure hot-pressed sesame oil were clearly separated ( Figure 7b ). With the increase of sesame oil volume percentage, the cluster of blended sesame oil gradually moved along the positive direction of PC1 axis and finally overlapped with the cluster of pure hot-pressed sesame oil.

[0183] PLS regression analysis was performed using Euclidean distance. When using 9 PLS components for analysis, r 2 = 0.9423, indicating a strong correlation between the Euclidean distance measured by the sensor array and the volume percentage of refined oil in a given sample ( Figure 8 ).

[0184] The limit of detection (LOD) was estimated using a three-sigma approach, where the LOD was calculated as 3 times the standard deviation of 0% v / v refined oil (as predicted by the PLS model). The LOD was estimated to be 19.5% v / v refined oil. This result suggests that the sensor array has the potential to detect refined oil in blended sesame oil based on its VOC profile when the volume percentage of refined oil is not less than 19.5% v / v.

[0185] Example 5 - Exemplary 23-sensor colorimetric sensor array for VOCs analysis

[0186] To demonstrate that additional indicators can be used for VOCs sensing and that the sensor array can be used to analyze VOCs in other consumer products besides vegetable oils, a series of experiments were performed.

[0187] Figure 9a The arrangement of sensors of the sensor array used in the experiment is shown. Sensors No. 15-19 were made with solvatochromic dyes, and sensors No. 17-23 were made with pH-sensitive dyes pretreated with alkaline chemicals.

[0188] Table 5 lists the active chemistries and target VOCs for additional sensors 15-23. Table 6 summarizes the preparation of additional indicator solutions. Table 5. Active chemical compositions and target VOCs of additional indicators. Sensor No. Active chemical ingredients Target VOCs 15 Nile Blue Polar VOCs 16 Merocyanine 540 Polar VOCs 17 Acridine Orange Polar VOCs 18 Nile Red (soluble in acetone) Polar VOCs 19 Nile Red (soluble in ethanol) Polar VOCs 20 Rhodamine + Arginine Acid, aldehyde 21 Bromothymol blue + arginine Acid, aldehyde 22 <![CDATA[Nitrazine Yellow + Na 2 CO 3 > Acid, aldehyde 23 Phenol red + KOH Acid, alcohol A1 Hydroxylamine sulfate + methyl orange Aldehydes, Ketones A2 Hydroxylamine sulfate + bromophenol blue Aldehydes, Ketones Table 6. Summary of preparation of additional indicator solutions.

[0189] To represent some common consumer products that can emit VOCs, two vinegar samples (apple vinegar and black vinegar), one soy sauce sample, one brewed black coffee sample, and one nail polish remover sample were collected and tested with the sensor array. The sensing was performed using the same experimental setup as described in Example 2. The results are shown in Figure 2. Figure 9b to Figure 9f For the two vinegar samples, most sensors could change color within 5 minutes.

[0190] To further demonstrate that the pH-sensitive dye in sensor No. 13 (hydroxylamine sulfate-Congo red) can be replaced by methyl orange or bromophenol blue, a simple experiment was performed. Schematic diagrams and scanned images of the two sensors are shown in Fig.10a and Fig.10b The two sensors were then evaluated using soy sauce containing aldehyde VOCs. Fig.10c Both sensors showed obvious color changes after being exposed to the soy sauce sample for 30 minutes.

[0191] Example 6 - Exemplary 26-sensor colorimetric sensor array for VOCs analysis

[0192] Fabrication of sensor arrays

[0193] Fig.11a The arrangement of sensors in a 26-element sensor array is shown. Sensor No. 13 contains a redox indicator that changes color when a redox reaction occurs. Sensors No. 14 and 15 are sensitive to phenolic compounds. Sensor No. 19 contains a solvatochromic dye that is particularly sensitive to humidity. Table 7 lists the active chemical components and target VOCs for sensors Nos. 1-26. Table 8 lists the recipes for additional indicator solutions used to make new sensors. Table 7. List of active ingredients in the 26 sensor arrays. Table 8. Recipe of indicator solution used to make new sensors.

[0194] Verification with chemical standards

[0195] To qualitatively demonstrate that the sensor array can react with common VOCs, acetic acid, hexanoic acid, phenylacetaldehyde, furfural, acetone and ethanol were used as VOC standards. The sensor array was exposed to the gas of chemical standards to conduct the experiment. 2 μL of liquid chemical was dropped on the bottom of a 1-liter glass reagent bottle, and then the reagent bottle was covered and the liquid chemical was allowed to evaporate for 30 minutes. Then, the colorimetric sensor array was placed in a chamber to react with the gas. After 30 minutes, the sensor array was taken out and a scanned image was obtained. Figure 11b to Figure 11g The scanned sensor image and the corresponding color difference map are shown.

[0196] The results show that sensors 1-11 and 20-22 can respond to acids, sensors 1-11 can also respond to small molecule aldehydes such as furfural, sensors 23-25 ​​can respond to aldehydes, acids, ketones (especially acetone) and alcohols (especially ethanol), but are more sensitive to aldehydes and acetone, sensor 26 can respond to furfural and phenylacetaldehyde, and sensor 12 can respond to ethanol.

[0197] VOCs Analysis of Roasted Coffee Beans

[0198] Twelve roasted coffee bean samples were tested. Samples A1-A6 were 6 different products containing roasted Arabica coffee beans (as claimed), samples R1-R5 were 5 different products containing roasted Robusta coffee beans (as claimed), and U was a product where the type of beans was not stated.

[0199] For VOCs sensing, 20 g of beans were used for each test. All experiments were performed using a homemade device consisting of a sample chamber (modified from a 100 mL blue-capped reagent bottle), a sensor chamber, a micro vacuum pump, and a power supply. The sensing was repeated 3 times for each sample. The sensing duration was 30 minutes. Figures 12a to 12l Examples of scanned sensor images and average color difference maps of the 12 roasted coffee bean samples are shown.

[0200] The results showed that the sensor array generally responded to VOCs emitted by roasted coffee beans. The six Arabica samples had similar patterns of colored VOC fingerprints, while larger differences could be observed between the five Robusta samples. Therefore, the sensor array can be used for simple aroma analysis of roasted whole coffee beans.

[0201] In-pack monitoring of strawberries

[0202] A 26-unit sensor array was used as an in-pack sensor to monitor the changes in strawberries over a two-day storage period. The strawberry groups were stored under two different conditions, room temperature (RT) and refrigerated at 4°C (F).

[0203] For in-package monitoring, two groups of strawberries were placed in 200 mL disposable plastic containers; the sensor was attached to the inner surface of the lid (facing the strawberries). The container was covered with a lid and sealed with parafilm. Figures 13a to 13f Scanned sensor images (after 2 days in the container) and color difference plots are shown.

[0204] The results showed that the sensor array was generally responsive to VOCs emitted by strawberries during storage. Although differences could be observed between groups stored under the same conditions, the room temperature group generally produced stronger signals in the right panel (i.e., sensors 14-26). These signals indicate that strawberries stored at room temperature have a faster metabolic rate, as a large number of gaseous metabolites (e.g., aldehydes, ketones, alcohols, carbon dioxide, and water vapor) are formed and detected by the sensors. Therefore, the sensor array has the potential to be used as an in-package sensor to monitor the storage conditions of strawberries during post-harvest management.

[0205] At present, the main methods for evaluating the aroma quality of samples are sensory evaluation and gas chromatography. Although the sensory evaluation method can sensitively detect changes in the aroma of samples, it is highly subjective and difficult to give specific chemical compositions of volatile organic compounds (VOCs). Since VOCs only account for a very small part of the total mass of the sample and are rich in variety, detection is difficult and requires reliance on specific detection instruments. In addition, the above methods all have the disadvantages of being time-consuming and having complicated procedures. Therefore, it is challenging to conduct rapid, accurate and simple detection of the aroma of samples.

[0206] The present invention provides a colorimetric sensor array that can visualize the odor of a sample. Through experimental research, the present invention found that not all indicators / dyes are suitable for detecting VOCs in food and beverages. Most common indicators / dyes have problems such as weak response signals and long response times. The colorimetric sensor provided by the present invention can not only respond to VOCs, but also visualize VOCs as specific colorimetric fingerprints. For example, Figure 3 As shown in Figure 11, the difference in the response of the colorimetric sensor of the present invention to different VOCs is very obvious, which is not only reflected in the difference in color intensity displayed by a certain (some) colorimetric sensor, but also in the overall response of the colorimetric sensor array to the VOC. Based on this, when facing food / beverage samples containing complex VOCs, the present invention can visualize the odor of a specific sample into an easy-to-interpret and unique colorimetric fingerprint (see Figures 11 to 13), and the difference in sample odor can be quickly observed by the naked eye, which helps to quickly evaluate the quality of the sample (such as adulteration or imitation, freshness, etc.). In addition, it is also possible to analyze which VOCs in the sample odor have changed by comparing with the established reference. In summary, the present invention can visualize the odor in the sample into a colorimetric fingerprint, which helps to achieve rapid, accurate, simple and low-cost qualitative identification and semi-quantitative analysis of VOCs in the sample.

Claims

1. A colorimetric sensor array for detecting volatile organic compounds (VOCs), comprising: one or more pH-sensitive dyes selected from the group consisting of litmus, bromocresol green or its salts, resazurin or its salts, xylenol orange or its salts, methyl red, bromothymol blue, bromocresol purple, rhodamine, phenol red, and nitrazine yellow; one or more carbonyl-sensitive indicators selected from the group consisting of parafuchsin or parafuchsin base, salts of hydroxylamine, and Schiff's reagent; and One or more solvatochromic dyes selected from the group consisting of Reichardt's dyes, Brooker's merocyanine, chrome azure S, Nile Red, Nile Blue, Acridine Orange, Merocyanine 540, and Disperse Orange 25; wherein each of said indicators or dyes is deposited on a substrate, and wherein said indicators and / or dyes are arranged in a predetermined linear or two-dimensional pattern.

2. The colorimetric sensor array of claim 1, further comprising: The redox indicator indigo carmine, and One or more phenolic compound sensitive indicators selected from the group consisting of ferric chloride and 4-nitrobenzene diazonium tetrafluoroborate.

3. The colorimetric sensor array of claim 1, comprising the following indicators and / or dyes: bromocresol green or its salt, resazurin or its salt, xylenol orange or its salt, methyl red, bromothymol blue, bromocresol purple, Reichardt's dye, Brooker's merocyanine and Schiff's reagent.

4. The colorimetric sensor array of claim 3, further comprising the following indicators and / or dyes: pararubin, litmus, chrome azuroin S, and salts of hydroxylamine.

5. The colorimetric sensor array of claim 4, further comprising the following indicators and / or dyes: Nile Blue, Merocyanine 540, Acridine Orange, Nile Red, Rhodamine B, Nitrazine Yellow, and Phenol Red.

6. The colorimetric sensor array of claim 4, further comprising the following indicators and / or dyes: nitrazine yellow, phenol red, indigo carmine, ferric chloride, 4-nitrobenzene diazonium tetrafluoroborate, Nile red, merocyanine 540, and disperse orange 25.

7. The colorimetric sensor array according to any one of claims 1 to 6, characterized in that The bromocresol green salt is bromocresol green sodium salt, the resazurin salt is resazurin sodium salt, the xylenol orange salt is xylenol orange tetrasodium salt, and / or the hydroxylamine salt is hydroxylamine sulfate.

8. The colorimetric sensor array according to any one of claims 1 to 7, characterized in that Methyl red, bromothymol blue, bromocresol purple, rhodamine, phenol red and / or nitrazine yellow are mixed with a base.

9. The colorimetric sensor array of claim 8, wherein: The base is an inorganic base selected from the group consisting of sodium carbonate (Na2CO3), sodium hydroxide (NaOH) and potassium hydroxide (KOH), or a basic amino acid selected from the group consisting of arginine and histidine.

10. The colorimetric sensor array according to claim 8 or 9, characterized in that Methyl red is mixed with sodium carbonate (Na2CO3), bromothymol blue is mixed with sodium carbonate (Na2CO3), potassium hydroxide (KOH) or arginine, bromocresol purple is mixed with potassium hydroxide (KOH), rhodamine is mixed with arginine, nitrazine yellow is mixed with sodium carbonate (Na2CO3), and / or phenol red is mixed with potassium hydroxide (KOH).

11. The colorimetric sensor array according to any one of claims 1 to 10, characterized in that The salt of hydroxylamine is mixed with a pH-sensitive dye selected from the group consisting of Congo red, methyl orange and bromophenol blue, wherein preferably, the salt of hydroxylamine mixed with the pH-sensitive dye is further mixed with a base, wherein the base is preferably an inorganic base, wherein the inorganic base is preferably sodium carbonate (Na2CO3).

12. The colorimetric sensor array of any one of claims 1 to 11, comprising the following indicators and / or dyes: bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, methyl red mixed with sodium carbonate (Na2CO3), bromothymol blue mixed with sodium carbonate (Na2CO3), bromocresol purple mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine and Schiff's reagent.

13. The colorimetric sensor array of any one of claims 1 to 11, comprising the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, methyl red mixed with sodium carbonate (Na2CO3), bromothymol blue mixed with sodium carbonate (Na2CO3), bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine, chrome azurol S, hydroxylamine sulfate mixed with Congo red, and Schiff's reagent.

14. The colorimetric sensor array of any one of claims 1 to 11, comprising the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, methyl red mixed with sodium carbonate (Na2CO3), bromothymol blue mixed with sodium carbonate (Na2CO3), bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), Reichardt's dye, Brooker's merocyanine, chrome azurol S, hydroxylamine sulfate mixed with Congo red, Schiff's reagent, Nile blue, merocyanine 540, acridine orange, Nile red, rhodamine mixed with arginine, bromothymol blue mixed with arginine, nitrazine yellow mixed with sodium carbonate (Na2CO3) and phenol red mixed with potassium hydroxide (KOH).

15. The colorimetric sensor array of any one of claims 1 to 11, comprising the following indicators and / or dyes: pararubin, litmus, bromocresol green sodium salt, resazurin sodium salt, xylenol orange tetrasodium salt, methyl red mixed with sodium carbonate (Na2CO3), bromothymol blue mixed with sodium carbonate (Na2CO3), bromocresol purple mixed with potassium hydroxide (KOH), bromothymol blue mixed with potassium hydroxide (KOH), bromothymol blue mixed with arginine, nitrazine yellow mixed with sodium carbonate (Na2CO3), phenol red mixed with potassium hydroxide (KOH), indigo carmine, ferric chloride, 4-nitrobenzene diazonium tetrafluoroborate, Nile red, merocyanine 540, disperse orange 25, Reichardt's dye, Brooker's merocyanine, chrome azuro S, hydroxylamine sulfate mixed with Congo red, hydroxylamine sulfate mixed with methyl orange, hydroxylamine sulfate mixed with bromophenol blue, and Schiff's reagent.

16. A system for detecting volatile organic compounds (VOCs) in a sample, comprising: The colorimetric sensor array according to any one of claims 1 to 15, a sensor chamber for housing the colorimetric sensor array, and a sample chamber for containing the sample, Wherein, the sensor chamber is in fluid communication with the sample chamber.

17. The system of claim 16, further comprising a flow facilitator, such as a pump, preferably a vacuum pump, more preferably a micro vacuum pump, wherein the flow facilitator is in fluid communication with the sample chamber and the sensor chamber.

18. The system of claim 16 or 17, further comprising an imaging device or an image sensor selected from the group consisting of a scanner and a camera.

19. A method for detecting and analyzing volatile organic compounds (VOCs) in a sample, comprising the following steps: (i) providing a colorimetric sensor array as claimed in any one of claims 1 to 15 or a system as claimed in any one of claims 16 to 18, (ii) acquiring a first image of the colorimetric sensor array, (iii) providing the sample and exposing the colorimetric sensor array to the sample for a period of time, (iv) acquiring a second image of the colorimetric sensor array, and (v) Analyzing differences between the first image and the second image.

20. The method of claim 19, wherein: Step (v) comprises measuring the RGB (red, green, blue) values ​​of each indicator and / or dye in the colorimetric sensor array in the first image (R1, G1, B1) and the second image (R2, G2, B2), calculating the differences ΔR, ΔG and ΔB, calculating the total Euclidean distance of the change in the RGB values, and analyzing the total Euclidean distance, wherein: ΔR=|R2–R1|, ΔG=|G2–G1|, ΔB=|B2–B1|, 21. A method of detecting adulteration or counterfeiting in a sample, assessing the freshness of a sample, assessing the general quality of a sample, or determining the geographical origin of a sample comprising the method of claim 19 or 20.

22. The method according to claim 21, characterized in that The sample is a crop, oil, liquid seasoning, sauce, paste, extract or beverage.

23. The method according to any one of claims 19 to 22, characterized in that The VOC is selected from the group consisting of acids, aldehydes and polar VOCs, preferably selected from the group consisting of acetic acid, propionic acid, formic acid, butyric acid, valeric acid, hexanoic acid, heptanoic acid, butyraldehyde, valeraldehyde, hexanal, heptaldehyde, furfural, benzaldehyde, formaldehyde, acetaldehyde and acetone.

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