Method of identifying tobacco carbonyl components using non-targeted mass spectrometry

Abstract

A method of identifying tobacco carbonyl components using non-targeted mass spectrometry is disclosed, which includes the following steps: (1) preparing a tobacco sample extract; (2) derivatizing (part of) the sample/extract with 2,4-dinitrophenylhydrazine (DNPH); (3) derivatizing (another part of) the sample/extract with DNPH-d.sub.3; (4) mixing the derivatized tobacco samples; (5) preparing blank samples; (6) performing ultra performance liquid chromatography (UPLC) and ion trap (Orbitrap) high resolution mass spectrometry (HRMS) on the (derivatized) tobacco samples; (7) processing the LC-MS data; (8) filtering the mass spectrometric characteristic data to retain final chromatographic peaks; and (9) structurally annotating or identifying the retained final chromatographic peaks to obtain the tobacco carbonyl components. The method quickly removes noise or interfering components in the original data set by multiple filtering of the mass spectrometry characteristic data, and enables obtaining composition information of aldehyde and ketone chemical components in cigarettes.

Claims

1. A non-targeted mass spectrometry identification method for identifying tobacco carbonyl components, comprising: soaking a tobacco product with water; oscillation extracting a tobacco extract from the tobacco product with acetonitrile; adding 2,4-dinitrophenylhydrazine (DNPH) to a first sample of the tobacco extract and derivatizing the first sample of the tobacco extract with the DNPH to obtain a first derivatized tobacco sample; adding DNPH-d.sub.3 to a second sample of the tobacco extract and derivatizing the second sample of the tobacco extract with the DNPH-d.sub.3 to obtain a second derivatized tobacco sample with an isotope-label; mixing the first derivatized tobacco sample and the second derivatized tobacco sample in a ratio of 1:1 thoroughly, and filtering the first and second derivatized tobacco samples through a filter membrane to obtain a third derivatized tobacco sample; preparing a blank sample by oscillation extracting a water extract from water with acetonitrile, derivatizing a first sample of the water extract with DNPH to obtain a first derivatized water sample, derivatizing a second sample of the water extract with DNPH-d.sub.3 to obtain a second derivatized water sample, mixing the first derivatized water sample and the second derivatized water sample in a ratio of 1:1 thoroughly, and filtering the first and second derivatized water samples through a filter membrane to obtain the blank sample; performing ultra performance liquid chromatography (UPLC) and ion trap high resolution mass spectrometry (HRMS) on the first derivatized tobacco sample, the second derivatized tobacco sample, the third derivatized tobacco sample and the blank sample to obtain original LC-MS data; performing peak detection, peak alignment and peak grouping on the original LC-MS data to obtain original mass spectral feature data of coexisting target components and interfering components, including m/z values, retention times and peak intensities of chromatographic peaks; filtering the original mass spectral feature data based on statistical characteristics, mass loss, paired chromatographic peaks based on DNPH and DNPH-d.sub.3 derivatization markers, and either secondary mass spectrometry or secondary mass spectrometry multiple ion mass spectrum characteristics to obtain final retained chromatographic peaks; and annotating the final retained chromatographic peaks and structurally identifying the tobacco carbonyl components using the final retained chromatographic peaks.

2. The method according to claim 1, wherein filtering the original mass spectral feature data based on statistical characteristics includes: calculating the coefficient of variation (CV) and fold change (FC) according to the formulas CV=IntSQC/IntMQC.sub.1100%, where IntSQC represents a standard deviation of the peak intensity of a first one of the chromatographic peaks in the original LC-MS data for the first tobacco sample, and IntMQC.sub.1 represents an average peak intensity, and FC=IntMQC.sub.2/IntMBK, where IntMQC.sub.2 represents an average peak intensity of the chromatographic peaks in the original LC-MS data for the first tobacco sample, and IntMBK represents an average peak intensity of the chromatographic peaks in the blank sample.

3. The method according to claim 1, wherein filtering the original mass spectral feature data based on the mass loss includes: calculating according to the formula MD=|MZceiling (MZ)|, wherein MZ represents an accurate mass of a precursor ion of a second one of the chromatographic peaks in the original LC-MS data for the first tobacco sample, and ceiling (MZ) is a ceiling number of the accurate mass.

4. The method according to claim 1, wherein filtering the original mass spectral feature data of the paired chromatographic peaks based on one or more DNPH and DNPH-d.sub.3 derivatization markers includes: detecting a pair of chromatographic peaks of the third tobacco sample at a same retention time, then retaining the pair of chromatographic peaks when |MZMZd.sub.3|=3.0186, |IntP1IntP2|/max(P1, P2)<30%, and |RT1RT2|<2, wherein MZ and MZd.sub.3 respectively represent an accurate mass of a precursor ion in the first tobacco sample and an accurate mass of a precursor ion of an isotope d.sub.3-labeled derivatization product in the second tobacco sample, IntP1 and IntP2 represent peak areas of first and second chromatographic peaks, respectively, and RT1 and RT2 represent retention times of the first and second chromatographic peaks, respectively.

5. The method according to claim 1, wherein the original mass spectral feature data are filtered based on secondary mass spectrometry multiple ion mass spectrum characteristics.

6. The method according to claim 1, wherein annotating or structurally identifying the final retained chromatographic peaks includes standard product matching, database searching, or cracking pattern analysis.

7. The method according to claim 1, wherein the ion trap HRMS comprises Orbitrap high resolution mass spectrometry.

8. The method according to claim 5, wherein filtering based on the secondary mass spectrometry multiple ion mass spectrum characteristics includes: when the secondary mass spectrum of the first tobacco sample produces fragment ions of m/z 76.018, m/z 120.008, m/z 122.024, m/z 135.019 and m/z 181.012, retaining the chromatographic peaks corresponding to the fragment ions.

9. The method according to claim 1, wherein filtering the original mass spectral feature data removes the original mass spectral feature data of the interfering components.

10. The method according to claim 9, wherein filtering the original mass spectral feature data further removes noise from the original mass spectral feature data.

11. The method according to claim 1, wherein the tobacco product comprises cut raw tobacco material, and the cut raw tobacco material is soaked in 5 mL of water for each 1 g of the cut raw tobacco material.

12. The method according to claim 1, wherein soaking the tobacco product with water comprises completely infiltrating the tobacco product with the water.

13. The method according to claim 1, wherein the tobacco product is oscillation extracted with 30 mL of the acetonitrile for each 1 g of the tobacco product, and the tobacco extract comprises the tobacco carbonyl components.

14. The method according to claim 1, wherein: derivatizing the first sample of the tobacco extract with the DNPH comprises diluting the first sample of the tobacco extract and DNPH with acetonitrile to form a first derivatization reaction, shaking the first derivatization reaction, and keeping the first derivatization reaction at room temperature for 30 minutes; and derivatizing the second sample of the tobacco extract with the DNPH-d.sub.3 comprises diluting the second sample of the tobacco extract and DNPH-d.sub.3 with acetonitrile to form a second derivatization reaction, shaking the second derivatization reaction, and keeping the second derivatization reaction at room temperature for 30 minutes.

15. The method according to claim 1, wherein the first and second derivatized tobacco samples are filtered through a 0.22 m organic phase filter.

16. The method according to claim 1, wherein the UPLC and the HRMS are performed with an instrument platform comprising an UHPLC system and a mass spectrometer, connected in series.

17. The method according to claim 16, wherein the HRMS is performed using conditions including a spray voltage of 3.7 kV, a sheath gas flow rate of 35 L/min, an auxiliary gas flow rate of 10 L/min, and a transfer tube temperature of 350 C.

18. The method according to claim 1, wherein the HRMS is performed using conditions further including a mass-to-charge ratio scanning range set to 100-1200 m/z, a resolution of 70,000, a mass-to-charge ratio scanning resolution of 35,000, and a high-energy collision-induced dissociation voltage of 30 eV.

19. The method according to claim 2, wherein filtering the original mass spectral feature data based on the statistical characteristics further comprises retaining the first one of the chromatographic peaks when CV30% and FC1.5.

20. The method according to claim 3, wherein filtering the original mass spectral feature data based on the mass loss further comprises retaining the second one of the chromatographic peaks when 0.02MD0.3 and m/z>209.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) FIG. 1 is a graph showing the number of characteristic peaks of the blank sample in Comparative Example 1 below, the number of characteristic peaks after filtering mass spectrometry characteristic data based on statistical characteristics, the number of characteristic peaks after filtering mass spectrometry characteristic data based on mass loss, the number of characteristic peaks after filtering mass spectral characteristic data of paired chromatographic peaks labeled in a derivatization reaction, and the number of characteristic peaks after filtering based on multiple ion mass spectrometry characteristics of secondary mass spectrometry.

(2) FIG. 2 is a graph showing the number of characteristic peaks of the mixed sample of Comparative Example 2 below, the number of characteristic peaks after filtering mass spectrometry characteristic data based on statistical characteristics, the number of characteristic peaks after filtering mass spectrometry characteristic data based on mass loss, the number of characteristic peaks after filtering mass spectral characteristic data of paired chromatographic peaks labeled based on derivatization reaction, and the number of characteristic peaks after filtering based on multiple ion mass spectrometry characteristics of secondary mass spectrometry.

(3) FIG. 3 is a graph showing the recall rate of a mixed standard sample in Comparative Example 2 below, the recall rate after filtering the mass spectrometry feature data based on statistical features, the recall rate after filtering the mass spectrometry feature data based on mass loss, the recall rate after filtering the mass spectra of paired chromatographic peaks based on derivatization reaction markers, and the recall rate after filtering based on multiple ion mass spectrometry features characteristics of secondary mass spectrometry.

(4) FIG. 4 is a graph of the number of characteristic peaks of a tobacco sample taken in accordance with an embodiment of the invention, the number of characteristic peaks after filtering the mass spectrometry characteristic data based on statistical characteristics, the number of characteristic peaks after filtering the mass spectrometry characteristic data based on mass loss, and the number of characteristic peaks after filtering mass spectral characteristic data of paired chromatographic peaks labeled based on derivatization reaction markers, and the number of characteristic peaks after filtering based on the multiple ion mass spectrometry characteristics of secondary mass spectrometry.

DETAILED DESCRIPTION

(5) The present invention will be further described in detail below through specific embodiments, but the scope of the present invention is not limited to the following examples. Without departing from the concept(s) of the present invention, various substitutions and changes made based on common and/or conventional technical knowledge in the art should be included in the scope of the present invention.

(6) Example: Method of identifying tobacco carbonyl components using non-targeted mass spectrometry, comprising the following steps: (1) soaking a tobacco product with water, then adding a certain amount of acetonitrile for oscillation extraction (e.g., extraction by shaking) to obtain a tobacco extract; (2) taking a certain amount of the tobacco extract and adding a certain amount of 2,4-dinitrophenylhydrazine (DNPH) to it for derivatization to obtain a first tobacco sample (CCs-DNPH); (3) repeating Step (2) using DNPH-d.sub.3 to obtain a second tobacco sample (CCs-DNPH-d.sub.3) with an isotope label; (4) mixing the first tobacco sample and the second tobacco sample in a ratio of 1:1 thoroughly, and filtering them through a filter membrane to obtain a third tobacco sample; (5) preparing a blank sample (e.g., containing no tobacco product[s]) according to Steps (1) and (2); (6) performing ultra performance liquid chromatography (UPLC) and ion trap (Orbitrap) high-resolution mass spectrometry (HRMS) on the first tobacco sample, the second tobacco sample, the third tobacco sample and the blank sample to obtain original LC-MS data; (7) performing peak detection, peak alignment and peak grouping on the original LC-MS data to obtain original mass spectral feature data, including m/z value, retention time and peak intensity, of coexisting target components and interfering components; (8) performing multiple filtering on the original mass spectral feature data obtained in Step (7) to obtain final retained chromatographic peaks; (9) annotating or identifying structurally the tobacco carbonyl components from the final retained chromatographic peaks.

(7) Detailed steps include:

(8) Step 1: Cut the raw tobacco material into pieces of about 0.5 cm0.5 cm in area; take 1.0 g of the raw tobacco material (accurate to 0.1 mg), place it in a 100 mL stoppered Erlenmeyer flask, add 5 mL of water, and wait until the sample is completely infiltrated with water. Then add 30 mL of acetonitrile accurately, shake it on an oscillator at 150 r/min for 30 minutes to and extract tobacco components from the raw tobacco material, and obtain a sample extract solution.

(9) Step 2: Accurately transfer 1.0 mL of the tobacco sample extract solution into a 10 mL volumetric flask, add 4 mL of DNPH, dilute to volume (10 ml) with acetonitrile, shake well, and place at room temperature for 30 minutes to derivatize tobacco components in the raw tobacco material and prepare a first tobacco sample (CCs-DNPH).

(10) Step 3: Repeat Step 2 using DNPH-d.sub.3 instead of DNPH to prepare an isotope-labeled second tobacco sample (CCs-DNPH-d.sub.3).

(11) Step 4: In a ratio of 1:1, take 1 mL each of the first tobacco sample (CCs-DNPH) and the second tobacco sample (CCs-DNPH-d.sub.3), mix thoroughly, and filter through a 0.22 m organic phase filter to obtain a third tobacco sample.

(12) Step 5: Prepare a blank sample according to the above Steps 1-4, except that there is no water infiltration step of tobacco raw materials (i.e., the raw tobacco material is omitted in Step 1).

(13) Step 6: Perform UPLC and Orbitrap HRMS on the first tobacco sample, the second tobacco sample, the third tobacco sample and the blank sample to obtain original LC-MS data.

(14) The conditions for UPLC-Orbitrap HRMS analysis include:

(15) UPLC-HRMS is performed with an instrument platform comprising a Dionex U3000 UHPLC system and a Q-Exactive mass spectrometer, connected in series.

(16) UPLC conditions include a Syncronis C18 column (2.1 mm100 mm, 1.7 m), a column temperature of 40 C., an injection volume of 1 L, a first mobile phase (mobile phase A) comprising a 0.1% aqueous solution of formic acid, a second mobile phase (mobile phase B) comprising acetonitrile, and a gradient elution program as follows: minutes 01: 95% mobile phase B, minutes 13: 95%60% mobile phase B, minutes 310: 60%10% mobile phase B, minutes 1018: 10% mobile phase B, minutes 1819: 10%95% mobile phase B, and minutes 1920: 95% mobile phase B, all at a flow rate of 0.2 mL/min;

(17) Mass spectrometry conditions include a spray voltage of 3.7 kV, a sheath gas flow rate of 35 L/min, an auxiliary gas flow rate of 10 L/min, and a DL transfer tube temperature of 350 C. Data collection was performed in the negative ion mode of Full MS-DDA. The mass-to-charge ratio scanning range of the primary mass spectrometer was set to 100-1200 m/z, with a resolution of 70,000. The mass-to-charge ratio scanning resolution of the secondary mass spectrometry was 35,000. The high-energy collision-induced dissociation voltage is 30 eV.

(18) Step 7: Performing peak detection, peak alignment and peak grouping on the original LC-MS data to obtain original mass spectral feature data, which may include coexisting target components and interfering components. The data includes m/z values, retention times and peak intensities.

(19) Step 8: Filtering the original mass spectral feature data obtained in Step (7) multiple times (e.g., according to 2, 3 or more different filtering criteria, such as statistical characteristics, mass loss, paired chromatographic peaks based on derivatization reaction markers, secondary mass spectrometry characteristics, and/or multiple ion mass spectrometry characteristics) to obtain final retained chromatographic peaks.

(20) Filtering mass spectrum feature data based on statistical features may include:

(21) Calculating the coefficient of variation (CV) and fold change (FC) according to the formulas CV=IntSQC/IntMQC.sub.1100%, where IntSQC represents the standard deviation of the peak intensity of a specific chromatographic peak in the first tobacco sample, and IntMQC.sub.1 represents the average peak intensity (e.g., of specific chromatographic peaks in the first tobacco sample), and FC=IntMQC.sub.2/IntMBK, wherein IntMQC.sub.2 represents the average peak intensity of specific chromatographic peaks in the first tobacco sample, and IntMBK represents the average peak intensity of specific chromatographic peaks in the blank sample. In these calculations, IntMQC.sub.1 may equal IntMQC.sub.2.

(22) If CV30% and FC1.5, the corresponding chromatographic peak(s) are retained.

(23) Filtering mass spectrometry characteristic data based on mass loss may include:

(24) Calculating a mass deviation (MD) according to the formula MD=|MZceiling (MZ)|, wherein MZ represents the accurate mass of the precursor ion of or corresponding to a specific chromatographic peak (e.g., corresponding to the precursor ion) in the first tobacco sample (that is, the m/z value), and ceiling (MZ) is the ceiling or rounded-up number of the accurate mass (that is, the nominal mass of the precursor ion corresponding to the specific chromatographic peak).

(25) If 0.02MD0.3, and m/z (MZ)>209, the corresponding chromatographic peak is retained.

(26) Filtering the mass spectrometry characteristic data based on pairs of chromatographic peaks including the derivatization reaction markers includes: detecting a pair of chromatographic peaks in the third tobacco sample at the same retention time, and retaining the corresponding chromatographic peaks when |MZMZd.sub.3|=3.0186, |IntP1IntP2|/max(P1, P2)<30%, and |RT1RT2|<2. MZ and MZd3 respectively represent the accurate mass and/or the m/z value of the precursor ions of (i) a particular non-isotopically labeled tobacco carbonyl component and (ii) the corresponding isotope d.sub.3-labeled derivatization product, IntP1 and IntP2 represent the peak areas of the first and second chromatographic peaks, respectively, and RT1 and RT2 respectively represent the retention times of the first and second chromatographic peaks of the pair of chromatographic peaks.

(27) Filtering based on the secondary mass spectrometry multiple ion mass spectrum characteristics includes retaining the corresponding chromatographic peaks when the secondary mass spectrum of the first tobacco sample produces fragment ions of m/z 76.018, m/z 120.008, m/z 122.024, m/z 135.019 and m/z 181.012.

(28) Step 9: Structurally annotating or identifying the finally retained chromatographic peaks may include standard product matching, database search, and/or cracking pattern analysis.

(29) Steps 7, 8 and 9 above may be performed automatically using one or more software packages. Such software packages may be commercially available (e.g., from Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA).

(30) The present disclosure develops a data processing package (MSFiltering package) based on the R language, which is used to perform peak detection, peak alignment and peak grouping processing on the original LC-MS data to obtain mass spectral characteristics for coexisting target components and interfering components. Based on statistical characteristics, multi-dimensional data filtering methods for mass loss or mass defects, isotope labeling and secondary mass spectrometry multiple ion information, as well as structural annotation or identification of the final retained chromatographic peaks, etc., can achieve efficient identification of aldehyde and ketone components in complex LC-MS data sets through automated processing identification and authentication.

(31) Using an embodiment of the invention, FIG. 4 shows the number of raw characteristic peaks of a tobacco sample, the number of characteristic peaks after filtering the mass spectrometry characteristic data based on statistical characteristics (SCF), the number of characteristic peaks after filtering the mass spectrometry characteristic data based on mass loss or mass defects (MDF), the number of characteristic peaks after filtering based on the paired chromatographic peaks including derivatization reaction markers (PPF), and the number of characteristic peaks after filtering based on the multiple ion mass spectrometry characteristics of secondary mass spectrometry (DFIF).

(32) As can be seen from FIG. 4, the number of original characteristic peaks of the tobacco sample was 12601. After mass spectrometry characteristic data filtering (SCF) based on statistical characteristics, the number of retained chromatographic peaks was reduced to 3452 (a decrease of 72.6%); based on mass loss after mass spectral characteristic data filtering (MDF), the number of retained chromatographic peaks continued to decrease to 975 (a decrease of 92.3%); after mass spectral characteristic data filtering (PPF) based on pairs of chromatographic peaks including derivatization reaction markers, the number of retained chromatographic peaks continued to decrease to 169 (a decrease of 98.6%); and after secondary mass spectrometry multiple ion mass spectrometry characteristic filtering (DFIF), the number of retained chromatographic peaks was reduced to 93 (a decrease of 99.3%). By evaluating their EIC quality, molecular formula prediction, primary and secondary mass spectrometry quality, 70 chromatographic peaks were finally retained, based on standard comparison and literature or database searching, and these were analyzed by comparing retention times, MS and MS/MS data. The retained chromatographic peaks were used for structural identification. For unknowns that did not have standards or known mass spectrum information, Frontier 7.0 (Thermo Fisher Scientific) was used to analyze the mass spectrum fragmentation patterns and annotate their chemical structures. The identification results are shown in Table 1, including molecular formula, secondary mass spectrum, annotation results and other information. Among them, 40 chromatographic peaks had obtained structural annotations, and the corresponding chemical structures of another 20 chromatographic peaks were further inferred. The annotated chromatographic peaks include hydrazones (i.e., the DNPH derivatization reaction products) of aldehydes or ketones such as formaldehyde, acetaldehyde, 2,3-butanedione, pyruvaldehyde, hydroxyacetone, furfural, 5-hydroxymethylfurfural, benzaldehyde, and salicylaldehyde.

(33) The results show that there is a large amount of redundant information in the original LC-MS data. The method of the present invention can efficiently eliminate interference information through multiple mass spectrometry filtering and quickly identify potential aldehyde and ketone chemical components from non-targeted data sets.

(34) Comparative Example 1: The same multiple filtering was performed on the mass spectrometry characteristic data of the blank sample prepared in the above Example, and the results are shown in FIG. 1. As can be seen from FIG. 1, the number of original (raw) characteristic peaks of the blank sample was 7372. After filtering the mass spectrometric feature data based on statistical characteristics (SCF), the number of retained chromatographic peaks was reduced to 641; after filtering the mass spectrometric feature data based on mass loss (MDF), the number of retained chromatographic peaks was reduced to 51; after filtering the mass spectrometric feature data based on pairs of chromatographic peaks including derivatization reaction markers (PPF), the number of retained chromatographic peaks was reduced to 0.

(35) Comparative Example 2: The same multiple filtering was performed on the mass spectral characteristic data of the mixed standard sample prepared according to the above Example. The preparation steps of mixed standard samples are the same as those described above. 24 known aldehydes and 24 known ketones were added to the mixed standard sample. The 24 aldehydes are: formaldehyde, acetaldehyde, acrolein, glyoxal, n-propionaldehyde, crotonaldehyde, malondialdehyde, n-butyraldehyde, valeraldehyde, furfural, glutaraldehyde, hexanal, benzaldehyde, 5-methylfurfural, n-heptaldehyde, phenylacetaldehyde, salicylaldehyde, 1-octanal, trans-cinnamaldehyde, 2,5-dimethylbenzaldehyde, p-methoxy-benzaldehyde, 2,4-nonadienal, 2,4-nonadienal, and decanal; and the 24 ketones are: acetone, cyclopentanone, 2,3-butanedione, 3-methyl-2-cyclopentenone, cyclohexanone, 2-methyltetra-hydrofuran-3-one, 3-hepten-2-one, 4-heptanone, acetophenone, 2,3-heptanedione, isophorone, alpha-ionone, hydroxyacetone (acetol), 2-pentanone, acetoin, 2,3-pentanedione, methylisobutylketone, 2,3-hexanedione, 2-heptanone, acetoxy-2-propanone, 6-methyl-3,5-benzene-2-one, 6-methyl-6-benzene-2-one, 4-methylacetophenone, and 5-nonanone. each known aldehyde and ketone was added in a concentration of 0.1 mg/mL. The results of multiple filtering of the mass spectral characteristic data of the mixed standard sample are shown in FIG. 2. As can be seen from FIG. 2, the number of original (raw) characteristic peaks of the mixed standard sample is 8021. After filtering the mass spectral characteristic data based on statistical characteristics, the number of the retained chromatographic peaks was reduced to 2440; after filtering the mass spectrometric feature data based on mass loss, the number of retained chromatographic peaks was reduced to 377; after filtering the mass spectrometric feature data based on pairs of chromatographic peaks including derivatization reaction markers, the number of retained chromatographic peaks was reduced to 109; after filtering the mass spectrometry characteristic data based on the multiple ion mass spectrometry characteristics of secondary mass spectrometry, the number of retained chromatographic peaks was reduced to 46. By observing the filtered reconstructed TIC, many interfering mass spectrometry signals were eliminated, and the chromatographic peaks of the target have been significantly exposed, while they were not revealed in the original TIC. This sharp reduction in the number of interfering mass spectrometry features very well narrowed the scope of identification of aldehydes and ketones.

(36) The recall rates obtained by filtering the mass spectral features of mixed standard samples using different filtering methods are shown in FIG. 3. As can be seen from FIG. 3, the recall rates of the original data set, statistical feature filtering, and statistical features combined with quality loss filtering are all 100%. The recall rate of statistical features combined with mass loss, paired chromatographic peaks and multiple product ion filtering is greater than 91%, indicating that the added standards can be effectively identified, proving the effectiveness of the multiple filtering method.

(37) TABLE-US-00001 TABLE 1 Identification results of aldehydes and ketones based on UHPLC-Q-Orbitrap-MS/MS No. t.sub.R(min) [M H].sup. AKMass AKFormula MS/MS Identification 1 6.27 329.0740 150.0525 C5H10O5 78.96 (62.9), 96.97 (55.6), unknown 122.02 (18.4), 141.09 (13.7), 152.02 (14), 182.02 (86.2), 209.08 (100), 210.08 (10.2), 225.07 (13.5) 2 6.72 327.0588 148.0369 C5H8O5 59.01 (30.6), 76.02 (11.4), unknown 78.96 (52.1), 96.97 (36.9), 122.02 (28.9), 130.09 (12.9), 137.03 (12.7), 152.02 (28.4), 177.02 (20.2), 182.02 (100), 183.01 (15.1) 3 6.89 269.0537 90.0315 C3H6O3 59.01 (20.7), 65.01 (21.6), Glyceraldehyde 66 (15.9), 78.96 (100), 96.97 (29.7), 106.04 (11.5), 121.03 (11.1), 122.02 (92.1), 125.04 (13.1), 152.02 (24.4), 182.02 (61.9), 185.04 (16.4) 4 6.89 295.0683 116.0471 C5H8O3 61.99 (26), 78.96 (100), unknown 79.96 (17.1), 96.96 (40.1), 96.97 (37.2), 108.02 (12.7), 122.02 (34.3), 137.03 (69.4), 138.02 (29.2), 158.92 (11.4), 167.03 (34.7), 182.02 (38.9), 230.86 (15.4) 5 7.03 280.0692 101.0475 C4H7NO2 76.02 (11.3), 78.96 (48.6), Acetoacetamide 96.97 (19.7), 108.02 (11.8), 122.02 (93), 137.03 (100), 138.02 (18.6), 152.02 (55.3), 167.03 (25) 6 7.17 323.0646 144.0420 C6H8O4 69.03 (10.6), 78.96 (100), Triacetic acid 83.02 (10.5), 96.96 (14.2), 96.97 (67.1), 122.02 (12.7), 125.01 (15.1), 182.02 (61.1), 242.86 (21.3), 323.17 (11.5) 7 7.17 341.0753 162.0525 C6H10O5 78.96 (20.6), 96.97 (16.3), unknown 122.02 (14.2), 152.02 (12.6), 182.02 (100), 340.2 (11.7) 8 7.24 280.0691 101.0475 C4H7NO2 76.02 (13.2), 78.96 (58.9), unknown 96.97 (22.6), 108.02 (12.2), 122.02 (100), 137.03 (99.6), 138.02 (18.9), 152.02 (58.7), 167.03 (24) 9 7.34 269.0537 90.0315 C3H6O3 65.01 (16.5), 66 (11.3), unknown 78.96 (80.7), 96.97 (21.7), 122.02 (100), 152.02 (23.8), 182.02 (62.9), 185.04 (12.8) 10 7.58 311.0637 132.0420 C5H8O4 122.02 (15.7), 182.02 unknown (61.9), 183.01 (100), 311.17 (82.3), 312.17 (14.6) 11 7.65 341.0742 162.0525 C6H10O5 78.96 (14), 96.97 (18.2), unknown 122.02 (11.3), 182.02 (100) 12 7.66 325.0427 146.0213 C5H6O5 122.02 (10.5), 182.02 unknown (78.6), 183.01 (81.9), 325.19 (100), 326.19 (19) 13 8.08 323.0646 144.0420 C6H8O4 78.96 (41.6), 96.97 (25.1), unknown 122.02 (25.5), 152.02 (11.2), 182.02 (100) 14 8.19 281.0532 102.0315 C4H6O3 78.96 (34.1), 96.97 (13.1), Acetoacetic acid 122.02 (56.6), 152.02 (17.6), 182.02 (100) 15 8.24 267.0379 88.0159 C3H4O3 65.01 (19.3), 66 (20.5), Glucosereduc- 76.02 (30.5), 78.96 (60.2), tone isomer 96.96 (22.5), 96.97 (12.6), 120.01 (36.5), 122.02 (40.7), 135.02 (54.9), 151.01 (36.5), 164.01 (33.4), 169.02 (21.9), 181.01 (100), 182.02 (16.5) 16 8.27 253.0583 74.0366 C3H6O2 108.02 (12.3), 122.02 (100), Hydroxyacetone 138.02 (12.3), 152.02 (14.9), 182.02 (10.8) 17 8.27 253.0583 74.0366 C3H6O2 108.02 (12.3), 122.02 (100), Hydroxyacetone 138.02 (12.3), 152.02 isomers (14.9), 182.02 (10.8) 18 8.32 359.0636 180.0420 C9H8O4 78.96 (11), 120.01 (10.1), unknown 122.02 (12.8), 135.02 (11.2), 151.01 (10.7), 181.01 (100), 182.02 (34.3) 19 8.48 249.0633 70.0417 C4H6O 65.01 (23.2), 66 (10.3), Crotonaldehyde 78.96 (100), 79.96 (46.2), isomers 80.97 (25.5), 81.04 (25.2), 96.97 (13.7), 105.02 (13), 132.04 (10.9), 184 (69.6), 184.5 (18.9) 20 8.69 295.0687 116.0471 C5H8O3 78.96 (16), 81.04 (13.3), Cyclotene 122.02 (100), 138.02 (14.8), 152.02 (32.2), 153.03 (11.1), 182.02 (45.5) 21 8.81 305.0534 126.0315 C6H6O3 50 (11.5), 65.01 (17.5), 66 5- (20.6), 76.02 (51.9), 78.96 Hydroxymethyl- (47.8), 96.97 (28.7), 105.02 furfural (16.6), 120.01 (26.7), 122.02 (38.2), 125.01 (11.6), 135.02 (24.2), 151.01 (12.8), 152.02 (10.6), 163.03 (31.9), 164.01 (12.9), 181.01 (42.7), 182.02 (100), 212.05 (19) 22 8.90 267.0736 88.0522 C4H8O2 78.96 (12.7), 108.02 (14.7), acetogamy 122.02 (100), 138.02 (20.6), 152.02 (31.5), 181.01 (10.4), 182.02 (40.7) 23 9.01 537.0978 178.0474 C6H10O6 182.02 (100) Gluconolactone 24 9.08 317.0529 138.0315 C7H6O3 78.96 (12.5), 134.02 (20.8), Gentisate 182.02 (100), 196.89 (21.3) aldehyde 25 9.11 309.0850 130.0627 C6H10O3 78.96 (30.2), 95.06 (12.9), unknown 96.96 (65), 96.97 (11.5), 116.93 (10.1), 122.02 (100), 138.02 (20.7), 152.02 (48.3), 153.03 (14.3), 182.02 (44.5), 309.17 (12.9) 65.01 (61.5), 66 (49), 76.02 (100), 78.96 (99.9), 89.01 26 9.18 209.0312 30.0105 CH2O (24.7), 90.01 (12.2), 91.02 formaldehyde (16.9), 99.92 (21.1), 105.02 (25.7), 120.01 (31.7), 122.02 (15.8), 135.02 (29.3) 121.03 (91.5), 138.02 27 9.28 593.2477 234.1970 H26N8O6 (19.3), 165.02 (14.5), unknown 209.05 (100), 210.05 (10.1) 28 9.46 267.0379 88.0159 C3H4O3 78.96 (14.1), 122.02 (36.6), Glucosereduc- 152.02 (12.4), 182.02 (100) tone 29 9.46 305.0534 126.0315 C6H6O3 65.01 (34.1), 67.02 (11), unknown 69.03 (12.5), 76.02 (71), 78.96 (79.1), 79.96 (17.1), 83.02 (20.7), 96.97 (42.3), 97.03 (15.4), 99.92 (22), 105.02 (19.4), 106.04 (23.3), 116.93 (24.2), 120.01 (36.4), 122.02 (51.4), 125.01 (20), 130.04 (10.4), 135.02 (34.5), 151.01 (13.2), 152.02 (15), 163.03 (46.9), 164.01 (21), 169.02 (12.1), 181.01 (57.1), 182.02 (100), 196.89 (12.8), 212.05 (26.9), 240.04 (14.1) 30 9.48 359.0636 102.0678 C9H8O4 182.02 (100) unknown 31 9.48 281.0893 180.0420 C5H10O2 50 (10.7), 59.01 (29.9), 3-Acetyl-1- 65.01 (45.3), 66 (30.1), propanol 66.01 (12.7), 76.02 (45.6), 78.96 (72.7), 81.04 (12.2), 82.04 (16.3), 83.02 (15.1), 87.04 (16.5), 89.01 (10.3), 91.03 (16), 96.96 (14.4), 96.97 (22.6), 99.92 (22), 105.02 (15), 106.04 (41.7), 116.93 (16.2), 120.01 (30.5), 120.06 (13.7), 122.02 (100), 130.04 (13), 132.06 (13.7), 135.02 (23.8), 151.01 (14.5), 152.02 (71.2), 153.03 (22.8), 157.05 (12.4), 163.03 (32.6), 164.01 (13.4), 171.07 (12.4), 181.01 (76.2) 32 9.52 323.0636 144.0420 C6H8O4 78.96 (18.9), 81.03 (13.5), unknown 122.02 (22), 152.02 (10.3), 182.02 (100) 78.96 (41.8), 96.96 (13.2), 33 9.58 267.0737 88.0522 C4H8O2 108.02 (10.9), 122.02 (100), Acetoin isomers 138.02 (15), 152.02 (31.4), 182.02 (87.6) 34 9.95 223.0472 44.0261 C2H4O 50 (23.2), 58.03 (11.9), Acetaldehyde 59.01 (10.8), 65.01 (36.4), 66 (29.9), 76.02 (65.9), 78.96 (70.8), 89.01 (16.4), 90.01 (10.7), 99.92 (17), 105.02 (12.6), 108.02 (19.4), 120.01 (27.7), 122.02 (100), 130.04 (11.2), 135.02 (20.1), 138.02 (12.8), 151.04 (21.4), 155.04 (11.3) 35 9.98 301.0586 122.0366 C7H6O2 78.96 (35), 118.03 (30.1), Salicylaldehyde 122.02 (12.5), 182.02 (100) 36 9.99 339.0587 160.0369 C6H8O5 116.93 (12.6), 182.02 unknown (31.3), 183.01 (54.8), 339.2 (100), 340.2 (21.1) 37 10.15 265.0583 86.0366 C4H6O2 78.96 (17.2), 96.96 (100) 2,3-butanedione 38 10.17 331.0686 152.0471 C8H8O3 133.02 (13.9), 182.02 (100) Vanillin 78.96 (32.5), 85.03 (12.1), 96.96 (47.3), 96.97 (25.1), 99.92 (11.4), 116.93 (26.3), 39 10.48 381.1063 202.0837 C9H14O5 122.02 (24.6), 127.04 unknown (15.3), 138.02 (15.1), 152.02 (46.5), 163.01 (18.3), 167.01 (19.8), 181.01 (100), 181.99 (11.2), 182.02 (30.1), 204.04 (11.5), 205.02 (13.7), 243.03 (28.2), 381.23 (30.5) 40 10.53 449.2051 270.1840 C16H22N4 122.02 (14.7), 138.02 unknown (14.4), 152.02 (100), 153.03 (30.7), 179.02 (34), 182.02 (10.2) 41 10.59 291.0738 112.0522 C6H8O2 65.01 (20.7), 78.96 (51.4), Cyclotene 96.97 (24.9), 99.92 (16.5), 106.04 (26.7), 116.93 (16.1), 122.02 (99.1), 135.02 (10.6), 152.02 (33), 153.03 (11.6), 181.01 (13.7), 182.02 (100), 196.89 (13.8) 42 10.61 261.0637 82.0417 C5H6O 65.01 (25.3), 66 (15.3), 2-Methylfuran 76.02 (11.2), 78.96 (100), 96.97 (16.4), 99.92 (29.7), 106.04 (11.9), 120.01 (10.4), 122.02 (10.7), 135.02 (23.8), 164.01 (12.2), 179.89 (14.6), 181.01 (25.7) 43 10.62 275.0429 96.0210 C5H4O2 50 (21.4), 65.01 (11.6), 66 Furfural (33.7), 67.02 (26.2), 76.02 (100), 78.96 (52.8), 89.01 (10.8), 95.01 (10.5), 96.97 (43.1), 99.92 (10.4), 105.02 (27), 120.01 (47.3), 122.02 (65.6), 125.01 (20.3), 135.02 (71.9), 146.02 (10.4), 151.01 (32.1), 152.02 (12), 163.02 (30.9), 164.01 (29.5), 169.02 (10.3), 180 (10.5), 181.01 (59.7), 182.02 (77.8) 44 10.71 237.0632 58.0417 C3H6O 50 (12.4), 65.01 (10.6), 66 acetone (14.5), 76.02 (39.5), 78.96 (11.4), 108.02 (11.9), 116.93 (16.3), 120.01 (13.8), 122.02 (100), 135.02 (13.6), 152.02 (13.3) 45 10.84 351.1313 172.1095 C9H16O3 76.02 (18.3), 78.96 (27.9), Butyl levulinate 96.96 (13), 96.97 (29.1), 116.93 (13.1), 122.02 (65.4), 136.03 (12), 138.02 (20.8), 152.02 (100), 153.03 (15.7), 163.03 (38.5), 181.01 (10.4), 182.02 (15.6) 46 10.89 345.0842 164.0834 C9H10O3 182.02 (100), 185.04 (26.4) Homovanillin 47 10.89 343.1052 166.0627 C10H12O2 181.01 (11.8), 182.02 (100) 4-(4- Hydroxyphenyl)- 2-butanone 48 10.90 237.0632 59.0495 C3H8O (11.4), 108.02 (11.9), Propionaldehyde 116.93 (16.3), 120.01 (13.8), 122.02 (100), 135.02 (13.6), 152.02 (13.3) 49 10.97 485.0813 126.0315 C6H6O3 167.01 (11.4), 182.02 (Z). (22.4), 183 (100), 244.05 Tamarindienal? (10.8), 247.05 (10.2) 50 11.12 345.0843 166.0627 C9H10O3 182.02 (100), 185.04 (26.4) Ethylvanillin 51 11.29 447.0656 88.0159 C3H4O3 182.02 (100) Reductone 52 11.41 503.0923 144.0420 C6H8O4 182.02 (100) unknown 53 11.56 329.0536 150.0315 C8H6O3 65.01 (30.9), 66 (46.2), 1,4-Benzodioxin- 66.01 (12.9), 76.02 (100), 2(3H)-one 78.96 (52.6), 82.04 (12), 83.02 (17.4), 89.01 (12), 91.02 (34.5), 96.97 (38.4), 99.08 (14.2), 99.92 (26.6), 105.02 (23.5), 106.04 (40.7), 108.02 (13), 109.03 (39.3), 116.93 (32.4), 118.03 (12.7), 120.01 (50.1), 121.03 (14.6), 122.02 (44.1), 127.11 (13.1), 129.09 (15), 135.02 (25.5), 151.01 (17.5), 152.02 (13.6), 163.03 (96.1), 164.01 (16.5), 165.02 (20.2), 169.02 (16), 171.1 (10.3), 181.01 (95.9), 182.02 (60.1), 199.13 (31.1), 201.11 (29.1), 224.06 (17.4), 253.05 (22.9), 254.06 (17.8), 328.18 (12.1), 329.23 (30.4) 54 11.62 253.0220 74.0003 C2H2O3 65.01 (33.3), 66 (20.5), Glyoxylic acid 66.01 (10.2), 76.02 (12.9), 78.96 (100), 91.03 (11.8), 96.96 (24.9), 96.97 (22.6), 106.04 (18.1), 120.01 (15.5), 122.02 (38.2), 125.04 (21.6), 135.02 (24.2), 138.02 (10.8), 152.02 (10.3), 156.06 (10.9), 164.01 (11.4), 181.01 (26.4), 182.02 (40.2), 183 (21.5), 235.08 (11.1) 55 11.66 251.0788 72.0573 C4H8O 65.01 (25.9), 66 (14.6), Butyraldehyde 76.02 (28.6), 78.96 (13.2), 106.04 (35.1), 120.01 (13.6), 122.02 (100), 135.02 (13.3), 152.02 (49.4) 56 11.77 417.0564 58.0054 C2H2O2 182.02 (100), 122.0236 Glyoxal (8.3), 76.0179 (3.1) 57 11.80 501.0777 142.0264 C6H6O4 182.02 (100), 167.0090 Dicarbonyls (9.1), 122.0236 (2.8) 58 11.85 315.0741 136.0522 C8H8O2 66 (13.1), 76.02 (35), 78.96 p-Methoxybenz- (50.6), 96.97 (100), 105.02 aldehyde (10.4), 118.03 (15.5), 120.01 (19.1), 121.03 (33.2), 122.02 (20.4), 135.02 (13), 163.03 (25.7), 181.01 (30.1), 182.02 (20.2), 196.89 (21.9), 253.05 (39.3), 300.05 (10.1) 59 11.87 285.0633 106.0417 C7H6O 50 (21.4), 65.01 (20.6), 66 Benzaldehyde (38.4), 76.02 (100), 78.96 (51.5), 82.04 (10.9), 96.97 (14.1), 105.02 (23.3), 106.04 (15.9), 118.03 (14.4), 120.01 (47.5), 121.03 (11.2), 122.02 (48.6), 125.01 (11.4), 135.02 (43.1), 151.01 (29.2), 163.03 (45.3), 164.01 (24.2), 166.04 (22.6), 169.02 (10.5), 181.01 (65.5), 182.02 (35.7), 186.87 (10.7), 208.06 (31.4), 238.06 (11.8) 60 12.07 475.0984 116.0471 C5H8O3 182.02 122.0235 (3.2) Ethyl pyruvate (1.7), (100), 163.0252 122.02 (20.5), 138.02 61 12.40 387.1688 208.1458 C13H20O2 (17.8), 152.02 (100), 168.02 Theaspirone A (10.6), 272.1 (12.1), 342.15 (55.4), 343.15 (10.7) 62 12.44 431.0717 72.0210 C3H4O2 182.02 152.0218 malondialdehyde (3.5), 122.0236 (3.1) 63 12.49 331.0507 152.0318 C4H8O6 65.01 (45.2), 66 (29), 66.01 unknown (33.7), 76.02 (60.4), 78.96 (63), 82.04 (18.7), 83.02 (16.4), 89.01 (11.1), 90.01 (10.1), 91.03 (10.9), 92.02 (13.5), 92.93 (20.8), 94.92 (11.6), 96.97 (51.1), 99.92 (15.2), 105.02 (13.8), 106.04 (100), 107.03 (13.9), 109.01 (11.2), 116.93 (23.2), 118.04 (13.4), 120.01 (26.2), 120.06 (11.5), 121.05 (12.1), 122.02 (32.6), 123.03 (16.3), 124 (10.7), 130.04 (19.1), 131.04 (10.2), 132.06 (12.3), 135.02 (15.2), 137.01 (31.2), 145.05 (12.3), 152.02 (11.2), 157.05 (13.5), 158.92 (12), 160.84 (17.4), 163.03 (47.1), 167.02 (23.5), 171.07 (10.6), 181.01 (38.2), 182.02 (27.8), 196.06 (10.2), 269.03 (67.3) 64 12.75 277.0940 98.0729 C6H10O 106.0399 (100), 65.0132 cyclohexanone (69.4), 122.0236 (67.2), 181.0121 (42.7), 182.0205 (18.9), 76.0179 (40.2) 65 12.90 683.1214 324.0719 C13H8N8O3 167.03 (12.7), 179.02 Tricarbonyl (13.1), 182.02 (100), 197.03 (18.4) 66 13.04 279.1099 100.0885 C6H12O 106.0938 (100), 65.0132 Hexanal (50.1), 122.0236 (26.7), 148.0619 (31.4) 67 13.12 445.0878 86.0366 C4H6O2 182.02 (100) Butyraldehyde 68 13.14 313.0944 134.0729 C9H10O 50 (13.3), 65.01 (14.2), 66 4-methylaceto- (23.7), 76.02 (82.1), 78.96 phenone (32.7), 82.04 (10.7), 96.97 (43.9), 105.02 (17.9), 106.04 (11.5), 120.01 (35.7), 122.02 (33.1), 135.02 (35.7), 151.01 (36.2), 163.03 (47), 164.01 (24.5), 169.02 (10.9), 181.01 (100), 182.02 (37.2), 183.01 (20.9), 184.01 (23.9), 185.01 (13.4), 236.1 (22.2), 266.09 (15.3), 312.17 (33.7) 69 13.60 459.1025 100.0522 C5H8O2 182.02 (100) glutaraldehyde 70 14.32 405.1780 226.1563 C13H22O3 122.02 (12.6), 152.02 (100) Methyl dihydrojasmonate

(38) The embodiments are preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.