Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2020 Jan 7;15(1):e0227235. doi: 10.1371/journal.pone.0227235

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

Xindan Liu 1, Ying Zhang 1, Menghua Wu 1, Zhiguo Ma 1, Hui Cao 1,*
Editor: Joseph Banoub2
PMCID: PMC6946158  PMID: 31910241

Abstract

Schizonepetae Spica (SS), the dried spike of Schizonepeta tenuifolia Briq., is a traditional Chinese medicinal herb. According to the color of persistent calyx, SS is categorized into two classes: the yellowish-green-type and the brownish-type. Based on the chemometrics analysis of gas chromatography-mass spectrometry (GC-MS), a novel model of identifying and evaluating the quality of SS in different colors was constructed for the first time in this work. 20 batches SS samples of different colors were collected and used to extract essential oils. The average essential oils yield of SS in yellowish-green color was significantly higher than that of SS in brownish color from the same origin (p<0.05). The GC-MS fingerprints of 20 batches SS samples whose correlation coefficients were over 0.964 demonstrated SS samples were consistent to some extent in spite of slightly different chemical indexes. A total of 39 common volatiles compounds were identified. Hierarchical clustering analysis (HCA), principal component analysis (PCA) and partial least-squares discriminate analysis (PLS-DA) were developed to distinguish SS samples characterized by different colors. Consistent results were obtained to show that SS samples could be successfully grouped according to their color. Finally, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were detected as the key variables for discriminating SS samples of different colors and for quality control. The obtained results proved that SS of good quality were often yellowish-green and those of poor quality were often brownish.

Introduction

Color discrimination is an important aspect for the macroscopic identification of Chinese medicinal material (CMM).[1] Some ancient Chinese medicine literature, such as Ben Cao Yuan Shi (Origins of the Materia Medica), emphasize the importance of color as an identifier of high quality medicinal herbs. Modern pharmacologic studies have proven that colors of some CMMs often have a large influence on the quality and quantity of the chemicals in medicinal herbs. For example, Salvia miltiorrhiza Bge. root (dan seng) in deep reddish-purple color is considered to be superior in quality, and modern experimental studies have demonstrated the deep reddish-purple color is indeed correlated with higher salvianolic acid B and tanshinones content.[2] Aucklandia lappa Decne. root (mu xiang) in blue-green color is thought to be superior, in yellowish-white color be mid-grade, and in black color be inferior in terms of quality.[3] In these cases, however, the correlation between color and chemical components is not well studied.

Schizonepetae Spica (SS, jing jie sui) is the dried spike of Schizonepeta tenuifolia Briq. (Chinese Pharmacopoeia, 2015 edition).[4] It was first recorded in Shen Nong Ben Cao Jing (Shen Nong’s herbal classic), a book written 2000 years ago. SS is commonly used in traditional Chinese medicine (TCM) prescriptions to treat colds, allergic dermatitis, eczema and psoriasis.[5] Apart from a wide range of applications in traditional and modern medicine, it also has culinary applications of S. tenuifolia as ingredients in several food recipes, beneficial drinks and herbal tea.[6] Chemical studies revealed that SS contained volatile oils, flavonoids, organic acids, etc.[7–9] Research into pharmacological activities of the oils accumulated by SS possesses anti-inflammatory,[10] antioxidant,[11] analgesia,[12] antineoplastic[13, 14] and antiviral[15, 16] properties. Thus, the volatile components could be selected as marker compounds for quality evaluation of SS. One of the major pharmacological components in SS is pulegone, which is also quality control marker in the Chinese pharmacopoeia (2015 edition).[4] In China, SS is widely grown in Hebei province, Jiangsu province, Jiangxi province and many other regions. In the Chinese pharmacopoeia (2015 edition),[4] the departmental handbook “Dictionary of Chinese Traditional Medicine”[17] and “Dictionary of Chinese Medicine Processing”,[18] SS is divided into two varieties according to the color of persistent calyx: the yellowish-green-type and the brownish-type.

Chromatographic fingerprinting is a unique pattern that indicates the presence of multiple biomarkers in a complex chemical system. The chromatographic fingerprint analysis could serve as a comprehensive approach for quality control of medicinal herbals and food products.[19] However, the minor differences between similar chromatograms generated by samples may not be readily detected. Multivariate statistical analyses, such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least-squares discriminate analysis (PLS-DA) have been proposed as proper tools to solve chromatographic problems and extract maximum useful information from the chromatographic fingerprinting.[20, 21]

In previous studies, gas chromatography-mass spectrometry (GC-MS) combined with chemometrics methods had been used to distinguish SS from different regions.[22, 23] However, few studies have done to analyze the correlation between the color and chemical composition in SS. Therefore, the investigation into the chemical difference of SS in different colors could be developed as an important approach to evaluate the quality of SS. In the present study, the volatile components of SS samples were acquired by GC-MS. Since SS samples in different colors may differ significantly, depending on a number of factors—such as plant cultivars, harvest time, processing, storage conditions and many other factors. The obtained information was then analyzed by multivariate methods including HCA, PCA and PLS-DA to find similarity among SS samples and to evaluate discriminating variables (biomarkers).

Material and methods

Materials and reagents

20 batches sample of medicinal herbals were purchased from various sources of China (Table 1), and their identities were confirmed as SS by Dr. Ying Zhang, Jinan University, PR China. Voucher specimens were deposited at the Research Center for Traditional Chinese Medicine of Lingnan, Jinan University.

Table 1. The details of the 20 batches Schizonepetae Spica samples and fingerprint similarities.

No. Voucher specimens R G B Calyx color Collection place Date of collection Similarities
1 YP132581301 90.72 74.52 40.40 Brownish Henan province November 29, 2018 0.978
2 YP132581401 81.27 62.55 31.23 Brownish Henan province January 17, 2019 0.964
3 YP132581501 92.32 98.24 45.06 Yellowish-green Guangdong province January 8, 2019 0.996
4 YP132581601 83.33 92.22 45.67 Yellowish-green Hubei province January 9, 2019 0.996
5 YP132581701 96.10 100.26 46.23 Yellowish-green Hubei province January 10, 2019 0.987
6 YP132581801 87.09 72.65 37.53 Brownish Shanxi province January 9, 2019 0.988
7 YP132581901 86.25 99.15 51.51 Yellowish-green Shanxi province January 12, 2019 0.994
8 YP132582001 81.02 92.38 45.57 Yellowish-green Anhui province January 10, 2019 0.994
9 YP132582101 81.51 68.26 38.24 Brownish Anhui province January 19, 2019 0.999
10 YP132580101 80.62 71.34 45.02 Brownish Hebei province June 7, 2018 0.986
11 YP132582201 80.59 95.29 39.18 Yellowish-green Jiangsu province January 10, 2019 0.997
12 YP132582301 97.19 105.54 52.24 Yellowish-green Hebei province January 9, 2019 0.996
13 YP132582401 85.38 98.34 43.10 Yellowish-green Hebei province January 13, 2019 0.998
14 YP132582501 86.35 97.09 40.83 Yellowish-green Zhejiang province January 10, 2019 0.999
15 YP132580701 82.43 68.02 40.78 Brownish Henan province January 10, 2019 0.989
16 YP132582601 91.48 101.2 53.97 Yellowish-green Jiangsu province January 11, 2019 0.994
17 YP132582701 80.12 74.90 41.14 Brownish Jiangsu province January 11, 2019 0.989
18 YP132582801 87.14 95.70 42.88 Yellowish-green Guangxi province January 11, 2019 0.998
19 YP132582901 92.76 101.42 48.61 Yellowish-green Jiangxi province January 11, 2019 0.987
20 YP132583001 84.17 70.81 44.45 Brownish Jiangxi province January 12, 2019 0.992
Open in a new tab

R = red; G = green; B = blue.

All solvents used in the experiments were of analytical grade. Ethyl acetate was purchased from Aladdin (Aladdin, Shanghai, China). n-Alkane (purity > 97%) which used as an internal quality standard for GC-MS analysis was purchased from o2si (Charleston, SC, USA).

Discrimination the color of Schizonepetae Spica calyx

Images were acquired using a digital camera (PowerShot G7 X Mark II, Canon Inc., Nagasaki, Japan) as shown in Fig 1. The red-green-blue (RGB) values were extracted from the images of samples using Photoshop CS6 (Adobe Systems Inc., USA) software (Table 1). The surface color of the Schizonepetae Spica calyx was selected to extract RGB values. And then the obtained RGB values were transformed into the CIE 1931XYZ color space, where the values can be normalized and plotted in a 2-dimensional CIE1931XYZ chromaticity diagram to identify the color of SS calyx as described by Wang et al.[24] According to the distribution of the SS samples in the CIE 1931XYZ chromaticity diagram (Fig 2), the yellowish-green-type consisted of samples 3, 4, 5, 7, 8, 11, 12, 13, 14, 16, 18 and 19; and the brownish-type contained samples 1, 2, 6, 9, 10, 15, 17 and 20 (Table 1).

Fig 1. Representative images of Schizonepetae Spica samples.

Fig 1

Open in a new tab

Fig 2. The distribution of the Schizonepetae Spica samples in the CIE 1931XYZ chromaticity diagram.

Fig 2

Open in a new tab

The samples mainly distribute among the upper left region favoring yellowish-green; the samples distribute among the lower right tending to brownish.

Essential oils extraction

Steam distillation method was chosen according to the Chinese Pharmacopoeia (2015 edition) for extraction of essential oils.[4] All samples were smashed and filtered through a 24 mesh sieve. Then the dried powder (50 g) was weighted and placed in a 1000 mL flask. 300 mL redistilled water was also placed in this 1000 mL flask. The essential oils were extracted by water distillation for 4 h. At last, essential oils were separated from the water layer, and then oil layer was dried over anhydrous sodium sulfate. The extraction yield was calculated in a milliliter of essential oils per 100 g of SS. The anhydrous essential oils were stored in the dark glass vial at -20°C. 50 mg of the essential oils sample were accurately weighted and transferred into a 5 mL volumetric flask, and make up to volume with ethyl acetate for GC-MS analysis.

GC-MS analysis

Volatile compounds were analyzed on an Agilent 7890B GC system coupled to an Agilent 7000C GC/MS Triple Quad mass spectrometer (Agilent, Santa Clara, CA, USA). Initial chromatographic separations of 1 μL samples were on a 15 m × 250 μm i.d. × 0.25 μm film thickness HP-5 (Agilent) capillary column with a He flow rate of 1.0 mL/min and an injection port temperature of 250°C with the split ratio of 1:10. The oven temperature ramp was 3 min at 50°C, then 10°C/min to 90°C, where the temperature was held for 5 min, then ramped at 10°C/min to 160°C, where it was maintained for 10 min, then a 20°C/min ramp to 260°C, where the temperature was held for 3 min. The detector was operated at 70 eV ionization energy, and the m/z values were recorded in range of 50–600 amu with a scan rate of 3.6 scan/s and a solvent delay of 3 min. Components were identified using the National Institute of Standards and Technology (NIST) 2.2L Mass Spectra Database containing about 189,000 compounds, as well as comparing with the literatures.[22, 25–27]

Data analysis

The GC-MS fingerprint was performed by professional software Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004 A) composed by the Chinese Pharmacopoeia Committee. HCA was performed by SPSS version 20.0 software (SPSS, Chicago, USA) based on Ward’s method and the squared Euclidean distance. PCA and PLS-DA were performed by SIMCA-P version 11.5 software (Umetrics, Umea, Sweden). The loading plot from PLS-DA was employed to find chemical markers for discriminating the samples in different colors.[21, 28] Statistical significance was assessed by ANOVA test with GraphPad Prism v.5.0 software. P-values < 0.05 were considered to be statistically significant, and p-values < 0.01 were considered to be statistically highly significant.

Results and discussion

Yield of essential oils from Schizonepetae Spica of different colors

The essential oils from SS samples were extracted by hydrodistillation, and the distilled essential oils gave clear yellow wax oils in yields ranging from 0.47% to 1.65% mL/g (Fig 3). In this study, we acquired different colors of the SS, including the yellowish-green-type and the brownish-type. The yellowish-green color of SS corresponded to a relatively higher concentration of volatiles (~ 0.69%-1.65% mL/g), while SS in brownish color was correlated with relatively lower volatiles concentration (~ 0.47%-0.85% mL/g). Interestingly, significant differences in essential oils yield were detected between the yellowish-green-type and the brownish-type of SS from the same geographic origin (Fig 3), which indicated a relationship between the color of the herb and its volatiles concentration.

Fig 3. Yield of essential oils from Schizonepetae Spica of different colors.

Fig 3

Open in a new tab

Data are presented as the mean ± SD (n = 2). *p<0.05, **p<0.01 vs. SS samples in brownish color from the same origin. DW = dry weight.

Validation of methodology

The precision and repeatability of the method was determined by performing six injections of sample solution and six replicates of the same sample (No. 12), respectively (Table 1). The results showed that precision of relative retention times and relative peak areas of volatile constituents were found in the range of 0.00%-0.03% and 0.00%-3.12% of relative standard deviation values (RSDs). The method repeatability of relative retention times and relative peak areas of volatile constituents were lower than 0.10% and 5.20% of RSDs, respectively. The method stability was determined at 0, 2, 4, 8, 12 and 24 h by using the same sample (No. 12). The RSDs of relative retention time and relative peak areas of volatile constituents were less than 0.08% and 5.50%, respectively. All the results indicated that the developed conditions for the GC-MS fingerprint analysis of SS were satisfactory.

GC-MS fingerprint of essential oils from Schizonepetae Spica

The chromatograms of the SS samples (20 batches) were shown in Fig 4. The correlation coefficient of similarity between each chromatographic profile of SS and the reference chromatogram, the representative standard fingerprint/chromatogram for a group of chromatograms, were calculated (Table 1). The correlation coefficients of the 20 SS samples were more than 0.964, which were in agreement with previous studies.[29, 30] These results demonstrated that the chromatographic fingerprints of SS from different geographic origins were consistent to some extent in spite of slightly different chemical composition. Correlation coefficient of each chromatogram for 12 batches SS in yellowish-green color was found to be 0.987–0.999, while those of the 8 batches SS in brownish color were below 0.990 except No. 9 (0.999) and No. 20 (0.992) (Table 1). Slight difference in correlation coefficients demonstrated different internal qualities. Some samples characterized by the brownish color exhibited relatively high correlation coefficient could not be discriminated by their color using the correlation coefficients. Thus, because of the limitation of GC-MS fingerprint analysis for detecting minor differences in samples of different colors, pattern recognition analysis for quality control of SS was employed.

Fig 4. GC-MS fingerprints of 20 batches of Schizonepetae Spica samples and reference chromatogram (R).

Fig 4

Open in a new tab

Identification of volatile components from Schizonepetae Spica

A total of 39 common compounds were identified in SS samples of different colors, which amounted for about 89% of the total essential oils (Table 2). Among these identified volatiles, monoterpenoids especially pulegone and L-menthone were the major compounds in 20 batches SS samples, a result which was consistent with the findings of recent studies.[22, 25, 26] However, 39 compounds in SS of different colors showed differences in relative contents. The relative content of pulegone, caryophyllene and germacrene D were relatively higher in the yellowish-green-type samples than in the brownish-type samples; whereas another four main components L-menthone, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran, caryophyllene oxide and (Z,Z,Z)-9,12,15-octadecatrienoic acid had a higher content in the brownish-type samples. The volatile components of SS have been recognized as the major constituents responsible for its biological effects. For example, pulegone, which is known for its pleasant odor, analgesia, anti-inflammatory and antiviral properties,[12, 31] is the chemical indicator in the Chinese Pharmacopoeia (2015 edition) of SS.[4] L-menthone also presents analgesia and antiviral effects.[31] Caryophyllene is a functional cannabinoid receptor (type 2) agonist.[32] 4,5,6,7-Tetrahydro-3,6-dimethyl-benzofuran is widely used as flavorings and fragrances.[33] In short, the differences among these variables may lead the difference in quality of SS samples characterized by different colors.

Table 2. Thirty-nine common compounds and their relative contents of Schizonepetae Spica in different colors.

No. Compound Molecule formula RI CAS Relative content (%)
Samples in yellowish-green color (n = 12) Samples in brownish color (n = 8)
V1 (R)-3-Methyl-cyclohexanone C7H12O 953.74 13368-65-5 0.08 ± 0.02 0.14 ± 0.05
V2 1-Octen-3-ol C8H16O 983.39 3391-86-4 0.17 ± 0.03 0.17 ± 0.08
V3 1,3,8-p-Menthatriene C10H14 1005.59 18368-95-1 0.04 ± 0.01 0.04 ± 0.02
V4 E,E-2,6-Dimethyl-1,3,5,7-octatetraene C10H14 1023.77 460-01-5 0.07 ± 0.02 0.07 ± 0.04
V5 D-Limonene C10H16 1027.61 5989-27-5 0.41 ± 0.33 0.23 ± 0.12
V6 Benzeneacetaldehyde C8H8O 1043.37 122-78-1 0.11 ± 0.05 0.09 ± 0.03
V7 2-Ethenyl-1,4-dimethyl-benzene C10H12 1089.74 2039-89-6 0.08 ± 0.03 0.05 ± 0.02
V8 Linalool C10H18O 1100.42 78-70-6 0.10 ± 0.02 0.10 ± 0.02
V9 trans-1-Methyl-4-(1-methylethenyl)-2-cyclohexen-1-ol C10H16O 1118.90 7212-40-0 0.76 ± 0.08 0.99 ± 0.19
V10 cis-p-Mentha-2,8-dien-1-ol C10H16O 1133.26 3886-78-0 0.71 ± 0.08 0.87 ± 0.17
V11 L-Menthone C10H18O 1151.53 14073-97-3 9.51 ± 3.72 16.95 ± 3.03
V12 4,5,6,7-Tetrahydro-3,6-dimethyl-benzofuran C10H14O 1160.88 494-90-6 1.35 ± 0.41 4.93 ± 1.34
V13 trans-5-Methyl-2-(1-methylethenyl)-cyclohexanone C10H16O 1173.08 29606-79-9 2.63 ± 0.42 3.26 ± 0.63
V14 (-)-cis-Isopiperitenol C10H16O 1202.38 96555-02-1 0.62 ± 0.18 0.94 ± 0.22
V15 2-Allyl-4-methylphenol C10H12O 1233.11 6628-06-4 0.70 ± 0.12 1.49 ± 0.44
V16 Pulegone C10H16O 1253.74 89-82-7 67.51 ± 3.44 49.34 ± 5.22
V17 3-Methyl-6-(1-methylethyl)-2-cyclohexen-1-one C10H16O 1261.45 89-81-6 0.26 ± 0.16 0.49 ± 0.09
V18 5-Formylmethyl-6-hydroxy-3,3-dimethyl-6-vinyl-bicyclo[3.2.0]heptan-2-one C13H18O3 1290.48 1000156-78-3 0.24 ± 0.03 0.57 ± 0.25
V19 (1S,3S,5S)-1-Isopropyl-4-methylenebicyclo[3.1.0]hexan-3-yl acetate C12H18O2 1294.44 139757-62-3 0.19 ± 0.02 0.19 ± 0.03
V20 Carveol C10H16O 1314.62 99-48-9 0.11 ± 0.02 0.14 ± 0.04
V21 2-Methyl-5-(1-methylethenyl)-2-cyclohexen-1-ol acetate C12H18O2 1335.28 97-42-7 0.12 ± 0.05 0.07 ± 0.02
V22 3-Methyl-6-(1-methylethylidene)-2-cyclohexen-1-one C10H14O 1344.05 491-09-8 3.44 ± 0.47 2.90 ± 0.54
V23 α-Copaene C15H24 1378.56 1000360-33-0 0.13 ± 0.03 0.07 ± 0.02
V24 (-)-β-Bourbonene C15H24 1386.74 5208-59-3 0.14 ± 0.04 0.11 ± 0.03
V25 1-Ethenyl-1-methyl-2,4-bis(1-methylethenyl)-cyclohexane C15H24 1393.37 515-13-9 0.11 ± 0.02 0.04 ± 0.01
V26 (Z)- 3-Methyl-2-(2-pentenyl)- 2-cyclopenten-1-one C11H16O 1399.03 488-10-8 0.07 ± 0.01 0.07 ± 0.02
V27 2-(2-Butenyl)-4-hydroxy-3-methyl-2-cyclopenten-1-one C10H14O2 1401.35 17190-74-8 0.29 ± 0.13 0.50 ± 0.18
V28 Caryophyllene C15H24 1422.16 87-44-5 1.84 ± 0.34 0.54 ± 0.40
V29 Humulene C15H24 1458.11 6753-98-6 0.21 ± 0.05 0.06 ± 0.04
V30 Germacrene D C15H24 1485.14 23986-74-5 1.21 ± 0.26 0.28 ± 0.25
V31 1,2,3,5,6,8a-Hexahydro-4,7-dimethyl-1-(1-methylethyl)-naphthalene C15H24 1524.78 483-76-1 0.15 ± 0.03 0.09 ± 0.06
V32 (-)-Spathulenol C15H24O 1581.27 77171-55-2 0.13 ± 0.04 0.14 ± 0.05
V33 Caryophyllene oxide C15H24O 1586.74 1139-30-6 0.42 ± 0.19 1.28 ± 0.61
V34 (1R,3E,7E,11R)-1,5,5,8-Tetramethyl-12-oxabicyclo[9.1.0]dodeca-3,7-diene C15H24O 1612.71 19888-34-7 0.03 ± 0.02 0.09 ± 0.05
V35 (1R,7S,E)-7-Isopropyl-4,10-dimethylenecyclodec-5-enol C15H24O 1690.12 81968-62-9 0.05 ± 0.02 0.02 ± 0.01
V36 6,10,14-Trimethyl-2-pentadecanone C18H36O 1842.16 502-69-2 0.06 ± 0.02 0.04 ± 0.02
V37 (Z,Z,Z)-9,12,15-Octadecatrienoic acid, methyl ester C19H32O2 2100.00 301-00-8 0.06 ± 0.03 0.12 ± 0.06
V38 (Z,Z,Z)-9,12,15-Octadecatrienoic acid C18H30O2 2149.50 463-40-1 1.30 ± 1.52 4.76 ± 1.96
V39 2,2'-Methylenebis[6-(1,1-dimethylethyl)-4-methyl-phenol C23H32O2 2429.11 119-47-1 0.11 ± 0.02 0.09 ± 0.01
Open in a new tab

Relative content (%) in the last two columns represents the mean ± SD. RI, retention index. CAS, Chemical Abstracts Service.

Hierarchical clustering analysis

Based on the results of above GC-MS fingerprint analyses, 39 common volatile components in 20 batches SS samples were used to conduct HCA. The dendrogram showed that 20 batches SS samples could be divided into two groups (Fig 5): cluster Ⅰ belonged to the brownish-type, while cluster Ⅱ belonged to the yellowish-green-type except No. 9. Therefore, herbal color could be an important influencing factor for the content of volatile components in SS. The pattern distribution of No. 9 suggested that the plant cultivar, harvesting time, processing methods, storage condition or other poorly controlled aspects may influence sample quality and sample classification.[34, 35] Generally, samples in the same color were still clustered, which indicated that the internal quality of these samples was quite similar to each other.

Fig 5. Dendrogram obtained from hierarchical clustering analysis of 39 common volatile components of 20 batches Schizonepetae Spica samples in different colors.

Fig 5

Open in a new tab

Principal component analysis

To further investigate the quality variation and differentiate the color of SS samples, PCA was performed based on the GC-MS data of 39 common compounds. The PCA (R2X = 0.885, Q2 = 0.602) scores plot showed that the 20 batches samples were obviously separated from two groups according to the different calyx color of SS (Fig 6), which yielded the same result as HCA. The first two PCs explained 63.08% of data variance (PC1 = 41.53% and PC2 = 21.55%). Of which, “PC1” played a significant role in discriminating samples of different colors. It should be pointed out that the samples belonged to one color were acquired from different collecting sites (Table 1). Therefore, it is acceptable that these samples do not have same chromatographic profiles and so were assigned to corresponding classes with an unsupervised PCA.

Fig 6. PCA scores plot for volatile oils in Schizonepetae Spica by GC-MS.

Fig 6

Open in a new tab

Partial least-squares discriminate analysis

Subsequently, a supervised PLS-DA was adopted to find out the specific variation between the yellowish-green-type and the brownish-type of SS. In this model, the parameters for the classification from SIMCA-P 11.5 software were R2Y = 0.905 and Q2 = 0.808, which were stable and good to fitness and prediction, respectively. The score plot showed a clear categorization of two classes: the yellowish-green-type and the brownish-type (Fig 7A). The results were in very good agreement with those obtained from HCA and PCA scores plot. To further validate the quality of the PLS-DA tests, random permutation class membership and the performance of 200 iterations were conducted. The R2 and Q2 intercept values were 0.352 and -0.23 and thus showed a low risk of over fitting and reliable (Fig 7B). Based on the PLS-DA, a loading plot was used to select the significant components that were differentially produced in the yellowish-green-type and the brownish-type of SS. The discriminant variables whose variable importance plot (VIP) are larger than 1.25 were selected as the significant different fragments. It could be seen from Fig 7C that V12 (4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran), V16 (pulegone), V30 (germacrene D), V28 (caryophyllene), V29 (humulene), V25 (1-ethenyl-1-methyl-2,4-bis(1-methylethenyl)-cyclohexane), V15 (2-allyl-4-methylphenol), V38 ((Z,Z,Z)-9,12,15-octadecatrienoic acid), V13 (trans-5-methyl-2-(1-methylethenyl)-cyclohexanone) and V11 (L-menthone) might be the discriminant compounds in distinguishing the two color varieties of SS samples (Table 1). The variable importance plot for PC1 and PC2 indicated that V12 (4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran) and V16 (pulegone) may have greater influence on the discrimination between the yellowish-green-type and the brownish-type of SS samples. The relative content of 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran was higher in the brownish-type samples than in the yellowish-green-type samples, while the relative content of pulegone was higher in the yellowish-green-type than in the brownish-type samples (Table 2). Interestingly, these two constituents had been demonstrated with good biological activities,[4, 12, 31, 33] and pulegone was also quality marker in the Chinese Pharmacopoeia (2015 edition).[4] Therefore, the relative content of these two compounds can be applied as marker components for quality evaluation of SS samples in different colors and two chemotypes of SS were proposed.

Fig 7.

Fig 7

Open in a new tab

PLS-DA scores plot (A), R2 and Q2 intercept values from 200 iterations (B), and variable importance plot (C) of identified compounds in volatile oils of 20 batches Schizonepetae Spica samples in different colors.

According to previous studies,[26, 36] 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran is a hepatotoxin and a major oxidative metabolite of pulegone, and cytochrome P450 enzyme (CYP) involved in the biosynthesis pathway had been identified in mint species. Building on the extensive genetic and biochemical knowledge accumulated for the genus Mentha, as calyx changed from yellowish-green to brownish, the plausible biotransformation in SS was hypothesized as shown in Fig 8.[37] However, evidence has been proved that pulegone, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and their oxidative product p-cresol could cause severe hepatotoxicity.[26] Thus, the pharmacological function should be further investigated to ensure the therapeutic effect and safety of SS in different colors.

Fig 8. Plausible biotransformation pathway in Schizonepetae Spica when calyx changed from yellowish-green to brownish.

Fig 8

Open in a new tab

CYP: cytochrome P450 enzyme.

Conclusion

This work reported for the first time applying the fingerprint analysis technology combined with chemometrics methods to characterize, discriminate and evaluate the quality of SS samples in different colors. The GC-MS fingerprints of 20 batches SS samples had relatively high similarity values (≥ 0.964) and 39 common components were identified. Accordingly, by using HCA, PCA and PLS-DA for analyzing the obtained results, the SS samples were categorized into two classes: the yellowish-green-type and the brownish-type. The amount of 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were identified as the major biomarkers of the SS quality which directly depend on the calyx color of samples. Our results demonstrated that samples of SS that had yellowish-green calyx was thought to be superior while those had brownish calyx were considered to be inferior in terms of quality. In summary, marker variables and correlation coefficients of GC-MS fingerprints between the yellowish-green-type and the brownish-type provided new clues to evaluate the quality of SS, as well as provided useful references for the standardization of color-based quality control for medicinal herbals, foods and other products.

Data Availability

All relevant data are within the paper.

Funding Statement

This work was supported by the sixth batch of National Academic Experience Inheritance Project of Chinese Medicine Experts (No. 176-2017-XMZC-0166-01).

References

  • 1.Zhao ZZ, Liang ZT, Guo P. Macroscopic identification of Chinese medicinal materials: traditional experiences and modern understanding. J Ethnopharmacol. 2011;134(3):556–64. 10.1016/j.jep.2011.01.018 [DOI] [PubMed] [Google Scholar]
  • 2.Shi DH, Long Y, Dai YM, Lu Q, Zhang J, Sun LL, et al. Scientific analysis of traditional identification experience of "redder is better" based on correlation between intrinsic quality and appearance color of Salviae miltiorrhizae radix et rhizoma. Chin J Exp Tradit Med Form. 2018;24(22):6–10. [Google Scholar]
  • 3.Li ZL. Ben Cao Yuan Shi. Beijing: Xue Yuan Press; 2011. [Google Scholar]
  • 4.State Commission of Chinese Pharmacopoeia. Pharmacopoeia of the People's Republic of China 2015 edtion. Beijing: China Medical Science Press; 2015. [Google Scholar]
  • 5.Fung D, Lau CBS. Schizonepeta tenuifolia: chemistry, pharmacology, and clinical applications. J Clin Pharmacol. 2002;42(1):30–6. 10.1177/0091270002042001003 [DOI] [PubMed] [Google Scholar]
  • 6.Su XJ. The best combination of medicine and food-Schizonepeta tenuifolia. Chin Wild Plant Resour. 2000;19(6):24–5. [Google Scholar]
  • 7.Du CZ, Qin JP, Chen YP, Cai Y. GC-MS analysis of volatile oil components in Schizonepeta tenuifolia Briq. from various habitats. Hubei Agric Sci. 2014;53(1):188–90. [Google Scholar]
  • 8.Hu J, Shi RB, Zhang YH. Content determination of luteolin and hesperidin in the effective fractions of Spica Schizonepeta by HPLC. Beijing Univ Tradit Chin Med. 2005;28(4):52–4. [Google Scholar]
  • 9.Jiang YH, Jiang DQ, Wu KJ, Peng LL. Contents determination of ursolic acid and oleanolic acid in different parts of Jiangxi Herba Schizonepetae and carbonized Herba Schizonepetae. China J Tradit Chin Med Pharm. 2016;31(3):1068–70. [Google Scholar]
  • 10.Shan MQ, Qian Y, Yu S, Guo SC, Zhang L, Ding AW, et al. Anti-inflammatory effect of volatile oil from Schizonepeta tenuifolia on carrageenin-induced pleurisy in rats and its application to study of appropriate harvesting time coupled with multi-attribute comprehensive index method. J Ethnopharmacol. 2016;194:580–6. 10.1016/j.jep.2016.10.045 [DOI] [PubMed] [Google Scholar]
  • 11.Wang BS, Huang GJ, Tai HM, Huang MH. Antioxidant and anti-inflammatory activities of aqueous extracts of Schizonepeta tenuifolia Briq. Food Chem Toxicol. 2012;50(3–4):526–31. 10.1016/j.fct.2011.12.010 [DOI] [PubMed] [Google Scholar]
  • 12.Yamahara J, Matsuda H, Watanabe H, Sawada T. Biologically active principles of crude drug, analgesic and anti-inflammatory effects of "Keigai (Schizonepeta tenuifolia Briq.)". Yakugaku Zasshi. 1980;100:713–7. 10.1248/yakushi1947.100.7_713 [DOI] [PubMed] [Google Scholar]
  • 13.Fan JX, Wang S, Meng XS, Bao YR, Li TJ. Study of cancer cell apoptosis induced by Schizonepeta tenuifolia with microfluidic chip technology. Acta Pharm Sin. 2017;52(1):126–31. [PubMed] [Google Scholar]
  • 14.Fan JX, Bao YR, Meng XS, Wang S, Li TJ. Study on relationship between efficacy against lung cancer and different parts of Schizonepeta tenuifolia based on microfluidic chip technology. China J Chin Mater Med. 2017;42(9):1717–21. [DOI] [PubMed] [Google Scholar]
  • 15.Chen SG, Cheng ML, Chen KH, Horng JT, Liu CC, Wang SM, et al. Antiviral activities of Schizonepeta tenuifolia Briq. against enterovirus 71 in vitro and in vivo. Sci Rep-Uk. 2017;7(935):1–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Ng YC, Kim YW, Lee JS, Lee SJ, Song MJ. Antiviral activity of Schizonepeta tenuifolia Briquet against noroviruses via induction of antiviral interferons. J Microbiol. 2018;56(9):683–9. 10.1007/s12275-018-8228-7 [DOI] [PubMed] [Google Scholar]
  • 17.State Administration of Traditional Chinese Medicine. Dictionary of Chinese Traditional Medicine. Shanghai: Shanghai Scientific and Technical Publishers; 1999. p. 197. [Google Scholar]
  • 18.Ye DJ, Yuan ST. Dictionary of Chinese Medicine Processing. Shanghai: Shanghai Scientific and Technical Publishers; 2005. p. 411. [Google Scholar]
  • 19.Ouyang Z, Yang L, Su SL, Feng X, Wang M. Fingerprint of volatile oil of Atractylodes lancea by GC-MS. Acta Pharm Sin. 2007;42(9):968–72. [PubMed] [Google Scholar]
  • 20.Lv SD, Wu YS, Song YZ, Zhou JS, Lian M, Wang C, et al. Multivariate analysis based on GC-MS fingerprint and volatile composition for the quality evaluation of Pu-Erh green tea. Food Anal Method. 2015;8(2):321–33. [Google Scholar]
  • 21.Liu QT, Kong DD, Luo JY, Kong WJ, Guo WY, Yang MH. Quantitative and fingerprinting analysis of Atractylodes rhizome based on gas chromatography with flame ionization detection combined with chemometrics. J Sep Sci. 2016;39(13):2517–26. 10.1002/jssc.201501275 [DOI] [PubMed] [Google Scholar]
  • 22.Chun MH, Kim EK, Lee KR, Jung JH, Hong J. Quality control of Schizonepeta tenuifolia Briq by solid-phase microextraction gas chromatography/mass spectrometry and principal component analysis. Microchem J. 2010;95(1):25–31. [Google Scholar]
  • 23.Chun MH, Kim EK, Yu SM, Oh MS, Moon KY, Jung JH, et al. GC/MS combined with chemometrics methods for quality control of Schizonepeta tenuifolia Briq: determination of essential oils. Microchem J. 2011;97(2):274–81. [Google Scholar]
  • 24.Wang JB, Zeng LN, Zang QC, Gong QF, Li BC, Zhang XR, et al. Colorimetric grading scale can promote the standardization of experiential and sensory evaluation in quality control of traditional Chinese medicines. Plos One. 2012;7(11):1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Liu CC, Srividya N, Parrish AN, Yue W, Shan MQ, Wu QN, et al. Morphology of glandular trichomes of Japanese catnip (Schizonepeta tenuifolia Briquet) and developmental dynamics of their secretory activity. Phytochemistry. 2018;150:23–30. 10.1016/j.phytochem.2018.02.018 [DOI] [PubMed] [Google Scholar]
  • 26.Yu S, Chen YW, Zhang L, Shan MQ, Tang YP, Ding AW. Quantitative comparative analysis of the bio-active and toxic constituents of leaves and spikes of Schizonepeta tenuifolia at different harvesting times. Int J Mol Sci. 2011;12(10):6635–44. 10.3390/ijms12106635 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Duan SL, Zeng WX, Sun LL. Chemical constituents of volatile oils in drug pair of menthae Haplocalycis herba and Schizonepetae spica by GC-MS. Chin J Exp Tradit Med Form. 2015;21(11):50–4. [Google Scholar]
  • 28.Hu YC, Kong WJ, Yang XH, Xie LW, Wen J, Yang MH. GC-MS combined with chemometric techniques for the quality control and original discrimination of Curcumae longae rhizome: Analysis of essential oils. J Sep Sci. 2014;37(4):404–11. 10.1002/jssc.201301102 [DOI] [PubMed] [Google Scholar]
  • 29.Zhang L, Shao X, Yu S, Bao BH, Ding AW. HSGC fingerprint of volatile oil in Schizonepetae Spica. Chin Tradit Herb Drugs. 2012;43(9):1767–9. [Google Scholar]
  • 30.Wang Q, Wang LX, Wang XY, Wang YF. Chromatographic fingerprint for Schizonepeta tenuisfolia Briq. Chin Tradit Pat Med. 2007;29(7):941–5. [Google Scholar]
  • 31.He T, Tang Q, Zeng N, Gong XP. Study on effect and mechanism of volatile oil of Schizonepetae Herba and its essential components against influenza virus. China J Chin Mater Med. 2013;38(11):1772–7. [PubMed] [Google Scholar]
  • 32.Oliveira GLD, Machado KC, Machado KC, Da Silva APDCL, Feitosa CM, Almeida FRD. Non-clinical toxicity of beta-caryophyllene, a dietary cannabinoid: absence of adverse effects in female Swiss mice. Regul Toxicol Pharmacol. 2018;92:338–46. 10.1016/j.yrtph.2017.12.013 [DOI] [PubMed] [Google Scholar]
  • 33.Wang Y, Zhang N. Review on the safety and fine processing technology of natural aromatic materials. Flavour Fragrance Cosmetics. 2016(4):53–8. [Google Scholar]
  • 34.Liu YP, Luo JP, Feng YF, Guo XL, Cao H. DNA profiling of Pogostemon cablin chemotypes differing in essential oil composition. Acta Pharm Sin. 2002;37(4):304–8. [PubMed] [Google Scholar]
  • 35.Chen Y, Wu YG, Xu Y, Zhang JF, Song XQ, Zhu GP, et al. Dynamic accumulation of sesquiterpenes in essential oil of Pogostemon cablin. Rev Bras Farmacogn. 2014;24(6):626–34. [Google Scholar]
  • 36.Lassila T, Mattila S, Turpeinen M, Pelkonen O, Tolonen A. Tandem mass spectrometric analysis of S- and N-linked glutathione conjugates of pulegone and menthofuran and identification of P450 enzymes mediating their formation. Rapid Commun Mass Sp. 2016;30(7):917–26. [DOI] [PubMed] [Google Scholar]
  • 37.Bertea CM, Schalk M, Karp F, Maffei M, Croteau R. Demonstration that menthofuran synthase of mint (Mentha) is a cytochrome P450 monooxygenase: cloning, functional expression, and characterization of the responsible gene. Arch Biochem Biophys. 2001;390(2):279–86. 10.1006/abbi.2001.2378 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Joseph Banoub

27 Nov 2019

PONE-D-19-27294

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

PLOS ONE

Dear Prof. Cao,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please see Academic Editor and Reviewer #1 comments below.

We would appreciate receiving your revised manuscript by Jan 10 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Joseph Banoub, Ph,D., D. Sc.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

Academic Editor comments to authors:

Color discrimination is an important aspect for the macroscopic identification of Chinese medicinal material (CMM). In this manuscript, the authors explain that the color of the persistent calyx of Schizonepetae Spica (SS) herb can be categorized into two classes: the yellowish-green-type and the brownish-type.

The authors described a novel approach based on gas chromatography-mass spectrometry (GC-MS) to identify and evaluate the quality of SS of different colors. The authors used 20 different colors batches of SS and extracted their essential oils. The authors found that the average essential oils yield of yellowish-green color SS was significantly higher than that of SS having the brownish color.

The GC-EI-MS fingerprints of 20 batches SS samples indicated the presence of a total of 39 identified common volatiles compounds.

The authors used hierarchical clustering analysis (HCA), principal component analysis (PCA) and partial least-squares discriminate analysis (PLS-DA) to distinguish SS samples characterized by different colors.

The authors showed that 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were detected as the key variables for discriminating SS samples of different colors and for quality control.

In summary, this manuscript is well written and presents a straightforward method for detecting the marker variables and correlation coefficients of GC-MS fingerprints between the yellowish-green-type and the brownish-type provided new clues to evaluate the quality of SS.

1.In page 3 of your pdf, lines 43-45, you have written the following:

Color discrimination is an important aspect for the macroscopic identification of 44 Chinese medicinal material (CMM) and for the evaluation of quality in traditional 45 experiences.[1]

QUERY: Please re-write as it makes no sense.

2. In page 6-7, Table 1. The details of the 20 batches Schizonepetae Spica samples and fingerprint 109 similarities.

QUERY: Can you please explain how did you obtain the values of R, G and B. this is not clear at all. Perhaps this table should be inserted after you discuss the Discrimination the color of Schizonepetae Spica calyx section.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Manuscript: PONE-D-19-2729

In this Manuscript, the authors used GC-MS to differentiate between the two different classes of Schizonepetae Spica (SS), a traditional Chinese medicinal herb. The SS samples can be classified according to the color of the calyx in to the yellowish-green-type and the brownish-type.

The authors performed GC-MS analysis on the essential oils extracted from 20 different SS samples. The resulting 20 GC-MS chromatograms are almost identical and allowed the identification of 39 common volatile compounds in all samples. The relative content of pulegone, caryophyllene and germacrene D were relatively higher in the yellowish-green-type samples than in the brownish-type samples; whereas another four main components L-menthone, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran, caryophyllene oxide and (Z,Z,Z)-9,12,15-octadecatrienoic acid had a higher content in the brownish-type samples.

Due to the limitation of GC-MS fingerprint analysis for detecting minor differences in samples of different colors, some statistical analysis (HCA, PCA and PLS-DA) was used to find chemical markers for the discrimination between the samples of different colors. Based on these statistical analyses, the SS samples were categorized into two classes: the yellowish-green-type and the brownish-type. The amount of 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were identified as the major biomarkers of the SS quality which directly depend on the calyx color of samples. The relative content of 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran was higher in the brownish-type samples than in the yellowish-green-type samples, while the relative content of pulegone was higher in the yellowish-green-type than in the brownish-type samples. Therefore, the relative content of these two compounds can be applied as marker components for quality evaluation of SS samples in different colors.

Minor Comments

1- In the conclusion section, the authors mentioned the following “ Our results demonstrated that samples of SS that had yellowish-green calyx was thought to be superior while those had brownish calyx were considered to be inferior in terms of quality” Please explain this conclusion in more details as it is not clear in the manuscript.

2- I recommend to demonstrate this section Identification of volatile components from Schizonepetae Spica before the section of Hierarchical clustering analysis

3- In table 2, Molecule structure should be Molecular Formula

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Jan 7;15(1):e0227235. doi: 10.1371/journal.pone.0227235.r002

Author response to Decision Letter 0

12 Dec 2019

Reviewer #1

1. The yellowish-green color of SS corresponded to a relatively higher concentration of volatiles (~ 0.69%-1.65% mL/g), while SS in brownish color was correlated with relatively lower volatiles concentration (~ 0.47%-0.85% mL/g) (in section Yield of essential oils from Schizonepetae Spica of different colors). In addition, pulegone, which is known for its pleasant odor, analgesia, anti-inflammatory and antiviral properties, is the chemical indicator in the Chinese Pharmacopoeia (2015 edition) of SS (in section Identification of volatile components from Schizonepetae Spica and section Partial least-squares discriminate analysis). In our manuscript, we demonstrated that the relative content of 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone could be applied as marker components for quality evaluation of SS samples in different colors. And the relative content of pulegone was higher in the yellowish-green-type than in the brownish-type samples (in section Partial least-squares discriminate analysis). Therefore, we can draw a conclusion that SS of good quality were often yellowish-green and those of poor quality were often brownish.

2. Thank you for your kindly recommendation. The section Identification of volatile components from Schizonepetae Spica has been inserted before the section of Hierarchical clustering analysis in the manuscript.

3. In table 2, “Molecule structure” has been revised as “Molecular Formula”.

Academic editor

1. The sentence “color discrimination is an important aspect for the macroscopic identification of Chinese medicinal material (CMM) and for the evaluation of quality in traditional experiences” has been revised as “color discrimination is an important aspect for the macroscopic identification of Chinese medicinal material (CMM)” as shown in section Introduction.

2. The red-green-blue (RGB) values were extracted from the images of samples using Photoshop CS6 (Adobe Systems Inc., USA) software (Table 1). The surface color of the Schizonepetae Spica calyx was selected to extract RGB values. Thank you for your kindly recommendation. Table 1 has been inserted after the Discrimination the color of Schizonepetae Spica calyx section.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (16.9KB, docx)

Decision Letter 1

Joseph Banoub

16 Dec 2019

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

PONE-D-19-27294R1

Dear Dr. Cao,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Joseph Banoub, Ph,D., D. Sc.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

I am sending you this letter to confirm that your manuscript is now acceptable for publication

Reviewers' comments:

Acceptance letter

Joseph Banoub

20 Dec 2019

PONE-D-19-27294R1

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

Dear Dr. Cao:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Joseph Banoub

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (16.9KB, docx)

    Data Availability Statement

    All relevant data are within the paper.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES