Forensic analysis of red lipsticks using ATR-FTIR spectroscopy and chemometrics

Journal Pre-proofs Forensic analysis of red lipsticks using ATR-FTIR spectroscopy and chemometrics Rito Chophi, Sweety Sharma, Rajinder Singh PII: DOI: Reference:

S2468-1709(19)30106-7 https://doi.org/10.1016/j.forc.2019.100209 FORC 100209

To appear in:

Forensic Chemistry

Received Date: Revised Date: Accepted Date:

3 October 2019 13 December 2019 13 December 2019

Please cite this article as: R. Chophi, S. Sharma, R. Singh, Forensic analysis of red lipsticks using ATR-FTIR spectroscopy and chemometrics, Forensic Chemistry (2019), doi: https://doi.org/10.1016/j.forc.2019.100209

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Forensic analysis of red lipsticks using ATR-FTIR spectroscopy and chemometrics Rito Chophia, Sweety Sharmaa, Rajinder Singhb,*,[email protected] a

Department of Forensic Science, Punjabi University Patiala, Punjab, 147002, India Department of Forensic Science, Punjabi University Patiala, Punjab, 147002, India

b

*Corresponding

author.

Graphical abstract Highlights Analysis of 38 red lipsticks of 20 different manufacturers Objective interpretation of results using chemometric methods 100% discrimination of samples utilising PCA (principal component analysis) 81.48% classification accuracy using PCA-LDA approach Study on the effect of substrates and environmental conditions Validation study on the current research methodology utilised

Abstract Lipsticks are used on routine basis, and due to its prevalence, it can be encountered at the crime scene as trace transferred evidence. Analyses of such exhibits can provide corroborative evidence to link the suspect with the victim or with the crime scene. In the present study, 38 different red shade lipsticks of 20 different manufacturers were analyzed using ATR-FT-IR (attenuated total reflectance-fourier transform-infrared) spectroscopy. Chemometric methods: PCA (principal component analysis) and PCA-LDA (linear discriminant analysis), applied to provide objective interpretation of results resulted in 100% discriminating power and 81.48% correct classification respectively. The effects of different substrates on lipstick analyses, lipstick wear time for one day, and exposure to different environmental conditions were also studied. More research is required for linking lipstick smudges on different substrates with their source of origin using chemometric methods.

Keywords:

forensic

science;

lipstick;

trace

evidence;

ATR-FTIR

spectroscopy;

chemometrics.

Introduction The art of applying lipstick on lips for beautification purpose is centuries old, and this art continues to be popularly practiced even in modern times. The industry for this cosmetic product is booming at rapid pace and varieties of new lipstick product lines are continually being added in the market. The market size is expected to reach USD 18.9 billion by 2025 from USD 11.5 billion in 2018 9 [1]. Owing to the prevalence and routine use of lipsticks, and the nature of the product as such, which gets easily transferred upon physical contact to materials such as clothing, drinking cups, tissue paper, and other substrates makes it likely to be encountered in criminal cases; especially pertaining to physical and sexual assault cases against women, anonymous threatening letters, suicides cases (where the victim has left behind written notes), and other criminal acts and offences [2, 3]. Lipstick evidence found on such substrates would indicate proof of physical contact, and the characterization of such evidence can be utilized as corroborative evidence to link the suspect with the victim or with the object in question. Lipstick evidence is also significant and purposeful in forensic cases as

the transferred material remains persistent on the transferred object, and is not easily seen by naked eye, therefore, it is left unremoved and undisturbed by the criminal. However, the evidential value of lipstick evidence found on such substrates would depend upon the circumstance of its finding, and whether it adds any merit to a particular case as lipsticks are mass produced and smudges of lipsticks can also be transferred during normal activities [4]. The analysis of lipstick evidence in forensic cases is a challenging task as it is composed of numerous chemical components to achieve properties such as aesthetic appeal (colour), strength and shape, viscosity, easy applicability, flexibility, adherence to lips, product preservation, moisture retention, and fragrance. A typical lipstick composition consist of oils (e.g. castor oil, lanolin oil, and mineral oil constituting about 40%–70% by weight), waxes (e.g. carnauba wax, candelilla wax, bees wax, and paraffin wax constituting about 8%–15%), colouring agents (e.g. rhodamine, erythrosine, titanium dioxide, and tartrazine accounting for about 0.5%–8%) and additives like antioxidants, preservatives, emollients, and perfumes in minor quantities [5, 6]. The percentage composition of components in lipstick varies with different manufacturers, [7] and hence, earlier studies on analysis of lipstick exhibits have mostly employed chromatography techniques such as TLC [8-11], HPLC [2, 12, 13], and GC [14, 15], mainly for analysis of colouring agents. These techniques, though have proven to provide high discriminatory power, involves destructive sample preparation, consumes much reagents, are affected by factors such temperature, humidity, purity of chemicals, and the results obtained are non-confirmatory in nature [16]. Hence, these techniques are less preferred, but can be utilized as an effective screening tool. Though GC-MS provides confirmatory results, yet it destroys the samples, and hence preservation of trace exhibit recovered in crime scene is compromised. On the other hand, technique like NAA is limited by cost, time consumption, and is not readily available in many forensic laboratories.

In recent years, spectroscopic techniques such as Raman spectroscopy [17-19] and ATRFTIR technique [20-22] have been employed for non-destructive analyses of lipstick samples. While the former is affected by florescence interferences, the use of latter technique has shown to be suitable and effective for discrimination of lipstick samples. Besides its nondestructive nature, this technique provides rapid and reproducible results free from sample preparation, and is environment friendly. The technique has also been applied for discrimination of other forensic exhibits such as paints [23], inks [24], kajal [25] and body fluids [26, 27]. In each of the study pertaining lipsticks, the results obtained using ATR-FTIR technique was interpreted objectively using a combination of methods such as PCA, LDA, cluster analysis, and correlation coefficient. The use of chemometric tool in the field of forensic science assists in handling huge spectral data, provides objective data interpretation in quick time domain, and enables unbiased and transparent decision making. Gladysz et al. [20] utilized ATR-FTIR spectroscopy to differentiate 38 lipstick samples of 20 different manufacturers supported by statistical tools such as PCA, cluster analysis, and correlation coefficient. The discriminating power of each tool was calculated to be 29%, 51% and 93% respectively. Some samples could not be discriminated, and was reasoned to have occurred due to similar chemical constituents used in the manufacturing of lipsticks. Study on the effect of substrates such as cigarette butts, envelope, paper, tissue, and white collar of shirt were also performed, and the smudges on each substrate could be correctly identified to its source of origin. Sharma et al. [21] analyzed 25 lipstick samples of 25 different manufacturers and using cluster analysis and PCA, discrimination of all the samples was achieved. Wong et al. [22] analyzed 40 lipstick samples of red and nude shade color of 20 different manufacturers, and using a combination of PCA and LDA reported correct classification with 100% accuracy in red color lipsticks, while misclassification of samples

(different series of lipstick samples of same manufacturer) were reported in nude shade lipsticks. In actual forensic case scenario, lipstick exhibits maybe encountered in different substrates under varying environmental conditions. However, most of the earlier studies have focused on differentiation of fresh lipsticks and only few studies have accounted for background material. Also, there are no studies regarding the effect of different environmental conditions on lipstick samples, except the effect of heating on lipstick samples [21]. Therefore, in the present research study, an attempt has been made to: (i) discriminate fresh lipstick samples of different manufacturer and series (ii) study the effect of different substrates such as cotton cloth, plastic, tissue paper and glass, and (iii) to check the effect of lipstick wear time, and different environmental conditions on analysis of lipstick exhibits.

Materials and methods Sample collection: Common brands of lipsticks were collected from the market in North Western India. A total of 38 different red color lipsticks, consisting of 20 different manufacturers were procured. Details regarding various samples collected are given in Table 1. Sample preparation: Fresh lipsticks about 1.5 mg were taken and directly placed on ATRFTIR crystal and analyzed. A good surface contact was maintained between the crystal and the sample with the help of tightened anvil. For substrate study, lipstick smudge was made on different background materials such as glass, plastic, tissue paper, and glass. About 1 mg of sample was scraped from glass and plastic substrate, and analyzed. While, lipstick smudge on cotton cloth and tissue paper were analyzed as such, directly from the material after

background subtraction. The smudged materials were placed in different environmental conditions at room temperature and outdoor environment, and analyzed after a gap of six months. Homogeneity test was performed on all the samples by analyzing three different points or location on the same sample. Intra-sample variation test was performed on all the samples by procuring each lipstick in triplicates. Precision test was carried out by analyzing the same sample for four consecutive days under same set of experimental conditions. Also, the study on the effect of lipstick wear time for one day was performed. Lipstick sample was applied on an individual in the morning hour (9:30 am). The spectrum of lipstick was taken after depositing on paper, and again the sample was analyzed in the evening hour (4:30 pm) after normal routine work of an individual. Instrumental set up The

analyses

of

samples

were

performed

using

Bruker

alpha

eco-ATR-FTIR

spectrophotometer equipped with ZnSe crystal, and Deuterated Tri Glysine Sulphate (DTGS) detector. Opus software (v.7.2) was used for recording spectrum in the mid infra red range of 4000-600 cm-1. Important parameters such as scan time and resolution of ATR-FTIR spectrometer was set at 24 scans and 4 cm-1 respectively based on optimization tests carried out. No significant change in spectrum was observed at 34, 44, 64 scans respectively. Prior to analysis of each new sample, a new background (air) measurement and subtraction were performed to remove the background effects. Similarly, for substrate study, respective blank substrate was taken as background measurement. ATR crystal was cleaned with acetone of spectroscopic grade after each sample analysis. Baseline correction, smoothing, and normalization (Min-max normalization method) were performed on each of the obtained spectra. Chemometric and computational tool approach

Comparing large spectral data visually is a tedious process, and bias interpretation could be involved where two or more samples show similar spectra. Therefore, in the current study, chemometric methods, that is, principal component analysis (PCA) and PCA-LDA (linear discriminant analysis) were used for the purpose of sample discrimination as these methods provide objective interpretation of results which are accurate and reproducible. Furthermore, it aids in recognition of patterns in data which is simple to understand and provides results in quick time domain [28]. The discriminating power (DP) of statistical tool (PCA) employed was calculated using the formula given by Smalldon and Moffat [29] DP =

Total number of discriminating pairs of sample Total number of possible sample pairs

x (100)

Total number of possible sample pairs = X (X-1)/2, where X is total number of samples PCA: It is a multivariate analysis technique which reduces large data set to few significant variables or co-ordinates called principal components (PC) for easy recognition of patterns and relationships in data [30, 31]. It is an unsupervised multivariate technique which is applicable when there are correlations present among the variables [32]. It explains the variance in a data set without any loss or less loss of information. PCA-LDA: LDA is a supervised pattern recognition method. While PCA selects a direction which retains maximal structure in a lower dimension among the given classes, the criterion in LDA is a maximum discrimination among the given classes [32, 33]. A combination of PCA and LDA is very useful as it improves the efficiency of classification by instinctively selecting the most significant features to build the classification model. As PCA only looks for projection to maximize the variance in a dataset, it becomes important to use PCA in combination with LDA to find discrimination between and within different lipstick groups [34]. In the current study PCA and PCA-LDA was carried out using Unscrambler X software (Version 10.5.1 (64 bit), CAMO AS, Norway. Results and discussion:

ATR-FTIR was utilized to obtain spectra of lipstick samples to identify the compositional variations between different lipstick samples. A typical spectrum of lipstick is given in Fig 1. In all the spectra, region from 3700 cm-1-3100 cm-1 showed a broad spectrum which is due to O-H vibrations from compounds such as water and alcohol. In the range 3100 cm-1-2800 cm1

, peaks at 3007 cm-1, 2917 cm-1, and 2850 cm-1 are attributed to CH3 stretching vibrations,

C-H asymmetric and C-H symmetric vibrations respectively. The presence of peaks in the spectral ranges 1730–1740 cm-1, 1370–1560 cm-1 and 850–1270 cm-1 are attributed to C-O stretching vibration (1742 cm-1) of propyl ester of hexanoic acid, aromatic compounds (1375 cm-1) and presence of silicates (1239 cm-1) respectively. The peaks present in the spectral ranges 1410–1470 cm-1, 1165–1380 cm-1 and 1165–1380 cm-1 are due to propyl ester of hexanoic acid (1461 cm-1), C=H bending vibration (1159 cm-1) and CH2 rocking mode (721 cm-1) respectively [20,21,35, 36]. Homogeneity test, intra sample variation test, and precision tests were performed as mentioned in ‘materials and methodology’ section, and through analysis, it was observed that there were no significant differences in spectra for all the three tests carried out. Representative spectra for homogeneity test, intra sample variation test, and precision test are shown in Fig. 2, Fig. 3 and Fig. 4 respectively. Chemometric discrimination All the ATR-FTIR spectra registered in the range 4000 cm-1-600 cm-1 were utilized for performing PCA. Fig 5 provided the optimum number of principal components to be considered for PCA scatter plot. Thus, four principal components were selected, and these four principal components described 92% variation in a dataset: 72%, 11%, 3%, and 2% for first, second, third and fourth PCs respectively. A two dimensional plot was presented as it depicted better discrimination between samples and provided easy visualization. A combination of different PCs (PC1, PC2, PC3, and PC4) were tried to find which PC

combination provided better discrimination between samples. While PC1 and PC2 accounted for most of the variation in a dataset (83%) as shown in Fig. 6, a combination of PC1 and PC4 provided better discrimination between samples as shown in Fig. 7. Nonetheless, each of these two combinations (PC1-PC2) and (PC2-PC4), provided discrimination of all the samples. The discriminating power (DP) of PCA in the current study was found to be 100%. The combined loading plot of PC-1 and PC-4 is shown in Fig. 8, and can be divided into six regions (R): R-I (3700 cm-1-2600 cm-1), R-II (1800 cm-1-1570 cm-1), R-III (1470 cm-1-1220 cm-1), R-IV (1219 cm-1- 1040 cm-1), R-V (1039 cm-1-800 cm-1), and R-V1 (799 cm-1- 600 cm1

) respectively. In R-I, R-II, R-IV, and R-VI, PC-1 and PC-4 were found to be negatively

correlated whereas in R-III and R-V, the two principal components were found to be positively correlated. While PCA provided discrimination between samples, it did not offer objective information regarding whether if the samples have been classified into its correct group or class. Hence, LDA was further applied to classify and discriminate the samples. Samples L1-L27 consists of 27 samples belonging to 9 manufacturers (three different series of same manufacturer in each group), and therefore, it was desired to investigate whether if these samples got correctly classified into their respective groups. LDA model was constructed using the first two principal components to classify the samples, and also to check the results shown in Fig. 6(PCA plot obtained using the first 2 PCs). Due to the availability of samples only in triplicate, 4 principal components could not be used for LDA model, and hence, Fig.7, obtained using PC1 and PC4 could not be investigated. As observed in Table 2, some samples (L16, L17, L18, and L26) got misclassified as G1, G7, G3, G5, and G3 respectively, and a classification accuracy of 81.48% was obtained. Effect of substrates:

As lipstick exhibit could be recovered from various substrates, therefore, in the current study, the following substrates were selected to check the effect of substrates on exhibit analysis: cotton cloth, tissue paper, plastic, and glass. Earlier study [20] had worked on substrates such as cigarette butts, envelope, paper, tissue, and white collar of shirt. The authors have reported that only wavenumber from the region 1800 cm-1- 650 cm-1 contributed to the differentiation of lipstick samples on substrates. In the present study, sample L1, L2, L10, L16 and L19 were selected, and the smudges of these samples were investigated on all the substrates as mentioned, and are shown in Table 3. As observed from Table 3, all the samples on substrates could be correctly identified and linked to its source of origin. Fig. 9 shows a representative sample L1 on all the substrates utilized for the present study.

Effects of lipstick wear time for one day and environmental conditions To check the effect of lipstick wear time for one day, lipstick sample (L19) was applied on an individual in the morning hours at 9:30 am. The spectrum of this sample was taken after depositing on paper, and again the sample was analyzed in the evening hours at 4:30 pm after normal routine work of an individual. No significant differences in spectra were observed as shown in Fig 10. Though noise was present in the spectrum taken at the evening hours, no loss of significant peaks was observed. Reuland and Trinler [13] conducted similar study using HPLC, and reported that worn lipsticks, after a gap of 2 hours no longer resembled the original chromatogram, and was reasoned to have occurred due to dissolution of fairly water soluble components such as polyparaben and dioctyl adipate. In the present study, as no sample extraction were involved, no chemical interferences was observed, and it led to the correct linking of spectrum taken in the evening hours to the spectrum taken in the morning hours. However, this does not guarantee that matching spectra can be obtained for all the

cases, but could vary from subject to subject eating habits and exposure to other factors which might cause interferences. And, this remains a domain to be further researched in detail. In order to investigate whether if the same set of lipstick samples (L1, L2, L10, L16 and L19) utilized for study on effect of substrates could be identified after a prolonged period of time, these samples were left under room temperature 35±4°C and outdoor environment 38±7°C. The results of analyses obtained after a gap of 6 months have been tabulated in Table 4. It is observed from Table 4 that the lipstick samples on plastic at room temperature could be identified correctly even after leaving it for a period of 6 month, while, the samples on the glass substrate could not be identified correctly. It was found that the samples on glass substrates were highly contaminated with dust and other fungal like material, and therefore, interfered in the analyses of the samples. Few samples left on cotton cloth showed majority of the peaks which were present in parent sample, but few peaks in the region 900 cm-1- 600 cm1

(precisely at 888 cm-1, 721 cm-1, 661 cm-1, and 624cm-1) were absent. And these samples

indicated to be coming from the same source, but could not be commented upon with certainty. The samples on tissue at room temperature could not be linked to its source of origin. The samples were found to be discoloured, dusty, and dry. It may have happened due to evaporation of certain components of lipstick. Though, evaporation phenomena was not observed in the case of plastic even after 6 months, or at least no significant changes in peak were observed, tissue being a good absorbent might have absorbed and spread the lipstick samples into thin layer, making it more susceptible to evaporation. With regard to lipstick samples on outdoor environment, the samples could not be linked to its source of origin. A representative sample L1 in Fig. 11 a-d shows the effect of room and environmental conditions on selected substrates such as cotton cloth, plastic, tissue paper and glass.

In the present study, the environmental effect on sample analysis was studied after a gap of 6 months. Therefore, future studies can involve continuous monitoring of samples on substrates exposed to various environmental conditions. Validation study In order to cross-validate the research methodology (PCA) utilized in the current study, PCA scatter plot was made by randomly selecting three blind samples (X1, X2, and X3) from the already collected samples, and was analyzed under the same set of experimental conditions. The identities of these samples were not revealed to the analyst until the predictions were completed. Two samples (Y1 and Y2) were additionally purchased (not a part of training set), and three samples Z1, Z2, and Z3 were also included in the PCA analysis; Z1 (cotton clothporous substrate) and Z2 (plastic substrate- non-porous) which were samples L4, and L16, and were selectively chosen (identities known to analyst). Lipstick L19 (Z3), which was the sample studied for lipstick wear time was also selected, and PCA was performed for the entire samples as shown in Fig 12. It was observed from Fig. 12 that samples X1, X2, and X3 (fresh lipsticks) got superimposed on samples L35, L7, and L23 respectively. Thus, these unknown samples got correctly linked to its original source. And, sample Y1 and Y2, which were additionally purchased, did not superimpose itself on any samples, and were discriminated. While sample Z2 (smudge on plastic substrate) got superimposed on selected sample L16 (correctly linked with source), samples Z1, and Z3 which were the spectra of lipstick smudges on substrates: cotton cloth and paper respectively, did not get superimposed on samples L4 and L19 as expected, though visual examination indicated correct identification (e.g. Fig. 10). This could be due to noise generated in the spectra of samples. As lipsticks could be encountered as transferred evidence on different substrates, more validation studies are required for linking the lipstick smudges on different substrates to their

initial source of origin. Also, in future studies, continuous monitoring of lipstick smudges on various substrates exposed to different environmental conditions can be carried out. Conclusions In the present study, ATR-FTIR spectroscopy was effectively utilized for the discrimination of lipstick samples. The samples were analyzed in a non-destructive and rapid manner. Repeatability results were obtained using this technique and no chemical reagents for sample preparation were involved. As visual comparison of spectra could involve bias interpretation, the data of spectra were fed into chemometric tools such as PCA and LDA. These tools helped in handling huge spectral data, and assisted in objective interpretation of the result. The discriminating power of PCA for the samples in the current study was found to be 100%. In order to investigate whether different series of same manufacturer got classified into their respective group, PCA-LDA was performed. Through PCA-LDA analysis, it was found that some samples got misclassified: L16, L17, L18, L26, and L27 as G1, G7, G3, G5, and G3 respectively. The obtained accuracy of the classification was 81.48%. The current research methodology utilised was also validated by blind testing of samples. Samples (X1, X2, and X3), which were randomly selected got superimposed on their respective source of origin and samples Y1 and Y2 which were additionally purchased (not a part of training data set) did not superimpose itself in any of the samples, but got differentiated from the rest of the samples. Samples Z1 (L4), Z2 (L16), and Z3 (L19) were selectively chosen, and while Z2 got correctly linked (lipstick smudge on plastic substrate), the other two samples Z1 and Z3 could not be linked to its source of origin. More studies are required to validate the present methodology, particularly with respect to linking lipstick smudges on substrates (especially porous substrates) with its source of origin. The effect of lipstick smudged substrate exposed to various environmental conditions on analyses was also conducted in this study. A set of lipstick samples on selected substrates such as cotton cloth, tissue paper, plastic, and glass

were left under room temperature and outdoor environmental conditions. Result shows that only the samples on plastic substrate under room temperature could be linked to its source of origin. The rest of the samples could not be linked to its source of origin. The major interferences were dust and fungal like material, and also evaporation of components in lipstick contributed to the incorrect identification of lipstick samples. None of the samples kept in outdoor environment could be linked to its source of origin. Thus, in forensic caseworks, the best analysis can be performed when the samples are recovered at the earliest time. The research methodology utilized in the present study will potentially assist in questioned versus known comparison of lipsticks by providing a statistical basis on which the examiners can support their findings. However, more research is required for validating the present research methodology, and more studies should be carried out to link the smudges of lipsticks on substrates with their source of origin.

Abbreviations TLC

— Thin Layer Chromatography

HPLC

— High Performance Liquid Chromatography

GC

— Gas Chromatography

GC-MS

— Gas Chromatography-Mass spectroscopy

NAA

— Neutron Activation Analysis

ATR-FT-IR

— Attenuated Total Reflectance-Fourier Transform-Infrared Spectroscopy

PCA

— Principal Component Analysis

LDA

— Linear Discriminant Analysis

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Fig. 1 Typical spectrum of lipstick represented by sample L8

Fig. 2 Homogeneity test represented by sample L1

Fig. 3 Intra sample variation test represented by sample L2

Fig. 4 Precision test represented by sample L10

Fig. 5 Scree plot

Fig. 6 PCA score plot of all the investigated lipstick samples using PC-1 and PC-2

Fig. 7 PCA score plot of all the investigated lipstick samples using PC-1 and PC-4

Fig. 8 loading plot of PC-1 and PC-4

Fig. 9 Representative overlay ATR-FTIR spectra of fresh lipstick L1, and the smudge on substrates such as cotton, plastic, tissue paper, and glass.

Fig. 10 Effect of eating habits and lipstick wear exposure to environment for one day

Fig. 11 Representative overlay ATR-FTIR spectra of fresh lipstick L1 after 7 months at room temperature and outdoor environment on substrates such as a) cotton b) plastic c) tissue paper and d) glass.

Fig. 12 Blind test to check the validity of PCA method

Table 1 Description of lipstick samples procured for the present study Sample Manufacturer code L1 ADS L2 ADS L3 ADS L4 Color castle L5 Color castle L6 Color castle L7 Love lipstick L8 Love lipstick L9 Love lipstick L10 Blue heaven L11 Blue heaven L12 Blue heaven L13 Color 18 L14 Color 18 L15 Color 18 L16 Aily L17 Aily L18 Aily L19 Mearl L20 Mearl L21 Mearl L22 Neckline L23 Neckline L24 Neckline L25 Fashion L26 Fashion L27 Fashion L28 Divine L29 Le Lady L30 Kiss beauty L31 Color 18 L32 Color alive L33 Moist lips L34 Heng Fang L35 Chilexy L36 Agro L37 ADS L38 Aishali ‘—’ indicates not available

sample number 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 03 01 01 01 01 01 01 01 01 01 01 01

series number — — — 06 102 103 Pineapple strawberry orange 13 01 07 31 29 09 003 040 038 3 8 4 A-12 A-71 A-8 M-049 M-126 M-108 118 — 4 08 — — 20 — — — —

comment Mini talk. Long-lasting Mini talk. Long-lasting Mini talk. Long-lasting — — — Herbal Herbal Herbal Walk free Walk free Walk free Lips therapy Lips therapy Lips therapy — — — — — — Lips fashion Lips fashion Lips fashion Fancy lipstick Fancy lipstick Fancy lipstick — Lipstick BB. Lipstick moisturized — Sweet heart — Experienced. Sheer gloss — Moisturized lips — Baby lips

Table 2 Results of classification obtained by PCA-LDA model Lipstick L1, L2,L3 L4,L5,L6 L7,L8,L9 L10,L11,L12 L13,L14,L15 L16,L17,L18 L19,L20,L21 L22,L23,L24 L25,L26,L27 TOTAL

Group G1 G2 G3 G4 G5 G6 G7 G8 G9

correct 3 3 3 3 3 0 3 3 1 (L25) 22

incorrect (classified as) 0 0 0 0 0 3 (G1,G7,G3) 0 0 2 (G5,G3) 5

% correct classification 100 100 100 100 100 0 100 100 33.33 81.48

Table 3 Effect of substrates on sample identification Lipstick code cotton cloth  L1  L2  L10  L16  L19 “” indicates correct identification

Wavenumber (2000 cm-1-600 cm-1) tissue paper plastic          

glass     

Table 4 Effect of environmental conditions on sample identification Wavenumber (2000 cm-1-600 cm-1) Room environment outdoor environment cotton tissue plastic glass cotton tissue plastic glass cloth paper cloth paper  L1 o x x x x x x  L2 x x x x x x x  L10 o x x x x x x  L16 o x x x x x x  L19 o x x x x x x “” indicates correct identification “x” indicates incorrect identification “o” some peaks were found missing (could not comment with regard to source of origin). Lipstick code

Highlights 

Analysis of 38 red lipsticks of 20 different manufacturers

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Objective interpretation of results using chemometric methods

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100% discrimination of samples utilising PCA (principal component analysis)

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81.48% classification accuracy using PCA-LDA approach

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Study on the effect of substrates and environmental conditions

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Validation study on the current research methodology utilised