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This study proposed a proof-of-concept methodology for the investigation of paper samples by utilizing ATR-FTIR spectroscopy supported by chemometric methods. An attempt on the analysis of aged writing papers due to the degradation of their chemical constituents with time has been made. The degradation of its constituents with time is directly linked to the age of the paper since its production. This further links the questioned document with the fraudster, and sometimes it becomes crucial information in the court of law to reach to conclusion. The present study offers a method to discriminate, and estimate the age of unknown writing paper. The statistical models like Curve Estimation (CE), multiple linear regressions (MLR), and partial least squares regression (PLSR), are built to predict the age of the papers. The maximum dating errors are in the CE model whereas, MLR and PLSR models show excellent age estimation of unknown paper with minimum error of ±5 days and ±3 days in actual and estimated date of artificial ageing respectively. The present methodology is expected to provide valuable insight for answering the queries related to the date/age of the suspected document documents/paper artefacts. [ABSTRACT FROM AUTHOR]

Abstract The potential to ascertain the origin and aging of bloodstains have various important applications in the forensic serological investigation. The individualization of bloodstain is necessary as both human and animals can be involved in the crimes. The foremost advantages of these types of investigation are: the expert significantly differentiates between human and animal blood which ultimately helps in the decipherment of criminal associated with the crimes; the aging of bloodstain assists in the determination of approximate time and date of incidence of crime. In recent time, significant advancement in analytical methods has been done to investigate the complex evidence collected from crime scene such as bloodstain. Along with modern analytical methods, the multivariate methods are also obtaining popularity in forensic science, especially in the bloodstain investigations. This review emphasizes the importance of analytical and chemometric models that have been utilized for the identification and aging of bloodstains. The reliability and sensitivity of these models are compared. Highlights • Advanced analytical and chemometric methods for bloodstain investigation are summarized. • Most of the studies utilized spectroscopy methods especially Raman and FTIR. • PLS-DA and regression-based modeling have been widely used for discrimination and dating studies. • New models like SVM and ANN provide better results than PLS-DA in discrimination as well as aging. [ABSTRACT FROM AUTHOR]

This review represents a detailed discussion of the multivariate methods used in the examination of forensic exhibits; their advantages, disadvantages, and efficiency are compared. The last decade has seen the application of the chemometric methods combined with analytical techniques for characterization and discrimination of samples, which leads to the informative and representative examinations of the samples. Many research articles with reference to the use of chemometrics in forensic science have been published. This review has been divided into various sections which include chemometrics, its history, multivariate methods, and the application of chemometrics in various disciplines of forensic science. It is suggested that these new techniques and mathematical/statistical methods should be utilized in forensic science casework to get statistical confidence in the results. [ABSTRACT FROM AUTHOR]

Among various trace evidence, the soil is very crucial evidence because it can link the suspect with the crime and crime with its geographical region. Based on this hypothesis, the aim of present research is to characterize, differentiate and classify the soil samples collected from various geological regions of northwestern India via using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics. The organic and inorganic parts of surface and depth soil samples are successfully characterized. Sieving and heating of soil in a muffle furnace (650 °C) affect the spectral features considerably. The differentiation of soil samples is done by utilizing two approaches i.e. qualitative analysis and multivariate analysis. Both approaches provide a high discriminating power (i.e. qualitative analysis, surface = 99.35%, depth = 97.38%, and multivariate analysis, surface = 100%, depth = 100%). A classification model based on canonical discriminant function analysis is also built for grouping of soil to its particular geographical region. The developed model provides 100% correct classification of soil samples after the leave-one-out cross-validation. Therefore, the current study provides useful methods of soil analysis which can further be utilized by soil as well as forensic expert dealing with such cases. [ABSTRACT FROM AUTHOR]

The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV–Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV–Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications. [ABSTRACT FROM AUTHOR]

The multivariate analysis methods have recently gained high popularity within the field of forensic sciences because of their high accuracy and precision. The accurate and unbiased results are the preliminary need for a forensic investigation. The aim of the present work is to examine the marker pen inks which are widely used in various places like documentation in parcels, for photograph attestation, and also as a study material in the classroom. This research is focused on the three important aspects; first is to characterize the marker inks, second, to discriminate permanent marker and whiteboard marker inks using destructive (extracting of ink samples from paper substrate) and nondestructive (without ink extraction) techniques of ultraviolet-visible absorbance combined with peak identification examination as well as chemometric methods, and the third is to build a classification model for permanent and whiteboard marker inks. It is concluded that the chemometric method, that is, principal component analysis provides better discrimination power as compared to visual examination. However, destructive and nondestructive approaches give almost similar discriminating power. The classification model developed using linear discriminant analysis provides 87.5% of correct classification of marker ink samples. The method can further be used to formulate a statistical model for the determination of class/group of the other forensic exhibits. [ABSTRACT FROM AUTHOR]

The present research is focused on the analysis of writing inks using destructive UV–Vis spectroscopy (dissolution of ink by the solvent) and non-destructive diffuse reflectance UV–Vis-NIR spectroscopy along with Chemometrics. Fifty seven samples of blue ballpoint pen inks were analyzed under optimum conditions to determine the differences in spectral features of inks among same and different manufacturers. Normalization was performed on the spectroscopic data before chemometric analysis. Principal Component Analysis (PCA) and K-mean cluster analysis were used on the data to ascertain whether the blue ballpoint pen inks could be differentiated by their UV–Vis/UV–Vis NIR spectra. The discriminating power is calculated by qualitative analysis by the visual comparison of the spectra (absorbance peaks), produced by the destructive and non-destructive methods. In the latter two methods, the pairwise comparison is made by incorporating the clustering method. It is found that chemometric method provides better discriminating power (98.72% and 99.46%, in destructive and non-destructive, respectively) in comparison to the qualitative analysis (69.67%). [ABSTRACT FROM AUTHOR]

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000 cm − 1 wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400–2000 cm − 1 , 2000–4000 cm − 1 and 400–4000 cm − 1 were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000–4000 cm − 1 . Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories. [ABSTRACT FROM AUTHOR]

The derivative diffuse reflectance UV-vis-NIR spectroscopy combined with the multivariate methods are utilized for the discrimination and classification of the soil samples collected from the north-western part of India. The acquired spectra reveal the presence of different organic and inorganic minerals such as humic acid, fulvic acid, hematite, etc. in varying amounts. The differentiation/segregation among soil samples is achieved by peak comparison and chemometric methods like clustering algorithm and principal component analysis (PCA). Among these, the PCA method gives clear discrimination of soil samples. The developed PCA model is further validated by analyzing unknown samples for the prediction to their respective clusters significantly. Principal component linear discriminant analysis (PC-LDA) based discriminant model is developed to classify the unknown soil samples to its respective groups. PC-LDA based model reveals 95 % accurate clustering of the soil by the leave-one-out cross-validation approach. [ABSTRACT FROM AUTHOR]

Cosmetic products such as sunscreens may often be encountered in forensic investigations as traces left on tissue paper, apparels, drinkware, painted exterior, or various alternative surfaces. The pilot study aimed at efficiently using Infrared spectroscopy coupled with chemometrics to cater to unbiased, rapid, and non-destructive identification of sunscreens which will aid various forensic investigations soon. In the present research, a total of 109 sunscreen samples were analyzed using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy. The physicochemical data from the FTIR instrument was then subjected to principal component analysis (PCA), which successfully distinguished most of the samples based on their spectral information. The trained model resulted in clear segregation of unknown sunscreen samples. This could provide an outstanding level of confidence during the conduction of 'questioned versus known' comparisons of similar sunscreens and will give the details of the manufacturer, thereby, helping in rounding off the suspects. Unlabelled Image • 109 sunscreen samples were analyzed using ATR-FTIR & Chemometric methods. • No prior sample preparation needed for the devised method of characterization. • The trained model was validated using unknown samples. • The trained model resulted in discrimination accuracies to 100%. • First such study on sunscreen stains identification utilizing IR and Chemometric methods. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • 1st study for Kohl samples characterization and discrimination through ATR-FTIR and Chemometric. • Kohl depicts presence of paraffin compounds, talc, mica, and silica compounds, aromatic compounds, etc. • The effects of heating is observed in the form of shifting and extinction of spectral peaks. • This study provides the maximum discrimination by multivariate and t-statistics altogether. Abstract In the present study, 33 Kohl samples were purchased from the local market of the north-western region of India and analyzed by using ATR-FTIR spectroscopy coupled with multivariate methods. All Kohl samples were characterized by a spectroscopic method and discriminated by chemometric tools. The chemical composition of the Kohl samples confirmed the presence of various organic compounds like hydroxyl group, aliphatic compounds, paraffin compounds, talc, mica, and silica compounds, aromatic compounds and −CH group. The effect of heating on the Kohl sample was also determined by FTIR technique. The discriminating power (DP) was calculated by both visual inspection and multivariate methods. The multivariate methods combined with t-statistics delivered a higher value of discriminating power i.e. 100% which was an improvement on the 99.43% discrimination power of visual comparison method. The developed method has been validated by analyzing five duplicate samples and predicted them to their respective brands significantly. This has been the first study on Kohl discrimination through FTIR and multivariate method. It could help in the forensic examination to link the criminals where Kohl stains have been transferred from the victim to the perpetrator and vice-versa during the struggle in sexual assault cases or other forensic cases where the Kohl could be encountered as evidence. [ABSTRACT FROM AUTHOR]

Abstract Thin films of various polymers are currently used for wrapping various food products and illicit drugs worldwide. In thin films, polyvinyl chloride is the third most widely used polymer after the polyethylene and polypropylene. These films usually contain harmful plasticizers such as adipates, phthalates, and citrates along with other additives. Plasticizers adversely affect the human health and therefore, their migration in foodstuff must be monitored carefully. By considering all these facts, this study summarizes the utilities of non-destructive ATR-FTIR spectroscopy in the identification of base polymer as well as plasticizers in various cling films and application of multivariate analysis in the identification and classification of the cling films to their respective groups. In the present research, a considerable transfer of plasticizers from the wrapping material is observed. A spectral library is developed for all 22 cling film samples for further comparison of the unknown sample. The obtained results are promising, especially for classification purposes. The multivariate method significantly provides 100% of cross-validation classification along with 99.13% discrimination. In this study, we have developed a method to compare or link a cling film which somebody uses and found that there is a transfer of plasticizers and other additives into the food and if the manufacturing company disown that this specific cling film does not belong to our company. In such type of cases, this method could link the suspected cling film to their manufacturers with precision and accurateness. The chronic effect of plasticizers on human health can also be linked to the type of cling film the accused was using consistently. Graphical Abstract Unlabelled Image Highlights • Migration of plasticizers/additives are observed in Group II and Group III cling film samples. • Chemometric method combined with FTIR provides 100% leave-one-out cross validation in the classification. • PCA analysis is able to discriminate 99.13% total samples. • This study offers a method to link a suspected cling film with its manufacturer. [ABSTRACT FROM AUTHOR]

[Display omitted] • Study of cosmetics creams using combination of non-destructive ATR-FTIR spectroscopy and Chemometric methods. • First report for identification between cream samples using this method. • No sample preparation required- sample over substrate can be directly analyzed. • PCA and PLS-DA are used as chemometric tools for the discrimination and classification between cream samples. • Validation of the developed method using unknown samples. Facial creams are considered to be essential beauty items and are used by both females and males on an everyday basis. These can be encountered as an evidentiary material in criminal investigations, particularly in cases related to sexual and physical assaults against women. These are found in trace amounts and therefore their analysis is difficult and also, it must be through non-destructive methods. In the present work ATR-FTIR spectroscopy was employed for the discrimination of 57 samples of face creams out of which 31 were non-herbal and 26 were from herbal category. Visual analysis of the obtained Spectra was done for discrimination purposes but the method was prone to human error and laborious too. The spectroscopic results were analyzed with PCA (Principal Component Analysis) and PLS-DA (Partial least square discriminant analysis) methods. A segregation of samples was seen in the PCA plots to some extent. The class separation and prediction of the samples was performed using PLS-DA method. A good classification was achieved between herbal and non-herbal samples using PLS-DA method. Further, validation of the model was also performed by testing 10 unknown samples. [ABSTRACT FROM AUTHOR]

• Study of eye cosmetics using non-destructive ATR-FTIR spectroscopy & Chemometrics. • First report for identification of eyeliner and mascara samples using this method. • No sample preparation required- sample over substrate can be directly analyzed. • PCA and PLS-DA for discriminating and classifying eyeliner and mascara. • Method developed was also validated for unknown samples. • Accuracy, sensitivity, and specificity of 95%, 0.9, and 1.0 achieved respectively. Eye cosmetics are used by most females and thus, can be an important corroborative forensic evidence in cases of crimes against women. These cosmetics can also sometimes be used to write suicide notes, threatening letters, and anonymous letters on a variety of substrates like skin, fabrics, paper (tissue paper or any writing paper) etc. Their traces can establish link of the perpetrator with the victim and the scene, and thus be an important corroborative evidence in various crimes. This paper reports the analysis of 102 cosmetic samples (62 different eyeliner samples from 37 brands and 40 mascara samples from 24 brands) using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy. Chemometric analysis was performed utilizing the Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). These methods have a higher discrimination ability than that of the visual spectral comparisons. In addition, the model is validated using 15 unknown eyeliner and mascara samples. The validation results show 95% accuracy making the model significant. Further, the sensitivity and specificity of the model are 90% and 100% respectively which makes the model apt for forensic casework. We used differences in peak patterns, their intensities, and the presence or absence of particular frequency in the fingerprint region for the discrimination of eyeliners and mascaras. The present work demonstrates a quick, non-destructive, robust and cost-effective method for the discrimination of eye cosmetics in cases of crime against women, as well as other forensic case work. [ABSTRACT FROM AUTHOR]

• Quick and non-invasive method for human gender sorting using FTIIR spectroscopy. • No prior sample preparation. • Pre-treatment methods like normalizing (SNV) and derivative spectra were performed. • Classification rate of derivative data is 100% for female and 90% for male. • First report on gender estimation through fingernail clippings. We report chemometric analysis of ATR-FTIR spectroscopy for classification and prediction of sex of male and female nail clippings from 100 individuals. An effort has been made for differentiation of fingernail clippings (50 each from males and females of age between 15 and 60 years). The spectral features through ATR-FTIR revealed the presence of prominent amide A & B band, amide I, amide II and amide III bands in the fingerprinting region. These bands confirmed the presence of keratin protein which is the main component present in fingernail clipping. PCA and PLS-DA were used for exploratory and predictive data analysis respectively. Before chemometric analysis, pre-treatment methods like normalization and obtaining derivative of spectra were performed on the raw data of the IR spectra. It was found that PCA could not differentiate the sexes well from these spectra, as such was only used for exploratory purposes. However, PLS-DA has been found to provide excellent classification and prediction with a high true positive rate for classification of sex. The correct classification rate from the normalised derivative data has been found to be 100% and 90% for females and males respectively, which is quite impressive from the forensic examination perspective. PLS-DA analysis after ATR-FTIR spectroscopy proves to be a suitable method for such type of forensic examination. This approach is a quick, non-invasive, and non-destructive method and can be used as an alternative technique to other conventional techniques. [ABSTRACT FROM AUTHOR]

Kajal, also known as Kohl (Arabic name) a cosmetic, is used for the beautificationof eyes and face as a whole. It can serve as an important corroborative evidence in various crimes against women and can also be used as a writing instrument to write the anonymous letters, threatening notes, suicide letters on a variety of substrates such as cotton cloth, tissue paper, tissue wipes, skin etc. 40 Kajal samples from 33 different brands were collected and analyzed using Attenuated Total Reflectance Fourier Transform Infrared (ATR FT-IR) Spectroscopy with advance statistical and computational tools. The present research investigated the application of this technique for the differentiation of locally manufactured Kajal based on the differences in the peak patterns, frequencies, and strengths of peak exhibited within the fingerprint region. The blind test was conducted with four unknown samples which were pretended to be unknown to the analyst and it was observed that all the unknown samples were predicted correctly with their respective classes. Effect of substrates and ageing were also studied under similar set of experimental conditions. This technique has been proven to be of high significance with complete non-destructive nature requiring minimal or no sample preparation and high repeatability. [ABSTRACT FROM AUTHOR]