Materials
Materials used in this study were canvas shoes, 100% cotton swabs (EXCUE brands), silica gel 60 (Merck & Co.), elastic-plastic purchased from the local supermarket. Acetone, n-hexane, methanol, isopropyl alcohol, and dodecanoic acid standard were purchased from Sigma Aldrich, UK.
Operating conditions for GC-FID
Method for VOCs analysis from the previous study on body odour analysis was referred and further optimised to improve the detection of the compounds (Pickett, 2017). Gas chromatography (GC) coupled with flame ionisation detector (FID) was utilised to analyse the shoe odour. The GC was equipped with G4513A Series Autosampler (Agilent Technologies) and Agilent J & W 19091 J-413 HP-5 fused-silica capillary column (30 m × 0.25 μm × 0.320 mm) with nitrogen as the carrier gas (flow rate, 1.0 mL/min). The inlet temperature was set at 300 °C. The initial oven temperature was held for 2 min at 40 °C then ramped at 25 °C/min until it reached 200 °C and held for 5 min and another 2 min for post-run. The detector was set up at 300 °C. The total run time was 12.5 min. The Chemstation software (revision B.04.02) (Agilent Technologies, Santa Clara, CA) was used for data acquisition and processing.
Sampling methods
Two sampling methods were tested, direct extraction with solvent and air passive sampling in order to determine the best sampling strategy for extraction of odour from the shoe. An old shoe was examined in this study, and the inner sole was divided into two areas for sampling using the respective methods.
Direct extraction with a solvent method
The inner sole of the old shoe was directly swabbed for 10 min with a cotton bud that was initially soaked in 70% isopropyl alcohol. The solvent employed for the extraction was a mixture of 70% acetone and 30% n-hexane. The cotton bud was cut and deposited into a clear glass vial and dissolved in 2 mL mixture of acetone—n-hexane solvent solution. The negative controls of neat swabs with each solvent were also analysed. The extracted sample was left for 10 min to maximise the extraction of VOC compounds. Five hundred microliters of the liquid sample was pipetted into a 2 mL GC vial, and 1 μl of the sample was injected into the GC for analysis. Other solvent mixtures, namely acetone, n-hexane and methanol, were also tested in order to determine the suitable solvents to be used for extraction (Rajan, 2015).
Air passive sampling method
Two hundred milligrams of silica gel powder was weighed and placed inside the old shoes. The shoe was wrapped and sealed tightly with an elastic-plastic and heated inside the hot air oven (Fig. 1) to avoid the evaporation of VOCs to surroundings during the heating process. The oven was set to 60 °C, and the shoes were left inside the oven for 1 h. After 1 h, the shoe was taken out, and plastic was removed to collect the silica gel powder. The silica gel was then deposited into a clean glass vial and spiked with 1.5 mL of acetone. The vial was shaken vigorously for 5 min, and the extracted sample was filtered into a GC vial using a 0.45 μm PTFE syringe filter attached to a 5 mL syringe filter to remove the small particle powder. The negative control of wrapped neat new shoe that contained silica gel was also analysed. The extracted solution was then analysed using GC-FID. A similar method was also applied by using other solvents such as methanol and hexane (Pickett, 2017).
Recovery
The recovery study was conducted as part of the extraction process to determine the effectiveness of the extraction method. A new shoe was analysed for the purpose of the recovery study. Extraction was carried out using passive air sampling. A neat blank shoe contained 200 mg silica gel powder was spiked with 25 mg/mL of the dodecanoic acid in the insole area and wrapped tightly with an elastic-plastic wrapper. Dodecanoic acid is a volatile compound that presents on human skin. The shoe was heated at 60 °C for 1 h. Silica gel powder was then extracted with 1.5 mL of a suitable solvent, i.e. methanol, and pipetted to a GC vial using a PTFE syringe filter attached to a 5 mL syringe filter. The extract was analysed using GC-FID with the analytical parameters previously established. The spiked sample was analysed in triplicate, and the concentration of the spiked sample was calculated from the calibration curve. The calibration curve was constructed using five concentration levels (1 mg/mL to 20 mg/mL) of dodecanoic acid standard solutions. The limit of detection (LOD) was estimated using the standard determination method, LOD: 3Sa/b; Sa is the standard deviation of the response while b is the slope of the calibration curve.
Analysis of real shoe odour samples
Ten volunteers (five adult males and five adult females aged 31.1 ± 8.7) were provided with two pairs of new canvas shoes, which were classified as pair 1 and pair 2 and labelled with initials of the subjects (example, MA1 & MB2). In order to conduct the study, human ethical approval was obtained from The Human Research Ethics Committee (JEPeM) Universiti Sains Malaysia (USM) Kubang Kerian, Kelantan (USM/JEPeM/19030200).
The test was conducted for 2 weeks. Subjects were asked to wear pair 1 for a week. Subjects were also instructed to wear the shoes during strenuous activities such as jogging, playing football or brisk walking for 2 h per day to maximise the production of sweat and increase the concentration of odour trapped in the shoe. The subjects were not allowed to wear socks or any lotion, cream, or anything onto the feet before and during the activities. During the 1 week of the experimental period, the shoes were stored inside a zipper storage plastic bag at room temperature every time the subjects completed their activities.
After 1 week of sample collection, the second pairs were given to the subjects while the first pairs were collected for sample extraction. Subjects needed to wear pair 2 for following 1 week and performing the same strenuous activities. Negative control (neat new shoe), as well as the two pairs of worn new shoes from each subject, was extracted using a passive air sampling method as described earlier, and the extract then analysed using GC-FID.
In total, there were 13 sets of the odour sample profiles to be subjected as the dataset for statistical analysis. Subjects A, B, C, D and E are males, and subjects F, G, H, I, and J are females. Three pairs of old shoes were collected from subjects A, B, and F as blind samples. These shoes were labelled as old shoes 1, 2 and 3, respectively, and extracted and analysed using the same procedure. The results of the blind samples were assessed to determine the consistency and accuracy of the predictive model in chemometrics analysis.
Statistical analysis
Principal Component Analysis-Discriminant Analysis (PCA-DA) was conducted to analyse the dataset utilising selected peaks in the chromatogram. PCA is a multivariate statistical method that enables the reduction of the dimensionality, which reconstructs the original dataset by creating a linear combination of variables. Upon the data transformation, the PCA software creates a new independent variable known as a principal component, which contains much of the original data set. A score plot for the first two or three principal components is often used to visualise the differences between samples that can be represented either in two-dimensional (2D) or three-dimensional (3D).
The score plot provides a more objective way of comparing variations between samples by showing the clustering of the sample. The closer the distance between a sample and forms a cluster on a score plot, the more similar they are according to the selected principal component. The first two components account or the largest possible variance in the data set. Discriminant analysis (DA) is a way to build a predictive model of group membership, which can then be applied to new cases or observations.
Prior to PCA, data of the selected peak undergone a pre-treatment procedure or pre-processing by normalisation of peak area to the total area of the selected peaks in each chromatogram (Ringnér, 2008). The analysis was conducted using the Minitab® software v.16 (Minitab Incorporated, State College, USA).