Tobacco Samples Research Articles

Post-consumption waterpipe tobacco waste as an unrecognized source of toxic metal(loid)s leachates into aquatic environments

Waterpipe is a common form of tobacco smoking, and recently, its use has been increasing globally. Therefore, concern arises regarding the large quantity of post-consumption waterpipe tobacco waste produced and released into the environment and which can contain high levels of dangerous pollutants such as toxic meta(loid)s. This study reports the concentrations of meta(loid)s in waste from fruit-flavoured and traditional tobacco smoking as well as the release rate of these pollutants from waterpipe tobacco waste into three types of water. These include distilled water, tap water, and seawater and contact times ranging from 15 min to 70 days. The mean concentration levels of Ʃmetal(loid)s in waste samples of Al-mahmoud, Al-Fakher, Mazaya, Al-Ayan brands and traditional tobacco brands were 212 ± 92.8, 198 ± 94.4, 197 ± 75.7, 214 ± 85.8 and 40.6 ± 16.1 μg/g, respectively. The concentration levels of Ʃmetal(loid)s in fruit-flavoured tobacco samples were significantly higher than for traditional tobacco samples (p < 0.05). It was found that waterpipe tobacco wastes leached toxic metal(loid)s into different water samples with similar trends. In addition distribution coefficients showed that most metal(loid)s are highly likely to enter the liquid phase. The concentration levels of these pollutants (except Ni and As) in deionized water and tap water exceeded the surface fresh water standards for sustaining aquatic life during long contact time (up to 70 days). In seawater, concentration levels of Cu and Zn exceeded the recommended standards for maintaining aquatic life in the sea. Therefore, due to the possibility of contamination by soluble metal(loid)s through disposal of waterpipe tobacco waste in wastewater, there is concern that these toxic chemicals might enter the human food chain. Appropriate regulatory measures for disposal of waterpipe tobacco waste are necessary to prevent environmental pollution due to discarded wastes into aquatic ecosystems.

Assessment of pH and Copper Content among Raw and Commercial Areca Nut Products, Contributing Factor towards Oral Submucous Fibrosis

Introduction: The increased prevalence of oral submucous fibrosis (OSMF) in the last few years relates to the increased consumption of areca nut(AN) products. OSMF is a premalignant condition and risk to progression to oral cancer is more when AN is chewed along with tobacco. Moreover, high copper content in AN is responsible for fibroblast dysfunction and fibrosis. This study was conducted with aim to assess and compare pH and copper content of raw AN and popular Indian commercial AN based (with and without tobacco) products. Method: Six samples each of twelve different brands of AN based commercial products i.e. six without tobacco (pan masala) and with tobacco were analyzed for pH and then the samples were dried, and powdered for estimation of the copper content. Results: For the six raw areca nuts (sample 1-6), the pH was found to range from 3.06±1.08 to 5.04±0.81, among the six non tobacco containing samples (sample 7-12), the pH was found to range from 6.03±1.08 to 9.09±0.81, and for six tobacco containing samples (sample 13-18), the pH was found to range from 9.18±0.90 to 11.07±0.09. The mean copper concentration among raw areca nut samples (sample 1-6) was 4.05±0.18 μg/g, among non-tobacco containing samples (sample 7-12) it was 10.17±1.08μg/g and among tobacco samples (sample 13-18),it was 18.09±1.08 μg/g (p&lt;0.001). Conclusion: High copper content present in quid and commercial AN may be a causative factor for an increased fibrosis in OSMF, our findings need evaluation by further research and standardization.

An advanced variable selection method based on information gain and Fisher criterion reselection iteration for multivariate calibration

The difficulty of analyzing high-dimensional data makes dimensionality reduction essential, and variable selection is widely used as a dimensionality reduction method to improve the interpretability of models. A variable selection method based on information gain and Fisher's criterion reselection iteration (IFRI) is proposed in this paper. It selects variables that have strong associations with the property of interest by two classical feature selection functions to improve interpretability of the selected variables. At first, information gain was employed to pre-select “global” feature variables with strong ability to distinguish between different classes, and Fisher's criterion was applied to re-select key variables further from the selected “global” variables that enable larger inter-class variance and smaller intra-class variance for the samples. Pearson correlation coefficients were then applied to eliminate variables with strong linear correlation and a series of subsets were obtained iteratively. At the end, cross-validation (CV) was used to calculate the obtained subset, and the one with the lowest root mean square error of cross-validation (RMSECV) was considered optimal. Combining with partial least squares (PLS), it was applied to the analysis of nicotine and total sugar content in tobacco samples. By comparing and validating with two representative variable selection algorithms, CARS and MC-UVE, IFRI has been demonstrated to be an effective and applicable method to establish high-performance models by selecting a few key variables. Differing from most methods, IFRI does not need to depend on the PLS model parameters in the process of variable selection, which makes it more interpretable. Moreover, the selected variables by IFRI are reproducible for the same dataset. Apparently, the principle of the method makes it not limited to spectral data and can be applied to the variable selection of different types of high-dimensional data by combining it with other modeling methods, for example it can be combined with qualitative discriminant models to classify tobacco or used to select critical chemical components affecting the tobacco quality.

Moisture-adaptive corrections of NIR for the rapid simultaneous analysis of 70 chemicals in tobacco: A case study on tobacco

Tobacco is one of the most widely cultivated non-food cash crops worldwide, and the quality of tobacco procured from different geographical locations varies considerably. This study proposes a comprehensive strategy for investigating tobacco quality using near-infrared (NIR) prediction models with moisture-adaptive corrections. This strategy enables the rapid and efficient quantification of 70 chemicals in tobacco by reducing the effect of moisture on the NIR spectra of tobacco samples. Additionally, this strategy has been proposed for the geographical discrimination and part identification of tobacco samples, with the Mahalanobis distance analysis, the accuracy of predicted values is higher than 81.5%. This study confirms that the tobacco chemical composition from different regions in China is inconsistent.

Effects of aroma additives on the release of smoke during the pyrolysis of reconstituted tobacco

The effects of typical acid and alkaline aroma additives on the release characteristics of aroma components from reconstituted tobacco were studied. In this study, the pyrolysis of reconstituted tobacco samples loaded with different aroma components was carried out, and the aroma components in the smoke were analyzed by the GC-MS. The results showed that adding a certain amount of acid aroma components in reconstituted tobacco could promote the release of aroma components in smoke. However, excessive acid aroma additives could inhibit the Maillard reaction to decrease the formation of additional aroma components during pyrolysis. The addition of ethanol in reconstituted tobacco could promote the release of olefin and acid aroma components in smoke. Alkaline aroma additives (sodium bicarbonate and potassium carbonate) could promote the release of all kinds of aroma components in smoke, because potassium and sodium ions could catalyze the pyrolysis of tobacco, which was preferred to generate aroma components. According to these results, the best promoting effect of the aroma components released in smoke was performed by adding 0.078 wt% of potassium carbonate and 0.01 wt% of citric acid in reconstituted tobacco.

Analysis of alkaloids and reducing sugars in processed and unprocessed tobacco leaves using a handheld near infrared spectrometer

Near infrared (NIR) spectroscopy calibration models were developed to predict chemical properties of flue-cured tobacco ( Nicotiana tabacum L.) leaf samples using a microPHAZIRTM handheld NIR spectrometer. The sample data set consisted of 348 leaf-bundled samples of upper-stalk flue-cured tobacco leaves collected from an array of cultivars evaluated in multiple locations. Unprocessed leaf samples were intact whole unground leaves collected from curing barns. Processed leaf samples were further dried and ground before scanning. The NIR prediction models for percent reducing sugars, percent total alkaloids, and percent nicotine were very good for processed leaves [r2 (SEP in %) values = 0.98 (0.82), 0.92 (0.17), and 0.92 (0.14), respectively]. The models for the same three variables for unprocessed leaves were also very good, with only slightly lower fit statistics [r2 (SEP) = 0.93 (1.58), 0.87 (0.22), and 0.88 (0.18), respectively). Fit statistics for anabasine NIR models were intermediate with r2 (SEP in %) values ranging from 0.73 (0.003) to 0.76 (0.003), while the lowest fit statistics were observed for anatabine and norticotine with r2 (SEP in %) ranging from 0.49 (0.005) to 0.55 (0.017), respectively, for both unprocessed and processed leaves. Hence, use of a handheld NIR spectrometer would be of more limited value for these variables. The chemical composition of flue-cured tobacco leaf samples for some chemical traits can be directly assessed at the point when the leaves exit the curing barns, thus minimizing the need to dry and grind samples for colorimetric and chromatographic analyses.

Detection of Tobacco Bacterial Wilt Caused by Ralstonia solanacearum by Combining Polymerase Chain Reaction with an α-Hemolysin Nanopore.

Tobacco bacterial wilt is a serious disease caused by the soil-borne bacterium Ralstonia solanacearum (R. solanacearum). Herein, a rapid and purification-free α-hemolysin (α-HL) nanopore-sensing strategy based on polymerase chain reaction (PCR) and lambda exonuclease digestion was established to detect R. solanacearum. A 198-nucleotide-long single-stranded DNA was obtained via asymmetric PCR or the lambda exonuclease-mediated digestion of the PCR product. The DNA fragment produced unique long-lived, current-blocking signals when it passed through the α-HL nanopore. This sensing approach can allow for the determination of R. solanacearum in tobacco samples and can be conveniently extended to other DNA monitoring because of the extremely wide range of PCR applications.

Direct analysis of tobacco specific nitrosamines in tobacco products using a molecularly imprinted polymer-packed column.

Tobacco specific nitrosamines (TSNAs) are highly carcinogenic by-products in tobacco samples, and their presence is regulated by the Food and Drug Administration. Molecularly imprinted polymers (MIPs) are synthetic polymers that have been "imprinted" with a template analyte in a co-polymer system, and can selectively extract analytes from complex matrices. MIPs can be incorporated into online systems, replacing traditional high performance liquid chromatography (HPLC) columns. MIP material specific for TSNAs was packed into an empty HPLC column using a slurry packing technique. The developed method with the MIP-packed HPLC column was validated on a LC-MS/MS system for the quantitation of N-nitrosonornicotine (NNN) and 4- (methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in commercial tobacco products. The method was linear over .1-10 ng/ml (.4-10 μg/g) for NNN and NNK. The limit of detection (LOD) was .03 ng/ml (12 μg/g) and the limit of quantitation (LOQ), .1 ng/ml (.4 μg/g). All column uniformity parameters with the exception of theoretical plate number were within the accepted criteria (% RSD values <15%). Theoretical plate number was <250, owing to the large (50 μm) sized MIP particles. Twenty-six tobacco products contained TSNA concentrations that were consistent with reported literature values. The TSNA-MIP based HPLC column effectively replaced a traditional reverse phase HPLC column, and was used for the direct analysis of nicotine and tobacco products without extensive sample preparation prior to instrumental analysis.

A colorimetric sensor with dual-ratio and dual-mode for detection of nicotine in tobacco samples.

Nicotine (NIC) is a harmful substance, drug, pesticide and chemical that is widely found in tobacco. It has carcinogenic, teratogenic and neurotoxic effects that have raised serious concerns. Herein, a colorimetric sensor with dual-ratio and dual-mode for the detection of NIC in tobacco samples was reported. The localized surface plasmon resonance signals of gold nanoparticles (AuNPs) and AuNPs-NIC are used as dual-ratio signals. The absorbance ratio of NIC to AuNPs or the absorbance ratio of NIC to AuNPs-NIC and the wavelength shift value of AuNPs-NIC are applied as dual-mode. Transmission electron microscopy, energy dispersive spectroscopy, dynamic light scattering spectroscopy, ultraviolet-visible spectrophotometry, cyclic voltammetry, and potentiostatic methods were used to characterize the sensor. Further analysis of NIC was conducted through morphological fitting and theoretical calculations. Under optimal conditions, the sensor shows a wide linear range of 5-500 μM. The detection limits for NIC are 2.48 μM, 1.63 μM and 1.34 μM, respectively. The experimental result shows that the dual-ratio signal of AuNPs and AuNPs-NIC has good selectivity and sensitivity, and can effectively reduce the interference of impurities on NIC detection. And the dual-mode of detection for NIC improves the accuracy and comparability of the result significantly. In addition, the proposed sensor was also applied to test NIC in tobacco samples with satisfactory recovery.

Advances in the Applications of Capillary Electrophoresis to Tobacco Analysis

Background: Capillary electrophoresis (CE) has found a wide range of applications because of its high separation efficiency, low expense, short analysis time and minimal sample volume requirement. The tobacco quality depends on the nature and quantity of numerous substances. CE has been applied in the constituent analysis of tobacco and tobacco products for quality control and tobacco research. Methods: The advances in the applications of CE to tobacco analysis are reviewed. The main subjects cover the separation modes of CE, the detection techniques of CE, sample preparations and the applications of CE in the measurements of various constituents in tobacco samples. In addition, the CE-based metabonomic investigation of tobacco is also introduced. Results: Capillary zone electrophoresis, micellar electrokinetic chromatography, capillary isotachophoresis, capillary gel electrophoresis, capillary electrochromatography and non-aqueous CE have been applied in the determination of a variety of constituents in tobacco and tobacco products. The assayed substances include alkaloids, amines, saccharides, organic acids, inorganic ions, phenols, phenolic acids, flavonoids, amino acids, peptides, proteins, hormones, agricultural chemicals, etc. Conclusion: This review demonstrates that CE is a promising analytical technique in the field of tobacco analysis. It is anticipated that CE will find more and more applications in tobacco investigations.

Feasibility of an NIR spectral calibration transfer algorithm based on optimized feature variables to predict tobacco samples in different states.

The prediction accuracy of calibration models for near-infrared (NIR) spectroscopy typically relies on the morphology and homogeneity of the samples. To achieve non-homogeneous tobacco samples for non-destructive and rapid analysis, a method that can predict tobacco filament samples using reliable models based on the corresponding tobacco powder is proposed here. First, as it is necessary to establish a simple and robust calibrated model with excellent performance, based on full-wavelength PLSR (Full-PLSR), the key feature variables were screened by three methods, namely competitive adaptive reweighted sampling (CARS), variable combination population analysis-iteratively retaining informative variables (VCPA-IRIV), and variable combination population analysis-genetic algorithm (VCPA-GA). The partial least squares regression (PLSR) models for predicting the total sugar content in tobacco were established based on three optimal wavelength sets and named CARS-PLSR, VCPA-IRIV-PLSR and VCPA-GA-PLSR, respectively. Subsequently, they were combined with different calibration transfer algorithms, including calibration transfer based on canonical correlation analysis (CTCCA), slope/bias correction (S/B) and non-supervised parameter-free framework for calibration enhancement (NS-PFCE), to evaluate the best prediction model for the tobacco filament samples. Compared with the previous two transfer algorithms, NS-PFCE performed the best under various wavelength conditions. The prediction results indicated that the most successful approach for predicting the tobacco filament samples was achieved by VCPA-IRIV-PLSR when coupled with the NS-PFCE method, which obtained the highest determination coefficient (Rp2 = 0.9340) and the lowest root mean square error of the prediction set (RMSEP = 0.8425). VCPA-IRIV simplifies the calibration model and improves the efficiency of model transfer (31 variables). Furthermore, it pledges the prediction accuracy of the tobacco filament samples when combined with NS-PFCE. In summary, calibration transfer based on optimized feature variables can eliminate prediction errors caused by sample morphological differences and proves to be a more beneficial method for online application in the tobacco industry.

Microbiome status of unregulated raw tobacco blends for hand-rolling cigarettes (RYO tobaccos)

The research was conducted on 18 samples of RYO tobacco. The density (CFU/g a.d.s.) of three heterotrophic groups of microorganisms and some physical-chemical indicators were determined. The analyses were performed according to classic methods. Quantitative and qualitative changes at the microbiome as a result of disruption of homeostasis in microbial communities and development of secondary succession in the direction of intensive mineralization processes were found. Statistically significant correlation dependences with the physical-chemical parameters were registered. In addition to a potential risk in term of sanitary-hygiene and health aspects, the changes also have a negative impact on the consumer qualities of tobacco blends.

Unraveling the Difference in the Composition/Content of the Aroma Compounds in Different Tobacco Leaves: For Better Use

The composition/content of aroma compounds in tobacco leaves in the different producing areas varies too much, and it is very meaningful to develop advanced analysis techniques to investigate the composition/content-producing area correlation. Here, gas chromatography-ion mobility spectroscopy (GC-IMS) was used to analyze the composition/content of aroma compounds in tobacco samples from eight different producing areas. With this technique, ion mobility spectrum, differential ion mobility spectrum, and fingerprint spectrum were constructed for two-dimensional analysis. Then, the principal component analysis (PCA) and similarity analysis were performed for the eight tobacco samples. The results showed that the GC-IMS can detect 197 volatile aroma compounds in tobacco leaves and 75 of them are well identified. The fingerprint spectrum directly showed the difference in the composition/content of volatile aroma compounds in tobacco leaves from different producing areas. PCA and similarity analysis can clearly distinguish tobacco samples from different producing areas. This work demonstrated that the application of GC-IMS in analyzing the composition/content of aroma compounds in tobacco leaves is efficient. GC-IMS is a very powerful tool to give a direct and visual comparison of the composition/content of aroma compounds in tobacco leaves from different producing areas. The relationship between the composition/content of aroma compounds and producing areas could be established by this advanced technology. This work offers the possibility of planting or grading tobacco with different taste and smell more precisely in the future.

Predicting tobacco pyrolysis based on chemical constituents and heating conditions using machine learning approaches

Tobacco is a special type of biomass that consists of complex chemical constituents. Currently, only global kinetic models have been developed for tobacco pyrolysis, but accurate kinetics considering the effects of the complex chemical constituents and heating conditions have not been well established. To this end, a general tobacco pyrolysis model was developed based on the complex chemical constituents and heating conditions using machine learning approaches. Specifically, chemical analysis and thermogravimetric analysis (TGA) of 49 tobacco samples under a wide range of heating rates were first conducted by experiments and then used to construct a database for the model development. Subsequently, the constructed database was divided into seen and unseen data-sets for the model development and evaluation. General pyrolysis models for single/multiple heating rates were developed from the seen data-set using an advanced machine learning approach, the Extremely Randomized Trees (Extra-Trees, ET). The performances of models were further evaluated on the unseen data-set through comparisons with the experimental data. The results showed that after feature selection based on Pearson correlation coefficient and hyper-parameters optimization, the trained models could accurately reproduce the tobacco pyrolysis behavior on the unseen data with R2>0.967 based on a single heating rate and with R2>0.974 based on all heating rates. In addition, the predicted derivative thermogravimetry (DTG) profiles were integrated to obtain the TGA profiles, and the results agreed very well with the experimental data (R2>0.99).

Triplex Immunostrip Assay for Rapid Diagnosis of Tobacco Mosaic Virus, Tobacco Vein Banding Mosaic Virus, and Potato Virus Y.

Mixed virus infection has increasingly become a problem in the production of Solanaceae crops in recent years; therefore, a fast and accurate detection method is needed. In this study, a novel triplex immunostrip assay was developed for the simultaneous detection of tobacco mosaic virus (TMV), tobacco vein banding mosaic virus (TVBMV), and potato virus Y (PVY). The limits of detection of this novel immunostrip reached 200 ppb (ng/ml), 1 ppm (µg/ml), and 2 ppm for TMV, PVY, and TVBMV particles, respectively. Importantly, no cross-reactivity was observed among TMV, TVBMV, and PVY or to a nontarget virus. When the assay was applied to suspected virus-infected tobacco, tomato, and potato samples collected from fields in Southwest China, samples of single or mixed virus infection were successfully identified. In conclusion, the triplex immunostrip assay provides a fast and easy to use on-site detection method for field epidemiological studies of TMV, TVBMV, and PVY, and for managing diseases that are caused by them.

Metagenomic insights into the changes in the rhizosphere microbial community caused by the root-knot nematode Meloidogyne incognita in tobacco

Root-knot nematode (RKN) disease is a destructive soil disease that affects crop health and causes huge losses in crop production. To explore the relationships between soil environments, rhizobacterial communities, and plant health, rhizosphere bacterial communities were analyzed using metagenomic sequencing in tobacco samples with different grades of RKN disease. The results showed that the community structure and function of the plant rhizosphere were significantly correlated to the RKN disease. RKN density and urease content were key factors affecting the rhizosphere bacterial community. Urease accelerated the catabolism of urea and led to the production of high concentrations of ammonia, which directly suppressed the development of RKNs or by improving the nutritional and growth status of microorganisms that were antagonistic to RKNs. Further experiments showed that the suppression role of ammonia should be attributed to the direct inhibition of NH3. The bacterial members that were positively correlated with RKN density, contained many plant cell wall degrading enzymes, which might destroy plant cell walls and promote the colonization of RKN in tobacco roots. The analysis of metatranscriptome and metabolism demonstrated the role of these cell wall degrading enzymes. This study offers a comprehensive insight into the relationships between RKNs, bacteria, and soil environmental factors and provides new ideas for the biological control of RKNs.

EKSTRAKSI DAUN TEMBAKAU DAN KOPI MENGGUNAKAN METODE VACUUM MICROWAVE ASSISTED EXTRACTION DENGAN VARIASI DAYA MICROWAVE

Indonesia, which has a tropical climate can be a very high commodity of tobacco and coffee, amounting to 236.900 tons tobacco and 774.600 tons coffee in 2021. It is a very big potential for Indonesia, but the use of coffee and tobacco so far, the majority are only used as ingredients for making cigarettes and coffee for making drinks. Research on the extraction of tobacco and coffee is expected to encourage opportunities for the use of tobacco and coffee for other purposes such as corrosion inhibitors. This study aims to determine the operating conditions of the extraction and yield obtained. The method is using VMAE (Vacuum Microwave Assisted Extraction) with variations in microwave power specifically 150 W and 300 W. The solvent is methanol and the extraction time is 10 minutes. The analysis carried out is the analysis of density, yield, and GC-MS. The results of the extract using methanol as a solvent reached a density 0,902 gram/mL of tobacco sample at 150 W and 0,909 gram/mL of tobacco sample at 300 W. For coffee samples, the density at 150 W is 0,855 gram/mL and the density at 300 W is 0,862 gram/mL. The yield is higher at 150 W with a tobacco samples of 16,94% and coffee samples of 12,90%. Based on the results of the GC-MS analysis, the highest component in tobacco extract is nicotine at 150 W which is equal to 92,85% and in coffee extract is caffein at 300 W with a large of 100%.

CRITERIA FOR TOBACCO IDENTIFICATION FOR HOOKAH AND NON-TOBACCO MIXTURE FOR HEATING

Hookah tobacco is positioned as a “nicotine alternative” to traditional smoking, but the aerosol produced contains the same toxic components as cigarette smoke. Consumer properties and safety indicators of tobacco aerosol for hookah depend on the component composition of the tobacco mixture and the coal used. The main factor that has a physiological effect on the user of hookah tobacco or non-tobacco mixture for heating is the content of nicotine that passes into the aerosol. There is no single approach to the regulation of a segmental product, in addition, there are no standardized methods for generating and collecting aerosol. The smoking pattern on a laboratory smoking machine does not fully reflect the behavioral profile of a person, however, the quantitative composition of the aerosol obtained from machine testing can be used as input to determine the risk of the product. During the research, laboratory and analytical equipment was used: CERULEAN SM 405 linear smoking machine; "Expert-001-1(0.1)" ionomer, SF-16 spectrophotometer, Crystal 2000M / HP 5890 Series 11 chromatograph with FID. Experimental data have been obtained to evaluate consumer and physic-chemical parameters, including organoleptic evaluation, the content of nicotine, glycerin and propylene glycol in samples of tobacco for hookah / non-tobacco mixture for heating. The method of machine generation and collection of the solid-liquid phase of an aerosol has been standardized, which makes it possible to obtain reliable data on the quantitative content of nicotine in the produced aerosol. The content of nicotine in the samples is 0.1–1.9%, the transition of nicotine into the produced aerosol is insignificant. The microscopy method for determining the structure of the base (carrier) in combination with the determination of consumer properties (organoleptic evaluation, total content of glycerol and propylene glycol, pH and nicotine content) are tools for identifying tobacco or non-tobacco hookah products.

Direct adsorption sampling and ambient mass spectrometry analysis of tobacco smoke with porous paper strips.

Chemical analysis of atmospheric aerosols by conventional analytical methods is usually required to perform complicated and time-consuming sample preparation processes. In recent decades, ambient ionization mass spectrometry (AI-MS) methods have been proven to be simple, rapid, and effective analytical tools for direct analysis of various complex samples. In this work, we applied porous paper filters for direct adsorptive sampling of tobacco smoke, and then the sampled paper filters were performed the emitters of the paper spray ionization (PSI) device. An auto-sampling device was made to control the generation and collection of tobacco smoke. Nicotine, the typical compound of tobacco smoke, was used to optimize the key conditions of auto-sampling. Moreover, different types of tobacco smoke were also compared with multivariate variable analysis, and the makers of tobacco smoke from different sources of tobacco smoke were investigated. By using this method, direct sampling and analysis of a single tobacco sample can be completed within minutes. Overall, our results show that PSI-MS is a powerful tool that integrates collection, extraction, ionization, and identification analytes in smoke.

PM 3/66 (3) Guidelines for the management of plant health risks of biowaste of plant origin

<scp>PM</scp> 3/66 (3) Guidelines for the management of plant health risks of biowaste of plant origin