Investigation of Phytochemical, Antioxidant and Antidiabetic Potentials of Scabiosa L. (Caprifoliaceae) Species with Chemometric Methods.

In this research, the total phenolic and flavonoid amounts, phenolic compositions, in vitro antioxidant, antibacterial and antidiabetic properties of the methanol extracts obtained from Scabiosa L. (Caprifoliaceae) species distributed in the flora of Türkiye were investigated using chemometric methods. For this purpose, principal component (PCA) and agglomerative hierarchical clustering analysis were performed as chemometric methods. Chlorogenic acid, quinic acid and cyranoside were determined in the extracts. According to chemometric analysis, S. columbaria subsp. ochroleuca var. ochroleuca and S. triniifolia species were found to be valuable in terms of methanol extract yields, total phenolic and flavonoid contents, antioxidant and antidiabetic activities while S. columbaria subsp. ochroleuca var. webbiana species were found to be valuable in terms of phenolic composition. The methanol extracts of Scabiosa species showed high antioxidant activity, with high phenolic and flavonoid contents. Among the tested 13 bacteria, Scabiosa extracts showed only low activity against Klebsiella pneumoniae, Streptococcus pneumoniae and Pseudomonas aeruginosa. The extracts showed high α-amylase and α-glucosidase inhibitory activity. The results show that Scabiosa methanol extracts may be a source of alternative antioxidants that may be beneficial in slowing or preventing the progression of various oxidative stress-related diseases.

Spectrum-Effect Relationships as an Effective Approach for Quality Control of Natural Products: A Review.

As natural products with biological activity, the quality of traditional Chinese medicines (TCM) is the key to their clinical application. Fingerprints based on the types and contents of chemical components in TCM are an internationally recognized quality evaluation method but ignore the correlation between chemical components and efficacy. Through chemometric methods, the fingerprints represented by the chemical components of TCM were correlated with its pharmacodynamic activity results to obtain the spectrum-effect relationships of TCM, which can reveal the pharmacodynamic components information related to the pharmacodynamic activity and solve the limitations of segmentation of chemical components and pharmacodynamic research in TCM. In the 20th anniversary of the proposed spectrum-effect relationships, this paper reviews its research progress in the field of TCM, including the establishment of fingerprints, pharmacodynamic evaluation methods, chemometric methods and their practical applications in the field of TCM. Furthermore, the new strategy of spectrum-effect relationships research in recent years was also discussed, and the application prospects of this technology were discussed.

Quantitative analysis of nutrients for nucleosides, nucleobases, and amino acids hidden behind five distinct regions-derived Poria cocos using ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry.

Poria cocos is an edible fungus used as a health product and traditional Chinese medicinal preparation. Nevertheless, little is known about its nutrients. In this study, ultra-high performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry was conducted to quantify nucleosides, nucleobases, and amino acids in 32 batches of Poria cocos samples collected from Anhui, Sichuan, Hubei, Hunan, and Guizhou. Subsequently, the linearity, precision, repeatability, stability, and recovery of our methods were validated. Samples from different regions were clearly separated by partial least squares discriminant analysis and cluster analysis. Our results suggested that Poria cocos samples from different geographical environments differed in nucleosides, nucleobases, and amino acids. The plot of variable importance for projection disclosed differential compositions of L-Leucine, Uridine, L-Asparagine, L-Glutamine, L-phenylalanine, L-Ornithine monohydrochloride, L-Hydroxyproline, Taurine, and Inosine in Poria cocos from five regions. We found the highest content of total analytes, total amino acids, and total non-essential amino acids in Poria cocos from Anhui, total essential amino acids in the Sichuan samples, and total nucleosides in the Hunan samples. Overall, we determined the content of Poria cocos-derived nucleosides, nucleobases, and amino acids, providing the foothold for further chemical mining and use of Poria cocos.

Screening of hypoglycemic components in Platycladi Cacumen by phytochemical investigation, spectrum-effect relationship, and chemometric methods.

In this work, the hypoglycemic components in Platycladi Cacumen, an essential traditional Chinese medicine, were evaluated by combining phytochemical investigation, spectrum-effect relationship analysis, and chemometric methods. The phytochemical studies on Platycladi Cacumen extract lead to the isolation of 21 potential bioactive compounds. The chromatographic fingerprints of Platycladi Cacumen samples were established by high-performance liquid chromatography. The hypoglycemic effects of Platycladi Cacumen samples were further evaluated by inhibition of α-glucosidase and detected by the high-performance liquid chromatography method. The spectrum-effect relationship study by bivariate correlations analysis and orthogonal partial least squares regression revealed that myricitrin (P9), quercitrin (P13), afzelin (P18), and amentoflavone (P24) were more relevant to the α-glucosidase inhibitory activity. The results of α-glucosidase inhibitory activity of 21 isolated compounds and molecular docking studies also indicated these flavonoids had potent α-glucosidase inhibitory activity. Collectively, the present study established the spectrum-effect relationship mode of Platycladi Cacumen and discovered the major hypoglycemic components, which provides a feasible method for screening bioactive components.

Prediction of fumonisins B1 and B2 in corn distiller's dried grains with solubles through near-infrared reflectance spectroscopy.

BACKGROUND: Distiller's dried grains with solubles (DDGS) are coproducts of the biofuel industries that use corn as raw material. This cereal is commonly contaminated by mycotoxins, including fumonisins (FBs), which can pose a serious health threat to humans and animals. Corn DDGS are typically used as a protein-rich animal feed. As mycotoxins from the original cereal grains become concentrated in DDGS, mycotoxicological monitoring is highly required before their use as ingredient in the industry. RESULTS: This work aimed to develop a methodology for predicting fumonisins B1 (FB1 ) and B2 (FB2 ) in corn DDGS using near-infrared reflectance spectroscopy (NIRS) technology associated with chemometric methods. One hundred and ninety corn DDGS samples originating from Brazilian ethanol plants and feed mills were included in this assessment. Two datasets were created: one for calibration (132 samples) and another for external validation (58 samples). Partial least squares regression and a cross-validation approach were applied to build the models. Liquid chromatography coupled to tandem mass spectrometry was used as the reference methodology. Calibration results of correlation coefficient and residual prediction deviation for FB1 and FB2 were, respectively, 0.90 and 0.88; and 2.16 and 2.06. CONCLUSION: Values of the external validation dataset were compared and no statistical difference was found between groups, indicating a satisfactory predictive ability and confirming the potential of NIRS to predict fumonisins in corn DDGS. © 2022 Society of Chemical Industry.

Prediction of tumor size in patients with invasive ductal carcinoma using FT-IR spectroscopy combined with chemometrics: a preliminary study.

Precise detection of tumor size is essential for early diagnosis, treatment, and evaluation of the prognosis of breast cancer. However, there are some errors between the tumor size of breast cancer measured by conventional imaging methods and the pathological tumor size. Invasive ductal carcinoma (IDC) is a common pathological type of breast cancer. In this study, serum Fourier transform infrared spectroscopy (FT-IR) combined with chemometric methods was used to predict the maximum diameter and maximum vertical diameter of tumors in IDC patients. Three models were evaluated based on the pathological tumor size measured after surgery and included grid search support vector machine regression (GS-SVR), back propagation neural network optimized by genetic algorithm (GA-BP-ANN), and back propagation neural network optimized by particle swarm optimization (PSO-BP-ANN). The results show that three models can accurately predict tumor size. The GA-BP-ANN model provided the best fitting quality of the largest tumor diameter with the determination coefficients of 0.984 in test set. And the GS-SVR model provided the best fitting quality of the largest vertical tumor diameter with the determination coefficients of 0.982 in test set. The GS-SVR model had the highest prediction efficiency and the lowest time complexity of the models. The results indicate that serum FT-IR spectroscopy combined with chemometric methods can predict tumor size in IDC patients. In addition, compared with traditional imaging methods, we found that the experimental results of the three models are better than traditional imaging methods in terms of correlation and fitting degree. And the average fitting error of PSO-BP-ANN and GA-BP-ANN models was less than 0.3 mm. The minimally invasive detection method is expected to be developed into a new clinical diagnostic method for tumor size estimation to reduce the diagnostic trauma of patients and provide new diagnostic experience for patients. Graphical Abstract.

Evaluation of the impact of buffered peptone water composition on the discrimination between Salmonella enterica and Escherichia coli by Raman spectroscopy.

The detection of Salmonella spp. in food samples is regulated by the ISO 6579:2002 standard, which requires that precise procedures are followed to ensure the reliability of the detection process. This standard requires buffered peptone water as a rich medium for the enrichment of bacteria. However, the effects of different brands of buffered peptone water on the identification of microorganisms by Raman spectroscopy are unknown. In this regard, our study evaluated the discrimination between two bacterial species, Salmonella enterica and Escherichia coli, inoculated and analyzed with six of the most commonly used buffered peptone water brands. The results showed that bacterial cells behaved differently according to the brand used in terms of biomass production and the spectral fingerprint. The identification accuracy of the analyzed strains was between 85% and 100% depending on the given brand. Several batches of two brands were studied to evaluate the classification rates between the analyzed bacterial species. The chemical analysis performed on these brands showed that the nutrient content was slightly different and probably explained the observed effects. On the basis of these results, Raman spectroscopy operators are encouraged to select an adequate culture medium and continue its use throughout the identification process to guarantee optimal recognition of the microorganism of interest.

Analysis and evaluation of nucleosides, nucleobases, and amino acids in safflower from different regions based on ultra high performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry.

Safflower has both medicinal and edible values but research on its nutrient composition is still lacking. This study was established for the quantitative determination of 28 nucleosides, nucleobases, and amino acids based on the ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry. Analysis of 30 batches of safflower from different producing areas indicated that the contents of l-proline, l-asparagine, l(+)-arginine, l-serine, l-histidine, uracil, guanosine, and uridine was high in safflower. Principle component analysis and cluster analysis found that samples from different regions could be distinguished well, and samples from the same area could be clustered into one class, different geographical environments may cause the differences of nucleosides, nucleobases, and amino acids in safflower. The analysis of principal component analysis, cluster analysis, and counter propagation artificial neural network show similar results. Then the content of nucleosides, nucleobases, and essential amino acids were compared, and found that the content in safflower from Gansu was higher than those from other regions, and there was a little difference between the samples from Xinjiang, Sichuan, and Yunnan. This research revealed the composition of nucleosides, nucleobases, and amino acids in safflower, and provided a theoretical basis for utilization of safflower.

Quality evaluation of traditional Chinese medicines based on fingerprinting.

The usage of traditional Chinese medicines has expanded globally, but the data about authentication, efficacy, and safety is far from sufficient to meet the criteria supporting their use worldwide due to complexity in the composition. Fingerprinting describes integral characterization and reflects interactive aspects of complex components; therefore, it can offer the possibility of evaluating quality of traditional Chinese medicines following the overall principle. Chemometric techniques introduce multivariate analytical methods into fingerprinting to obtain more information that is useful, which is consistent with the holistic thought and plays an important role in research on the substantial basis. In this review, we will start with three aspects to expound the quality evaluation of traditional Chinese medicines based on fingerprints. The analytical techniques used in developing fingerprints including chromatographic methods, spectroscopic methods, and capillary electrophoresis are introduced. Strategies for fingerprints analysis usually based on chemometric methods including unsupervised and supervised pattern recognition are described. Applications of fingerprints for multi-component quantification, quality control, screening of bioactive components, and fingerprint-efficacy relationship study are also outlined. Finally, we propose challenges and future perspectives of fingerprints in quality evaluation to promote the development of modernization and internationalization of traditional Chinese medicines.

A First Tentative for Simultaneous Detection of Fungicides in Model and Real Wines by Microwave Sensor Coupled to Molecularly Imprinted Sol-Gel Polymers.

A molecularly imprinted silica (MIS) coupled to a microwave sensor was used to detect three fungicides (iprodione, procymidone and pyrimethanil) present in most French wines. Chemometric methods were applied to interpret the microwave spectra and to correlate microwave signals and fungicide concentrations in a model wine medium, and in white and red Burgundy wines. The developed microwave sensor coupled to an MIS and to its control, a nonimprinted silica (NIS), was successfully applied to detect the three fungicides present in trace levels (ng L-1) in a model wine. The MIS sensor discriminated the fungicide concentrations better than the NIS sensor. Partial Least Squares models were suitable for determining iprodione in white and red wines. A preliminary method validation was applied to iprodione in the white and red wines. It showed a limit of detection (LOD) lower than 30 ng L-1 and a recovery percentage between 90 and 110% when the iprodione concentration was higher than the LOD. The determined concentrations were below the authorized level by far.

Chemical profiling by LC-MS/MS and HPLC fingerprint combined with chemometrics and simultaneous determination of 16 characteristic ingredients for the quality consistency evaluation of Shaoyao-Gancao Decoction.

In this paper, to evaluate the effect of the region of origin on the quality consistency of Shaoyao-Gancao Decoction (SGD), the SGD fingerprint was developed for the first time. Chemometric methods including similarity analysis, hierarchical clustering analysis and principal component analysis were employed to study the quality consistency of SGD. Meanwhile, high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry was applied for comprehensive analysis of SGD and 93 compounds were tentatively characterized. Furthermore, a high-performance liquid chromatography method with multi-wavelength switching for simultaneous determination of 16 characteristic ingredients comprising gallic acid, oxypaeniflorin, albiflorin, paeoniflorin, liquiritin apioside, liquiritin, isoliquiritin apioside, galloylpaeoniflorin, 1,2,3,4,6-penta-O-galloyl-d-galactopyranose (PGG), ononin, isoliquiritin, liquiritigenin, benzoylpaeoniflorin, glycyrrhizic acid, isoliquiritigenin and formononetin, was established. All 16 analytes show excellent linearity (R2 ≥ 0.9990) with recoveries ranging from 96.58 to 104.61% and limits of detection and quantification of 0.022-0.291 and 0.037-0.635 µg/mL, respectively. Finally, it was successfully applied to determine 15 batches of SGD. The results of our research indicate that different regions of origin have a significant effect on the quality consistency of SGD, and its fingerprint combined with chemometrics and multi-ingredient determination comprise an efficient and reliable approach for quality consistency evaluation.

Detection of Pirimiphos-Methyl in Wheat Using Surface-Enhanced Raman Spectroscopy and Chemometric Methods.

Pesticide residue detection is a hot issue in the quality and safety of agricultural grains. A novel method for accurate detection of pirimiphos-methyl residues in wheat was developed using surface-enhanced Raman spectroscopy (SERS) and chemometric methods. A simple pretreatment method was conducted to extract pirimiphos-methyl residue from wheat samples, and highly effective gold nanorods were prepared for SERS measurement. Raman peaks assignment was calculated using density functional theory. The Raman signal of pirimiphos-methyl can be detected when the concentrations of residue in wheat extraction solution and contaminated wheat is as low as 0.2 mg/L and 0.25 mg/L, respectively. Quantification of pirimiphos-methyl was performed by applying regression models developed by partial least squares regression, support vector machine regression and random forest with principal component analysis using different preprocessed methods. As for the contaminated wheat samples, the relative deviation between gas chromatography-mass spectrometry value and predicted value is in the range of 0.10%-6.63%, and predicted recovery is 94.12%-106.63%, ranging from 23.93 mg/L to 0.25 mg/L. Results demonstrated that the proposed SERS method is an effective and efficient analytical tool for detecting pirimiphos-methyl in wheat with high accuracy and excellent sensitivity.

Evidence on the discrimination of quinoa grains with a combination of FT-MIR and FT-NIR spectroscopy.

Quinoa is considered as a valuable re-emergent crop due to its nutritional composition. In this study, five quinoa grains from different geographical origin (Real, CHEN 252, Regalona, BO25 and UDc9) were discriminated using a combination of FT-MIR and FT-NIR spectra as input for principal component analysis (PCA), cluster analysis (CA) and soft independent modelling class analogy (SIMCA). The results obtained from PCA and CA show a great power of discrimination, with an average silhouette width value of 0.96. Moreover, SIMCA showed an error rate and accuracy values of 0 and 1 respectively with only 4% misclassified samples. A relationship between each principal component and the most important variables for the discrimination were mainly due to vibrations of several oleofins groups (C-H, C-H2, C-H3), alkene group (-CH=CH-), hydroxyl group (O-H) and Amides I and II vibrational modes.

Geographical discrimination of Glechomae Herba based on fifteen phenolic constituents determined by LC-MS/MS method combined with chemometric methods.

Glechomae Herba (GH) is rich in bioactive phenolic constituents and is widely used for treatment of cholelithiasis, urolithiasis and dropsy. The simultaneous determination of phenolic constituents in GH from different geographical origins is significant for authentication and quality control purposes. In this study, we developed a strategy integrating targeted analysis and chemometric methods for quality evaluation and discrimination of GH from different geographical origins. Firstly, an accurate and reliable liquid chromatography-tandem mass spectrometry method was developed for simultaneous quantification of 15 phenolic constituents in GH from different geographical origins. The established method was well validated in terms of desirable specificity, linearity, precision and accuracy. Secondly, the quantitative data were subjected to principal component analysis and orthogonal partial least squares discriminant analysis. Thirdly, a heatmap visualization was employed for clarifying the distribution of 15 phenolic compounds in GH from different geographical origins. These results indicated that GH samples from Shandong province obviously differ from those from other provinces in the content of bioactive phenolic constituents. Collectively, the proposed platform might be a suitable tool for quality evaluation and discrimination of GH from different geographical origins, providing promising perspectives in tracking the formulation processes of traditional Chinese medicine products.

Assessment of ecotoxicity and total volatile organic compound (TVOC) emissions from food and children's toy products.

The development of new methods for identifying a broad spectrum of analytes, as well as highly selective tools to provide the most accurate information regarding the processes and relationships in the world, has been an area of interest for researchers for many years. The information obtained with these tools provides valuable data to complement existing knowledge but, above all, to identify and determine previously unknown hazards. Recently, attention has been paid to the migration of xenobiotics from the surfaces of various everyday objects and the resulting impacts on human health. Since children are among those most vulnerable to health consequences, one of the main subjects of interest is the migration of low-molecular-weight compounds from toys and products intended for children. This migration has become a stimulus for research aimed at determining the degree of release of compounds from popular commercially available chocolate/toy sets. One of main objectives of this research was to determine the impact of time on the ecotoxicity (with Vibrio fischeri bioluminescent bacteria) of extracts of products intended for children and to assess the correlation with total volatile organic compound emissions using basic chemometric methods. The studies on endocrine potential (with XenoScreen YES/YAS) of the extracts and showed that compounds released from the studied objects (including packaging foils, plastic capsules storing toys, most of toys studied and all chocolate samples) exhibit mostly androgenic antagonistic behavior while using artificial saliva as extraction medium increased the impact observed. The impact of time in most cases was positive one and increased with prolonging extraction time. The small-scale stationary environmental test chambers - µ-CTE™ 250 system was employed to perform the studies aimed at determining the profile of total volatile organic compounds (TVOCs) emissions. Due to this it was possible to state that objects from which the greatest amounts of contaminants are released are plastic containers (with emission rate falling down from 3273 to 2280 ng/g of material at 6 h of conditioning in elevated temperature).

Effects of Growing Location on the Contents of Main Active Components and Antioxidant Activity of Dasiphora fruticosa (L.) Rydb. by Chemometric Methods.

Traditional Chinese Medicine (TCM) is a very important raw material source for natural medicines in China. The content and activity of active component are main indexes that evaluate the quality of TCM, however, they may vary with environmental factors. In this study, the effects of environmental factors on the active component contents and antioxidant activity of Dasiphora fruticosa collected from the five main growing areas of China were investigated. The contents of tannin, total flavonoids and rutin were determined to be 7.65 - 10.69%, 2.30 - 5.39% and 0.18 - 0.81%, respectively. Antioxidant activity was determined by DPPH assay, with the DPPH IC50 values ranged from 8.791 to 32.534 µg mL-1 . In order to further explore the cause of these significant geographical variations, the chemometric methods including correlation analysis, principal component analysis, gray correlation analysis and path analysis were applied. The results showed that environmental factors had significant effect on the contents of active components and antioxidant activity. Rapidly available phosphorus (RAP) and rapidly available nitrogen (RAN) were common dominant factors, and a significant positive action existed between RAP and active components and antioxidant activity (P < 0.05). Contributed by their high active components and strong antioxidant activity, Bange in Tibet and Geermu in Qinghai Province were selected as a favorable growing location, respectively.

Development of Noninvasive Classification Methods for Different Roasting Degrees of Coffee Beans Using Hyperspectral Imaging.

This study aimed to develop an approach for quickly and noninvasively differentiating the roasting degrees of coffee beans using hyperspectral imaging (HSI). The qualitative properties of seven roasting degrees of coffee beans (unroasted, light, moderately light, light medium, medium, moderately dark, and dark) were assayed, including moisture, crude fat, trigonelline, chlorogenic acid, and caffeine contents. These properties were influenced greatly by the respective roasting degree. Their hyperspectral images (874⁻1734 nm) were collected using a hyperspectral reflectance imaging system. The spectra of the regions of interest were manually extracted from the HSI images. Then, principal components analysis was employed to compress the spectral data and select the optimal wavelengths based on loading weight analysis. Meanwhile, the random frog (RF) methodology and the successive projections algorithm were also adopted to pick effective wavelengths from the spectral data. Finally, least squares support vector machine (LS-SVM) was utilized to establish discriminative models using spectral reflectance and corresponding labeled classes for each degree of roast sample. The results showed that the LS-SVM model, established by the RF selecting method, with eight wavelengths performed very well, achieving an overall classification accuracy of 90.30%. In conclusion, HSI was illustrated as a potential technique for noninvasively classifying the roasting degrees of coffee beans and might have an important application for the development of nondestructive, real-time, and portable sensors to monitor the roasting process of coffee beans.

Quality Analysis of American Ginseng Cultivated in Heilongjiang Using UPLC-ESI--MRM-MS with Chemometric Methods.

American ginseng (Panax quinquefolium) has long been cultivated in China for the function food and medicine. Here, ultra-high performance liquid chromatography was coupled with electrospray ionization and triple quadrupole mass spectrometry (UPLC-ESI--TQ-MS) for simultaneous detection of 22 ginsenosides in American ginseng cultivated in Mudanjiang district of Heilongjiang. The extraction conditions also were optimized by a Box Behnken design experiment. The optimized result was 31.8 mL/g as ratio of liquid to raw materials, 20.3 min of extraction time, and 235.0 W of extraction powers. The quantitative MS parameters for these 22 compounds were rapidly optimized by single factor experiments employing UPLC-ESI--multiple reaction monitoring or multiple ion monitoring (MRM/MIM) scans. Furthermore, the established UPLC-ESI--MRM-MS method showed good linear relationships (R² > 0.99), repeatability (RSD < 3.86%), precision (RSD < 2.74%), and recovery (94⁻104%). This method determined 22 bioactive ginsenosides in different parts of the plant (main roots, hairy roots, rhizomes, leaves, and stems) and growth years (one year to four years) of P. quinquefolium. The highest total content of the 22 analytes was in the hairy roots (1.3 × 105 µg/g) followed by rhizomes (7.1 × 104 µg/g), main roots (6.5 × 104 µg/g), leaves (4.2 × 104 µg/g), and stems (2.4 × 104 µg/g). Finally, chemometric methods, hierarchical clustering analysis (HCA) and partial least squares discrimination analysis (PLS-DA), were successfully used to classify and differentiate American ginseng attributed to different growth years. The proposed UPLC-ESI--MRM-MS coupled with HCA and PLS-DA methods was elucidated to be a simple and reliable method for quality evaluation of American ginseng.

Hyperspectral imaging for predicting the allicin and soluble solid content of garlic with variable selection algorithms and chemometric models.

BACKGROUND: Allicin and soluble solid content (SSC) in garlic is the responsible for its pungent flavor and odor. However, current conventional methods such as the use of high-pressure liquid chromatography and a refractometer have critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to predict allicin and SSC in garlic using hyperspectral imaging in combination with variable selection algorithms and calibration models. RESULTS: Hyperspectral images of 100 garlic cloves were acquired that covered two spectral ranges, from which the mean spectra of each clove were extracted. The calibration models included partial least squares (PLS) and least squares-support vector machine (LS-SVM) regression, as well as different spectral pre-processing techniques, from which the highest performing spectral preprocessing technique and spectral range were selected. Then, variable selection methods, such as regression coefficients, variable importance in projection (VIP) and the successive projections algorithm (SPA), were evaluated for the selection of effective wavelengths (EWs). Furthermore, PLS and LS-SVM regression methods were applied to quantitatively predict the quality attributes of garlic using the selected EWs. Of the established models, the SPA-LS-SVM model obtained an Rpred2 of 0.90 and standard error of prediction (SEP) of 1.01% for SSC prediction, whereas the VIP-LS-SVM model produced the best result with an Rpred2 of 0.83 and SEP of 0.19 mg g-1 for allicin prediction in the range 1000-1700 nm. Furthermore, chemical images of garlic were developed using the best predictive model to facilitate visualization of the spatial distributions of allicin and SSC. CONCLUSION: The present study clearly demonstrates that hyperspectral imaging combined with an appropriate chemometrics method can potentially be employed as a fast, non-invasive method to predict the allicin and SSC in garlic. © 2018 Society of Chemical Industry.

Rapid detection of adulteration in Anoectochilus roxburghii by near-infrared spectroscopy coupled with chemometric methods.

To determine the authenticity of Anoectochilus roxburghii, this study presents an application of near-infrared spectroscopy and chemometric methods for evaluating adulteration of A. roxburghii with two cheaper adulterants, i.e. C. Goodyera schlechtendaliana and Ludisia discolor. Partial least squares discriminant analysis models were built for the accurate classification of authentic A. roxburghii and A. roxburghii adulterated at 5-100% (w/w) levels. Partial least squares regression models were used to predict the level of adulteration in the A. roxburghii. After by compared different spectral pretreatment methods, and using interval PLS and synergy interval PLS for variable selection, optimum models were developed. These results show that the NIR spectroscopy combined with chemometric methods offers a simple, fast, and reliable method for classifying and quantifying the adulteration of A. roxburghii.