SERS-based Ag NCs@PDMS flexible substrate combined with chemometrics for rapid detection of foodborne pathogens on egg surface.

An innovative method is introduced based on the combination of label-free surface-enhanced Raman scattering with advanced multivariate analysis. This technique allows both quantitative and qualitative assessment of Salmonella typhimurium and Escherichia coli on eggshells. Using silver nanocubes embedded in polydimethylsiloxane, we consistently achieved Raman spectra of bacteria. The stability of the Ag NCs@PDMS substrate is confirmed using rhodamine 6G over 30 days under standard conditions. Principal component analysis (PCA) effectively distinguishes between S. typhimurium and E. coli spectra. Partial least squares regression (PLS) models were developed for quantitative determination of bacteria on egg surfaces, yielding accurate results with minimal error. The S. typhimurium model achieves Rc2 = 0.9563 and RMSEC = 0.601 in calibration, and Rv2 = 0.9113 and RMSEV = 0.907 in validation. Similarly, the E. coli model achieves Rc2 = 0.9877 and RMSEC = 0.322 in calibration, and Rv2 = 0.9606 and RMSEV = 0.579 in validation. Recoveries validate PLS predictions by inoculating egg surfaces with varying bacterial amounts. Our study demonstrates the feasibility of SERS-PLS for quantitative determination of S. typhimurium and E. coli on eggshells, promising enhanced food safety protocols.

Use of microscale heterogeneity in samples for spectral factorization-A strategy to build robust prediction models for nondestructive analyses.

Nondestructive spectroscopic analysis is widely used to evaluate food composition. However, distinguishing analytes of interest from other compounds remains challenging. Since most foods are heterogeneous when viewed under a microscope, we hypothesized that spectra measured at microscopic points would be "purer" than spectra acquired from a larger area. By coupling this data with nonnegative matrix factorization (NMF), the analytes of interest can be separated. This preliminary study discusses the quantification of glucose in mixtures of different sugars. Samples were made by mixing glucose with other powders in different ratios and Raman spectra were measured at 200 micro-points for each sample. NMF was applied to factorize the mixed spectra into spectra of pure compounds and their concentrations, leading to the accurate quantification of glucose, while eliminating the effects of other compounds. While this study targets simple powders, separation of analytes using microscale heterogeneity is applicable for measuring more complex foods.

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.

A comprehensive "quality-quantity-activity" approach based on portable near-infrared spectrometer and membership function analysis to systematically evaluate spice quality: Cinnamomum cassia as an example.

Spices have long been popular worldwide. Besides serving as aromatic and flavorful food and cooking ingredients, many spices exhibit notable bioactivity. Quality evaluation methods are essential for ensuring the quality and flavor of spices. However, existing methods typically focus on the content of particular components or certain aspects of bioactivity. For a systematic evaluation of spice quality, we herein propose a comprehensive "quality-quantity-activity" approach based on portable near-infrared spectrometer and membership function analysis. Cinnamomum cassia was used as a representative example to illustrate this approach. Near-infrared spectroscopy and chemometric methods were combined to predict the geographical origin, cinnamaldehyde content, ash content, antioxidant activity, and integrated membership function value. All the optimal prediction models displayed good predictive ability (correlation coefficient of prediction > 0.9, residual predictive deviation > 2.1). The proposed approach can provide a valuable reference for the rapid and comprehensive quality evaluation of spices.

The microalgae's ability to accumulate selected trace elements studied by ICP-MS/MS and chemometric methods.

BACKGROUND: Microalgae can be used in different branches of industry, including cosmetology, pharmaceutics and the food industry, information on their ability to accumulate different elements becomes more important. The microalgae biomass grown in the media enriched in elements can increase the accumulation of different ions and give a possibility to control the contents of the various elements. METHODS: The aim of the study was to determine the total content of metals in microalgae by tandem mass spectrometry with inductively coupled plasma (ICP-MS/MS) and analysis of the contents of particular metals as a function of the type of microalgae and conditions of cultivation. As the adverse effects of metals on the health of humans and animals have been well-documented and the use of microalgae has increased, the knowledge of metal contents in them is of particular importance in control of their quality. RESULTS: Analysis of results permitted distinction of three main groups of microalgae with similar total metal content levels. Moreover, the results revealed the ways of stimulating more significant accumulation of selected elements (for example, Se concentration in control algae 0.279 µg g-1, in the algae cultivated in enriched medium - 219.7 µg g-1). They indicated the possible correlations between the accumulation of different ions. The result obtained shows a significant effect of metal accumulation and has a considerable impact on the differentiation of Arthrospira platensis grown in the medium enriched in different elements (selenium, zinc, chromium) (p ≤ 0.05). CONCLUSIONS: Particular impact on the content of selected elements had the conditions of cultivation (type of support) and the microalgae species. Although the one species as the most significant source of selected elements cannot be indicated, it is possible to control the accumulation by the composition of the medium.

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.

Determination of Metal Content by Inductively Coupled Plasma-Mass Spectrometry in Polish Red and White Wine Samples in Relation to Their Type, Origin, Grape Variety and Health Risk Assessment.

The main objective of the research was to assess the influence of selected factors (type of wine, grape variety, origin, alcohol content and daily consumption) on the concentration levels of 26 elements in 53 Polish wine samples, also using chemometric analysis tools. Concentration of Al, As, B, Ba, Be, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Ni, Pb, Sb, Se, Sr, Ti, V, Zn and Zr was analyzed by ICP-MS, while concentration of Ca, Na, K and Mg was determined by ICP-OES. White wines were characterized by higher concentrations of Al, As, Be, Ca, Co, Cu, Fe, Hg, Li, Mg, Na, Pb, Sb, Ti, V, Zn and Zr (mean values: 0.075-86,403 µg·L-1 in white wines, 0.069-81,232 µg·L-1 in red wines). Red wines were characterized by higher concentrations of Ba, Cd, Cr, K, Mn, Se and Sr (mean values: 0.407-1,160,000 µg·L-1 in white wines, 0.448-1,521,363 µg·L-1 in red wines). The results obtained for the health risk assessment indices, including the Target Hazard Quotient (THQ, mean values per glass of wine: 2.097 × 10-5 (Cr)-0.041 (B) in all wines), indicate that the analyzed elements do not show a potential toxic effect resulting from wine consumption. The chemometric analysis confirmed that elements such as Li, Ti, Ca, Mn, Sr, Ba, Zn, Mg, Cu, Se and B were closely related to local conditions and soil properties, and the presence of Fe, Cr, V and Pb was related to contamination of the soil.

Linking Metallic Micronutrients and Toxic Xenobiotics to Atherosclerosis and Fatty Liver Disease-Postmortem ICP-MS Analysis of Selected Human Tissues.

Dyslipidaemia is a disorder of the lipid metabolism, caused mainly by poor eating habits. The most severe consequence of an inappropriate diet is the development of atherosclerosis and hepatic steatosis. It is generally believed that a change in nutrition, and increased physical activity can eliminate these health problems. The contemporary research and therapies used to treat dyslipidemia mainly focus on lowering the triglyceride and cholesterol levels. However, disturbances in trace element homeostasis or the accumulation of toxic elements can also affect physiological processes, and be involved in the development of metabolically mediated diseases. The present study aimed to determine the mineral profiles of liver and brain tissues collected at autopsy (n = 39) in groups of people with hepatic steatosis (n = 5), atherosclerosis (n = 9), hepatic steatosis, and atherosclerosis (n = 16), and others without the selected disorders (n = 9). Concentrations of 51 elements were analysed via inductively coupled plasma mass spectrometry (ICP-MS) after the initial wet mineralisation of the samples with nitric acid. The results obtained allow us to conclude that the hepatic steatosis group suffers from a deficiency of important trace elements, such as copper, zinc, and molybdenum (p < 0.05), whereas the group with atherosclerosis is characterised by elevated levels of cadmium in the liver tissue (p = 0.01). Analysing the mean values of the element concentrations measured in 11 brain areas, statistically significant higher levels of calcium and copper (p < 0.001) were found in the atherosclerosis group, compared to the hepatic steatosis group, confirming the involvement of these elements in the pathogenesis of atherosclerosis. In addition, an accumulation of cadmium, lead, titanium, and strontium in the brain tissue was observed in the atherosclerosis group. While the accumulation of individual elements differs in different parts of the brain, the differences in the cadmium content (p < 0.05) between the study groups apply to the whole brain, except for the nucleus accumbens septi area, where a statistically significant titanium accumulation occurs in the atherosclerosis and steatosis groups, compared to the others (p < 0.05). In addition, the disruption of elemental homeostasis in the brain of a single case with bipolar disorder, and a case with hip replacement was observed. Our results confirm the involvement of chemical elements in the pathogenesis of selected metabolic diseases, and the need for further studies in larger populations.

UV-Vis absorption spectrophotometry and LC-DAD-MS-ESI(+)-ESI(-) coupled to chemometrics analysis of the monitoring of sulfamethoxazole degradation by chlorination, photodegradation, and chlorination/photodegradation.

Sulfamethoxazole (SMX) is one of the most widely used antibiotics worldwide and has been detected at high concentrations in wastewater treatment plant effluents and river waters. In this study, the SMX degradation process combining the simultaneous chlorine oxidation and UV photodegradation is assessed and compared with both photodegradation and chlorine oxidation processes individually. Photodegradation and Chlorine/UV tests were performed using Suntest CPS equipment. Different experimental techniques, including UV-Visible spectrophotometry and liquid chromatography coupled to a diode array detector and positive and negative ionization mass spectrometry (LC-DAD-MS-ESI(+)-ESI(-)), were used to evaluate the degradation reaction of SMX. All the analytical data generated have been processed with the Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) method to monitor, resolve, and identify the several transformation products generated during the studied degradation processes. A new data fusion analysis strategy is proposed to examine the three processes simultaneously (with only photodegradation, only chlorination, and simultaneous chlorination+photodegradation). Combined with the analysis of different analytical techniques individually (spectrophotometry, LC-DAD, and LC-MS), the fusion of all generated data improved the description of the degradation processes. Detection using DAD allowed a better correspondence among the species monitored spectrophotometrically (UV-Vis) with those analyzed chromatographically. On the other side, detection using MS in both positive and negative acquisition modes allowed resolving a larger number of chemical compounds (specially SMX degradation subproducts) that could not be detected by UV-Vis spectrometry. The results obtained permitted the comparison of the effects produced by the three different degradation processes.

HPLC-DAD fingerprinting coupled with chemometric analysis can successfully differentiate Indian Berberis species and its plant parts.

Identification of the plant parts and genuine species is one of the most important steps for the quality control of raw material used in herbal medicines. In the present study, comparative analysis of TLC, HPLC and FTIR-ATR fingerprinting in conjunction with chemometric method was done to select the most appropriate fingerprinting method for quality control of Berberis aristata and its related species. To achieve this, extracts were first utilized to obtain TLC, HPLC and FT-IR fingerprinting data. The data was analyzed by chemometric methods and similarity analysis. The PCA model obtained with HPLC fingerprinting method could successfully classify the Berberis species as well plant parts viz. root, stem and leaves which was not possible with the PCA model of TLC or FT-IR fingerprints. Similarity analysis based on the mean HPLC fingerprinting chromatogram could also appropriately assess the chemical variability and identification of different Berberis species. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03644-6.

Rapid Test for Adulteration of Fritillaria Thunbergii in Fritillaria Cirrhosa by Laser-Induced Breakdown Spectroscopy.

Fritillaria has a long history in China, and it can be consumed as medicine and food. Owing to the high cost of Fritillaria cirrhosa, traders sometimes mix it with the cheaper Fritillaria thunbergii powder to make profit. Herein, we proposed a laser-induced breakdown spectroscopy (LIBS) technique to test the adulteration present in the sample of Fritillaria cirrhosa powder. Experimental samples with different adulteration levels were prepared, and their LIBS spectra were obtained. Partial least squares regression (PLSR) was adopted as the quantitative analysis model to compare the effects of four data standardization methods, namely, mean centring, normalization by total area, standard normal variable, and normalization by the maximum, on the performance of the PLSR model. Principal component analysis and least absolute shrinkage and selection operator (LASSO) were utilized for feature extraction and feature selection, and the performance of the PLSR model was determined based on its quantitative analysis. Subsequently, the optimal number of features was determined. The residuals were corrected using support vector regression (SVR). The mean absolute error and root mean square error of prediction obtained from the quantitative analysis results of the combined LASSO-PLSR-SVR model for the test set data were 5.0396% and 7.2491%, respectively, and the coefficient of determination R2 was 0.9983. The results showed that the LIBS technique can be adopted to test adulteration in the sample of Fritillaria cirrhosa powder and has potential applications in drug quality control.

Exploring Surface-Enhanced Raman Spectroscopy (SERS) Characteristic Peaks Screening Methods for the Rapid Determination of Chlorpyrifos Residues in Rice.

Surface-enhanced Raman spectroscopy (SERS), coupled with characteristic peak screening methods, was developed for analyzing chlorpyrifos (CM) pesticide residues in rice. Au nanoparticles (AuNPs) were prepared as Raman signal enhancement. Magnesium sulfate (MgSO4), primary secondary amine (PSA), and C18 were used to purify the rice extraction. A successive projections algorithm (SPA) was performed to identify the optimal characteristic peaks of CM in rice from full Raman spectroscopy. Support vector machine (SVM) and partial least squares (PLS) were implemented to investigate the quantitative analysis models. The results demonstrated that six Raman peaks such as 671, 834, 1016, 1114, 1436, and 1444 cm-1 were selected by the SPA and SVM models and had better performance using six peaks (only 0.92% of the full spectra variables) with R2p = 0.97, RMSEP = 2.89 and RPD = 4.26, and the experiment time for a sample was accomplished within 10 min. Recovery for five unknown concentration samples was 97.45-103.96%, and T-test results also displayed no obvious differences between the measured value and the predicted value. The study stated that SERS, combined with characteristic peak screening methods, can be applied to rapidly monitor the chlorpyrifos residue in rice.

Quality control strategies of medicine food homology materials based on fingerprint profiling and chemometrics: Citri Reticulata Pericarpium as an example.

The study aimed to provide a reliable and feasible strategy for the comprehensive quality control of medicine food homology materials (MFHM). The high performance liquid chromatography (HPLC) fingerprints and Fourier transform mid-infrared (FT-MIR) quantized fingerprints were successfully developed to comprehensively evaluate overall quality of Citri Reticulata Pericarpium (CRP) by applying comprehensive quantified fingerprint method (CQFM). All samples were well distinguished and divided into 5 grades. In addition, through principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), the identification ability of HPLC fingerprints and FT-MIR fingerprints on CRP with different storage years was discussed. The results showed that HPLC fingerprints combined with PCA had good discrimination ability, and the PLS-DA model established by the preprocessed FT-MIR fingerprint data could accurately distinguish and predict the storage period of CRP. Finally, based on 1, 1-diphenyl-2-picrylhydrazyl radical (DPPH•) scavenging assay, combined with bivariate correlation analysis, the fingerprint-activity relationship of offline antioxidant activity of CRP samples with the fingerprints peak were studied. In general, the comprehensive strategies provide a reliable and scientific reference scheme for the quality control of MFHM in the future.

Assessment of surface water quality during different tides and an anthropogenic impact on coastal water at Gulf of Kachchh, West Coast of India.

The port-based activity is often associated with industrial growth in the hinterland and similar phenomenon reported from the Gulf of Kachchh, India. Industrialization exerts pressure on coastal water through the release of waste water or effluents which influence the entire marine ecosystem. The present paper tries to evaluate the variation in the water quality during the high tide and low tide in relation to the anthropogenic or natural influence in Gulf of Kachchh. The tidal variation is important as it reflects the influence of the land-based activity on the coastal waters. To prove this logic, a series of stations were taken along the coastal water and statistical analysis, viz., Pearson correlation, Box plot, hierarchical cluster analysis (HCA), and factor analysis (PCA/FA) were conducted. Pearson correlation and Box plot represent visual impact of parameter variations in respected tides. The chemometric analysis, i.e., HCA and PCA/FA, clearly indicates an anthropogenic impact on coastal water. The results of HCA revealed that major anthropogenic and domestic impacts were found at various stations during the low tide. The HCA points out that an anthropogenic and the tidal activity in the Gulf of Kachchh influence the physical water quality parameters like pH, salinity, dissolved solid, oxygen, turbidity, sulfate, and nutrients in the coastal ecosystem. The PCA/FA further ascertains the finding of HCA analysis that the state of the art of the water quality of coastal ecosystem has direct relevance with the land-based activities and sewage outfall points. Tide-based control on the water quality parameters was evident that the high tide nutrients like phosphates and nitrogen were high, while during the low tide, temperature, salinity, total solids, and sulfate showed higher concentrations. The findings of the paper will be useful for developing effective management strategies for policy makers or stakeholders operating in the coastal area.

Identification of anti-inflammatory components in Dioscorea nipponica Makino based on HPLC-MS/MS, quantitative analysis of multiple components by single marker and chemometric methods.

The rhizome of Dioscorea nipponica Makino (RDN) is a widely used herbal medicine, which has significant anti-inflammatory activities on various inflammatory diseases. However, the bioactive compositions responsible for the anti-inflammatory activity of RDN are still unknown. This study aimed to identify the anti-inflammatory bioactive compounds in RDN using high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-Q/TOF-MS), quantitative analysis of multiple components by single marker (QAMS) and chemometric methods. Firstly, an HPLC-Q/TOF-MS method was employed for identification of bioactive steroidal saponins in RND, and a total of twelve steroid saponins were identified. Then, QAMS method was employed to determine the contents of seven bioactive steroidal saponins, including protodioscin, protogracillin, methyl protodioscin, pseudoprotodioscin, pseudoprogracillin, dioscin and gracillin in RND samples using dioscin as the reference analyte. The anti-inflammatory effects of RDN samples were then evaluated by inhibition of NO production in LPS-induced RAW264.7 cells. Furthermore, chemometric methods, including Pearson correlation analysis and partial least squares regression (PLSR) were employed to investigate the correlations between chemical components and anti-inflammatory activities, and explore the potential anti-inflammatory bioactive compounds of RDN. The results indicated that protodioscin, dioscin and gracillin were selected as the major anti-inflammatory compounds in RND. The further verification experiments showed that protodioscin, dioscin and gracillin exhibited great inhibition on NO production with IC50 values (the half maximal inhibitory concentration) of 0.712 µM, 0.469 µM and 0.815 µM, respectively. They also significantly reduced the levels of TNF-α, IL-1ß, and IL-6 in LPS-induced RAW264.7 cells. The present study provided evidences for the anti-inflammatory activity of RND and identification of the anti-inflammatory components in RDN.

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.

A green spectrophotometric method for the simultaneous determination of nasal binary mixture used in respiratory diseases: Applying isosbestic point and chemometric approaches as a resolving tool, greenness evaluation.

Nasal drug combination is a very useful therapy for elevating the symptoms of various respiratory diseases as seasonal allergic rhinitis and infectious respiratory illness as pandemic COVID-19. One of best combination is Fluticasone propionate (FLU) and Azelastine (AZE). In this study, different UV spectrophotometric and chemometric methods have been applied for quantitative analysis of FLU and AZE without previous separation in their pure form, laboratory prepared mixture and pharmaceutical dosage form. Absorbance subtraction (AS) and Amplitude modulation (AM) spectrophotometric methods have been applied for the simultaneous determination of the cited drugs. Besides, three well-known chemometric techniques; namely, classical least squares (CLS), partial least square (PLS), and principal component regression (PCR) have been applied for the simultaneous analysis of both drugs by using spectrophotometric data. To be friendly to the environment, the greenness of the proposed methods was taken into consideration and evaluation of the analytical methods' greenness was done using two green analytical chemistry metrics known as, Analytical Greenness Calculator and an eco-scale scoring method. They indicated that the methods were environmentally friendly in relation to numerous approaches like instrument, reagents, and safety of waste. Analyzing laboratory prepared mixtures including different quantities of FLU and AZE, as well as their marketed dose form, was used to assess the selectivity of the applied methods. The validity of the developed methods was investigated by applying the standard addition technique. The resulting data were statistically compared to those obtained by the official or reported HPLC methods for FLU and AZE, which revealed no significant difference in accuracy and precision at p = 0.05.

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.

Determination of Cultivation Regions and Quality Parameters of Poria cocos by Near-Infrared Spectroscopy and Chemometrics.

Poria cocos (PC) is an important fungus with high medicinal and nutritional values. However, the quality of PC is heavily dependent on multiple factors in the cultivation regions. Traditional methods are not able to perform quality evaluation for this fungus in a short time, and a new method is needed for rapid quality assessment. Here, we used near-infrared (NIR) spectroscopy combined with chemometric method to identify the cultivation regions and determine PC chemical compositions. In our study, 138 batches of samples were collected and their cultivation regions were distinguished by combining NIR spectroscopy and random forest method (RFM) with an accuracy as high as 92.59%. In the meantime, we used partial least square regression (PLSR) to build quantitative models and measure the content of water-soluble extract (WSE), ethanol-soluble extract (ASE), polysaccharides (PSC) and the sum of five triterpenoids (SFT). The performance of these models were verified with correlation coefficients (R2cal and R2pre) above 0.9 for the four quality parameters and the relative errors (RE) of PSC, WSE, ASE and SFT at 4.055%, 3.821%, 4.344% and 3.744%, respectively. Overall, a new approach was developed and validated which is able to distinguish PC production regions, quantify its chemical contents, and effectively evaluate PC quality.

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.