Infrared microspectroscopic identification of marker ingredients in the finished herbal products based on the inherent heterogeneity of natural medicines

Effects of different types of flame-retardant treatment on the flame performance of polyurethane/wood-flour composites

To improve the flammability of foamed polyurethane/wood-flour composites (FWPC), ammonium polyphosphate (APP) was used as a flame retardant to modified FWPC. The effects of different flame treatment processes on flame performance, smoke suppression, thermal property, and surface micrographs of flame retardant FWPC were investigated. The results showed that FWPC with the addition or impregnation process both improved the combustion behaviors. Compared with the addition process, FWPC-impregnation (FWPC-I) had a lower total heat release (THR), lower peak heat release rate (PHRR), prolonged time to ignition (TTI), more residues, and better combustion safety. FWPC-I had the highest residual carbon rate reaching 39.98%. A flame-retardant layer containing the P-O group was formed in the residual carbon of FWPC-I. Although APP had negative effects on the physical properties of FWPC, it was an effective flame-retardant ability for foamed polyurethane/wood-flour composites.

Attenuated Total Reflection Fourier Transform Infrared Mapping for the Identification of the Prescribed and Abnormal Ingredients of Herbal Powder Preparations

Herbal powder preparations (HPPs) are common forms of traditional medicine made by blending the powder of two or more ingredients. The first step to ensure the safety and efficacy of HPPs is to confirm the prescribed ingredients and screen the abnormal ingredients. With the help of attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) imaging or mapping, the particles of different ingredients in an HPP sample can be measured individually. In this way, the overlapped absorption signals of different ingredients in the ATR FT-IR spectrum of the bulk sample can be isolated in the ATR FT-IR spectra of the microscopic particles, which leads to the substantial increase of the specificity and sensitivity of the infrared spectral identification method. The characteristic particles of each ingredient can be identified by the objective comparison of the microscopic ATR FT-IR spectra against the reference spectra based on the correlation coefficients. Since the ATR FT-IR imaging or mapping tests of HPPs are free of the separation preprocess, multiple organic and inorganic ingredients are able to be recognized by a single identification procedure simultaneously rather than by different separation and identification procedures. As an example, the ATR FT-IR mapping method was used in this research to successfully identify three prescribed ingredients and two abnormal ingredients in oral ulcer pulvis, which is a classic HPP for oral ulcer in traditional Chinese medicine. The results show the feasibility of the ATR FT-IR microspectroscopic identification method for the objective and simultaneous identification of the prescribed and abnormal ingredients of HPPs.

Comparison of the Phytochemical Composition of Serenoa repens Extracts by a Multiplexed Metabolomic Approach

Phytochemical extracts are highly complex chemical mixtures. In the context of an increasing demand for phytopharmaceuticals, assessment of the phytochemical equivalence of extraction procedures is of utmost importance. Compared to routine analytical methods, comprehensive metabolite profiling has pushed forward the concept of phytochemical equivalence. In this study, an untargeted metabolomic approach was used to cross-compare four marketed extracts from Serenoa repens obtained with three different extraction processes: ethanolic, hexanic and sCO₂ (supercritical carbon dioxide). Our approach involved a biphasic extraction of native compounds followed by liquid chromatography coupled to a high-resolution mass spectrometry based metabolomic workflow. Our results showed significant differences in the contents of major and minor compounds according to the extraction solvent used. The analyses showed that ethanolic extracts were supplemented in phosphoglycerides and polyphenols, hexanic extracts had higher amounts of free fatty acids and minor compounds, and sCO₂ samples contained more glycerides. The discriminant model in this study could predict the extraction solvent used in commercial samples and highlighted the specific biomarkers of each process. This metabolomic survey allowed the authors to assess the phytochemical content of extracts and finished products of S. repens and unequivocally established that sCO₂, hexanic and ethanolic extracts are not chemically equivalent and are therefore unlikely to be pharmacologically equivalent.

Integrated recognition and quantitative detection of starch in surimi by infrared spectroscopy and spectroscopic imaging

Surimi products have become increasingly-consumed food with prominent characteristics of high nutrition and convenience and its supply falls short of demand. However, due to exhausted fishery resource in recent years, surimi adulteration, such as addition of plant proteins, starch and other animal origin meat, is becoming serious, so recognition of these exogenous substances has become an urgent issue. In this study, Fourier transform infrared spectroscopy (FT-IR) combined with infrared spectroscopic imaging could distinguish heterogeneity in surimi qualitatively and quantitatively and obtain integral chemical images so that spatial distribution of each component in surimi could be visually displayed, thus a rapid recognition method and a prediction model were developed. The different starch contents in surimi had been primarily identified through intensity change of infrared absorption peaks at 1045cm^-1 and 988cm^-1, specifically with peak shifts to 1041cm^-1 and to 992cm^-1, respectively. In infrared imaging analysis, principal components (PCs) were separated and one key PC was confirmed as starch by characteristic peaks comparison at 1147cm^-1, 1075cm^-1, 997cm^-1 and 930cm^-1. Meanwhile, an established statistic model could predict starch content in surimi correctly with a reliable correlation coefficient (R=0.9856) and root mean square error of prediction (RMSEP=5.64). Therefore, FT-IR combined with infrared spectroscopic imaging could be applicable to integrally recognize and quantitatively detect starch in surimi.

Enhanced chemical and spatial recognition of fish bones in surimi by Tri-step infrared spectroscopy and infrared microspectroscopic imaging

Surimi is an intermediate product with an increasing popularity worldwide. Discrimination of impurities like fish bones in surimi has become an urgent issue owing to the food safety and the improved requirements for assessment methods in identification of surimi quality and grades. A Tri-step infrared spectroscopy, including Fourier transform infrared spectroscopy (FT-IR), second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR) has been applied to integrally discriminate different contents (1%-8%) of fish bones in surimi at macro-scale. Meanwhile, attenuated total reflection infrared spectroscopy (ATR-IR) microspectroscopic imaging has been employed to recognize and identify the location of fish bones (less than 1.0 mm in size) in micro-scale. Fishbone characteristic infrared absorption peak at 1011 cm^-1 contributes to surimi peaks at 1045 cm^-1 and 988 cm^-1 confirmed by calculation of their peak heights and ratios of peak areas in original spectra. SD-IR spectra enhance the difference in range of 1440-500 cm^-1, and specifically peak intensity at 599 cm^-1 is significantly increased in surimi with 3%-8% fish bones. Moreover, 2DCOS-IR spectra reveal that surimi containing fish bones have increased intensity of auto-peaks at 525 cm^-1, 519 cm^-1, 512 cm^-1 and 505 cm^-1 mainly contributed by hydroxyapatite and collagen. In ATR-IR microspectroscopic images, a clear fishbone shape (800 × 200 μm) corresponding to its visible image is clearly observed in principal component (PC) score image, which is confirmed as a fish bone by corresponding pixel spectra. Furthermore, the single-wavenumber image shows the spatial chemical distribution of various components for both the fish bone and surimi. Consequently, fish bones can be integrally recognized by physical and chemical imaging manners. It has been demonstrated that the developed Tri-step infrared spectroscopy and ATR-IR microspectroscopic imaging could be applicable for rapidly recognizing impurities and adulterants in surimi.

Rapid and Integrated Quality Assessment of Organic-Inorganic Composite Herbs by FTIR Spectroscopy-Global Chemical Fingerprints Identification and Multiple Marker Components Quantification of Indigo Naturalis (Qing Dai)

This research aimed to develop an FTIR-based method for rapid and low-cost integrated quality assessment of organic-inorganic composite herbs, which are kinds of herbs composed of both organic and inorganic active ingredients or matrix components. A two-step quality assessment route was designed and verified using the example of Indigo Naturalis (Qing Dai). First, the FTIR spectra were used as global chemical fingerprints to identify the true and fake samples. Next, the contents of the organic and inorganic marker components were estimated by FTIR quantification models to assess the quality of the true samples. Using the above approaches, all the 56 true samples and five fake samples of Indigo Naturalis could be identified correctly by the correlation threshold of the FTIR chemical fingerprints. Furthermore, the FTIR calibration models provided an accurate estimation of the contents of marker components with respect to HPLC and inductively coupled plasma optical emission spectrometry (ICP-OES). The coefficients of determination (R²) for the independent validation of indigo, indirubin, and calcium were 0.977, 0.983, and 0.971, respectively. Meanwhile, the mean relative errors (MRE) for the independent validation of indigo, indirubin, and calcium were 2.2%, 2.4%, and 1.8%, respectively. In conclusion, this research shows the potential of FTIR spectroscopy for the rapid and integrated quality assessment of organic-inorganic composite herbs in both chemical fingerprints identification and marker components quantification.

Assessment of chemical equivalence in herbal materials using chromatographic fingerprints by combination of three similarity indices and three-dimensional kernel density estimation

An intuitive and practical way to control chemical equivalence of secondary metabolites in herbal materials based on chromatographic fingerprints deserves a thorough discussion, yet it is relatively unexplored. For the first time, we propose a mixture of three similarity indices, the congruence coefficient, the average of the peak area ratios, and the larger value between the maximum peak area ratio and the reciprocal of the minimum peak area ratio, to make up for the weak points of some widely used similarity indices and to evaluate the chemical equivalence of two fingerprints from various perspectives. The three similarity values are fed into a three-dimensional kernel density estimation to determine the quality of herbal materials. This estimation enables precise detection of anomalies in the absence of prior quality determination experience. Forty Atractylodes samples similar in appearance and indiscriminately used for medical purposes were used to demonstrate the effectiveness of the developed approach. After a reference sample was postulated, a quality assessment of the 40 samples was performed using the three similarity values and the estimated kernel density. The samples that were judged by the developed approach to be of good quality were compared with those chosen by the most popular approach using decision criterion of a single similarity index. The benefits of the proposed approach were evident in that the qualified samples had the composition ratio and individual concentrations of multi-components closer to those of the reference in general, and their inter-sample deviation was significantly smaller.

Direct and simultaneous detection of organic and inorganic ingredients in herbal powder preparations by Fourier transform infrared microspectroscopic imaging

Herbal powder preparation is a kind of widely-used herbal product in the form of powder mixture of herbal ingredients. Identification of herbal ingredients is the first and foremost step in assuring the quality, safety and efficacy of herbal powder preparations. In this research, Fourier transform infrared (FT-IR) microspectroscopic identification method is proposed for the direct and simultaneous recognition of multiple organic and inorganic ingredients in herbal powder preparations. First, the reference spectrum of characteristic particles of each herbal ingredient is assigned according to FT-IR results and other available information. Next, a statistical correlation threshold is determined as the lower limit of correlation coefficients between the reference spectrum and a larger number of calibration characteristic particles. After validation, the reference spectrum and correlation threshold can be used to identify herbal ingredient in mixture preparations. A herbal ingredient is supposed to be present if correlation coefficients between the reference spectrum and some sample particles are above the threshold. Using this method, all kinds of herbal materials in powder preparation Kouqiang Kuiyang San are identified successfully. This research shows the potential of FT-IR microspectroscopic identification method for the accurate and quick identification of ingredients in herbal powder preparations.

Data-driven signal-resolving approaches of infrared spectra to explore the macroscopic and microscopic spatial distribution of organic and inorganic compounds in plant

The nondestructive and label-free infrared (IR) spectroscopy is a direct tool to characterize the spatial distribution of organic and inorganic compounds in plant. Since plant samples are usually complex mixtures, signal-resolving methods are necessary to find the spectral features of compounds of interest in the signal-overlapped IR spectra. In this research, two approaches using existing data-driven signal-resolving methods are proposed to interpret the IR spectra of plant samples. If the number of spectra is small, "tri-step identification" can enhance the spectral resolution to separate and identify the overlapped bands. First, the envelope bands of the original spectrum are interpreted according to the spectra-structure correlations. Then the spectrum is differentiated to resolve the underlying peaks in each envelope band. Finally, two-dimensional correlation spectroscopy is used to enhance the spectral resolution further. For a large number of spectra, "tri-step decomposition" can resolve the spectra by multivariate methods to obtain the structural and semi-quantitative information about the chemical components. Principal component analysis is used first to explore the existing signal types without any prior knowledge. Then the spectra are decomposed by self-modeling curve resolution methods to estimate the spectra and contents of significant chemical components. At last, targeted methods such as partial least squares target can explore the content profiles of specific components sensitively. As an example, the macroscopic and microscopic distribution of eugenol and calcium oxalate in the bud of clove is studied.