Rapid determination of baicalin and total baicalein content in Scutellariae radix by ATR-IR and NIR spectroscopy

Green extraction of bioactive flavonoids in Scutellariae Radix using deep eutectic solvents-based ultrasound-assisted matrix solid phase dispersion combined with computer-aided analysis

An efficient and sustainable deep eutectic solvents-based ultrasound-assisted matrix solid phase dispersion (DES-UAMSPD) method was proposed for extracting the bioactive flavonoids in Scutellariae Radix (SR), with molecular sieve (ZSM-5) as dispersant and betaine-levulinic acid (Bet-Lea (1:2, 50 % water content)) as the effective extractant. The interaction mechanism of DES formation and extraction process was comprehensively elucidated by computer simulation techniques such as electrostatic potential (ESP) distributions, independent gradient model based on hirshfeld partition (IGMH) and frontier molecular orbitals theory. The response surface methodology experiments were conducted to optimize the extraction conditions. Under optimal extraction conditions, the total content of five analytes (baicalin, oroxyloside, wogonoside, baicalein and wogonin) reached 182.66 mg g-1, which was 1.50-2.19 folds higher than conventional extraction solvents. The greenness and environmental friendliness of the proposed method were evaluated through Green Analytical Procedure Index and Analytical Eco-Scale. Additionally, this quantitative method exhibited reliable linearity for the analytes (r2 > 0.9997) and excellent recovery (95.4 %-102 %, RSD < 2.72 %). The limits of detection ranged from 0.02 to 0.04 μg mL-1. Overall, these results highlighted the excellent extraction and quantification capability of the proposed approach, which offered an environmentally friendly strategy for effective extraction of bioactive compounds from natural products.

An integrated and rapid evaluation of Curcumae Radix from different botanical origins based on chemical components, antiplatelet aggregation effect and Fourier transform near-infrared spectroscopy

Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, β-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, β-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.

Rapid and comprehensive quality evaluation of Huang-qin from different origins by FT-IR and NIR spectroscopy combined with chemometrics

INTRODUCTION

Quality evaluation of Huang-qin is significant to ensure its clinical efficacy.

OBJECTIVE

This study aims to establish an accurate, rapid and comprehensive Huang-qin quality evaluation method to overcome the time-consuming and laborious shortcomings of traditional herbal medicine quality assessment methods.

METHODS

The contents of baicalin, baicalein and scutellarin in Huang-qin from five different origins were analyzed by FT-IR and NIR spectra combined with multivariate data technology. The quality of Huang-qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored.

RESULTS

Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT-IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang-qin from different geographical origins was significantly different. The results showed that the quality of Huang-qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang-qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins.

CONCLUSION

This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.

Designing green and recyclable switchable supramolecular deep eutectic solvents for efficient extraction of flavonoids from Scutellariae Radix and mechanism exploration

A green and recyclable switchable supramolecular deep eutectic solvent (SS-DES) was designed and prepared for effective extraction of flavonoids from Scutellariae Radix. The novel SS-DES has both excellent extraction performance of DES and the host guest inclusion of cyclodextrin, thereby showing superior extraction efficiency and selectivity. The characteristic of polarity switching can endow the SS-DES with achieving homogeneous extraction and rapid two-phase separation, shorting per-treatment time largely. Parameters affecting the extraction performance were investigated by the response surface methodology. The results indicated that the SS-DES showed better extraction yield of total flavonoids (157.95 mg/g) compared with pure DES (135 mg/g) and traditional organic solvent (60 % ethanol, 104.87 mg/g). Moreover, the switching mechanism of SS-DES was characterized by FT-IR and 1H NMR, and the extraction mechanism was studied by density functional theory and molecular docking analysis. After evaluating the ecological impact of the method, the cytotoxicity of SS-DES was investigated and the result displayed that its toxicity was very low or even negligible with the EC50>2000 mg/L. After being adsorbed by macroporous AB-8 resin, the regenerated SS-DES was recycled 5 times and the extraction efficiency still remained above 90 %, indicating the desirable reusability. Therefore, the proposed method was efficient and sustainable, and revealed favorable application prospect for the extraction of bio-active compounds from plant materials.

Baicalin-Current Trends in Detection Methods and Health-Promoting Properties

Baicalin (7-D-glucuronic acid-5,6-dihydroxyflavone) belongs to natural flavonoids extracted from the roots of Scutellaria baicalensis, the plant used in traditional Chinese medicine. It has been proven that baicalin has various pharmacological activities, such as antioxidant, anti-inflammatory, anticancer, antibacterial, and anti-apoptotic ones. However, it is essential not only to determine the medical usefulness of baicalin, but also to find and develop the most effective methods for its extraction and detection. Therefore, the aim of this review was to summarize the current methods of detection and identification of baicalin and to present the medical applications of baicalin and the underlying mechanisms of its action. Based on the review of the latest literature, it can be concluded that liquid chromatography alone or together with mass spectrometry is the most commonly used method for the determination of baicalin. Recently, also new electrochemical methods have been established, e.g., biosensors with fluorescence, which have better detection limits, sensitivity, and selectivity.

Discrimination and Prediction of Lonicerae japonicae Flos and Lonicerae Flos and Their Related Prescriptions by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Combined with Multivariate Statistical Analysis

LJF and LF are commonly used in Chinese patent drugs. In the Chinese Pharmacopoeia, LJF and LF once belonged to the same source. However, since 2005, the two species have been listed separately. Therefore, they are often misused, and medicinal materials are indiscriminately put in their related prescriptions in China. In this work, firstly, we established a model for discriminating LJF and LF using ATR-FTIR combined with multivariate statistical analysis. The spectra data were further preprocessed and combined with spectral filter transformations and normalization methods. These pretreated data were used to establish pattern recognition models with PLS-DA, RF, and SVM. Results demonstrated that the RF model was the optimal model, and the overall classification accuracy for LJF and LF samples reached 98.86%. Then, the established model was applied in the discrimination of their related prescriptions. Interestingly, the results show good accuracy and applicability. The RF model for discriminating the related prescriptions containing LJF or LF had an accuracy of 100%. Our results suggest that this method is a rapid and effective tool for the successful discrimination of LJF and LF and their related prescriptions.

Electrospun polycaprolactone nanofibrous membranes loaded with baicalin for antibacterial wound dressing

Due to the rise in bacterial resistance, the antibacterial extractions from Chinese herbs have been used more frequently for wound care. In this work, baicalin, an extraction from the Chinese herb Scutellaria baicalensis, was utilized as the antibacterial component in the poly(ε-caprolactone)/MXene (PCL/Ti₃C₂T_X) hybrid nanofibrous membranes for wound dressing. The results revealed that the presence of Ti₃C₂T_X aided in the diameter reduction of the electrospun nanofibers. The PCL hybrid membrane containing 3 wt% Ti₃C₂T_X nanoflakes and 5 wt% baicalin exhibited the smallest mean diameter of 210 nm. Meanwhile, the antibacterial tests demonstrated that the PCL ternary hybrid nanofibers containing Ti₃C₂T_X and baicalin exhibited adequate antibacterial activity against the Gram-positive bacterial S. aureus due to the good synergistic effects of Ti₃C₂T_X naoflakes and baicalin. The addition of Ti₃C₂T_X nanoflakes and baicalin could significantly improve the hydrophilicity of the membranes, resulting in the release of baicalin from the nanofibers. In addition, the cytotoxicity of the nanofibers on rat skeletal myoblast L6 cells confirmed their good compatibility with these PCL-based nanofibrous membrances. This work offers a feasible way to prepare antibacterial nanofibrous membranes using Chinese herb extraction for wound dressing applications.

Application of multi-dimensional and multi-informational (MD-MI) integrated xanthine oxidase and superoxide anion fingerprint in quality evaluation of Scutellariae Radix

A multi-hyphenated analytical method that was successfully established in previous research was applied to quality evaluation of traditional Chinese medicine (TCM) to verify its feasibility in complex systems. Scutellariae Radix (SR), which significantly protects against oxidative damage from ischemia and reperfusion, was selected as the TCM for this study. A dual-activity detection system based on xanthine oxidase (XOD) inhibition and superoxide anion (O₂^-) scavenging activity was used to generate a multi-dimensional-multi-informational (MD-MI) integrated fingerprint of SR. Combined with HPLC-ESI-Q-TOF-MS analysis, 17 active compounds in SR were tentatively identified by comparison with reference substances or literature data. The quality of SR from different habitats was comprehensively and systematically evaluated in respect of chemical composition, XOD inhibition and O₂^- scavenging activity. It was confirmed that SR contains many antioxidants and XOD inhibitory substances with diverse functions. Among them, baicalin, norwogonin-7-O-glucuronide and baicalein are the main contributors to direct antioxidant activity. Acteoside, 5,7,2',5'-tetrahydroxy-8,6'-dimethoxy flavone, baicalin and baicalein are the main XOD inhibitory components of SR. Comprehensive analysis found that the antioxidant activity of SR from Gansu Province was superior to that from other provinces in terms of both XOD inhibition and O₂^- scavenging activity. It has been demonstrated that the method is capable of analyzing complex TCM matrices, and can provide a useful reference for establishing quality control of TCM from the perspective of MD-MI.

The effect of baicalein-loaded Y-shaped miktoarm copolymer on spatial memory and hippocampal expression of DHCR24, SELADIN and SIRT6 genes in rat model of Alzheimer

In the present study, we successfully synthesized nanocarriers (NCs) based on Y-shaped miktoarm copolymers, Poly Ethylene Glycol-Lysine-(Poly Caprolactone)₂ (PEG-Lys-PCL₂), which were loaded by baicalein (B) through the nanoprecipitation process to assess their in-vitro and in-vivo properties. We applied various methods and measurements including proton nuclear magnetic resonance (HNMR), dynamic light scattering (DLS), differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), MTT assay, hemolysis test, lethal dose, real-time PCR, and Morris water maze. The results of DLS indicated that the size and zeta potential of the obtained NCs and B-loaded NCs were acceptable. Also, in-vivo and in-vitro biocompatibility examinations proved that miktoarm-based NCs were safe, and all rats treated with miktoarm-based NCs did not exhibit any remarkable weight loss during the experiment. The results of the Morris water maze (in-vivo test) revealed that the normal saline-treated group, as well as B-miktoarm + Scopolamine (M + B + S) and B-miktoarm-Tween80 + Scopolamine (M + B + T + S) pretreatment groups, spent more time in the target quadrant. Thus, this experiment showed that pretreatment of rats with M + B + S and M + B + T + S had the most effects on spatial memory. According to quantitative PCR analysis, we hypothesized that, in comparison with other experimental groups, pretreatment of rats with M + B + T + S could be more effective in preventing cholinergic dysfunction, brain oxidative stress and cognitive deficits which cause by Scopolamine HBr. This outcome may be partially due to the upregulation of DHCR24, SELADIN, and SIRT6 in entire of the hippocampal region of normal saline-treated and M + B + T + S pretreatment groups. These results may be because mimicking the cell membrane structure would be an excellent feature for miktoarm, and partial coating of Tween-80 can play a critical role for PEG-Lys-PCL₂-based NCs in crossing the brain cell membrane, and they can easily be uptaken by the cells. Eventually, all of the obtained data confirmed that PEG-Lys-PCL₂ miktoarm star copolymers are suitable for delivering therapeutic agents to the brain for the treatment of Alzheimer's disease (AD). Also, it seems that baicalein should be taken into account as a potent compound for the treatment of AD.

Assessment of ATR-NIR and ATR-MIR spectroscopy as an analytical tool for the quantification of the total polyphenols in Dendrobium huoshanense

In this study, the potentiality of applying attenuated total reflectance near-infrared (ATR-NIR) and attenuated total reflectance mid-infrared (ATR-MIR) techniques combined with a partial least squares (PLS) regression technology to quantify the total polyphenols (TPs) in Dendrobium huoshanense (DHS) was investigated and compared. The real TP contents in the DHS samples were analysed using methods of reference. The capability of the two IR spectroscopic techniques to quantify the TPs in DHS was assessed by the root-mean-square error of calibration (RMSEC) and determination coefficients (R² ). The results showed that both NIR and MIR might be used as a fast and simple tool to replace traditional chemical assays for the determination of the TP contents in DHS, and the best NIR model showed slightly better prediction performance [root-mean-square error of prediction (RMSEP): 0.307, R² : 0.9122, ratio performance deviation (RPD): 4.43] than the best MIR model (RMSEP: 0.440, R² : 0.9069, RPD: 3.09). Results from this study indicated that both the NIR and MIR models could be used to quantify the TP in DHS, and ATR-NIR appeared to be the more predominant and more robust technique for the quantification of the TP in DHS.

An electrochemical sensing platform amplified with a Au@Ag nanoparticle-decorated three-dimensional N-doped graphene aerogel for ultrasensitive determination of baicalein

A novel electrochemical method for highly sensitive determination of baicalein was developed with Au@Ag/3DNGA as signal amplifier.

Traceability the provenience of cultivated Paris polyphylla Smith var. yunnanensis using ATR-FTIR spectroscopy combined with chemometrics

The conventional procedures, based on attenuated total reflectance-Fourier transform infrared spectrometry (ATR-FTIR), have been developed for the origins traceability of cultivated Paris polyphylla Smith var. yunnanensis (PPY) samples with the help of partial least square discriminant analysis (PLS-DA) and random forest. In this study, a set of 219 batch cultivated PPY samples, containing the cultivation years of 5, 6 and 7, and covering the municipal districts of Chuxiong, Dali, Honghe, Lijiang and Yuxi in Yunnan Province, China, were used to build the discrimination models. Firstly, a visualized analysis was carried out by t-distributed stochastic neighbor embedding (t-SNE) to reduce each data point in a two-dimensional map and make a knowledge of the sample distribution tendency. Secondly, the single spectra data sets of Paridis rhizome and leaf tissues, and the combination of these two data sets with variable selection (mid-level data fusion strategy), were used to establish PLS-DA and random forest models, and parallelly compared the model performance. Results demonstrated that the discrimination ability of PLS-DA preceded the random forest model, and the classification performance was remarkably improved after mid-level data fusion. These results verified each other by 5-, 6- and 7-year old Paridis samples and indicated that the model performance established in the present study was reliable. Besides, five agronomic characters, including the plant height, dry weight of rhizome and leaf tissues, and the allocation of rhizome and leaf were determined and analyzed, results of which indicated that the dry weight and their allocation was significantly different among various origins and fluctuated with the cultivation years. This study was using a comprehensive and green analytical method to discriminate the cultivated Paridis according to their provenances, which was simultaneously benefited for the appropriate cultivation areas selection based on the dry weight of rhizome tissues.

Traceability of wild Paris polyphylla Smith var. yunnanensis based on data fusion strategy of FT-MIR and UV-Vis combined with SVM and random forest

Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz (PPY) was a frequently used herbal medicine in pharmaceutical field and different provenances might affect the clinical efficacy. Tracing the geographical origin was an important portion for PPY authentication and quality assessment. Present study was compared low-, mid- and high-level data fusion methodology for geographical traceability of PPY samples (161 batches) combined with multivariate classification methods such as support vector machine gird search (SVM-GS) and random forest (RF) on the basis of Fourier transform mid-infrared (FT-MIR) and ultraviolet-visible (UV-Vis) spectra. Compared with the low- and mid-level data fusion strategy results basing on SVM-GS algorithm, result of high-level data fusion method (calculated by RF) was more satisfying. Result of RF basing on high-level data fusion strategy showed that merely two samples were misclassified and one sample was multiple assigned after voting with fuzzy set theory. Values of specificity, sensitivity, and accuracy rates were exceeded 0.91, 0.99 and 90.91%, for each class respectively, satisfying results of these were shown in training and test sets for high-level data fusion method. This feasible result indicated that the RF algorithm could establish a reliable and good performance model in geographical traceability on the basis of high-level data fusion strategy. Combination of high-level data fusion and RF algorithm could consider as a good choice for establishing a discrimination multivariate model for origins identification of PPY samples.

From quality markers to data mining and intelligence assessment: A smart quality-evaluation strategy for traditional Chinese medicine based on quality markers

BACKGROUND

The quality of traditional Chinese medicine (TCM) forms the foundation of its clinical efficacy. The standardization of TCM is the most important task of TCM modernization. In recent years, there has been great progress in the quality control of TCM. However, there are still many issues related to the current quality standards, and it is difficult to objectively evaluate and effectively control the quality of TCM.

PURPOSE

To face these challenge, we summarized the current quality marker (Q-marker) research based on its characteristics and benefits, and proposed a reasonable and intelligentized quality evaluation strategy for the development and application of Q-markers.

METHODS

Ultra-performance liquid chromatography-quadrupole/time-of-flight with partial least squares-discriminant analysis was suggested to screen the chemical markers from Chinese medicinal materials (CMM), and a bioactive-guided evaluation method was used to select the Q-markers. Near-infrared spectroscopy (NIRS), based on the distinctive wavenumber zones or points from the Q-markers, was developed for its determination. Then, artificial intelligence algorithms were used to clarify the complex relationship between the Q-markers and their integral functions. Internet and mobile communication technology helped us to perform remote analysis and determine the information feedback of test samples.

CHAPTERS

The quality control research, evaluation, standard establishment and quality control of TCM must be based on the systematic analysis of Q-markers to study and describe the material basis of TCM efficacy, define the chemical markers in the plant body, and understand the process of herb drug acquisition, change and transmission laws affecting metabolism and exposure. Based on the advantages of chemometrics, new sensor technologies, including infrared spectroscopy, hyperspectral imaging, chemical imaging, electronic nose and electronic tongue, have become increasingly important in the quality evaluation of CMM. Inspired by the concept of Q-marker, the quantitation can be achieved with the help of artificial intelligence, and these subtle differences can be discovered, allowing the quantitative analysis by NIRS and providing a quick and easy detection method for CMM quality evaluations.

CONCLUSION

The concept of Q-markers focused on unique CMM differences, dynamic changes and their transmission and traceability to establish an overall quality control and traceability system. Based on the basic attributes, an integration model and artificial intelligence research path was proposed, with the hope of providing new ideas and perspectives for the TCM quality management.

Application of benchtop and portable near-infrared spectrometers for predicting the optimum harvest time of Verbena officinalis

This study examined the applicability of near-infrared (NIR) spectroscopy coupled with multivariate data analysis (MVA) to determine the ideal harvest time of Verbena officinalis. NIR analyses were performed non-invasively on the fresh plant material based on the quantification of the key constituents verbenalin and verbascoside. Vibrational spectroscopic measurements were performed applying a conventional NIR benchtop device as well as a laboratory independent handheld NIR spectrometer. A novel high performance liquid chromatography (HPLC) method was applied as a reference method. For both instruments partial least squares (PLS) regression models were established performing cross validations (CV) and test-set validations (TSV). Quality parameters obtained for the benchtop device revealed that the newly established NIR method enabled reliable quantifications of the main compounds verbenalin and verbascoside related to the dried and fresh plant material. The results of the miniaturised spectrometer revealed that accurate quantitative calibration models could be developed for verbascoside achieving a comparable prediction power to the benchtop device. PLS models for verbenalin were less precise suggesting the application of portable devices including a different spectral range and resolution. The work demonstrated the feasibility of NIR vibrational spectroscopy performing direct measurements on pharmaceutically relevant fresh plant material enabling a quick and simple determination of the ideal harvest time of Verbena officinalis.

Application of NIR and MIR spectroscopy for rapid determination of antioxidant activity of Radix Scutellariae from different geographical regions

INTRODUCTION

The beneficial health effects of traditional Chinese medicines are often attributed to their potent antioxidant activities, usually established in vitro. However, these wet chemical methods for determining antioxidant activities are time-consuming, laborious, and expensive.

OBJECTIVES

This study was conducted to establish a rapid determination of antioxidant activity of Radix Scutellariae using near-infrared (NIR) and mid-infrared (MIR) spectroscopy.

MATERIAL AND METHODS

Antioxidant capabilities were evaluated using 2,2-diphenyl-1-picrylhydrazyl hydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays. The total flavonoid contents (TFCs) of Radix Scutellariae were measured by the aluminium chloride colorimetric method. The same sample was then scanned using NIR and MIR spectroscopy. Chemometrics analysis using partial least-squares (PLS) regression was performed to establish the models for predicting the antioxidant activities of Radix Scutellariae.

RESULTS

A better predictive performance was achieved using PLS models based on NIR data. The determination coefficient (R(2)) and the residual predictive deviation (RPD) for the validation set were 0.9298 and 2.84 for DPPH, and 0.9436 and 2.66 for TFCs, respectively. MIR-PLS algorithms gave a slightly lower reliability (R(2) = 0.9090 and 0.9374, RPD = 2.01 and 2.42, for DPPH and TFC, respectively). Very comparable results for ORAC were obtained with the two methods.

CONCLUSION

The developed spectroscopic method can be successfully applied in high-throughput screening of the antioxidant capability of Radix Scutellariae samples. It can also be a viable and advantageous alternative to laborious chemical procedures.

Combining PLS regression with portable NIR spectroscopy to on-line monitor quality parameters in intact olives for determining optimal harvesting time

This study presents a systematized method for predicting water content, fat content and free acidity in olive fruits by on-line NIR Spectroscopy combined with chemometric techniques (PCA, LDA and PLSR). Three cultivar varieties of Olea europaea - Hojiblanca cv., Picual cv. and Arbequina cv. - were monitored. Five olive cultivation areas of Southern Spain (Andalucia) and Southern Portugal (Alentejo) were studied in 2011 and 2012. 465 olive samples were collected during the ripening process (non-mature olives) and compared with other 203 samples of mature olives collected at the final ripening stage. NIR spectra were measured directly in the olive fruits in the wavelength region from 1000 to 2300 nm in reflectance mode. The reference analyses were performed on the olive paste by oven drying for the moisture, by mini-Soxhlet extraction for the fat content and by acid titration of the oil extracted from the olive paste. Calibrations and predictive models were developed by Partial Least Square Regression (PLSR) previous Principal Component and Linear Discriminant analyses (PCA and LDA) were employed as exploratory and clean-up tools of data sets. The final models obtained for the total samples showed acceptable statistics of prediction with R(2)=0.88, RMSEV%=4.88 and RMSEP%=4.98 for water content, R(2)=0.76, RMSECV%=19.5 and RMSEP%=20.0 for fat content and R(2)=0.83, RMSECV%=36.8 and RMSEP%=38.8 for free acidity. Regression coefficients were better for only one maturity state (ripe period) than for olive fruit with different composition (ripening period). All models obtained were applied to predict LQPs on a new set of samples with satisfactory results, a good prediction potential of the models.

Phylogeny of cultivated and wild wheat species using ATR-FTIR spectroscopy

Within the last decade, an increasing amount of genetic data has been used to clarify the problems inherent in wheat taxonomy. The techniques for obtaining and analyzing these data are not only cumbersome, but also expensive and technically demanding. In the present study, we introduce infrared spectroscopy as a method for a sensitive, rapid and low cost phylogenetic analysis tool for wheat seed samples. For this purpose, 12 Triticum and Aegilops species were studied by Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. Hierarchical cluster analysis and principal component analysis clearly revealed that the lignin band (1525-1505 cm(-1)) discriminated the species at the genus level. However, the species were clustered according to their genome commonalities when the whole spectra were used (4000-650 cm(-1)). The successful differentiation of Triticum and its closely related genus Aegilops clearly demonstrated the power of ATR-FTIR spectroscopy as a suitable tool for phylogenetic research.