Classification of moroccan olive cultivars by linear discriminant analysis applied to ATR-FTIR spectra of endocarps

Quality Control and Authentication of Black Betel Leaf Extract (Piper acre Blume) from East Kalimantan as an Antimicrobial Agent Using a Combination of High-Performance Liquid Chromatography and Chemometric Fourier Transform Infrared

Black betel leaf from East Kalimantan contains various secondary metabolites such as alkaloid saponins, flavonoids, and tannins. A compound, piperenamide A, which has antimicrobial activity, is also found in black betel leaf. This study aims to identify and authenticate the compound piperenamide A found in black betel leaf extract in other types of betel plant using HPLC and FTIR-chemometrics. The extraction method used was maceration with 70% ethanol solvent. Determination of piperenamide A content in black betel leaf extract was via HPLC column C18, with a maximum wavelength of 259 nm and a mobile phase of water:acetonitrile at a flow rate of 1 mL/minute. From the results, piperenamide A was only found in black betel (Piper acre) and not in Piper betel and Piper crocatum. Piperenamide A levels obtained were 4.03, 6.84, 5.35, 13.85, and 2.15%, respectively, in the samples studied. The combination of FTIR spectra with chemometric methods such as PCA and PLS-DA was used to distinguish the three types of betel. Discriminant analysis can classify black betel (Piper acre), Piper betel, and Piper crocatum according to its type. These methods can be used for identification and authentication of black betel.

Application of supervised chemometric techniques and synchronized excitation-emission spectrofluorometric analysis for the verification of Maltese extra virgin olive oils

The authentication of virgin olive oil samples usually requires the use of sophisticated and very expensive analytical techniques. In this study, the potential of fluorescence spectroscopy for the authentication and discrimination of Maltese extra virgin olive oils was carried out using synchronized excitation-emission spectroscopy. Samples were collected from various producers around the Maltese islands. Synchronous excitation emission spectra were collected in the region of 240-750 nm with wavelength intervals of 10, 30, 60, 80 120 and 185 nm and subjected to several supervised chemometric procedures. Partial least square regression, linear discriminate analysis, and artificial neural network were used to define the origin of the Maltese olive oil against olive oils derived from other neighboring countries in the Mediterranean region. After subjecting the spectroscopic data to different pre-treatments and variable selection procedures results obtained evidenced a higher classification accuracy. This accuracy and predictability were highly dependent on the wave interval used and on the chemometric method used, however it was found that in general spectra obtained using δ 10 nm were deemed the most appropriate, with PLS, ANN and LDA reaching 100% accuracy and predictability in discriminating Maltese extra virgin olive oils when using derivatized spectral transformations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-022-05371-x.

Identification of bovine, porcine and fish gelatin signatures using chemometrics fuzzy graph method

Gelatin is a protein substance that is widely used in food and pharmaceutical industries. Gelatin is mainly derived from bovine and porcine sources. Fish gelatin is becoming alternative source of gelatin due to concern on health issue and religious constraints. Numerous studies for identification of gelatin sources have been reported. In this study, Fourier transform infrared (FTIR) spectroscopy was used in combination with chemometrics fuzzy autocatalytic set (c-FACS) to distinguish between bovine, porcine and fish gelatins. The gelatin spectra at Amide and 1600–1000 cm⁻¹ regions were analyzed using c-FACS and the results were compared to principal component analysis (PCA) and linear discriminant analysis (LDA). The results obtained from c-FACS method showed that each bovine, porcine and fish gelatin possessed dominant wavenumbers at 1470–1475 cm⁻¹, 1444–1450 cm⁻¹ and 1496–1500 cm⁻¹ respectively, which represent their unique signatures. Furthermore, a clear distinction for porcine gelatin was observed in coordinated FACS. The c-FACS method is rigor and faster than PCA and LDA in differentiating the gelatin sources. The novel method promises at least another chemometrics method for FTIR related analysis and the possibilities for other applications are endless.

Detection and discrimination of seminal fluid using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy combined with chemometrics

Semen is most frequently encountered body fluid in forensic cases apart from blood especially in sexual assault cases. The presence and absence of semen can help in conviction or exoneration of a suspect by either confirming or refuting the claims put forward by the suspect and the victim. However, in the wake of limited studies on non-destructive and rapid analysis of semen, it is fairly difficult. Therefore, it is an increasing demand to pioneer the application of available analytical methods in such manner that non-destructive, automated, rapid, and reliable identification and discrimination of body fluids can be established. In the present study, such a methodological application of attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy has been put forward as one of the initial steps towards the identification and discrimination/classification of seminal fluid from vaginal fluid and other human biological as well as non-biological look-alike semen substances using chemometric tools which are principal component analysis (PCA), partial least square regression (PLSR), and linear discriminant analysis (LDA). Effect of other simulated factors such as substrate interference, mixing with other body fluids, dilutions, and washing and chemical treatments to the samples has been studied. PCA resulted in 98.8% of accuracy for the discrimination of seminal fluid from vaginal fluid whilst 100% accuracy was obtained using LDA method. One hundred percent discrimination was achieved to discriminate semen from other biological fluids using PLSR and LDA, and from non-biological substances using PCA-LDA models. Furthermore, results of the effect of substrates, chemical treatment, mixing with vaginal secretions, and dilution have also been described.

Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000-550 cm^-1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

FTIR spectroscopy for prediction of quality parameters and antimicrobial activity of commercial vinegars with chemometrics

BACKGROUND

The aim of this study was to discriminate between commercial apple, rice, balsamic, red-wine, rose, white-wine, grape, and pomegranate vinegars according to their antimicrobial activities, total phenolic contents (TPC), antioxidant activities, and color parameters, and to predict the quality characteristics of vinegars using Fourier transform infrared (FTIR) spectroscopy.

RESULTS

Results showed that the highest TPC (3971.43 ± 25.00) was found in balsamic vinegar whereas the lowest TPC was observed in rice vinegar (14.36 ± 0.16). Antioxidant activities of vinegars were correlated with TPC. Grape-based vinegars exhibited higher antimicrobial activity against Staphylococcus aureus (S. aureus), Escherichia coli (E.coli) and Pseudomonas aeruginosa (P.aeruginosa). However, there were no statistically significant differences among vinegars in terms of antimicrobial activities. According to principal component analysis (PCA) and hierarchical cluster analysis (HCA), vinegars were classified into three groups and each group consisted of vinegars from different raw materials. Prediction models were constructed successfully using partial least squares (PLS) considering whole FTIR spectral data.

CONCLUSION

The results indicated that FTIR could be used as a rapid method to estimate the antimicrobial activities, TPC, color and antioxidant activities of vinegars. © 2018 Society of Chemical Industry.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Synthesis and photodegradation studies of analogues of muscle relaxant 1,4-dihydropyridine compounds

This paper describes the synthesis of 1,4-dihydropyridine compounds (DHPs) endowed with good muscle relaxant activity and stability to light. Six new condensed DHPs were synthesized by the microwave irradiation method. A long-chain ester moiety [2-(methacryloyloxy)ethyl] and various substituents on the phenyl ring were demonstrated to affect the muscle relaxant activity occurring in isolated rabbit gastric fundus smooth muscle strips. Forced photodegradation conditions were applied to the molecules according to the ICH rules. The degradation profile of the drugs was monitored by spectrophotometry coupled with the multivariate curve resolution technique. Formation of the oxidized pyridine derivative was observed for all the studied DHPs, except for one compound, which showed very fast degradation and formation of a second photo-product. Pharmacological tests on the molecules showed a good muscle relaxing effect, with a mechanism similar to that of nifedipine, however, proving to be more stable to light.

Photodegradation studies of 1,4-dihydropyridine compounds by MCR analysis on UV spectral data

Background: 1,4-Dihydropyridines (DHPs) are well-known light-sensitive compounds. Photostability studies are necessary to ensure safety in therapy. Materials & Methods: Photodegradation experiments on 15 condensed DHP derivatives were made according to the International Conference on Harmonization rules. Degradation profiles were monitored by spectrophotometry and the data were processed by multivariate curve resolution analysis. Results: The analysis of the spectral data showed the formation of a single photoproduct from two DHPs, due to the aromatization of the pyridine ring. Traces of a second photoproduct were revealed in 12 DHPs and a third photoproduct was verified only in one case. Conclusion: DHPs showed high stability when fluorine was in the position R1 of the phenyl ring or simultaneously present in R1 and R2 positions. In contrast, the presence of chlorine in R1 or R2 strongly increased the degradation.