Application of NIR Spectroscopy Coupled with PLS Regression for Quantification of Total Polyphenol Contents from the Fruit and Aerial Parts of Citrullus colocynthis

Quality study of animal-derived traditional Chinese medicinal materials based on spectral technology: Calculus bovis as a case

INTRODUCTION

Calculus bovis (C. bovis) is a typical traditional Chinese medicine (TCM) derived from animals, which has a remarkable curative effect and high price.

OBJECTIVES

Rapid identification of C. bovis from different types was realized based on spectral technology, and a rapid quantitative analysis method for the main quality control indicator bilirubin was established.

METHODS

We conducted a supervised and unsupervised pattern recognition study on 44 batches of different types of C. bovis by five spectral pretreatment methods. Three variable selection methods were used to extract the essential information, and the partial least squares regression (PLSR) quantitative model of bilirubin by near-infrared (NIR) spectroscopy was constructed.

RESULTS

The partial least squares discriminant analysis (PLS-DA) model could achieve 100% accuracy in identifying different types of C. bovis. The R2 of the NIR quantitative model was 0.979, which is close to 1, and the root mean square error of calibration (RMSEC) was 2.3515, indicating the good prediction ability of the model.

CONCLUSION

The study was carried out to further improve the basic data of quality control of C. bovis and help the high-quality development of TCM derived from animals.

Formation and Application of Starch-Polyphenol Complexes: Influencing Factors and Rapid Screening Based on Chemometrics

Understanding the nuanced interplay between plant polyphenols and starch could have significant implications. For example, it could lead to the development of tailor-made starches for specific applications, from bakinag and brewing to pharmaceuticals and bioplastics. In addition, this knowledge could contribute to the formulation of functional foods with lower glycemic indexes or improved nutrient delivery. Variations in the complexes can be attributed to differences in molecular weight, structure, and even the content of the polyphenols. In addition, the unique structural characteristics of starches, such as amylose/amylopectin ratio and crystalline density, also contribute to the observed effects. Processing conditions and methods will always alter the formation of complexes. As the type of starch/polyphenol can have a significant impact on the formation of the complex, the selection of suitable botanical sources of starch/polyphenols has become a focus. Spectroscopy coupled with chemometrics is a convenient and accurate method for rapidly identifying starches/polyphenols and screening for the desired botanical source. Understanding these relationships is crucial for optimizing starch-based systems in various applications, from food technology to pharmaceutical formulations.

Characterization of Bioactive Compounds and Novel Proteins Derived from Promising Source Citrullus colocynthis along with In-Vitro and In-Vivo Activities

Herbal products are preferable to synthetic medicines, and the use of traditional medicines is increasing day-by-day. The current study was designed to evaluate the potentials of bioactive compounds from Citrullus colocynthis by performing FTIR, HPLC, and GC-MS analyses, which explore the good concentration of the secondary metabolites, such as gallic acid (74.854 ppm), vanillic acid (122.616 ppm), and ferulic acid (101.045 ppm) with considerable bioactivities. Antimicrobial protein was estimated by performing SDS-PAGE, ranging from 15 to 70 kDa in all protein fractions. The current study also checked the cytotoxicity of the bioactive compounds in the active fraction of C. colocynthis, and to perform this activity, the groups of rats were arranged with 16 rats randomly divided into four groups (three experimental and one control) by administering various dosage of methanolic fractions in dose-dependent manner. Histopathology was conducted on the livers of the rats after 15 days of sacrifice under deep anesthesia. In liver cell slides examined at the maximum dose of 600 mg/kg, minimal morphological changes, such as slight ballooning, nuclear variation, vacuolar degeneration, and hydropic degeneration, were observed. Furthermore, the in silico analysis identified bioactive compounds as potential drug candidates.

Heritable Variation of Foliar Spectral Reflectance Enhances Genomic Prediction of Hydrogen Cyanide in a Genetically Structured Population of Eucalyptus

Plants produce a wide diversity of specialized metabolites, which fulfill a wide range of biological functions, helping plants to interact with biotic and abiotic factors. In this study, an integrated approach based on high-throughput plant phenotyping, genome-wide haplotypes, and pedigree information was performed to examine the extent of heritable variation of foliar spectral reflectance and to predict the leaf hydrogen cyanide content in a genetically structured population of a cyanogenic eucalyptus (Eucalyptus cladocalyx F. Muell). In addition, the heritable variation (based on pedigree and genomic data) of more of 100 common spectral reflectance indices was examined. The first profile of heritable variation along the spectral reflectance curve indicated the highest estimate of genomic heritability ( h g 2 =0.41) within the visible region of the spectrum, suggesting that several physiological and biological responses of trees to environmental stimuli (ex., light) are under moderate genetic control. The spectral reflectance index with the highest genomic-based heritability was leaf rust disease severity index 1 ( h g 2 =0.58), followed by the anthocyanin reflectance index and the Browning reflectance index ( h g 2 =0.54). Among the Bayesian prediction models based on spectral reflectance data, Bayes B had a better goodness of fit than the Bayes-C and Bayesian ridge regression models (in terms of the deviance information criterion). All models that included spectral reflectance data outperformed conventional genomic prediction models in their predictive ability and goodness-of-fit measures. Finally, we confirmed the proposed hypothesis that high-throughput phenotyping indirectly capture endophenotypic variants related to specialized metabolites (defense chemistry), and therefore, generally more accurate predictions can be made integrating phenomics and genomics.

Phenolic Contents and Antioxidant Activity of Citrullus colocynthis Fruits, Growing in the Hot Arid Desert of the UAE, Influenced by the Fruit Parts, Accessions, and Seasons of Fruit Collection

Citrullus colocynthis (Cucurbitaceae) is an important medicinal plant traditionally used in the United Arab Emirates (UAE). In a recent study, it has been reported that different individuals of the same population of C. colocynthis, growing in the hot arid desert of the UAE, exhibited variations in their fruit size, color, and stripe pattern. In addition, these plants differed genetically, and their seeds showed variation in size, color, and germination behavior (hereinafter, these individuals are referred to as accessions). In the present study, the total phenolic content (TPC) and antioxidant activity of different fruit parts (rinds, pulps, and seeds) of three different accessions with significant genetic variations, from a single C. colocynthis population, were assessed in response to different seasonal environments. Green fruits were collected in summer and winter from three accessions growing in the botanic garden of the University of Sharjah, UAE. Methanolic extracts from different fruit parts were prepared. The TPC was qualitatively determined by a Folin–Ciocalteu assay, while the antioxidant capacity was analyzed using the 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) radical scavenging ability. The metabolic profiling of the antioxidant metabolites was determined using a gas chromatograph coupled to mass spectrometry (GC–MS), associated with a literature search. The results showed that the TPC and the DPPH free radical scavenging activity varied between seasons, accessions, and fruit parts. The highest phenolics were in rinds, but the highest antioxidant activities were in seeds during the summer, reflecting the role of these compounds in protecting the developed seeds from harsh environmental conditions. The metabolomic analysis revealed the presence of 28 metabolites with significant antioxidant activities relevant to fruit parts and season. Collectively, the formation of phenolics and antioxidant activity in different fruit parts is environmentally and genetically dependent.

An Effective Prediction Approach for Moisture Content of Tea Leaves Based on Discrete Wavelet Transforms and Bootstrap Soft Shrinkage Algorithm

The traditional method used to determine the moisture content of tea leaves is time consuming and destructive. To address this problem, an effective and non-destructive prediction method based on near-infrared spectroscopy (NIRS) is proposed in this paper. This new method combines discrete wavelet transforms (DWT) with the bootstrap soft shrinkage algorithm (BOSS). To eliminate uninformative or interfering variables, DWT is applied to remove the noise in the spectral data by decomposing the origin spectrum into six layers. BOSS is used to select informative variables by reducing the dimensions of the sub-layers’ reconstruction spectrum. After selecting the effective variables using DWT and BOSS, a prediction model based on partial least squares (PLS) is built. To validate effectiveness and stability of the prediction model, full-spectrum PLS, genetic algorithm PLS (GA-PLS), and interval PLS (iPLS) were compared with the proposed method. The experiment results illustrate that the proposed prediction model outperforms the other classical models considered in this study and shows promise for the prediction of the moisture content in Yinghong No. 9 tea leaves.

Aspergillus flavus as a Model System to Test the Biological Activity of Botanicals: An Example on Citrullus colocynthis L. Schrad. Organic Extracts

Citrullus colocynthis L. Schrader is an annual plant belonging to the Cucurbitaceae family, widely distributed in the desert areas of the Mediterranean basin. Many pharmacological properties (anti-inflammatory, anti-diabetic, analgesic, anti-epileptic) are ascribed to different organs of this plant; extracts and derivatives of C. colocynthis are used in folk Berber medicine for the treatment of numerous diseases-such as rheumatism arthritis, hypertension bronchitis, mastitis, and even cancer. Clinical studies aimed at confirming the chemical and biological bases of pharmacological activity assigned to many plant/herb extracts used in folk medicine often rely on results obtained from laboratory preliminary tests. We investigated the biological activity of some C. colocynthis stem, leaf, and root extracts on the mycotoxigenic and phytopathogenic fungus Aspergillus flavus, testing a possible correlation between the inhibitory effect on aflatoxin biosynthesis, the phytochemical composition of extracts, and their in vitro antioxidant capacities.

Development of a NIR Method for the In-Line Quantification of the Total Polyphenolic Content: A Study Applied on Ajuga genevensis L. Dry Extract Obtained in a Fluid Bed Process

This study describes an innovative in-line near-infrared (NIR) process monitoring method for the quantification of the total polyphenolic content (TPC) of Ajuga genevensis dry extracts. The dry extract was obtained in a fluidized bed processor, by spraying and adsorbing a liquid extract onto an inert powder support. NIR spectra were recorded continuously during the extract’s spraying process. For the calibration of the in-line TPC quantification method, samples were collected during the entire process. The TPC of each sample was assessed spectroscopically, by applying a UV-Vis reference method. The obtained values were further used in order to develop a quality OPLS prediction model by correlating them with the corresponding NIR spectra. The final dry extract registered good flowability and compressibility properties, a concentration in active principles three times higher than the one of the liquid extract and an overall process yield of 85%. The average TPC’s recovery of the NIR in-line prediction method, compared with the reference UV-Vis one, was 98.7%, indicating a reliable monitoring method which provided accurate predictions of the TPC during the process, permitting a good process overview and enabling us to establish the process’s end point at the exact moment when the product reaches the desired TPC concentration.