Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

Increment of Ginsenoside Accumulation in Ginseng Rhizome Joints and the Prediction of the Growth Year

INTRODUCTION

The growth year of ginseng is relevant to its quality and commercial value. Ginseng rhizome joint number increases by growth year. The relationship between the metabolite accumulation and the growth year of a rhizome remains unclear. Most forest-grown ginseng rhizomes can conveniently be separated into different joints and are suitable materials for investigating ginseng metabolite accumulation.

OBJECTIVES

This work aims to elucidate how ginsenoside accumulates in the ginseng rhizome joint and if it is applicable for growth-year determination.

METHODS

Forest-grown Panax ginseng rhizomes were separated into different joints according to their growth scars; ginsenosides in each joint were then tested using high-performance liquid chromatography-tandem mass spectrometry. The age-related ginsenosides screening was performed using orthogonal partial least squares analysis (OPLS). Several ground-cultivated ginseng rhizomes have also been tested.

RESULTS

Ginsenoside contents in different joints of a rhizome increase with its growth year and reach their corresponding equilibriums in specific years. Notoginsenoside R3 and ginsenoside Rg1 were the most relevant to the growth year. They increase continuously from 0 to 8 years. Perhaps, the OPLS improved the linearity of the relationship between scores and ages. The predictions of the growth year of a rhizome joint using the OPLS models were accurate.

CONCLUSION

Some ginsenosides increased in ginseng rhizome joints by their growth year. The OPLS score of a rhizome joint can be used to determine its growth year.

Rapid discrimination of Panax ginseng powder adulterated with various root plants by FT-IR spectroscopy coupled with multivariate analysis

Panax ginseng powder adulterated with other root plants (arrowroot, bellflower, and lance asiabell) was discriminated using Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis visually diagnosed the adulteration by showing two distinct clusters based on presence of adulteration. Wavenumber regions (1000 cm-1 and 3300 cm-1) selected from the loading plot associated with the vibration of OH and CH bond in ginsenoside and aromatic compounds. A quantitative model for the content of ginsenosides and specific aromatic compounds as indicators of pure ginseng powder, was developed based on partial least square regression analysis. The performance of the prediction model preprocessed with the Savizky-Golay 1st derivative was improved to R2 of 0.9650, 0.9635, and 0.9591 for Rb1, Rc, and β-Panasinsene, respectively. Therefore, FT-IR technology makes it possible to rapidly authenticate pure ginseng product based on the ginsenoside contents and aroma compound.

A novel method for age identification of mountain-cultivated ginseng

Panax ginseng, a slow-growing perennial herb, is the most praised and popular traditional medicinal herb. Mountain-cultivated ginseng (MCG) and cultivated ginseng (CG) both belong to Panax ginseng C. A. Meyer. The market price and medical effects of this popular health product are closely related to its age. It is widely acknowledged that CG is typically harvested after 4-6 years of growth, but MCG is often collected after 10 years. Until now, the age identification of MCG or mountain wild ginseng (MWG) has remained a major challenge. In this study, we established a novel and rapid method for staining xylem vessels with phloroglucinol and identifying the "annual growth rings" of ginseng by utilizing a stereoscope, which serves as a reliable indicator of the age of MCG. Statistical analysis of the ring radius and the ring density of MCG aged from 1 to 20 years shows that the secondary xylem of MCG increases rapidly in the first 3 years but then gradually slows down from 4 to 10 years, and minor fluctuation is observed in the next 10 years. Meanwhile, the space between the growth rings (ring density) becomes increasingly small with age. This straightforward staining approach can reveal the age of MCG with remarkable clarity and can distinguish MCG from CG. RESEARCH HIGHLIGHTS: A novel rapid staining method for Panax ginseng was established. The age of mountain-cultivated ginseng (MCG) can be identified by microscopic techniques. MCG and cultivated ginseng (CG) can be discriminated by microstructure characteristics.

Biosynthesis of Functional Silver Nanoparticles Using Callus and Hairy Root Cultures of Aristolochia manshuriensis

This study delves into the novel utilization of Aristolochia manshuriensis cultured cells for extracellular silver nanoparticles (AgNPs) synthesis without the need for additional substances. The presence of elemental silver has been verified using energy-dispersive X-ray spectroscopy, while distinct surface plasmon resonance peaks were revealed by UV-Vis spectra. Transmission and scanning electron microscopy indicated that the AgNPs, ranging in size from 10 to 40 nm, exhibited a spherical morphology. Fourier-transform infrared analysis validated the abilty of A. manshuriensis extract components to serve as both reducing and capping agents for metal ions. In the context of cytotoxicity on embryonic fibroblast (NIH 3T3) and mouse neuroblastoma (N2A) cells, AgNPs demonstrated varying effects. Specifically, nanoparticles derived from callus cultures exhibited an IC50 of 2.8 µg/mL, effectively inhibiting N2A growth, whereas AgNPs sourced from hairy roots only achieved this only at concentrations of 50 µg/mL and above. Notably, all studied AgNPs' treatment-induced cytotoxicity in fibroblast cells, yielding IC50 values ranging from 7.2 to 36.3 µg/mL. Furthermore, the findings unveiled the efficacy of the synthesized AgNPs against pathogenic microorganisms impacting both plants and animals, including Agrobacterium rhizogenes, A. tumefaciens, Bacillus subtilis, and Escherichia coli. These findings underscore the effectiveness of biotechnological methodologies in offering advanced and enhanced green nanotechnology alternatives for generating nanoparticles with applications in combating cancer and infectious disorders.

Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy

Herbs have been used as natural remedies for disease treatment, prevention, and health care. Some herbs with functional properties are also used as food or food additives for culinary purposes. The quality and safety inspection of herbs are influenced by various factors, which need to be assessed in each operation across the whole process of herb production. Traditional analysis methods are time-consuming and laborious, without quick response, which limits industry development and digital detection. Considering the efficiency and accuracy, faster, cheaper, and more environment-friendly techniques are highly needed to complement or replace the conventional chemical analysis methods. Infrared (IR) and Raman spectroscopy techniques have been applied to the quality control and safety inspection of herbs during the last several decades. In this paper, we generalize the current application using IR and Raman spectroscopy techniques across the whole process, from raw materials to patent herbal products. The challenges and remarks were proposed in the end, which serve as references for improving herb detection based on IR and Raman spectroscopy techniques. Meanwhile, make a path to driving intelligence and automation of herb products factories.

Hybrid volatilomics in cancer diagnosis by HS-GC-FID fingerprinting

Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck-HNC,n= 15; and gastrointestinal cancer-GIC,n= 19) and healthy controls (n= 37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q²Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q²Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q²Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q²Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis.

Application of FT-IR spectroscopy and chemometric technique for the identification of three different parts of Camellia nitidissima and discrimination of its authenticated product

Camellia nitidissima C.W. Chi is a golden camellia recognized in Chinese herbology and widely used as tea and essential oil in Chinese communities. Due to its diverse pharmacological properties, it can be used to treat various diseases. However, unethical sellers adulterated the flower with other parts of Camellia nitidissima in their product. This study used an integrated tri-step infrared spectroscopy method and a chemometric approach to distinguish C. nitidissima’s flowers, leaves, and seeds. The three different parts of C. nitidissima were well distinguished using Fourier transform infrared spectroscopy (FT-IR), second-derivative infrared (SD-IR) spectra, and two-dimensional correlation infrared (2D-IR) spectra. The FT-IR and SD-IR spectra of the samples were subjected to principal component analysis (PCA), PCA-class, and orthogonal partial least square discriminant analysis (OPLS-DA) for classification and discrimination studies. The three parts of C. nitidissima were well separated and discriminated by PCA and OPLS-DA. The PCA-class model’s sensitivity, accuracy, and specificity were all >94%, indicating that PCA-class is the good model. In addition, the RMSEE, RMSEP, and RMSECV values for the OPLS-DA model were low, and the model’s sensitivity, accuracy, and specificity were all 100%, showing that it is the excellent one. In addition, PCA-class and OPLS-DA obtained scores of 27/32 and 26/32, respectively, for detecting adulterated and other TCM reference flower samples from C. nitidissima. Combining an infrared spectroscopic method with a chemometric approach proved that it is possible to differentiate distinct sections of C. nitidissima and discriminate adulterated samples of C.nitidissima flower.

Use of ATR-FTIR Spectroscopy and Chemometrics for the Variation of Active Components in Different Harvesting Periods of Lonicera japonica

Lonicera japonica Thunb is a commonly used Chinese herbal medicine, which belongs to the family Caprifoliaceae. The active components varied greatly during bud development. Research on the variation of the main active components is significant for the timely harvesting and quality control of Lonicera japonica. In this study, the attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) combined with the chemometric method was performed to investigate the variability of different harvesting periods of Lonicera japonica. The preliminary characterization from ATR-FTIR fingerprints showed various characteristic absorption peaks of the main active components from the different harvesting times, such as flavonoids, organic acids, iridoids, and volatile oils. Additionally, principal component analysis (PCA) scatter plots showed that there was a clear clustering trend in the samples of the same harvesting period, and the samples of the different harvesting periods could be well distinguished. Finally, further analysis by the orthogonal partial least-squares discriminant analysis (OPLS-DA) showed that there were regular changes in flavonoids, phenolic acids, iridoids, and volatile oils in different harvesting periods. Therefore, ATR-FTIR, as a novel and convenient analytical method, could be applied to evaluate the quality of Lonicera japonica.

LC-MS metabolomics analysis of Stevia rebaudiana Bertoni leaves cultivated in Malaysia in relation to different developmental stages

INTRODUCTION

Stevia is known for its sweet taste, attributed to the presence of steviol glycosides. Although reports on the dynamic changes of steviol glycosides during development of stevia are available, the data are mainly focused on stevioside and rebaudioside A. Information concerning the comprehensive metabolite profile of stevia in relation to different developmental stages is still lacking.

OBJECTIVE

This study investigated the metabolite changes along the developmental stages of a local stevia cultivar.

METHODOLOGY

Stevia leaves were harvested at 4 different developmental stages (early vegetative, late vegetative, budding, and flowering). Samples were then subjected to LC-MS metabolomics analysis to determine the metabolite variations.

RESULTS

A total of 55 metabolites, comprising phenolic acids, flavonoids, and terpenoids were identified by MS/MS analysis of the stevia leaf extracts, revealing a metabolite profile which was comparatively similar with those of cultivars grown in other countries. PLS-DA differentiated the early vegetative stage stevia leaf samples from those of the later stages by higher content of phenolic acids. The leaf metabolomes of the later 3 stages (late vegetative, budding, and flowering) were collectively richer in flavonoids. Meanwhile, the content of steviol glycosides is highest during the late vegetative and budding stages.

CONCLUSION

The present study provided, for the first time, a general overview of the metabolite variations with regard to the different developmental stages of stevia. The information may facilitate decision making of suitable harvesting times for higher yields of steviol glycosides or a more balanced metabolite profile in terms of pharmacologically useful metabolites.

Machine learning methods to predict the cultivation age of Panacis Quinquefolii Radix

Background

American ginseng (AG) is a valuable medicine widely consumed as a herbal remedy throughout the world. Huge price difference among AG with different growth years leads to intentional adulteration for higher profits. Thus, developing reliable approaches to authenticate the cultivation ages of AG products is of great use in preventing age falsification.

Methods

A total of 106 batches of AG samples along with their 9 physicochemical features were collected and measured from experiments, which was then split into a training set and two test sets (test set 1 and 2) according to the cultivation regions. Principle component analysis (PCA) was carried out to examine the distribution of the three data sets. Four machine learning (ML) algorithms, namely elastic net, k-nearest neighbors, support vector machine and multi-layer perception (MLP) were employed to construct predictive models using the features as inputs and their growth years as outputs. In addition, a similarity-based applicability domain (AD) was defined for these models to ensure the reliability of the predictive results for AG samples produced in different regions.

Results

A positive correlation was observed between the several features and the growth years. PCA revealed diverse distributions among different cultivation regions. The most accurate model derived from MLP shows good prediction power for the fivefold cross validation and the test set 1 with mean square error (MSE) of 0.017 and 0.016 respectively, but a higher MSE value of 1.260 for the test set 2. After applying the AD, all models showed much lower prediction errors for the test samples within AD (IDs) than those outside the AD (ODs). MLP remains the best predictive model with an MSE value of 0.030 for the IDs.

Conclusion

Cultivation years have a close relationship with bioactive components of AG. The constructed models and AD are also able to predict the cultivation years and discriminate samples that have inaccurate prediction results. The AD-equipped models used in this study provide useful tools for determining the age of AG in the market and are freely available at https://github.com/dreadlesss/Panax_age_predictor.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00511-5.

Shrimp count size: GC/MS-based metabolomics approach and quantitative descriptive analysis (QDA) reveal the importance of size in white leg shrimp (Litopenaeus vannamei)

INTRODUCTION

"Count size" is a term used to represent the number of shrimps in one pound or kilogram that applies globally in the shrimp industry. Based on shrimp body weight, count sizes range over the smallest (> 70) up to the largest size (U15) of shrimp. Large shrimps are considered highly palatable; therefore, they are priced higher than the small shrimps. However, the pricing of shrimp has not been based on scientific findings since there have been no studies reporting the correlation between shrimp quality and shrimp size.

OBJECTIVE

In this study, we aimed to investigate the importance of shrimp size in terms of metabolite profile and sensory properties.

METHODS

Nine groups of Litopenaeus vannamei, categorized based on their body weight similarity, were collected from various sampling sites regardless of the difference in days of culture (count size 16/20, 21/25, 26/30, 41/50, and 51/60). Gas chromatography/mass spectrometry (GC/MS)-based metabolomics analysis was employed to characterize their metabolite profiles. Furthermore, a robust PLS regression model was constructed to predict the shrimp size using metabolome data. Following this, the difference in sensory attributes among commercial shrimp count sizes 21/25-41/50 was confirmed using quantitative descriptive analysis (QDA).

RESULTS

Small shrimp (> 70-51/60) had higher accumulation of proteinogenic and non-proteinogenic amino acids, sugars, and organic acids compared to large shrimps (41/50-16/20). The QDA of commercial count sizes (21/25-41/50) performed by trained panelists showed that sweetness, juiciness, crispness, and red color attributes increased with an increase in shrimp size. Based on the PLS model, proline as a sweet-tasting metabolite also showed an increased level along with the shrimp size.

CONCLUSIONS

These findings demonstrate the importance of shrimp count size with regard to shrimp quality.

Localization of constituents for determining the age and parts of ginseng through ultraperfomance liquid chromatography quadrupole/time of flight-mass spectrometry combined with desorption electrospray ionization mass spectrometry imaging

Ginseng has been used for prevention and treatment of disease for thousands of years in China and many other Asian countries. Phytochemical studies have indicated that ginsenosides, polysaccharides, alkaloids, and phenolic acids are the active constituents of ginseng. Main and branch roots of ginseng exhibit distinct bioactive behavior. Furthermore, the bioactive behavior of ginseng depends on its age. Traditional analysis is complex preparation and provides inadequate of chemical information of the original distribution of analytes. Therefore, in this study, ultraperformance liquid chromatography quadrupole/time of flight-mass spectrometry (UPLC-QTOF MS) and desorption electrospray ionization mass spectrometry imaging (DESI-MSI) combined with orthogonal partial least squares discriminant analysis were used to discriminate ginseng in different age and parts of ginseng, and profiled distribution of selected markers. The results indicated that UPLC-QTOF-MS and DESI-MSI could be used to determine the parts and age of ginseng. Fifteen variables including five of protopanaxatriol (PPT), four of protopanaxadiol (PPD), and six of other types were assumed as markers for different parts of ginseng. Moreover, four variables of PPT, four of PPD, and ten of other types were used to determine the age of ginseng samples. An analysis of localization of markers indicated that malonyl ginsenoside, including malonyl-ginsenoside Rb₁, Rb₂, Rc, and Rd was mainly distributed in the corks. Neutral ginsenoside Rg₁, yesanchinoisde D, and chikusetsusaponin Iva were mainly distributed in the cork and phloem. Non-ginsenoside castanoside H, 20(S)-protopanaxatriol, unknown 2, saponin III and cistanoside C were distributed in all tissues. Ethyloleate, unknown 1 and monolinolein were distributed in the cork.

Phytochemical analysis of Panax species: a review

Panax species have gained numerous attentions because of their various biological effects on cardiovascular, kidney, reproductive diseases known for a long time. Recently, advanced analytical methods including thin layer chromatography, high-performance thin layer chromatography, gas chromatography, high-performance liquid chromatography, ultra-high performance liquid chromatography with tandem ultraviolet, diode array detector, evaporative light scattering detector, and mass detector, two-dimensional high-performance liquid chromatography, high speed counter-current chromatography, high speed centrifugal partition chromatography, micellar electrokinetic chromatography, high-performance anion-exchange chromatography, ambient ionization mass spectrometry, molecularly imprinted polymer, enzyme immunoassay, ¹H-NMR, and infrared spectroscopy have been used to identify and evaluate chemical constituents in Panax species. Moreover, Soxhlet extraction, heat reflux extraction, ultrasonic extraction, solid phase extraction, microwave-assisted extraction, pressurized liquid extraction, enzyme-assisted extraction, acceleration solvent extraction, matrix solid phase dispersion extraction, and pulsed electric field are discussed. In this review, a total of 219 articles published from 1980 to 2018 are investigated. Panax species including P. notoginseng, P. quinquefolius, sand P. ginseng in the raw and processed forms from different parts, geographical origins, and growing times are studied. Furthermore, the potential biomarkers are screened through the previous articles. It is expected that the review can provide a fundamental for further studies.

Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng

The grading of ginseng (Panax ginseng) including the evaluation of internal quality attributes is essential in the ginseng industry for quality control. Assessment for inner whitening, a major internal disorder, must be conducted when identifying high quality ginseng. Conventional methods for detecting inner whitening in ginseng root samples use manual inspection, which is time-consuming and inaccurate. This study develops an internal quality measurement technique using near-infrared transmittance spectral imaging to evaluate inner whitening in ginseng samples. Principle component analysis (PCA) was used on ginseng hypercube data to evaluate the developed technique. The transmittance spectra and spectral images of ginseng samples exhibiting inner whitening showed weak intensity characteristics compared to normal ginseng in the region of 900-1050 nm and 1150-1400 nm respectively, owing to the presence of whitish internal tissues that have higher optical density. On the basis of the multivariate analysis method, even a simple waveband ratio image has the great potential to quickly detect inner whitening in ginseng samples, since these ratio images show a significant difference between whitened and non-whitened regions. Therefore, it is possible to develop an efficient and rapid spectral imaging system for the real-time detection of inner whitening in ginseng using minimal spectral wavebands. This novel strategy for the rapid, cost-effective, non-destructive detection of ginseng's inner quality can be a key component for the automation of ginseng grading.