Stable isotope characterization of tobacco products: A determination of synthetic or natural nicotine authenticity.

RATIONALE: "Tobacco-free" or synthetic nicotine products have appeared in some markets, increasing potential health risks and regulatory compliance challenges. Currently, there are few reliable methods for the determination of authenticity of natural and synthetic nicotine. Analytical techniques based on stable isotopes have broad application prospects in the traceability and identification of agricultural products. METHODS: Tobacco leaves from four main tobacco production regions in China and different types of tobacco products were extracted with n-hexane and 5% sodium hydroxide to obtain nicotine extracts. Subsequent stable isotope mass spectrometry was performed by analyzing δ2 H, δ13 C, and δ15 N values of nicotine. RESULTS: Firstly, results from a batch of 233 samples indicated stable isotopes were closely related to climate and geographical locations and provide a basis for a determination of the origin of tobacco leaves. In addition, the δ2 H values had significant differences between natural and synthetic nicotine and the results indicate a δ2 H value of -163.0‰ could be the threshold for assessing synthetic and natural nicotine. Finally, a total of 239 results further validated the δ2 H value as a metric for source authentication of commercial tobacco products. CONCLUSIONS: Synthetic (S)-(-)-nicotine could be accurately and quickly identified using the method developed by measuring δ2 H values in a qualitative manner. To our knowledge, this is the first time a stable isotope mass spectrometry technique has been used for distinguishing the source of nicotine. This technique will aid in the accurate identification, labelling, and regulation of synthetic nicotine-based tobacco products.

Structure and Electron Configuration of Imidazole-2-carboxaldehyde and Its Excited Triplet: Resonance Raman and Transient Absorption Spectroscopy and DFT Calculation Investigations.

Imidazole-2-carboxaldehyde (IC) can be generated in atmospheric waters and absorbs solar radiation in the near UV region to produce its excited triplet state (3IC), which contributes to the formation of a secondary organic aerosol (SOA). The photoreactivity of IC is significantly influenced by its surroundings, such as water and acidic environment, because IC is capable of transforming into gem-diol under above conditions. Meanwhile, the electron configuration of 3IC is critical in elucidating the reaction mechanism of 3IC with other anthropogenic and biogenic volatile organic compounds (VOCs). In this study, steady-state and time-resolved resonance Raman as well as transient absorption spectroscopic experiments were conducted to provide vibrational and kinetic information on IC and 3IC in the presence of water and acid conditions. Using density functional theory (DFT) calculations, the H-bonding at the carbonyl O was confirmed and the hydrated structure of IC and 3IC was determined. 1,4-Cyclohexadiene is a good hydrogen donor, and it has a second-order rate constant of ∼107 M-1 s-1 toward 3IC. The results of CASSCF calculations suggest that the hydrogen abstraction may involve the transition from the ππ* to nπ* triplet state via the surface-crossing point.

Authenticating bioplastics using carbon and hydrogen stable isotopes - An alternative analytical approach.

RATIONALE: A combination of stable carbon (δ13 C) and hydrogen (δ2 H) isotope ratios and carbon content (% C) was evaluated as a rapid, low-cost analytical approach to authenticate bioplastics, complementing existing radiocarbon (14 C) and Fourier transform infrared (FTIR) analytical methods. METHODS: Petroleum- and bio-based precursor materials and in-market plastics were analysed and their δ13 C, δ2 H and % C values were used to establish isotope criteria to evaluate plastic claims, and the source and biocontent of the samples. 14 C was used to confirm the findings of the isotope approach and FTIR analysis was used to vertify the plastic type of the in-market plastics. RESULTS: Distinctive carbon and hydrogen stable isotope ratios were found for authentic bio-based and petroleum-based precursor plastics, and it was possible to classify in-market plastics according to their source materials (petroleum, C3, C4, and mixed sources). An estimation of C4 biocontent was possible from a C4-petroleum isotope mixing model using δ13 C which was well correlated (R2 = 0.98) to 14 C. It was not possible to establish a C3-petroleum isotope mixing model due to δ13 C isotopic overlap with petroleum plastics; however, the addition of δ2 H and % C was useful to evaluate if petroleum-bioplastic mixes contained C3 bioplastics, and PLS-DA modelling reliably clustered each plastic type. CONCLUSIONS: A combined dual stable isotope and carbon content approach was found to rapidly and accurately identify C3 and C4 bio-based products from their petroleum counterparts, and identify instances of petroleum and bio-based mixes frequently found in mislabelled bioplastics. Out of 37 in-market products labelled as bioplastic, 19 were found to contain varying amounts of petroleum-based plastic and did not meet their bio-based claims.

Geographical traceability of Chinese green tea using stable isotope and multi-element chemometrics.

RATIONALE: Deliberate and fraudulent origin mislabeling of Chinese green tea motivated by large price differences often brings significant food safety risks and damages consumer trust. Currently, there is no reliable method to verify the origin of green tea produced in China. Stable isotope and multi-element analyses combined with statistical models are widely acknowledged as useful traceability techniques for many agro-products, and could be developed to confirm the geographical origin of Chinese green tea and, more importantly, combat illegal green tea mislabeling and fraud. METHODS: An analytical strategy combining elemental analyzer/isotope ratio mass spectrometry (EA/IRMS) and inductively plasma coupled mass spectrometry (ICP-MS) with chemometrics tools was used to confirm the origin of green tea grown in the main tea production provinces around China. Stable C, N, H, O isotope ratios and twenty elements were measured to build mathematical discriminant models using unsupervised principal component analysis (PCA) and supervised linear discriminant analysis (LDA). Two main problems: (i) tracing the origin of Chinese green tea from different tea growing provinces (Zhejiang, Shandong, and other provinces); (ii) authentication of high-value Westlake Longjing tea from the Westlake region and surrounding areas in Zhejiang province, were investigated and assessed. RESULTS: The results demonstrated that PCA and follow-up LDA based on stable isotope and multi-element signatures can verify the geographical origin of Chinese green tea from different provinces, and even localized zones in the same province could be distinguishable, with discrimination accuracies higher than 92.3% and 87.8%, respectively. CONCLUSIONS: Geochemical fingerprinting techniques coupled with chemometric tools offer an accurate and effective verification method for the geographical origin of Chinese green tea, providing a promising tool to combat fraudulent mislabeling of high-value green tea.

Influence of leaf age, species and soil depth on the authenticity and geographical origin assignment of green tea.

RATIONALE: Stable isotope fractionation occurring during leaf growth provides internal characteristics for identifying the geographical origin, traceability and authentication of tea. Studying the influence of leaf age, species and the relationship with the cultivated soil may reveal previously undocumented stable isotope fractionation mechanisms, and provide a deeper understanding of the physiological isotopic effects on the tractability and authentication accuracy of green tea to combat mislabeling and fraudulent conduct. METHODS: A total of 36 pairs of young (one bud with one leaf) and mature growth (older leaf) samples from two species of Longjing tea (Longjing #43 and Colonial cultivar) and corresponding cultivation soil samples from two different depth layers (0-20 cm and 20-40 cm) were collected in Westlake district, Hangzhou, Zhejiang province, China. Four stable isotope ratios (δ13 C, δ15 N, δ2 H, and δ18 O values) were measured using an elemental analyzer coupled with an isotope ratio spectrometer. Linear correlation and one-way analysis of variance (ANOVA) statistical analyses were performed to investigate isotopic fractionation mechanisms during plant growth, and reflect the dynamic physiological processes from soil to leaf. RESULTS: The carbon and nitrogen isotope ratios (δ13 C and δ15 N values) reflected the absorption, migration and fractionation of carbon dioxide and nitrogenous nutrients during photosynthesis, nutrient uptake, nitrogen fixation and leaf respiration. The water isotope ratios (δ2 H and δ18 O values) reflected the use and fractionation of water by tea plants at different growth stages. CONCLUSIONS: Considerable differences were found for hydrogen and oxygen isotope ratios according to leaf age, revealing complex isotopic fractionation mechanisms and possible interference factors. Leaf maturity effects should be considered, as they will influence the precision and accuracy of models when assigning the geographical origin, traceability and authentication of tea.

Effects of Water Isotope Composition on Stable Isotope Distribution and Fractionation of Rice and Plant Tissues.

Rice origin authenticity is important for food safety and consumer confidence. The stable isotope composition of rice is believed to be closely related to its water source, which affects its origin characteristics. However, the influence of water availability on the distribution of rice stable isotopes (δ2H and δ18O) is not clear. In this study, three irrigation waters with different isotopic values were used to investigate isotopic water use effects of Indica and Japonica rice, using pot experiments. Under three different water isotope treatments, the δ2H values of Indica polished rice showed significant differences (-65.0 ± 2.3, -60.5 ± 0.8 and -55.8 ± 1.7‰, respectively, p < 0.05) compared to δ13C and δ15N, as did Japonica polished rice. The values of δ2H and δ18O of rice became more positive when applying more enriched (in 2H and 18O) water, and the enrichment effect was higher in rice than in the corresponding plant tissue. In addition, the δ2H and δ18O values of Indica rice leaves decreased at the heading stage, increased at the filling stage, and then decreased at the harvest stage. Japonica rice showed a similar trend. δ2H changes from stem to leaf were more negative, but δ18O changes were more positive, and δ2H and δ18O values from leaf to rice were more positive for both brown and polished rice. The results from this study will clarify different water isotopic composition effects on rice and provide useful information to improve rice origin authenticity using stable isotope-based methods.

Aberrant angiogenic signaling pathways: Accomplices in ovarian cancer progression and treatment.

Ovarian cancer is one of the most common malignant tumors in women, and treatment options are limited. Despite efforts to adjust cancer treatment models and develop new methods, including tumor microenvironment (TME) therapy, more theoretical support is needed. Increasing attention is being given to antiangiogenic measures for TME treatment. Another important concept in ovarian cancer TME is angiogenesis, where tumor cells obtain nutrients and oxygen from surrounding tissues through blood vessels to support further expansion and metastasis. Many neovascularization signaling pathways become imbalanced and hyperactive during this process. Inhibiting these abnormal pathways can yield ideal therapeutic effects in patients, even by reversing drug resistance. However, these deep TME signaling pathways often exhibit crosstalk and correlation. Understanding these interactions may be an important strategy for further treating ovarian cancer. This review summarizes the latest progress and therapeutic strategies for these angiogenic signaling pathways in ovarian cancer.

Fertilizer Effects on the Nitrogen Isotope Composition of Soil and Different Leaf Locations of Potted Camellia sinensis over a Growing Season.

The nitrogen-stable isotopes of plants can be used to verify the source of fertilizers, but the fertilizer uptake patterns in tea (Camellia sinensis) plants are unclear. In this study, potted tea plants were treated with three types of organic fertilizers (OFs), urea, and a control. The tea leaves were sampled over seven months from the top, middle, and base of the plants and analyzed for the δ15N and nitrogen content, along with the corresponding soil samples. The top tea leaves treated with the rapeseed cake OF had the highest δ15N values (up to 6.6‱), followed by the chicken manure, the cow manure, the control, and the urea fertilizer (6.5‱, 4.1‱, 2.2‱, and 0.6‱, respectively). The soil treated with cow manure had the highest δ15N values (6.0‱), followed by the chicken manure, rapeseed cake, control, and urea fertilizer (4.8‱, 4.0‱, 2.5‱, and 1.9‱, respectively). The tea leaves fertilized with rapeseed cake showed only slight δ15N value changes in autumn but increased significantly in early spring and then decreased in late spring, consistent with the delivery of a slow-release fertilizer. Meanwhile, the δ15N values of the top, middle, and basal leaves from the tea plants treated with the rapeseed cake treatment were consistently higher in early spring and lower in autumn and late spring, respectively. The urea and control samples had lower tea leaf δ15N values than the rapeseed cake-treated tea and showed a generalized decrease in the tea leaf δ15N values over time. The results clarify the temporal nitrogen patterns and isotope compositions of tea leaves treated with different fertilizer types and ensure that the δ15N tea leaf values can be used to authenticate the organic fertilizer methods across different harvest periods and leaf locations. The present results based on a pot experiment require further exploration in open agricultural soils in terms of the various potential fertilizer effects on the different variations of nitrogen isotope ratios in tea plants.

Study on the correlation between color and taste of beauty tea infusion and the pivotal contributing compounds based on UV-visible spectroscopy, taste equivalent quantification and metabolite analysis.

This study utilized a colorimeter to determine the color values of 23 beauty tea (BT) samples, the color and the taste characteristics were also quantitatively described through ultraviolet-visible (UV-Vis) spectroscopy and taste equivalent quantification. Furthermore, metabolomic analysis was conducted by using ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS). Correlation analysis was employed to preliminarily identify the compounds that contribute to the color and taste of BT infusion. Finally, the contributing compounds were further determined through verification experiment. The results showed that within a certain range, as the color of BT infusion deepened, the taste became stronger, more bitter and astringent, while on the contrary, it became sweeter and mellower. Theaflavins, kaempferol, astragalin, and 5-p-coumaroylquinic acid influenced both the color and taste of the BT infusion. Gallic acid was also determined as a contributor to the color. This study provides new insights into research on tea quality in infusion color and taste aspects.

Comparative analysis of nitrogen content and its influence on actinorhizal nodule and rhizospheric microorganism diversity in three Alnus species.

Alnus spp. (alder) are typical nonleguminous nitrogen-fixing trees that have a symbiotic relationship with Frankia. To explore the differences in nitrogen-fixing microorganisms between three alders (A. cremastogyne, A. glutinosa, and A. formosana) with different chromosome ploidies, the community structure and compositional diversity of potential nitrogen-fixing microorganism in root nodules and rhizosphere soil were comparatively analyzed using 16S rRNA and nitrogenase (nifH) gene sequencing. The nitrogen contents in the root nodules and rhizosphere soil were also determined. The results showed that the contents of total nitrogen and nitrate nitrogen in the root nodules of the three alders are significantly higher than those in the rhizosphere soils, while the ammonium nitrogen content show the opposite trend. The family, genus, and species levels showed obviously differences between root nodules and rhizosphere soils, while there were no significant differences at the classification level between the three alders. At the phylum level, the dominant phyla from 16S rRNA and nifH gene data in the root nodules and rhizosphere soil of the three alders are phylum Actinomycetota and phylum Pseudomonadota, respectively. The LEfSe results showed that there are significant differences in the dominant groups in the root nodules and rhizosphere oil of the three alders. The relative abundances of dominant groups also showed obvious differences between the root nodules and rhizosphere soils of three alders. The relative abundances of Frankia and unclassified_Frankia in root nodules are obviously higher than those in rhizosphere soils, and their relative abundances in A. glutinosa root nodules are significantly higher than those in A. cremastogyne and A. formosana at the genus and species levels. The diversity of potential nitrogen-fixing microorganism from 16S rRNA and nifH gene data in the A. glutinosa root nodules and rhizosphere soils are all higher than those in A. cremastogyne and A. formosana. The results of functional prediction also showed that the OTUs for nitrogen fixation, nitrate respiration, and ureolysis in A. glutinosa root nodules are higher than those in the other two alders. Redundancy analysis revealed that the total nitrogen content mostly affects the Frankia community. Overall, there are significant differences in the community composition and structure of potential nitrogen-fixing microorganism in the root nodules and rhizosphere soils between the three alders. A. glutinosa showed a relatively stronger nitrogen fixation capacity than A. formosana and A. cremastogyne. The results help elucidates how the community structure and nitrogen-fixing ability of potential nitrogen-fixing microorganism differ between alder species and serve as a reference for applying Frankia to alder plantations.

A review of recent compound-specific isotope analysis studies applied to food authentication.

Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper provides a review of recent on-line and off-line CSIA applications of plant and animal origin foods, essential oils and plant extracts. Different food discrimination techniques, applications, scope, and recent studies are discussed. CSIA δ13C values are widely used to verify geographical origin, organic production, and adulteration. The δ15N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ2H and δ18O values are useful to link food products with local precipitation for geographical origin verification. Most CSIA techniques focus on fatty acids, amino acids, monosaccharides, disaccharides, organic acids, and volatile compounds enabling more selective and detailed origin and authentication information than bulk isotope analyses.. In conclusion, CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods.

Tracing the geographical origin of tobacco at two spatial scales by stable isotope and element analyses with chemometrics.

Tobacco is a widely cultivated cash crop, but it is often smuggled and sold illegally. Unfortunately, there is currently no way to verify the origin of tobacco in China. In an effort to address this issue, we conducted a study using stable isotopes and elements from 176 tobacco samples at both provincial and municipal scales. Our findings revealed significant differences in δ13C, K, Cs, and 208/206Pb at the provincial-level, and Sr, Se, and Pb at the municipal level. We created a heat map at the municipal level, which showed a similar cluster classification to geographic grouping and provided an initial assessment of tobacco origins. Using OPLS-DA modeling, we achieved a 98.3% accuracy rate for the provincial scale and 97.6% for the municipal scale. It is worth noting that the importance of rankings of variables varied depending on the spatial scale of the evaluation. This study offers the first traceability fingerprint dataset of tobacco and has the potential to combat mislabeling and fraudulent conduct by identifying the geographical origin of tobacco.

Application of hyperspectral imaging assisted with integrated deep learning approaches in identifying geographical origins and predicting nutrient contents of Coix seeds.

Coix seed (CS, Coix lachryma-jobi L. var. ma-yuen (Roman.) Stapf) has rich nutrients, including starch, protein and oil. The geographical origin with a protected geographical indication and high levels of nutrient contents ensures the quality of CS, but non-destructive and rapid methods for predicting these quality indicators remain to be explored. This paper proposed hyperspectral imaging (HSI) assisted with the integrated deep learning models of attention mechanism (AM), convolutional neural networks, and long short-term memory. The method achieved the effective wavelengths selection, the highest prediction accuracy for production region discrimination and the lowest mean absolute error and root mean squared error for nutrient contents prediction. Moreover, the wavelengths selected via the AM model were explicable and reliable for predicting the geographical origins and nutrient contents. The proposed combination of HSI with integrated deep learning models has great potential in the quality evaluation of CS.

Recent advances in Chinese food authentication and origin verification using isotope ratio mass spectrometry.

Over the last decade, isotope ratio mass spectrometry (IRMS) using up to 5 light stable isotopes (13C/12C, 2H/1H, 15N/14N, 18O/16O, 34S/32S) has become more widely applied for food origin verification as well as food authentication in China. IRMS technology is increasingly used to authenticate a range of food products including organic foods, honey, beverages, tea, animal products, fruits, oils, cereals, spices and condiments that are frequently unique to a specific region of China. Compared to other food authenticity and traceability techniques, IRMS has been successfully used to characterize, classify and identify many Chinese food products, reducing fraud and food safety problems and improving consumer trust and confidence. IRMS techniques also provides scientific support to enhance China's strict government regulatory policies. Isotope testing verifies geographical origin labelling of domestic and imported foods, protects and verifies high value foods that are unique to China, and indicates environmentally friendly farming practices such as 'green' or 'organic' methods. This paper reviews recently published Chinese research to highlight the recent advances of IRMS as a regulatory and verification tool for Chinese food products.

Effects of Light Shading, Fertilization, and Cultivar Type on the Stable Isotope Distribution of Hybrid Rice.

The effect of fertilizer supply and light intensity on the distribution of elemental contents (%C and %N) and light stable isotopes (C, N, H, and O) in different rice fractions (rice husk, brown rice, and polished rice) of two hybrid rice cultivars (maintainer lines You-1B and Zhong-9B) were investigated. Significant variations were observed for δ13C (-31.3 to -28.3‱), δ15N (2.4 to 2.7‱), δ2H (-125.7 to -84.7‱), and δ18O (15.1‱ to 23.7‱) values in different rice fractions among different cultivars. Fertilizer treatments showed a strong association with %N, δ15N, δ2H, and δ18O values while it did not impart any significant variation for the %C and δ13C values. Light intensity levels also showed a significant influence on the isotopic values of different rice fractions. The δ13C values showed a positive correlation with irradiance. The δ2H and δ15N values decreased with an increase in the irradiance. The light intensity levels did not show any significant change for δ18O values in rice fractions. Multivariate ANOVA showed a significant interaction effect of different factors (light intensity, fertilizer concentration, and rice variety) on the isotopic composition of rice fractions. It is concluded that all environmental and cultivation factors mentioned above significantly influenced the isotopic values and should be considered when addressing the authenticity and origin of rice. Furthermore, care should be taken when selecting rice fractions for traceability and authenticity studies since isotopic signatures vary considerably among different rice fractions.

Stable isotope and elemental profiles determine geographical origin of saffron from China and Iran.

Origin verification of high-value saffron is essential for fair trade and to protect consumers' interests and rights. A traceability method using elemental content (% C and % N) and stable isotopes (δ13C, δ2H, δ18O, and δ15N) combined with chemometrics was developed to discriminate saffron from Iran and China and classify major domestic production areas in China. Results showed that Iranian samples had lower % C and % N contents but higher δ13C values than Chinese origin saffron, with δ13C acting as an important variable for origin discrimination. Moreover, δ2H and δ13C isotopes were found to be important variables to classify Chinese regional saffron origin. Two supervised pattern recognition models (PLS-DA) developed to classify Iranian and Chinese saffron, and regional Chinese saffron had a discrimination accuracy of 85.0 % and 80.2 %, respectively. These models provide the basis for a new regulatory inspection procedure to verify saffron origin and label claims, minimizing fraudulent mislabeling and adding value to saffron from specific regions.

Combining stable isotope, multielement and untargeted metabolomics with chemometrics to discriminate the geographical origins of ginger (Zingiber officinale Roscoe).

Ginger (Zingiber officinale Roscoe) is a high-value food and herb worldwide. The quality of ginger is often related to its production regions. In this study, stable isotopes, multiple elements, and metabolites were investigated together to realize ginger origin traceability. Chemometrics showed that ginger samples could be preliminarily separated, and 4 isotopes (δ13C, δ2H, δ18O, and δ34S), 12 mineral elements (Rb, Mn, V, Na, Sm, K, Ga, Cd, Al, Ti, Mg, and Li), 1 bioelement (%C), and 143 metabolites were the most important variables for discrimination. Furthermore, three algorithms were introduced, and the fused dataset based on VIP features led to the highest accuracies for origin classification, with predictive rates of 98% for K-nearest neighbor and 100% for support vector machine and random forest. The results demonstrated that isotopic, elemental, and metabolic fingerprints were useful indicators for the geographical origins of Chinese ginger.

Comparison of greenhouse and field degradation behaviour of isoprocarb, hexaflumuron and difenoconazole in Perilla frutescens.

Isoprocarb, hexaflumuron and difenoconazole were used in Perilla frutescens at 600, 60 and 75 g a.i./ha respectively. High performance liquid chromatography-tandem mass spectrometry was used for residue determination because of high selectivity and simple treatment. The results showed that the half-lives of isoprocarb, hexaflumuron and difenoconazole at greenhouse condition were 0.71, 1.63 and 1.21 days respectively, and at field condition, the values were 1.13, 1.07 and 0.92 days respectively.

Geographical origin classification of peanuts and processed fractions using stable isotopes.

This study investigates the use of stable isotopes (C, N, H, and O) to characterize the geographical origin of peanuts along with different peanut fractions including whole peanut kernel, peanut shell, delipidized peanuts and peanut oil. Peanut samples were procured in 2017 from three distinctive growing regions (Shandong, Jilin, and Jiangsu) in China. Peanut processing significantly influenced the δ 13C, δ 2H, and δ 18O values of different peanut fractions, whereas δ 15N values were consistent across all fractions and unaffected by peanut processing. Geographical differences of peanut kernels and associated peanut fractions showed a maximum variance for δ 15N and δ 18O values which indicated their strong potential to discriminate origin. Different geographical classification models (SVM, LDA, and k-NN) were tested for peanut kernels and associated peanut fractions. LDA achieved the highest classification percentage, both on the training and validation sets. Delipidized peanuts had the best classification rate compared to the other fractions.

Nutrient content prediction and geographical origin identification of red raspberry fruits by combining hyperspectral imaging with chemometrics.

The geographical origin and the important nutrient contents greatly affect the quality of red raspberry (RRB, Rubus idaeus L.), a popular fruit with various health benefits. In this study, a chemometrics-assisted hyperspectral imaging (HSI) method was developed for predicting the nutrient contents, including pectin polysaccharides (PPS), reducing sugars (RS), total flavonoids (TF) and total phenolics (TP), and identifying the geographical origin of RRB fruits. The results showed that these nutrient contents in RRB fruits had significant differences between regions (P < 0.05) and could be well predicted based on the HSI full or effective wavelengths selected through competitive adaptive reweighted sampling (CARS) and variable iterative space shrinkage approach (VISSA). The best prediction results of PPS, RS, TF, and TP contents were achieved with the highest residual predictive deviation (RPD) values of 3.66, 3.95, 2.85, and 4.85, respectively. The RRB fruits from multi-regions in China were effectively distinguished by using the first derivative-partial least squares discriminant analysis (DER-PLSDA) model, with an accuracy of above 97%. Meanwhile, the fruits from three protected geographical indication (PGI) regions were successfully classified by using the orthogonal partial least squares discrimination analysis (OPLSDA) model, with an accuracy of above 98%. The study results indicate that HSI assisted with chemometrics is a promising method for predicting the important nutrient contents and identifying the geographical origin of red raspberry fruits.