Chiang Mai Journal of Science

Characteristic and Discriminant Analysis of Artemisia argyi from Different Origins Based on Their Stable Isotope Ratios

1. INTRODUCTION

     Artemisia argyi is the dried leaf of Artemisia argyi Levl. et Vant., a perennial herbaceous plant in the Asteraceae family. As a traditional bulk medicinal material in China, it possesses efficacies such as warming the meridians to stop bleeding, dispelling cold to alleviate pain, and regulating qi to calm the fetus. It is commonly prescribed for conditions including hematemesis, epistaxis, vaginal bleeding during pregnancy, and cold pain in the lower abdomen [1-6]. In recent years, with the enhancement of public health awareness and increasing recognition of traditional Chinese medicine, the market demand for A. argyi—the core material for moxibustion therapy—has continued to rise. According to statistics from the National Forestry and Grassland Administration, the annual demand for A. argyi ranges from 50,000 to 100,000 metric tons. This trend has driven the large-scale cultivation of A. argyi and the rapid development of related industries. However, differences in ecological factors such as soil, rainfall, and sunlight across producing regions can lead to variations in the synthesis and accumulation of secondary metabolites in medicinal plants [7]. This is also a key factor contributing to the substantial fluctuations in the quality of A. argyi from different origins. Studies have shown that the quality of A. argyi varies markedly depending on its geographical source [8-10]. Such variability not only seriously affects the clinical efficacy of A. argyi but also hinders the healthy development of its industrial chain. Therefore, there is an urgent need for accurate geographical origin tracing to enable effective quality control, ensuring the efficacy, consistency, and safety of its clinical application.
     In recent years, with the rapid advancement of analytical technologies, techniques such as infrared spectroscopy, high-performance liquid chromatography (HPLC), and inductively coupled plasma mass spectrometry (ICP-MS) have been applied to develop origin traceability methods for various Chinese medicinal materials. However, these approaches often suffer from drawbacks including complex procedures and long analysis times. Stable isotope-based origin traceability has emerged as a novel technique for authenticating materials of regional typicity [11-13]. The stable isotope composition in medicinal materials originates from the natural fractionation effects that occur during material exchange between the medicinal plants and their ecological environment [14, 15]. This process is primarily influenced by factors such as the local climate, soil, and biological metabolism at the place of origin. As this process encodes unique environmental signatures of the origin and remains unaffected by human intervention, stable isotopes can serve as a “natural fingerprint” to characterize the geographical source of medicinal materials [16, 17]. Among various isotopes, the ratios of carbon (C), nitrogen (N), hydrogen (H), and oxygen(O) isotopes serve as crucial indicators for authenticity verification and geographical origin tracing. These indicators have been widely applied in the authenticity identification and origin traceability of agricultural products—such as edible fungi, grains, and tea [18-25]—as well as Chinese medicinal materials [26-30]. However, it remains unreported whether significant differences exist in the stable C, N, H, and O isotope compositions of A. argyi from different regions, and whether this technology is feasible for tracing its origin. Historical Chinese herbological texts record several traditional production regions for authentic A. argyi. These include Siming (now Ningbo, Zhejiang) producing ‘Hai Ai’ (海艾), Fudao (now Anyang, Henan) producing ‘Bei Ai’ (北艾), Qizhou (now Qichun, Hubei) producing ‘Qi Ai’ (蕲艾), and Qizhou (now Anguo, Hebei) producing a product similarly pronounced ‘Qi Ai’ but written with a different Chinese character as ‘Qi Ai’ (祁艾) [31–33]. Although the two ‘Qi Ai’ names are phonetically identical in Mandarin, they refer to distinct geographical origins and are represented by different Chinese characters (蕲 vs. 祁), each carrying its own historical and regional identity. At present, the A. argyi industry in Nanyang City, Henan Province, has been developing rapidly and continuously, with its industrial scale ranking first nationally. Hence, conducting origin traceability research on A. argyi from these five major production areas encompasses the current primary producing regions in China, holding significant practical importance. Based on this rationale, this study collected a total of 75 A. argyi samples from these five main production areas, determined the C, N, H, and O isotope ratios in the samples, and evaluated the discriminative efficacy of stable isotope technology for origin tracing by integrating statistical analysis methods. The aim is to provide a theoretical foundation for the origin traceability and healthy industrial development of A. argyi.

2. MATERIALS AND METHODS

2.1 Instruments and Equipment
     The instruments used were a Flash EA-1112 elemental analyzer (Thermo Electron SPA Co., USA), a 253-Plus isotope ratio mass spectrometer (Thermo Fisher Scientific Co., USA), an MS-105 electronic balance (Mettler-Toledo Inc., Switzerland), and an FSJ-A05N6 Micro grinder (Guangdong Bear Electric Co., Ltd.).

2.2 Sample Collection
     During the harvesting period of A. argyi from May to June 2024, samples were collected from Nanyang City in Henan Province, Anyang City in Henan Province, Huanggang City in Hubei Province, Ningbo City in Zhejiang Province, and Baoding City in Hebei Province. All collected samples were identified by Professor Zhang Chaoyun of Nanyang Institute of Technology as the dried leaves of Artemisia argyi Levl. et Vant., a herbaceous species of the genus Artemisia in the Asteraceae family. After removing impurities, the A. argyi samples were sorted, dried, cut into pieces, and thoroughly mixed. The processed samples were then stored in a desiccator for subsequent use.

2.3 Measurement of Stable C and N Isotope Ratios
     Approximately 2.0–3.0 mg of A. argyi powder was weighed into a tin capsule and introduced into an elemental analyzer via an autosampler. Within the analyzer, the sample underwent instant high-temperature combustion in an oxygen-rich atmosphere. In the presence of Cr₂O₃, the sample was oxidized to CO₂ and nitrogen oxides. Subsequently, the nitrogen oxides were reduced to N₂ over a copper reactor. Through this process, the carbon and nitrogen elements in the sample were converted into CO₂ and N₂, respectively. The generated CO₂ and N₂ were then carried by a helium (He) stream into an isotope ratio mass spectrometer (IRMS) for the determination of their isotope ratios. The operational parameters were set as follows: oxygen injection time, 3 s; pyrolysis furnace temperature, 1100 °C; He carrier gas flow rate, 180 mL/min; reference CO₂ gas flow rate, 100 mL/min; and oxygen gas flow rate, 200 mL/min.
     For quality control and calibration, certified reference materials (IAEA-CH-6, δ¹³C = -10.45‰; IAEA-N-1, δ¹⁵N = 0.4‰) were analyzed every 8 samples to correct for instrumental drift. Isotope ratios were normalized to the Vienna Pee Dee Belemnite (VPDB) scale (δ¹³C) and Air scale (δ¹⁵N). Analytical precision, verified via replicate analyses of both homogenized A. argyi subsamples and certified reference materials, consistently met the stringent performance specifications established for high-resolution stable isotope ratio determinations in ecological and phytochemical research.

2.4 Measurement of Stable H and O Isotope Ratios
     Approximately 1.0–2.0 mg of A. argyi powder was weighed into a silver capsule and allowed to equilibrate at ambient temperature for 48 hours. The sample was then introduced into an elemental analyzer via an autosampler. Within the analyzer, the sample underwent high-temperature pyrolysis to generate CO and H₂, meaning the hydrogen and oxygen elements in the sample were converted into H₂ and CO, respectively. The resulting H₂ and CO were carried by a helium (He) stream into an isotope ratio mass spectrometer (IRMS) for analysis. The instrument parameters were set as follows: carrier gas (He) flow rate, 150 mL/min; purge gas (He) flow rate, 200 mL/min; and pyrolysis furnace temperature for H and O, 1380 °C.
     For calibration and quality control, the matrix-matched certified reference material USGS43 (L-glutamic acid, δ²H = -21.3‰, δ¹⁸O = 28.6‰) was analyzed every 8 samples to correct for instrumental drift and matrix-induced biases. All δ²H and δ¹⁸O values were normalized to the VSMOW-SLAP scale per IAEA guidelines. Analytical precision, validated via replicate analyses of homogenized A. argyi subsamples and reference materials, consistently met stringent performance criteria for high-precision stable isotope analysis in plant biogeochemistry.

2.5 Calculation of Stable Isotope Ratios
     The stable isotope ratios of C, N, H, and O are expressed as δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O, respectively. The international reference standards for these values are Vienna Pee Dee Belemnite (V-PDB) for δ¹³C, atmospheric air (Air) for δ¹⁵N, and Vienna Standard Mean Ocean Water (V-SMOW) for δ²H and δ¹⁸O. The isotope ratio is calculated using the following formula: δ (‰) = (R_sample / R_standard − 1) × 1000, where R represents the abundance ratio of the heavy to light isotope (i.e., ¹³C/¹²C, ¹⁵N/¹⁴N, ²H/¹H, and ¹⁸O/¹⁶O).

2.6 Data Analysis
     SPSS 19.0 and SIMCA-p 13.5 software were used to analyze the measured data and plot graphs. For discriminant analysis, the leave-one-out cross-validation (LOOCV) method was applied to evaluate the classification performance, i.e., each sample was iteratively excluded from the training set and predicted by the model built on the remaining samples.

3. RESULTS

3.1 Differences in δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O Among A. argyi from Different Origins
     The δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O values for A. argyi samples from different origins are presented in Table 1. Multiple comparisons and analysis of variance indicated considerable variation in these isotopic signatures across the production regions. The highest δ¹³C values were observed in A. argyi from Nanyang, Henan, with a mean value of –27.98‰, which was significantly higher (P < 0.05) than those from all other origins.Values then decreased in the order A. argyi from Qichun (Hubei), Anyang (Henan), Anguo (Hebei), and Ningbo (Zhejiang). For δ²H, the highest mean value (–89.51‰) was also found in samples from Nanyang, Henan, differing significantly from other origins. Samples from Anguo (Hebei), Anyang (Henan), and Qichun (Hubei) showed intermediate δ²H values, with means of –94.52‰, –96.49‰, and –94.98‰, respectively. No significant differences were detected among these three, but their values were all significantly higher than that of samples from Ningbo (Zhejiang), which had the lowest mean δ2H value (–103.67‰). Regarding δ¹⁸O, the highest mean value (27.55‰) was recorded for A. argyi from Qichun, Hubei, which differed significantly from other origins. Samples from Nanyang and Anyang in Henan Province exhibited intermediate δ¹⁸O values, with means of 25.46‰ and 24.59‰, respectively. While no significant difference existed between these two, their values were significantly higher than those from Ningbo (Zhejiang) and Anguo (Hebei). The latter two origins had relatively lower and statistically similar mean δ¹⁸O values of 23.05‰ and 23.10‰, respectively. For δ¹⁵N, relatively higher mean values were observed in samples from Nanyang (Henan) and Anguo (Hebei), at 3.15‰ and 4.58‰, respectively. These two did not significantly differ from each other but were significantly higher than those from the other three origins. A. argyi from Anyang (Henan), Ningbo (Zhejiang), and Qichun (Hubei) showed relatively lower mean δ¹⁵N values of 0.49‰, –0.14‰, and –1.44‰, respectively, with no significant differences among them.

Y (Qichun, Hubei) =－32.617 δ¹³C－4.869 δ²H＋5.762 δ¹⁸O＋0.972 δ¹⁵N－778.696,

Y (Nanyang, Henan) =－32.541 δ¹³C－4.609 δ²H＋4.744 δ¹⁸O＋1.799 δ¹⁵N－726.377,

Y (Ningbo, Zhejiang) =－37.321 δ¹³C－5.351 δ²H＋3.038 δ¹⁸O＋1.690 δ¹⁵N－898.154,

Y (Anguo, Hebei) =－36.826 δ¹³C－4.956 δ²H＋2.961 δ¹⁸O＋2.475 δ¹⁵N－843.626,

Y (Anyang, Henan) =－34.558 δ¹³C－4.975 δ²H＋4.131 δ¹⁸O＋1.542 δ¹⁵N－802.484.

     As indicated by the discriminant functions above, δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O were all selected as discriminant variables. This result confirms that each of these isotopes serves as a significant variable in the Fisher discriminant functions, highlighting their individual importance in discriminating the geographical origin of A. argyi.
     The established discriminant functions were applied to classify A. argyi samples from different geographical origins, and the classification results were validated using the leave-one-out cross-validation method. The discriminant analysis results for each origin are presented in Table 3. In the original classification, all samples from Qichun, Hubei, were correctly classified, achieving a 100% correct rate. The correct classification rates for samples from Nanyang (Henan), Ningbo (Zhejiang), Anguo (Hebei), and Anyang (Henan) were 80.0%, 93.3%, 93.3%, and 80.0%, respectively. In the cross-validation, the correct classification rates were 93.3% for Qichun samples, 80.0% for Nanyang samples, 73.3% for Ningbo samples, 86.7% for Anguo samples, and 73.3% for Anyang samples.
     In summary, the discriminant model established in this study based on chemometric methods achieved an overall correct classification rate of 89.3% in the original classification and 81.3% in cross-validation. The results demonstrate that this method can effectively differentiate A. argyi from different geographical origins, exhibiting high discriminative accuracy and robustness. This also confirms the feasibility of using discriminant analysis for origin identification of A. argyi, providing a technical reference for its geographical traceability and quality control.

4. DISCUSSION

     This study applied stable isotope traceability technology to investigate the regional typicity of A. argyi, a bulk medicinal material, using stable isotope ratios combined with chemometric methods. We evaluated the discriminative efficacy of stable isotope technology for tracing the geographical origin of A. argyi. The principal component analysis (PCA) results confirmed the feasibility of classifying and evaluating A. argyi from different origins using stable isotope technology. The discriminant analysis showed an initial correct classification rate of 89.3%, with a cross-validated rate of 81.3%. This indicates that stable isotope ratios, as integrative and endogenous indicators, can effectively capture the “regional effect” shaped by the combined influence of various ecological factors at the origin. Consequently, this approach overcomes the strong subjectivity inherent in traditional morphological identification. The constructed model not only demonstrates good classification performance but also exhibits considerable robustness, holding potential for practical application in origin traceability. These findings are consistent with studies on the origin traceability of other medicinal materials, such as Panax ginseng [34], Panax quinquefolius [35], and Atractylodes macrocephala [36]. All these studies achieved discrimination of medicinal materials from different origins by measuring stable isotope ratios (e.g., C, N, H, O), validating the feasibility of stable isotopes serving as a “natural fingerprint” reflecting the origin environment. However, in the study on Atractylodes macrocephala [36], the correct classification rate of the established stable isotope discriminant model was 88.17%, whereas combining it with mineral elements achieved a 100% correct rate. This suggests that for production regions with similar ecological environments, a single chemical fingerprint may have a resolution ceiling. Integrating multi-dimensional traceability technologies can yield a more comprehensive “regional fingerprint”, thereby enhancing the accuracy and reliability of origin discrimination. This also provides a valuable reference for future research on precise origin traceability of A. argyi and other medicinal materials.
     The observed discriminatory power can be attributed to the tight coupling between the stable isotope composition of plant tissues and their local growth environment. Ecological factors essential for the growth of medicinal plants—such as climate, soil, and hydrology—are closely linked to their growth, development, and quality, and carry fingerprint characteristics imprinted with geographical information. The stable isotope composition of C, H, O, and N in organisms undergoes fractionation due to influences from the ecological environment and the type of biological metabolism, resulting in natural variations in the abundance of heavy and light isotopes among materials from different sources. The δ¹³C, δ²H, δ¹⁸O, and δ¹⁵N values determined in this study reflect distinct environmental and physiological information. Specifically, δ¹³C values primarily indicate a plant's water-use efficiency and photosynthetic pathway, which are influenced by factors such as precipitation, air humidity, and the degree of water stress. δ²H and δ¹⁸O values mainly reflect the water source information of the origin and also record details related to plant evapotranspiration. δ¹⁵N values reflect the soil nitrogen cycle processes and nitrogen source information, affected by factors such as the soil type, field fertilization practices, and organic matter content at the production site. In this study, the correct classification rates for Nanyang (Henan) and Anyang (Henan) were relatively low. Among the Nanyang samples, one was misclassified as Anyang and two were misclassified as Qichun (Hubei). Among the Anyang samples, one was misclassified as Nanyang, one as Qichun (Hubei), and one as Anguo (Hebei). The geographical proximity of Henan, Hebei, and Hubei provinces, where these misclassified samples originated, results in similar climatic and ecological conditions. This is likely the primary reason for the partial deviations observed in the model's discrimination.
     However, this study has certain limitations. Although the samples covered the five main regions known for regional typicity, the sample size (n = 75) and geographical coverage remain relatively limited. Moreover, regarding the validation procedure, the leave-one-out cross-validation employed herein, while appropriate for the present sample size, may provide an optimistic estimate of the model’s generalizability. Given the limited number of samples per origin (n = 15), the cross-validated accuracy (81.3%) should be interpreted with caution, as it reflects the model’s stability within the current dataset rather than its predictive performance on entirely independent external samples. A potential inflation of accuracy could arise from the inherent similarities among samples sharing the same cultivation conditions within each region.
     Consequently, the reported cross-validation rates represent an upper-bound estimate of discriminability under the studied conditions, and the true generalization capacity of this model needs to be further tested with larger and more diverse sample collections.
     Furthermore, the current model's discriminatory power for regions with similar ecological environments still requires verification. It remains to be determined whether subtle environmental variations or differences in agronomic practices, existing beneath the overarching “regional effect”, might influence the model's validation performance. To further enhance the universality and reliability of the traceability technique, future research should expand both the sample size and the sampling scope. It is also essential to comprehensively consider the environmental factors of the sample origins to more precisely decipher the driving mechanisms behind isotopic fractionation in these environments. Additionally, efforts should be made to integrate data from stable isotope technology with other traceability techniques, such as infrared spectroscopy, high-performance liquid chromatography (HPLC), and inductively coupled plasma mass spectrometry (ICP-MS), to construct a comprehensive, multi-technique model for origin traceability. This approach would further improve the accuracy of geographical origin discrimination.

5. CONCLUSIONS

     Stable isotope technology, combined with appropriate chemometric methods, enables the geographical origin discrimination of A. argyi. In this study, the stable isotope ratio method was applied for the first time to trace the geographical origin of A. argyi, achieving a discriminatory accuracy exceeding 80%. This approach not only provides robust technical support for quality control and the protection and identification of its regional typicity but also offers a novel methodological reference for the development of traceability technology systems for Chinese medicinal materials.

ACKNOWLEDGEMENTS

     The authors would like to thank Nanyang Institute of Technology, Henan Provincial Key Laboratory of Zhang Zhongjing Formulae and Immunomodulation, and Henan Institute of Medical and Health Technology for their technical support, financial assistance, and for providing the laboratory facilities used in this study.

AUTHOR CONTRIBUTIONS

Chao Li: Conceptualization, Methodology, Investigation, Writing – original draft preparation. Fang-wei Duan: Software, Visualization. Biao Zhou: Validation, Investigation, Resources. Meng-zhi Li: Data curation, Investigation, Formal analysis. Chun-yan Wang: Writing – review & editing, Validation. Guang-wei Wei: Project administration, Resources. Kuan Yang: Conceptualization, Writing – review & editing, Project administration.

CONFLICT OF INTEREST STATEMENT

     All authors declare that there are no conflicts of interest.

DECLARATION OF USE OF GENERATIVE AI

     During the manuscript preparation, DeepSeek was employed for language polishing and standard formatting. The authors have comprehensively reviewed and edited the full text, and assume full responsibility for all content of this paper. All core data and research conclusions are original works of the authors with authentic data sources.

FUNDING

     This research was financially supported by the National Natural Science Foundation of China (Grant Number 81803661), the Key Research and Development Special Project of Henan Province (Grant Number 2411111313700), the Major Special Project of Nanyang City (Grant Number 25ZDZX002), and the Key Research and Development Project of Nanyang City (Grant Number 24ZDYF008).

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