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Spectroscopic Evaluation and Analytical Validation of Lead (Pb) Determination in River Water Using Atomic Absorption Spectrophotometry

Rati Nur Ainna
Alauddin State Islamic University Makassar
Indonesia
rnnaainna@gmail.com
Erik Lotfi
American University of Bahrain ROR
Bahrain
Amrita Mitra
Okinawa Institute of Science & Technology
Japan
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  • Purpose of the study: This study aims to determine the presence or absence of lead (Pb) in the Kelay River water and to quantify its concentration using atomic absorption spectrophotometry as a reliable analytical technique for environmental monitoring.

    Methodology: This study used atomic absorption spectrophotometry (Varian Spectr AA) for analysis. Supporting tools included analytical balance (KERN ALJ 220-4 NM), volumetric glassware (Pyrex), and electric heater. Methods involved judgment sampling, acid digestion using HNO3, preparation of Pb(NO3)2 standard solutions, calibration curve construction, and linear regression analysis.

    Main Findings: Lead (Pb) was detected in Kelay River water samples. The concentrations in samples D and E were 0.0773 mg/L and 0.0634 mg/L, respectively, exceeding acceptable limits. In contrast, samples A, B, and C showed concentrations below 0.01 mg/L. The calibration curve exhibited strong linearity with a high correlation coefficient.

    Novelty/Originality of this study: This study applies an analytical spectroscopy-based approach to determine lead (Pb) levels in a specific river system with consideration of local environmental characteristics. It integrates calibration and detection limit evaluation, contributing to improved analytical reliability and providing new data for environmental assessment in underreported regions.

  • How to cite

    [1]
    R. N. Ainna, E. . Lotfi, and A. . Mitra, “Spectroscopic Evaluation and Analytical Validation of Lead (Pb) Determination in River Water Using Atomic Absorption Spectrophotometry”, Jor. Chem. Lea. Inn, vol. 3, no. 1, pp. 15–24, Apr. 2026, doi: 10.37251/jocli.v3i1.2965.

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    1. A. Sarker et al., “Heavy metals contamination and associated health risks in food webs—a review focuses on food safety and environmental sustainability in Bangladesh,” Environ. Sci. Pollut. Res., vol. 29, no. 3, pp. 3230–3245, 2022, doi: 10.1007/s11356-021-17153-7. DOI: https://doi.org/10.1007/s11356-021-17153-7
    2. S. Mishra, G. Singh, A. Gupta, and R. K. Tiwari, “Heavy Metal/Metalloid Contamination: Their Sources in Environment and Accumulation in Food Chain,” in Heavy Metal Toxicity: Environmental Concerns, Remediation and Opportunities, Singapore: Springer Nature Singapore, 2023, pp. 19–47. doi: 10.1007/978-981-99-0397-9_2. DOI: https://doi.org/10.1007/978-981-99-0397-9_2
    3. O. S. Bello, O. S. Agboola, and K. A. Adegoke, “Sources of Various Heavy Metal Ions,” in Heavy Metals in the Environment: Management Strategies for Global Pollution, vol. 1456, in ACS Symposium Series, vol. 1456. , American Chemical Society, 2023, pp. 4–59. doi: doi:10.1021/bk-2023-1456.ch004. DOI: https://doi.org/10.1021/bk-2023-1456.ch004
    4. B. Zhang, K. Yang, K. Zhang, Q. Wang, and N. Wu, “Migration transformation, prevention, and control of typical heavy metal lead in coal gangue: a review,” Int. J. Coal Sci. Technol., vol. 10, no. 1, pp. 1–12, 2023, doi: 10.1007/s40789-023-00656-8. DOI: https://doi.org/10.1007/s40789-023-00656-8
    5. A. Sharma, A. S. Grewal, D. Sharma, and A. L. Srivastav, “Heavy metal contamination in water: consequences on human health and environment,” in Metals in Water, Elsevier, 2023, pp. 39–52. doi: 10.1016/B978-0-323-95919-3.00015-X. DOI: https://doi.org/10.1016/B978-0-323-95919-3.00015-X
    6. Khushbu, R. Gulati, Sushma, A. Kour, and P. Sharma, “Ecological impact of heavy metals on aquatic environment with reference to fish and human health,” J. Appl. Nat. Sci., vol. 14, no. 4, pp. 1471–1484, Dec. 2022, doi: 10.31018/jans.v14i4.3900. DOI: https://doi.org/10.31018/jans.v14i4.3900
    7. E. P. Maharani, H. Briliana, E. H. Putri, F. S. Faraditta, and A. R. Azzhaffirah, “A comprehensive review on atomic absorption spectroscopy: Principles, techniques, and applications,” J. Ilm. Wahana Pendidik., vol. 10, no. 15, pp. 20–29, 2024, doi: 10.5281/zenodo.13764070.
    8. S. Dila, N. Pratiwi, A. Khumaeni, and I. Nurhasanah, “The effect of laser ablation time on the concentration of gold nanoparticle colloids,” J. Phys. Its Appl., vol. 8, no. 1, pp. 50–53, 2026, doi: 10.14710/jpa.v8i1.30233.
    9. F. Xu, W. Bai, J. Zhang, and L. Jin, “The synthesis and application of MRI-fluorescence dual mode materials with absorption ability on quantitative analysis of malachite green,” Phys. Scr., vol. 99, no. 10, p. 105575, Oct. 2024, doi: 10.1088/1402-4896/ad7d4a. DOI: https://doi.org/10.1088/1402-4896/ad7d4a
    10. C. Cheng, F. Zhang, J. Shi, and H. Te Kung, “What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective,” Environ. Sci. Pollut. Res., vol. 29, no. 38, pp. 56887–56907, 2022, doi: 10.1007/s11356-022-21348-x. DOI: https://doi.org/10.1007/s11356-022-21348-x
    11. Z. Song et al., “Emerging applications of synchrotron radiation X‐ray techniques in single atomic catalysts,” Small Methods, vol. 6, no. 11, pp. 1–19, Nov. 2022, doi: 10.1002/smtd.202201078. DOI: https://doi.org/10.1002/smtd.202201078
    12. K. Fu et al., “Understanding the Selective Removal of Perfluoroalkyl and Polyfluoroalkyl Substances via Fluorine–Fluorine Interactions: A Critical Review,” Environ. Sci. Technol., vol. 58, no. 38, pp. 16669–16689, Sep. 2024, doi: 10.1021/acs.est.4c06519. DOI: https://doi.org/10.1021/acs.est.4c06519
    13. R. Clough, A. Fisher, B. Gibson, and B. Russell, “Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials,” J. Anal. At. Spectrom., vol. 38, no. 11, pp. 2215–2279, 2023, doi: 10.1039/D3JA90038J. DOI: https://doi.org/10.1039/D3JA90038J
    14. M. S. H. Akash and K. Rehman, “Comprehensive Insights into Spectrophotometric Analysis,” in Essentials of Pharmaceutical Analysis, Singapore: Springer Nature Singapore, 2025, pp. 63–94. doi: 10.1007/978-981-96-5996-8_2. DOI: https://doi.org/10.1007/978-981-96-5996-8_2
    15. J. Luo, J. Guo, G. Zhao, Y. Shao, Z. Yin, and G. Li, “Design of an intelligent inspection system for power equipment based on multi-technology integration,” Electron., vol. 15, no. 4, pp. 1–24, 2026, doi: 10.3390/electronics15040827. DOI: https://doi.org/10.3390/electronics15040827
    16. L. Stefanini-Oresic, “Validation of analytical procedures: ICH guidelines Q2(R2),” Farm. Glas., vol. 2, no. 0, pp. 1–34, 2022.
    17. A. Coskun, “Are your laboratory data reproducible? The critical role of imprecision from replicate measurements to clinical decision-making,” Ann. Lab. Med., vol. 45, no. 3, pp. 259–271, 2025, doi: 10.3343/alm.2024.0569. DOI: https://doi.org/10.3343/alm.2024.0569
    18. Y. Shastak, W. Pelletier, and A. Kuntz, “Insights into analytical precision: Understanding the factors influencing accurate vitamin a determination in various samples,” Analytica, vol. 5, no. 1, pp. 54–73, 2024, doi: 10.3390/analytica5010004. DOI: https://doi.org/10.3390/analytica5010004
    19. S. C. Ihenetu, V. O. Njoku, F. C. Ibe, G. Li, A. Chinweuba, and C. E. Enyoh, “Determination of pollutions in the surface of water samples from Ogbajarajara river, Nigeria by spectrophotometer and atomic absorption spectrometry before evaluation of health risk assessment,” Anal. Methods Environ. Chem. J., vol. 5, no. 1, pp. 5–21, 2022, doi: 10.24200/amecj.v5.i01.162. DOI: https://doi.org/10.24200/amecj.v5.i01.162
    20. C. Adinda, E. L. Rustiati, I. Susanti, and O. Cicilia, “Analysis of cadmium (Cd) and lead (Pb) levels in water samples by atomic absorption spectrophotometry (AAS) at the Lampung health laboratory center,” J. Eng. Sci., vol. 3, no. 4, pp. 301–314, 2026, doi: 10.62885/improsci.v3i4.1053. DOI: https://doi.org/10.62885/improsci.v3i4.1053
    21. M. S. H. Akash and K. Rehman, “Comprehensive Insights into Atomic Absorption Spectroscopy,” in Essentials of Pharmaceutical Analysis, Singapore: Springer Nature Singapore, 2025, pp. 241–282. doi: 10.1007/978-981-96-5996-8_6. DOI: https://doi.org/10.1007/978-981-96-5996-8_6
    22. M. Patriarca et al., “Atomic spectrometry update: review of advances in the analysis of clinical and biological materials, foods and beverages,” J. Anal. At. Spectrom., vol. 37, no. 3, pp. 410–473, 2022, doi: 10.1039/D2JA90005J. DOI: https://doi.org/10.1039/D2JA90005J
    23. R. C. Castro, R. N.M.J. Páscoa, M. Lúcia, J. L. M. Santos, and D. S. M. Ribeiro, “Selective determination of Fe (III) with carbon dots as photoluminescence Probes: Chemometric analysis using Excitation-Emission matrices,” Microchem. J., vol. 205, no. May, pp. 1–10, 2024, doi: 10.1016/j.microc.2024.111207. DOI: https://doi.org/10.1016/j.microc.2024.111207
    24. Y. Shi et al., “Recent developments in heavy metals detection: Modified electrodes, pretreatment methods, prediction models and algorithms,” Metals (Basel)., vol. 15, no. 1, pp. 1–32, 2025, doi: 10.3390/met15010080. DOI: https://doi.org/10.3390/met15010080
    25. O. Thomas and J. Causse, “From spectra to qualitative and quantitative results,” in UV-Visible Spectrophotometry of Waters and Soils, Elsevier, 2022, pp. 59–94. doi: 10.1016/B978-0-323-90994-5.00011-3. DOI: https://doi.org/10.1016/B978-0-323-90994-5.00011-3
    26. M. Guo, K. Wang, H. Lin, L. Wang, L. Cao, and J. Sui, “Spectral data fusion in nondestructive detection of food products: Strategies, recent applications, and future perspectives,” Compr. Rev. Food Sci. Food Saf., vol. 23, no. 1, pp. 1–23, Jan. 2024, doi: 10.1111/1541-4337.13301. DOI: https://doi.org/10.1111/1541-4337.13301
    27. A. C. S. Lisboa, A. F. de S. Silva, and A. F. de Oliveira, “Evaluation of syringes as a substitute for precision glassware in quantitative experiments in high school education,” Am. J. Educ. Learn., vol. 10, no. 1, pp. 23–33, Jan. 2025, doi: 10.55284/ajel.v10i1.1271. DOI: https://doi.org/10.55284/ajel.v10i1.1271
    28. D. Sarathkumar, R. A. Raj, P. Sujeet, S. Sukitha, J. Sumithra, and R. Muralidharan, “An extensive critique on quality checking of natural ester based oil,” in 2023 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), 2023, pp. 1–6. doi: 10.1109/SCEECS57921.2023.10061815. DOI: https://doi.org/10.1109/SCEECS57921.2023.10061815
    29. P. R. Chowdhury, H. Medhi, K. G. Bhattacharyya, and C. M. Hussain, “Guidelines to establish the quality assurance, analytical parameters, and inter-laboratory studies,” in Sample Handling and Trace Analysis of Pollutants, Elsevier, 2025, pp. 435–455. doi: 10.1016/B978-0-323-85601-0.00015-1. DOI: https://doi.org/10.1016/B978-0-323-85601-0.00015-1
    30. S. N. Thomas, D. French, P. J. Jannetto, B. A. Rappold, and W. A. Clarke, “Liquid chromatography–tandem mass spectrometry for clinical diagnostics,” Nat. Rev. Methods Prim., vol. 2, no. 1, pp. 96–105, Dec. 2022, doi: 10.1038/s43586-022-00175-x. DOI: https://doi.org/10.1038/s43586-022-00175-x
    31. M. M. Ntona, K. Chalikakis, G. Busico, M. Mastrocicco, K. Kalaitzidou, and N. Kazakis, “Application of judgmental sampling approach for the monitoring of groundwater quality and quantity evolution in mediterranean catchments,” Water (Switzerland), vol. 15, no. 22, pp. 1–19, 2023, doi: 10.3390/w15224018. DOI: https://doi.org/10.3390/w15224018
    32. P. P. Bhave and K. Sadhwani, “Sampling in environmental matrices: a critical review,” Environ. Forensics, vol. 23, no. 1–2, pp. 75–92, Mar. 2022, doi: 10.1080/15275922.2021.1887971. DOI: https://doi.org/10.1080/15275922.2021.1887971
    33. V. N. Levinskiy, “Comparative experiment on the use of a film electric heater for drying wood in vacuum conditions,” in BIO Web of Conferences, V. Trukhachev, V. Khavinson, A. Zhuravlev, S. Belopukhov, R. Migunov, and V. Kukhar, Eds., Jan. 2024, pp. 1–8. doi: 10.1051/bioconf/20248205025. DOI: https://doi.org/10.1051/bioconf/20248205025
    34. B. Demeler, “Methods for the design and analysis of analytical ultracentrifugation experiments,” Curr. Protoc., vol. 4, no. 2, pp. 1–31, 2024, doi: 10.1002/cpz1.974. DOI: https://doi.org/10.1002/cpz1.974
    35. M. S. H. Akash and K. Rehman, “Comprehensive Insights into UV-VIS Spectrophotometry,” in Essentials of Pharmaceutical Analysis, Singapore: Springer Nature Singapore, 2025, pp. 95–160. doi: 10.1007/978-981-96-5996-8_3. DOI: https://doi.org/10.1007/978-981-96-5996-8_3
    36. Z. Zhang, F. Xie, W. Wang, and Y. L. Bai, “A novel quantitative analysis method for lead components in waste lead paste,” Metals (Basel)., vol. 13, no. 9, pp. 1–14, 2023, doi: 10.3390/met13091517. DOI: https://doi.org/10.3390/met13091517
    37. F. Agustiyar, W. K. Umar, and A. Guritno, “Validation of calcium (Ca) analysis in dolomite fertilizer using atomic absorption spectrophotometer (AAS),” Anjoro Int. J. Agric. Bus., vol. 3, no. 1, pp. 7–18, 2022, doi: 10.31605/anjoro.v3i1.1417. DOI: https://doi.org/10.31605/anjoro.v3i1.1417
    38. B. Cahyady, . Suharman, M. Taufik, Z. Alfian, M. Razali, and D. Ardilla, “Analysis of Arsenic in Purple cabbage (Brassica oleracea var. Capitata} L) after the Eruption of Mount Sinabung using Atomic Absorption Spectrophotometer,” in Proceedings of the 1st International MIPAnet Conference on Science and Mathematics, SCITEPRESS - Science and Technology Publications, 2019, pp. 592–595. doi: 10.5220/0010614200002775. DOI: https://doi.org/10.5220/0010614200002775
    39. M. Fiandini, A. B. D. Nandiyanto, D. F. Al Husaeni, D. N. Al Husaeni, and M. Mushiban, “How to Calculate Statistics for Significant Difference Test Using SPSS: Understanding Students Comprehension on the Concept of Steam Engines as Power Plant,” Indones. J. Sci. Technol., vol. 9, no. 1, pp. 45–108, 2024, doi: 10.17509/ijost.v9i1.64035. DOI: https://doi.org/10.17509/ijost.v9i1.64035
    40. R. Delgado, “Misuse of beer–lambert law and other calibration curves,” R. Soc. Open Sci., vol. 9, no. 2, pp. 1–21, Feb. 2022, doi: 10.1098/rsos.211103. DOI: https://doi.org/10.1098/rsos.211103
    41. N. Roustaei, “Application and interpretation of linear-regression analysis,” Med. Hypothesis, Discov. Innov. Ophthalmol., vol. 13, no. 3, pp. 151–159, 2024, doi: 10.51329/mehdiophthal1506. DOI: https://doi.org/10.51329/mehdiophthal1506
    42. S. W. Lee, “Regression analysis for continuous independent variables in medical research: statistical standard and guideline of Life Cycle Committee,” Life Cycle, vol. 2, no. e3, pp. 1–8, 2022, doi: 10.54724/lc.2022.e3. DOI: https://doi.org/10.54724/lc.2022.e3
    43. C. Stalikas and V. Sakkas, “From a glimpse into the key aspects of calibration and correlation to their practical considerations in chemical analysis,” Microchim. Acta, vol. 191, no. 2, pp. 1–15, 2024, doi: 10.1007/s00604-023-06157-4. DOI: https://doi.org/10.1007/s00604-023-06157-4
    44. S. S. Soliman, A. M. Mahmoud, A. M. Kessiba, and R. M. Ahmed, “Dual-mode sensing strategy for assaying phosphate ions using Fe, N-co-doped carbon dots with peroxidase mimetic activity,” Anal. Bioanal. Chem., vol. 418, no. 4, pp. 1259–1275, 2025, doi: 10.1007/s00216-025-06279-z. DOI: https://doi.org/10.1007/s00216-025-06279-z
    45. P. Vogel et al., “Critical offset magnetic particle spectroScopy for rapid and highly sensitive medical point-of-care diagnostics,” Nat. Commun., vol. 13, no. 1, pp. 1–9, 2022, doi: 10.1038/s41467-022-34941-y. DOI: https://doi.org/10.1038/s41467-022-34941-y
    46. M. S. Jatav et al., “Chemical Analysis Method for Surface and Ground Water Quality Assessment,” 2025, pp. 93–129. doi: 10.1007/978-981-96-8189-1_5. DOI: https://doi.org/10.1007/978-981-96-8189-1_5
    47. M. Ciopec, B. Pascu, and P. Negrea, “Inductively Coupled Plasma Optical Spectroscopy and Atomic Absorption Spectroscopy,” in Microbial Electrochemical Technologies, Wiley, 2023, pp. 201–228. doi: 10.1002/9783527839001.ch7. DOI: https://doi.org/10.1002/9783527839001.ch7
    48. D. Wu, Y. Hu, H. Cheng, and X. Ye, “Detection techniques for lead ions in water: A review,” Molecules, vol. 28, no. 8, pp. 1–15, 2023, doi: 10.3390/molecules28083601. DOI: https://doi.org/10.3390/molecules28083601
    49. M. Soylak, M. Alasaad, and Ö. Özalp, “Fabrication and characterization of MgCo2O4 for solid phase extraction of Pb(II) from environmental samples and its detection with high-resolution continuum source flame atomic absorption spectrometry (HR-CS-FAAS),” Microchem. J., vol. 178, p. 107329, Jul. 2022, doi: 10.1016/j.microc.2022.107329. DOI: https://doi.org/10.1016/j.microc.2022.107329
    50. M. L. Williams, A. A. Olomukoro, R. V. Emmons, N. H. Godage, and E. Gionfriddo, “Matrix effects demystified: Strategies for resolving challenges in analytical separations of complex samples,” J. Sep. Sci., vol. 46, no. 23, pp. 1–18, 2023, doi: 10.1002/jssc.202300571. DOI: https://doi.org/10.1002/jssc.202300571
    51. R. Ríos-Reina and S. M. Azcarate, “How chemometrics revives the UV-Vis spectroscopy applications as an analytical sensor for spectralprint (nontargeted) analysis,” Chemosensors, vol. 11, no. 1, pp. 1–22, 2023, doi: 10.3390/chemosensors11010008. DOI: https://doi.org/10.3390/chemosensors11010008
    52. G. M. Foody, “Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient,” PLoS One, vol. 18, no. 10 October, pp. 1–27, 2023, doi: 10.1371/journal.pone.0291908. DOI: https://doi.org/10.1371/journal.pone.0291908
    53. D. Goretzko, K. Siemund, and P. Sterner, “Evaluating model fit of measurement models in confirmatory factor analysis,” Educ. Psychol. Meas., vol. 84, no. 1, pp. 123–144, 2024, doi: 10.1177/00131644231163813. DOI: https://doi.org/10.1177/00131644231163813
    54. J. N. Chukwunweike, A. N. Anang, A. A. Adeniran, and J. Dike, “Enhancing manufacturing efficiency and quality through automation and deep learning: addressing redundancy, defects, vibration analysis, and material strength optimization,” World J. Adv. Res. Rev., vol. 23, no. 3, pp. 1272–1295, Sep. 2024, doi: 10.30574/wjarr.2024.23.3.2800. DOI: https://doi.org/10.30574/wjarr.2024.23.3.2800
    55. C. Atakari, “A deep learning-based security model for ERP-integrated IoT in national defense manufacturing environments,” Int. J. Emerg. Trends Comput. Sci. Inf. Technol., vol. 5, no. 3, pp. 90–98, 2024, doi: 10.63282/
    56. M. D. Chatfield, L. Marquart-Wilson, A. J. Dobson, and D. M. Farewell, “Mean relative error and standard relative deviation,” Stat. Neerl., vol. 79, no. 1, pp. 1–7, 2025, doi: 10.1111/stan.70001. DOI: https://doi.org/10.1111/stan.70001
    57. D. Kako, M. M. Ghareeb, and M. S. Al-Lami, “High-Performance Liquid Chromatography (HPLC) Method Validation for Identifying and Quantifying Rebamipide in Ethosomes,” Cureus, vol. 16, no. 3, pp. 1–12, 2024, doi: 10.7759/cureus.56061. DOI: https://doi.org/10.7759/cureus.56061
    58. V. Kumar, N. Kedam, K. V. Sharma, D. J. Mehta, and T. Caloiero, “Advanced machine learning techniques to improve hydrological prediction: A comparative analysis of streamflow prediction models,” Water (Switzerland), vol. 15, no. 14, pp. 1–24, 2023, doi: 10.3390/w15142572. DOI: https://doi.org/10.3390/w15142572
    59. N. Bastola, M. P. Jahan, N. Rangasamy, and C. S. Rakurty, “A Review of the residual stress generation in metal additive manufacturing: Analysis of cause, measurement, effects, and prevention,” Micromachines, vol. 14, no. 7, pp. 1–30, 2023, doi: 10.3390/mi14071480. DOI: https://doi.org/10.3390/mi14071480
    60. R. D. Prasad et al., “A review on spectroscopic techniques for analysis of nanomaterials and biomaterials,” ES Energy Environ., vol. 27, no. 1264, pp. 1–71, 2025, doi: 10.30919/es1332. DOI: https://doi.org/10.30919/es1332
    61. A. Kaseem et al., “Applications of fourier transform-infrared spectroscopy in microbial cell biology and environmental microbiology: Advances, challenges, and future perspectives,” 2023. doi: 10.3389/fmicb.2023.1304081. DOI: https://doi.org/10.3389/fmicb.2023.1304081
    62. D. D. Gbedzi et al., “Impact of mining on land use land cover change and water quality in the Asutifi North District of Ghana, West Africa,” Environ. Challenges, vol. 6, no. 100441, pp. 1–15, 2022, doi: 10.1016/j.envc.2022.100441. DOI: https://doi.org/10.1016/j.envc.2022.100441
    63. O. Igwe and M. E. Omeka, “Hydrogeochemical and pollution assessment of water resources within a mining area, SE Nigeria, using an integrated approach,” Int. J. Energy Water Resour., vol. 6, no. 2, pp. 161–182, 2022, doi: 10.1007/s42108-021-00128-2. DOI: https://doi.org/10.1007/s42108-021-00128-2
    64. Y. Cai, Y. Lin, H. Cai, and H. Ni, “Deep learning in vibrational spectroscopy: Benefits, limitations, and recent progress,” J. Chinese Chem. Soc., vol. 72, no. 6, pp. 611–626, Jun. 2025, doi: 10.1002/jccs.70031. DOI: https://doi.org/10.1002/jccs.70031
    65. Y. Jiang et al., “From fingerprint spectra to intelligent perception: Research advances in spectral techniques for ginseng species identification,” Foods, vol. 15, no. 4, pp. 1–23, 2026, doi: 10.3390/foods15040684. DOI: https://doi.org/10.3390/foods15040684
    66. Q. N. Hong and S. Fàbregues, “A Critical reflection of generalization in mixed methods research,” Eval. Rev., vol. 50, no. 2, pp. 200–230, 2025, doi: 10.1177/0193841X251331723. DOI: https://doi.org/10.1177/0193841X251331723
    67. V. S. Yadav et al., “Global prevalence of gingival recession: A systematic review and meta‐analysis,” Oral Dis., vol. 29, no. 8, pp. 2993–3002, Nov. 2023, doi: 10.1111/odi.14289. DOI: https://doi.org/10.1111/odi.14289
    68. X. Qi, Y. Lian, L. Xie, Y. Wang, and Z. Lu, “Water quality detection based on UV-Vis and NIR spectroscopy: a review,” Appl. Spectrosc. Rev., vol. 59, no. 8, pp. 1036–1060, Sep. 2024, doi: 10.1080/05704928.2023.2294458. DOI: https://doi.org/10.1080/05704928.2023.2294458
    69. A. Riyadh and N. M. Peleato, “Natural organic matter character in drinking water distribution systems: A review of impacts on water wuality and characterization techniques,” Water (Switzerland), vol. 16, no. 3, pp. 1–22, 2024, doi: 10.3390/w16030446. DOI: https://doi.org/10.3390/w16030446
    70. W. Xu, Y. Jin, and G. Zeng, “Introduction of heavy metals contamination in the water and soil: a review on source, toxicity and remediation methods,” Green Chem. Lett. Rev., vol. 17, no. 1, pp. 1–25, 2024, doi: 10.1080/17518253.2024.2404235. DOI: https://doi.org/10.1080/17518253.2024.2404235
    71. R. Teschke, “Copper, iron, cadmium, and arsenic, all generated in the universe: Elucidating their environmental impact risk on human health including clinical liver injury,” Int. J. Mol. Sci., vol. 25, no. 12, pp. 1–62, 2024, doi: 10.3390/ijms25126662. DOI: https://doi.org/10.3390/ijms25126662