[1] BOSE D, PADMAVATI M.Honey Authentication:A review of the issues and challenges associated with honey adulteration[J].Food Bioscience, 2024, 61:105004.
[2] AHMAD N N, KHAIRATUN S N.Exploring fraudulent honey cases from readily available food fraud databases[J].GATR Global Journal of Business Social Sciences Review, 2021, 9(2):99-113.
[3] HIRPARA P, RAMESHBHAI P M, KELE V D, et al.Honey:A functional food and its application in food products[J].Journal of Xidian University, 2023, 17(10):764-782.
[4] ZHANG X W, XU L T, WANG S Y, et al.How to effectively reduce honey adulteration in China:An analysis based on evolutionary game theory[J].Foods, 2023, 12(7):1538.
[5] ŽDINIAKOVÁ T, LÖRCHNER C, DE RUDDER O, et al.EU Coordinated action to deter certain fraudulent practices in the honey sector[J].European Union, 2023,EUR 31461 EN:1-16.
[6] OTHMAN S, MAVANI N R, HUSSAIN M A, et al.Artificial intelligence-based techniques for adulteration and defect detections in food and agricultural industry:A review[J].Journal of Agriculture and Food Research, 2023, 12:100590.
[7] MORARIU I D, AVASILCAI L, VIERIU M, et al.A comprehensive narrative review on the hazards of bee honey adulteration and contamination[J].Journal of Food Quality, 2024, 2024(1):3512676.
[8] DE NOVAIS L M R, DE FÁTIMA COSTA SANTOS M, MARQUES A C Q, et al.Combining analytical techniques to detect honey adulteration in Brazil—A case study[J].Journal of Food Composition and Analysis, 2025, 144:107716.
[9] BISWAS A, NARESH K, JAYGADKAR S S, et al.Enabling honey quality and authenticity with NMR and LC-IRMS based platform[J].Food Chemistry, 2023, 416:135825.
[10] LIMM W, KARUNATHILAKA S R, MOSSOBA M M.Fourier transform infrared spectroscopy and chemometrics for the rapid screening of economically motivated adulteration of honey spiked with corn or rice syrup[J].Journal of Food Protection, 2023, 86(4):100054.
[11] MARTINELLO M, STELLA R, BAGGIO A, et al.LC-HRMS-based non-targeted metabolomics for the assessment of honey adulteration with sugar syrups:A preliminary study[J].Metabolites, 2022, 12(10):985.
[12] YAN S, WANG X, WU Y C, et al.A metabolomics approach revealed an Amadori compound distinguishes artificially heated and naturally matured Acacia honey[J].Food Chemistry, 2022, 385:132631.
[13] ALGHAMDI B A, ALSHUMRANI E S, BIN SAEED M S, et al.Analysis of sugar composition and pesticides using HPLC and GC-MS techniques in honey samples collected from Saudi Arabian markets[J].Saudi Journal of Biological Sciences,2020, 27(12):3720-3726.
[14] GARDETTE V, MOTTO-ROS V, ALVAREZ-LLAMAS C, et al.Laser-induced breakdown spectroscopy imaging for material and biomedical applications:Recent advances and future perspectives[J].Analytical Chemistry, 2023, 95(1):49-69.
[15] GONG Z A, ZHI Z H, ZHANG C L, et al.Non-destructive detection of soluble solids content in fruits:A review[J].Chemistry, 2025, 7(4):115.
[16] KABIR M H, GUINDO M L, CHEN R Q, et al.Application of laser-induced breakdown spectroscopy and chemometrics for the quality evaluation of foods with medicinal properties:A review[J].Foods, 2022, 11(14):2051.
[17] RAI D, RAI A K, RAI A K, et al.Libs-a promising technique for control of food quality[J].Journal of Optics, 2025. https://doi.org/10.1007/s12596-024-02436-2.
[18] BISWAS A, CHAUDHARI S R.Exploring the role of NIR spectroscopy in quantifying and verifying honey authenticity:A review[J].Food Chemistry, 2024, 445:138712.
[19] KEERTHI K, GEORGE S D, KULKARNI S D, et al.Elemental analysis of liquid samples by laser induced breakdown spectroscopy (LIBS):Challenges and potential experimental strategies[J].Optics & Laser Technology, 2022, 147:107622.
[20] SINGH, JAGDISH P, SURYA N, et al.Laser-Induced Breakdown Spectroscopy[M].Susan Dennis, Online:Elsevier, 2020, 107-130.
[21] PALLESCHI V, LEGNAIOLI S, POGGIALINI F, et al.Laser-induced breakdown spectroscopy[J].Nature Reviews Methods Primers, 2025, 5(1):17.
[22] LEE L C, LIONG C Y, JEMAIN A A.A contemporary review on Data Preprocessing (DP) practice strategy in ATR-FTIR spectrum[J].Chemometrics and Intelligent Laboratory Systems, 2017, 163:64-75.
[23] MOKARI A, GUO S X, BOCKLITZ T.Exploring the steps of infrared (IR) spectral analysis:Pre-processing,(classical) data modelling, and deep learning[J].Molecules, 2023, 28(19):6886.
[24] DAYANANDA B, OWEN S, KOLOBARIC A, et al.Pre-processing applied to instrumental data in analytical chemistry:A brief review of the methods and examples[J].Critical Reviews in Analytical Chemistry, 2024, 54(8):2745-2753.
[25] YAN C S.A review on spectral data preprocessing techniques for machine learning and quantitative analysis[J].iScience, 2025, 28(7):112759.
[26] FU G R, LI Z X, XU J, et al.Prediction of heavy metal Cd and stress on minerals in rice by analysis of LIBS spectra[J].Applied Optics, 2022, 61(10):2536-2541.
[27] SUN L X, YU H B.Automatic estimation of varying continuum background emission in laser-induced breakdown spectroscopy[J].Spectrochimica Acta Part B:Atomic Spectroscopy, 2009, 64(3):278-287.
[28] REMUS J J, GOTTFRIED J L, HARMON R S, et al.Archaeological applications of laser-induced breakdown spectroscopy:An example from the Coso Volcanic Field, California, using advanced statistical signal processing analysis[J].Applied Optics, 2010, 49(13):C120-C131.
[29] UNNIKRISHNAN V K, NAYAK R, AITHAL K, et al.Analysis of trace elements in complex matrices (soil) by laser induced breakdown spectroscopy (LIBS)[J].Analytical Methods, 2013, 5(5):1294-1300.
[30] YAROSHCHYK P, EBERHARDT J E.Automatic correction of continuum background in laser-induced breakdown spectroscopy using a model-free algorithm[J].Spectrochimica Acta Part B:Atomic Spectroscopy, 2014, 99:138-149.
[31] GORNUSHKIN I B, EAGAN P E, NOVIKOV A B, et al.Automatic correction of continuum background in laser-induced breakdown and Raman spectrometry[J].Applied Spectroscopy, 2003, 57(2):197-207.
[32] LIU J L, ZHANG R, LI X T, et al.Continuous background correction using effective points selected in third-order minima segments in low-cost laser-induced breakdown spectroscopy without intensified CCD[J].Optics Express, 2018, 26(13):16171-16186.
[33] GUEZENOC J, GALLET-BUDYNEK A, BOUSQUET B.Critical review and advices on spectral-based normalization methods for LIBS quantitative analysis[J].Spectrochimica Acta Part B:Atomic Spectroscopy, 2019, 160:105688.
[34] ZAMAN M H, REHMAN F, TAHIR M S, et al.A study on the effect of preprocessing and normalization on classification of plant samples in machine learning assisted laser-induced breakdown spectroscopy[J].Arabian Journal for Science and Engineering, 2024, 49(7):10003-10019.
[35] YAO J Q, YANG Q, HE X Y, et al.Spectral filtering method for improvement of detection accuracy of Mg, Cu, Mn and Cr elements in aluminum alloys using femtosecond LIBS[J].RSC Advances, 2022, 12(50):32230-32236.
[36] ZHOU P, CHEN J Y, DU L, et al.Balanced spectral feature selection[J].IEEE Transactions on Cybernetics, 2023, 53(7):4232-4244.
[37] KHARINTSEV S S, SALAKHOV M K.A simple method to extract spectral parameters using fractional derivative spectrometry[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2004, 60(8-9):2125-2133.
[38] RINNAN Å, VAN DEN BERG F, ENGELSEN S B.Review of the most common pre-processing techniques for near-infrared spectra[J].TrAC Trends in Analytical Chemistry, 2009, 28(10):1201-1222.
[39] ZHANG G S, HAO H, WANG Y C, et al.Optimized adaptive Savitzky-Golay filtering algorithm based on deep learning network for absorption spectroscopy[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2021, 263:120187.
[40] NAEEM S, ALI A, ANAM S, et al.An unsupervised machine learning algorithms:Comprehensive review[J].International Journal of Computing and Digital Systems, 2023, 13(1):911-921.
[41] GREENACRE M, GROENEN P J F, HASTIE T, et al.Principal component analysis[J].Nature Reviews Methods Primers, 2022, 2:100.
[42] EZUGWU A E, IKOTUN A M, OYELADE O O, et al.A comprehensive survey of clustering algorithms:State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects[J].Engineering Applications of Artificial Intelligence, 2022, 110:104743.
[43] VALPOLA H. From Neural PCA to Deep Unsupervised Learning[M]. Amsterdam: Elsevier, 2015:143-171.
[44] ZHOU T, LI Q, LU H L, et al.GAN review:Models and medical image fusion applications[J].Information Fusion, 2023, 91:134-148.
[45] TENG G E, WANG Q Q, KONG J L, et al.Extending the spectral database of laser-induced breakdown spectroscopy with generative adversarial nets[J].Optics Express, 2019, 27(5):6958.
[46] SARKER I H.Machine learning:Algorithms, real-world applications and research directions[J].SN Computer Science, 2021, 2(3):160.
[47] ESPOSITO VINZI V, RUSSOLILLO G.Partial least squares algorithms and methods[J].WIREs:Computational Statistics, 2013, 5(1):1-19.
[48] SOLANKI R B, KULKARNI H D, SINGH S, et al.Optimization of regression model using principal component regression method in passive system reliability assessment[J].Progress in Nuclear Energy, 2018, 103:126-134.
[49] MONTESINOS LÓPEZ O A, MONTESINOS LÓPEZ A, CROSSA J.Support Vector Machines and Support Vector Regression[M].Cham:Springer International Publishing, 2022:337-378.
[50] HE Y X, KE C, WEN Q F, et al.Automatic focusing remote laser. induced breakdown spectroscopy analysis of trace elements in steel using support vector machine regression[J].IEEE Transactions on Instrumentation and Measurement, 2025, 74:7009408.
[51] SOROCHAN ARMSTRONG M D, DE LA MATA A P, HARYNUK J J.Review of variable selection methods for discriminant-type problems in chemometrics[J].Frontiers in Analytical Science, 2022, 2:867938.
[52] ZHAO S P, ZHANG B, YANG J, et al.Linear discriminant analysis[J].Nature Reviews Methods Primers, 2024, 4:70.
[53] HAO N, GAO X, ZHAO Q, et al.Rapid origin identification of Chrysanthemum morifolium using laser-induced breakdown spectroscopy and chemometrics[J].Postharvest Biology and Technology, 2023, 197:112226.
[54] ALZUBAIDI L, ZHANG J L, HUMAIDI A J, et al.Review of deep learning:Concepts, CNN architectures, challenges, applications, future directions[J].Journal of Big Data, 2021, 8(1):53.
[55] AHMED S F, BIN ALAM M S, HASSAN M, et al.Deep learning modelling techniques:Current progress, applications, advantages, and challenges[J].Artificial Intelligence Review, 2023, 56(11):13521-13617.
[56] QAMAR R, ALI ZARDARI B.Artificial neural networks:An overview[J].Mesopotamian Journal of Computer Science, 2023, 2023:124-133.
[57] HUANG W H, GUO L B, KOU W P, et al.Identification of adulterated milk powder based on convolutional neural network and laser-induced breakdown spectroscopy[J].Microchemical Journal, 2022, 176:107190.
[58] VALE K M O, GORGÔNIO A C, DA LUZ E GORGÔNIO F, et al.An efficient approach to select instances in self-training and co-training semi-supervised methods[J].IEEE Access, 2021, 10:7254-7276.
[59] MÜLLER S, MEIMA J A.Mineral classification of lithium-bearing pegmatites based on laser-induced breakdown spectroscopy:Application of semi-supervised learning to detect known minerals and unknown material[J].Spectrochim.Acta B, 2022, 189:106370.
[60] YANG X L, SONG Z X, KING I, et al.A survey on deep semi-supervised learning[J].IEEE Transactions on Knowledge and Data Engineering, 2023, 35(9):8934-8954.
[61] STEFAS D, GYFTOKOSTAS N, KOURELIAS P, et al.A laser-based method for the detection of honey adulteration[J].Applied Sciences, 2021, 11(14):6435.
[62] NESPECA M G, VIEIRA A L, SANTOS JÚNIOR D, et al.Detection and quantification of adulterants in honey by LIBS[J].Food Chemistry, 2020, 311:125886.
[63] LASTRA-MEJÍAS M, IZQUIERDO M, GONZÁLEZ-FLORES E, et al.Honey exposed to laser-induced breakdown spectroscopy for chaos-based botanical classification and fraud assessment[J].Chemometrics and Intelligent Laboratory Systems, 2020, 199:103939.
[64] PENG J Y, XIE W Y, JIANG J D, et al.Fast quantification of honey adulteration with laser-induced breakdown spectroscopy and chemometric methods[J].Foods, 2020, 9(3):341.
[65] KANTEMIRIS G, KOURELIAS P, PANAGIOTOPOULOU C, et al.Authentication of the botanical origin of honey via laser induced breakdown spectroscopy[J].Microchemical Journal, 2025, 212:113537.
[66] STEFAS D, GYFTOKOSTAS N, KOURELIAS P, et al.Honey discrimination based on the bee feeding by laser induced breakdown spectroscopy[J].Food Control, 2022, 134:108770.
[67] STEFAS D, GYFTOKOSTAS N, COURIS S.Laser induced breakdown spectroscopy for elemental analysis and discrimination of honey samples[J].Spectrochimica Acta Part B:Atomic Spectroscopy, 2020, 172:105969.
[68] ZHAO Z F, CHEN L, LIU F, et al.Fast classification of geographical origins of honey based on laser-induced breakdown spectroscopy and multivariate analysis[J].Sensors, 2020, 20(7):1878.
[69] SE K W, GHOSHAL S K, WAHAB R A.Laser-induced breakdown spectroscopy unified partial least squares regression:An easy and speedy strategy for predicting Ca, Mg and Na content in honey[J].Measurement, 2019, 136:1-10.
