[1] Zhao M, Yu J, Liu L et al. Thoughts on improving the quality of experimental teaching of forensic evidence[J]. Journal of Zunyi Medical University, 34, 441-443(2011).

[2] Feng X P. Study on the morphology and characteristics detection of bloodstains based on hyperspectral imaging technology[D], 8-9(2013).

[3] Hu N N. Research on blood stain detection based on hyper-spectral imaging technology[D], 2(2019).

[4] Cen Y. Research on safety testing technology and safety control measures of food additives[J]. China Food Safety Magazine, 163-165(2024).

[5] Xie Y, Shi Z Y, Pang H D et al. Research on microplastics pollution and development of its detection methods[J]. Environmental Science and Management, 49, 105-110(2024).

[6] Chu X L[M]. Chemometric methods in modern spectral analysis, 3-14(2022).

[7] Zhao Y. Exploration on the analysis method of bloodstain age based on clustering algorithm[D], 1-64(2022).

[8] Li M, Yuan Z J. Analytical chemistry in bloodstain examination[J]. Chinese Journal of Chemical Education, 42, 11-16(2021).

[9] Yan X Y, Zhang J Z, Jin J et al. Application progress of bloodstain presumptive test reagents to detect bloodstains at fire scenes[J]. Chinese Journal of Chemical Education, 44, 7-14(2023).

[10] Chen W B, Huo S H, Zhu K W. Experimental study on potential blood stains and influencing factors of luminol and tetramethylbenzidine[J]. Guangdong Gongan Keji, 22, 23-27(2014).

[11] Gao W Y, Pan J C. Study on the sensitivity and false positive reaction of blue star reagent[J]. Journal of Railway Police College, 28, 105-109(2018).

[12] Rong Z W, Du X J, Chang B N. Methods for fixing and developing blood handprints[J]. Forensic Science and Technology, 22-23(1980).

[13] She X, Huang Y P, Chen W J et al. Research on the method of latent blood stains in crime scene[J]. Journal of Jiangsu Police Institute, 29, 39-44(2014).

[14] Zhu C H, Zheng D L, Ni Y Z et al. DNA quantification of blood samples pre-treated with pyramidon[J]. Journal of Forensic Medicine, 30, 188-190(2014).

[15] Kan C, Zhu X J, Cheng L et al. Obsolescence degree of bloodstain in non-porous object detected by micro spectrophotometer method[J]. Journal of Nature Science, 4, 145-155(2016).

[16] Li Y Q, Zhao G S, Chen J et al. The conclusive test of hemochromogen by micro spectroscopic method[J]. Chinese Journal of Forensic Medicine, 31, 601-604(2016).

[17] Guo X D. Extraction and purification process optimization and industrialization of yak blood hemin[D], 1-2(2022).

[18] Dong Y, Yu X H. Analysis and discussion of methods for inferring time of death[J]. Guangdong Gongan Keji, 26, 72-73(2018).

[19] Zhou T, Fu L P. The application of digital signal processing technology in chemical analysis[J]. Shandong Chemical Industry, 53, 125-127(2024).

[20] Yang Z C. Study on detection method of hazardous substances in milk based on surface-enhanced Raman spectroscopy[D], 8(2023).

[21] Xu S F, Lin S Z, Chen R. Absorption spectrum of blood components in human and rabbit[J]. Proceedings of SPIE, 3344, 212-220(1998).

[22] Shaine M L. Optimization of the forensic identification of blood using surface-enhanced Raman spectroscopy[D], 1-77(2020).

[23] Thomas J M. The detection and identification of blood on interfering substrates using Raman spectroscopy and Hamand for forensic purposes[D], 1-22(2021).

[24] Butt M H F, Ayaz H, Ahmad M et al. A fast and compact hybrid CNN for hyperspectral imaging-based bloodstain classification[C](2022).

[25] Kistenev Y V, Borisov A V, Samarinova A A et al. A novel Raman spectroscopic method for detecting traces of blood on an interfering substrate[J]. Scientific Reports, 13, 5384(2023).

[26] Shi Q H, Ren X L. Research advance on detection methods of salmonella[J]. Meat Research, 23, 75-79(2009).

[27] Bai P L, Wang J, Yin H C et al. Discrimination of human and nonhuman blood by Raman spectroscopy and partial least squares discriminant analysis[J]. Analytical Letters, 50, 379-388(2017).

[28] Fujihara J, Fujita Y, Yamamoto T et al. Blood identification and discrimination between human and nonhuman blood using portable Raman spectroscopy[J]. International Journal of Legal Medicine, 131, 319-322(2017).

[29] Doty K C, Lednev I K. Differentiation of human blood from animal blood using Raman spectroscopy: a survey of forensically relevant species[J]. Forensic Science International, 282, 204-210(2018).

[30] Zhao Y F, Hu N N, Wang Y N et al. The application of near-infrared reflectance hyperspectral imaging for the detection and extraction of bloodstains[J]. Cluster Computing, 22, 8453-8461(2019).

[31] Huang W, Gao L M, Guo W W et al. Analysis into functional data of spectral images from bloodstains of human and two species of animal[J]. Forensic Science and Technology, 46, 551-558(2021).

[32] Zhuang Y, Gao S H, Xie F et al. Identifying bloodstain species using hyperspectral imaging[J]. Laser & Optoelectronics Progress, 59, 1630001(2022).

[33] Fonseca A C S, Pereira J F Q, Honorato R S et al. Hierarchical classification models and Handheld NIR spectrometer to human blood stains identification on different floor tiles[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 267, 120533(2022).

[34] Chen J S, Wang P, Tian Y B et al. Identification of blood species based on surface-enhanced Raman scattering spectroscopy and convolutional neural network[J]. Journal of Biophotonics, 16, e202200254(2023).

[35] Dickler H. Discrimination between human and non-human blood using Raman spectroscopy and a self-reference algorithm for forensic purposes: method expansion and validation[D], 1-14(2022).

[36] Bi F L, Wang W, Qi Y Y et al. Rapid identification of bloodstain based on near infrared spectroscopy and extreme learning machine algorithm[J]. Forensic Science and Technology, 49, 507-513(2024).

[37] Fonseca A C S, Pereira J F Q, Honorato R S et al. Classification of bloodstains deposited at different times on floor tiles using hierarchical modelling and a handheld NIR spectrometer[J]. Analytical Methods, 15, 5459-5465(2023).

[38] Liang Y, Wu J Q, Zeng Q et al. Rapid identification of the species of bloodstain based on near infrared spectroscopy and convolutional neural network-support vector machine algorithm[J]. Journal of the Brazilian Chemical Society, 35, 1-6(2024).

[39] Cooney G S, Köhler H, Chalopin C et al. Discrimination of human and animal bloodstains using hyperspectral imaging[J]. Forensic Science, Medicine, and Pathology, 20, 490-499(2024).

[40] Zhang L J. The body’s circadian rhythms has an influence on blood indicators in the exercise[D], 6-7(2014).

[41] Bremmer R H, de Bruin D M, de Joode M et al. Biphasic oxidation of oxy-hemoglobin in bloodstains[J]. PLoS One, 6, e21845(2011).

[42] Brutin D, Sobac B, Loquet B et al. Pattern formation in drying drops of blood[J]. Journal of Fluid Mechanics, 667, 85-95(2011).

[43] Gao Q Y, Gao S M. Authentication of age of bloodstains using UV visible reflection spectrum[J]. Spectroscopy and Spectral Analysis, 35, 2221-2224(2015).

[44] Yan L Q, Gao Y. Determination of bloodstain age by UV visible integrating sphere reflection spectrum[J]. Journal of Forensic Medicine, 32, 326-328(2016).

[45] Hu Q L, Liu J W, Feng A Q et al. Application of photometric analysis of blood stain to evidence analysis[J]. Physical Testing and Chemical Analysis (Part B: Chemical Analysis), 45, 70-72(2009).

[46] Chen R Y, Zhang L Y, Zang D Y et al. Blood drop patterns: Formation and applications[J]. Advances in Colloid and Interface Science, 231, 1-14(2016).

[47] Li H K, Cao Q F, Shi H et al. Comparative analysis of main properties of thermal sublimation transfer paper at home and abroad[C], 94-101(2024).

[48] Duan Y Q, Liao H H, Zheng C et al. Identification of selenium-enriched green tea based on improved kmeans algorithm[J]. Journal of Hubei Minzu University (Natural Science Edition), 37, 445-448, 462(2019).

[49] Cao H, Zhang J D. Analysis of digital color space model in ship video surveillance[J]. Journal of Dalian Maritime University, 38, 108-110, 116(2012).

[50] Xu Y W, Sun S R, Zhang J C et al. Research on the Marangoni effect in droplet explosions[J]. College Physics, 43, 44-50(2024).

[51] Deegan R D, Bakajin O, Dupont T F et al. Capillary flow as the cause of ring stains from dried liquid drops[J]. Nature, 389, 827-829(1997).

[52] Feng S S. Research on automatic blood stain classification based on drip spatter and spatter patterns[D], 10-11(2019).

[53] Sobac B, Brutin D. Desiccation of a sessile drop of blood: cracks, folds formation and delamination[J]. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 448, 34-44(2014).

[54] Choi W, Shin J, Hyun K A et al. Highly sensitive and accurate estimation of bloodstain age using smartphone[J]. Biosensors and Bioelectronics, 130, 414-419(2019).

[55] Zheng J L, Wen H Y, Zhang B et al. Development of integrated device of trace bloodstains imaging and age analysis[J]. Journal of Forensic Medicine, 35, 230-233, 239(2019).

[56] Li H Y, Shen C, Wang G J et al. BloodNet: an attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference[J]. Briefings in Bioinformatics, 24, bbac557(2023).

[57] Qian Z L, Li X, Jia Z J et al. Research on bloodstain age inference based on Image J software[J]. Chinese Journal of Forensic Medicine, 38, 43-47(2023).

[58] Edelman G, van Leeuwen T G, Aalders M C G. Hyperspectral imaging for the age estimation of blood stains at the crime scene[J]. Forensic Science International, 223, 72-77(2012).

[59] Li B, Beveridge P, O’Hare W T et al. The estimation of the age of a blood stain using reflectance spectroscopy with a microspectrophotometer, spectral pre-processing and linear discriminant analysis[J]. Forensic Science International, 212, 198-204(2011).

[60] Feng Y, Cai J. Age estimation of the bloodstains on different substrates based on the hyperspectral imaging technology[J]. Laser & Optoelectronics Progress, 57, 053004(2020).

[61] Kumar R, Sharma K, Sharma V. Bloodstain age estimation through infrared spectroscopy and Chemometric models[J]. Science & Justice, 60, 538-546(2020).

[62] Sun W, Liu H C, Liu J K et al. Age imaging by hyperspectral estimation of bloodstains technology based on partial least squares regression[J]. Applied Chemical Industry, 51, 273-276, 285(2022).

[63] Yang Q F, Zhang X Y, Qi Y Y et al. Age estimation of bloodstains based on convolutional neural network algorithm and hyperspectral imaging technology[J]. Analytical Methods, 15, 5063-5070(2023).

[64] Zhang R, Wang P, Chen J S et al. Age estimation of bloodstains based on Raman spectroscopy and chemometrics[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 290, 122284(2023).

[65] Giulietti N, Discepolo S, Castellini P et al. Neural network based hyperspectral imaging for substrate independent bloodstain age estimation[J]. Forensic Science International, 349, 111742(2023).

[66] Gariglio S, Malegori C, Menżyk A et al. Determination of time since deposition of bloodstains through NIR and UV-Vis spectroscopy-A critical comparison[J]. Talanta, 278, 126444(2024).

[67] Mengual-Pujante M, Perán A J, Ortiz A et al. Estimation of human bloodstains time since deposition using ATR-FTIR spectroscopy and chemometrics in simulated crime conditions[J]. Chemometrics and Intelligent Laboratory Systems, 251, 105172(2024).

[68] Barber A P, Weber A R, Lednev I K. Raman spectroscopy to determine the time since deposition of heated bloodstains[J]. Forensic Chemistry, 37, 100549(2024).

[69] Nagesh D, Nagarajamurthy B. Estimation of time-since-deposition of bloodstains on different surfaces using ATR-FTIR spectroscopy and chemometrics[EB/OL]. https://link.springer.com/content/pdf/10.1007/s12024-024-00849-w.pdf

[70] Shi L, Li Y S, Han Y et al. Two-branch network with feature fusion for time since deposition estimation of bloodstains[C], 2191-2196(2024).