[2] [2] NAJI A, KHAN F R, HASHEM S H. Potential human health risk assessment of trace metals via the consumption of marine fish in Persian Gulf［J］. Marine Pollution Bulletin, 2016, 109(1): 667-671.

[3] [3] ADEL M, OLIVERI C G, DADAR M, et al. Heavy metal concentrations in edible muscle of whitecheek shark, Carcharhinus dussumieri (elasmobranchii, chondrichthyes) from the Persian Gulf: A food safety issue［J］. Food & Chemical Toxicology, 2016, 97: 135-140.

[4] [4] ARDUINI F, PALLESCHI G. Screening and confirmatory methods for the detection of heavy metals in foods persistent organic［C］. Pollutants and Toxic Metals in Foods, Woodhead Publishing Series in Food Science Technology and Nutrition, Cambridge, 2013.

[5] [5] CUI Lin, WU Jie, JU Huang-xian. Electrochemical sensing of heavy metal ions with inorganic, organic and bio-materials［J］. Biosensors & Bioelectronics, 2015, 63(63): 276-286.

[6] [6] MOHAMMAD B, TAPEH N, MAHYARI M, et al. Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet［J］. Environmental Monitoring and Assessment, 2014, 186(11): 7245-7257.

[7] [7] CHEN X, YUAN L, CHEN X, et al. A strategy for rapid identification of healthy Tegillarca granosa from among those contaminated with unspecified heavy metals using infrared spectroscopy ［J］. Analytical Methods, 2017, 9(30): 4447-4454.

[8] [8] CHEN X, LIU K, CAI J, et al. Identification of heavy metal-contaminated Tegillarca granosa using infrared spectroscopy ［J］. Analytical Methods, 2015, 7(5): 2172-81.

[9] [9] CHEN X, WU D, GUAN X, et al. Feasibility of infrared and Raman spectroscopies for identification of juvenile black seabream (sparus macrocephalus) intoxicated by heavy metals［J］. Journal of Agricultural and Food Chemistry, 2013, 61(50): 12429-12435.

[10] [10] SHI T, CHEN Y, LIU Y, et al. Visible and near-infrared reflectance spectroscopy-an alternative for monitoring soil contamination by heavy metals［J］. Journal of Hazardous Materials, 2014, 265(2): 166-176.

[11] [11] SHI Rong-jie, PAN Xian-zhang, WANG Chang-kun, et al. Prediction of cadmium content in the leaves of navel orange in heavy metal contaminated soil using VIS-NIR reflectance spectroscopy［J］. Spectroscopy and Spectral Analysis, 2015, 35(11): 3140-3145.

[12] [12] OLUMEGBON I A, OLOYEDE A, AFARA I O. Near-infrared (NIR) spectroscopic evaluation of articular cartilage: a review of current and future trends［J］. Applied Spectroscopy Reviews, 2016, 52(6): 1-19.

[13] [13] GALBACS G. A critical review of recent progress in analytical laser-induced breakdown spectroscopy ［J］. Analytical and Bioanalytical Chemistry, 2015, 407(25): 7537-7562.

[14] [14] SUN Tong, LIU Jin, GAN Lan-ping, et al. Detection of dimethoate content with laser induced breakdown spectroscopy combined with LSSVM and internal standard method［J］. Spectroscopy and Spectral Analysis, 2018, 38(4): 1251-1255.

[15] [15] SHEN Qin-mei, ZHOU Wei-dong, LI Ke-xue. Determination of Cr and Ba in soil using laser induced breakdown spectroscopy with artificial neural networks［J］. Acta Photonica Sinica, 2010, 39(12): 2134-2138.

[16] [16] YUAN L-M, CHEN X, LAI Y, et al. A novel strategy of clustering informative variables for quantitative analysis of potential toxics element in tegillarca granosa using laser-induced breakdown spectroscopy［J］. Food Analytical Methods, 2018, 11(5): 1405-1416.

[17] [17] LIU K, CHEN X, LI L, et al. A consensus successive projections algorithm-multiple linear regression method for analyzing near infrared spectra ［J］. Analytica Chimica Acta, 2015, 858: 16-23.

[18] [18] JI G, HUANG G, YANG Z, et al. Using consensus interval partial least square in near infrared spectra analysis ［J］. Chemometrics and Intelligent Laboratory Systems, 2015, 144: 56-62.

[19] [19] GARCIMUO M, PACE D M D, BERTUCCELLI G. Laser-induced breakdown spectroscopy for quantitative analysis of copper in algae［J］. Optics & Laser Technology, 2013, 47(4): 26-30.

[20] [20] CHEN X, DING H, YUAN L M, et al. New approach of simultaneous, multi‐perspective imaging for quantitative assessment of the compactness of grape bunches［J/OL］. Australian Journal of Grape and Wine Research, 2018, doi: 10.1111/ajgw.12349.

[21] [21] NI W, BROWN S D, MAN R. Stacked partial least squares regression analysis for spectral calibration and prediction［J］. Journal of Chemometrics, 2009, 23(10): 505-517.