Multivariate calibration of on-line enrichment near-infrared (NIR) spectra and determination of trace lead in water

Huang, Zixia; Wei, Tao; Juanjuan, Fang; Wei, Xuemei; Du, Yukou

doi:10.1016/j.chemolab.2009.07.001

Cited by 26 publications

(3 citation statements)

References 20 publications

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“…8,9 Du and co-workers developed an enrichment device of silica-based monolithic material and applied it to determine low concentrations of carbaryl 10 and lead ions using near infrared diffuse reflectance spectroscopy (NIR-DRS). 11 In our previous works, adsorption preconcentration was combined with NIR-DRS for simultaneous determination of low-content substances, such as metal ions, 12,13 organic acids, 14 phenols 15 etc. Moreover, the indirect modelling of trace element contents and NIR spectra have been investigated for natural or environmental samples, such as sediments, foods and soils.…”

Section: Introductionmentioning

confidence: 99%

Determination of Bilirubin Using near Infrared Diffuse Reflectance Spectroscopy with Selective Concentration on β-Cyclodextrin

Wang

Cai

Shao

2016

Journal of Near Infrared Spectroscopy

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Near infrared diffuse reflectance spectroscopy (NIR-DRS) is a convenient and fast quantitative method for direct analysis of complex samples. The low sensitivity of NIR-DRS, however, is a problem for micro-analysis. A method for improving the sensitivity of NIR-DRS is proposed using selective adsorption. The method makes use of an adsorbent containing b-cyclodextrin to achieve the specific adsorption of bilirubin (BR). Preconcentration of BR from an aqueous solution with complex matrix was achieved through hydrophobic interaction and hydrogen bonding. Then NIR-DRS of the adsorbate was conducted and a partial least squares model was built for quantitative prediction. Both the preconcentration and the specific adsorption improve the analysis. The former enhances the spectral response by enrichment, and the latter makes the NIR response less affected by interferences such as metal ions, glucose etc. The results for the validation samples were a coefficient of determination (r 2 ) between the predicted and reference concentration of 0.98 with recoveries in the range 94.5-107.5% in a concentration range of 3.30-8.60 µg mL −1 . The concentration that can be quantitatively detected was as low as 2.60 µg mL −1 . Considering that the normal concentration range of BR in serum is 3.5-10.0 µg mL −1 , the method may provide a feasible tool for determination of BR in serum or other solution samples.

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Section: Introductionmentioning

confidence: 99%

Determination of Bilirubin Using near Infrared Diffuse Reflectance Spectroscopy with Selective Concentration on β-Cyclodextrin

Wang

Cai

Shao

2016

Journal of Near Infrared Spectroscopy

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“…In addition, the electromagnetic radiation spectrum in the near-infrared region contains useful information about environmental sample constituents such as soil that can be used for prediction of metal concentrations [25,28,33]. For instance, the absorption features associated with electronic transitions of Fe 3+ and Fe 2+ ions in Fe-bearing minerals can be found in the near-infrared region at 780-1200 nm [33][34][35]. In addition, the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water can be found in near infrared at 780-2500 nm region [24,33,34,36].…”

Section: Application Of Near-infrared Spectroscopy (Nirs) For Analysimentioning

confidence: 99%

“…This was achieved by quantitative evaluations of the spectral activity of sediment and soil properties [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. However, due to challenges such as the collinearity, band overlaps, and interactions for some soil properties, the spectra of soil, sediment, or suspended solids are often broad and nonspecific [25].…”

Section: Application Of Near-infrared Spectroscopy (Nirs) For Analysimentioning

confidence: 99%

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

Nomngongo¹,

Munonde²,

Mpupa³

et al. 2017

Developments in Near-Infrared Spectroscopy

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Environmental contamination by trace elements is becoming increasingly important problem worldwide. Trace metals such as cadmium, copper, lead, chromium, and mercury are major environmental pollutants that are predominantly found in areas with high anthropogenic activities. Therefore, there is a need for rapid and reliable tools to assess and monitor the concentration of heavy metal in environmental matrices. A nondestructive, cost-effective, and environmentally friendly procedure based on near-infrared reflectance spectroscopy (NIRS) and chemometric tools has been used as alternative technique for the simultaneous estimation of various heavy metal concentrations in environmental sample. The metal content is estimated by assigning the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water at 780-2500 nm in the near-infrared region.This chapter, reviewed the application of NIRS combined with chemometric tools such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression. The disadvantages and advantages of each chemometric tool are discussed briefly.

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Correcting NIR spectra of dimethyl fumarate in milk measured for different brands and in different dates

Zheng

Xiang

Cao

et al. 2013

Eur Food Res Technol

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Multivariate calibration of on-line enrichment near-infrared (NIR) spectra and determination of trace lead in water

Cited by 26 publications

References 20 publications

Determination of Bilirubin Using near Infrared Diffuse Reflectance Spectroscopy with Selective Concentration on β-Cyclodextrin

Determination of Bilirubin Using near Infrared Diffuse Reflectance Spectroscopy with Selective Concentration on β-Cyclodextrin

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

Correcting NIR spectra of dimethyl fumarate in milk measured for different brands and in different dates

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