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. 2015 Nov 3;15(11):27854-68.
doi: 10.3390/s151127854.

Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy

Affiliations

Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy

M Inmaculada González-Martín et al. Sensors (Basel). .

Abstract

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption.

Keywords: cross-validation; determination; lead; mineral composition; near-infrared spectroscopy; propolis.

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Figures

Figure 1
Figure 1
Schematic of the used NIRS equipment with fiber optic probe.
Figure 2
Figure 2
Comparison of reference values (mg/kg) with values predicted by the calibration equations obtained by NIR. R2, determination coefficient; RMSEP, root mean square error of prediction. (a) Al; (b) Ca; (c) Cr; (d) Cu; (e) Fe; (f) K; (g) Mg; (h) Ni; (i) Pb; (j) P; (k) Zn.
Figure 2
Figure 2
Comparison of reference values (mg/kg) with values predicted by the calibration equations obtained by NIR. R2, determination coefficient; RMSEP, root mean square error of prediction. (a) Al; (b) Ca; (c) Cr; (d) Cu; (e) Fe; (f) K; (g) Mg; (h) Ni; (i) Pb; (j) P; (k) Zn.

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