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Multivariate calibration (MVC) and near-infrared (NIR) spectroscopy have demonstrated potential for rapid analysis of melamine in various dairy products. However, the practical application of ordinary MVC can be largely restricted because the prediction of a new sample from an uncalibrated batch would be subject to a significant bias due to matrix effect. In this study, the feasibility of using NIR spectroscopy and the standard addition (SA) net analyte signal (NAS) method (SANAS) for rapid quantification of melamine in different brands/types of milk powders was investigated. In SANAS, the NAS vector of melamine in an unknown sample as well as in a series of samples added with melamine standards was calculated and then the Euclidean norms of series standards were used to build a straightforward univariate regression model. The analysis results of 10 different brands/types of milk powders with melamine levels 0~0.12% (w/w) indicate that SANAS obtained accurate results with the root mean squared error of prediction (RMSEP) values ranging from 0.0012 to 0.0029. An additional advantage of NAS is to visualize and control the possible unwanted variations during standard addition. The proposed method will provide a practically useful tool for rapid and nondestructive quantification of melamine in different brands/types of milk powders.

Dairy products are essential components of a healthy diet for human and are very popular in all age groups owing to their high nutritional value and pleasurable flavor [

One of the most notorious exogenous adulterants used in dairy products is melamine, chemically known as 2,4,6-triamino-1,3,5-triazine [

To prevent further contamination and frauds, maximum limits have been established for melamine in infant formula and other foods by many countries. The emergent need for regulation of melamine has promoted extensive and intensive laboratory efforts to develop rapid, widely available, and cost-effective methods for analysis of melamine in various samples [

Although MVC combined with NIR spectroscopy has shown good accuracy and precision in analysis of melamine for some specific samples, the practical application of ordinary MVC to different brands/types of samples can be largely limited because the prediction of a new sample from an uncalibrated group would be subject to a significant bias due to matrix effect. This problem can be solved by performing calibration transfer [

Net analyte signal (NAS) theory [

The objective of this work was to study the feasibility of using multivariate standard addition method and NIR spectroscopy for rapid quantification of melamine in milk powders of different brands/types. To control the possible variations in preparation and measurement of added samples, the SANAS method was used to analyze different brands/types of milk powder samples.

Ten different brands/types of milk powder samples were collected from the quality inspection departments of producers as shown in Table

The original milk powder samples of 10 different batches.

Number | Codes of brands/types | Types |
Production date |
---|---|---|---|

1 | Q1 | Skimmed, regular | May 3, 2015 |

2 | Y1 | Semiskimmed, high-calcium | Apr. 13, 2015 |

3 | Q2 | Skimmed, regular | May 22, 2015 |

4 | M1 | Semiskimmed, regular | Jun. 7, 2015 |

5 | A1 | Whole, sweet | May 19, 2015 |

6 | Y2 | Whole, sweet, high-calcium | Apr. 15, 2015 |

7 | M2 | Whole, high-calcium | Jun. 7, 2015 |

8 | Y3 | Skimmed, regular | May 12, 2015 |

9 | M3 | Skimmed, high-calcium | Jun. 9, 2015 |

10 | Q3 | Whole, regular | Apr. 27, 2015 |

Composition of serial samples spiked with different amounts of melamine standard.

Sample levels | Melamine content |
Gradient of melamine standard added |
---|---|---|

1 | 0 | 0.01, 0.02, 0.04, and 0.08 |

2 | 0.01 | 0.01, 0.03, 0.07, and 0.11 |

3 | 0.02 | 0.02, 0.06, 0.10, and 0.14 |

4 | 0.04 | 0.04, 0.08, 0.12, and 0.20 |

5 | 0.08 | 0.04, 0.08, 0.16, and 0.24 |

6 | 0.12 | 0.04, 0.12, 0.20, and 0.36 |

The NIR diffuse reflectance spectra of milk powder samples were measured in the spectral range from 4000 to 10000 cm^{−1} on an Antaris II Fourier transform-NIR spectrometer (Thermo Electron Co., Waltham, Massachusetts, USA) using the RESTLT 3.0 software. All samples were measured with a PbS detector and an internal gold background as the reference. The resolution was 8 cm^{−1} and the scanning interval was 3.857 cm^{−1}. Therefore, each spectrum had 1557 individual data points for chemometric analysis. For each object, 32 scans were performed and more scans did not enhance the spectral signals significantly.

For a detailed description of the net analyte signal (NAS) theory, one can refer to [

To do standard addition, a set of

Subsequently, the NAS vectors of the

By plotting the Euclidean norm of the row vectors of

All the data analysis was performed using MATLAB 7.10.0 (R2010a) platform (MathWorks, USA). The data preprocessing and SANAS algorithms were performed based on in-house computational coded scripts written by authors in MATLAB.

The NIR spectra of the original milk powder samples and pure melamine as well as the melamine-adulterated samples are demonstrated in Figure ^{−1} is the combination absorbance of C–H symmetric stretching and C–H bending, and those at 4335 cm^{−1} can be attributed to the combination absorbance of C–H antisymmetric stretching and C–H bending. Other peak assignments are as follows: 4750 cm^{−1}, combination of the basebands of N–H stretching and bending; 5157 cm^{−1}, combination of the basebands of O–H stretching and bending; ~5700 cm^{−1}, the first overtones of C–H stretching in various groups; ~6500 cm^{−1}, the first overtone of N–H stretching; ~6900 cm^{−1}, the first overtone of O–H stretching; and ~8300 cm^{−1}, the second overtones of C–H stretching in various groups. By comparing the spectra of milk powder and melamine, the most significant difference is the intensive peak of melamine at 6811 cm^{−1}, which could be attributed to the baseband of N–H antisymmetric stretching. Figure

The NIR spectra of the original milk powder samples, pure melamine, and adulterated milk powder samples.

The second-order derivative (D2) spectra of the original and melamine-adulterated milk powder samples.

For each unknown sample, in order to compute the NAS vector, the spectrum of the original sample was subtracted from each of the melamine-spiked samples to obtain the matrix

The

The NAS vectors of milk powder sample Q1.

Theoretically, the melamine level in an unknown sample could be estimated by plotting the Euclidean norm of the computed NAS vectors,

By setting the value of

The prediction results of melamine levels in 10 different batches of milk powder samples by SANAS using the raw and D2 spectra.

Melamine level |
Raw spectra | D2 spectra | ||
---|---|---|---|---|

RSD |
RMSEP |
RSD (%) | RMSEP | |

0 | — | 0.0019 | — | 0.0014 |

0.01 | 19.5 | 0.0019 | 17.3 | 0.0016 |

0.02 | 9.8 | 0.0019 | 9.2 | 0.0017 |

0.04 | 4.8 | 0.0018 | 3.1 | 0.0012 |

0.08 | 3.8 | 0.0029 | 2.6 | 0.0020 |

0.12 | 1.3 | 0.0014 | 1.2 | 0.0014 |

The prediction results and reference values of melamine levels by SANAS.

To further evaluate the figures of merit of the method, the selectivity, sensitivity in terms of limit of detection (LOD), linearity (Pearson’s

The figures of merit of melamine analysis in 10 different batches of milk powder samples by D2 spectra.

Selectivity | Sensitivity (LOD |
Linearity ( |
Accuracy (RSD |
Precision (RSD) |
---|---|---|---|---|

0.614 | 0.0025 | 0.953 | 5.80% | 3.74% |

The feasibility of using NIR and SA for rapid quantification of melamine in different brands/types of milk powders was investigated. The analysis results for the 10 batches of melamine-adulterated milk powder samples demonstrate that SANAS is an effective method for SA multivariate calibration, which can visualize and control the spectral variations caused during SA in univariate regression. Moreover, the calibration accuracy was not significantly influenced by melamine levels to be analyzed. Compared with traditional multivariate calibration, combination of NIR and SANAS will provide a more practically applicable method for analysis of melamine in different brands/types of milk powder without requiring complex calibration transfer procedures.

This paper does not involve any animal or human experiments.

Bang-Cheng Tang, Chen-Bo Cai, Wei Shi, and Lu Xu declare no competing interests.

The authors are grateful to the financial support from the Research Projects of Guizhou Science and Technology (no. QKHJZLKT[