[Determination of soil quality from Chinese apple plant area by NIR spectroscopy].

In the present work, 111 soil samples from 11 different Chinese apple plant areas were used to take the diffuse reflection spectra from 12 500 to 4 000 cm(-1) by FT-NIR. The models of organic substance and pH value of soil samples were built by using partial least square regression (PLSR). The calibration model gave the correlation coefficients of 0.818 and 0.836 for the two values respectively, with the root mean square error of prediction (RMSEP) of 0.377 (%) and 0.251, respectively. In order to improve the robustness and performance of calibration, several spectra preprocessing methods were employed, including standard normalized variate (SNV), multiplicative scatter correction (MSC) and direct orthogonal signal correction (DOSC). Finally, the performance of DOSC was found to be the best for organic substance and pH value with RMSEP of 0.258 (%) an 0.248, respectively. The results showed that the technology of NIR spectroscopy was useful to nondestructive determination of the organic substance and pH value of soil. These research findings provide theoretic base for fertilization and pomiculture by means of NIR diffuse reflection.

[Feasibility of using NIR spectroscopy to detect melamine in milk].

In the present study, 22 certified milk samples without melamine were collected, then 50 adulterated milk samples with added different content of melamine (0.1-1 500 mg x kg(-1)) were prepared. The near-infrared (NIR) spectra of these milk samples were measured. The possibility of using NIR spectra to detect melamine in milk was studied. Partial least square regression (PLSR) was applied to construct the calibration model between NIR spectra and the content of melamine. The results showed that NIR spectroscopy can not accurately predict the content of melamine because of its poor detection limit. However, the combination of NIR spectra and partial least square-discriminate analysis (PLS-DA) was applied to differentiate the certified milk samples and the adulterated milk sample. The classification accuracy was 100%. Therefore, NIR spectra could be used to preliminarily detect whether the milk was adulterated with melamine. As a complementary detecting method to the high performance liquid chromatography (HPLC), NIR spectra could improve the detecting efficiency of milk