[Study on the Enhancement Intensity of Cd in Rice with Microwave-Assisted Laser-Induced Breakdown Spectroscopy].

As food safety problem has become the focus of attention all over the world, green detection methods of the contaminants in food is in accordance with the sustainable development of environment. Heavy metal pollutant Cd element in rice was used as the object of study in this work, laser induced breakdown spectroscopy (LIBS) and microwave assisted laser induced breakdown spectroscopy (MA-LIBS) were utilized to detect the blank and laboratory polluted rice samples respectively. The characteristic line of Cd Ⅰ 228.

[Determination of Cu in Shell of Preserved Egg by LIBS Coupled with PLS].

In this work, the content of copper in the shell of preserved eggs were determined directly by Laser induced breakdown spectroscopy (LIBS), and the characteristics lines of Cu was obtained. The samples of eggshell were pretreated by acid wet digestion, and the real content of Cu was obtained by atomic absorption spectrophotometer (AAS). Due to the test precision and accuracy of LIBS was influenced by a serious of factors, for example, the complex matrix effect of sample, the enviro nment noise, the system noise of the instrument, the stability of laser energy and so on.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed.