Rapid Detection Of Heavy Metals In Tegillarca Granosa Based On Near Infrared Temperature Control Spectroscopy

Under the background of happy life in the post industrial era,the rapid economic development has brought about the aggravation of environmental pollution,which heavy metal pollution is a serious problem in the current water pollution.As a common aquatic product,Tegillarca granosa has the function of aggregation to heavy metals,and can enrich heavy metals in livers and gills.In this thesis,both the protein samples of healthy and heavy metal stress Tegillarca granosa were extracted and analyzed by two methods: control culture(Health Group)and experimental culture(Heavy Metal Stress Group).When heavy metal ions enter aquatic animals,by binding with membrane proteins,a large number of detoxification proteins are synthesized in the body,which results in internal changes in molecular structure.At the same time,temperature was used as stress factor to identify different samples by infrared spectrum.The main contents and conclusions are as follows:First of all,healthy Tegillarca granosa was cultured in heavy metal solution,and four kinds of total protein samples of healthy Tegillarca granosa and heavy metal stressed Tegillarca granosa were extracted.The spectral data of four kinds of samples from 25? to 60? were collected by temperature controlled near infrared spectrum,and the interval was 5?.Partial least squares(PLS-DA)and Liner Regerssion Classification(LRC)were used to classify the original spectral data.Second,analysis of total variable modeling: Four kinds of spectral pretreatment(multivariate scattering correction,derivative,standard normal transformation,mean centralization)is applied to the original data;then PLS-DA and LRC algorithms are used to model and classify the data,and the classification accuracy of the model after multivariate scattering correction and mean centralization is higher.Based on the characteristic variable modeling analysis: Competitive adaptive reweighting sampling(CARS),Uninformative variable elimination(UVE),Genetic algorithm(GA),and Successive projection algorithm(SPA),were used to process the original data of four types of Tegillarca granosa total protein samples,and a series of models with different numbers and wavelength varia.Third,in order to further distinguish and study the differences between different types of spectra,two-dimensional near infrared spectroscopy was used to analyze the overlapped and similar peaks in the spectrum by using the synchronous and asynchronous spectra in the twodimensional spectrum in this study.It is found that the two-dimensional spectrogram can be more intuitive and clear to identify different types of Tegillarca granosa total protein samples.The results shows the feasibility of using two dimensional spectral technology to detect the contamination of heavy metals in Tegillarca granosa.