Quantitative of pesticide residue on the surface of navel orange by confocal microscopy Raman spectrometer

The potential of Confocal micro Raman spectroscopy in the quantitative analysis of pesticide(Chlorpyrifos,Omethoate)residues on orange surface is investigated in this work.Quantitative analysis models were established by partial least squares(PLS)using different preprocessing methods(Smoothing,First derivative,MSC,Baseline)for pesticide residues.For pesticide resi-dues,the higher correlation coefficients(r)is 0.972 and 0.943,the root mean square error of prediction(RMSEP)is 2.05%and 2.36%,respectively.It is therefore clear that Confocal micro-Raman spectroscopy techniques enable rapid,nondestructive and reliable measurements,so Raman spectrometry appears to be a prormising tool for pesticide residues.

Online quantitative analysis of soluble solids content in navel oranges using visible-nearinfrared spectroscopy and variable selection methods

Variable selection is applied widely for visible-near infrared(Vis-NIR)spectroscopy analysis of internal quality in fruits.Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content(SSC)in navel oranges.Moving window partial least squares(MW-PLS),Monte Carlo uninformative variables elimination(MC-UVE)and wavelet transform(WT)combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges.The performances of these methods were compared for modeling the Vis NIR data sets of navel orange samples.Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation cofficient(r)of 0.89 and lower root mean square error of prediction(RMSEP)of 0.54 at 5 fruits per second.It concluded that Vis NIR spectroscopy coupled with WT-MC-UVE may be a fast and efective tool for online quantitative analysis of SSC in navel oranges.

DETERMINATION OF COPPER,ZINC,CADMIUM AND LEAD IN WATER USING CO-PRECIPITATION METHOD AND RAMAN SPECTROSCOPY

Mn co-precipitation method combined with Raman spectroscopy were used to detenmine trace heavy metals(copper,zinc,cadmium and lead)in water sample.Different concentrations of heavy metals including copper,zinc,cadmiun and lead in water samples were separated and enriched by Mn^(2+)-phen SCN-ternary complex 0o-precipitation procedure.The Raman spectra of co-precipitation sediments were collected using confocal micro-Raman spectrometry.Different preprocessing treatments and regression calibration methods were compared.The best models using partial least squares regression(PLS)of copper,zinc,cadmium and lead were built with a correlation cofficient of prediction(R_(p))of 0.979,0.964,0.956 and 0972,respectively,and the root mean square error of prediction(RMSEP)of 6.587,9.046,9.998 and 7.751 pug/kg,respectively.The co-precipitation procedure combined with Raman spectroscopy method are feasible to detect the amount of heavy metals in water.