Muhua Liu

Detection of chromium in wastewater from refuse incineration power plant near Poyang Lake by laser induced breakdown spectroscopy

A laser induced breakdown spectroscopy (LIBS) system was developed for determination of toxic metals Cr in wastewater collected from a refuse incineration power plant near Poyang Lake. The plasma was generated by focusing a pulsed Nd:YAG laser at 1064 nm on the surface of liquid. Experimental conditions were optimized for improving the sensitivity and repeatability of the LIBS system through a parametric dependence study in potassium bichromate (K(2)Cr(2)O(7)) aqueous solutions. Calibration curves for Cr I 425.43 and 357.87 nm lines are compared and the limit of detection is found to be 39 and 86 ppm, respectively. This calibration curve of Cr I 425.43 nm has been used for quantification of Cr in wastewater collected from a refuse incineration power plant near Poyang Lake where the concentration of Cr is found to be 97 ppm. The results between LIBS and standard analytical technique such as atomic absorption spectroscopy were compared, and the relative standard deviation was 8.5%.

Detection of heavy metal Cd in polluted fresh leafy vegetables by laser-induced breakdown spectroscopy

In seeking a novel method with the ability of green analysis in monitoring toxic heavy metals residue in fresh leafy vegetables, laser-induced breakdown spectroscopy (LIBS) was applied to prove its capability in performing this work. The spectra of fresh vegetable samples polluted in the lab were collected by optimized LIBS experimental setup, and the reference concentrations of cadmium (Cd) from samples were obtained by conventional atomic absorption spectroscopy after wet digestion. The direct calibration employing intensity of single Cd line and Cd concentration exposed the weakness of this calibration method. Furthermore, the accuracy of linear calibration can be improved a little by triple Cd lines as characteristic variables, especially after the spectra were pretreated. However, it is not enough in predicting Cd in samples. Therefore, partial least-squares regression (PLSR) was utilized to enhance the robustness of quantitative analysis. The results of the PLSR model showed that the prediction accuracy of the Cd target can meet the requirement of determination in food safety. This investigation presented that LIBS is a promising and emerging method in analyzing toxic compositions in agricultural products, especially combined with suitable chemometrics.

Hyperspectral Laser-induced Fluorescence Imaging for Nondestructive Assessing Soluble Solids Content of Orange

Laser-induced fluorescence imaging is a promising technique for assessing quality of fruit. This paper reports on using a hyperspectral laser-induced fluorescence imaging technique for measurement of laser-induced fluorescence from orange for predicting soluble solids content (SSC) of fruit. A laser (632 nm) was used as an excitation source for inducing fluorescence in oranges. Fluorescence scattering images were acquired from ‘Nanfeng’ orange and navel orange by a hyperspectral imaging system at the instance of laser illumination. Subsequent analysis of Fluorescence scattering images consisted in selecting regions of interest (ROIs) of 100 50 pixels, and ROIs were segment around the laser illumination point from Fluorescence scattering images. The hyperspectral fluorescence image data in the wavelength range of 700-1100 nm were represented by mean grey value of the ROIs. The fruit soluble solids content were measured using hand-held refractometer. A line regressing method was used for developing prediction models to predict fruit soluble solids content. Excellent predictions were obtained for soluble solids content with the correlation coefficient of prediction of 0.998 (‘Nanfeng’ orange) and 0.96 (navel orange). The results show that hyperspectral laser-induced fluorescence imaging is a very good method for nondestructive assessing soluble solids content of orange.

Determination of heavy metal chromium in pork by laser-induced breakdown spectroscopy

Meat can be polluted by heavy metals during the feeding of livestock and processing of meat. It is necessary to monitor the concentration of toxic metals in meat. The element chromium (Cr) in pork was selected as a determination target for this work. Fresh pork was polluted in a Cr solution to create a different content level, then dried and pressed into pellets to eliminate the effect of water and improve the stability and sensitivity of laser-induced breakdown spectroscopy (LIBS). The spectra of pressed pellets were collected at optimized LIBS experimental parameters. After that, the real content of samples was obtained by atomic absorption spectroscopy. Characteristic lines Cr I 425.43, Cr I 427.48, and Cr I 428.97 were verified, and a model comparing the LIBS intensity of the line peak and the actual concentration of Cr was constructed. The results showed that the model has better predicted precision and accuracy, especially applying the line Cr I 425.43 for calibration. This work makes it obvious that LIBS has food safety potential for detecting residue of heavy metals in meat.

Vitamin C content estimation of chilies using Vis/NIR spectroscopy

Vitamin C has value in treatment or prevention of scurvy and it can be obtained from vegetable and fruit. Vitamin C is usually determined by traditional chemical methods which are destructive, time-consuming. This paper was conducted to study the vitamin C (VC) content estimation in chilies using quantitative analysis technique based on visible/near infrared (Vis/NIR) diffuse reflectance spectroscopy. Total 141 fresh chilies were purchased from market. After the samples have been washed and air-dried, Vis/NIR spectral data were collected using a QualitySpec® Pro Vis/NIR spectrometer (ASD Inc.). Then the vitamin C contents in samples were determined by 2, 6-dichloro-indophenol titration method. Spectral preprocessing techniques, including standard normal variate (SNV), multiplicative scatter corrections (MSC), first derivative (FD), second derivative (SD) and smoothing methods were applied to the spectral data and examined for their effectiveness at reducing or eliminating scatter effects. Partial least squares (PLS) regression was applied to examine the impact of the preprocessing transforms on assessing the content of vitamin C in chilies. The result shows that the best calibration model can be obtained by the first derivative preprocessing method in the spectral range of 450–1000nm. The prediction results are 0.803 and 0.509 for correlation coefficient (r) and root mean square errors of prediction (RMSEP), respectively. The study shows that vitamin C (VC) content in chilies can be effectively estimated using Vis/NIR spectroscopy technology.

Analysis of Trace Elements in Leaves Using Laser-Induced Breakdown Spectroscopy

Laser-Induced Breakdown Spectroscopy (LIBS) is a new way to analyze the plant ecology. The experimental used a Q-switched Nd:YAG laser to be the laser source and equipped with an eight-channel model spectrometer which’s wavelength range between 200 and 1100 nm. Studying the spectrum of the air-drying leaves and the nature leaves and detected the elements which contain Fe, Ca, Na, Mg, K, Cu, Al and Mn. Displaying the list which shows the all spectrum and elements. Refer to Fe as the benchmark, obtain the relative content of trace elements. At the same time, this technology can be employed for food safety and environment pollution evaluation. It will be the based for studying the portable LIBS instrument of detecting the pollution of heavy metal.

Determination of Soluble Solids Content in Cuiguan Pear by Vis/NIR Diffuse Transmission Spectroscopy and Variable Selection Methods

The objective of this research was to assess soluble solids content (SSC) of Cuiguan pears by visible/near infrared (Vis/NIR) and variable selection methods. Vis/NIR transmission spectra of Cuiguan pears were taken by a USB4000 spectrometer. A variety of pretreatment methods and three variable selection methods were used to select important variables in this study. After that, Partial least squares (PLS) was used to develop calibration model. The results show that competitive adaptive reweighted sampling (CARS) is an effective variable selection method for SSC of Cuiguan pears. PLS using the selected variables by CARS combined with multiplicative scattering correction (MSC) obtains the best results. Compared with full spectrum PLS, The number of variables in MSC-CARS-PLS model reduces from 1,400 to 84, the correlation coefficient rises from 0.88 to 0.96, and the root mean square error decreases to 0.29 °Brix.

Application of LS-SVM and Variable Selection Methods on Predicting SSC of Nanfeng Mandarin Fruit

The objective of this research was to investigate the performance of LS-SVM combined with several variable selection methods to assess soluble solids content (SSC) of Nanfeng mandarin fruit. Visible/near infrared (Vis/NIR) diffuse reflectance spectra of samples were acquired by a QualitySpec spectrometer in the wavelength range of 350~1800 nm. Four variable selection methods were conducted to select informative variables for SSC, and least squares-support vector machine (LS-SVM) with radial basis function (RBF) kernel was used develop calibration models. The results indicate that four variable selection methods are useful and effective to select informative variables, and the results of LS-SVM with these variable selection methods are comparable to the results of full-spectrum partial least squares (PLS). Genetic algorithm (GA) combined with successive projections algorithm (SPA) is the best variable selection method among these four methods. The correlation coefficients and RMSEs in LS-SVM with GA-SPA model for calibration, validation and prediction sets are 0.935, 0.560%, 0.912, 0.631% and 0.933, 0.594%, respectively.

Determination of dichlorvos contamination on navel orange surface based on least squares support vector machines

Spectral technique can provide a rapid, nondestructive means to assess quality and safety of agricultural commodities for human consumption. A procedure for determination of dichlorvos contamination has been developed with Vis-NIR spectroscopy. Four spectral preprocessing methods, including multiplicative scatter corrections (MSC), standard normal variate (SNV), first derivative (FD) and second derivative (SD) were used to reduce or eliminate scatter effects. Based on the spectral preprocessing methods, least squares support vector machines (LS-SVM) was performed. A total of 160 navel oranges were separated into two sets, one was calibration set (including 110 samples), and the other was prediction set (including 50 samples). It was found that LS-SVM model with the application of the preprocessing method of FD could predict dichlorvos residue. In the prediction set, the root mean squared error of prediction samples (RMSEP) was 6.2598 and the correlation coefficient Rpre was 0.8174.

The Detection of Early-Maturing Pear’s Effective Acidity Based on Hyperspectral Imaging Technology

The hyperspectral imaging technology is used to detect early-maturing pear’s effective acidity nondestructively, and effective prediction model is established. 145 pears’ hyperspectral images are obtained in the wavelength range of 400nm-1000nm. Total 145 pears are separated into the calibration set (77 samples) and prediction set (68 samples). Early-maturing pear’s effective acidity partial least squares (PLS) prediction model is built in different range of spectrum band. By comparison, the range 498 nm - 971 nm was selected in using partial least squares (PLS) to build early-maturing pear’s effective acidity prediction model. The experimental results show that, PLS prediction model of early-maturing pear’s effective acidity has the best effect in this range of wavelength. The correlation coefficient R between early-maturing pear’s actual effective acidity and predicted effective acidity is 0.9944 and 0.9233 for calibration set and prediction set respectively, the root mean squared error of prediction samples (RMSEP) is 0.022 and 0.072 for calibration set and prediction set respectively.