Xiaobo Zou

Determination of pork spoilage by colorimetric gas sensor array based on natural pigments

A new colorimetric gas-sensor array based on four natural pigments, that were extracted from spinach (Spinacia oleracea), red radish (Raphanus sativus L.), winter jasmine (Jasminum nudiflorum), and black rice (Oryza sativa L. indica), was developed for pork freshness evaluation. A colour change profile for each sample was obtained by differentiating the images of the sensor array before and after exposure to the odour of sample. The total viable count (TVC) per gram of pork was obtained by classical microbiological plating methods, and the biogenic amines were measured by HPLC. Biogenic amine index (BAI) for the determination of meat freshness was developed from the sum of putrescine and cadaverine. The colour change profiles were analysed using principal component analysis and correlated with conventional methods (BAI, TVC). A partial least squares (PLS) prediction model was obtained with r=0.854 and 0.933 for BAI and TVC, respectively.

Sensing the quality parameters of Chinese traditional Yao-meat by using a colorimetric sensor combined with genetic algorithm partial least squares regression

Yao-meat is a traditional Chinese salted meat. Total volatile basic nitrogen content (TVB-N), total viable bacterial count (TVC), and residual nitrite (RN) level are important indexes of freshness for Yao-meat. This paper attempted the feasibility to determine TVB-N content, TVC and RN level in Yao-meat by a colorimetric sensor array chip. A color change profile for each sample was obtained by differentiating the image of sensor array before and after exposure to Yao-meats volatile organic compounds. Genetic algorithm partial least squares regression (GA-PLS) was proposed to build the relationship between the TVB-N content, TVC, RN and the color change profiles of sensor array, and to select informative chemically responsive dyes for the three quality parameters. The GA-PLS models were achieved with RTVB-N=0.812, RTVC=0.856, RRN=0.855, in prediction set. This study demonstrated that colorimetric sensory array with GA-PLS algorithm could be used successfully to analyze the quality of Chinese traditional Yao-meat.

Electrodeposition of gold nanoparticles and reduced graphene oxide on an electrode for fast and sensitive determination of methylmercury in fish

Fish consumption is the main source of methylmercury (CH3Hg+) exposure for humans. In this study, gold nanoparticles and reduced graphene oxide (AuNPs-RGO) modified electrode was fabricated for determination of CH3Hg+ in fish. The AuNPs-RGO composite was synthesized by electroreduction method. The composite was characterized by scanning electron microscopy and energy dispersive spectra, X-ray diffraction and Raman spectroscopy. Electrochemical performance of the proposed sensor was studied by cyclic voltammetry, electrochemical impedance spectroscopy and differential pulse stripping voltammetry. The excellent conductivity and large surface of graphene contributed to an improvement in the voltammetric stripping signal. Under the optimized conditions, the methylmercury concentration in the range from 3 to 24μgL-1 had a good linear relation with the peak current. The detection limit of AuNPs-RGO modified electrode was 0.12μgL-1. Finally, the developed electrode was applied to detect methylmercury in fish samples, and the obtained results were in good agreement with certified values.

Rapid and wide-range determination of Cd(II), Pb(II), Cu(II) and Hg(II) in fish tissues using light addressable potentiometric sensor

A rapid and wide-range method, based on light addressable potentiometric sensor (LAPS), is introduced into determination of Cd(II), Pb(II), Cu(II) and Hg(II) in fish tissues. A compact LAPS module is prepared by integrating four LAPS chips specifically sensitive to target elements. Its responses in digestions from various settings are investigated to find suitable factors. Analytical properties of this method are evaluated in consequent experiments under optimized conditions. Measurement range for each target element exceeds 0.1 to 1000mgL-1, and response time is less than 10s. Accuracy, precision and selectivity of the proposed method are also well defined in measurements. It is successively performed to detect the target elements in real fish samples from 4 species, and obtained results are consistent with certified method.

Microfabricated interdigitated Au electrode for voltammetric determination of lead and cadmium in Chinese mitten crab (Eriocheir sinensis).

An in-situ plating bismuth modified interdigitated Au electrode (IAE) was developed for determination of Pb(2+) and Cd(2+) in crab. The IAE was fabricated and used as counter electrode and working electrode. Cyclic voltammetry (CV) was performed with the IAE for studying electrochemical performance, showing clear redox peaks. The key operational parameters were optimized, which were 600 μg L(-1) of Bi(3+) concentration, 0.1 mol L(-1) of acetate buffer (pH 4.5), -1.2V of deposition potential and 180 s of deposition time. Under optimized condition, the linear range of IAE was from 5 to 50 μg L(-1) for both metal ions, with detection limit (threefold signal-to-noise) of 0.74 μg L(-1) for Pb(2+) and 0.86 μg L(-1) for Cd(2+). Finally, the developed sensor was applied to detect Pb(2+) and Cd(2+) in crab extract solutions by standard addition method. The results were in good agreement with outcomes obtained by inductively coupled plasma mass spectrometry.

A rapid and nondestructive method to determine the distribution map of protein, carbohydrate and sialic acid on Edible bird’s nest by hyper-spectral imaging and chemometrics

Edible birds nest (EBN) is a precious functional food in Southeast Asia. A rapid and nondestructive method for determining the distribution map of protein content (PC), carbohydrate content (CC) and sialic acid content (SAC) on EBN sample was proposed. Firstly, 60 EBNs were used for hyperspectral image acquisition, and components content (PC, CC and SAC) were determined by chemical analytical methods. Secondly, the spectral signals of EBN hyperspectral image and EBN components content were used to build calibration models. Thirdly, spectra of each pixel in EBN hyperspectral image were extracted, and these spectra were substituted in the calibration models to predict the PC, CC and SAC of each pixel in the EBN image, so the visual distribution maps of PC, CC and SAC on the whole EBN were obtained. It is the first time to show the distribution tendency of PC, CC and SAC on the whole EBN sample.

A real-time-range potentiostat coupled to nano-Au-modified microband electrode array for high-speed stripping determination of human blood lead

A novel method of real-time-range measurement, characterized by pre-sampling forecast and balanced-range switching, is introduced in this study. According to this method, raw current signals in biosensing procedures may be measured and recorded with real-time-optimized instrumental settings. A low-cost and high-performance potentiostat is developed to validate the proposed method. The transient process of real-time-range measurement is investigated to optimize sampling interval and circuit parameters. Typical time consumption of a sampling cycle is less than 100μs, which makes high-speed and real-time-range measurement possible. The proposed method also brings excellent current resolution that is better than 0.8pA. It improves weak signals in stripping determinations, and is particularly suitable for biological samples. As-fabricated potentiostat, coupled to a nano-Au-modified microband electrode array, is adopted in high-speed stripping determinations towards human blood lead levels (HBLLs). Accuracy and precision of this method are validated with certified reference material (CRM). Obtained values (4.31 ± 0.18μgL-1) meet with certified levels of CRM (4.24 ± 0.11μgL-1). Coefficient of variation percent (CV %) is no more than 5.0% for intra- or inter-assay analyses. Finally, this method is utilized for human population based study. Two groups of data, from this method and inductively coupled plasma mass spectrometry (ICP-MS), are analyzed using a statistic tool of t-test, and no statistically significant difference is found.

A heuristic and parallel simulated annealing algorithm for variable selection in near‐infrared spectroscopy analysis

A new heuristic and parallel simulated annealing algorithm was proposed for variable selection in near‐infrared spectroscopy analysis. The algorithm employs a parallel mechanism to enhance the search efficiency, a heuristic mechanism to generate high‐quality candidate solutions, and the concept of Metropolis criterion to estimate accuracy of the candidate solutions. Several near‐infrared datasets have been evaluated under the proposed new algorithm, with partial least squares leading to improved analytical figures of merit upon wavelength selection. Improved robust and predictive regression models were obtained by the new algorithm. The method could also be helpful in other chemometric activities such as classification or quantitative structure‐activity relationship problems.

Determination of Retrogradation Degree in Starch by Mid-infrared and Raman Spectroscopy during Storage

Retrogradation behavior is an important physicochemical property of starch during storage. A fast and sensitive method was developed for determining the retrogradation degree (RD) in corn starch by mid-infrared (MIR), Raman spectroscopy, and combination of MIR and Raman. MIR and Raman spectra were collected from different retrogradation starch and then processed by partial least squares (PLS), interval PLS (iPLS), synergy interval PLS (siPLS), and backward interval PLS (biPLS). Two different levels of fusion data extracted from MIR and Raman spectra were analyzed by PLS. The developed models demonstrated that both MIR and Raman techniques combined with chemometrics can be used to determine the RD in starch. The PLS model built by medium-level fusion approach achieved the most satisfied performance with a correlation coefficient of 0.9658. Integrating MIR and Raman technique combined with chemometrics improved the prediction performance of RD in comparison with a single technique.

A ZnO–RGO-modified electrode coupled to microwave digestion for the determination of trace cadmium and lead in six species fish

Herein, a composite of a ZnO nanoparticle and reduced graphene oxide (RGO) was employed as a sensing interface in a practical electrode for the determination of cadmium (Cd2+) and lead (Pb2+). A suspension comprising the ZnO nanoparticle and RGO was synthesized via the wet-chemical method. The ZnO–RGO-modified electrode was obtained by drop-coating the prepared suspension onto a screen-printed electrode. The modification was validated via scanning electron microscopy and cyclic voltammetry. The properties of the sensor were studied by analyzing digested fish samples at various settings and gradually increasing concentrations. Stripping responses were significantly improved by optimizing the digestion factors including acid mixture ratio, microwave power, and digestion time. Signal losses during digestions were less than 25%. The detection limits of the electrode for Cd2+ and Pb2+ were as low as 0.16 and 0.17 μg L−1, respectively, in the matrix of the real sample. Finally, this method was applied to determine trace Cd2+ and Pb2+ in six species of fish, and the obtained results were in good agreement with those obtained via ICP-MS.