An anti-passivation ink for the preparation of electrodes for use in electrochemical immunoassays.

p-Nitrophenylphosphate (PNPP) is usually employed as the substrate for enzyme-linked immunosorbent assays. p-Nitrophenol (PNP), the product of PNPP, with the catalyst alkaline phosphatase (ALP), will passivate an electrode, which limits applications in electrochemical analysis. A novel anti-passivation ink used in the preparation of a graphene/ionic liquid/chitosan composited (rGO/IL/Chi) electrode is proposed to solve the problem. The anti-passivation electrode was fabricated by directly writing the graphene-ionic liquid-chitosan composite on a single-side conductive gold strip. A glassy carbon electrode, a screen-printed electrode, and a graphene-chitosan composite-modified screen-printed electrode were investigated for comparison. Scanning electron microscopy was used to characterize the surface structure of the four different electrodes and cyclic voltammetry was carried out to compare their performance. The results showed that the rGO/IL/Chi electrode had the best performance according to its low peak potential and large peak current. Amperometric responses of the different electrodes to PNP proved that only the rGO/IL/Chi electrode was capable of anti-passivation. The detection of cardiac troponin I was used as a test example for electrochemical immunoassay. Differential pulse voltammetry was performed to detect cardiac troponin I and obtain a calibration curve. The limit of detection was 0.05 ng/ml.

The relationship of spectral sensitivity with growth and reproductive response in avian breeders (Gallus gallus).

A previous study demonstrated that birds that are exposed to light at night develop advanced reproductive systems. However, spectrum might also affect the photoperiodic response of birds. The present study was aimed to investigate the effects of spectral composition on the growth and reproductive physiology of female breeders, using pure light-emitting diode spectra. A total of 1,000 newly hatched female avian breeders (Gallus gallus) were equally allocated to white-, red-, yellow-, green- and blue-light treated groups. We found that blue-light treated birds had a greater and faster weight gain than did red- and yellow-light treated birds (P = 0.02 and 0.05). The red light expedited the sexual maturation of the chicks, whose age at sexual maturity was 7 and 14 days earlier than that of the green- and blue-light treated birds, respectively. The accumulative egg production of the red-light treated birds was 9 and 8 eggs more than that of the blue- and green-light treated birds. The peak lay rate of the red-light treated groups was significantly greater than the blue-light treated birds (P = 0.028). In conclusion, exposure to short-wavelength light appears to promote growth of female breeder birds, whereas exposure to long-wavelength light appears to accelerate reproductive performance.

[Evaluation of Sugar Content of Huanghua Pear on Trees by Visible/Near Infrared Spectroscopy].

A method of ambient light correction was proposed to evaluate the sugar content of Huanghua pears on tree by visible/near infrared diffuse reflectance spectroscopy (Vis/NIRS). Due to strong interference of ambient light, it was difficult to collect the efficient spectral of pears on tree. In the field, covering the fruits with a bag blocking ambient light can get better results, but the efficiency is fairly low, the instrument corrections of dark and reference spectra may help to reduce the error of the model, however, the interference of the ambient light cannot be eliminated effectively. In order to reduce the effect of ambient light, a shutter was attached to the front of probe. When opening shutter, the spot spectrum were obtained, on which instrument light and ambient light acted at the same time. While closing shutter, background spectra were obtained, on which only ambient light acted, then the ambient light spectra was subtracted from spot spectra. Prediction models were built using data on tree (before and after ambient light correction) and after harvesting by partial least square (PLS). The results of the correlation coefficient (R) are 0.1, 0.69, 0.924; the root mean square error of prediction (SEP) are 0. 89°Brix, 0.42°Brix, 0.27°Brix; ratio of standard deviation (SD) to SEP (RPD) are 0.79, 1.69, 2.58, respectively. The results indicate that, method of background correction used in the experiment can reduce the effect of ambient lighting on spectral acquisition of Huanghua pears in field, efficiently. This method can be used to collect the visible/near infrared spectrum of fruits in field, and may give full play to visible/near-infrared spectroscopy in preharvest management and maturity testing of fruits in the field.

[Quantitative analysis of goose and duck mixed down using visible/NIR spectroscopy].

Goose down and duck down have very similar appearance but the quality of goose down is better than that of duck down in general. There is a highest allowable limit as specified by the various national standards of feather and down for the percentage of duck feather or down mixed in goose feather or down. Traditional detection method, manual inspection with a high-scale microscope, is labor intensive and not suitable for large-volume samples analysis and on-site rapid testing. In the present paper, visible/near-infrared (NIR) spectroscopy combined with successive projection algorithm (SPA) for characteristic wavelengths selection was used to determinate the content of duck down mixed in goose down. In the range of 450-930 nm, the multiple linear regression (MLR) model established with the 8 characteristic wavelengths selected by SPA achieved good prediction, the correlation coefficient of 0.983, root mean square error of calibration (RMSEC) of 5.44%, and root mean square error of prediction (RMSEP) of 5.75%. Therefore, it is expected to be used for rapid detection of feather and down quality in future.

[Application of hyperspectral fluorescence image technology in detection of early rotten oranges].

Rottenness is most prevalent and devastating disease that threats citrus fruit. Automatic detection of early rottenness can enhance the competitiveness and profitability of the citrus industry. However, there is no efficient automatic detection technology at this time that could detect this disease. The navel orange was selected as research objective. Hyperspectral fluorescence imaging was used to detect early rottenness in orange. Optimum index factor (OIF) method was applied to identify the optimal band combination. 100% detection rate was achieved based on the optimal bands ratio image and two threshold values. The research showed that the proposed method can effectively overcome the affect from florescence effect because stem damage area and stem also can produce florescence under ultraviolet light. This study will lay a foundation for developing multispectral detection system used in on-line detection of early rottenness fruit.

[Advance on application of hyperspectral imaging to nondestructive detection of agricultural products external quality].

Hyperspectral imaging is an emerging technique that integrates conventional imaging and spectroscopy to obtain both spatial and spectral information from a studied object simultaneously. The images data can reflect the external features, surface defects and contamination. The spectra data can analyze physical structure and chemical composition in studied object. Therefore, hyperspectral imaging technology causes more and more attention, and has become a hot research topic recently. In order to track the latest research developments at home and abroad, application of hyperspectral reflectance and fluorescence imaging techniques to nondestructive detection of agricultural products external quality was reviewed, which would provide reference for application of hyperspectral imaging to agriculture.

[Rapid detection of Escherichia coli O157 : H7 using surface plasmon resonance (SPR) biosensor].

A biosensor based on surface plasmon resonance (SPR) was developed for rapid detection of Escherichia coli O157 : H7. BIACORE 3000 SPR instrument and a dextran-modified sensor chip (CM5) were used. After activation with EDC/NHS, anti-E. coli O157 : H7 antibody was immobilized on the gold surface of the SPR sensor, and then following ethanolamine was injected, and the chip was ready for E. coli O157 : H7. Regeneration was achieved using NaOH in order to detect several samples. The limit of detection was found to be 3 x 10(5) CFU x mL(-1) for E. coli O157 : H7, and the change of RU was linearly correlated with the concentration of E. coli O157 : H7 cells (R2 = 0.99). The detection time ranged from 5 to 7 min, and the result of regeneration was effective which allowed the chip to be reused for more than 50 samples. This method is convenient, and stable, and shows potentials for applications in food areas.

[Research on the trash content measurement and classification of ginned cotton by using NIR spectroscopy technique].

Near infrared (NIR) spectroscopy was investigated to predict trash content and classify types of ginned cotton by using a fiberoptic in diffuse reflectance mode. Different spectra preprocessing methods were compared, and partial least-squares (PLS) regression was established to predict the trash content of ginned cotton. Discriminant analysis (DA) was used to classify various types of lint and content level of trash. The correlation coefficient r was 0.906 for optimal PLS model using three factors based on first-order derivative spectra, and RMSEC and RMSEP was 0.440 and 0.823 respectively. To classify ginned cotton with and without plant trash, the accuracy rate reached 95.4% using 15 principal components (PCs) via DA, whereas the prediction accuracy rate was only 80.9% for the classification of sample types due to containing foreign fiber, and the classification result for the content level of trash in lint was not good for the samples without any preprocessing. The result indicated that the NIR spectra of sample can be used to predict trash content in ginned cotton, which is often disturbed by type, content and distribution of foreign matters, and the accuracy of some prediction model is unsatisfactory. In order to improve the prediction accuracy, some methods would be applied in future research, such as pretreatment according to acquisition request of solid sample, or using transmission mode.

[Applications of atomic emission spectrum from liquid electrode discharge to metal ion detection].

The fast and precise detection of metal ion is an important research project concerning studies in diverse academic fields and different kinds of detecting technologies. In the present paper, the authors review the research on atomic emission spectrum based on liquid electrode discharge and its applications in the detection of metal ion. In the first part of this paper the principles and characteristics of the methods based on electrochemistry and spectroscopy were introduced. The methods of ion-selective electrode (ISE), anodic stripping voltammetry, atomic emission spectrum and atomic absorption spectrum were included in this part and discussed comparatively. Then the principles and characteristics of liquid electrode spectra for metal ion detection were introduced. The mechanism of the plasma production and the characteristics of the plasma spectrum as well as its advantages compared with other methods were discussed. Secondly, the authors divided the discharge system into two types and named them single liquid-electrode discharge and double-liquid electrode respectively, according to the number of the liquid electrode and the configuration of the discharge system, and the development as well as the present research status of each type was illustrated. Then the characteristics and configurations of the discharge systems including ECGD, SCGD, LS-APGD and capillary discharge were discussed in detail as examples of the two types. By taking advantage of the technology of atomic emission spectrum based on liquid electrode discharge, the detecting limit of heavy metals such as copper, mercury and argent as well as active metal ions including sodium, potass and magnesium can achieve microg x L(-1). Finally, the advantages and problems of the liquid-electrode discharge applied in detection of metal ion were discussed. And the applications of the atomic emission spectrum based on liquid electrode discharge were prospected.

[Application of near-infrared spectroscopy to detection of pesticide phoxim residues].

Near-infrared (NIR) spectroscopy technique was applied directly to the detection of pesticide phoxim residues. A sample pretreatment method was introduced. Samples were mixed with silica gel. Silica gel as a sorbent was employed to extract and enrich the low-concentration samples. Subsequently, diffuse reflection spectrum was measured on silica gel. Calibration models were developed using partial least square regression (PLSR) algorithm. Leave-one-out cross-validation was used to evaluate and compare the models. Two experiments were carried out, and the results show that 21 samples with the concentration gradient of 0.5 mg x L(-1) exhibited a high correlation coefficient of cross-validation of 0. 958, and a root mean square error of cross validation (RMSECV) of 0.872 mg x L(-1), while 41 samples with the concentration gradient of 0.25 mg x L(-1) gave a correlation coefficient of cross-validation of 0.924 and RMSECV of 1.15 mg x L(-1). It is indicated that with the reduction in concentration gradient, the prediction capacity of models dropped, but there still existed a high correlation coefficient with the concentration of phoxim in the samples. The experiments proved that the sample pretreatment method with the introduction of silica gel as an absorber to enrich low concentration analyte was effective. The method was able to lower the detection limit of NIR. The developed technique has a potential application in low-concentration sample detection by NIR spectroscopy, such as pesticide residues.

[Application of immunomagnetic separation to E. coli O157 : H7 detection].

In the present paper, the capture efficiencies of four different proportions of E. coli O157 : H7 and immunomagnetic beads (IMB) (1 : 6.34, 1 : 12.69, 1 : 25.38 and 1 : 30.07) and three different proportions of E. coli O157 : H7 and Bacillus subtilis (0.3 mL : 0.1 mL, 0.2 mL : 0.2 mL and 0.1 mL : 0.3 mL) were compared, with the total volume and capacity of IMB remaining constant. It was revealed that the capture efficiency could reach 100% when the proportion of E. coli O157 : H7 and IMB was 1 : 30, meaning that almost all targets E. coli O157 : H7 could be captured at 1 : 30, and that the capture efficiency decreased and then increased with the number of Bacillus subtilis increasing. Moreover, the combination of ATP bioluminescence and IMS was correlated well with conventional culture methods, R2 = 0.9882, and the detection limit was as low as 10(2) CFU x mL(-1).

[Application and recent development of research on near-infrared spectroscopy for meat quality evaluation].

As one of new optical detection methods, near-infrared spectroscopy (NIRS) technique has been widely used in food industry in recent years. NIRS technique is also promising for quality evaluation of meat and meat products and is characterized by its quickness, online operation and nondestructive detection. The present paper reviews the main application and recent development of research on near-infrared spectroscopy in meat industry, including components analysis, sensory quality evaluation as well as discrimination of production. It's necessary to determine the content of main chemical components in a variety of meat such as protein, fat, water etc as they exert important influence on meat quality. Sensory quality including tenderness, water holding capacity, color, and freshness is commonly evaluated by human sensory system. Thus there is an obvious potential profit to achieve online determination industrialization for meat quality. Additionally the utilization of NIRS in quality detection of common meat products is particularized in this paper. Most study of near-infrared spectroscopy technique for meat quality evaluation lays emphasis on component analysis that especially has shown a progress in the determination of protein, fat, water and part of fatty acid, which has been investigated much recently. Not any kind of sensory quality can be well predicted by NIRS as it depends on the species of meat and the limitation of this optical technique. Therein beef is the mostly used object with many reports on the evaluation of tenderness compared to other types. There is a lot of investigation for sensory quality detection of pork on water holding capacity etc. Meanwhile this review also tries to come up with some perspectives on meat quality detection with near-infrared spectroscopy according to current development trend: on the basis of deeply improving the meat detection precision, near-infrared spectroscopy technique combined with other non-detection techniques like machine vision will be investigated in order to realize overall evaluation of meat quality.

[Applications of terahertz spectroscopy and imaging techniques in food safety inspection].

With the development of ultra-fast laser technology and the further understanding of the mechanism behind the interaction of terahertz radiation and materials, THz radiation is actively developed as a new-style technology for a wide range of applications. Currently THz spectroscopy and imaging techniques show great promise in security detection, medical diagnosis, wireless communication, pharmaceutical and many other areas. Because of the growing importance of food safety issues, the detection technology of food safety is also faced with great opportunities and challenges, while THz spectroscopy and imaging techniques provide a new solution to the problem. Compared to other technologies, THz radiation with higher signal-to-noise ratio and wide dynamic range can simultaneously obtain both frequency-domain and time-domain information of the sample which relates to the information of physical structure and chemical composition of materials. Above all THz radiation features unique advantages in food safety inspection. In the present paper, the brief concept of terahertz radiation was introduced, while the properties and technical methods of THz wave were also discussed. The most recent progress in THz technology used in food safety inspection was summarized. The prospect and restricted factors of this novel technology in food industry were also discussed.

[Study on Vis/NIR spectra detecting system for watermelons and quality predicting in motion].

To make Vis/NIR diffuse transmittance technique applied to quality prediction for watermelon in motion, the dynamic spectra detecting system was rebuilt. Spectra detecting experiments were conducted and the effects of noises caused by motion on spectra were analyzed. Then the least--square filtering method and Norris differential filtering method were adopted to eliminate the effects of noise on spectra smoothing, and statistical models between the spectra and soluble solids content were developed using partial least square method. The performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples, root mean square errors of calibration (RMSEC) and root mean square errors of prediction (RMSEP). Calibration and prediction results indicated that Norris differential method was an effective method to smooth spectra and improve calibration and prediction results, especially, with r of 0.895, RMSEC of 0.549, and RMSEP of 0.760 for the calibration and prediction result of the first derivative spectra.

[Advance in nondestructive detection of fruit internal quality based on hyperspectral imaging].

The present paper reviews the development in the field of hyperspectral imaging technology for nondestructive detection of fruit internal quality in recent years up to the year 2007. With the increasing maturity of hyperspectral imaging technology, decline of cost for its hardware and software, and improvement in hyperspectral image data processing algorithms, hyperspectral imaging technology for fruit quality nondestructive detection has become a hot research topic. In order to track the latest research developments at home and abroad, the fruit internal quality (maturity, firmness, soluble solid content, water content) detection with hyperspectral imaging was reviewed, which would provide reference for Chinese researchers.

[NIR spectroscopy based on least square support vector machines for quality prediction of tomato juice].

The application of least square support vector machines (LS-SVM) regression method based on statistics study theory to the analysis with near infrared (NIR) spectra of tomato juice was introduced in the present paper. In this method, LS-SVM was used for establishing model of spectral analysis, and was applied to predict the sugar contents (SC) and available acid (VA) in tomato juice samples. NIR transmission spectra of tomato juice were measured in the spectral range of 800-2,500 nm using InGaAs detector. The radial basis function (RBF) was adopted as a kernel function of LS-SVM. Sixty seven tomato juice samples were used as calibration set, and thirty three samples were used as validation set. The results of the method for sugar contents (SC) and available acid (VA) prediction were: a high correlation coefficient of 0.9903 and 0.9675, and a low root mean square error of prediction (RMSEP) of 0.0056 degree Brix and 0.0245, respectively. And compared to PLS and PCR methods, the performance of the LSSVM method was better. The results indicated that it was possible to built statistic models to quantify some common components in tomato juice using near-infrared (NIR) spectroscopy and least square support vector machines (LS-SVM) regression method as a nonlinear multivariate calibration procedure, and LS-SVM could be a rapid and accurate method for juice components determination based on NIR spectra.

[Study on classification of ethylene treated and non-ethylene treated watermelons by visible/near infrared spectroscopy].

According to the fact that farmers often picked unripe watermelon and treated them with high concentration ethylene to quicken ripeness, classification experiments on the two classes of watermelon mentioned above were conducted based on the Vis/NIR spectroscopy diffuse transmittance technique. In the discriminant analysis, a method to classify them by diffuse transmittance ration at two wavelengths was adopted to discriminate them. Result of mistake ratio 32.5% for samples without ethylene treatment and 20% for ethylene treatment samples indicated that this method could discriminate the two classes of watermelons roughly. Mahalanobis distance and partial least square methods were also used here for discriminant analysis and satisfied results were obtained. The first derivative spectra with Norris derivative filtering of samples without being ethylene-treated using Mahalanobis distance discriminant analysis got the result of mistake ratio 1.67% for calibration set, no mistake for prediction set and no mistake for samples being ethylene treated. No mistake took place for the second derivative spectra using partial least square method. In discriminant analysis, spectral data pretreatment methods influence the discriminant results and it should be selected according to the analysis methods.

[Effect of pathlength variation on the NIR spectra for quality evaluation of chinese rice wine].

Near infrared (NIR) spectroscopy and chemometrics were applied to determine the effect of pathlength variation on the spectra of the Chinese rice wine and the consequences of the prediction precision of calibration models developed for measuring alcoholic degree, sugar content, and pH was investigated in the present research Samples were scanned in transmission mode using a commercial FT-NIR spectrometer and a demountable liquid cell for versatile path length liquid sampling. By comparing the results of performance between models based on different optical pathlength (0.5, 1, 1.5, 2, 2.5, and 3 mm), the best indicators of optical pathlength were identified. Based on the optimum pathlength, the models for alcoholic degree, sugar content and pH were established. The best optical pathlength for the alcoholic degree was 2 mm, using partial least squares regression (PLSR) model with the original spectra, correlation coefficient (r) was 0.942, root mean standard error of calibration (RMSEC) and root mean standard error of cross-validation (RMESCV) were 0.256 (%, (phi)) and 0.292 (%, (phi)), respectively; the best optical pathlength for the sugar content was 1 mm, using PLSR model with the original spectra, r was 0.945, and RMSEC and RMESCV were 0.125% and 0.149%, respectively; the best optical pathlength for the pH was 2 mm, using PLSR model with the original spectra, r was 0.947, and RMSEC and RMESCV were 0.018 and 0.039, respectively. This study showed that pathlength variation had influence on the performance of calibration models for Chinese rice wine, and a suitable pathlength could effectively improve detection accuracy.

Use of near-infrared spectroscopy and least-squares support vector machine to determine quality change of tomato juice.

Near-infrared (NIR) transmittance spectroscopy combined with least-squares support vector machine (LS-SVM) was investigated to study the quality change of tomato juice during the storage. A total of 100 tomato juice samples were used. The spectrum of each tomato juice was collected twice: the first measurement was taken when the tomato juice was fresh and had not undergone any changes, and the second measurement was taken after a month. Principal component analysis (PCA) was used to examine a potential capability of separating juice before and after the storage. The soluble solid content (SSC) and pH of the juice samples were determined. The results show that changes in certain compounds between tomato juice before and after the storage period were obvious. An excellent precision was achieved by LS-SVM model compared with discriminant partial least-squares (DPLS), soft independent modeling of class analogy (SIMCA), and discriminant analysis (DA) models, with 100% of a total accuracy. It can be found that NIR spectroscopy coupled with LS-SVM, DPLS, SIMCA, and DA can be used to control the quality change of tomato juice during the storage.

[Identification of tea from different regions using X-ray fluorescence].

The existence of fake tea from non-origin seriously impacts on the credibility of the famous tea. A method was developed to identify tea from difference regions on the basis of the fact that the content of heavy metals in different origin tea is varied by using X-ray fluorescence technique and pattern recognition technique. Samples from different origins were grouped respectively, and their X-ray fluorescence spectra were acquired, and then the principal components of these spectral data were calculated, and the average of the principal components of each group was used as the center of each group. The Mahalanobis distance value between a sample and the center of a group were calculated, when the Mahalanobis distance value reached minimum, the sample was classed to current group, and in this way, a sample was identified. A Niton 792 portable X-ray spectrometer was used to class 120 tea samples from Anji, Jinhua, Hangzhou and Taizhou, in zhejiang province of China. It was found that the spectra between 3 and 13 KeV and the first 4 principal components give enough information for the identification of tea from different regions,and the rate of error was 4.2%.