In this paper, 104 samples of Chinese rice wines of the same variety (Shaoxing rice wine), collected in three winery ("guyuelongshan", "pagoda" brand, "kuaijishan"), three brewed years (2002, 2004, 2004-2006) were analyzed by near-infrared transmission spectroscopy between 800 and 2500 nm. The spectral differences were studied by principal components analysis (PCA), and Classifications, according the brand, were carried out by discriminant analysis (DA) and partial least squares discriminant analysis (PLSDA). The DA model gained a total accuracy of 94.23% and when used to predict the brand of the validation set samples, a better result, correctly classified all of the three kinds of Chinese rice wine up to 100%, are obtained by PLSDA model. The work reported here is a feasibility study and requires further development with considerable samples of more different brands. Further studies are needed in order to improve the accuracy and robustness, and to extend the discrimination to other Chinese rice wine varieties or brands.
Biological cells have components acting as electrical elements that maintain the health of the cell by regulation of the
electrical charge content. Plant impedance is decided by the state of plant physiology and pathology. Plant physiology
and pathology can be studies by measuring plant impedance. The effect of Cucumber Mosaic Virus red bean isolate
(CMV-RB) on electrical resistance of tomato leaves was studied by the method of impedance measurement. It was found
that the value of resistance of tomato leaves infected with CMV-RB was smaller than that in sound plant leaves. This
decrease of impedances in leaf tissue was occurred with increased severity of disease. The decrease of resistance of
tomato leaves infected with CMV-RB could be detected by electrical resistance detecting within 4 days after inoculation
even though significant visible differences between the control and the infected plants were not noted, so that the
technique for measurement of tomato leaf tissue impedance is a rapid, clever, simple method on diagnosis of plant
The biosensors, consisting of immobilized antibodies which were for specific recognition to target molecules and electrodes which were able to convert the binding event between antigen and antibody to a detectable signal, were developed for rapid detection of organophosphate (OPs) pesticides. Anti-OPs antibodies were immobilized onto indium-tin-oxide (ITO) coated interdigitated microsensor electrodes (IMEs). The Faradaic impedance spectra, presented as Nyquist plots (Z' vs Z'') and Bode diagrams, (impedance vs frequency) were recorded in the frequency range from 1Hz to 100 kHz respectively. A linear relationship between the electron-transfer resistance and concentrations of OPs pesticide was found ranging from 0.1 ppm to 100 ppm. The regression equations were Y = 658 X +1861, with the correlation coefficient of 0.977. The biosensing procedure was simple and rapid, and could be completed within 1 h.
Some issues related to nondestructive evaluation of valid acidity in intact apples by means of Fourier transform near infrared (FTNIR) (800-2631nm) method were addressed. A relationship was established between the diffuse reflectance spectra recorded with a bifurcated optic fiber and the valid acidity. The data were analyzed by multivariate calibration analysis such as partial least squares (PLS) analysis and principal component regression (PCR) technique. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influence of data preprocessing and different spectra treatments were also investigated. Models based on smoothing spectra were slightly worse than models based on derivative spectra and the best result was obtained when the segment length was 5 and the gap size was 10. Depending on data preprocessing and multivariate calibration technique, the best prediction model had a correlation efficient (0.871), a low RMSEP (0.0677), a low RMSEC (0.056) and a small difference between RMSEP and RMSEC by PLS analysis. The results point out the feasibility of FTNIR spectral analysis to predict the fruit valid acidity non-destructively. The ratio of data standard deviation to the root mean square error of prediction (SDR) is better to be less than 3 in calibration models, however, the results cannot meet the demand of actual application. Therefore, further study is required for better calibration and prediction.