[Rapid diagnostics of early phosphorus deficiency in mini-cucumber plants under protected cultivation by near infrared spectroscopy].

The morphological symptom of phosphorus deficiency at early stage is similar to the appearance of leaf aging process in preliminary phase, so that visual diagnostics of phosphorus deficiency in mini-cucumber plants at early stage is practically impossible. Near infrared reflectance spectra contain information about differences in compositions of leaf tissues between phosphorus-deficient plants and healthy plants. In the present paper, near infrared reflectance spectroscopy was used to provide diagnostic information on phosphorus deficiency of mini-cucumber plants grown under non-soil conditions. Near infrared spectra was collected from 90 leaves of mini-cucumber plants. Raw cucumber spectra was preprocessed by SNV and divided into 27 intervals. The top 10 principal components (PCs) were extracted as the input of BP-ANN classifiers by principal component analysis (PCA) while the values of nutrient deficient were used as the output variables of BP-ANN and three layers BP-ANN discrimination model was built. The best experiment results were based on the top 3 principal components of No. 7 interval when the spectra was divided into 27 intervals and identification rates of the ANN model are 100% in both training set and the prediction set. The overall results show that NIR spectroscopy combined with BP-ANN can be efficiently utilized for rapid and early diagnostics of phosphorus deficiency in mini-cucumber plants.

[A new method of characteristic wavelength sub-range selection of near infrared spectroscopy].

To improve and simplify the prediction model of carotenoid content of cucumber leaves, genetic algorithm (GA) combined with Metropolis acceptance criterion of simulated annealing algorithm (SAA) as well as interval partial least square (iPLS) were proposed and used to establish the calibration models of carotenoid content against cucumber leaves spectra. The cucumber leaves spectra data were divided into 40 intervals, among which 7 subsets, i. e. No. 3, 4, 14, 18, 21, 32 and 33, were selected by SAA-GA-iPLS. The comparison was made between SAA-GA-iPLS and traditional genetic algorithm interval partial least square (GA-iPLS), and the result of this study shows that SAA-GA-iPLS was better than traditional genetic algorithm interval partial least square (GA-iPLS).

[Near infrared determination of sugar content in apples based on GA-iPLS].

To improve and simplify the prediction model of sugar content, genetic algorithm interval partial least square (GA-iPLS) methods, the evolution of iPLS described by Lars Nørgaard, were proposed and used to establish the calibration models of sugar content against apple spectra. The apple spectra data were divided into 40 intervals, among which 5 subsets, i. e. No. 4, 6, 8, 11 and 18, containing 362 data points were selected by GA-iPLS. The optimum GA-iPLS calibration model was obtained with the correlation coefficient (rc) of 0.962, the root mean square error of cross-validation (RMSECV) of 0.3346 and the root mean square error of prediction (RMSEP) of 0.3846. Compared with the whole spectra data model, the data points and the factors in the GA-iPLS were decreased significantly. Consequently, the running time of the PLS model build by GA-iPLS was shorter than that of the whole spectra data model. Furthermore, the GA-iPLS model could not only improve precision, but also simplify the model.

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.

A new sensor for ammonia based on cyanidin-sensitized titanium dioxide film operating at room temperature.

Design and fabrication of an ammonia sensor operating at room temperature based on pigment-sensitized TiO2 films was described. TiO2 was prepared by sol-gel method and deposited on glass slides containing gold electrodes. Then, the film immersed in a 2.5×10(-4)M ethanol solution of cyanidin to absorb the pigment. The hybrid organic-inorganic formed film here can detect ammonia reversibly at room temperature. The relative change resistance of the films at a potential difference of 1.5V is determined when the films are exposed to atmospheres containing ammonia vapors with concentrations over the range 10-50 ppm. The relative change resistance, S, of the films increased almost linearly with increasing concentrations of ammonia (r=0.92). The response time to increasing concentrations of the ammonia is about 180-220 s, and the corresponding values for decreasing concentrations 240-270 s. At low humidity, ammonia could be ionized by the cyanidin on the TiO2 film and thereby decrease in the proton concentration at the surface. Consequently, more positively charged holes at the surface of the TiO2 have to be extracted to neutralize the adsorbed cyanidin and water film. The resistance response to ammonia of the sensors was nearly independent on temperature from 10 to 50°C. These results are not actually as good as those reported in the literature, but this preliminary work proposes simpler and cheaper processes to realize NH3 sensor for room temperature applications.

Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy.

Total flavonoids content is often considered an important quality index of Ginkgo biloba leaf. The feasibility of using near infrared (NIR) spectra at the wavelength range of 10,000-4000cm(-1) for rapid and nondestructive determination of total flavonoids content in G. biloba leaf was investigated. 120 fresh G. biloba leaves in different colors (green, green-yellowish and yellow) were used to spectra acquisition and total flavonoids determination. Partial least squares (PLS), interval partial least squares (iPLS) and synergy interval partial least squares (SiPLS) were used to develop calibration models for total flavonoids content in two colors leaves (green-yellowish and yellow) and three colors leaves (green, green-yellowish and yellow), respectively. The level of total flavonoids content for green, green-yellowish and yellow leaves was in an increasing order. Two characteristic wavelength regions (5840-6090cm(-1) and 6620-6880cm(-1)), which corresponded to the absorptions of two aromatic rings in basic flavonoid structure, were selected by SiPLS. The optimal SiPLS model for total flavonoids content in the two colors leaves (r(2)=0.82, RMSEP=2.62mg g(-1)) had better performance than PLS and iPLS models. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total flavonoids content in fresh G. biloba leaf.