[Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film].

In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380～1 030 nm) and NIR (874～1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.

[Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient content of fruit trees at canopy level. This would provide valuable information for the implementation of individual tree-based fertilization schemes in precision orchard management practices.

[Development of prediction models for determining N content in citrus leaves based on hyperspectral imaging technology].

The present study presents prediction models for determining the N content in citrus leaves by using hyperspectral imaging technology combined with several chemometrics methods. The steps followed in this study are: hyperspectral image scanning, extracting average spectra curves, pretreatment of raw spectra data, extracting characteristic wavelengths with successive projection algorithm and developing prediction models for determining N content in citrus leaves. The authors obtained three optimal pretreatment methods through comparing eleven different pretreatment methods including Savitzky-Golay (SG) smoothing, standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (1-Der) and so on. These selected pretreatment methods are SG smoothing, detrending and SG smoothing-detrending. Based on these three pretreatment methods, the authros first extracted the characteristic wavelengths respectively with successive projection algorithm, and then used the spectral reflectance of the extracted characteristic wavelengths as input variables of partial least squares regression (PLS), multiple linear regression (MLR) and back propagation neural network (BPNN) modeling. Hence, the authors developed three prediction models with each pretreatment method, and obtained nine models in total. Among all the nine prediction models, the two models based on the methods of SG smoothing-detrending-SPA-BPNN (R(p): 0.8513, RMSEP: 0.1881) and detrending-SPABPNN (R(p): 0.8609, RMSEP: 0.1595) were found to have achieved the best prediction results. The final results show that using hyperspectra data to determine N content in citrus leaves is feasible. This would provide a theoretical basis for real-time and accurate monitoring of N content in citrus leaves as well as rational N fertilizer application during the plant's growth.

Meta-analysis of association between particulate matter and stroke attack.

AIMS: We conducted systematic review as well as meta-analyses on the association between particulate matter and daily stroke attack from a number of epidemiologic studies. METHODS: Twelve quantitative studies about the associations between particulate matter and stroke attack met the inclusive criteria. We evaluated the odds ratio (OR) of stroke attack associated with per 10 µg/m(3) increase of the concentration of PM(10) (particulate matter with aerodynamic diameter ≤ 10 µm) or PM(2.5) (particulate matter with aerodynamic diameter ≤ 2.5 µm) as effect scale, and a sensitivity analysis for the results was conducted. RESULTS: In the time-series design, PM(10) exposure wasn't related to an increased risk of daily stroke attack [OR per 10 µg/m(3) = 1.002, 95% confidence interval (CI): 0.999~1.005], PM(2.5) exposure were related to an increased risk of daily stroke attack (OR per 10 µg/m(3) = 1.006, 95%CI: 1.002~1.010]; but in the case-crossover studies, PM(10) exposure was related to increase in risk of daily stroke attack (OR per 10 µg/m(3) = 1.028, 95%CI: 1.001~1.057). PM(2.5) exposure was not significant association with daily stroke attack (OR per 10 µg/m(3) = 1.016, 95%CI: 0.937~1.097). Sensitivity analysis showed that the results for PM(10) , PM(2.5) and daily stroke attack were robust in the time-series design. CONCLUSIONS: We found some evidence for an effect of air pollutants on stroke attack risk.

[Nondestructive measurement of cellular ATP contents in vegetables using UV-Vis-NIR spectroscopy].

The cellular ATP content level in agricultural products directly reflects cell viability, therefore it can be potentially used as an indicator of freshness and quality of agricultural products during storage. Spectral data of sample spinach leaves were obtained using a UV-Vis-NIR spectrophotometer UV-3600. Protoplast suspensions were prepared by following the conventional physical-chemical methods, and the ATP contents in protoplasts were determined by the firefly luciferase bioluminescence technology. Person's correlation analysis was performed to identify the key wavelengths. Models were developed for estimating the ATP contents in spinach protoplasts based on the two identified key wavelengths, i. e. the ultraviolet 298 nm and the near-infrared 730 nm wavelengths. Results showed that both of the two key wavelengths (298 and 730 nm) have a considerable promise in estimating the ATP content in spinach protoplasts (R2 = 0.802 9 and 0.901 respectively). The spectroscopy based estimation of cellular ATP content in vegetables proposed in this study provides a new approach to the accurate, rapid, and non-destructive evaluation of the freshness of vegetables.

[Association between air particulate matter and stroke attack or mortality: a Meta-analysis].

OBJECTIVE: To analyze the associations between particulate air pollution (PM(10), PM(2.5)) and stroke daily attack or mortality. METHODS: Meta-analysis method was used to polysynthetically analyze 16 quantitative studies about the associations between particulate air pollution and stroke daily attack or mortality. The relative odds ratio (OR)of stroke attack or mortality associated with per 10 µg/m(3) increase of particulate matter concentration was used as effective value, taking a sensitivity analysis for the results. RESULTS: A 10 µg/m(3) increase in PM(10) was associated with a 1.09% (95%CI: 0.10% - 2.08%) increase in stroke daily attack (OR = 1.011, 95%CI: 1.001 - 1.021) and 0.70% (95%CI: 0.60% - 0.80%) increase in stroke daily mortality (OR = 1.007, 95%CI: 1.006 - 1.008). The results of sensitivity analysis supported above results. As for PM(2.5) OR appeared to be 1.001 (95%CI: 0.992 - 1.010) with a 10 µ g/m(3) increase in stroke daily attack and 1.052 (95%CI: 0.958 - 1.154) for daily mortality. CONCLUSION: There are positive associations between PM(10) and stroke daily attack and mortality, increase of PM(2.5) was not associated with stroke attack and mortality.

[Development of citrus yield prediction model based on airborne hyperspectral imaging].

The phenomenon of alternate bearing of fruits seriously affects the fruit yields as well as the economic benefits of orchards. The present study investigated the possibility of airborne hyperspectral images to predict the fruit yield of individual citrus trees. The hyperspectral data were first extracted from the images and the predictors were determined using partial least-squares regression (PLS). The optimal number of PLS factors were identified, and they were used as inputs of citrus yield prediction models developed by means of multiple linear regression (MLR) and artificial neural network (ANN) modelling techniques. The results showed that the models based on the hyperspectral images obtained in May achieved the best prediction, and the PLS-MLR model has a better stability and consistency than the PLS-ANN model. These results provide an important theoretical and technical foundation for the future research and development of hyperspectral imaging-based citrus production techniques.

[Association of the behavior problems of school-age children with gender, age and registered permanent residence].

OBJECTIVE: To assess whether and how the prevalence of behavior problems among the school-age children are associated with their gender, age and registered permanent residence. METHODS: The behavior problems in 2156 children were estimated with the aid of Rutter Parent Questionnaire (RA2) and Rutter Teacher Questionnaire (RB2) from September to October 2004. RESULTS: The prevalence rates of children having behavior problems were 13.5% in RA2 and 13.8% in RB2, and these were higher in boys than in girls (RA2:1.79; RB2: 2.82). According to parents' and teachers' assessments, the highest positive rates in grades were 16.3% in grade 2 and 15.1% in grade 4, and the highest positive rates among the three groups of permanent residence were 16.3% in rural children and 19.5% in urban pupils. In multivariate logistic regression analyses, the significant positive correlates were male, urban for antisocial behavior and male for neurotic behavior in RA2, and male, urban and higher grade for all behavior problems in RB2. CONCLUSION: The detected rate of behavior problems among school-age children in Zhejiang province was higher than that reported by other researchers. The differences of gender, age, and registered permanent residence were significant in both RA2 and RB2. Male, urban and higher grade children should be an important group of school-age children in need of guidance with mental health.

[A study on awareness of sexually-transmitted disease/acquired immunodeficiency syndrome and related factors among migrant workers in Hangzhou City, Zhejiang Province of China].

OBJECTIVE: To understand awareness on transmission routes of sexually transmitted diseases and acquired immunodeficiency syndrome (STD/AIDS) among migrant workers in Hangzhou City, Zhejiang Province. METHODS: A cross-sectional study was conducted in migrant workers in Hangzhou with self-administered anonymous questionnaire to collect their demographic information and awareness on STD/AIDS. All the data were analyzed by SPSS 11.0 software. RESULTS: A total of 3 001 subjects were interviewed. Most of them have already had some knowledge about STD/AIDS, but not complete. There were 556 (18.8%) migrant workers did not understand that condom could prevent from STD, and 759 did not know if it could do. There were 357 (11.9%) workers did not know AIDS could be prevented, and 746 (24.9%) thought that AIDS could be cured. There were 637 workers did not know that correct use of condom could reduce occurrence of AIDS, and 725 of them thought AIDS could be infected by hands-shaking and hugging with patients of AIDS. There existed statistically significant difference in awareness on STD/AIDS between men and women, workers with varied marital status and education levels. CONCLUSIONS: Awareness on STD/AIDS in migrant workers was smattering, allowing of not optimistic. Community-based health education on knowledge about STD/AIDS should be strengthened among high-risk migrant workers with varied channels to improve their awareness.