a b s t r a c t a r t i c l e i n f oWe propose an automatic pest identification method suitable for large scale, long term monitoring for mobile or embedded devices in situ with less computational cost. A procedure of segmentation and image separation was devised to identify common greenhouse pests, whiteflies, aphid and thrips. Initially, the watershed algorithm was used to segment insects from the background (i.e., sticky trap) images. Color feature of the insects were subsequently extracted by Mahalanobis distance for identification of pest species. Accuracy and computational costs were evaluated across different image resolutions. The correlation of determination (R 2 ) between the proposed identification scheme and manual identification were high, showing 0.934 for whitefly, 0.925 for thrips, and 0.945 for aphids even with low resolution images. Comparing with the conventional methods, pests were efficiently identified with low computational cost. Optimal image resolution for species identification regarding long-term survey was discussed in practical aspect with less computational complexity.

The Fuzzy Comprehensive Evaluation (FCE) and the Principal Component Analysis (PCA) were simulated to assess water quality of the Nansi Lake Basin, China. The membership functions were established via the Nor-Half Sinusoidal Distribution Method, and the weight was calculated via the Exceeding Standard Multiple Method. To enhance the efficiency of extracting principal pollutant, the eigenequation was solved through the Jacobi Method, and the principal components were extracted based on eigenvalue, contribution ratio, accumulating contribution ratio, principal component loading and score. Water quality classification based on “National Surface Water Environmental Quality Standards of China (GB3838-2002) was used to assess the water quality. Considering the difference of the temporal and spatial distribution in average, water quality of Level I was 28.9%, 28.1%, 25.1%, 25.6%, respectively in spring, summer, autumn, and winter, which suggested that water quality in spring and summer was better than in autumn and winter. The order of water quality was Zhaoyang Lake (Level I) > Nanyang Lake (Level I) > Dushan Lake (Level III) > Weishan Lake (Level III and IV). There were four extracted principal components that can replace the fourteen pollutant indexes for assessing water quality. According to the annual mean data of the 1st principal components, the most important pollutions were heavy metals, including As (0.933), Hg (0.931), Cd (0.929), Cr(VI) (0.926), Pb (0.925), and Cu (0.534). It is proved that the combined FCE-PCA model could provide valuable information in the water quality assessment for the Nansi Lake Basin.

Polybrominated diphenyl ethers (PBDEs), due to their widespread usage as flame retardants and their lipophilicity and persistence, have become ubiquitous in the environment. It is urgent to understand the environmental characteristics of PBDEs in marine system, but they have attracted little attention. We summarize the available data and analyze the regional distributions, controlling factors, and congener patterns of PBDEs in marine and associated environmental matrixes worldwide. Based on meta-analysis, after separating the estuarial sites from the marine sites, ignoring the extraordinary sample sites such as those located just near the point source, the PBDE concentration levels are still in the same order of magnitude from global scale. Despite Principal Component Analysis, the congener patterns of sediments are predominant with the heavy brominated congeners (BDE-209 contributing over 75% to the total load) while the biota abound with the light ones (BDE-47, BDE-99, and BDE-100 taking about 80%). The ratio between BDE-99 and BDE-100 for the lower trophic-level species often turns to be greater than 1, while for those higher species the ratio may be below 1, and some species feed mainly on the crustaceans and zooplankton seems to have a higher ratio value. The data of the PBDEs in marine system are currently limited; thus, data gaps are identified as well.

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