Pine wilt disease is a devastating forest disease worldwide caused by the pinewood nematode (PWN; Bursaphelenchus xylophilus). Esteya vermicola is widely recognized as a promising bio‐control agent effective against PWN. During a survey of associated microorganisms of Pinus yunnanensis in Southwest China, a novel isolate of E. vermicola was obtained. This isolate produced two types of conidia. One type of conidia was hyaline, unicellular, bacilloid, and non‐adhesive. The second type of conidia is solitary, hyaline, unicellular asymmetric elliptic or lunate, concave inward, ending slightly apiculate, adhesive on the concave surface, and contained an ovoid endospore‐like structure. Only the lunate conidia showed infection activity against PWN. This novel isolate produced a high proportion of infective lunate conidia and exhibited high adhesion and infection activity against PWN by adhering to the nematode within 48 h and killing 74.5% of the tested PWN individuals within 4 days. Given that the isolate was obtained from P. yunnanensis, it may be well adapted to the endogenous environment of pine trees. The isolate shows potential as a bio‐control agent against a plant‐parasitic nematode in the field.
The most weakness link in credible monitoring is that how to process multidimensional dynamic behavior data effectively. System behavior monitoring often needs to deal with different kinds of behavior data and those data can adopt status snapshot in multi-dimensional vector form to express. Obviously, data has strong useful knowledge information, which is regarded as a kind of classification ability. So we need to finish the mapping and classification between a variety of network behavior snapshot and dependable level. This paper introduces on network state snapshot owning the characteristics of high dimension, heterogeneous and dynamic and uses the theory of interval intuitionistic fuzzy to judge credible degree in the system and generate behavior quality trust level of nodes.
This paper process spectral data of the water based on normalization and Envelope elimination methods, by correlation analysis between land surface spectral data of single band or combining band and concentration of chlorophyll a and Suspended Solid to select band with max correlation coefficients, construct the best linear regressive models between spectral data and chlorophyll a and suspended solid. Firstly, the reflectance of the land surface of Hyperion images were obtained through geometric rectification and atmospheric modification adopted the 6S model, then the maps of spatial distributions of the concentration of chlorophyll a and suspended solid in the Nansi Lake were obtained using the best linear regressive model of chlorophyll a and the best linear regressive model of suspended solid. The results show that, data process of envelope elimination can remove the effect of the background spectral effectively and stand out the features of spectral absorption and reflection, and the combination of spectral R700/R560 and R736/R759 can be used to retrieved the concentration of chlorophyll a and suspended solid in the Nansi Lake.
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