A rapid method for screening potential biological control agents of wood decay

Sixteen isolates of microfungi, obtained from freshly felled pine, were screened for inhibitory activity on a number of wood-decay basidiomycetes. The screening procedure employed a bi-layer test which involved growing the potential biocontrol isolates on either agar medium or irradiated pine discs. The influence that the two different substrata had on subsequent inhibition of decay fungi may have important implications for the screening of isolates for biocontrol activity. The use of such techniques for screening biocontrol agents is discussed.     

Effect of growing site,sampling date,wood location in trunk and drying method on concentration of soluble proanthocyanidins in Betula pendula wood,with special reference to wood colour

Proanthocyanidins (PAs), which are common phenolic compounds in plants, are considered to be mainly defensive compounds against different kinds of stress, e.g. herbivory. In addition to increasing after stress, they may condense and/or oxidize to form coloured compounds when cells die, which may affect both the resistance of xylem to rot and its colour. This is important in the mechanical wood industry. The effects of some biological factors (growing site, sampling date, wood location in the trunk) on the concentration of soluble PAs (sPAs) were studied in fresh and dried birch wood. Those factors that affected sPA concentration most were sampling date and radial location. Drying method also had a great effect on the sPA concentration, which in turn correlated with the colour of the wood.     

A multistep approach to classify full canopy and leafless trees in bottomland hardwoods using very high-resolution imagery

The distribution of leafless and full-canopy trees in fall is essential in understanding the phenological and morphological characteristics of forests and those are critical baseline information for several scientific questions and management scenarios. The rapid progress of very high-resolution satellite-borne sensors provides a feasible solution to fast and accurately map tree coverage during the growing season. However, less attention has been paid to the leaf-off seasons. One biggest challenge with classification on fall imagery is the potential confusion among different land features, as evidenced by the no significant difference between bare land and leafless trees from t-test and transformed divergence (TD) analysis results. We proposed an integrative approach to classifying leafless and full-canopy trees on fall imagery of 0.46-m WorldView-2 (WV-2). We adopted a two-step classification approach by first removing the non-forest area from the WV-2 imagery with the mask layer generated from the publicly available summer imagery of 1-m National Agriculture Imagery Program imagery via object-based image analysis. Two classification methods, namely decision tree (DT) and nearest neighborhood (NN), were employed to classify full canopy and leafless trees in the masked WV-2 imagery. DT performed slightly better than NN regarding higher overall accuracy and fewer feature requirements.