Actinomycetes are considered to be the biggest producer of bioactive compounds which are expected to have antifungal activity for controlling many fungi such as Rhizoctonia solani. The objective of this study was to obtain potential soybean rhizosphere actinomycetes as a biocontrol agent for R. solani which cause damping-off disease both in vitro and in vivo, including their ability to produce siderophore, chitinase, and HCN. Out of 26 isolates, 18 (56%) showed diverse antifungal activities against R. solani with percentages of inhibition radial growth (PIRG) from 18.9 to 64.8%, as evaluated by a dual culture method. Ten isolates with the strongest antifungal activity were numbered for further characterization. All the tested isolates were not antagonistic towards Bradyrhizobium japonicum. These isolates were able to suppress damping-off disease caused by R. solani in the greenhouse experiment. Isolate ASR53 showed the highest disease suppression, 68% and 91% in sterile and non-sterile soil, respectively. Based on 16S rRNA sequence analysis this isolate belonged to Streptomyces violaceorubidus LMG 20319 (similarity 98.8%) according to GenBank data base available at www.ncbi.nlm.gov.nih. Furthermore, isolate ASR53 had significantly longer roots and shoots, as well as greater fresh and dry weights of seedlings than the control. Crude extract derived from ASR53 isolates contained 10 dominant compounds that were biologically active against fungal pathogens. Thus, this study suggests that the application of potential actinomycetes of the soybean rhizosphere can act as a promising biocontrol agent against damping-off disease caused by R. solani.

Species diversity of Collembola was studied in the vicinity of Polish Polar Station, Hornsund area, West Spitsbergen. A list of 32 species has been compiled, and their distribution over microlandscapes and microhabitats in the study area has been presented.

In this article the authors investigated and presented the experiments on the sentence boundaries annotation from Polish speech using acoustic cues as a source of information. The main result of the investigation is an algorithm for detection of the syntactic boundaries appearing in the places of punctuation marks. In the first stage, the algorithm detects pauses and divides a speech signal into segments. In the second stage, it verifies the configuration of acoustic features and puts hypotheses of the positions of punctuation marks. Classification is performed with parameters describing phone duration and energy, speaking rate, fundamental frequency contours and frequency bands. The best results were achieved for Naive Bayes classifier. The efficiency of the algorithm is 52% precision and 98% recall. Another significant outcome of the research is statistical models of acoustic cues correlated with punctuation in spoken Polish.