The ecology of algae in relation to river water equality surveillance

The broad objectives of the work were to develop standard methods for the routine biological surveillance of river water quality, using the non-planktonic algae. Studies on sampling methodology indicated that natural substrata should be sampled directly wherever possible, but for routine purposes, only a semi-quantitative approach was found to be feasible. Artificial substrata were considered to be useful for sample collection in deeper waters, and of three different types tested, Polythene strips were selected for further investigation essentially on grounds of practicality. These were tested in the deeper reaches of a wide range of river types and water qualities: 26 pool sites in 14 different rivers were studied over a period of 9 months. At each site, the assemblages developing on 3 strips following a 4, or less commonly, an 3 week immersion period were analysed quantitatively. Where possible, the natural substrata were also sampled semi-quantitatively at each site, and at a nearby riffle. The results of this survey were very fragmentary: many strips failed to yield useful data, and the results were often difficult to interpret, and of limited value for water quality surveillance purposes. In one river, the Churnet, the natural substrata at 14 riffle sites were sampled semi-quantitatively on 14 occasions at intervals of 4 weeks. In this survey, the results were more readily interpreted in relation to water quality, and no special data processing was found to be necessary or helpful. Further studies carried out on the filamentous green alga Cladophora showed that this alga may have some value as a bioaccumulation indicator for metals, and as a bioassay organism for the assessment of the algal growth promoting potential of natural river waters.

Case-based reasoning enabling database mining for cryo-preserving algae applications

Case-based Reasoning's (CBR) origins were stimulated by a desire to understand how people remember information and are in turn reminded of information, and that subsequently it was recognized that people commonly solve problems by remembering how they solved similar problems in the past. Thus CBR became an appropriate way to find out the most suitable solution method for a new problem based on the old methods for the same or even similar problems. The research highlights how to use CBR to aid biologists in finding the best method to cryo preserve algae. The study found CBR could be used successfully to find the similarity percentage between the new algae and old cases in the case base. The prediction result showed approximately 93.75% accuracy, which proves the CBR system can offer appropriate recommendations for most situations. © 2011 IEEE.