In vitro propagation of <Emphasis Type="Italic">Helleborus</Emphasis> species

A general in vitro cloning system was established for four Helleborus species: H. argutifolius, H. foetidus, H. niger and H. orientalis. The plant material was introduced in vitro from axillary buds. A Murashige and Skoog (MS)—based medium (Murashige and Skoog 1962) was used supplemented with 2% (w/v) sucrose, 2-isopentenyladenine (2-iP) and 6-benzylaminopurine (BA). Multiplication rates depended on the genotype and varied from 1.3 for H. foetidus till 3.8 for H. niger. The first results showed that the rooting phase could be done ex vitro. Rooting was induced by a drench for one week in a solution of indole-3-butyric acid (IBA -3 mg l⁻¹) and 1-naphthaleneacetic acid (NAA-1 mg l⁻¹) at 5°C.     

Methods for rapid screening and isolation of bacteria producing acidic lipase: feasibility studies and novel activity assay protocols

Acidic lipase finds its commercial values in medical applications and bioremediation of food wastes. In this work, approaches for rapid screening of lipase-producing bacteria were developed and the feasibility assessment of the screening methods was performed. From food waste samples, the proposed screening procedures allowed isolation of sixteen pure bacterial strains expressing higher lipase activity at acidic pH (pH 6.0) than at alkaline pH (pH 9.0). To enhance the accuracy of lipase activity determination under acidic conditions, a novel assay procedure was also developed by deactivating lipase activity by microwave treatment prior to back titration. This additional step could minimize interferences arising from residual lipase activity during conventional direct back-titration methods in measuring lipase activity at acidic pH. Using the four strategies proposed in this work, the best acidic-lipase-producing isolate was obtained by strategy C (SSC) and was identified as Aeromonas sp. C14, displaying an optimal lipase activity of 0.7 U/ml at an acidic pH of 6.0.     

Plant-growth regulators from common starfish (<Emphasis Type="Italic">Asterias amurensis</Emphasis> Lütken) waste

Starfish waste has been shown to be an effective compost material not only in the promotion of plant growth but also in terms of having insecticidal activity. In the present study, plant growth regulation by chemicals from starfish was examined. The aqueous fraction from a hot water extract of the starfish Asterias amurensis Lütken showed plant-growth activity, while the aqueous fraction from a methanol extract inhibited growth of Brassica campestris. The lipophilic fraction from the methanol extract also exhibited a plant growth-promoting effect. The active components from each extract were identified. Asterubine from the hot water extract promoted plant growth. A ceramide from the lipophilic fraction showed root growth promoting effect, and three glucocerebrosides had promotive effects on the entire plant. Asterosaponins were identified as the main growth inhibitors in the aqueous fraction of the methanol extract. These active compounds from starfish waste could be analyzed as potential plant growth regulators in agricultural applications in the future.     

A neural network study on the dynamic identification of a fermentation system

The objective of this paper is to propose neural networks for the study of dynamic identification and prediction of a fermentation system which produces mainly 2,3-butanediol (2,3-BDL). The metabolic products of the fermentation, acetic acid, acetoin, ethanol, and 2,3-BDL were measured on-line via a mass spectrometer modified by the insertion of a dimethylvinylsilicone membrane probe. The measured data at different sampling times were included as the input and output nodes, at different learning batches, of the network. A fermentation system is usually nonlinear and dynamic in nature. Measured fermentation data obtained from the complex metabolic pathways are often difficult to be entirely included in a static process model, therefore, a dynamic model was suggested instead. In this work, neural networks were provided by a dynamic learning and prediction process that moved along the time sequence batchwise. In other words, a scheme of two-dimensional moving window (number of input nodes by the number of training data) was proposed for reading in new data while forgetting part of the old data. Proper size of the network including proper number of input/output nodes were determined by trained with the real-time fermentation data. Different number of hidden nodes under the consideration of both learning performance and computation efficiency were tested. The data size for each learning batch was determined. The performance of the learning factors such as the learning coefficient η and the momentum term coefficient α were also discussed. The effect of different dynamic learning intervals, with different starting points and the same ending point, both on the learning and prediction performance were studied. On the other hand, the effect of different dynamic learning intervals, with the same starting point and different ending points, was also investigated. The size of data sampling interval was also discussed. The performance from four different types of transfer functions, x/(1+|x|), sgn(x)·x ²/(1+x ²), 2/(1+e ^{? x} )?1, and 1/(1+e ^{? x} ) was compared. A scaling factor b was added to the transfer function and the effect of this factor on the learning was also evaluated. The prediction results from the time-delayed neural networks were also studied.     

Linkages between seagrass,mangrove and saltmarsh as fish habitat in the Botany Bay estuary,New South Wales

Shallow-water vegetated estuarine habitats, notably seagrass, mangrove and saltmarsh, are known to be important habitats for many species of small or juvenile fish in temperate Australia. However, the movement of fish between these habitats is poorly understood, and yet critical to the management of the estuarine fisheries resource. We installed a series of buoyant pop nets in adjacent stands of seagrass, mangrove and saltmarsh in order to determine how relative abundance of fishes varied through lunar cycles. Nets were released in all habitats at the peak of the monthly spring tide for 12 months, and in the seagrass habitat at the peak of the neap tide also. The assemblage of fish in each habitat differed during the spring tides. The seagrass assemblage differed between spring and neap tide, with the neap tide assemblage showing greater abundances of fish, particularly those species which visited the adjacent habitats when inundated during spring tides. The result supports the hypothesis that fish move from the seagrass to the adjacent mangrove and saltmarsh during spring tides, taking advantage of high abundances of zooplankton, and use seagrass as a refuge during lower tides. The restoration and preservation of mangrove and saltmarsh utility as fish habitat may in some situations be linked to the proximity of available seagrass.