Simplification of a haemolytic micromethod for toxic saponin quantification in alfalfa

A simplification of a haemolytic micromethod is presented. In the orginal method, alfalfa (<i>Medicago media</i> Pers.) leaf sap is spotted on the plate covered with a blood-gelatine suspension. In the presented method, the mashed alfalfa pulp is used instead of sap. Due to saponin diffusion and the reaction with erythrocytes, a haemolytic ring appears, which has a width proportional to the concentration of toxic saponins. It is shown that the width of haemolytic ring does not depend on the sample weight ranging from 20 to 100 mg. This allows for the omission of laborious sap pressing and sample quantification. Individual alfalfa plants with different saponin contents were tested using leaf sap and leaf pulp for analyses. Good agreement was found with sap and leaf pulp methods. The correlation obtained by both methods was high, <i>r</i> = 0.87. The modified method requires only a small amount of plant material and makes the analyses of large numbers of individual plants per day possible. The method is especially recommended for breeding purposes.

Influence of sample quantification and taxonomic resolution on the ordination of macroinvertebrate communities from running waters in Victoria, Australia

The influence of sample quantification and taxonomic resolution on the ordination of macroinvertebrate communities from nine Victorian rivers was examined by progressively reducing the degree of detail in the original data (species level, quantitative). Five additional data sets were created that consisted of binary (presence or absence) data on species, quantitative or binary data on families, and quantitative data on PET (plecopteran, ephemeropteran and trichopteran) species or families. Ordinations were performed with detrended correspondence analysis (DCA) and semi-strong hybrid multi-dimensional scaling (SSH). With both ordination techniques, the ordinations of each data set (including the original) revealed the same three underlying gradients. An altitudinal gradient consistently achieved the highest correlations with the ordinations (r = 0.71-0.93), followed by a substratum gradient (r = 0.50-0.88) and a combined pH and conductivity gradient (r = 0.47-0.76). Each of the five less-complete data sets thus provides an adequate degree of detail for ordination analysis and subsequent interpretation of environmental gradients.