Sequential analysis for testing quality standard of fish ham and sausage

Fish sausages are finely ground fish flesh, either of a single species or mixed, homogenised with starch, sugar, fat, spices and preservatives, generally filled in cylindrical synthetic or natural casings and pasteurised. Similar products containing small pieces of quality fish and lard are termed "fish ham". They are highly relished products in Japan, annual consumption exceeding 2 lakh tones. Preliminary studies have shown that they can catch a lucrative market in our country. However, being a pasteurised product which is often consumed as such without any further cooking, strict quality control measures have to be enforced so as to avoid food poisoning hazards. Besides physical characteristics like absence of damages, pin-holes, curliness and air pockets as well as jelly strength, texture and flavour, chemical characteristics like pH and acid values, moisture, carbohydrate and fat contents and volatile bases have to be assessed. A very important test that has to be carried out along with the above, before passing a lot for free distribution is the bacteriological examination to avoid the presence of pathogenic organisms.

A programme to carry out analysis of variance: two-way classification on Micro 2200

A brief description is given of a program to carry out analysis of variance two-way classification on MICRO 2200, for use in fishery data processing.

On the problem of nonadditivity in two-way analysis of variance of data for comparing the efficiency of fishing gears

To bring out the relative efficiency of various types of fishing gears, in the analysis of catch data, a combination of Tukey's test, consequent transformation and graphical analysis for outlier elimination has been introduced, which can be advantageously used for applying ANOVA techniques, Application of these procedures to actual sets of data showed that nonadditivity in the data was caused by either the presence of outliers, or the absence of a suitable transformation or both. As a corollary, the concurrent model: X sub(ij) = µ + α sub(i) + β sub(j) + λ α sub(i) β sub(j) + E sub(ij) adequately fits the data.