Two New Approaches for Examining Multivariate Aquaculture Growth

Two new approaches foi the multivariate analysis of fish growth in aquaculture are presented. The first of these two approaches, the "extended Bayley plot" is a multiple regression expansion of an existing bivariate method, which permits the inclusion of environmental and treatment variables when estimating the parameters Lm and K of the von Bertalanflj. growth function, given precise measurements of fish length and weight at different ages. The derived regression model which must be base'd on a Type 11, or "functional" regression, can be used to predict fish growth under anticipated mnditions and thus identify appropriate farm management options. The differences of this method with the related 'extended Gulland-and-Holt plot" are discussed. The semnd approach perlains to the application of "path" (or "causal*) analysis in the context of aquaculture. Causal path diagrams, based on either extended 'Bayley" or extended "Gulland-and-Holt" plots, can be used to put into a rigorous framework hypothesized networks of interacting variables controlling, for example, tilapia growth in ponds. Both methods were applied to a dataset based on pond growth experiments with Nile tilapia Oreochromis niloticus, conducted in Mufioz, Philippines.