Abstract: This paper analyses the effect of fertilizer (organic and
inorganic) in the growth of tilapia. An experiment was implemented
in the Aquapesca Company of Mozambique; there were considered
four different treatments. Each type of fertilizer was applied in two of
these treatments; a feed was supplied to the third treatment, and the
fourth was taken as control. The weight and length of the tilapia were
used as the growth parameters, and to measure the water quality, the
physical-chemical parameters were registered. The results show that
the weight and length were different for tilapias cultivated in different
treatments. These differences were evidenced mainly by organic and
feed treatments, where there was the largest and smallest value of
these parameters, respectively. In order to prove that these differences
were caused only by applied treatment without interference for the
aquatic environment, a Fisher discriminant analysis was applied,
which confirmed that the treatments were exposed to the same
environment condition.
Abstract: Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.