Abstract
This work points out the use of experimental design for peulh cheese making process optimisation. Peulh cheese, a milk coagulum, well-known in certain West African countries (e.g. Benin), is unfortunately ill-known in Côte d’Ivoire (Ivory Coast). However, it could be a transformation way of milk. This work consisting in use of a central composite design enables the determination of optimal process conditions concerning: leaf extract volume added (7 mL), heating temperature (84.12°C) and heating time (15 min). When these optimal conditions are reached, the maximal value for process yield is 58.88 %, the minimal value for TCB is 6.40 min and the value found for totalsolids is 42.75 %. Furthermore, this work has showed that the experimental design is more suitable than the traditional study method called “one factor at a time”. @JASEM
Highlights
Since two decades, the Côte d’Ivoire (Ivory Coast), has initiated an intensive development program, in the purposes of (DCGTX and MINAGRA, 1988):
The traditional technique of cheese making well known in the West African region, but few known in Côte d’Ivoire, appears to be the appropriate solution to save milk produced by farmers, especially in rainy period (Kees et al, 1996)
THEORY The experimental design is a statistical tool which purpose is to point out relationships that can exist between a dependent variable and factors [Massart et al, 1988; Cochran and Cox, 1992)
Summary
The Côte d’Ivoire (Ivory Coast), has initiated an intensive development program, in the purposes of (DCGTX and MINAGRA, 1988):. THEORY The experimental design is a statistical tool which purpose is to point out relationships that can exist between a dependent variable (response) and factors (parameters) [Massart et al, 1988; Cochran and Cox, 1992). It consists in studying these relationships by varying together all factors under study, and to appreciate the effect of these variations on the response. The most used in this group is the central composite design whose composite matrixes enable the estimation of second degree polynomial
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