Partial Least Squares Regression

A procedure that has come to the fore in recent years is partial least squares regression analysis (PLS). The calculation and functioning have been described (26). Assume one has two blocks of variables: sensory and instrumental. PSC searches for a few latent orthogonal variables (factors) to describe the interrelationships between the two blocks of variables (27). It extracts from the regressor matrix (ie, the instrumental block), those factors relevant to prediction of the sensory parameters of the food. The procedure may be looked upon as a combination of PCA and multiple linear regression performed simultaneously on the latent variables. Several research publications are available that detail applications in sensory-instrumental correlation (26,27).

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