“…A high number of variables, with respect to the number of data samples, are also permissible in PLS, which can result in the modelling of noise for LLR (wise and Gallagher, 1996). In summary, PLS is capable of producing robust, effective models, despite operational data limitations, for example, imprecise measurements and missing data (Oliveira-Esquerre, 2004). The ability to predict dependent data values, especially in the case of product quality data, which is often measured infrequently, is useful in process monitoring (MacGregor, 2005).…”