Abstract
Partial least squares regression modeling (PLSR) was used to elucidate the relationship and predictability among the chemical parameters, the GC–MS data and electronic nose responses for controlled oxidation of tallow. Models for predicting chemical parameters changes during controlled oxidation from electronic nose data were estimated by projection of test samples onto calibration models based on PLSR. The results showed that peroxide value (PV) and p-anisidine value (p-AV) were significantly well predicted by the electronic nose responses, whereas acid value (AV) was found fairly well predicted only for mildly oxidized tallow. Overall this study gave evidence of the electronic nose system to be a relevant device for future at- or on-line implementation in oxidation control of tallow for preparing fat flavour.
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