Prediction of maturity and sensory attributes of Cheddar cheese using near-infrared spectroscopy

Abstract

Abstract Twenty-four experimental Cheddar cheeses were produced using 5 renneting enzymes and stored at 4 °C for up to 9 months. At 2, 4, 6 and 9 months, cheeses were analysed for sensory attributes (“crumbly”, “fragmentability”, “firmness”, “rubbery”, “gritty/grainy”, “moist”, “chewy”, “mouthcoating”, “greasy/oily”, “melting” and “massforming”) by a trained panel of 10 assessors. Near-infrared (750–2498 nm) reflectance spectra were recorded contemporaneously. Predictive models for the sensory attributes and age (months) were developed by partial least-squares (PLS) regression; raw, derivatised and scatter-corrected spectral data were investigated. As a general rule, the most accurate models were produced by spectral data in the range 750–1098 nm after a 2nd derivatisation step. Age was predicted with a root mean square error of cross-validation (RMSECV) equal to 0.61; sensory attributes successfully modelled and their respective RMSECV values were “crumbly” (2.3), “rubbery” (3.4), “chewy” (4.0), “mouthcoating” (5.0) and “massforming” (4.1). These models are sufficiently accurate to be industrially useful.