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

Twenty-four experimental Cheddar cheeses were produced using 5 renneting enzymes and stored at 4 degrees 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. (c) 2005 Elsevier Ltd. All rights reserved.