Rapid Evaporative Ionisation Mass Spectrometry fingerprinting can discriminate lamb meat due to different ageing methods and levels of dehydration.

Dry-ageing is a technique for developing characteristic dry-aged flavour through the interplay of dehydration, lipid oxidation and microbial activities. In this study, we tested the hypothesis that the extent of drying influences the metabolite profile and the final flavour of lamb using an "Age-and-Dry" regime; and that Rapid Evaporative Ionisation Mass Spectrometry (REIMS) fingerprinting can be used to discriminate the metabolic fingerprints of lambs due to ageing methods and dehydration levels. Lamb loins (n = 60) were dehydrated with low (12%), medium (17%) and high (22%) weight losses and compared with the wet-aged equivalents using REIMS and evaluated by 12-member sensory panel. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) models based on 1400 tentatively identified m/z features were obtained for ageing methods (Q2 > 0.95) and dehydration levels (Q2 > 0.82) with high discrimination accuracy. Increased concentrations of dipeptides and metabolites associated with energy metabolism were observed in aged-and-dried lamb meat which supports the umami and savoury taste perceived by the sensory panel. A reduced concentration of polyunsaturated fatty acids with more aldehydes was observed in aged-and-dried lamb meat contributing to the nutty, roasted, and fatty flavour notes detected by the sensory panellists in these samples compared to the wet-aged. SIGNIFICANCE: Outcomes of this study demonstrated that REIMS can be used to accurately discriminate between different ageing methods and dehydration levels of meat, and the compounds that are associated with lamb flavour. The implications of this finding include: (1) the metabolite concentrating effect of dehydration and the associated effect on aged lamb flavour determined in this study could be used to tailor the processing of dry-aged lamb to deliver specific flavour outcomes in an industrial setting; (2) the ability of REIMS to rapidly detect differences in the aged lamb flavour due to dehydration effect would improve the quality of dry-aged meat and the efficiency with which it can be industrially produced. Thus, REIMS can be used as a rapid authentication and quality prediction tool for different ageing regimes and flavour for the meat industry.

Comparative evaluation of miniaturized and conventional NIR spectrophotometer for estimation of fatty acids in cheeses.

The miniaturization of near-infrared spectrometers has been growing rapidly. Several designs are now available, but there is a lack of understanding of how spectral data from these designs are affected by complex matrices and what are the limitations when compared to established systems. This study compares a popular miniaturized NIR device based on Hadamard-transform spectrometer (named miniaturized NIR) with a system based on dispersive spectrometer (named handheld-NIR) to assess: 1) their predictive performance; 2) the effect of a complex matrix on the performance, and 3) ability to discriminate multiples compounds in that matrix. The devices were challenged with a wide range of cheese types (n = 36) from different species (cow, goat, ewe and buffalo), brands (n = 30), countries of origin (n = 9) and with a broad range of cheese matrices (soft, fresh, semi-hard, hard and aged) to predict fat composition. Spectra were collected non-invasively with no sample preparation. Three wavelength ranges from handheld NIR were compared to miniaturized NIR based on two modelling approaches were used: a linear (Partial Least Square - PLS) and a non-linear (Support Vector Machine - SVM). The important wavelengths for each model were identified and used to assess the ability of the spectral data to differentiate among fatty acids. The highest prediction performance was observed for saturated fatty acids (C4.0, C14.0, C15.0 C16.0, total SCF and total SFA) with the RPDEXT-VAL for the external validation dataset presenting values higher than 3 and the coefficient of determination for the external validation dataset (R2EXT-VAL) higher than 0.89, mostly for SVM models. The sum of fatty acids also shows good prediction performance with RPDEXT-VAL higher than 3 and R2EXT-VAL higher than 0.89. Models with RPDEXT-VAL between 2 and 3 includes: C6.0; C17.0; C18.0; C10.1; C16.1; C17.1; iso.C15.0; iso.C.16; iso.C17; C18.1.c11; C18.1.c9; anteiso C17; total MUFA; and total BCFA. The cheese matrix affected the linearity between spectral data and fatty acids concentration requiring a more complex model (SVM), but this effect was not enhanced by the instrument type. It was shown that the spectral information allows discrimination among fatty acids and this ability was not affected by the type of instrument. These findings demonstrated that the miniaturized NIR can be directly applied to a cheese matrix to monitor fatty acid composition with results equivalent to an optical-based design.