Predictable puree: a smart food formulation approach
Apple puree is a major market player, integral to various products, yet its quality varies with the diversity of apple cultivars and processing conditions. For fruit processors, the ever-increasing variability of raw fruits means that their empirical know-how may not be sufficient to produce expected and constant final purees. Recently, advances in visible and near-infrared (Vis-NIR) spectroscopy have shown potential in predicting puree quality by analysing the spectral data of apple varieties.
Food Innovation and Advances published an online paper entitled ‘Infrared guided smart food formulation: an innovative spectral reconstruction strategy to develop anticipated and constant apple puree products’ on 19 March 2024. The paper proposes a smart food formulation model to optimise puree formulation, aiming to reach the anticipated and constant quality of final products.
This study describes an innovative concept concerning the feasibility of using infrared spectroscopy to drive the formulation of apple purees issued from the mix of single-cultivar purees. An innovative chemometric method based on multivariate curve resolution-alternative least squares (MCR-ALS) coupled with the spectra of single-cultivar purees was firstly tested to reconstruct the spectra of formulated purees.
PLS regression models coupled with selected Vis-NIR spectral variables demonstrated good prediction abilities for colour parameters, viscosity (η50), total sugar content (TSC), titratable acidity (TA), pH, glucose and malic acid content in formulated purees. PLS models were developed using the reconstructed Vis-NIR spectra of all formulated purees and predicted their a* colour value (Rp2 = 0.92, PRD = 3.30), TSC (Rp2 = 0.86, PRD = 2.64), TA (Rp2 = 0.85, PRD = 2.55) and malic acid (Rp2 = 0.86, PRD = 2.67). Although prediction results for TSC and TA based on reconstruction spectrum were less accurate than direct spectral analyses, these results still opened a potential way to directly estimate the variation of sweetness, acidity and colouration for formulated purees based only on the selected Vis-NIR spectral variables of single-cultivar purees.
This is claimed to be the first report demonstrating that Vis-NIR spectroscopy has the potential to guide puree formulation: a multiparameter optimisation of texture and taste (viscosity, colour, sugars and acids) of final apple purees can be obtained using only the spectral data of single-cultivar purees. The successful application of this spectral reconstruction strategy offers new insights into optimising puree formulation for consistent quality, marking an advancement in the field of food technology. This chemometric approach can not only enhance the predictive modelling of apple puree characteristics but also opens avenues for its application in smart food formulations.
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