Infrared guided smart food formulation: an innovative spectral reconstruction strategy to develop anticipated and constant apple puree products

Abstract

An innovative chemometric method was developed to exploit visible and near-infrared (Vis-NIR) spectroscopy to guide food formulation to reach the anticipated and constant quality of final products. First, a total of 671 spectral variables related to the puree quality characteristics were identified by spectral variable selection methods. Second, the concentration profiles from multivariate curve resolution-alternative least squares (MCR-ALS) made it possible to reconstruct the identified spectral variables of formulated purees. Partial least square based on the reconstructed Vis-NIR spectral variables was evidenced to predict the final puree quality, such as a* values (RPD = 3.30), total sugars (RPD = 2.64), titratable acidity (RPD = 2.55) and malic acid (RPD = 2.67), based only on the spectral data of composed puree cultivars. These results open the possibility of controlling puree formulation: a multiparameter optimization of the color and taste of final puree products can be obtained using only the Vis-NIR spectral data of single-cultivar purees.

Keywords

Malus domestica Borkh. / Puree processing / Formulation guidance / Spectral variable selection.

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The authors thank Patrice Reling, Barbara Gouble, Marielle Boge, Caroline Garcia and Gisèle Riqueau (INRAE, SQPOV unit) for their technical help. This work was supported by the 'Interfaces' project, an Agropolis Foundation Flashship project publicly funded through the ANR (French Research Agency) under the 'Investissements d'Avenir' program (ANR-10-LABX-01-001 Labex Agro, coordinated by Agropolis Fondation), the National Natural Science Foundation of China (NSFC, 32302204), and Research Startup Foundation of Nanjing Agricultural University (No. 804120).

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2024 Editorial Office of Food Innovation and Advances