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  • Rapid quantification of phe...
    José de Souza Santos, Yves; Carolina Almeida Silva, Ana; Aparecida de Carvalho, Rosemary; Alberto Colnago, Luiz; Maria Vanin, Fernanda

    Microchemical journal, December 2023, 2023-12-00, Letnik: 195
    Journal Article

    Display omitted •Pupunha flour is a promising alternative for cookie production.•Micro-NIR obtained excellent predictions for phenolic compound content.•Micro-NIR represents a great advantage when applied in industrial environments.•Even with narrow spectral range, excellent results were obtained.•Pupunha flour is an alternative product aimed at the celiac public. There are several reports of the potential benefits of phenolic compound (PC) in food products, due to their antioxidant activities (AC). However, in recent years, new research results have demonstrated that PC has potential health risks due to the reduction in absorption of protein nutrients and cytotoxic effects. The PC and AC quantifications are laborious and time-consuming methods, therefore it is necessary to develop simple, fast and precise method to determine these parameters, not only in the raw materials, but also in food products. Therefore, this study focused on the potential of Micro-NIR spectrometer data modeled with partial least square regression to predict PC and AC in processed food (cookies) prepared with peach palm (PP), that is rich in PC. The cookies were prepared using 12.5 to 100 % of PP flour in substitution to wheat flour (WF). The NIR model for AC, determined by the ferric reducing antioxidant power (FRAP) method, shows R2cv = 0.93 (regression coefficient of cross-validation step); RMSECV = 0.05; R2p = 0.87 (regression coefficient of prediction step); RMSEP = 0.04; RPD = 2.73, and by 2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) radical capture (ABTS) exhibit R2cv = 0.83; RMSECV = 3.72; R2p = 0.70; RMSEP = 4.12; RPD = 1.76, and for PC, determined by Folin-Ciocalteu, shows R2cv = 0.86; RMSECV = 0.44; R2p = 0.80; RMSEP = 0.43; RPD = 2.04. These excellent results, mainly for FRAP and PC, demonstrated that portable NIR spectrometers could be a fast, simple and reliable method to predict PC and AC in cookies prepared with different proportion of PP flour and WF. Similar models can also be developed to predict PC and AC in other food products.