Rapid quantification of phenolic content and antioxidant activity in cookies produced with amazonian palm fruit flour using Micro-NIR spectrometer and PLS regression

Author(s)

Santos, Yves Jose de Souza ; Silva, Ana Carolina Almeida ; de Carvalho, Rosemary Aparecida ; Colnago, Luiz Alberto ; Vanin, Fernanda Maria

• Document type: Journal article
• Source: Microchemical Journal; v. 195, p. 7-pg., 2023-09-28.

Abstract

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 po-tential 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 coef-ficient 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 re-sults, 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. (AU)

• FAPESP's process: 13/12693-0 - Study of functional French bread producing during the baking process: a local study to better understanding the technological and sensory properties of final product
• Grantee: Fernanda Maria Vanin
• Support Opportunities: Regular Research Grants
• FAPESP's process: 19/11479-1 - Inclusive and efficient food systems: effect of process on the functionality of alternative flours (chemical, structural and product digestibility properties)
• Grantee: Yves José de Souza Santos
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 21/12270-9 - Homemade and industrialized baby food: a theoretical and practical assessment of quality, safety, classification and consumer perception aspects
• Grantee: Fernanda Maria Vanin
• Support Opportunities: Regular Research Grants
• FAPESP's process: 21/12694-3 - Applications of NMR and infrared spectroscopies in the non-destructive analysis of products and agroindustrial processes
• Grantee: Luiz Alberto Colnago
• Support Opportunities: Regular Research Grants
• FAPESP's process: 18/03324-5 - Sustainable food production: a case study of Brazilian orange juice industry waste application.
• Grantee: Fernanda Maria Vanin
• Support Opportunities: Regular Research Grants