Authentication of chickpea flour using spectral mixture algorithms based on NIR spectra and chemometrics

• Grant number: 25/09896-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Agronomical Sciences - Food Science and Technology - Food Engineering
• Principal Investigator: Douglas Fernandes Barbin
• Grantee: João Victor Benedetti Pereira
• Host Institution: Faculdade de Engenharia de Alimentos (FEA). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 23/07385-7 - Applications of artificial vision for quality monitoring of emerging foods, AP.R

Abstract

The continuous growth of vegetarianism and veganism has driven the demand for legumes, vegetables, and oilseeds, increasing the consumption of ingredients such as chickpea flour, which has a higher added value compared to other plant-based protein sources. This scenario, combined with advancements in innovative technologies like 3D food printing, facilitates food fraud involving low-cost and easily manipulated ingredients, such as cassava starch. However, traditional methods used in the industry for detecting adulteration are generally destructive and time-consuming, limiting their use for real-time analysis. Near-infrared (NIR) spectroscopy combined with portable devices emerges as a promising alternative for quality control of chickpea flour. Therefore, this project proposes to investigate the application of near-infrared (NIR) spectroscopy, associated with a portable spectrometer and spectral unmixing algorithms, using chemometric tools such as Multivariate Curve Resolution (MCR), Principal Component Analysis (PCA), and Partial Least Squares Discriminant Analysis (PLS-DA), to authenticate chickpea flour samples adulterated with cassava starch. The proposed approach aims to provide more sustainable and intelligent routine methods capable of ensuring consumers' legal rights, contributing to the advancement of Process Analytical Technologies (PAT) in scientific and industrial sectors.