# Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Combined with Chemometrics for Protein Profiling and Classification of Boiled and Extruded Quinoa from Conventional and Organic Crops

**Authors:** Rocío Galindo-Luján, Laura Pont, Fredy Quispe, Victoria Sanz-Nebot, Fernando Benavente

PMC · DOI: 10.3390/foods13121906 · Foods · 2024-06-17

## TL;DR

This study uses a fast method to analyze quinoa proteins and distinguish between organic and conventional, as well as boiled and extruded, quinoa samples.

## Contribution

A novel MALDI-TOF-MS and chemometrics approach for protein-based classification of quinoa based on farming and processing methods.

## Key findings

- 49 proteins were detected, with 31 tentatively identified, from quinoa protein extracts.
- PLS-DA models reliably classified quinoa samples by farming and processing conditions.
- The method effectively traces agricultural origins and processing treatments of quinoa.

## Abstract

Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry.

## Full-text entities

- **Species:** Chenopodium quinoa (quinoa, species) [taxon 63459]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC11203106/full.md

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11203106/full.md

## References

51 references — full list in the complete paper: https://tomesphere.com/paper/PMC11203106/full.md

---
Source: https://tomesphere.com/paper/PMC11203106