Nil Caballero Alcazar

@ub.edu

Research Assistant at Faculty of "Ciències de la Terra" at "Mineralogia, Petrologia i Geologia Aplicada" department
MAIMA

Nil Caballero Alcazar


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https://researchid.co/nilcaballero
Analytical Chemist.
PhD student at MAIMA.

EDUCATION

2023 Master in Analytical Chemistry
Department of Chemical Engineering and Analytical Chemistry
University of Barcelona, Barcelona

2022 Bachelor’s Degree in Chemistry
University of Barcelona, Barcelona

RESEARCH, TEACHING, or OTHER INTERESTS

Aquatic Science, Ecology, Evolution, Behavior and Systematics
1

Scopus Publications

Scopus Publications

  • Fingerprinting of quinoa grain protein extracts by liquid chromatography with spectrophotometric detection for chemometrics discrimination
    Rocío Galindo-Luján, Nil Caballero-Alcazar, Laura Pont, Victoria Sanz-Nebot, Fernando Benavente
    Lwt, 2023
    Quinoa (Chenopodium quinoa Willd.) grain is gaining great popularity worldwide because it is a rich source of nutrients, bioactive compounds, complete essential amino acids, and high-quality proteins. The demand for quinoa-based products is on the rise, which makes them prone to adulteration with less expensive cereals. In this study, we described a rapid and simple procedure for fingerprinting of quinoa grain protein extracts based on the combination of liquid chromatography with ultraviolet absorption diode array detection (LC-UV-DAD) and chemometrics. First, we developed a novel LC-UV-DAD method to obtain distinctive multiwavelength chromatographic profiles of protein extracts from various commercial quinoa grains, which encompass different quinoa varieties sold as black, red, white (from Peru), and royal (white from Bolivia). Then, the components of the LC-UV-DAD fingerprints were deconvoluted by multivariate curve resolution alternating least squares (MCR-ALS), and principal component analysis (PCA) followed by partial least squares discriminant analysis (PLS-DA) were applied to efficiently discriminate the commercial quinoa grains according to their differential composition. The chemometrics-assisted LC-UV-DAD fingerprinting methodology demonstrated its potential to rapidly and reliably discriminate quinoa grains according to the differential composition of their protein extracts and it may be applied in food quality and food fraud control.

INDUSTRY EXPERIENCE

CCiTUB-Senior Laboratory Technician –UCGEMA- Organic Elemental Analysis Laboratory (1 year).

Agustí Y Masoliver, S.A.- Laboratory Technician (1 year).