Amino acid profile of the quinoa (Chenopodium quinoa Willd.) using near infrared spectroscopy and chemometric techniques

• Published in: Journal of cereal science Vol. 60; no. 1; pp. 67 - 74
• Main Authors: Escuredo, Olga, González Martín, M. Inmaculada, Wells Moncada, Guillermo, Fischer, Susana, Hernández Hierro, José Miguel
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2014
• Subjects: Amino acids; Chenopodium quinoa; Modified partial least squares regression; Near infrared spectroscopy; Near infrared spectroscopy; Amino acids; Modified partial least squares regression; Chenopodium quinoa
• ISSN: 0733-5210; 1095-9963
• DOI: 10.1016/j.jcs.2014.01.016

The high content of amino acids of the quinoa, especially essential amino acids (higher than other cereals) makes a food increasingly demanded by consumers. A total of twelve amino acids (arginine, cystine, isoleucine, leucine, lysine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine and valine) were analyzed in quinoa samples from Chile by near infrared spectroscopy (NIR) with direct application to the samples of a remote fiber-optic reflectance probe. The calibration results using modified partial least squares (MPLS) regression satisfactorily allowed the determination of the concentrations of this amino acid group with high multiple correlation coefficients (RSQ = 0.97–0.71) and low standard prediction errors (SEPC = 0.07–0.20). The prediction capacity (RPD) for the arginine, the cystine, the isoleucine, the lysine, the serine, the threonine, the tryptophan, the tyrosine and the valine ranged between 2.6 and 5.2, for the rest of amino acids were higher to 1.8, indicating that the NIRS equations obtained were applicable to unknown samples. It has confirmed that NIRS technology is a method that may be useful to replace the traditional methods for routine analysis of some amino acids. •Amino acid composition in quinoa using NIR spectroscopy was evaluated.•The use of chemometric techniques and NIR data allowed the estimation of amino acids.•Results were good in the prediction capacity for the most amino acids in quinoa.•NIRS is capable of predicting chemical characteristics without destroying sample.