El editor solo permite decargar el artículo en su versión post-print desde el repositorio. Por favor, si usted posee dicha versión, enviela a
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor


Quinoa flour has been receiving an increasing attention as a substitute for wheat flour in bread formulations due to immuno-nutritional features. This growing interest in quinoa has increased the demand and consequently the prices, being a target for possible adulterations with cheaper cereals. Fourier transform Mid-infrared spectroscopy (FT-MIR) was used in the present work as a fingerprinting technique to detect the presence of three adulterants (soybean, maize and wheat flours). Partial least squares discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) models were used to classify pure from adulterated samples. 414 samples were measured, including pure quinoa flour, pure adulterant flours and adulterated quinoa flours using three different proportions (10, 5 and 1% w/w). PLS-DA showed better classification results than SIMCA, with error rates from 2 to 8% for the three strategies used to detect the presence of adulterants. © 2018 Elsevier Ltd


Documento: Artículo
Título:Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods
Autor:Rodríguez, S.D.; Rolandelli, G.; Buera, M.P.
Filiación:Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Buenos Aires, Argentina
CONICET – Universidad de Buenos Aires, Instituto de Biodiversidad y Biología Experimental y Aplicada (IBBEA), Buenos Aires, Argentina
Palabras clave:Chemometric methods; FT-IR; PLS-DA; Quinoa flour adulteration; SIMCA; Discriminant analysis; Infrared spectroscopy; Least squares approximations; Water analysis; Chemometric method; Classification results; Fingerprinting techniques; Fourier transform mid infrared spectroscopy; Partial least squares discriminant analyses (PLSDA); PLS-DA; Quinoa flour adulteration; SIMCA; Chromatography; article; chemometric analysis; Chenopodium quinoa; discriminant analysis; Fourier transformation; infrared spectroscopy; maize; major clinical study; nonhuman; partial least squares regression; soybean; wheat flour; analysis; chemistry; Chenopodium quinoa; discriminant analysis; flour; food contamination; food quality; information science; infrared spectroscopy; Chenopodium quinoa; Discriminant Analysis; Flour; Food Contamination; Food Quality; Informatics; Spectroscopy, Fourier Transform Infrared
Página de inicio:392
Página de fin:401
Título revista:Food Chemistry
Título revista abreviado:Food Chem.


  •; Aluwi, N.A., Murphy, K.M., Ganjyal, G.M., Physicochemical characterization of different varieties of Quinoa (2017) Cereal Chemistry Journal, 94 (5), pp. 847-856
  • AOAC, Official Methods of Analysis of AOAC INTERNATIONAL (2016), 20th Ed. AOAC INTERNATIONAL Gaithersburg, MD, USA; Ballabio, D., Consonni, V., Classification tools in chemistry. Part 1: Linear models. PLS-DA (2013) Analytical Methods, 5 (16), p. 3790
  • Ballabio, D., Grisoni, F., Todeschini, R., Multivariate comparison of classification performance measures (2018) Chemometrics and Intelligent Laboratory Systems, 174, pp. 33-44
  • Berrueta, L.A., Alonso-Salces, R.M., Héberger, K., Supervised pattern recognition in food analysis (2007) Journal of Chromatography A, 1158 (1-2), pp. 196-214
  • Botelho, B.G., Reis, N., Oliveira, L.S., Sena, M.M., Development and analytical validation of a screening method for simultaneous detection of five adulterants in raw milk using mid-infrared spectroscopy and PLS-DA (2015) Food Chemistry, 181, pp. 31-37
  • Cocchi, M., Foca, G., Lucisano, M., Marchetti, A., Pagani, M.A., Tassi, L., Ulrici, A., Classification of cereal flours by chemometric analysis of MIR Spectra (2004) Journal of Agricultural and Food Chemistry, 52 (5), pp. 1062-1067
  • Collins, E.J.T., Food adulteration and food safety in Britain in the 19th and early 20th centuries (1993) Food Policy, 18 (2), pp. 95-109
  • Ellis, D.I., Brewster, V.L., Dunn, W.B., Allwood, J.W., Golovanov, A.P., Goodacre, R., Fingerprinting food: Current technologies for the detection of food adulteration and contamination (2012) Chemical Society Reviews, 41 (17), p. 5706
  • Ferreira, D.S., Pallone, J.A.L., Poppi, R.J., Direct analysis of the main chemical constituents in Chenopodium quinoa grain using Fourier transform near-infrared spectroscopy (2015) Food Control, 48, pp. 91-95
  • Filho, A.M.M., Pirozi, M.R., Borges, J.T.D.S., Pinheiro Sant'Ana, H.M., Chaves, J.B.P., Coimbra, J.S.D.R., Quinoa: Nutritional, functional, and antinutritional aspects (2017) Critical Reviews in Food Science and Nutrition, 57 (8), pp. 1618-1630
  • González-Muñoz, A., Montero, B., Enrione, J., Matiacevich, S., Rapid prediction of moisture content of quinoa (Chenopodium quinoa Willd.) flour by Fourier transform infrared (FTIR) spectroscopy (2016) Journal of Cereal Science, 71, pp. 246-249
  • Granato, D., Putnik, P., Kovacevic, D.B., Sousa Santos, J., Calado, V., Silva Rocha, R., Pomerantsev, A., Trends in Chemometrics: Food authentication, microbiology, and effects of processing (2018) Comprehensive Reviews in Food Science and Food Safety, 17 (3), pp. 663-677
  • Gurdeniz, G., Ozen, B., Detection of adulteration of extra-virgin olive oil by chemometric analysis of mid-infrared spectral data (2009) Food Chemistry, 116 (2), pp. 519-525
  • Guzmán-Ortiz, F.A., Hernández-Sánchez, H., Yee-Madeira, H., San Martín-Martínez, E., del Robles-Ramírez, M.D.C., Rojas-López, M., Mora-Escobedo, R., Physico-chemical, nutritional and infrared spectroscopy evaluation of an optimized soybean/corn flour extrudate (2015) Journal of Food Science and Technology, 52 (7), pp. 4066-4077
  • Karoui, R., Downey, G., Blecker, C., Mid-Infrared spectroscopy coupled with chemometrics: A tool for the analysis of intact food systems and the exploration of their molecular structure−quality relationships − A review (2010) Chemical Reviews, 110 (10), pp. 6144-6168
  • Knödler, M., Most, M., Schieber, A., Carle, R., A novel approach to authenticity control of whole grain durum wheat (Triticum durum Desf.) flour and pasta, based on analysis of alkylresorcinol composition (2010) Food Chemistry, 118 (1), pp. 177-181
  • Laparra, J.M., Haros, M., Inclusion of whole flour from Latin-American crops into bread formulations as substitute of wheat delays glucose release and uptake (2018) Plant Foods for Human Nutrition
  • Lohumi, S., Lee, S., Lee, H., Cho, B.-K., A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration (2015) Trends in Food Science & Technology, 46 (1), pp. 85-98
  • López, M.I., Colomer, N., Ruisánchez, I., Callao, M.P., Validation of multivariate screening methodology. Case study: Detection of food fraud (2014) Analytica Chimica Acta, 827, pp. 28-33
  • López, M.I., Trullols, E., Callao, M.P., Ruisánchez, I., Multivariate screening in food adulteration: Untargeted versus targeted modelling (2014) Food Chemistry, 147, pp. 177-181
  • Luna, A.S., da Silva, A.P., Alves, E.A., Rocha, R.B., Lima, I.C.A., de Gois, J.S., Evaluation of chemometric methodologies for the classification of Coffea canephora cultivars via FT-NIR spectroscopy and direct sample analysis (2017) Analytical Methods, 9 (29), pp. 4255-4260
  • Luna, A.S., Pinho, J.S.A., Machado, L.C., Discrimination of adulterants in UHT milk samples by NIRS coupled with supervision discrimination techniques (2016) Analytical Methods, 8 (39), pp. 7204-7208
  • Manning, L., Soon, J.M., Developing systems to control food adulteration (2014) Food Policy, 49, pp. 23-32
  • Nowak, V., Du, J., Charrondière, U.R., Assessment of the nutritional composition of quinoa (Chenopodium quinoa Willd.) (2016) Food Chemistry, 193, pp. 47-54
  • Ojinnaka, D., Legislative control of quinoa in the United Kingdom and European Union (2016) Madridge Journal of Food Technology, 1 (1), pp. 53-57. ,
  • Oliveri, P., Downey, G., Multivariate class modeling for the verification of food-authenticity claims (2012) Trends in Analytical Chemistry, 35, pp. 74-86
  • Ozen, B.F., Mauer, L.J., Detection of hazelnut oil adulteration using FT-IR spectroscopy (2002) Journal of Agricultural and Food Chemistry, 50 (14), pp. 3898-3901
  • Pallone, J.A.L., Caramês, E.T.S., Alamar, P.D., Green analytical chemistry applied in food analysis: Alternative techniques (2018) Current Opinion in Food Science
  • Pomerantsev, A.L., Rodionova, O.Y., Process analytical technology: A critical view of the chemometricians: PAT: A critical view of the chemometricians (2012) Journal of Chemometrics, 26 (6), pp. 299-310
  • Roa, D.F., Santagapita, P.R., Buera, M.P., Tolaba, M.P., Ball milling of Amaranth starch-enriched fraction. Changes on particle size, starch crystallinity, and functionality as a function of milling energy (2014) Food and Bioprocess Technology, 7 (9), pp. 2723-2731
  • Rodionova, O.Y., Titova, A.V., Pomerantsev, A.L., Discriminant analysis is an inappropriate method of authentication (2016) Trends in Analytical Chemistry, 78, pp. 17-22
  • Rodriguez-Saona, L.E., Allendorf, M.E., Use of FTIR for rapid authentication and detection of adulteration of food (2011) Annual Review of Food Science and Technology, 2 (1), pp. 467-483
  • Ropodi, A.I., Panagou, E.Z., Nychas, G.-J.E., Data mining derived from food analyses using non-invasive/non-destructive analytical techniques; determination of food authenticity, quality & safety in tandem with computer science disciplines (2016) Trends in Food Science & Technology, 50, pp. 11-25
  • Ruiz, K.B., Biondi, S., Oses, R., Acuña-Rodríguez, I.S., Antognoni, F., Martinez-Mosqueira, E.A., Molina-Montenegro, M.A., Quinoa biodiversity and sustainability for food security under climate change. A review (2014) Agronomy for Sustainable Development, 34 (2), pp. 349-359
  • Stevens, A.W., Quinoa quandary: Cultural tastes and nutrition in Peru (2017) Food Policy, 71, pp. 132-142
  • Su, W.-H., Sun, D.-W., Evaluation of spectral imaging for inspection of adulterants in terms of common wheat flour, cassava flour and corn flour in organic Avatar wheat (Triticum spp.) flour (2017) Journal of Food Engineering, 200, pp. 59-69
  • Sujka, K., Koczoń, P., Ceglińska, A., Reder, M., Ciemniewska-Żytkiewicz, H., The Application of FT-IR spectroscopy for quality control of flours obtained from polish producers (2017) Journal of Analytical Methods in Chemistry, 2017, pp. 1-9
  • van den Berg, F., Lyndgaard, C.B., Sørensen, K.M., Engelsen, S.B., Process analytical technology in the food industry (2013) Trends in Food Science & Technology, 31 (1), pp. 27-35
  • Verdú, S., Vásquez, F., Grau, R., Ivorra, E., Sánchez, A.J., Barat, J.M., Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread (2016) Food Control, 62, pp. 373-380
  • Warren, F.J., Gidley, M.J., Flanagan, B.M., Infrared spectroscopy as a tool to characterise starch ordered structure—A joint FTIR–ATR, NMR, XRD and DSC study (2016) Carbohydrate Polymers, 139, pp. 35-42
  • Ziegler, J.U., Leitenberger, M., Longin, C.F.H., Würschum, T., Carle, R., Schweiggert, R.M., Near-infrared reflectance spectroscopy for the rapid discrimination of kernels and flours of different wheat species (2016) Journal of Food Composition and Analysis, 51, pp. 30-36


---------- APA ----------
Rodríguez, S.D., Rolandelli, G. & Buera, M.P. (2019) . Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods. Food Chemistry, 274, 392-401.
---------- CHICAGO ----------
Rodríguez, S.D., Rolandelli, G., Buera, M.P. "Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods" . Food Chemistry 274 (2019) : 392-401.
---------- MLA ----------
Rodríguez, S.D., Rolandelli, G., Buera, M.P. "Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods" . Food Chemistry, vol. 274, 2019, pp. 392-401.
---------- VANCOUVER ----------
Rodríguez, S.D., Rolandelli, G., Buera, M.P. Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods. Food Chem. 2019;274:392-401.