Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods
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. Four...
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todo:paper_03088146_v274_n_p392_Rodriguez2023-10-03T15:22:57Z Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods Rodríguez, S.D. Rolandelli, G. Buera, M.P. 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 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 JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03088146_v274_n_p392_Rodriguez |
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Universidad de Buenos Aires |
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I-28 |
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R-134 |
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
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 |
| spellingShingle |
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 Rodríguez, S.D. Rolandelli, G. Buera, M.P. Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| topic_facet |
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 |
| description |
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 |
| format |
JOUR |
| author |
Rodríguez, S.D. Rolandelli, G. Buera, M.P. |
| author_facet |
Rodríguez, S.D. Rolandelli, G. Buera, M.P. |
| author_sort |
Rodríguez, S.D. |
| title |
Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| title_short |
Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| title_full |
Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| title_fullStr |
Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| title_full_unstemmed |
Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods |
| title_sort |
detection of quinoa flour adulteration by means of ft-mir spectroscopy combined with chemometric methods |
| url |
http://hdl.handle.net/20.500.12110/paper_03088146_v274_n_p392_Rodriguez |
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