An overview of the use of infrared spectroscopy and chemometrics in authenticity and traceability of cereals |
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| Affiliation: | 1. Istituto di Metodologie Chimiche, Laboratorio di Risonanza Magnetica “Annalaura Segre”, CNR, Monterotondo, Rome, Italy;2. Dipartimento di Chimica e Tecnologie del Farmaco, Sapienza Università di Roma, Piazzale Aldo Moro 5, Rome, Italy;1. CEOT, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;2. MED, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;3. Physics Department, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;1. Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa, and Instituto de Ciencias de La Tierra y Ambientales de La Pampa (INCITAP), Av. Uruguay 151 (6300) Santa Rosa, La Pampa, Argentina;2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, Buenos Aires, CP C1425FQB, Argentina;3. Instituto de La Grasa (CSIC), Campus Universidad Pablo de Olavide, Edificio 46, Ctra. de Utrera, Km. 1, 41013, Sevilla, Spain;4. IKERBASQUE, Basque Foundation for Science, Bilbao, 48011, Spain;5. Department of Analytical Chemistry, University of the Basque Country UPV/EHU, P.O. Box 644, Bilbao, Basque Country, 48080, Spain;6. Laboratorio de Desarrollo Analítico y Quimiometría, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional Del Litoral, Ciudad Universitaria, 3000, Santa Fe, Argentina |
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| Abstract: | Although both near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy combined with multivariate data analysis (MVA) have been extensively used to measure chemical composition (e.g. protein, moisture, oil) in a wide number of grains few reports can be found on the use of this methods for varietal discrimination and traceability of cereals. In this overview applications of NIR spectroscopy and MIR spectroscopy combined with multivariate data methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA) to aid on the authentication and traceability of cereals are discussed. |
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