Analysis of corn and sorghum flour mixtures using laser‐induced breakdown spectroscopy

• Published in: Journal of the science of food and agriculture Vol. 101; no. 3; pp. 1076 - 1084
• Main Authors: Akın, Pervin A, Sezer, Banu, Bean, Scott R, Peiris, Kamaranga, Tilley, Michael, Apaydın, Hakan, Boyacı, İsmail H
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.02.2021; John Wiley and Sons, Limited
• Subjects: Adaptability; Animal feed; Biofuels; Calibration; Chemical composition; Chemometrics; Classification; Climate change; Composition; Corn; Cornflour; Discriminant Analysis; Environmental regulations; Feeds; Flour; Flour - analysis; Food Analysis - methods; Food Contamination - analysis; Grain; Industrial products; Laser induced breakdown spectroscopy; Lasers; Least squares; LIBS; Plant Preparations - chemistry; PLS regression; PLS‐DA; Regression analysis; Sample preparation; Sorghum; Sorghum - chemistry; Spectroscopy; Spectrum analysis; Spectrum Analysis - instrumentation; Spectrum Analysis - methods; Zea mays - chemistry; PLS regression; sorghum; PLS-DA; LIBS; corn
• DOI: 10.1002/jsfa.10717
• ISSN: 0022-5142

BACKGROUND In a world constantly challenged by climate change, corn and sorghum are two important grains because of their high productivity and adaptability, and their multifunctional use for different purposes such as human food, animal feed, and feedstock for many industrial products and biofuels. Corn and sorghum can be utilized interchangeably in certain applications; one grain may be preferred over the other for several reasons. The determination of the composition corn and sorghum flour mixtures may be necessary for economic, regulatory, environmental, functional, or nutritional reasons. RESULTS Laser‐induced breakdown spectroscopy (LIBS) in combination with chemometrics, was used for the classification of flour samples based on the LIBS spectra of flour types and mixtures using partial least squares discriminant analysis (PLS‐DA) and the determination of the sorghum ratio in sorghum / corn flour mixture based on their elemental composition using partial least squares (PLS) regression. Laser‐induced breakdown spectroscopy with PLS‐DA successfully identified the samples as either pure corn, pure sorghum, or corn‐sorghum mixtures. Moreover, the addition of various levels of sorghum flour to mixtures of corn‐sorghum flour were used for PLS analysis. The coefficient of determination values of calibration and validation PLS models are 0.979 and 0.965, respectively. The limit of detection of the PLS models is 4.36%. CONCLUSION This study offers a rapid method for the determination of the sorghum level in corn‐sorghum flour mixtures and the classification of flour samples with high accuracy, a short analysis time, and no requirement for time‐consuming sample preparation procedures. © 2020 Society of Chemical Industry