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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Grain Quality and Structure Research » Research » Publications at this Location » Publication #371560

Research Project: Impact of the Environment on Sorghum Grain Composition and Quality Traits

Location: Grain Quality and Structure Research

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

Author
item ARI AKIN, PERVIN - Institute For Field Crops - Turkey
item SEZER, BANU - Hacettepe University
item Bean, Scott
item PEIRIS, KAMARANGA - Kansas State University
item Tilley, Michael - Mike
item APAYDIN, HAKIN - Hitit University
item BOYACI, ISMAMIL HAKKI - Hacettepe University

Submitted to: Journal of the Science of Food and Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/7/2020
Publication Date: 8/9/2020
Citation: Ari Akin, P., Sezer, B., Bean, S.R., Peiris, K., Tilley, M., Apaydin, H., Boyaci, I. 2020. Analysis of corn and sorghum flour mixtures using laser induced breakdown spectroscopy. Journal of the Science of Food and Agriculture. https://doi.org/10.1002/jsfa.10717.
DOI: https://doi.org/10.1002/jsfa.10717

Interpretive Summary: Corn and sorghum are two important grains because of high productivity, adaptability and their multifunctional usage in different fields such as human food, animal feed and feed stock 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 grain mixtures may be necessary for economic, regulatory, environmental, functional or nutritional reasons. As closely related cereal grains, corn and sorghum share many similarities which can make distinguishing mixtures of the two grains difficult. To distinguish flour mixtures of corn and and sorghum, the use of laser induced breakdown spectroscopy (LIBS) in combination with chemometric data analysis was evaluated for determining the composition of corn-sorghum flour mixtures. LIBS was found to successfully identify flours as sorghum, corn or corn-sorghum mixtures as well as determining the composition of mixtures with a coefficient of determination of 0.97 and a limit of detection of 4.36%. Thus LIBS could be used as a rapid method for determining the sorghum levels in corn-sorghum flour mixtures.

Technical Abstract: In a world constantly challenged by climate change, corn and sorghum are two important grains because of high productivity, adaptability and their multifunctional usage in different fields such as human food, animal feed and feed stock 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 grain mixtures may be necessary for economic, regulatory, environmental, functional or nutritional reasons. A new method, Laser Induced Breakdown Spectroscopy (LIBS) in combination with chemometrics, was used for the classification of grain samples based on LIBS spectra of grain types and mixtures using Partial Least Squares Discriminant Analysis (PLS-DA) and the determination of the sorghum ratio in sorghum/corn mixture based on their elemental composition using Partial Least Squares (PLS). LIBS with PLS-DA identified successfully the samples either pure corn, pure sorghum or corn-sorghum mixture. Moreover, various levels of sorghum addition in the mixture of corn and sorghum are 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 (LOD) of the PLS models is 4.36%. These values show that the method is highly sensitive to determine the level of sorghum in the mixture. This study offers a rapid method for the determination of sorghum ratio in sorghum/corn mixture and the classification of grain samples with high accuracy, a short analysis and no requirement for timeconsuming sample preparation procedures.