Submitted to: Cereal Chemistry
Publication Type: Peer reviewed journal
Publication Acceptance Date: 9/19/2003
Publication Date: 3/1/2004
Citation: Ram, M.S., Seitz, L.M., Dowell, F.E. 2004. Natural fluorescence of red and white wheat kernals. Cereal Chemistry. 2004. 81(2):244-248. Interpretive Summary: For marketing purposes, red and white wheat need to be kept segregated because mixtures of these wheats are discounted, and some have different end uses. Identification of wheat color class is not straightforward, and currently, there is a great interest in characterizing red and white wheat using spectroscopy and chemical tests. During preliminary observations, we noticed that all varieties of red and white wheat exhibited natural fluorescence under UV light in a viewing cabinet, and there appeared to be some differences between red and white wheats. From a study of 90 cultivars (41 red and 49 white) we found that fluorescence emission spectra of red wheat kernels are different from those of white wheats, as indicated by partial least-squares (PLS) and neural networks analysis (NNA). This information may aid development of a simple, rapid wheat color class identification process easily without the use of chemicals. Only a relatively inexpensive spectrofluorometer would be required, and the test may be extendable to single kernels.
Technical Abstract: Red and white wheats must be segregated for marketing purposes, because they have different end uses. Identification of wheat color is not straightforward, and currently there is interest in characterizing red and white wheats using spectroscopy and / or chemical tests. The kernels of both red and white wheats exhibit natural fluorescence that can readily be viewed under UV light, although it is not possible to differentiate the fluorescence spectra of red and white wheats by visual inspection only. Fluorescence emission spectra, in the wavelength range of 370-670 nm, of 90 wheat samples consisting of 41 red and 49 white were analyzed by partial least- squares (PLS) and neural networks (NNAis ANN is more common?: Artificial Neural Networks) after normalization. Classification accuracies were ~90% for both analyses, with ANN results being slightly better. Samples that were not classified correctly by NNA*** also were not classified by PLS, but the reverse was not true. A plot of¿¿-coefficient vs. wavelength in PLS analysis indicated that fluorescence of red wheat cultivars was greater than that for white wheat cultivars at 415 ("20 ) nm wavelength, and fluorescence of white wheat cultivars was greater than that for red cultivars at 535 (" 35) nm. Fluorescence emission at around 450 nm from wheat samples increased in intensity after treatment with NaOH. The increase was greater for red than for white wheat. Wheat harvested after rainfall also exhibited a slight increase in fluorescence.