Measurement of Blend Concentrations of Conventional and Waxy Hard Wheats Using NIR Spectroscopy. Issue 4 (23rd July 2014)

• Record Type: Journal Article
• Authors: Delwiche, Stephen R.; Graybosch, Robert A.
• Is Part Of: Cereal chemistry. Volume 91:Issue 4(2014.)
• Page Start: 358
• Page End: 365
• Publication Date: 2014-07-23
• Subjects: Chemistry, Technical -- Periodicals; Baking -- Periodicals; Baking; Chemistry, Technical; Edible Grain; Food Analysis; Electronic journals; Periodicals; 664.72
• DOI: 10.1094/CCHEM-09-13-0195-R
• Languages: English
• ISSNs: 0009-0352

Abstract

ABSTRACT: Breeding development of waxy (amylose‐free) hard wheat lines adapted to the North American climate has been underway for more than a decade, with releases of competitive varieties imminent. Because of required identity preservation and a possible premium value placed on waxy lots, a rapid and accurate method is desired to identify and quantify the mixing of conventional wheat with waxy wheat, a condition that might occur at harvest or any point downstream. Our previous work demonstrated that lines pure with waxy starch can be identified from nonwaxy lines by use of near‐infrared (NIR) spectroscopy applied either on a whole kernel or ground meal basis. However, mixture quantification by NIR techniques has not been examined until now. Using hard winter wheat grown in two seasons (2011 and 2012) and at two locations (Nebraska and Arizona), a series of mixtures ranging in proportion (conventional/waxy) percentage by weight, from 0:100 to 100:0, were formed from nine pairs of waxy and nonwaxy varieties or lines, with year and location being consistent within a pair. Twenty‐nine mixtures (0, 1, 2, 3, 4, 5, 10, 15, …, 85, 90, 95, 96, 97, 98, 99, and 100%) were formed for each pair. Partial least squares regression models were developed by using eight of the nine pairs, with model validation accomplished by using the pair excluded. This procedure was repeated for each pair. The results indicate that, regardless of sample format or spectral pretreatment, the optimal models typically produce coefficients of determination in excess of 0.98, with standard errors of 4–7%, thus demonstrating the feasibility of the use of the NIR technique to predict the mixture level to within 10% by weight.