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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Food Quality Laboratory » Research » Publications at this Location » Publication #298069

Title: Measurement of blend concentrations of conventional and waxy hard wheats using NIR spectroscopy

Author
item Delwiche, Stephen - Steve
item GRAYBOSCH, ROBERT

Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/10/2014
Publication Date: 7/1/2014
Citation: Delwiche, S.R., Graybosch, R.A. 2014. Measurement of blend concentrations of conventional and waxy hard wheats using NIR spectroscopy. Cereal Chemistry. 91(4):358-365.

Interpretive Summary: Wheat endosperm, the material that becomes flour upon milling operations, is approximately three quarters starch by weight. Combined with the other major nutritional fractions, protein, lipid, and other carbohydrates, starch has a substantial role in determining the suitability of flour for various end products, such as bread, cake, crackers, and noodles. The starch molecule itself is a combination of two macromolecules, the linear-chained amylose and the branch-chained amylopectin, such that the abundance of one with respect to the other has a determining effect on flour physical and chemical properties. A recent development in North American plant breeding has resulted in the imminent release of the first commercial variety of hard wheat whose starch is composed of amylopectin in entirety. This condition, commonly referred to as ‘waxy’, offers unique processing characteristics, and hence will command a higher price during trade. Acceptance of waxy wheat by the industry will require the successful segregation of the lots that possess this trait. Underlying such identity preservation will be a mechanism to readily and reliably determine the authenticity of the waxy kernel that, to the untrained eye, has the same appearance as a conventional kernel. In the current study, we examined the use of near-infrared spectroscopy, a technology that is broadly accepted in cereals commerce and industry for measurement of protein and moisture, but is unknown in performance for starch analysis, until now. We found that this very rapid non-chemical technology can predict mixture levels to within five percent by weight, and thus provide assurance of the general purity of a stated waxy consignment. Owing to the already universal presence of NIR instruments in the cereals industry, the benefit of this research is immediate to those contemplating the incorporation of waxy wheat in their product line.

Technical Abstract: Breeding development of waxy hard wheat lines adapted to the North American climate has been underway for more than a decade, with releases of viable varieties imminent. Because of an anticipated 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 in the waxy condition can be identified from non-waxy 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 non-waxy varieties or lines, with year and location being consistent within a pair. Twenty-nine mixtures (0, 1, 2, …, 5, 10, …, 90, 95, 96, …, 99, 100 percent) were formed for each pair. Partial least squares regression models were developed using eight of the nine pairs, with model validation accomplished using the pair excluded. This procedure was repeated for each pair. The results indicate that regardless of sample format and regression algorithm, the optimal models typically produce coefficients of determination (R-squared) in excess of 0.98, with standard errors of ca. 3-5%, thus demonstrating the feasibility of the use of the NIR technique to predict the mixture level to within five percent by weight.