Predicting Wheat Quality Characteristics and Functionality Using Near-Infrared Spectroscopy

Cereal Chem. 83(5):529–536 The accuracy of using near-infrared spectroscopy (NIRS) for predicting 186 grain, milling, flour, dough, and breadmaking quality parameters of 100 hard red winter (HRW) and 98 hard red spring (HRS) wheat and flour samples was evaluated. NIRS shows the potential for predicting protein content, moisture content, and flour color b* values with accuracies suitable for process control (R > 0.97). Many other parameters were predicted with accuracies suitable for rough screening including test weight, average single kernel diameter and moisture content, SDS sedimentation volume, color a* values, total gluten content, mixograph, farinograph, and alveograph parameters, loaf volume, specific loaf volume, baking water absorption and mix time, gliadin and glutenin content, flour particle size, and the percentage of dark hard and vitreous kernels. Similar results were seen when analyzing data from either HRW or HRS wheat, and when predicting quality using spectra from either grain or flour. However, many attributes were correlated to protein content and this relationship influenced classification accuracies. When the influence of protein content was removed from the analyses, the only factors that could be predicted by NIRS with R > 0.70 were moisture content, test weight, flour color, free lipids, flour particle size, and the percentage of dark hard and vitreous kernels. Thus, NIRS can be used to predict many grain quality and functionality traits, but mainly because of the high correlations of these traits to protein content. Quality characteristics of wheat (Triticum aestivum L.) whole grain, flour, dough, and bread can be measured by various qualitative and quantitative tests. These measurements are typically used to determine value or used to predict functionality and end use quality. There are standard or recommended measurement methods for many of these quality parameters such as those found in the Approved Methods of AACC International (2000) and the United States Department of Agriculture (USDA) Grain Inspection Handbook (USDA 2004). These methods are generally difficult and time-consuming, and most cannot be used to rapidly measure quality characteristics and functionality. Near-infrared spectroscopy (NIRS) has been used as a rapid, accurate, and nondestructive technique for measuring many wheat quality parameters. Williams et al (1988) used NIRS to predict wheat strength from hard red spring (HRS) flour spectra with good accuracies. Their samples were selected to represent a wide range in dough strength, sedimentation volume, and loaf volume. Rubenthaler and Pomeranz (1987) showed good correlations of water absorption, mix time, and loaf volume of hard red winter (HRW) wheat to flour NIR spectra. Delwiche et al (1998) applied NIRS models of flour from pure HRW cultivars to predict glutenin and gliadin content, SDS sedimentation volume, and mixograph peak resistance. When using commercial HRW and HRS flour, Delwiche and Weaver (1994) predicted absorption, mix time, bake score, loaf height, and mix tolerance from NIR spectra. Pawlinsky and Williams (1998) further showed that, when scanning Canadian HRW and HRS wheat grain, they could predict functionality parameters for the identification of suitable material for advancement in breeding programs. Their tests were limited to predicting protein content, wet gluten content, Zeleny sedimentation volume, mixing time, and farinograph parameters. In a study using spectra from whole grain and flour, Millar (2003) developed NIRS calibrations from U.K. and French wheat and showed potential for predicting protein and moisture content, water absorption, and flour color using NIR spectra, but had poor results when attempting to predict loaf volume and crumb grain score. Sissons et al (2006) used NIR spectra from grain from durum (Triticum turgidum L.) breeding lines to predict kernel, flour, and dough characteristics for breeding programs. Their results showed potential for grouping samples into low, medium, and high categories for test weight, thousand kernel weight, semolina yield, semolina yellow color, semolina browning, grain hardness, and cooked pasta firmness. Hruskova and Famera (2003) used flour NIR spectra for quantitative screening based on moisture and protein content, ash, and wet gluten content. However, related research showed that farinograph (Hruskova et al 2001) and alveograph (Hruskova and Smejda 2003) parameters were predicted poorly when using NIR spectra from flour. Devaux et al (1986) used NIRS models to assign French soft wheat samples into three breadbaking quality categories (good, unsuitable, and irregular), but actual quality measurements or predictions were not made. Thus, although other researchers have examined the potential for NIRS to predict various quality parameters from flour and whole grain spectra, most were limited to small sample sets, pure cultivars, or predicting a few specific parameters. No previous research has attempted to predict multiple whole kernel, milling, flour, dough, and breadmaking quality from whole kernels and flour from samples representing those in commercial trade. Thus, the objective of this research was to evaluate the potential of NIRS to measure whole kernel, milling, flour, dough, and breadmaking quality characteristics from whole kernels and flour of HRW and HRS wheat samples selected to represent the quality range expected in U.S. commercial wheat. It is not the goal of this research to develop calibrations but to examine where NIRS may provide the grain industry with a potential rapid means to predict grain, flour, dough, and bread quality, and where to focus future calibration efforts. 1 USDA ARS, Grain Marketing and Production Research Center, Engineering Research Unit, 1515 College Avenue, Manhattan, KS 66502. Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by the USDA implies no approval of the product to the exclusion of others that may also be suitable. 2 Corresponding author. Phone: 785-776-2753. Fax: 785-537-5550. E-mail: floyd. [email protected] 3 Kansas State University, Department of Grain Science and Industry, Manhattan, KS 66506. 4 USDA, Grain Inspection, Packers, and Stockyards Administration, Federal Grain Inspection Service, Kansas City, MO 64163. 5 USDA ARS, Grain Marketing and Production Research Center, Grain Quality and Structure Research Unit, 1515 College Avenue, Manhattan, KS 66502. DOI: 10.1094 / CC-83-0529 This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. AACC International, Inc., 2006.