D.W. Hatcher

Phenolic acid composition of sprouted wheats by ultra-performance liquid chromatography (UPLC) and their antioxidant activities.

The phenolic acid profiles of flours from two Canadian wheat classes, Canadian Western Red Spring (CWRS) and Canadian Western Amber Durum (CWAD), were investigated using two different extraction mediums and analysed on an ultra-performance liquid chromatography (UPLC) system at different degrees of sprout damage. A sound (non-sprouted) control sample as well as two different sprouted sub-samples, derived from different germination protocols of the control, were prepared for both the CWAD and CWRS. Free phenolic acids were extracted from the ground whole wheat meal using three repetitive 80% ethanol extractions. Bound phenolic compounds were subsequently released from the residue by alkaline hydrolysis followed by triplicate extraction with diethyl ether:ethyl acetate (1:1, v/v). Twelve phenolic acid standards were clearly resolved and quantified using a short 5min elution gradient. Seven phenolic acids (4-hydroxybenzoic, vanillic, caffeic, syringic, p-coumaric, ferulic and sinapic) were detected in the CWRS and CWAD alcoholic and alkaline extracts. Syringic acid was the main compound in the free phenolic alcoholic extracts of the wheat meal representing 77.0% and 75.3% of the total amount of detected free phenolic compounds for CWRS and CWAD, respectively. However, the major released phenolic compound detected in the alkaline hydrolysed extracts was ferulic acid accounting for 72.3% and 71.0% for CWRS and CWAD respectively total bound phenolics. During germination, syringic acid levels rose as the length of germination time increased, resulting in the increase in total phenolic compound and antioxidant activity of the sprouted wheat flours. There was an increase in total phenolic compounds and the antioxidant activity of the alcoholic extracts from the CWRS and CWAD wheat flours as the germination time was extended. As a result, the sprouted wheats exhibits better nutritional properties than un-germinated wheat and could be used to improve the nutrition value in food products.

Analysis of wheat gluten proteins by matrix-assisted laser desorption/ionization mass spectrometry

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI/MS) was used to analyze the protein composition in several common and durum wheat varieties. Mass spectra were obtained directly from crude and partially purified wheat gliadin and reduced glutenin subunit fractions. Mass spectra of the gliadins and the low molecular weight (LMW) glutenin subunits show a complex pattern of proteins in the 30–40 kDa range. The observed gliadin patterns may be suitable for differentiation between wheat varieties, but the complexity of the mass spectra precludes the use of MALDI/MS as a stand-alone technique for the identification of most individual gliadin components. The mass spectra of the high molecular weight (HMW) glutenin subunits are much simpler and the complete HMW subunit profile can be determined directly from a single mass spectrum. This may prove particularly useful in wheat breeding programs for rapid identification of lines containing subunits associated with superior quality. The correspondence between previously identified HMW subunits and the mass spectral peaks was established with MALDI measurements of HPLC-separated subunits. Delayed extraction proved effective in improving the mass resolution for the monomeric gliadins and LMW glutenin subunit fractions, with masses less than 40 kDa. However, it gave little improvement for the HMW glutenin subunits which have masses of ∽80 kDa.

Flour Particle Size, Starch Damage, and Alkali Reagent: Impact on Uniaxial Stress Relaxation Parameters of Yellow Alkaline Noodles

ABSTRACT Three patent flours, each possessing three different levels of starch damage were prepared from a single hard white spring wheat. Each flour was sieved to yield three flours with different particle size distributions (85–110, 110–132, 132–183 μm). Raw alkaline noodles were prepared from the nine flours using either 1% w/w kansui (sodium and potassium carbonates in 9:1 ratio) or 1% w/w sodium hydroxide. Uniaxial stress relaxation parameters percent stress relaxation (SR%), initial rate of relaxation (k1) and the extent of relaxation (k2) were measured on the raw noodles immediately after production (t = 0 min) and at 60 min. Raw noodles after resting for 60 min were optimally cooked and stress relaxation parameters were measured. Raw noodles at t = 0 min exhibited SR%, k1, and k2 that were significantly (P < 0.0001) influenced by both the degree of starch damage and the type of alkaline reagent used. Flour particle size only influenced SR% and k1 (P < 0.025) but had no impact on k2. In raw noodles...

Refrigerated Storage of Yellow Alkaline Durum Noodles : Impact on Color and Texture

ABSTRACT Durum wheat straight-grade flour samples, representing the cultivars Commander and Strongfield, a composite cargo mixture of Canada Western Amber Durum cultivars and a Japanese commercial durum flour were used to make yellow alkaline noodles. A Canada Western Red Spring common wheat composite straight-grade flour was included in the study for comparative purposes. Alkaline noodles were prepared using 1% w/w kansui reagent (sodium and potassium carbonates, 9:1) and stored for 1, 2, 3 and 7 days at 4°C to duplicate a normal convenience store operation. The raw noodle color of the durum alkaline noodles exhibited significantly better noodle brightness, L*, and yellowness, b*, as compared to noodles prepared from common wheat at all storage periods. The number of discolored specks in the durum flour based noodles was significantly lower as well as significantly lighter than those of common wheat at all time intervals. Noodles prepared from Commander, Strongfield, or the cargo composite flours display...

Impact of Genotype and Environment on the Quality of Amber Durum Wheat Alkaline Noodles

ABSTRACT Canada Western Amber Durum wheat cultivars (4), Canada Western Red Spring (1), and Canada Western Hard White Spring (1) wheat were grown at three sites in 2007 to evaluate the effect of genotype (G) and environment (E) on the quality of yellow alkaline noodles (YAN). YAN were evaluated for color, appearance, and cooked texture. Brightness (L*) and yellowness (b*) of YAN made from durum cultivars were significantly higher than common wheat. Durum flour yellow pigment content was approximately fourfold greater than common wheat while noodle speckiness was approximately half of CWRS at 2 hr with environment accounting for >75% of the variance for each parameter. Resistance to compression (RTC) and recovery (REC) of cooked durum alkaline noodles were equivalent or superior to common wheat noodles even when lower grade durum wheat flour was used. In conclusion, cooked durum noodle texture parameters were all significantly influenced by genotype and environment, with environment accounting for 66–71% o...

Use of Imaging Methods for Assessment of Asian Noodle Color

Asia represents a major component of the wheat export market for Australia, Canada, and the United States. Depending on the Asian country, 35–40% of the imported wheat is used for the production of a wide variety of noodles (6). Fresh yellow alkaline and white salted noodles are very popular, and consumer purchasing is initially determined by product appearance (21,22). Noodle appearance can be influenced by flour protein content (23), degree of flour refinement (18), enzyme levels (1), flour particle size and the degree of starch damage (8), the presence of degrading factors (7,13), the type of alkaline reagent used (21,24), enrichment (16), and even the amount of water used in noodle production (9). The most common problem in noodles is speckiness due to the presence of small wheat bran particles in the flour. Wheat bran is a natural component of flour, but its presence and the size of the particles is a function of the degree of flour selection and sieving during the milling process. In many Asian countries, noodles are manufactured daily in small plants and transported to various vendors. The time, elevated temperature, and humidity after production all influence the changing appearance of the noodle product. Bran particles are very rich in a wide variety of phenolic compounds that undergo oxidation by enzymes and yield undesirable colored byproducts (4). Over time (24 hr), large areas of discoloration are produced that cause the consumer to reject the product. Image analysis methods can measure the degradation in noodle appearance. Image analysis of raw noodles can effectively discriminate a large number of factors influencing final product appearance (14). For example, image analysis can effectively discriminate and quantify the degree of bran contamination and its impact on noodle appearance in both major noodle types (12). Initial research utilized costly CCD cameras to detect undesirable features on noodle surfaces. Refinements in imaging technology, in combination with advances in scanner technology, have resulted in the use of inexpensive scanner systems capable of providing noodle manufacturers with a high degree of appearance assessment and discrimination (28). Continuous advancements in the associated software for the analyses of captured images provides manufacturers with the ability to customize their quality control practices to meet the demands of their market niche (15,26). This technology also allows noodle manufacturing firms to stipulate quality specifications to their suppliers. An operator has the ability to quantify noodle appearance in seconds on the basis of number of specks, size of speck, and discrimination from the background matrix. While the use of inexpensive color scanners provides a wide variety of essential noodle quality information critical to the manufacturer for meeting the continually changing needs of consumers, concurrent color assessment from the captured images will greatly benefit the noodle industry. The current procedure for assessing the noodle color under either commercial or laboratory conditions is through the measurement of CIE L*, a*, and b* values on a small piece of noodle, usually <2.5 cm in diameter. A series of readings taken across the entire noodle sheet is averaged to quantify noodle color. The use of commercial colorimeters, while objectifying color measurement, does not offer any means to integrate and measure consumer perception of speckiness. An imaging system could potentially measure noodle color as perceived by humans. The captured images of noodles show the overall noodle color represented by the distribution (histogram) of individual color channels. Histograms have been widely used to represent, analyze, and characterize images for pattern recognition and content-based image retrieval from databases (5,25,30). The fundamental task that remains is to somehow relate image color histograms to the CIE L*, a*, and b* values measured with a colorimeter. Black and Panozzo (2) compared two techniques to predict the color of grains and wheat flour (L*, a*, b*) based on nearinfrared reflectance (NIR) spectra. They found that the standard CIE method for computing color (Standard E308-95) performed better than calibrations derived from the spectra and reference colorimeter data. An earlier study (3) showed that a neural network model for converting a device-dependent color space (red, green, blue [RGB] and hue, light, saturation [HLS]) to a device-independent color space (CIE L*, a*, b*) outperformed statistical as well as optimization approaches in terms of lowest error. Neural networks have been widely used for modeling complex problems where input-output relationships are not readily discernible (17,19,27,29). The objective of this study was to incorporate existing noodle imaging refinements with the development of a fast, reliable, and relatively inexpensive imaging method to concurrently predict the color of Asian noodles.

Development of multispectral imaging systems for quality evaluation of cereal grains and grain products

Abstract: The commercial value of small grains such as wheat and barley is determined by their overall quality. Grading systems established by the major countries exporting these grains establish maximum tolerances for various contaminants and damage factors to the grain kernels. Grading factors are mainly visual characteristics. Collectively, the grading factors describe grain quality and safety as affected by growing conditions, handling and storage practices. Human visual inspection is the current method of grain quality assessment, which can be subjective and inconsistent. Alternative instrumental approaches to quality assurance are constantly being researched. Hyperspectral imaging has been used effectively for the detection and quantification of grain damage due to various grading factors such as mildew, fusarium, sprouting and green immature seeds. Hyperspectral systems, while effective, are expensive research tools. Multispectral systems using a few wavelengths provide practically viable, less expensive and simpler imaging solutions. A multispectral system using three band-pass filters successfully detected and scored green barley kernels. Development of fast, accurate and low-cost multispectral systems is expected to have a profound effect on the acceptance of instrumental methods of grain grading by the grain industry.