Relationship of Bread Quality to Kernel,Flour, and Dough Properties

This study measured the relationship between bread quality and 49 hard red spring (HRS) or 48 hard red winter (HRW) grain, flour, and dough quality characteristics. The estimated bread quality attributes included loaf volume, bake mix time, bake water absorption, and crumb grain score. The best‐fit models for loaf volume, bake mix time, and water absorption had R² values of 0.78–0.93 with five to eight variables. Crumb grain score was not well estimated, and had R² values ≈0.60. For loaf volume models, grain or flour protein content was the most important parameter included. Bake water absorption was best estimated when using mixograph water absorption, and flour or grain protein content. Bake water absorption models could generally be improved by including farinograph, mixograph, or alveograph measurements. Bake mix time was estimated best when using mixograph mix time, and models could be improved by including glutenin data. When the data set was divided into calibration and prediction sets, the loaf volume and bake mix time models still looked promising for screening samples. When including only variables that could be rapidly measured (protein content, test weight, single kernel moisture content, single kernel diameter, single kernel hardness, bulk moisture content, and dark hard and vitreous kernels), only loaf volume could be predicted with accuracies adequate for screening samples.     

Gluten,Pasting, and Mixograph Parameters of Hard Winter Wheat Flours in Relation to Breadmaking

Flour gluten, pasting, and mixogram characteristics of 12 hard winter wheat cultivars grown in six counties in Kansas were analyzed using the Glutomatic System, a Rapid Visco-Analyser, and MIXSMART computer software, respectively, to investigate their relationships with breadmaking. Gluten contents and hydration amounts had significant correlations with water absorption. In addition, gluten parameters were significantly correlated to kernel hardness. One of the most difficult challenges in mixograph usage is to find the optimum water absorption of a given flour. Flour protein contents (FP) and near-infrared hardness scores or FP and gluten parameters could predict mixograph water absorptions, showing R² values of 0.842 or 0.814, respectively, by multiple regression analysis. For our set of 72 wheat samples, computer-analyzed mixograph parameters were significantly correlated to conventional parameters. Computer-analyzed mixograph midline peak times and bandwidths at 6 min were highly correlated to conventional mixograph mix times and mixing tolerances, respectively. Flour pasting temperatures complemented FP in predicting loaf volumes. The ratios of FP to pasting temperatures had a significant curvilinear relationship with loaf volumes showing an R² of 0.725.     

NIR Transmittance Estimation of Free Lipid Content and Its Glycolipid and Digalactosyldiglyceride Contents Using Wheat Flour Lipid Extracts

Free lipids (FL) in 72 hard winter wheat flours were extracted and dissolved in hexane. Absorbance (log 1/T) values were measured using a scanning spectrophotometer with a 2‐mm cuvette, and used to develop calibration models for estimating flour FL content and glycolipid (GL) and digalactosyldiglyceride (DGDG) contents. Fifty‐one calibration samples were selected based on the cutoff point of 0.3 of Mahalanobis distance, and the remaining twenty‐one samples were used for validation. The best model for the estimation of FL content showed coefficients of determination (R²) of 0.95 for the calibration set and R² = 0.89 for the validation set. Glycolipid contents could be estimated by a model which had R² = 0.87 for the calibration set and R² = 0.89 for the validation set. For DGDG, the best model showed R² = 0.94 for the calibration set and R² = 0.88 for the validation set.     

Rapid Assessment and Prediction of Wheat and Gluten Baking Quality With the 2‐g Direct Drive Mixograph Using Multivariate Statistical Analysis

A computerized 2‐g direct drive mixograph was used to study the mixing characteristics of flours milled from a range of breadmaking cultivars obtained from five separate locations around the UK, providing 54 flour samples. Fifteen parameters were extracted from each mixograph trace using the Mixsmart software program and correlated with baking volume using partial least squares multiple regression statistical analysis to give a prediction of baking volume. Location had a considerable influence on the prediction of baking volume. Excellent predictions of baking volume were obtained from flours from individual locations (R² = 0.805–0.995), but predictions based on all cultivars without discriminating locations were poor. When mixograph and baking volume data for each cultivar were averaged over all five locations, a very high correlation was obtained (R² = 0.999). Preparation of flour samples using rapid, small‐scale milling procedures (Brabender Quadrumat Jr. mill and Perten 3100 hammer mill) did not have any adverse effect on prediction of baking volume. Mixograph parameters obtained from six commercial glutens of varying quality gave good correlations with test baking volumes, based on 6% gluten addition to a control flour.     

Prediction of Baking Characteristics of Hard Winter Wheat Flours Using Computer‐Analyzed Mixograph Parameters

The objective of this research was to determine whether computer‐analyzed (objective) mixograph parameters could replace conventional mixograph parameters in the evaluation of flour quality. The 642 hard winter wheat flours, collected from federal regional performance nurseries in 1995 and 1996, were analyzed by a conventional and computerized mixograph. Mixograph bandwidths at 6 min (BW6) showed the most significant linear correlation with subjective mixing tolerance scores (r = 0.81, P < 0.1%, n = 642). Prediction models of conventional and experimental baking parameters were developed by continuum regression using computer‐analyzed mixograph parameters of a calibration set (n = 282). The developed models could estimate conventional mixograph mixing time and tolerance scores, baking water absorption and mixing time, and bread loaf volume, showing R² values of 0.86, 0.74, 0.68, 0.80, and 0.51, respectively, for a validation set (n = 380). These results indicated that computer‐analyzed mixograph parameters could be applied to develop prediction models to be used for flour quality evaluation in wheat breeding programs.     

Predicting Protein Composition,Biochemical Properties,and Dough-Handling Properties of Hard Red Winter Wheat Flour by Near-Infrared Reflectance

Breadmaking quality in wheat is one of several considerations that plant breeders face when developing new cultivars. In routine breeding programs, quality is assessed by small-scale dough-handling and bake tests, and to some extent, by biochemical analysis of gluten proteins. An alternative, not yet fully examined, method for wheat flour quality assessment is near-infrared reflectance (NIR) spectrophotometry. The present study was performed on 30 genotypes of hard red winter wheat grown during two crop years at eight to nine locations in the Great Plains area of the United States. Biochemical testing consisted of measuring protein fractions from size-exclusion HPLC (M _r > 100k, M _r 25–100k, and M _r < 25k designated as glutenin, gliadins, and albumin and globulins, respectively), pentosan content, and SDS sedimentation volume. Dough-handling properties were measured on a mixograph and recorded as the time to peak dough development, the peak resistance, the width of the mixing curve, and the width of the curve at 2 min past peak. Partial least squares analyses on diffuse NIR spectra (1,100–2,498 nm) were developed for each constituent or property. When applied to a separate validation set, NIR models for glutenin content, gliadin content, SDS sedimentation volume, and mixograph peak resistance demonstrated reference vs. predicted correlations ranging from r = 0.87 to r = 0.94. Such models were considered sufficiently accurate for screening purposes in breeding programs. NIR spectra were responsive to each constituent or property at a level higher than expected from a correlation between the constituent or property and protein content (recognizing that protein content is modeled by NIR with high accuracy).     

Levels of Protein and Protein Composition in Hard Winter Wheat Flours and the Relationship to Breadmaking

Protein and protein fractions were measured in 49 hard winter wheat flours to investigate their relationship to breadmaking properties, particularly loaf volume, which varied from 760 to 1,055 cm³ and crumb grain score of 1.0–5.0 from 100 g of flour straight‐dough bread. Protein composition varied with flour protein content because total soluble protein (SP) and gliadin levels increased proportionally to increased protein content, but albumins and globulins (AG), soluble polymeric proteins (SPP), and insoluble polymeric protein (IPP) levels did not. Flour protein content was positively correlated with loaf volume and bake water absorption (r = 0.80, P < 0.0001 and r = 0.45, P < 0.01, respectively). The percent SP based on flour showed the highest correlation with loaf volume (r = 0.85) and low but significant correlation with crumb grain score (r = 0.35, P < 0.05). Percent gliadins based on flour and on protein content were positively correlated to loaf volume (r = 0.73, P < 0.0001 and r = 0.46, P < 0.001, respectively). The percent IPP based on flour was the only protein fraction that was highly correlated (r = 0.62, P < 0.0001) with bake water absorption followed by AG in flour (r = 0.30, P < 0.05). Bake mix time was correlated positively with percent IPP based on protein (r = 0.86) but negatively with percent SPP based on protein (r = ‐0.56, P < 0.0001).     

Mixograph Absorption Determination by Response Surface Methodology

The advantages of using the mixograph to determine dough mixing properties include minimal flour requirements (2–35 g) and an efficient mixing process that rapidly resolves mixing peaks. A disadvantage to using this instrument is that it lacks an objective absorption measurement. This article describes an analysis system, RsMix, that objectively determines water absorption and statistically evaluates (R² and probability values) this measurement. The RsMix system also exports files that produce response surface plots. These plots illustrate the response of the dough to different combinations of mixing time and absorption. Each data set analyzed by the RsMix system was composed of an absorption series run at 2% absorption increments. The RsMix system attempts to maximize power input over data collected over absorption and time ranges. These data can be input manually or automatically acquired from MixSmart data files. To measure the precision of the RsMix system, a replicated absorption series composed of four to six different amounts of added water was analyzed. Depending on the mixer and formulation used, calculated standard deviations for optimum absorptions ranged from 0.8 to 2.0%. A regression comparing flour protein content to 2-g mixograph absorption had r² = 0.80. A similar regression comparing 2-g mixograph to 50-g farinograph absorption had r² = 0.81. Mixograph parameters could also account for 90% or more of the variation in bake absorption, bread volume, and total bread scores.     

Predicting Wheat Quality Characteristics and Functionality Using Near‐Infrared Spectroscopy

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 (R² > 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 R² > 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.     

Free Lipids in Air‐Classified High‐Protein Fractions of Hard Winter Wheat Flours and Their Effects on Breadmaking Quality

Free lipids (FL) were extracted from straight‐grade flours (SF) and the air‐classified high‐protein fractions (ACHPF) of nine hard winter wheats. The mean values of FL contents in 10 g (db) SF and ACHPF were, respectively, 92.8 and 178.5 mg for total FL, 74.1 and 141.9 mg for nonpolar lipids (NL), 12.8 and 20.9 mg for glycolipids (GL), and 4.9 and 12.0 mg for phospholipids (PL). FL compositions of SF and ACHPF showed nonsignificant differences in NL (80.7 and 81.1% of the FL) but significant differences in GL (13.9 and 12.0% of the FL) and PL (5.4 and 6.9% of the FL). Fortification of SF with ACHPF by blending to reach 13% protein content increased gluten quantity and thereby loaf volume but decreased gluten index, loaf volume regression, and crumb grain scores. NL contents showed significant relationships with dry gluten contents (r = 0.79) and gluten index (r = ‐0.83) values, indicating that high NL content in ACHPF could decrease gluten quality of fortified flours. Thus, an optimum balance should be maintained during fortification.     

Observations on the Quality Characteristics of Waxy (Amylose‐Free) Winter Wheats

Previous investigations have suggested waxy (amylose‐free) wheats (Triticum aestivum L.) possess weak gluten properties and may not be suitable for commercial gluten extraction. This limitation could prevent the use of waxy wheat as a source of unique starch, because gluten is a by‐product of the wheat starch purification process. Fifty waxy wheat lines were used to determine the extent to which gluten protein and other grain quality related traits might vary and, consequently, allow the development of waxy wheat with acceptable gluten properties. Among the waxy lines, significant variation was observed for all measured quality traits with the exception of flour protein concentration. No waxy entries statistically equaled the highest ranking nonwaxy entry for grain volume weight, falling number, flour yield, or mixograph mix time. No waxy lines numerically exceeded or equaled the mean of the nonwaxy controls for falling number, flour yield, or mixograph mix time. For grain and flour protein related variables, however, many waxy lines were identified well within the range of acceptability, relative to the nonwaxy controls used in this study. Approximately 50% of the waxy lines did not differ from the highest ranking nonwaxy cultivar for grain and flour protein concentrations. Forty‐three (86%) of the tested waxy lines were not sig‐nificantly different from the nonwaxy line with the highest mixograph mixing tolerance, 22/50 (44%) of the waxy wheat lines did not differ from the highest ranking nonwaxy line in gluten index scores, and 17/50 (34%) did not differ from the highest ranking nonwaxy line in extracted wet gluten. All waxy experimental lines produced gluten via Glutomatic washing. The quality of the gluten, as measured both by mixograph and gluten index, varied widely among the waxy lines tested. These observations suggest that weak gluten is not a natural consequence of the waxy trait, and waxy cultivars with acceptable gluten properties can be developed.     

Effect of Kernel Size and Mill Type on Protein,Milling Yield,and Baking Quality of Hard Red Spring Wheat

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end‐use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, and small kernels, as well as unsorted kernels. The four fractions were milled in three roller mills: Brabender Quadrumat Jr., Quadrumat Sr., and Bühler MLU‐202 laboratory mills. Large kernels had consistently higher flour yield than small kernels across mills, with the Quadrumat Jr. mill showing the lowest flour yield. Mill type and kernel size significantly affected variation in flour protein molecular weight distribution. When compared with larger kernels, flour milled from the small‐kernel fraction contained a higher gliadin fraction and SDS‐unextractable high‐molecular‐weight polymeric proteins, which had positive correlations with bread loaf volume (r = 0.61, P < 0.05) and mixograph peak time (r = 0.84, P < 0.001). Overall, small kernels could contribute to enhancing flour breadmaking quality while having a detrimental effect on milling yield.     

Relationship Between Soft Wheat Flour Physicochemical Composition and Cookie‐Making Performance

Nowadays in Argentina, cookies, crackers, and cakes are made of flour obtained from bread wheat with additives or enzymes that decrease the gluten strength but increase production costs. The present research work aims to study the relationship between flour physicochemical composition (particle size average [PSA], protein, damaged starch [DS], water soluble pentosans [WSP], total pentosans [TP], and gluten), alkaline water retention capacities behavior, solvent retention capacities profile (SRC) and cookie‐making performance in a set of 51 adapted soft wheat lines with diverse origin to identify better flour parameters for predicting cookie quality. Cookie factor (CF) values were 5.06–7.56. High and significant negative correlations between sucrose SRC (–0.68), water SRC (–0.65), carbonate SRC (–0.59), and CF were found, followed by lactic SRC that presented a low negative but significant correlation (r = –0.35). The flour components DS (r = –0.67), WSP (r = –0.49), and TP (r = –0.4) were negatively associated to CF. PSA showed a negative correlation with CF (r = –0.43). Protein and gluten were the flour components that affected cookie hardness, but no significant correlation were found with pentosan or DS content. A prediction equation for CF was developed. Sucrose SRC, PSA, and DS could be used to predict 68% of the variation in cookie diameter. The cluster analysis was conducted to assess differences in flour quality parameters among genotypes based on CF. Clusters 1 and 4 were typified by lower CF (5.70 and 5.23, respectively), higher DS, pentosan content, and SRC values. Cluster 2 with a relative good CF (6.47) and Cluster 3 with the best cookie quality, high CF (7.32) and low firmness, and the lowest DS, TP, WSP content, and sucrose SRC values.     

Correlation of Quality Parameters with the Baking Performance of Wheat Flours

The baking performance of a set of flours from 13 wheat cultivars was determined by means of two different microscale baking tests (10 g of flour each). In the micro‐rapid‐mix test the dough was mixed for a fixed time at a high speed, whereas the microbaking test used mixing to optimum dough consistency in a microfarinograph. Quality parameters such as sedimentation value, crude protein content, dough and gluten extension data, and microfarinograph data were also determined. Finally, quality‐related protein fractions (gliadins, glutenins, SDS‐soluble proteins, and glutenin macropolymer) were quantitated by extraction/HPLC methods with reversed‐phase and gel‐permeation columns. All quality parameters were correlated with the bread volumes of both baking tests. The results demonstrated that the microbaking test (adapted mixing time) was much more closely related to the quality parameters than the micro‐rapid‐mix test (fixed mixing time), which hardly showed any correlation. Among the standard quality parameters, only the crude protein content showed a medium correlation with the bread volume of the microbaking test (r = 0.71), whereas the contents of gliadins (r = 0.80), glutenins (r = 0.76), and glutenin macropolymer (r = 0.80) appeared to be suitable parameters to predict the baking performance of wheat flour. All other quality parameters were not or were only weakly correlated and unsuitable for predicting baking performance.     

Solvent Retention Capacity Values in Relation to Hard Winter Wheat and Flour Properties and Straight‐Dough Breadmaking Quality

Solvent retention capacity (SRC) was investigated in assessing the end use quality of hard winter wheat (HWW). The four SRC values of 116 HWW flours were determined using 5% lactic acid, 50% sucrose, 5% sodium carbonate, and distilled water. The SRC values were greatly affected by wheat and flour protein contents, and showed significant linear correlations with 1,000‐kernel weight and single kernel weight, size, and hardness. The 5% lactic acid SRC value showed the highest correlation (r = 0.83, P < 0.0001) with straight‐dough bread volume, followed by 50% sucrose, and least by distilled water. We found that the 5% lactic acid SRC value differentiated the quality of protein relating to loaf volume. When we selected a set of flours that had a narrow range of protein content of 12–13% (n = 37) from the 116 flours, flour protein content was not significantly correlated with loaf volume. The 5% lactic acid SRC value, however, showed a significant correlation (r = 0.84, P < 0.0001) with loaf volume. The 5% lactic acid SRC value was significantly correlated with SDS‐sedimentation volume (r = 0.83, P < 0.0001). The SDS‐sedimentation test showed a similar capability to 5% lactic acid SRC, correlating significantly with loaf volume for flours with similar protein content (r = 0.72, P < 0.0001). Prediction models for loaf volume were derived from a series of wheat and flour quality parameters. The inclusion of 5% lactic acid SRC values in the prediction model improved R² = 0.778 and root mean square error (RMSE) of 57.2 from R² = 0.609 and RMSE = 75.6, respectively, from the prediction model developed with the single kernel characterization system (SKCS) and near‐infrared reflectance (NIR) spectroscopy data. The prediction models were tested with three validation sets with different protein ranges and confirmed that the 5% lactic acid SRC test is valuable in predicting the loaf volume of bread from a HWW flour, especially for flours with similar protein contents.     

Textural Comparisons of Gluten‐Free and Wheat‐Based Doughs,Batters, and Breads

Studies were conducted with two newly developed gluten‐free bread recipes. One was based on corn starch (relative amount 54), brown rice (25), soya (12.5), and buckwheat flour (8.5), while the other contained brown rice flour (50), skim milk powder (37.5), whole egg (30), potato (25), and corn starch (12.5), and soya flour (12.5). The hydrocolloids used were xanthan gum (1.25) and xanthan (0.9) plus konjac gum (1.5), respectively. Wheat bread and gluten‐free bread made from commercial flour mix were included for comparison. Baking tests showed that wheat and the bread made from the commercial flour mix yielded significantly higher loaf volumes (P < 0.01). All the gluten‐free breads were brittle after two days of storage, detectable by the occurrence of fracture, and the decrease in springiness (P < 0.01), cohesiveness (P < 0.01), and resilience (P < 0.01) derived from texture profile analysis. However, these changes were generally less pronounced for the dairy‐based gluten‐free bread, indicating a better keeping quality. Confocal laser‐scanning microscopy showed that the dairy‐based gluten‐free bread crumb contained network‐like structures resembling the gluten network in wheat bread crumb. It was concluded that the formation of a continuous protein phase is critical for an improved keeping quality of gluten‐free bread.     

Evaluation of a New Viscometer Performance in Predicting the Technological Quality of Soft Wheat Flour

Gluten aggregation properties were investigated by means of the GlutoPeak device, a viscometer recently proposed as a rapid and sensitive test for measurement of wheat flour technological performance. In this study, 62 soft wheat flour samples of different quality and end use were utilized to evaluate if the GlutoPeak parameters could adequately predict chemical and rheological characteristics of soft wheat flour dough, that is, protein content measured by the Kjeldahl method, dough strength measured by a Chopin alveograph, and dough stability and water absorption measured by a Brabender farinograph. Linear correlation analysis showed that most GlutoPeak curve parameters were strongly correlated with protein content, dough strength, and water absorption. The statistical models, obtained by a stepwise multiple regression method, showed the GlutoPeak device to be a promising tool to characterize wheat flour (R_adj² = 0.84 for protein content, R_adj² = 0.71 for dough strength, and R_adj² = 0.67 for water absorption). The rather high accuracy of the prediction models for the three mentioned parameters confirmed that GlutoPeak parameters are well correlated with other frequently used flour quality parameters and are able to describe flour technological performance.     

Variation and Correlation of Protein Molecular Weight Distribution and Semolina Quality Parameters for Durum Genotypes Grown in North Dakota

This research assessed variation of protein molecular weight distribution (MWD) parameters and their correlations with quality characteristics of semolina samples that were obtained from durum genotypes grown in North Dakota. Sodium dodecyl sulfate buffer extractable and unextractable proteins in semolina were analyzed for MWD by size‐exclusion HPLC with a microbore column. ANOVA indicated that quantitative variations of all the HPLC protein fractions were significantly (P < 0.001) influenced by growing environments. The extractable and unextractable gluten proteins correlated differently with semolina gluten characteristics. Both gluten index and mixograph classification showed positive correlations (P < 0.05) with unextractable polymeric proteins and negative correlations (P < 0.05) with extractable gliadins and polymeric proteins. Quantitative variations of gluten proteins greatly influenced spaghetti cooking characteristics. Specifically, cooked spaghetti firmness (CSF) had high and positive simple linear correlations (P < 0.001) with quantity of gluten proteins in both extractable and unextractable fractions. However, a qualitative MWD parameter, percentage of the extractable gliadins in total protein, had a negative genotypic correlation with CSF (r = –0.81, P < 0.01), whereas percentage of the unextractable polymeric proteins had a positive genotypic correlation (r = 0.75, P < 0.01). Those two MWD parameters also showed significant (P < 0.05) variations for genotypes, indicating that they might be useful for screening durum genotypes for pasta cooking quality.     

Rapid Quality Assessment of Wheat Cultivars Registered in Poland Using the 2‐g Mixograph and Multivariate Statistical Analysis

Baking and 2‐g mixograph analyses were performed for 55 cultivars (19 spring and 36 winter wheat) from various quality classes from the 2002 harvest in Poland. An instrumented 2‐g direct‐drive mixograph was used to study the mixing characteristics of the wheat cultivars. A number of parameters were extracted automatically from each mixograph trace and correlated with baking volume and flour quality parameters (protein content and high molecular weight glutenin subunit [HMW‐GS] composition by SDS‐PAGE) using multiple linear regression statistical analysis. Principal component analysis of the mixograph data discriminated between four flour quality classes, and predictions of baking volume were obtained using several selected mixograph parameters, chosen using a best subsets regression routine, giving R² values of 0.862–0.866. In particular, three new spring wheat strains (CHD 502a‐c) recently registered in Poland were highly discriminated and predicted to give high baking volume on the basis of two mixograph parameters: peak bandwidth and 10‐min bandwidth.     

Estimation of Free Glycolipids in Wheat Flour by HPLC

The chloroform-acetone mixture (4:1, v/v) was an effective solvent for eluting the nonpolar lipid fraction, including free fatty acids, from the polar lipid (glycolipid and phospholipid) fractions from free lipids of 21 hard winter wheat flours using a solid-phase extraction system. Amounts of monogalactosyldiglycerides (MGDG) and digalactosyldiglycerides (DGDG) in the glycolipid fraction were determined by normal-phase HPLC with a gradient system using an evaporative light-scattering detector (ELSD) and a diode array detectors (DAD). Unsaturated fatty acids showed higher UV absorbances from 200 to 213 nm when compared with saturated palmitic acid. However, significant linear correlation coefficients were obtained between the peak areas measured by a DAD and GL contents determined by an ELSD, suggesting that fatty acid composition of flour GL could be fairly constant. Using an ELSD as a reference, equations for determination of MGDG or DGDG quantities were derived from the peak areas of a DAD by multivariate regression methods. Determination of MGDG and DGDG quantities was also possible using only a DAD.