Relationships of High Molecular Weight Glutenin Subunit Composition and Molecular Weight Distribution of Wheat Flour Protein with Water Absorption and Color Characteristics of Noodle Dough

Colors of noodle doughs made from hard white winter wheat flours from Oregon were measured at optimum noodle water absorptions (NWA). Partial correlations, removing effect of protein concentration, indicated that NWA had negative relationships with 0 hr L* and 24 hr b*, and positive relationships with 0 and 24 hr a*. Kernel hardness index had positive simple and partial correlations with NWA without any significant (P < 0.05) correlation with color parameters. High molecular weight glutentin subunits (HMW‐GS) significantly (P < 0.05) affected all measured noodle parameters except for 0 hr L*. Covariance analysis, using protein concentration as a covariate, indicated that HMW‐GS significantly affected NWA and a* (P < 0.01). Wheat cultivars with HMW‐GS 17+18 showed significantly higher mean NWA and a* values than those with alternative Glu‐B1 subunits. Protein molecular weight distributions affected noodles, as shown by significant correlations with absorbance areas and % areas of protein size exclusion (SE) HPLC chromatograms. Protein fractions that had positive correlations with redness had negative correlations with yellowness. Applying multivariate analyses to SE‐HPLC data to derive calibration models to predict fresh noodle dough a* and b* values had R² > 0.91 and cross validations values of R² > 0.75.     

Relationship Between Physicochemical Properties of Wheat Flour,Wheat Protein Composition,and Textural Properties of Cooked Chinese White Salted Noodles

Physicochemical properties and protein composition of 39 selected wheat flour samples were evaluated and correlated with the textural properties of Chinese hard‐bite white salted noodles. Flour samples were analyzed for their protein and wet gluten contents, sedimentation volume, starch pasting properties, and dough mixing properties by farinograph and extensigraph. Molecular weight distribution of wheat flour proteins was determined with size‐exclusion (SE) HPLC, SDS‐PAGE, and acid‐PAGE. Textural properties of Chinese hard‐bite white salted noodles were determined through texture profile analysis (TPA). Hardness, springiness, gumminess, and chewiness of cooked noodles were found to be related to the dough mixing properties. Both protein content and protein composition were found to be related to TPA parameters of noodles. The amount of total flour protein was positively correlated to hardness, gumminess, and chewiness of noodles. The absolute amounts of different peak proteins obtained from SE‐HPLC data showed positive correlations with the hardness, gumminess, chewiness, and springiness of noodles. The proportions of these peak proteins were, however, not significantly related to texture parameters. The proportions of low‐molecular‐weight glutenins/gliadins and albumins/globulins, as observed from SDS‐PAGE, were correlated positively and negatively, respectively, to the hardness, gumminess, and chewiness of cooked noodles. Among the alcohol‐soluble proteins (from acid‐PAGE data), β‐gliadins showed strong correlations with the texture properties of cooked noodles. For the selected flour samples, the total protein content of flour had a stronger relationship with the noodle texture properties than did the relative proportion of different protein subgroups. Prediction equations were developed for TPA parameters of cooked noodles with SE‐HPLC and rapid visco analysis data of the 30 flour samples, and it was found that about 75% of the variability in noodle hardness, gumminess, and chewiness values could be explained by protein composition and flour pasting properties combined together. About 50% of the variations in cohesiveness and springiness were accounted for by these prediction equations.     

Milling Quality and White Salt Noodle Color of Chinese Winter Wheat Cultivars

Improvement of milling quality is an important aspect in wheat breeding programs. However, the milling quality of Chinese wheats remains largely unexplored. Fifty‐seven Chinese winter wheat cultivars from four regions were used to investigate the variation of milling quality parameters and to determine the associations between milling quality traits and color of noodle sheet. Substantial variation was presented for all measured parameters in this germplasm pool. Complete soft, hard, and medium‐hard types were observed. Soft wheat and hard wheat show significant differences in flour ash content, flour bran area, and flour color grade. No simple trait can be used to select for flour milling quality. High flour ash content and bran speck area contributed negatively to brightness of dry flour. Correlation coefficients (r) between L* value of dry flour and flour ash content and bran speck area were ‐0.47 and ‐0.65 for hard cultivars, and ‐0.51 and ‐0.72 for soft cultivars, respectively. Flour color grade (FCG) was significantly and positively associated with bran speck area; r = 0.56 and 0.73 for hard and soft wheats, respectively. There was a high correlation between FCG and L* value of flour water slurry (r = ‐0.95). Strong associations were also established between milling quality index (MQI) and FCG, L* value of dry flour, flour‐water slurry, and white salted noodle sheet for both hard and soft wheats. In conclusion, substantial progress could be achieved in improvement of milling quality in Chinese winter wheats through genetic selection, and FCG and MQI could be two important parameters for evaluation of milling quality in breeding programs.     

Cluster Analysis of Historical and Modern Hard Red Spring Wheat Cultivars Based on Parentage and HPLC Analysis of Gluten‐Forming Proteins

Thirty hard red spring (HRS) wheat cultivars released between 1910 and 2013 were analyzed to determine how they cluster in terms of parentage and HPLC analysis of gliadins and unreduced proteins. Markers for reduced height genes were assessed to determine associations between semidwarfism and protein composition, as well as quality characteristics. In terms of parentage, the clusters formed were grouped according to release year and semidwarfism. Farinograph development time and stability showed significant (P ≤ 0.05) differences between clusters, indicating improvement of mixing characteristics over time. Flour ash content was significantly different (P ≤ 0.05) between clusters, indicating improved milling quality. The clusters based on the gliadin reverse‐phase HPLC peak binary data did not group cultivars according to release year and the semidwarf characteristic. However, cultivars were grouped according to year in the absorbance area based dendrogram. The clusters based on absorbance area of size‐exclusion HPLC showed significant (P ≤ 0.05) differences for release year, the semidwarf characteristic, and farinograph stability. Overall, the results indicate that the introduction of reduced height genes accompanied the improvements of dough mixing and breadmaking quality characteristics, without altering the composition of gliadin proteins over the last 100 years of HRS wheat breeding.     

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.     

Size‐Exclusion HPLC of Protein Using a Narrow‐Bore Column for Evaluation of Breadmaking Quality of Hard Spring Wheat Flours

The objective of this study was to investigate whether a narrow‐bore column (NBC) (300 × 4.5 mm, i.d.) improved analyses of unreduced proteins in flour by size‐exclusion HPLC (SE‐HPLC) and subsequent evaluation of breadmaking quality of hard spring wheat flours. Total protein extracts and SDS buffer extractable and unextractable proteins were analyzed by SE‐HPLC. NBC separated proteins in 10 min at a flow rate of 0.5 mL/min with similar resolution to a regular column (300 × 7.8 mm, i.d.) which took 30 min. SE‐HPLC absorbance area (AA) data obtained from an NBC showed comparable or superior repeatability and correlations with flour breadmaking characteristics when compared with those of a regular column. AA values of total protein that were calculated by adding AA values of SDS extractable and unextractable proteins showed greater repeatability and correlations with quality characteristics than those of actual total protein extracts. The improvements including employment of an NBC in SE‐HPLC provide enhancement of rapid quality evaluation and decreased consumption of hazardous organic solvents.     

Effects of Protein Content and Composition on White Noodle Making Quality: Color

Wheat cultivars, representing three winter and three spring wheats were grown in western Canada with six levels of nitrogen fertilizer and flours were prepared from them with an extraction rate of 65%. Using a chromameter, flour color and the color of uncooked white noodle sheets made from these flours with different resting times were assessed. The cooked noodle sheet color was also assessed. While protein content initially declined with added nitrogen and increased with further nitrogen addition, brightness (L*) of flour decreased and redness (a*) and yellowness (b*) increased. Positive correlation coefficients of flour brightness with particle size index (PSI) were also observed. Flour redness (a*) and yellowness (b*) were also affected by flour moisture content, whereas L* values were not significantly correlated with moisture contents. For the uncooked white noodle sheet, as protein content increased brightness decreased but there was an increase in a* and b* values. Thus, the L* value for noodle sheets was negatively correlated with the a* and b* values. The percentages of monomeric protein and soluble glutenin in flour were equal to or better than protein content in relation to most noodle sheet color characters. Uncooked noodle sheet brightness decreased, while redness and yellowness increased with rest time. In general, uncooked white noodle sheets prepared from different wheat flours can be ranked in terms of brightness and yellowness within each level of nitrogen fertilization.     

Measurement of Color,Gloss, and Translucency of White Salted Noodles: Effects of Water Addition and Vacuum Mixing

Sensory evaluation showed panelists could detect small differences in gloss and translucency in boiled white salted noodles (WSN) but sensory evaluation requires significant resources. Methods for the measurement of noodle gloss and translucency in boiled WSN were developed and the effects of hardness, protein, water addition, and vacuum mixing on these visual sensory characteristics and color (as measured by CIE L*, a*, and b*) were investigated. Noodles derived from hard wheats at low flour protein contents were more translucent than noodles from soft wheat flour at low protein. This trend changed at the highest flour protein contents observed. Translucency of the soft wheat noodles increased to levels equal to or exceeding the translucency of high protein hard wheat noodles. Translucency of all noodle varieties increased as flour protein increased. CIE L* decreased, a* increased, and b* increased when water addition to dough increased from 30 to 35%, but there was no further effect on color when water addition was increased to >35% for raw soft and hard WSN. Boiled noodle translucency was significantly increased when water addition to the dough was increased from 35 to 38% and when noodles made from soft wheat flour were mixed under vacuum. Vacuum mixing significantly increased gloss of boiled noodles made from soft wheat flours.     

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.     

Genotypic and Environmental Modification of Asian Noodle Quality of Hard Winter Wheats

The relative effects of environment, genotype, and their interactions on the modification of Asian noodle quality attributes were assessed using 38 winter wheat (Triticum aestivum L.) cultivars and breeding lines grown in replicated trials at three Nebraska locations in harvest year 2000. Noodle color was determined in both white salted and yellow alkaline procedures, and noodle textural features were investigated by producing white salted noodles. Significant environmental, genotypic, and genotype‐by‐environment variation was observed for nearly all initial and 24‐hr noodle color traits in both types of noodles. Significant genotypic effects were observed for several textural traits, while significant environmental effects were observed only for noodle hardness and water uptake. However, among the noodle textural traits, the genotype‐by‐environment interaction was significant only for noodle firmness. High and significant phenotypic correlations were observed between color traits in the two noodle applications. Genetic correlations were of lower magnitude, indicating the possibility of breeding wheats specifically for various noodle color types. Strong negative phenotypic and genetic correlations were observed between flour protein content and noodle brightness (L*) values in both yellow alkaline and white‐salted applications. Textural traits largely were independent of noodle color traits. When significant phenotypic or genetic correlations were observed between variable pairs, invariably similar correlations were observed with flour protein content. Noodle cutting force, cutting area, and final thickness showed strong phenotypic and genetic correlations with each other and with protein content. These variables largely were independent of noodle firmness and hardness, which were, in turn, more dependent on alleles at the wheat wx‐A1 and wx‐B1 (waxy) loci. Noodle firmness was greatest in flours from wild‐type wheats; lines with a null allele only at the wx‐A1 locus did not differ from wild‐type. Softest noodles were produced from lines carrying null alleles at both wx‐A1 and wx‐B1, while lines with a null only at wx‐B1 were intermediate in softness.     

A Comprehensive Genotype and Environment Assessment of Wheat Grain Ash Content in Oregon and Washington: Analysis of Variation

A comprehensive analysis of the variation in wheat grain ash content has not been previously conducted. This study assessed the relative contribution of genotype and environment to variation in ash content, with a particular aim of ascertaining the potential for manipulating the trait using contemporary adapted germplasm. A total of 2,240 samples were drawn from four years of multilocation field plots grown in the wheat production areas of Oregon and Washington states. Genotypes included commercial cultivars and advanced breeding lines of soft and hard winter, and soft and hard spring wheats with red and white kernel color, several soft white club wheats, and one soft white spring waxy wheat cultivar. In addition to ash, protein content, test weight, and Single Kernel Characterization System kernel hardness, weight and size were also measured. In total, 20 separate fully balanced ANOVA results were conducted. Whole model R² values were highly significant, 0.62–0.91. Nineteen of the 20 ANOVA results indicated significant genotype effects, but the effects were not large. In contrast, environment effects were always highly significant with F values often one to two orders of magnitude larger than the genotype F values. The grand mean for all samples was 1.368% ash. For individual data sets, genotype means across environments varied ≈0.1–0.3% ash. The genotypes judged noteworthy because they had the highest least squares mean ash content were OR9900553 and ClearFirst soft white winter, NuHills hard red winter, Waxy‐Pen and Cataldo soft white spring, and WA8010 and Lochsa hard spring wheats. Genotypes with lowest least squares mean ash were Edwin (club) soft white winter, OR2040073H hard red winter, WA7952 soft white spring, and WA8038 hard spring wheats. In conclusion, wheat grain ash is more greatly influenced by crop year and location than by genotype. However, sufficient genotype variation is present to plausibly manipulate this grain trait through traditional plant breeding.     

Measurement of Wheat Starch Granule Size Distribution Using Image Analysis and Laser Diffraction Technology

Starch was isolated from flour of four wheats representing hard red winter (Karl), hard red spring (Gunner), durum (Belfield 3), and spelt (WK 86035‐8) wheat classes. Digital image analysis (IA) coupled with light microscopy was used to determine starch size distributions where the volume of granules was calculated as spherical particles or oblate spheroids. Starch granules were classified into three size ranges: A‐type granules (> 15 μm), B‐type granules (5–15 μm), and C‐type granules (<5 μm). An error was noted in using digital image analysis because the perimeter of some granules touch the edge (PTE) of the field being analyzed. To correct for this error, the PTE granules were manually replaced into the field by measuring their diameters and entering them into the database. The results showed differences in the starch size distributions between the classes of wheat evaluated, as well as the method of analysis. Four laser diffraction sizing (LDS) instruments were used to measure granule distributions of the four classes of wheat. LDS compared with IA resulted in a ≈40% underestimation of the A‐type granule diameter and a ≈50% underestimation of the B‐type granule diameter. A correction factor (adjustment) was developed from IA data to correct LDS analysis. LDS data correlations before adjustments to IA data were R² = 0.02^ns to 0.55***. After adjustment, these correlations improved to R² = 0.81*** to 0.93*** depending on the class of wheat starch evaluated.     

Correlation Between NIR Spectra and RVA Parameters During Germination of Maize

The physical, chemical, and morphological changes of maize seeds during germination were investigated using near‐infrared spectroscopy (NIR) and a method based on the Rapid Visco Analyser (RVA). Near‐infrared spectra provide information about both chemical and physical changes that occur in maize seed. The RVA curves make it possible to follow the process of germination. Four RVA parameters (peak viscosity, final viscosity, trough, and setback) were linearly correlated with germination time (R = 0.64–0.96), while the first derivatives of RVA curves contain specific information about starch structure. Water‐soluble protein (WSP) content of germinated maize seeds was measured using a flow injection analyser; this technique proved to be suitable for monitoring germination by following the mobilization of proteins. WSP and RVA parameters were highly correlated (R² = 0.82–0.95) with predicted values calculated from NIR spectra of dry samples. Strong intercorrelations existed between NIR spectra and viscosity data from the beginning of the swelling and gelatinization process. The NIR and RVA methods and WSP measurements are sensitive tools for investigating the physiological status of maize seeds during germination. Detecting early phase of germination and predicting functional properties rapidly and nondestructively may enhance the importance of NIR spectroscopic methods in agricultural quality control.     

Glutenin Macropolymer in Salted and Alkaline Noodle Doughs

An attempt was made to understand the physicochemical attributes that are the basis of physical differences between alkaline and salted noodle doughs. Flour and dough properties of one soft and three hard‐grained wheat cultivars were observed. Doughs were made with either sodium chloride or sodium carbonate. Each formulation variant was tested at both high and low water additions. Samples for glutenin macropolymer (GMP) isolation were taken at selected noodle dough processing stages. When a 1.67% w/v Na₂CO₃ solution was used for mixograph testing, dough characteristics were radically altered and differences between cultivars were masked. In lubricated squeezing flow (LSF) testing, hard wheat noodle doughs had significantly (P < 0.01) longer relaxation times and higher % residual force values than soft wheat doughs in both the salted and alkaline variants. LSF maximum force and biaxial viscosity were significantly higher in alkaline doughs than salted. GMP extracted from alkaline doughs was gummy and sticky, and was more opaque than GMP from salted doughs. GMP weight decreased sequentially when extracted from samples taken in the active phase (mix, compound, sheet) of noodle dough processing and decreased more in alkaline doughs. GMP weight increased more after 24 hr of dough rest in salted doughs. GMP gel strength was noticeably higher in GMP extracted from alkaline doughs. After dough resting, alkaline GMP gel strength significantly increased, whereas it decreased in GMP from salted doughs, suggesting a role for GMP in the increased stiffness of alkaline noodle doughs.     

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.     

Developing Agreement Between Very Short Flow and Longer Flow Test Wheat Mills

Variations in soft wheat moisture content and kernel texture greatly affected the flour yield produced by a small (short flow) microtest mill (Quadrumat Jr.). An algorithm was developed that adjusted Quadrumat Jr. flour yield to 15% wheat moisture content, precluding the need to temper the wheat before milling. Another algorithm was developed to adjust Quadrumat flour yield relative to a constant softness equivalent (measurement of kernel texture) obtained during the micromilling procedure. Predicting the flour yield of the longer flow Allis‐Chalmers mill from Quadrumat Jr. unadjusted flour yield (R ² = 0.55) was compared with predicting Allis‐Chalmers flour yield from the Quadrumat Jr. adjusted flour yield (R ² = 0.90) across five diverse confirmation data sets. An algorithm to adjust flour yield for softness equivalent was individually developed for soft and hard wheats. Representative micromilling flour yield and softness equivalent data could be produced using as little as 10 g of untempered wheat and ≈3 min of operator time.     

Association of Size‐Exclusion HPLC of Endosperm Proteins with Dough Mixing and Breadmaking Characteristics in a Recombinant Inbred Population of Hard Red Spring Wheat

Variation of polymeric proteins affects wheat end‐use quality. This research investigated associations of polymeric proteins with dough mixing strength and breadmaking characteristics in a near‐homogenous population of 139 recombinant inbred lines (RILs) derived from a cross between two hard red spring wheat breeding lines. Flours from the RILs grown at three locations were analyzed for molecular weight (MW) distribution of SDS‐extractable and unextractable proteins using size‐exclusion HPLC protocol. Correlations were calculated between mixing and breadmaking properties and HPLC absorbance data obtained a 0.01‐min retention time interval to identify protein fractions that had a significant effect on the quality traits. Very high MW polymeric proteins in the unextractable fraction had more distinct and positive associations with dough mixing strength and bread loaf volume than did other polymeric protein fractions, whereas extractable polymeric had negative influence. Consequently, the ratio of unextractable very high MW polymeric proteins to extractable polymeric proteins had greater correlations with dough mixing parameters than other HPLC absorbance area data. Covariate‐effect biplots also visually validated positive effects of unextractable very high MW polymeric proteins and negative effects of extractable polymeric proteins on mixing properties and loaf volume across three growing locations.     

Determination of Rapid Visco Analyser Parameters in Rice by Near‐Infrared Spectroscopy

The objective of these studies was to find alternative Rapid Visco Analyser (RVA) viscoelastic parameters that are predictable by near‐infrared spectroscopy (NIRS). Currently, RVA instruments are widely used in assessing cooking and processing characteristics in rice. The ability to predict RVA parameters by NIRS would be useful in rapidly determining rice pasting qualities, but NIRS does not correlate with the traditional parameters (peak viscosity, final viscosity, breakdown, consistency, and setback). Alternative RVA parameters were sought by collecting RVA and NIRS data for a total of 86 short, medium, and long grain rice cultivars. The amylose contents were 0.41–24.90% (w/w) and protein concentrations were 8.47–11.35% (w/w). Partial least squares (PLS) regression models generated for the entire NIR spectrum against the RVA curve showed viscosity at 212–228 sec (80°C ± 1) varied linearly with NIR spectra (1,100 to ‐2,500 nm). Regression coefficient values were R = 0.961 for 212 sec and R = 0.903 for 228 sec. The PLS correlation coefficient for the prediction of amylose at 212–228 sec decreases along with the NIRS correlation to the same time frame. An opposite trend was observed for the correlation with protein at 212–228 sec. This comparison suggests the importance of amylose and protein in water absorption during this time frame.     

Relationship Between NIR Spectra and RVA Parameters During Wheat Germination

The process of germination in six different wheat cultivars was monitored using NIR spectroscopy and the Rapid Visco Analyser (RVA) method. Near‐infrared spectra provided insight into both chemical and physical changes that occur in the seed, in particular mobilization processes involving carbohydrates. RVA curves also contain physical and chemical information and can be interpreted as physicochemical spectra. The process of germination was followed sensitively through the RVA curves and some rheological parameters (peak viscosity, trough, breakdown, final viscosity, and setback) were highly correlated (R = 0.95–0.98) with predicted values calculated from NIR spectra. Viscosity data calculated from RVA curves collected at 200–480 sec showed the most characteristic changes during the early heat treatment stage of the pasting procedure. Strong intercorrelations were found between viscosity data and NIR spectra from the beginning of the swelling and gelatinization processes in germinating seed. The NIR and RVA methods were sensitive tools for the rapid investigation of the germination process, which is important both from a physiological and technological point of view.     

Detection of Incipient Germination in Malting Barley with a Starch Viscosity Method and a Proposed Ethanol Emission Method

The risk of germination loss during storage in two‐row malting barley can be reduced by identifying grain lots that have undergone incipient germination (IG) during harvest. A method based on starch viscosity that utilizes a Rapid Visco Analyzer (RVA) is currently available for IG analysis. A new potential method, based on the measurement of ethanol emission (EE) from whole barley, may be more efficient and less expensive than the RVA procedure. Three storage experiments were performed: experiments 1 and 3 at 25°C and 80% rh, and experiment 2 in unheated, uninsulated buildings. Decline in germination energy (GE) varied from <1% to about 80% during storage. In experiments 1 and 3, R² for GE loss (expressed as [weeks to 5% loss of GE]^0.2) versus EE was 0.76 in both cases, whereas R² for GE loss versus RVA viscosity was 0.64 and 0.68, respectively. In experiment 2, the greatest loss of GE was associated with high temperatures and relative humidity in July and August. EE performed as well as RVA in the prediction of germination loss in all three trials. Although further evaluation of the EE method is required, it appears to be a promising alternative to the RVA technique.