Association of Barley Kernel Hardness with Physical Grain Traits and Food Processing Parameters

Kernel hardness is not a well‐characterized food quality trait in barley. Unlike wheat, not much is known about the effect of barley kernel hardness on food processing. Ten barley genotypes differing in single kernel characterization system hardness index (SKCS‐HI) (30.1–91.2) of dehulled kernels were used to determine the association of barley HI with other physical grain traits and food processing parameters. Thousand kernel weight (TKW) values of 10 genotypes were 29.7–38.1 g. Values for bulk density of grains were 721.1–758.9 kg/m³. Crease width and depth values were 0.9–1.3 mm and 0.4–0.7 mm, respectively. Barley HI showed no significant association with TKW, bulk density, or kernel crease dimensions. Kernel loss due to pearling after 325 sec of abrasion was 28.8–38.4% and showed significant negative correlation with HI (r = –0.87, P < 0.01). Proportion of barley flour particles >106 μm had values of 34.5–42.0%, and starch damage values were 1.8–4.5% among those 10 barley genotypes. HI showed significant positive correlations with both proportion of barley flour particles >106 μm (r = 0.93, P < 0.01) and starch damage (r = 0.93, P < 0.01). Water imbibition of barley kernels and cooked kernel hardness did not show significant correlation with HI.     

Evaluation of the Single Kernel Characterization System (SKCS) for Measurement of Sorghum Grain Attributes

The single kernel characterization system (SKCS) has been widely used in the wheat industry, and SKCS parameters have been linked to end‐use quality in wheat. The SKCS has promise as a tool for evaluating sorghum grain quality. However, the SKCS was designed to analyze wheat, which has a different kernel structure from sorghum. To gain a better understanding of the meaning of SKCS predictions for grain sorghum, individual sorghum grains were measured for length, width, thickness (diameter), and weight by laboratory methods and by the SKCS. SKCS predictions for kernel weight and thickness were highly correlated to laboratory measurements. However, SKCS predictions for kernel thickness were underestimated by ≈20%. The SKCS moisture prediction for sorghum was evaluated by tempering seven samples with varying hardness values to four moisture levels. The moisture contents predicted by SKCS were compared with a standard oven method and, while correlated, SKCS moisture predictions were less than moisture measured by air oven, especially at low moisture content. Finally, SKCS hardness values were compared with hardness measured by abrasive decortication. A moderate (r = 0.67, P < 0.001) correlation was observed between the hardness measurements. The SKCS predictions of kernel weight and diameter were highly correlated with laboratory measurement. Moisture prediction, however, was substantially lower by the SKCS than as measured by an air oven method. The SKCS should be suitable for measuring sorghum grain attributes. Further research is needed to determine how SKCS hardness predictions are correlated to milling properties of sorghum grain.     

Comparison of Quality Characteristics and Breadmaking Functionality of Hard Red Winter and Hard Red Spring Wheat

Various whole‐kernel, milling, flour, dough, and breadmaking quality parameters were compared between hard red winter (HRW) and hard red spring (HRS) wheat. From the 50 quality parameters evaluated, values of only nine quality characteristics were found to be similar for both classes. These were test weight, grain moisture content, kernel size, polyphenol oxidase content, average gluten index, insoluble polymeric protein (%), free nonpolar lipids, loaf volume potential, and mixograph tolerance. Some of the quality characteristics that had significantly higher levels in HRS than in HRW wheat samples included grain protein content, grain hardness, most milling and flour quality measurements, most dough physicochemical properties, and most baking characteristics. When HRW and HRS wheat samples were grouped to be within the same wheat protein content range (11.4–15.8%), the average value of many grain and breadmaking quality characteristics were similar for both wheat classes but significant differences still existed. Values that were higher for HRW wheat flour were color b*, free polar lipids content, falling number, and farinograph tolerance. Values that were higher for HRS wheat flour were geometric mean diameter, quantity of insoluble polymeric proteins and gliadins, mixograph mix time, alveograph configuration ratio, dough weight, crumb grain score, and SDS sedimentation volume. This research showed that the grain and flour quality of HRS wheat generally exceeds that of HRW wheat whether or not samples are grouped to include a similar protein content range.     

Application of the Single‐Kernel Characterization System to Durum Wheat Testing and Quality Prediction

The Single Kernel Characterization System (SKCS 4100) measures single kernel weight, width, moisture content, and hardness in wheat grain with greater speed than existing methods and can be calibrated to predict flour starch damage and milling yield. The SKCS 4100 is potentially useful for testing applications in a durum improvement program. The mean SKCS 4100 kernel weight and moisture values from the analysis of 300 individual kernels gave good correlations with 1,000 kernel weight (r² = 0.956) and oven moisture (r² = 0.987), respectively. Although significant correlations were obtained between semolina mill yield and SKCS 4100 weight, diameter, and peak force, they were all very low and would be of little use for prediction purposes. Similarly, although there were significant correlations between some SKCS 4100 parameters and test weight and farinograph parameters, they too were small. The SKCS 4100 has been calibrated using either the single kernel hardness index or crush force profile to objectively measure the percentage vitreous grains in a sample with reasonable accuracy, and it correlates well with visual determination. The speed and accuracy of the test would be of interest to grain traders. An imprecise but potentially useful calibration was obtained for the prediction of semolina mill yield using the SKCS 4100 measurements on durum wheat. The SKCS 4100 is useful for some traits such as hardness, grain size and moisture for early‐generation (F3) selection in a durum improvement program.     

Molecular Weight Distribution of Proteins in Hard Red Spring Wheat: Relationship to Quality Parameters and Intrasample Uniformity

Molecular weight distribution (MWD) of proteins extracted from hard red spring wheat was analyzed by size‐exclusion HPLC to investigate associations with wheat and breadmaking quality characteristics. Certain protein fractions were related to associations between wheat and breadmaking parameters, specifically when effect of quantitative variation of protein on those parameters was statistically eliminated by partial correlation analysis. SDS‐unextractable high molecular weight polymeric proteins had positive partial correlations with percent vitreous kernel content and breadmaking parameters, including mix time and bread loaf volume. SDS‐extractable protein fractions that were eluted before the primary gliadin peak had positive partial correlations with kernel hardness and water absorption parameters. The proportion of main gliadin fractions in total protein had a negative partial correlation with bread loaf volume and positive correlations with kernel hardness and water absorption parameters. Intrasample uniformity in protein MWD and kernel characteristics was estimated from three kernel subsamples that were separated according to single kernel protein content within individual wheat samples by a single‐kernel near‐infrared sorter. Wheat subsamples were significantly different in protein MWD. Intrasample uniformity in protein MWD did not differ greatly among wheat samples.     

Single‐Kernel Near‐Infrared Analysis for Evaluating Wheat Samples for Fusarium Head Blight Resistance

This report describes a method to estimate the bulk deoxynivalenol (DON) content of wheat grain samples with the single‐kernel DON levels estimated by a single‐kernel near‐infrared (SKNIR) system combined with single‐kernel weights. The described method estimated the bulk DON levels in 90% of 160 grain samples to within 6.7 ppm of DON when compared with the DON content determined with the gas chromatography–mass spectrometry method. The single‐kernel DON analysis showed that the DON content among DON‐containing kernels (DCKs) varied considerably. The analysis of the distribution of DON levels among all kernels and among the DCKs of grain samples is helpful for the in‐depth evaluation of the effect of varieties or fungicides on Fusarium head blight (FHB) reactions. The SKNIR DON analysis and estimation of the single‐kernel DON distribution patterns demonstrated in this study may be helpful for wheat breeders to evaluate the FHB resistance of varieties in relation to their resistance to the spread of the disease and resistance to DON accumulation.     

Development,growth, and nitrogen use of autumn- and spring-sown facultative wheat

Spring-sown crops are expected to have a higher risk of drought during summer in the next decades in Central Europe due to expected climate change. Therefore, a two-year experiment was conducted under Pannonian growing conditions in Eastern Austria to investigate the effect of autumn- and spring-sowing of facultative wheat. Autumn-sowing of facultative wheat enhanced crop development, soil coverage, crop stand height, crop growth rate, and nitrogen (N) utilization efficiency during the vegetation period compared to spring-sowing; duration of growth stages was prolonged and crops were earlier ripe. In contrast, spring-sowing resulted in higher relative growth rates, higher N concentrations of aboveground dry matter, higher relative N uptake rates, and more mineral N in the soil. At harvest, grain yield and yield components ears m^?2 and thousand kernel weight (TKW) were higher in autumn-sown than in spring-sown wheat, resulting thereby in an increased seed yield. Spring-sown wheat had higher N concentrations in grain and in straw. Anyhow, N yield was slightly higher with autumn-sowing due to the higher grain and straw yields. Grain and straw yield, plant stand height, ears m^?2, and TKW were impaired in the second experimental year by a severe drought for both sowing dates as well as N concentrations and N yields of grain and straw, partial factor N use efficiency and N utilization efficiency. But the yield components harvest index, grains m^?2, and grains ear^?1 were strongly impaired with spring-sowing under drought conditions. Thus, autumn-sowing of wheat resulted in higher yield stability across both years, based on these yield components highlighting possible benefits of autumn-sowing with expected summer drought under climate change.     

基于微波反射法的谷物含水率在线检测装置研制

针对稻麦联合收割机在收获作业时难以对小麦、水稻等谷物的含水率进行准确在线测量的问题,该文基于微波反射法研究了谷物含水率在线检测方法,建立了稻麦含水率检测模型,研发了一种稻麦联合收割机谷物含水率在线检测装置。该装置采用微波测量模块对稻麦含水率进行非接触式测量,设计了电压转换电路将微波参数转换成电压信号,采用滑动平均滤波算法进行信号滤波,最后通过标定试验所建立的含水率检测模型进行稻麦含水率计算,计算结果经CAN总线通讯在显示器上实时显示。基于上述理论研究、技术开发和结构设计对所研制的谷物含水率在线检测装置分别进行了室内静态试验和田间收割试验研究,试验结果表明:检测装置的对稻麦含水率的测量范围为14%～34%,在室内静态试验和田间收割试验中的性能标准差分别为0.458 3%和1.078 0%,相对误差分别在2.5%和5%左右,具有良好的准确性与实用性。     

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.     

Relationship of Kernel Size to Flour Water Absorption for Canada Western Red Spring Wheat

Canada Western Red Spring (CWRS) wheat exhibits consistent positive relationships between kernel weight and farinograph and baking water absorption. These relationships are sufficiently robust to be statistically significant (P < 0.05) for historical Canadian Grain Commission harvest survey data generated one year apart for 17 years, and for historical data on individual cultivars in advanced Canadian wheat breeding trials, also generated annually. Verification of the relationships were obtained by analyzing different kernel size fractions obtained by sieving CWRS harvest survey samples and pure CWRS cultivars from various origins. In all cases, highly significant positive relationships were observed between kernel size and water absorption. The relationships were evident for individual streams from pilot‐scale millings of sized fractions from CWRS harvested in two different years. Strong correlations of kernel weight to farinograph and baking absorption also were shown for sized fractions from commercial samples of American Dark Northern Spring and Australian Prime Hard wheat. The strong statistical association between kernel size and water absorption could not be explained on the basis of wheat hardness (flour starch damage), protein content, or dough strength. In view of the importance of flour water absorption to bakers, further investigation is warranted to identify the cause for the association between large kernel size and high water absorption.     

Influence of Microwave Heating on Biological Activities and Electrophoretic Pattern of Albumin Fraction of Wheat Grain

Microwave treatment is a sufficiently alternative technique to be applied widely in food production and cereals protection against insect pests. Water‐soluble proteins were washed out from microwave‐heated wheat grain for the purpose of assaying the influence on biological activities, reducing sugars content, and SDS‐PAGE electrophoresis proteins patterns. The differences between microwave‐heated grain samples were verified by analysis of variance at the P ≤ 0.05 level of significance. Microwave heating of wheat grain within the temperature range of 28–98°C caused a decrease in water‐extractable proteins, statistically significant when grain temperature reached 79 and 98°C. Statistically significant increase in reducing sugars content was noted in grain samples heated only to 48°C; a decrease was noted above this temperature. All biological activities studied (amylolytic and inhibition activities against α‐amylases from insects (Sithophilus granarius L., Tribolium confusum Duv., Ephestia kuehniella Zell.), human saliva, hog pancreas, antitryptic activity) were distinctly diminished in grain samples heated to 79°C. At the highest grain temperature of 98°C, the loss of all biological activities were even more pronounced due to denaturation of ≈45% of extractable proteins. Among the wheat albumins studied by SDS‐PAGE, only eight and nine protein bands were detected in the grains heated to 98 and 28°C, respectively, whereas 12 bands were present in the control. The highest number of protein bands (13) was found in the grains heated to 48 and 64°C, respectively.     

不同栽培模式下两个旱地小麦品种籽粒灌浆特性与产量构成分析

在长武旱塬地区通过大田试验,研究了该地区主栽的两个小麦品种长武134及长旱58在不同栽培模式下,籽粒灌浆特性、旗叶叶绿素含量与产量的关系,并对产量构成及灌浆各参数进行分析。结果表明,千粒重与灌浆持续天数T_d、平均灌浆速度V_a、灌浆渐增期天数T₁、灌浆速增天数T₂、最大灌浆速度V_m均呈显著相关,通过对不同栽培模式下旗叶叶绿素含量的比较发现,有机肥与化肥的互作,可以适当延长灌浆持续时间,使籽粒获得较高的千粒重,提高了小麦的水分利用效率和收获指数。通过比较不同栽培模式下籽粒千粒重、产量的差异表明有机肥与化肥互作的栽培模式较只使用化肥的栽培模式籽粒的千粒重、产量和水分利用效率分别增加了7.527%,10.74%和23.85%。对产量构成进行分析,粒重是影响籽粒产量的主要因素。     

Characterization of a Unique “Super Soft” Kernel Trait in Wheat

Kernel texture in wheat (Triticum sp.) is central to end‐use quality and utilization. Here we report the discovery of a novel soft kernel trait in soft white winter wheat (T. aestivum L.). Two heritable kernel phenotypes were selected among F₃‐derived sibs, hereafter designated “normal soft” (wild‐type) and “super soft.” Normal soft lines exhibited single kernel characterization system (SKCS) hardness index (HI) values typical of soft wheat (HI ≈ 20), whereas the super soft lines were unusually soft (HI ≈ 5). Under some environments, individual super soft lines exhibited HI values as low as HI = –4. The super soft trait was manifested in reduced SKCS kernel texture and higher break flour yields, with some increase in sodium carbonate SRC (solvent retention capacity) values and sponge cake volumes. Straight‐grade flour yield, flour ash, milling score, and cookie diameter were largely unaffected. With the possible exception of the sodium carbonate SRC values, we observed no indication that the super soft trait conferred any negative aspects to commercial soft wheat quality. As such, the super soft trait may provide wheat breeders with new opportunities to modify the end‐use quality of wheat.     

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.     

Effects of Roll Gap,Kernel Shape,and Moisture on Wheat Breakage Modeled Using the Double Normalized Kumaraswamy Breakage Function

Flour milling separates endosperm from bran through repeated roller milling and sifting, in which the size distribution of particles produced by the initial breakage of the wheat kernels critically affects the process. The double normalized Kumaraswamy breakage function (DNKBF), previously developed to describe wheat breakage during roller milling, was extended to refine the modeling of the effect of roll gap on breakage. The DNKBF describes two populations of particles arising from roller milling of wheat, a narrow peak of mid‐sized particles and a wider distribution of both small and very large particles. A new dataset was obtained from milling a set of wheat samples bred to give a range of shapes by cross‐breeding a conventional wheat, Cappelle, with an almost spherical wheat, Triticum sphaerococcum. A residual analysis showed a statistically significant effect of kernel shape on breakage using this new dataset. This analysis supports earlier suggestions that more elongated kernels break to give slightly larger particles than more spherical kernels of equivalent hardness, because of the relatively greater bran content of elongated kernels. The extended DNKBF was also used to model effects of moisture content, showing a distinct disjunction at around 16% moisture that aligns with commercial practice for wheat milling.     

Cooking behavior of rice in relation to kernel physicochemical and structural properties

A set of 27 rice varieties were evaluated for their morphological grain characteristics (length, width, thickness, thousand kernel weight, TKW), chemical composition (amylose, protein, and ash content) and starch properties (gelatinization temperature and enthalpy, amylose-lipid complex). In addition, cell walls were characterized by the arabinoxylan and beta-glucan contents. A rapid method for determining optimum rice cooking time was developed based on the swelling ratio; a fixed value of 2.55 gave a gelatinization level of 95% assessed by differential scanning calorimetry and translucence testing. Optimum cooking time appears positively correlated with kernel thickness and TKW but also with ash content. Confocal laser and scanning electron microscope observation of uncooked rice grains revealed different structural features (cell size) and fracture behavior: for some cultivars, the fracture showed ruptured cells, whereas for others most cells were intact. These structural differences, which may be linked to pectin content, could partly explain rice kernel cooking behavior.     

硫肥对小麦蛋白质组分及产量的影响

试验在高肥力而硫素极缺的土壤上进行了试验,在施用常规氮磷钾肥料的基础上,比较不同小麦品种施硫肥与不施硫肥对小麦蛋白质组分及产量的影响。结果表明:在常规肥料措施下增施硫肥,提高了小麦营养体及籽粒中的含氮量,显著提高了籽粒中醇溶蛋白及总蛋白含量,而且不同蛋白质含量的小麦对硫肥的反应存在差异.施用硫肥极显著降低了千粒重和容重,产量也有所下降,但未达显著水平。     

Variation in Kernel Hardness and Associated Traits in U.S. Barley Breeding Lines

Kernel hardness is an important trait influencing postharvest handling, processing, and food product quality in cereal grains. Though well‐characterized in wheat, the basis of kernel hardness is still not completely understood in barley. Kernels of 959 barley breeding lines were evaluated for hardness using the Single Kernel Characterization System (SKCS). Barley lines exhibited a broad range of hardness index (HI) values at 30.1–91.9. Distribution of kernel diameter and weight were 1.7–2.9 mm and 24.9–53.7 mg, respectively. The proportion of hull was 10.2–20.7%. From the 959 breeding lines, 10 hulled spring barley lines differing in HI values (30.1–91.2) were selected to study the associations of HI with proportion of hull, kernel weight, diameter, vitreousness, protein, β‐glucan, and amylose content. Vitreousness, evaluated visually using a light box, showed a clear distinction between hard and soft kernels. Hard kernels appeared translucent, while soft kernels appeared opaque when illuminated from below on the light box. Kernel brightness (L*), determined as an indicator of kernel vitreousness, showed a significant negative correlation (r = –0.83, P < 0.01) with HI. Protein, β‐glucan, amylose content, proportion of hull, kernel weight, and diameter did not show any significant association with HI.     

Effect of Moisture Content on the Viscoelastic Properties of Individual Wheat Kernels Evaluated by the Uniaxial Compression Test Under Small Strain

Wheat product quality is related to its physicochemical properties and to the viscoelastic properties of the kernel. The aim of this work was to evaluate the viscoelastic properties of individual wheat kernels using the uniaxial compression test under small strain (3%) to create experimental conditions that allow the use of the elasticity theory to explain the wheat kernel viscoelasticity and its relationships to physicochemical characteristics, such as weight tests, size, and ash and protein contents. The following viscoelastic properties of the kernels of hard and soft wheat cultivars at two different moisture contents (original and tempered at 15%) were evaluated: total work (W_t), elastic work (W_e), plastic work (W_p), and modulus of elasticity (E). There was a significant decrease in W_t as the moisture content increased. In the soft wheat Saturno, W_t decreased 80% (from 0.217 to 0.044 N·mm) as the moisture content increased. Individual wheat kernels at their original moisture content showed higher W_e than under the tempered condition. W_p increased as the moisture content increased. E decreased as the moisture content increased. The soft wheat Saturno showed the highest decline (54.9%) in E (from 14.18 to 6.39 MPa) as the moisture content increased. There were significant negative relationships between the viscoelastic properties and the 1,000‐kernel weight and kernel thickness. The uniaxial compression test under small strain can be applied to evaluate the viscoelastic properties of individual wheat kernels from different classes and cultivars.     

Segregating Hard Red Winter Wheat into Dough Factor Groups Using Single Kernel Measurements and Whole Grain Protein Analysis

In accordance with the Grain Quality Acts of 1986 and 1990, scientists at Kansas State University are studying the feasibility of implementing a quality-based marketing system for hard red winter (HRW) wheat in the Southern Plains. This research addresses the development of a segregation system that uses the single kernel characterization system and the whole grain near-infrared analyzer to evaluate the milling and baking quality of wheat as a single value called “dough factor”. This single value represents the amount of flour-water dough that can be produced from a given unit of wheat. Samples of HRW wheat (≈100 per location) were collected at five Kansas country elevators during the 1995 and 1996 harvests. After the dough factor was measured for individual samples, the samples were composited into seven dough factor groups to establish binning and segregation strategies and to explore the relationship between wheat quality measurements and dough factor groups. Results showed that dough factor groups were significantly different from each other and that dough factor groups were related (P < 0.05) to increases in test weight, single kernel weight, single kernel size, flour yield, and mixing time. Although locations showed year-to-year variability for test weight, kernel weight, and kernel size, the differences among dough factor groups for these characteristics across locations were consistent, indicating that the mean values within dough factor groups are similar regardless of location. The lack of significant differences in protein content among dough factor groups was attributable to high variability within dough factor groups between years. High protein values were present in low and high dough factor groups, indicating that protein content alone is not a good indicator of wheat quality. Patterns of differences in wheat quality characteristics among dough factor groups suggest that the seven groups studied can be reduced to three groups: <107, 107–112.9, ≥113. This study demonstrates that dough factor as a segregation and marketing tool is related to single kernel characteristics, differentiates wheats of varying quality, and reflects the end-use value of wheat.