Canada Western Soft White Spring Research Articles

AAC Paramount soft white spring wheat

AAC Paramount is a soft white spring wheat (Triticum aestivum L.) cultivar that meets the end-use quality specifications of the Canada Western Soft White Spring (CWSWS) class. AAC Paramount is adapted to the irrigated wheat growing regions of southern Alberta and southern Saskatchewan, and for dry land production in the western prairies. On average, AAC Paramount had 6% higher grain yield (under both irrigated and dry land conditions) than the check cultivar AC Andrew. AAC Paramount exhibited excellent straw strength and similar maturity to AC Andrew and Sadash but was 2 d earlier than AAC Indus. Its plant height was taller than both AC Andrew and Sadash but similar to AAC Indus. AAC Paramount exhibited high levels of resistance to the prevalent races of stripe rust, powdery mildew, and loose smut; intermediate reactions to leaf rust, stem rust, and kernel black point; was moderately susceptible to Fusarium head blight and leaf spot diseases, and susceptible to common bunt.

AAC Indus soft white spring wheat

Randhawa, H. S., Graf, R. J. and Sadasivaiah, R. S. 2015. AAC Indus soft white spring wheat. Can. J. Plant Sci. 95: 793–797. AAC Indus is a soft white spring wheat (Triticum aestivum L.) cultivar that meets the end-use quality specifications of the Canada Western Soft White Spring (CWSWS) class. AAC Indus is adapted to the irrigated wheat-growing regions of southern Alberta and southern Saskatchewan, and for dryland production in the western prairies. AAC Indus had higher (P≤0.05) grain yield under dryland conditions than all of the check cultivars. AAC Indus exhibited excellent straw strength and was 2 d later in maturity. AAC Indus exhibited good levels of resistance to the prevalent races of stripe rust and powdery, mildew and intermediate reactions to kernel black point and leaf rust. AAC Indus was susceptible to stem rust, common bunt, loose smut and Fusarium head blight.

AAC Chiffon soft white spring wheat

Randhawa, H. S., Graf, R. J. and Sadasivaiah, R. S. 2014. AAC Chiffon soft white spring wheat. Can. J. Plant Sci. 94: 1303–1308. AAC Chiffon is a soft white spring wheat (Triticum aestivum L.) cultivar that meets the end-use quality specifications of the Canada Western Soft White Spring (CWSWS) class. AAC Chiffon is well-adapted to the irrigated wheat growing regions of southern Alberta and southern Saskatchewan, and for rain-fed production in the western prairies. Based on data from the Western Soft White Spring Wheat Cooperative registration trials from 2008 to 2011, AAC Chiffon exhibited higher grain yield than the check cultivars, similar maturity, and taller stature with moderate straw strength. AAC Chiffon expressed resistance to the prevalent races of stripe rust, intermediate responses to powdery mildew, kernel black point and leaf rust, and susceptibility to stem rust, common bunt, loose smut and Fusarium head blight. Based on end-use quality analysis performed by the Grain Research Laboratory of the Canadian Grain Commission, AAC Chiffon was eligible for grades of CWSWS wheat.

Comparison of Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) Methods for Protein and Hardness Predictions using the Near-Infrared (NIR) Hyperspectral Images of Bulk Samples of Canadian Wheat

The objective of this study was to compare the predictions of the protein contents and hardness values by partial least squares regression (PLSR) and principal components regression (PCR) models for bulk samples of Canadian wheat, which were obtained from different locations and crop years. Wheat samples of Canada Western Red Spring (CWRS), Canada Western Hard White Spring (CWHWS), Canada Western Soft White Spring (CWSWS), and Canada Prairie Spring Red (CPSR) classes were obtained from nearby agricultural farms in the main wheat growing locations in the Provinces of Alberta, Saskatchewan, and Manitoba from 2007, 2008, and 2009 crop years. Wheat samples were conditioned to moisture levels of 13, 16, and 19 % (wet basis) and pooled together for developing the regression models. A database of the near-infrared (NIR) hyperspectral image cubes of bulk samples of wheat classes was created in the wavelength region of 960–1,700 nm with 10 nm intervals. Reference protein contents and hardness values were determined using the Dumatherm method and single kernel characterization system (SKCS), respectively. A tenfold cross-validation was used for the ten-factor partial least squares regression (PLSR) and principal components regression (PCR) models for prediction purposes. Prediction performances of regression models were assessed by calculating the estimated mean square errors of prediction (MSEP), standard error of cross-validation (SECV), and correlation coefficient (r). Using the full data set in the protein prediction study, the ten-component PLSR model gave 1.76, 1.33, and 0.68 for the estimated MSEP, SECV, and r, respectively, which were better than the results for the ten-component PCR model (2.02, 1.42, and 0.62, respectively). For the hardness prediction, the estimated MSEP, SECV, and r values were 147.7, 12.15, and 0.82, respectively, for the ten-component PLSR model using the full data set. The PLSR models prediction performances outperformed the PCR models for predicting protein contents and hardness of wheat.

Comparing Two Statistical Discriminant Models with a Back-Propagation Neural Network Model for Pairwise Classification of Location and Crop Year Specific Wheat Classes at Three Selected Moisture Contents Using NIR Hyperspectral Images

<abstract><title><italic>Abstract.</italic></title> Knowledge of wheat classes and seed moisture contents not only determines the end use of wheat flour but also helps in developing effective storage systems for wheat. Samples of four classes of wheat, including Canada Western Red Spring (CWRS), Canada Western Hard White Spring (CWHWS), Canada Western Soft White Spring (CWSWS), and Canada Prairie Spring Red (CPSR), were obtained from at least five different locations for each class in Manitoba, Saskatchewan, and Alberta for the 2007, 2008, and 2009 crop years and conditioned to moisture contents of 13%, 16%, and 19%. Near-infrared (NIR) hyperspectral images were acquired from bulk samples in the 960-1700 nm wavelength region at 10 nm intervals. The first and second principal component score images were compared for the segmented images of all wheat classes. Pairwise wheat class identification was done using a non-parametric statistical model and a four-layer back-propagation neural network (BPNN) model. The NIR wavelengths of 1260 to 1380 nm had the highest factor loadings for the first principal component using principal component analysis (PCA). The four-layer BPNN model was used for two-class identification of wheat classes. Overall average pairwise classification accuracies of 83.7% were obtained for discriminating wheat samples based on their moisture contents. Average classification accuracies of 83.2%, 75.4%, and 73.1%, were obtained for identifying wheat classes for samples with 13%, 16%, and 19% moisture content (m.c.), respectively. In this study, discriminant models yielded better classification accuracies than BPNN models. Overall average classification accuracies of wheat classes using statistical models were 80.6% for the linear discriminant analysis (LDA) and 76.3% for the quadratic discriminant analysis (QDA). This work showed that NIR hyperspectral imaging can be used as a potential nondestructive tool for classifying moisture-specific wheat classes.

A Canadian Ethanol Feedstock Study to Benchmark the Relative Performance of Triticale: II. Grain Quality and Ethanol Production

Cereal grain ethanol production may need to supplement biomass ethanol production to meet the increasing long‐term demand for ethanol. A study was initiated to benchmark the relative performance of triticale (×Triticosecale ssp.) to wheat (Triticum aestivum L.) classes utilized for ethanol production. Ten cultivars: three triticale, two Canada prairie spring (CPS) wheat, three Canada western soft white spring (CWSWS) wheat, one Canada western red spring (CWRS) wheat, and one Canada western general purpose (CWGP) wheat cultivars were grown at 45 locations across Canada from 2006 to 2009. The locations were subgrouped by agroecological zone for western Canada, by province for Ontario and Quebec, and Charlottetown, PEI, for the Maritimes. The greatest grain yield was usually observed for Hoffman (red spring wheat) followed by triticale cultivars and CWSWS cultivars. Ethanol yield varied by region as a reflection of grain yield, and differences among cultivars generally were: triticale (excluding Tyndal) = Hoffman = CWSWS &gt; CPS &gt; CWRS. Ethanol concentration was least for Tyndal triticale and AC Superb CWRS. Stability assessments indicated that Pronghorn and AC Ultima triticales and Bhishaj CWSWS wheat provide consistent and high ethanol yields. The other CWSWS cultivars, AC Sadash and AC Andrew, had similarly high ethanol yields but were variable, indicating that utilization outside the Parkland and Western Prairies agroecological zones could pose greater risk for ethanol plants over Pronghorn and AC Ultima. Ethanol fermentation plants could therefore increase efficiency by replacing CPS wheat feedstocks with select triticales and potentially improve the consistency of production by using select triticales in regions where CWSWS wheats are less stable.

A Canadian Ethanol Feedstock Study to Benchmark the Relative Performance of Triticale: I. Agronomics

A need has been identified for alternative crop(s) with high grain yield, low grain protein concentration, and high starch for the ethanol industry. The objective of this study was to benchmark the relative performance of triticale (×Triticosecale ssp.) to wheat (Triticum aestivum L.) classes currently utilized for ethanol production. Sixteen cultivars—three triticale, four Canada prairie spring (CPS) wheat, three Canada western soft white spring wheat (CWSWS), two Canada western red spring (CWRS) wheat, and four Canada western general purpose (CWGP) candidate cultivars—were grown at 36 locations across western Canada from 2006 to 2009. The performance of these cereal classes can generally be summarized as triticale = Hoffman (CWGP) = CWSWS &gt; CPS white &gt; CPS red &gt; CWRS for most variables. The triticale and white wheats produced 12 and 13% more grain, respectively, than the hard red spring wheats. Among the triticales, AC Ultima’s and Pronghorn’s yield potential were most notable because they exceeded the CWRS cultivars AC Barrie and AC Superb by an average of 32% and the CPS red cultivars 5700PR and AC Crystal by 18%. The triticales and Hoffman matured later than most other cultivars. Pronghorn consistently displayed low levels of fusarium head blight (FHB), Septoria nodorum blotch, and powdery mildew, but elevated ergot levels were observed for all triticales. We conclude that triticale would be superior to CPS and CWRS wheat and similar to CWSWS in many agronomic traits desired by ethanol fermentation plants and is superior for biomass production.

Prediction of energetic value of wheat and triticale in broiler chicks: A chick bioassay and an in vitro digestibility technique

Variation in apparent metabolizable energy (AME) of diets is a concern in poultry feeding. Thus, predicting variations in AME content of cereal grains is important, because this will allow a more accurate diet formulation. Eight samples, six wheat and two triticale, were collected from western Canada and a modified chick bioassay was used to determine their nitrogen-corrected AME (AMEn) content for broiler chicks. A total of 768 one-d-old male broiler chicks were randomly assigned to 8 dietary treatments (8 cages per treatment and 12 chicks per cage). Birds were fed a starter diet from 0 to 7d of age and experimental diets were fed from 7 to 13d of age. The experimental diets were composed of 80% of test sample and the remaining 20% was a combination of other ingredients held constant across diets. Digestibility of nutrients and energy differed significantly among birds fed the experimental diets. The AMEn values of the test samples determined in the bioassay ranged from 12.7MJ/kg of DM for Canada Western Soft White Spring sample to 14.6MJ/kg of DM for Canada Western Amber Durum sample. Energetic values of the 8 test samples were also evaluated using a two-step in vitro digestibility technique simulating digestive processes in broiler chicks. In vitro AME value of the test samples were calculated and related to in vivo AMEn by regression analysis. The equation for prediction of in vivo AMEn based on in vitro AME was: In vivo AMEn (MJ/kg of DM)=5.4108+0.7016×in vitro AME (R2=0.81, standard error of prediction (SEP)=0.22MJ/kg, P=0.002). Inclusion of other energy-related characteristics of test samples (e.g., starch, ether extract, and crude protein) into the regression equation increased the R2 and decreased the SEP. Specifically, inclusion of neutral detergent fiber, ether extract, starch, and crude protein of samples together with the in vitro AME resulted in the strongest prediction equation for in vivo AMEn (R2=0.99, SEP=0.05MJ/kg, P=0.014). The predicted in vivo AMEn of test samples ranged from 12.7 to 14.5MJ/kg of DM. In conclusion, this in vitro digestibility technique accurately predicted in vivo AMEn of wheat and triticale samples for broiler chickens and can serve as a reference analysis to develop calibration equations for rapid feed quality evaluation methods such as near infrared reflectance spectroscopy (NIRS).

Phenotypic Effects of the Flowering Gene Complex in Canadian Spring Wheat Germplasm

Wheat (Triticum aestivum L.) has inherent genetic potential to synchronize its flowering and maturity to a broad growing period and is therefore one of the most widely adapted and grown food crops. Vernalization and photoperiod response genes are of primary importance to this adaptability. We screened 102 Canadian spring wheat cultivars and/or lines, developed between 1885 and 2008, from the Canada Western Red Spring (CWRS), Canada Prairie Spring Red (CPSR), and Canada Western Soft White Spring (CWSWS) classes and studied their phenotypic response both in the field and the greenhouse. Almost all the hard red cultivars possessed the Vrn‐A1a gene either alone or in combination with the dominant Vrn‐B1 while 74% of the higher yielding soft white lines possessed the Vrn‐B1 gene alone or in combination with other Vrn genes. The Vrn‐A1a alone or in combination with the Vrn‐B1 gene was the most potent gene conferring early maturity. Ppd‐D1a did not alter flowering and maturity in the hard red cultivars tested in the field but did in the greenhouse. Ppd‐D1a reduced days to flowering for soft white spring wheat but did not alter maturity. The photoperiod sensitive gene (Ppd‐D1b) is being replaced with the insensitive gene, Ppd‐D1a, in most modern Canadian germplasm, suggesting its adaptive advantages in the prairies. An overall analysis of the data for the hard red class revealed a declining trend of 0.04 d yr−1 in days to maturity in cultivars released from 1885 to 2008 and an increase of 8 kg ha−1 yr−1 in grain yield. The findings of this study may aid wheat breeders selecting parents with appropriate vernalization and photoperiod gene complexes.

New breeding tools impact Canadian commercial farmer fields

The high cost of cultivar development encourages efficiencies to reduce time and costs to develop cultivars. Doubled haploid (DH) technology and marker assisted breeding (MAB) are two such tools that improve efficiencies. Since 1997, twenty five wheat cultivars in seven market classes, developed using DH methods, have been registered by the Canadian Food Inspection Agency. These DH cultivars accounted for more than one third of the Canadian wheat acreage in 2009. The DH cultivar Lillian, eligible for grades of Canada Western Red Spring class and currently the most widely grown wheat cultivar in Canada, was developed using MAB to improve grain protein content with the Gpc-B1/Yr36 on chromosome 6BS introgressed from Triticum turgidum&amp;nbsp;L. (Zhuk.) dicoccoides (K&amp;ouml;rn. Ex Asch. &amp;amp; Graebn). AC Andrew, a Canada Western Soft White spring DH cultivar, was the most widely grown cultivar in its class for the last two years. The new market class, Canada Western Hard White Spring wheat, is based entirely on DH cultivars. Goodeve, one of the first Canada Western Red Spring cultivars released with the gene Sm1 on chromosome 2BS for resistance to the orange wheat blossom midge (Sitodiplosis mosellana (G&amp;eacute;hin)) was selected by application of the DNA marker WM1. Glencross, the first cultivar in the Canada Western Extra Strong wheat class with Sm1, was selected using the WM1 marker on haploid plants prior to doubling. Development of the durum wheat cultivars CDC Verona and Brigade involved the use of a marker for Cdu1, a major gene on chromosome 5B that regulates grain cadmium concentration. Marker technology permits a more strategic and integrated approach to breeding by quantifying the introgression of various key genes into advanced breeding material, identifying targeted loci in parents and following up with MAB in the progeny.

Bhishaj soft white spring wheat

Randhawa, H. S., Sadasivaiah, R. S., Graf, R. J. and Beres, B. L. 2011. Bhishaj soft white spring wheat Can. J. Plant Sci. 91: 805–810. Bhishaj is a soft white spring wheat (Triticum aestivum L.) that meets the end-use quality specifications of the Canada Western Soft White Spring class. Bhishaj is well-adapted to the wheat growing regions of southern Alberta and southern Saskatchewan. Based on data from the Western Soft White Spring Wheat Cooperative Registration Test from 1999 to 2001 and 2006 to 2009, Bhishaj exhibited high grain yield, mid-season maturity, semi-dwarf stature with moderate straw strength, and good resistance to shattering. Bhishaj expressed resistance to the prevalent races of leaf rust, stripe rust and powdery mildew, intermediate response to loose smut, susceptibility to stem rust, common bunt, and Fusarium head blight. Based on end-use quality analysis performed at the Grain Research Laboratory of the Canadian Grain Commission, Bhishaj had similar milling and baking performance as the check cultivars AC Reed and AC Phil.

Characterization of the Influence of Moisture Content on the Morphological Features of Single Wheat Kernels Using Machine Vision

The objective of this study was to quantify changes in morphological features of kernels of western Canadian wheat classes caused by moisture increase using a machine vision system. One hundred single wheat kernels for each of eight western Canadian wheat classes were successively conditioned from 12% to 20% (wet basis) moisture contents using potassium hydroxide (KOH) concentrations which regulated relative humidity. A digital camera of 7.4 7.4-m pixel resolution with an inter-line transfer charge-coupled device (CCD) image sensor was used to acquire images of single kernels. A machine vision algorithm developed at the Canadian Wheat Board Centre for Grain Storage Research, University of Manitoba, was implemented to extract seven morphological features (area, perimeter, major axis length, minor axis length, maximum radius, minimum radius, and mean radius) from the wheat kernel images. All the seven features of Canada Western Red Spring, Canada Western Amber Durum, Canada Prairie Spring White, Canada Prairie Spring Red, Canada Western Extra Strong, Canada Western Red Winter, Canada Western Hard White Spring, and Canada Western Soft White Spring wheat kernels were significantly (a = 0.05) different as the moisture content increased from 12% to 20%. All seven features showed a linearly increasing trend with an increase in moisture content.

Identification of wheat classes at different moisture levels using near-infrared hyperspectral images of bulk samples

Wheat classes at different moisture levels need to be identified to accurately segregate, properly dry, and safely store before processing. This paper introduces a new method using a near infrared (NIR) hyperspectral imaging system (960–1,700 nm) to identify five western Canadian wheat classes (Canada Western Red Spring (CWRS), Canada Western Extra Strong (CWES), Canada Western Red Winter (CWRW), Canada Western Soft White Spring (CWSWS), and Canada Western Hard White Spring (CWHWS)) and moisture levels, independent of each other. The objectives of this research also included identification of each wheat class at specific moisture levels of 12, 14, 16, 18, and 20%. Bulk samples of wheat were scanned in the 960–1,700 nm wavelength region at 10 nm intervals using an Indium Gallium Arsenide (InGaAs) NIR camera. Spectral feature data sets were developed by calculating relative reflectance intensities of the scanned images. Principal components analysis was used to generate scores images and loadings plots. The NIR wavelengths in the region of 1,260–1,360 nm were important based on the loadings plot of first principal component. In statistical classification, the linear and quadratic discriminant analyses were used to classify wheat classes giving accuracies of 61–97 and 82–99%, respectively, independent of moisture contents. It was also found that the linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) could classify moisture contents with classification accuracies of 89–91 and 91–99%, respectively, independent of wheat classes. Once wheat classes were identified, classification accuracies of 90–100 and 72–99% were observed using LDA and QDA, respectively, when identifying specific moisture levels. Spectral features at key wavelengths of 1,060, 1,090, 1,340, and 1,450 nm were ranked at top in classifying wheat classes with different moisture contents. This work shows that hyperspectral imaging techniques can be used for rapidly identifying the wheat classes even at varying moisture levels.

Sadash soft white spring wheat

Sadash is a soft white spring wheat (Triticum aestivum L.) that meets the end-use quality specifications of the Canada Western Soft White Spring class. Sadash is well-adapted to the wheat-growing regions of southern Alberta and southern Saskatchewan. Based on data from the Western Soft White Spring Wheat Cooperative Registration Test from 2003 to 2005, Sadash exhibited high grain yield, mid-season maturity, semi-dwarf stature with very strong straw, and good resistance to shattering. Sadash expressed resistance to the prevalent races of stem rust and powdery mildew, intermediate resistance to loose smut, moderate susceptibility to leaf rust and common bunt, and susceptibility to Fusarium head blight. Based on end-use quality analysis performed at the Grain Research Laboratory of the Canadian Grain Commission, Sadash had improved test weight over the check cultivars AC Reed and AC Phil and similar milling and baking performance.Key words: Triticum aestivum L., cultivar description, wheat (soft white spring), grain yield, quality, disease resistance

Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes

Differentiation of wheat classes is one of the important challenges to the Canadian grain industry. Even though some wheat classes may look similar, their chemical composition and consequently the end-product quality can vary significantly. Visual differentiation of wheat classes suffers from disadvantages such as inconsistency, low throughput, and labour intensiveness. A near-infrared (NIR) hyperspectral imaging system was used to develop classification models to differentiate wheat classes grown in western Canada. Wheat bulk samples were scanned in the wavelength region of 960–1700 nm at 10 nm intervals using an InGaAs NIR camera. Seventy-five relative reflectance intensities were extracted from the scanned images and used for the differentiation of wheat classes using a statistical classifier and an artificial neural network (ANN) classifier. Classification accuracies were 100% in classifying Canada Prairie Spring Red (CPSR), Canada Western Red Winter (CWRW), and Canada Western Soft White Spring (CWSWS) wheat classes and >94% for the other wheat classes (Canada Western Extra Strong (CWES), Canada Western Hard White Spring (CWHWS), Canada Western Red Spring (CWRS), Canada Prairie Spring White (CPSW) and Canada Western Amber Durum (CWAD)) using Linear Discriminant Analysis (LDA) with a leave-one-out cross-validation method. In Quadratic Discriminant Analysis (QDA) with a leave-one-out cross-validation method, the classification accuracies were >86% for all wheat classes. The overall classification accuracies of 60% training–30% testing–10% validation (referred to as 60-30-10) and 70% training–20% testing–10% validation (referred to as 70-20-10) ANN models were above 90% for independent validation sets using three-layer standard and Wardnet back-propagation neural network architectures.

Reactions of western Canadian spring wheat and triticale varieties to Tilletia indica, the causal agent of Karnal bunt

The reactions of 47 Canadian wheat and triticale cultivars to Tilletia indica Mitra, the causal agent of Karnal Bunt (KB), were evaluated in the field at Centro de Investigaciones Agricolas del Noroeste (CIANO), Yaqui Valley, Mexico, during 1998 and 1999. The majority of lines and cultivars flowered during January and February, which coincided with the onset of cooler temperatures and high relative humidity required for optimum infection by the fungus. Canada Western Amber Durum (CWAD) and triticale were resistant, ranging from 0 to 6% infection. Canada Western Red Spring (CWRS) wheats were also generally resistant, but the cultivars Roblin, BW90 and Laura, and the experimental line Roblin*2/BW 553, were susceptible, ranging from 11 to 28% in treatments with the highest infection levels. Canada Western Extra Strong (CWES) wheats varied in reaction from moderately resistant to susceptible, ranging from 1 to 15% infection. Canada Prairie Spring (CPS) wheats were generally susceptible, exhibiting infection levels ranging from 5 to 31% infection in the most severely infected treatments. Canada Western Soft White Spring (CWSWS) wheats were uniformly susceptible; the highest recorded infection level among Canadian wheats was observed on AC Reed (38%) during 1999. The susceptibility of CPS and CWSWS cultivars may represent an increased risk to the establishment of KB if the fungus were to become introduced into western Canada. Key words: Karnal bunt, wheat, disease resistance, disease susceptibility

Black Point Reaction of Durum and Common Wheat Cultivars Grown Under Irrigation in Southern Saskatchewan.

Six durum (Triticum turgidum L. var. durum) and six common (T. aestivum L.) wheat cultivars were compared for reaction to black point under irrigation at two locations in southern Saskatchewan in 1990 to 1992 and 1994. There were individual varietal differences in black point levels within each of the species. The Canada Western Soft White Spring wheat Fielder was the most susceptible and the Canada Western Red Spring wheat Katepwa was the most resistant to black point. The location-cultivar-year interaction was a significant source of variation and a crossover cultivar-environment interaction was significant, suggesting that rank order of cultivars differed with environment. The durum wheat had significantly higher black point levels than the common wheat cultivars in three of the seven environments conducive to black point, two of which were in 1992, and had high overall black point levels. This greater black point severity on the durum wheat cultivars might have been due to cool, wet weather conditions and frosts during seed development that delayed ripening.

Comparison of Durum and Common Wheat Cultivars for Reaction to Leaf Spotting Fungi in the Field

Durum (Triticum turgidum var. durum) and common (T. aestivum) wheat cultivars (Canada Western Red Spring, Canada Prairie Spring, and Canada Western Soft White Spring), grown at two locations for 3 years, were assessed for severity of the leaf spot complex and relative proportion of leaf spotting fungi. The most prevalent fungi isolated were Pyrenophora tritici-repentis and Phaeosphaeria nodorum. Their percent isolation and leaf spot severity varied among years and between locations. The relative prevalence of the leaf spotting fungi in the individual cultivars, or cultivars grouped by species, varied with year, whereas the leaf spot score varied with location. Cultivars and species differed in susceptibility to the leaf spotting fungi. The common wheat classes were mostly colonized by P. nodorum and the durum wheat by P. tritici-repentis. Cultivars, but not cultivars grouped by species, also differed in the severity of the leaf spot complex. Within both durum and common wheat there were cultivars with low and high leaf spot scores.

Evaluation of some characteristics of Chinese steamed buns prepared from Canadian wheat flours

A laboratory procedure for preparing and evaluating end-product characteristics of Chinese steamed buns from Canadian wheat flours is described. A blend of 60% Canada Western Red Winter (80% patent) and 40% Canada Western Soft White Spring (straight grade) wheat flours was evaluated and subsequently used as the control flour. Buns were prepared by a straight dough procedure using only flour, yeast and water. Evaluation of bun quality included measurement of volume with a loaf volumeter, symmetry by the width-to-height ratio, physical measurements of hardness, cohesiveness and gumminess with the Instron Universal Testing Machine, and color (L*, a*, b*) of crust and crumb using the HunterLab Labscan II Colorimeter. Buns prepared from different classes of Canadian wheats were evaluated. Both Canada Western Red Winter and Canada Western Red Spring wheat flours produced steamed buns which were similar to the control, whereas those made from a non-blended Canada Western Soft White wheat flour produced a less appealing product.Key words: Wheat, steamed buns, test-baking, flour, quality evaluation

Wheat grain colour analysis by digital image processing II. Wheat class discrimination

The extent to which wheat grain colour, objectively measured by video colorimetry, can be used to distinguish kernel type according to wheat class and variety was investigated. Discriminant analyses were performed based on mean red (R), green (G) and blue (B) pixel reflectance (tristimulus) features obtained by colour digital image analysis. Colour data collected from individual kernels of 10 cultivars representing six Canadian wheat classes were used to develop discriminant models. Pairwise discrimination between selected varieties representing the different wheat classes was achieved with considerable success. Over all pairwise trials, 88 % correct varietal classification was achieved on average. In pairwise trials between certain red-grained varieties (cvs), e.g. Neepawa, Norstar or Glenlea and amber durum cv. Wakooma or white spring wheat cv. Owens, correct classification exceeded 96%. A more demanding discrimination problem of correctly classifying grain of single wheat varieties according to official grade class was also posed. Correct classification scores for individual varieties varied from 34 to 90%. Average correct classification scores for the Canada Western Soft White Spring, Amber Durum and Red Spring classes of wheat were 76, 76 and 62 %, respectively. Relatively lower scores of 56 and 34 % were achieved for the Canada Western Hard Red Winter and Canada Prairie Spring wheat classes. The average correct classification for hard red spring type kernels was approximately 90 %.