Canada Western Red Spring Research Articles

Cereal Grain and Dockage Identification using Machine Vision

Algorithms were written to extract a total of 230 features (51 morphological, 123 colour, and 56 textural) from the high-resolution images of kernels of five grain types [barley, Canada Western Amber Durum (CWAD) wheat, Canada Western Red Spring (CWRS) wheat, oats, and rye] and five broad categories of dockage constituents [broken wheat kernels, chaff, buckwheat, wheat spikelets (one to three wheat kernels inside husk), and canola (rapeseed with low erucic acid content in the oil and low glucosinolate content in the meal)]. Different feature models, viz. morphological, colour, texture, and a combination of the three, were tested for their classification performances using a neural network classifier. Kernels and dockage particles with well-defined characteristics ( e.g. CWRS wheat, buckwheat, and canola) showed near-perfect classification whereas particles with irregular and undefined features ( e.g. chaff and wheat spikelets) were classified with accuracies of around 90%. The similarities in shape and size of some of the particles of chaff and wheat spikelets with the kernels of barley and oats affected the classification accuracies of the latter, adversely.

Saskatchewan Regional Meeting, 2002, The Canadian Phytopathological Society / Réunion régionale de la Saskatchewan, 2002, La Société Canadienne de Phytopathologie

Blight of coriander and caraway in Saskatchewan, 2000–2002. L.J. Duczek and A.E. Slinkard. 30 Birch Place, Saskatoon, SK S7N 2P6, Canada; and (A.E.S) Department of Plant Science, University of Saskatchewan, Saskatoon, 51 Campus Drive, SK S7N 5A8, Canada. Association of seed color with incidence and severity of kernel discoloration caused by Pyrenophora triticirepentis. M.R. Fernandez and R.M. DePauw. Semiarid Prairie Agricultural Research Centre, Agriculture and Agri- Food Canada, P.O. Box 1030, Swift Current, SK S9H 3X2, Canada. Potential synergy of a plant pathogen and herbicides for improved control of scentless chamomile. G.L. Graham, G. Peng, K.L. Bailey, and F.A. Holm. Saskatoon Research Centre, Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK S7N 0X2, Canada; and (G.L.G., F.A.H.) Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada. Histochemical and molecular genetic analyses of sucrose hydrolysis in mildewed wheat leaves. D.L. Greenshields, F. Wang, G. Selvaraj, and Y. Wei. Department of Biology, University of Saskatchewan, 112 Science Place, Saskatoon, SK S7N 5E2, Canada; and (G.S.) Plant Biotechnology Institute, National Research Council of Canada, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada. Glyphosate herbicides affect plant pathogenic fungi. K.G. Hanson and M.R. Fernandez. Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, P.O. Box 1030, Swift Current, SK S9H 3X2, Canada. Metabolism of the phytoalexins camalexin and 6- methoxycamalexin by the fungus Sclerotinia sclerotiotum causing stem rot. M.S.C. Pedras and P.W.K. Ahiahonu. Department of Chemistry, University of Saskatchewan, 110 Science Place, Saskatoon, SK S7N 5C9, Canada. Isolation, structure determination, and antifungal activity of phytoalexins produced by Thlaspi arvense. M.S.C. Pedras and P.B. Chumala. Department of Chemistry, University of Saskatchewan, 110 Science Place, Saskatoon, SK S7N 5C9, Canada. Study of the biotransformation of the cruciferous phytoalexins cyclobrassinin, brassilexin, and spirobrassinin by the fungus Sclerotinia sclerotiorum causing stem rot. M.S.C. Pedras and M. Hossain. Department of Chemistry, University of Saskatchewan, 110 Science Place, Saskatoon, SK S7N 5C9, Canada. Secondary metabolites produced by the phytopathogenic fungus Rhizoctonia solani. M.S.C. Pedras and J. Liu. Department of Chemistry, University of Saskatchewan, 110 Science Place, Saskatoon, SK S7N 5C9, Canada. Biotic and abiotic stresses regulate the expression of cytosolic ascorbate peroxidase and glutathione peroxidase in wheat. X. Sheng, G. Selvaraj, and Y. Wei. Department of Biology, University of Saskatchewan, 112 Science Place, Saskatoon, SK S7N 5E2, Canada; and (S.G.) Plant Biotechnology Institute, National Research Council of Canada, 110 Gymnasium Place, Saskatoon, SK S7N 0W9,Canada. Genetic similarity among isolates of Pyrenophora triticirepentis. P.K. Singh and G.R. Hughes. Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada. Genotypic differences in kernel discoloration in Canada Western Red Spring and Canada Western Amber Durum wheats. H. Wang, M.R. Fernandez, T.N. McCaig, and Y.T. Gan. Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, P.O. Box 1030, Swift Current, SK S9H 3X2, Canada.

SOFT X–RAY INSPECTION OF WHEAT KERNELS INFESTED BY SITOPHILUS ORYZAE

The potential of a soft Xray method (15 kV and 65 .A) to detect internal seed infestations by the rice weevil(Sitophilus oryzae) in Canada Western Red Spring wheat was determined in this study. The infested kernels were identifiedby the presence of egg plugs and were scanned with a realtime fluoroscope every 5 to 7 d until the adults emerged from thekernels. A total of 57 features using histogram groups, textural features, and histogram and shape moments were extractedfrom the Xray images of the wheat kernels. Parametric and nonparametric classifiers, and a 4layer back propagationneural network classifier were used to identify uninfested and infested wheat kernels using histogram and textural featuresindependently, and using all 57 features together. There was no significant difference between the classifiers for theidentification of uninfested and infested wheat kernels. More than 95% of uninfested kernels and kernels infested by larvalstages were correctly identified by all the classifiers. Wheat kernels infested by pupaeadults and insectdamaged kernelswere identified with more than 99% accuracy by the classifiers.

Effect of dry heat treatment on seed-borne Fusarium graminearum and other cereal pathogens

Pathogen levels and seed viability of two samples each of barley (Hordeum vulgare) (B1, B2), Canada western red spring wheat (Triticum aestivum) (RS1, RS2), and Canada western amber durum wheat (AD1, AD2) were assessed after heating seed at 50 or 70°C for up to 14 days. RS2 and B2, with an initial incidence of 23 and 84% of Fusarium graminearum, respectively, were also heated at 60°C for 24 days and 80°C for 10 days. Pathogen levels and seed viability were assessed by plating seed onto potato dextrose agar and wet filter paper, respectively. Fusarium graminearum was eliminated from RS2 after 15 days at 60°C, 5 days at 70°C, or 2 days at 80°C. In B2, F. graminearum was eliminated after 21 days at 60°C, 9 days at 70°C, or 5 days at 80°C. After heating at 50 or 70°C, the observed frequency of Cochliobolus sativus in B1 declined slightly but significantly over time, whereas it substantially increased in B2. A significant decline in the incidence of C. sativus was observed in B2 after heating at 80°C. Pyrenophora teres was observed significantly more often in B1 after heating at 50 or 70°C, whereas Pyrenophora tritici-repentis in AD1 and AD2 was unaffected by heating at 50°C. However, the detection of P. tritici-repentis did significantly increase over time in AD2 when heated at 70°C. In AD1, heating at 70°C initially increased, then decreased the observed incidence of this pathogen. Cochliobolus sativus, P. teres and P. tritici-repentis were still viable in the samples after 14 days of heating at 70°C, but C. sativus was not detected after 10 days at 80°C. Germination of wheat tempered to 12, 14, and 16% moisture content was unaffected by heating at 70°C for 7 days, whereas barley tempered to the same moisture content had a slight decline in germination. Germination rates in most samples were unaffected by the treatment times and temperatures sufficient to eradicate F. graminearum, but a significant decline in viability was recorded for AD2 and B1 heated at 70°C. The germination of B2 increased when heated at 70°C, but declined when heated at 80°C. It is recommended that thermotherapy be applied to control national and international movements of F. graminearum and other heat-sensitive pathogens in germplasm used for research and breeding purposes.Key words: thermotherapy, Cochliobolus sativus, Pyrenophora teres, Pyrenophora tritici-repentis.

Understanding and Modeling the Processing‐Mechanical Property Relationship of Bread Crumb Assessed by Indentation

ABSTRACTMeasuring fundamental mechanical parameters such as Young's modulus and critical stress is a straightforward and valid approach to evaluating the physical texture of breadcrumb. The objectives of this study were to evaluate whether such fundamental mechanical properties could be measured by indentation techniques such as the AACC crumb firmness method, and then to alter breadmaking conditions so as to model the relationship between these indentation mechanical properties as a function of crumb moisture content and crumb density. Bread was baked according to a short dough process using Canadian western red spring (CWRS) wheat flour. Factors considered in the design of experiments were proofing time, water absorption, crosshead speed, and indenter diameter. Young's modulus and critical stress, measured with 12‐ and 20‐mm cylindrical indenters, were well covalidated with those obtained from a standard compression test. With increases in proofing time and water absorption, a more porous and compliant bread texture led to decreasing Young's modulus and critical stress. Our results revealed a good mapping of mechanical properties to crumb moisture content and density that were correlated to breadmaking conditions, thus permitting more precise prediction of the mechanical properties that determine bread texture.

AE—Automation and Emerging Technologies: Specialist Neural Networks for Cereal Grain Classification

In the past few years, artificial neural networks have gained widespread acceptance for cereal grain classification and identification tasks. With the availability of different types of neural network architectures, the choice of the architecture for a particular task becomes crucial. It was hypothesized that robust specialist networks can be designed using a combination of simple networks having similar or different network architectures. To test this hypothesis, the classification accuracies of four simple network architectures (namely, back propagation network (BPN), Ward network, general regression neural network (GRNN) and probabilistic neural network (PNN)) were compared with the accuracies given by specialist networks. Each specialist network was designed using a combination of five simple networks, each specializing in classifying one grain type. The grain types used in this study were Canada Western Red Spring (CWRS) wheat, Canada Western Amber Durum (CWAD) wheat, barley, oats and rye. To evaluate the classification accuracy of the different neural network architectures, high resolution colour images of 7500 kernels (1500 kernels of each grain type) were taken for training and testing of networks. For each kernel, eight morphological features (namely, area, perimeter, length of major axis, length of minor axis, elongation, roundness, Feret diameter and compactness) and four colour features (namely, mean, median, mode and standard deviation of the grey-level values of the objects in the image) were extracted and used as input to the neural networks. Best classification accuracies (98·7, 99·3, 96·7, 98·4, and 96·9 for barley, CWRS wheat, CWAD wheat, oats and rye, respectively) were obtained using specialist probabilistic neural networks.

Physiological characteristics of recent Canada Western Red Spring wheat cultivars: Yield components and dry matter production

Genetic yield gains have been difficult to achieve within the Canada Western Red Spring (CWRS) wheat (Triticum aestivum L.) class because of stringent quality requirements and a short growing-season environment with low precipitation and high temperatures. Understanding the physiological basis of yield gains may provide breeders with better insight in selecting parents and screening tools to identify desirable genotypes. The objective of the present study was to compare four new CWRS wheat cultivars with two older cultivars, Neepawa and Marquis, for yield components and dry matter production. When grown at Swift Current, SK, for 3 yr, the average yield for the group of new cultivars was 34.3% higher than that of Marquis (P < 0.01), and 5.9% higher than that of Neepawa (P = 0.10). The new cultivars, as a group, had significantly increased kernel weight, kernels per spike, yield per spike, and spike-filling rate relative to either of the older cultivars. When cultivars were compared individually, all four of the new cultivars had significantly higher yield per spike and spike-filling rate than Neepawa or Marquis, suggesting that these factors may be closely related to the increased yields of the newer cultivars. The trend toward higher kernel weight and kernels per spike suggests that the new cultivars have increased the sink size of each tiller. The number of spikes per plant and the length of the grain-filling period do not appear to be associated with the increased yield. Harvest index of the group of new cultivars, while significantly higher than that of Marquis, has not increased significantly compared to Neepawa, probably because this group is similar in height to Neepawa. Key words: Triticum aestivum, wheat, Canada Western Red Spring, yield, quality

Effects of Flour Particle Size and Starch Damage on Processing and Quality of White Salted Noodles

ABSTRACTSeveral reduction grinding conditions were used on a Canadian Western Red Spring (CWRS) farina to yield flours of comparable protein content within three specific particle size ranges (132–193, 110–132, 85–110 μm) at three starch damage levels (3.0, 3.9, 7.0 Megazyme units). White salted noodles (1% w/w NaCl) were initially processed at a fixed absorption (32%). Dynamic oscillatory and large deformation creep measurements indicated that doughs with lower starch damage, thick or thin, exhibited lower G′ (storage modulus), higher tan δ (G″ [loss modulus]/G′) values, and greater maximum strain during creep than doughs with higher starch damage. There were no clear trends between work input during sheeting and either starch damage or particle size. Instrumental texture analysis of raw noodles showed no significant differences due to either starch damage or flour particle size. Flours with fine particle size gave cooked noodles with the best textural attributes, whereas starch damage exhibited no consistent relationship with cooked noodle texture. Cooking loss was greatest in samples with highest starch damage and coarsest particle size; water uptake was inversely related to starch damage and particle size. Experiments were repeated at adjusted water absorptions (32–36.5%) for fine and coarse flours with highest and lowest starch damage. Differences in raw noodle dough rheological properties were largely eliminated, confirming that differences noted at constant absorption were primarily due to flour water absorption. Work input during sheeting was inversely related to starch damage and was higher for fine particle size. Cooking losses were highest for higher starch damage and fine particle size. Water uptake was highest for fine particle size, but in contrast to cooking loss, was higher at lower starch damage. Textural parameters indicated superior cooking quality when particle size was finer and starch damage was lower. Flour particle size and starch damage (as indicated by water absorption) are both primary quality determinants of white salted noodle properties and, to some extent, exert their influence independently.

Neural network models to predict the maturity of spring wheat in western Canada

The Canadian Wheat Board (CWB) and the railways require accurate predictions of harvest dates to facilitate the movement of grain from the Canadian Prairies. Our objective was to develop neural network (NN) models to predict, 4–8 wk in advance, the maturity date of spring wheat (Triticum aestivum L.) across the Prairies with an accuracy of 0.5 wk. We used soil and climatic zone information, cultivar, CWB wheat class, seeding date, and the first 9 wk of weather after seeding to predict days to maturity in the standing crop from seeding date. Our first Prairie-wide model (MD1), derived from data at 76 locations over 1970 –1995, performed well (R2 = 0.82–0.83, average absolute error = 3.0–3.1 d), but used solar radiation inputs, which may not always be available. Therefore, a second model (MD2) was developed (R2 = 0.76–0.80, average absolute error = 3.3–3.4 d) without solar radiation inputs. A third model (MD3) was developed (R2 = 0.72, average absolute error = 3.8 d) specifically for Canada Western Red Spring (CWRS) wheat grown at dryland locations. The MD2 and MD3 models were tested on more recent (1996–1998) data, but their performance was poor (R2 = 0.26–0.33; average absolute errors = 5.2–6.9 d) because of differences in the weather data. Thus, a fourth model (MD4) was developed (R2 = 0.85–0.90; average absolute error = 2.7–2.8 d) using 1989–1998 crop data from 19 locations combined with more recent Environment Canada “Real Time” Weather (ECRTW) data. Considering the variation in soil types, cultivars, seeding dates, and weather conditions across the Prairies, the NN models gave accurate predictions of wheat maturity. Key words: Neural networks, model, wheat, maturity, weather, Canadian prairies

Studies on the distribution and binding of endogenous glutathione in wheat dough and gluten. II. Binding sites of endogenous glutathione in glutenins

For the identification of the binding sites of glutathione (GS) in glutenins, flour of the wheat cultivar " Canadian Western Red Spring " was mixed with water containing 35S-labelled reduced GS as a tracer. The resulting dough was washed in a Glutomatic, and, in order to remove gliadins, the gluten obtained was extracted with 70% aqueous ethanol adjusted to pH 5.5 with acetic acid. The residual proteins (glutenins) were hydrolyzed with thermolysin, and the hydrolysate was separated by gel permeation chromatography on Sephadex G25 and by several steps of reversed-phase HPLC on C18 silica gel. The major radioactive disulphide peptides identified by scintillation analysis were collected and analysed for their amino acid sequences. Twenty-five peptides linked to GS could be assigned to known sequences of gluten proteins. Most peptides (16) were derived from low molecular weight (LMW) subunits of glutenin. Among these, 13 peptides contained the cysteine residue Cb*, which is present in the repetitive sequence region of LMW subunits and which has been postulated to form intermolecular disulphide bonds. This peptide type represented 45% of the total radioactivity of isolated peptides. Three further peptides from LMW subunits representing 46% of radioactivity included cysteine Cx, which has also been proposed to form intermolecular disulphide bonds. Four peptides with 3.2% of radioactivity could be assigned to high molecular weight subunits (cysteines Cb, Cd, Ce, Cy) and four peptides (3.0% of radioactivity) to glutenin-bound γ-gliadins (Cb*, Cw, Cz). One peptide (3.3% of radioactivity) corresponded to cysteine Cc from γ-gliadins or LMW subunits. Altogether the cysteine residues in glutenins, which are usually linked by intermolecular disulphide bonds, contributed up to 95% of total radioactivity. The results obtained are in accordance with the effect of reduced GS on the rheological properties of dough, namely the weakening of dough by depolymerization of glutenin polymers via specific cleavage of intermolecular disulphide bonds.

Studies on distribution and binding of endogenous glutathione in wheat dough and gluten. I. Distribution of glutathione in Osborne fractions

Glutathion (GS) present in wheat flour or added to wheat flour has a large effect on the rheological properties of dough and gluten. To study the distribution of endogenous glutathione (GS) in Osborne fractions of dough and gluten, 35S-labelled reduced glutathione (GSH) was added as a tracer (about 0.1% of endogenous GSH) to the flours of three wheat cultivars (Canadian Western Red Spring, Dark Northern Spring, Maris Huntsman). After mixing of flours with water, the doughs obtained were fractionated into water-solubles, globulins, gliadins and glutenins. The radioactivity of the freeze-dried fractions was determined with a scintillation counter. The distribution of radioactivity was similar for the different cultivars and about 65% in the water-soluble fraction (mainly non-protein bound GS), 6–7 % in each of the globulin and gliadin fractions and 21% in the glutenin fraction. RP-HPLC of water-solubles, globulins and gliadins using simultaneous UV and radioactivity detection demonstrated that protein-bound labelled GS was distributed over the whole area of eluted protein. A dough resting time of 35 min did not influence distribution and 35S-labelled oxidized glutathione (GSSG) was distributed in the same proportions as GSH. In gluten washed from dough, radioactivity was increased in the gliadin (11%) and glutenin fractions (35%) and decreased in the water-soluble fraction. The addition of GSH to flour (100 nmol/g) led to an increase of radioactivity in the water-soluble fraction of dough and to a decrease in the other dough fractions; the effect of GSSG (50 nmol/g) was less pronounced. The influence of ascorbic acid (170 nmol/g) was dependent on the content of endogenous GSH in flour; at high levels of endogenous GSH, a strong shift of radioactivity from the water-soluble fraction to the glutenin fraction was observed. Amongst oxidants studied, CuSO4 (315 nmol/g) had only small effects. KBrO3 (300 nmol/g) increased radioactivity of the water-soluble fraction and decreased that of the glutenin fraction, whereas the effect of KIO3 (117 nmol/g) was dependent on the wheat cultivar.

Effects of cultivar and environment on farinograph and Canadian short process mixing properties of Canada Western Red Spring wheat

Fourteen Canada Western Red Spring (CWRS) wheat (Triticum aestivum L.) cultivars grown at six Saskatchewan sites in 1995 were used to assess the impact of cultivar and environment on dough mixing properties. ANOVA showed that cultivar, environment and interactions thereof generally had highly significant effects on farinograph and Canadian short process (CSP) water absorption and mixing parameters. Most of the variance in farinograph and CSP absorption could be attributed to environment, while cultivar was the predominant contributor to farinograph dough development time and stability. Both cultivar and environment had a strong influence on CSP mixing time and mixing energy. Neither protein nor particle size index as covariate had a strong influence on the partitioning of variance. Strong significant relationships were evident among absorption parameters and among most mixing strength parameters. No strongly significant relationships were found between absorption and mixing strength parameters. Significant differences were evident among cultivar means and among station means for all parameters. The strong impact of environment on most mixing properties suggests that attention should be focused on the potential adverse impact on the uniformity of CWRS shipments due to the trend towards reduced blending among regions associated with the continued development of large high throughput primary elevators. Key words: Cultivar, environment, wheat, dough mixing properties

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

Reaction of common and durum wheat cultivars to infection of kernels by Pyrenophora tritici-repentis

Kernel discoloration caused by Pyrenophora tritici-repentis (Died.) Drechs. is an important downgrading factor in wheat. Twenty-nine durum and common wheat cultivars belonging to four different quality classes were compared for their reaction to inoculation of kernels with P. tritici-repentis under controlled conditions. All cultivars were susceptible to this pathogen but they differed in the predominant type and (or) intensity of kernel discoloration and in incidence and severity of infection. The most common symptom associated with infection by this pathogen is red smudge, a pink to bright red discoloration. This developed in all Canada Western Amber Durum cultivars but was less apparent in the Canada Western Red Spring cultivars. Other common symptoms observed in all cultivars were black point, dark smudge, and specks. Some differences in the incidence and severity of the discoloration among cultivars appeared to be related to seed colour. The white-seeded cultivars, regardless of quality class, were in general more susceptible than the red-seeded cultivars. However, there were also differences in the predominant type of symptom and in the incidence and severity of infection among and within classes that were not related to seed colour. It was concluded that the type of symptom, and its incidence and severity, are mostly genotype-dependent and only partially conditioned by seed colour or wheat quality class or species.

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.

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

ABSTRACTCanada 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.

Uptake of foliar or soil application of 15N-labelled urea solution at anthesis and its affect on wheat grain yield and protein

Two growth chamber experiments were conducted to determine the effect of 15N-labelled urea solution foliar- or soil-applied at anthesis on recovery of fertilizer N in grain, grain protein and grain yield of Canadian Western Red Spring wheat (Triticum aestivum L.). Recovery of 15N-labelled urea-N in grain ranged from 4.5 to 26.7% with foliar application, and from 32.3 to 70.1% with soil application. Amending the urea solution with the urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) improved recovery of soil-applied N in exp. 1 only and did not increase N recovery from foliar applications. Nitrogen recovery of foliar-applied urea was increased on average from 10.6 to 25.0% by adding nonyl phenol ethoxylates (NPE), a non-ionic surfactant, to the urea solution. Grain protein was higher when urea was applied to the soil than when applied to the foliage. Addition of N at planting increased both grain protein and yield while only protein was enhanced with fertilizer N applied at anthesis. Although wheat cultivar, soil type and growing environment differed in the two experiments, protein content consistently increased with N application at anthesis, indicating the effect of N applied at anthesis is constant across a range of conditions. Key words: Triticum aestivum L., N-(n-butyl) thiophosphoric triamide, NBPT, non ionic surfactant, wetting agent, nitrogen recovery

CLASSIFICATION OF CEREAL GRAINS USING MACHINE VISION: II. COLOR MODELS

A digital image analysis (DIA) algorithm was developed based on color features to classify individual kernelsof Canada Western Red Spring (CWRS) wheat, Canada Western Amber Durum (CWAD) wheat, barley, oats, and rye.Eighteen color features (mean, variance, and range of red, green, and blue, and hue, saturation, and intensity) were usedfor the discriminant analysis. Grains from 15 growing regions (300 kernels per growing region) were used as the trainingdata set and another five growing regions were used as the test data set. When the first 10 most significant color featureswere used in the color model and tested on an independent data set (the test data set where total number of kernels usedwas 10,500; for CWRS wheat, 300 kernels each were selected for three grades), the classification accuracies of CWRSwheat, CWAD wheat, barley, oats, and rye were 94.1, 92.3, 93.1, 95.2, and 92.5%, respectively. When the model wastested on the training data set (total number of kernels used was 31,500), the classification accuracies were 95.7, 94.4,94.2, 97.6, and 92.5%, respectively, for CWRS wheat, CWAD wheat, barley, oats, and rye.

CLASSIFICATION OF CEREAL GRAINS USING MACHINE VISION: IV. COMBINED MORPHOLOGY, COLOR, AND TEXTURE MODELS

Classification models by combining two or three feature sets (morphological, color, textural) were developedto classify individual kernels of Canada Western Red Spring (CWRS) wheat, Canada Western Amber Durum (CWAD)wheat, barley, oats, and rye. The mean accuracies (the average of the classification accuracies of the above mentionedcereal grains) of 98.6 and 99.3% were achieved when the morphology-texture model with the 15 most significant featureswas used to test on an independent data set (total number of kernels used was 10,500) and on the training data set (totalnumber of kernels used was 31,500), respectively. When the morphology-color model (with the 15 most significantfeatures) was tested on the independent data set and on the training data set, the mean accuracies were 99.4 and 99.6%,respectively. Similarly, using the texture-color model (with the 15 most significant features) the mean accuracies were98.4 and 98.0% for the independent and the training data sets, respectively. The highest classification accuracies wereachieved when the morphology-texture-color model was used. The mean accuracies using the 20 most significant featuresin the morphology-texture-color model were 99.7 and 99.8% when tested on the independent and the training data sets,respectively. The differences in mean accuracies were not significant when the models were tested with independent andtraining data sets.

CLASSIFICATION OF CEREAL GRAINS USING MACHINE VISION: I. MORPHOLOGY MODELS

An algorithm was developed based on morphological features to classify individual kernels of CanadaWestern Red Spring (CWRS) wheat, Canada Western Amber Durum (CWAD) wheat, barley, oats, and rye. Twenty-threemorphological features were used for the discriminant analysis. Grains from 15 growing regions (300 kernels pergrowing region) across Western Canada were used as the training data set and from another five growing regions as thetest data set. The classification accuracies of individual kernels using the 10 most significant features in the morphologymodel were 98.9, 93.7, 96.8, 99.9, and 81.6%, respectively for CWRS wheat, CWAD wheat, barley, oats, and rye whentested on an independent data set (i.e., the test data set where the total number of kernels used was 10 500; for CWRSwheat, 300 kernels each were selected for three grades). When the model was tested on the training data set (total numberof kernels used was 31 500), the classification accuracies of CWRS wheat, CWAD wheat, barley, oats, and rye were 98.9,91.6, 97.9, 100.0, and 91.6%, respectively.