Wheat Kernel Samples Research Articles

Machine Learning Analysis of Hyperspectral Images of Damaged Wheat Kernels.

Fusarium head blight (FHB) is a disease of small grains caused by the fungus Fusarium graminearum. In this study, we explored the use of hyperspectral imaging (HSI) to evaluate the damage caused by FHB in wheat kernels. We evaluated the use of HSI for disease classification and correlated the damage with the mycotoxin deoxynivalenol (DON) content. Computational analyses were carried out to determine which machine learning methods had the best accuracy to classify different levels of damage in wheat kernel samples. The classes of samples were based on the DON content obtained from Gas Chromatography-Mass Spectrometry (GC-MS). We found that G-Boost, an ensemble method, showed the best performance with 97% accuracy in classifying wheat kernels into different severity levels. Mask R-CNN, an instance segmentation method, was used to segment the wheat kernels from HSI data. The regions of interest (ROIs) obtained from Mask R-CNN achieved a high mAP of 0.97. The results from Mask R-CNN, when combined with the classification method, were able to correlate HSI data with the DON concentration in small grains with an R2 of 0.75. Our results show the potential of HSI to quantify DON in wheat kernels in commercial settings such as elevators or mills.

Metabolome dynamics during wheat domestication

One of the most important crops worldwide is wheat. Wheat domestication took place about 10,000 years ago. Not only that its wild progenitors have been discovered and phenotypically characterized, but their genomes were also sequenced and compared to modern wheat. While comparative genomics is essential to track genes that contribute to improvement in crop yield, comparative analyses of functional biological end-products, such as metabolites, are still lacking. With the advent of rigorous mass-spectrometry technologies, it is now possible to address that problem on a big-data scale. In attempt to reveal classes of metabolites, which are associated with wheat domestication, we analyzed the metabolomes of wheat kernel samples from various wheat lines. These wheat lines represented subspecies of tetraploid wheat along primary and secondary domestications, including wild emmer, domesticated emmer, landraces durum, and modern durum. We detected that the groups of plant metabolites such as plant-defense metabolites, antioxidants and plant hormones underwent significant changes during wheat domestication. Our data suggest that these metabolites may have contributed to the improvement in the agricultural fitness of wheat. Closer evaluation of specific metabolic pathways may result in the future in genetically-engineered high-yield crops.

Tremellomycetes Yeasts in Kernel Ecological Niche: Early Indicators of Enhanced Competitiveness of Endophytic and Mycoparasitic Symbionts against Wheat Pathobiota.

Tremellomycetes rDNA sequences previously detected in wheat kernels by MiSeq were not reliably assigned to a genus or clade. From comparisons of ribosomal internal transcribed spacer region (ITS) and subsequent phylogenetic analyses, the following three basidiomycetous yeasts were resolved and identified: Vishniacozyma victoriae, V. tephrensis, and an undescribed Vishniacozyma rDNA variant. The Vishniacozyma variant’s clade is evolutionarily close to, but phylogenetically distinct from, the V. carnescens clade. These three yeasts were discovered in wheat kernel samples from the Canadian prairies. Variations in relative Vishniacozyma species abundances coincided with altered wheat kernel weight, as well as host resistance to chemibiotrophic Tilletia (Common bunt—CB) and necrotrophic Fusarium (Fusarium head blight—FHB) pathogens. Wheat kernel weight was influenced by the coexistence of Vishniacozyma with endophytic plant growth-promoting and mycoparasitic biocontrol fungi that were acquired by plants. Kernels were coated with beneficial Penicillium endophyte and Sphaerodes mycoparasite, each of which had different influences on the wild yeast population. Its integral role in the kernel microbiome renders Vishniacozyma a measurable indicator of the microbiome–plant interaction. The ability of NGS technology to detect specific endophytic DNA variants and early changes in dynamics among symbionts within the kernel ecological niche enables the prediction of crop disease emergence, suggesting that advanced microbiological testing may be a potentially useful tool for both phytoprotection and more efficient wheat breeding programs.

Pre-harvest glyphosate application and effects on wheat starch chemistry: Analysis from application to harvest.

The objective of this study was to determine if the pre-harvest glyphosate application time affects the chemistry of wheat starch. Glyphosate was sprayed at the ripe stage (recommended) and the soft dough stage (early application) of hard red spring wheat. Wheat kernel samples were collected before application and every 3days until harvest, after which different starch characteristics were analyzed. The results indicate that glyphosate timing does not impact the spatial distribution or morphology of starch granules, as well as the percentage or molecular weight of amylose and amylopectin. However, thermal characteristics of wheat starch, especially when glyphosate was applied at the soft dough stage, showed significant differences. A decrease in the average amylopectin chain length and differences in the proportion of short-, medium-, and long-chain amylopectin was also observed. Overall, this study shows that the pre-harvest application of glyphosate can affect wheat starch chemistry, especially if applied earlier than recommended. PRACTICAL APPLICATIONS: Glyphosate is the most commonly used herbicide in the world, and it is sometimes used pre-harvest during wheat cultivation. The recommended time of application is 7days prior to harvest when the crops are in the ripe stage of physiological maturity. However, some crops may not be at this stage during application due to non-uniform maturation in the field. The goal of this work was to determine the effect of glyphosate application time (recommended/ripe stage vs. early/soft dough stage) on wheat starch chemistry. The results show that the starch chain length characteristics and thermal behavior are impacted, especially if applied early. Thus, this study shows the importance of timely application to avoid effects on starch chemical properties, which in return could impact starch functionality in food systems. This information is critical in the field of agriculture and to our knowledge this study is one of the first in this area.

Integration of spectroscopy and image for identifying fusarium damage in wheat kernels.

Hyperspectral imaging (HSI) was studied for the detection of varying degrees of damage in wheat kernels caused by Fusarium head blight (Gibberella zeae), a major disease in wheat worldwide. A total of 810 wheat kernel samples were collected from a field trial with the three levels of Fusarium infection, healthy, moderate, and severe. Hyperspectral image of the wheat kernels was acquired over a wavelength range of 400-1000nm. The raw spectral data were pre-processed, and then the optimal wavelengths were selected using principal component analysis (PCA), successive projection algorithm (SPA) and random forest (RF). The image features were extracted based on the optimal wavelengths, and then the spectral features and image features were combined as fusion features. Support vector machine (SVM), random forest (RF) and naive Bayes (NB) were employed to build the classification models to identify the degrees of Fuasrium damage based on spectral and fusion features. The best performance was obtained by using the SPA-RF method to select the optimal wavelengths and corresponding image features, with a classification accuracy of 96.44%. The method developed from this study can provide a more effective way to identify the degrees of Fusarium damage in wheat kernels.

Comparison of Vis-NIR and SWIR hyperspectral imaging for the non-destructive detection of DON levels in Fusarium head blight wheat kernels and wheat flour

Fusarium head blight is a severe wheat disease that affects yield and food safety. Chemical and biological methods are the main techniques for detection of the deoxynivalenol (DON) content, but despite being highly accurate, these techniques are destructive and time-consuming. A nondestructive, efficient and accurate method for estimating the DON content levels of scabs is required in post-harvest wheat processing. Hyperspectral imaging (HSI) systems have the capability of detecting subsurface defects and the contents or properties of organic substances. Because this method is nondestructive and fast and can be fully automated, the HSI technique was used in this study for detection of the wheat grain quality. Mycotoxins can destroy tissues, cells, and even molecules in cereals. Furthermore, the contents or properties of organic substances such as proteins, carbohydrates, and lipids in wheat infected by DON toxin undergo changes that can be reflected in their spectral characteristics. In this study, data for both wheat kernels and wheat flour obtained using two types of HSI systems, i.e., visible near-infrared (Vis-NIR) (ranging from 400 to 1000 nm) and short-wave infrared (SWIR) (ranging from 1000 to 2500 nm), were investigated. Ninety-six samples of wheat kernels and wheat flour samples were divided into two groups, and the multiplicative scatter correction (MSC) and standard normal variate (SNV) were used for spectral data pre-processing. A support vector machine (SVM) and a sparse autoencoder (SAE) network were used to the build classifiers with the extracted important wavelengths by genetic algorithm (GA). The results suggest that it is possible to detect wheat kernel samples in the Vis-NIR bands and to detect wheat flour samples from SWIR data with high accuracy. Moreover, for wheat kernel samples, the results of the SAE and SVM models were roughly the same. For all types of classification models for wheat kernel samples using the Vis-NIR, the MSC-GA-SAE model achieved the highest prediction accuracy (100% for both the training and test sets). In contrast to the wheat kernels samples, for the wheat flour samples, the SNV-GA-SAE models achieved better results with the SWIR data in terms of correctly classifying the samples (100% for the training set and 96% for the test set), which suggested that it is possible to detect wheat flour samples from SWIR data with high accuracy.

Individual wheat kernels vigor assessment based on NIR spectroscopy coupled with machine learning methodologies

Knowledge of the seed vigor status of individual wheat kernels could provide scientific evidence for the screening of excellent germplasm and the breeding of seedlings. Although many factors collaborate to reduce or render seed vigor, many methods have been employed to detect individual kernel vigor. This study aims to demonstrate the feasibility for using near-infrared (NIR) spectroscopy to detect individual wheat seed vigor and determine suitable machine learning classification models. For this study, 1152 wheat kernel samples were selected, and five-sixths of the portion was treated by artificial aging (AA). All seeds spectra were acquired using a single-seed near-infrared system covering the spectral range of 1200–2400 nm. After NIR spectral collection, all kernels underwent a germination test to confirm their vigor. The spectral data from kernels within 3 germination days, 5 germination days and the non-germination kernels were further used for the development of three-category classification models. After pretreatment by using Savitzky-Golay (SG) second derivative-method and standard normal variate (SNV) correction, the high-dimension spectral data were smoothed, and then were reduced to select most effective wavelengths by two spectral dimensional reduction algorithms: principal component analysis (PCA) and successive projections algorithm (SPA). Four machine learning methodologies, support vector machine (SVM), extreme learning machine (ELM), random forest (RF) and adaptive boosting (AdaBoost) were combined with the two spectral dimensional reduction algorithms to build eight models to discriminate and predict each wheat kernel’s vigor. The results demonstrated that the eight three-category machine learning classification models developed with the two spectral dimensional reduction algorithms provided comparable results for individual wheat kernel vigor. The accuracies of the eight models were higher than 84.0%, and PCA-ELM and SPA-RF models afforded the two highest classification accuracies at 88.9% and 88.5%, respectively. The macro-average F1 of these two models were at the same level of 0.887, which means these two models had almost the same ability to assess kernel’s vigor. This study could serve as a major step towards the development of a fast and non-destructive high-throughput NIR-based sorting system of individual wheat kernel vigor determination for plant breeders, wheat quality inspectors, wheat processors, etc.

Differentiation between Aspergillus flavus and Aspergillus parasiticus isolates originated from wheat

The species of the genus Aspergillus, A. flavus and A. parasiticus, are the most aflatoxin-producing fungi. All previous studies carried out under the production conditions of Serbia showed no presence of A. parasiticus on wheat kernel. On the basis of changes in climatic factors, such as occurrence of high temperatures and prolonged droughts, which favour increased frequency of Aspergillus spp., we assumed that this pathogen can also be present in Serbia. The significance of direct losses as a consequence of wheat kernel infection, as well as potential contamination with aflatoxins, have pointed out to the need to determine the presence of toxigenic potential of A. flavus and A. parasiticus isolates originating from Serbia. For that purpose, wheat kernel samples were collected in nine locations. According to morphological, toxicological and molecular traits of isolated fungi, the presence of A. flavus and A. parasiticus was confirmed. This is the first time that A. parasiticus was identified on wheat under climatic conditions in Serbia. This study indicates that these pathogens may be a potential danger in wheat production in the region of Serbia. This danger will be much more certain if global climatic changes continue as they will provide more intensive development of these pathogens.

Natural Occurrence of Alternaria Toxins in the 2015 Wheat from Anhui Province, China.

The exposure to Alternaria toxins from grain and grain-based products has been reported to be related to human esophageal cancer in China. In this study, a total of 370 freshly harvested wheat kernel samples collected from Anhui province of China in 2015 were analyzed for the four Alternaria toxins tenuazonic acid (TeA), tentoxin (TEN), alternariol (AOH) and alternariol monomethyl ether (AME) by high performance liquid chromatography-tandem mass spectrometry method (HPLC-MS/MS). TeA was the predominant toxin detected followed by TEN, AOH and AME. The concentrations of the four Alternaria toxins varied geographically. The samples from Fuyang district showed higher TEN concentration levels than the other regions studied (p < 0.05). Furthermore, 95% (352/370) of the wheat samples were positive for more than one type of Alternaria toxins. Positive correlation was observed between concentration levels of TeA and TEN, AOH and AME, TeA and AOH, and the total dibenzopyrone derivatives (AOH + AME) and TeA. Results indicate that there is a need to set the tolerance limit for Alternaria toxins in China, and more data on the contamination of these toxins in agro-products is required.

Effects of region, genotype, harvest year and their interactions on δ13C, δ15N and δD in wheat kernels

The objective of this study was to investigate the influences of region, genotype, harvest year and their interactions on stable carbon, nitrogen and hydrogen isotopic ratio (δ13C, δ15N and δD) fingerprints in wheat kernels. A total of 270 wheat kernel samples including ten genotypes were collected from three different regions of China during 2011–2013 harvest. Analysis of variance was employed to investigate the effects of region, genotype, harvest year and their interactions on the δ13C, δ15N and δD. The results showed that the δ13C and δ15N values in wheat kernels were significantly influenced by the region, genotype, harvest year and their interactions (region×genotype, genotype×year, region×year and region×genotype×year), δD was significantly affected by region, genotype, harvest year and region×year. Region accounted for the largest proportion of the total variation and explained 47.57%, 58.02% and 27.96% for δ13C, δ15N and δD, respectively.

Possible reservoir and routes of transmission of Cronobacter (Enterobacter sakazakii) via wheat flour

Contamination of food products is a major route of transmission for opportunistic foodborne pathogen. Cronobacter spp. (formerly Enterobacter sakazakii) are an important group of emerging opportunistic foodborne pathogens that may cause rare but severe systemic infection such as neonatal meningitis, septicemia, and enterocolitis in neonates. Here, we tried to investigate the possible natural reservoir and routes of transmission of this pathogen. Samples of food (N = 141) were screened for the presence of the bacterium, and 34 isolates of Cronobacter spp. were collected in total. Of the initial of 108 samples including infant formulas, dry milk powder, milk and milk related beverages, cereal (products), chocolate and candy, miscellaneous food products, 12% were positive for Cronobacter spp., with the highest percentage (69.3%) coming from cereal products. Further investigation indicated that 100% of 13 wheat flours, 5 of 8 (62.5%) wheat kernel samples, 100% of 5 different brands of dry noodles, and 3 of 7 (42.9%) deep-frozen dumpling samples contained Cronobacter spp. Biochemical analysis (ID32E strips) of the 34 isolates resulted in 11 different biogroups based on the utilization of 8 substrates. In addition, pulsed field gel electrophoresis (PFGE) demonstrated extremely high genetic diversity as 24 unique PFGE profiles were revealed among the 25 isolates acquired mainly from wheat flour or related products. We therefore conclude that wheat flour is one likely reservoir and/or transmission route for Cronobacter spp., and special care should be taken while preparing infant foods or formulas in order to avoid cross-contamination from this source.

Development of a Sensitive Monoclonal Antibody-Based Enzyme-Linked Immunosorbent Assay for the Analysis of Paclobutrazol Residue in Wheat Kernel

An indirect competitive enzyme-linked immunosorbent assay (icELISA) was developed with monoclonal antibody (mAb) mAb6H73C9 recognizing the plant growth regulator paclobutrazol (PBZ). The icELISA had a half-maximum inhibition concentration (IC50) and working range of approximately 8.7 and 2.0-50.4 ng/mL, respectively. Average recoveries of PBZ in the wheat (Triticum aestivum) kernel samples were between 84.3 and 118.9% with relative standard deviations between 3.9 and 14.2%. As determined by the icELISA and further confirmed by liquid chromatography-electrospray ionization quadrupole Orbitrap mass spectrometry (LC-ESI-MS) analysis, the maximum residue concentration was about 0.07 mg/kg in the kernel samples, which indicated that PBZ could transfer from PBZ- treated seedlings to the kernel samples. The correlation coefficient (R(2)) between icELISA and LC-ESI-MS results was 0.979, which manifested that the developed icELISA was sensitive enough for monitoring PBZ residues in wheat kernels.

Cyclic hexadepsipeptides in wheat field samples andesyn1 gene divergence among enniatin producingFusarium avenaceum strains

Fusarium avenaceum is one of the most important pathogenic species in agricultural and forest environments of moderate climate, particularly in cereals and legume pulse crops. Numerous mycotoxins can be synthesized by the species, with moniliformin and enniatins (ENN) being the prevailing metabolites. The aims of this work were to examine the amounts of ENN and beauvericin present in naturally contaminated field samples of wheat kernels and chaffs collected in Poland in 2005 and 2009 from heads infected withF. avenaceum, and to reveal the divergence of theesyn1 gene amongF. avenaceum strains of different origin. ENN-B and ENN-B1 were the major metabolites identified in wheat field samples. Chaff fractions contained significantly more mycotoxins than grain. Samples originating from 2005 were in general less contaminated with ENN than those from the 2009 season. The highest amount of ENN-B found in grain was 28,520 μg/kg. Beauvericin was only found in trace amounts in all the samples tested.F. avenaceum strains isolated from the analysed wheat samples were identified using species-specific DNA marker and translation elongation factor 1α (tef-1α) sequence analysis. A higher level of sequence polymorphism was revealed for the enniatin synthetase (esyn1) gene than ecorded bytef-1α analysis. Moreover, species known to be typical beauvericin producers, e.g.Fusarium oxysporum andFusarium proliferatum, were clustered into a separate branch on the dendrogram, apart from the strains of ENN-producing species, i.e.F. avenaceum andFusarium scirpi.

Study of Fungal Colonization of Wheat Kernels in Syria with a Focus on Fusarium Species

Wheat is one of the main crops in Mediterranean countries, and its cultivation has an important role in the Syrian economy. In Syria, Fusarium head blight (FHB) has not been reported so far. Mycological analysis of 48 samples of wheat kernels collected from cultivation areas with different climatic conditions were performed in 2009 and 2010. Fungal isolates were identified at the genus level morphologically; Fusarium species were characterized morphologically and by species-specific PCR. The most frequent fungal genera found were Alternaria spp. and Cladosporium spp., with frequencies of 24.7% and 8.1%, respectively, while the frequency of Fusarium spp. was 1.5% of kernels. Most frequent Fusarium species were F. tricinctum (30% of all Fusarium isolates), F. culmorum (18%), F. equiseti (14%) and F. graminearum (13%). The mycotoxin production potential of selected Fusarium isolates was assessed by HPLC-MS analysis of rice cultures; chemotyping by PCR was carried out for comparison. All six F. graminearum strains tested produced small amounts (<3 mg/kg) of nivalenol (NIV). All ten F. culmorum strains tested produced large amounts of trichothecenes (>100 mg/kg); four strains produced NIV and six strains produced deoxynivalenol (DON) and 3-acetyl-deoxynivalenol (3Ac-DON). PCR chemotyping lead to an oversimplified picture, because all 3Ac-DON chemotype strains produced more DON than 3Ac-DON; furthermore, the strongest NIV producers produced significant amounts of DON. All tested strains of F. culmorum, F. graminearum, F. pseudograminearum (two strains) and most F. equiseti strains (five of six strains) produced zearalenone. Grains of durum wheat were more frequently colonized by Fusarium spp. than grains of soft wheat. Incidence of Fusarium spp. in irrigated fields was higher than in rainfed fields. The incidence of Fusarium strains producing mycotoxins raises concerns about the risk of Fusarium head blight to Syria and its consequences for public health.

Effects of Wheat Origin, Genotype, and Their Interaction on Multielement Fingerprints for Geographical Traceability

The objective of this study was to investigate the effects of origin, genotype, and their interaction on multielement fingerprints in wheat kernels to provide theoretical basis for geographical traceability. Ten varieties were grown in three different regions of China during the 2010-2011 growing seasons. The concentrations of 10 elements (Na, Mg, Ca, V, Mn, Fe, Cu, Zn, Mo, and Ba) were determined in 90 wheat kernel samples and 30 provenance soil samples. Multiway analysis of variance results demonstrated that both origin and genotype had significant influences on the content of each element, and their interaction had significant influences on the contents of Mn, Fe, Cu, Zn, Mo, and Ba. The elements Na, Ca, Fe, Zn, and Mo were associated with origin, and Mg, Mn, Cu, and Ba were related to genotype. Na, Ca, Fe, Zn, and Mo were proved to be good indicators to discriminate wheat geographical origin.

Effect of Aspergillus niger xylanase on dough characteristics and bread quality attributes.

The present study was conducted to investigate the impact of various treatments of xylanase produced by Aspergillus niger applied in bread making processes like during tempering of wheat kernels and dough mixing on the dough quality characteristics i.e. dryness, stiffness, elasticity, extensibility, coherency and bread quality parameters i.e. volume, specific volume, density, moisture retention and sensory attributes. Different doses (200, 400, 600, 800 and 1,000IU) of purified enzyme were applied to 1kg of wheat grains during tempering and 1kg of flour (straight grade flour) during mixing of dough in parallel. The samples of wheat kernels were agitated at different intervals for uniformity in tempering. After milling and dough making of both types of flour (having enzyme treatment during tempering and flour mixing) showed improved dough characteristics but the improvement was more prominent in the samples receiving enzyme treatment during tempering. Moreover, xylanase decreased dryness and stiffness of the dough whereas, resulted in increased elasticity, extensibility and coherency and increase in volume & decrease in bread density. Xylanase treatments also resulted in higher moisture retention and improvement of sensory attributes of bread. From the results, it is concluded that dough characteristics and bread quality improved significantly in response to enzyme treatments during tempering as compared to application during mixing.

Identifying nutrition sensitive spectral changes in various winter wheat samples

The hyperspectral imaging spectroscopy is a promising future tool in the field of optical remote sensing and it creates new perspective for modern information management in site specific agricultural production. One can determine quantitative relationships between the environmental and physiological parameters of vegetation cover and the soil quality parameters as well as the features of the reflectance spectra by the newgeneration data monitoring and sampling method. These reflectance spectra have characteristics of the different crops and provide with the possibility of accurate classification and detection. The objective was to present the technological capabilities of hyperspectral imaging and show some exprimental results of nutrient sensitive changes in the winter wheat spectra. There were found two characteristic wavelength ranges: the 500 to 800 nm for wheat kernel samples and the 1650 nm to 1800 nm for wheat ear samples where fertilizer treatments showed definite trend on the basis of the normalized reflectance spectra.

Trichothecene mycotoxin genotypes ofFusarium graminearum sensu strictoandFusarium meridionalein wheat from southern Brazil

A total of 82 fungal isolates was obtained from wheat kernel samples affected by fusarium head blight collected from 20 locations in southern Brazil. Polymerase chain reaction (PCR) assays were used to characterize trichothecene mycotoxin genotypes [deoxynivalenol (DON), nivalenol (NIV) and two acetylated derivatives of DON]. To identify isolates that producing DON and NIV, portions of theTri13gene were amplified. To identify 3‐acetyl‐deoxynivalenol (3‐ADON) and 15‐acetyl‐deoxynivalenol (15‐ADON) genotypes, portions ofTri3andTri12were amplified. Nearly all of the isolates studied (76/82) were of the DON/15‐ADON genotype. Six of the isolates were of the NIV genotype. The DON/3‐ADON genotype was not observed. Portions of three genes were sequenced from representative isolates of the NIV and DON/15‐ADON genotypes and compared with sequences from curated reference isolates ofFusariumin GenBank.blastqueries for individual gene sequences and pairwise comparisons of percentage identity and percentage divergence based on 1676 bp of concatenated DNA sequence suggested that the isolates representing the DON/15‐ADON genotype wereFusarium graminearum sensu strictoand the isolates representing the NIV genotype wereFusarium meridionale. This is the first detailed report of trichothecene mycotoxin genotypes ofF. graminearumandF. meridionalein Brazil.

Influence of High Molecular Weight Glutenins on Viscoelastic Properties of Intact Wheat Kernel and Relation to Functional Properties of Wheat Dough

ABSTRACTHigh and low molecular weight glutenin subunits (HMW‐GS and LMW‐GS, respectively) are the main factors determining the viscoelastic properties of wheat dough. The mechanical and viscoelastic properties of 29 samples of wheat kernels differing in HMW‐GS were evaluated with load‐compression tests. Samples were grouped by genotypes differing in HMW‐GS composition (allelic variants: Glu‐A1: null, 1, 2*; Glu‐B1: 7, 7+8, 7+9, 13+16, and 17+18; Glu‐D1: 5+10, 2+12). Groups representing Glu‐A1 1 and 2*; Glu‐B1 7, 7+9 and 17+18; and Glu‐D1 5+10 generally possessed hard grain and showed the largest kernel elasticity values, while those representing subunits Glu‐A1 null; Glu‐B1 7+8; and Glu‐D1 2+12 had soft kernels and showed lower elastic work values. Genotypes possessing HMW‐GS 1, 17+18 and 5+10 gave large SDS‐sedimentation values and better dough viscoelastic properties than those with allelels: null, 7+8, and 2+12. Kernel hardness showed significant correlation with the dough‐strength‐related parameters: SDS‐sedimentation; dough mixing time; and the alveographic parameters, W and P. There was a negative correlation between kernel plastic work and dough mixing time and the dough tenacity/extensibility parameters, P/L. The significant relationship between sedimentation tests and kernel elastic work seems to indicate that elastic work is related to genotype (protein composition). The general tendency was that higher values in kernel elastic work and size corresponded to better dough rheological quality. Mechanical properties of the kernel were significantly related to the elastic behavior measured in a single wheat kernel. The use of the compression test on individual kernels is easy, rapid and nondestructive and therefore seems to show potential use as a rapid tool in breeding to improve wheat quality.

Effects of fertilisers on winter wheat infection caused by Fusarium species

Effects of fertilisers on the grain yield (t ha-1) and the development of mycobiota, especially of the Fusarium species, in winter wheat kernels were observed. Fertilisers were applied in the following variants: T1 - 30m3 of slurry (pre-sowing treatment) and 25 m3 of slurry (top-dressing), T2 - 22.500 kg of manure (pre-sowing treatment) and 220 kg of urea (top-dressing), T3 - 300 kg of urea (top-dressing) and T4 - the control without application of fertilisers. The average wheat grain yield was the highest in the treatment T2 (6.9 t ha-1), then in T3 (6.3 t ha-1) and T1 (6.2 t ha-1), while the lowest wheat grain yield (4.3 t ha-1) was registered in the control (T4). Fungi of genera Alternaria (88.8-96.3%) and Fusarium (3.7-11.1%) were mainly isolated from all wheat kernel samples collected after harvest (T1-T4). Species of the genus Dreschlera were isolated in treatments T1 (0.3%) and T2 (0.2%). The species Stemphylium botryosum was isolated only in the treatment T1 (0.2%). F. graminearum (3.5-10.8%) was isolated from wheat kernels in all observed treatments, while F. sporotrichioides was isolated in treatments T1 (0.6%), T2 (0.5%) and T3 (0.3%). F. poae (0.3%) and F. subglutinans (0.2%) were isolated in the treatment T2, while F. graminearum was predominantly present in treatments T3 (10.8%), T1 (8.7%) and T2 (7.8%), and in the control T4 (3.5%). The obtained results point out that the application of urea affected the decrease in the intensity of Alternaria species infestation, but it also affected the increase of frequency of Fusarium species, especially F. graminearum, in comparison with the control and other treatments. Negative correlation was registered between the grain yield and the intensity of infestation of Fusarium species (collectively) and F. graminearum (individually).