Search Results (353)

Hairless canary seed (Phalaris canariensis L.) can play significant roles in human health and nutrition due to its unique nutrient profile. It belongs to the Gramineae family similar to common cereal grains like wheat, rice and corn. On the other hand, the traditional canary seed is characterized by the presence of silicified spicules or hairs on the hulls of the kernel that could pose health hazards to humans. The hairless canary seed was developed in Canada by a conventional breeding program to mitigate the health concerns associated with the silicified hairs. The hairless grain is silica free, i.e., totally glabrous, and is granted regulatory food approvals by Health Canada and US-FDA. The hairless grain holds a great potential as a whole grain functional food ingredient due to its unique nutritional and functional attributes. As a cereal grain, it is rich in protein that is non-gluten and exceptionally high in tryptophan and bioactive peptides. The grain also contains reasonable amounts of carotenoids, polyphenols, and healthy unsaturated oil. Because of these special characteristics, it is considered a promising nutritious and therapeutic food. This review provides insights into the potential of hairless canary seed as a functional ingredient in products designed to mitigate oxidative stress, diabetes and celiac disease and/or to improve vision and cognition. Full article

A new method of selecting wheat genotypes for tolerance and resistance to Pratylenchus thornei could enhance early-generation selection in wheat-breeding programs. Currently, the tolerance of fixed genotypes is determined in field experiments at a P. thornei-infested site, and resistance indices are determined by inoculated glasshouse experiments. For early-generation selection from segregating populations, resistance screening is limited to assessing single plants for resistance only using glasshouse experiments. The objective of this study was to develop a novel method that evaluates a single plant for both tolerance and resistance by using low density (LD) sowing in the field. Four replicated LD (1, 4, 16 and 32 plants/m²) field experiments evaluated 14 or 15 fixed wheat genotypes over two growing seasons in a field with damaging population densities of P. thornei (>2500 P. thornei/kg soil). To check the validity of these experiments, a linear regression analysis was performed for each experiment between the single plant grain yield and the population density of P. thornei with the published tolerance and resistance indices derived from multiple field and glasshouse experiments, respectively. Tolerance was best determined by the grain yield of each single plant grown at a density of 16 plants/m² in 2021 (R² = 0.63, p < 0.001) and 4 plants/m² in 2022 (R² = 0.79, p < 0.001), when compared to published results of tolerance indices assessed by grain yield from plots grown at 100 plants/m². Resistance was best determined from the final population density of P. thornei in the soil and roots under each single plant when grown at a density of 4 plants/m² in 2021 (R² = 0.73, p < 0.001) and 1 plant/m² in 2022 (R² = 0.54, p = 0.001), when compared to published resistance indices derived from multiple glasshouse resistance experiments. This study demonstrated that LD can be used to effectively identify individual plants with both tolerance and resistance to P. thornei, with single-plant ultra-low densities (ULD) between 1 and 4 plants/m² being the most suitable. The advantage of using ULD sowing in the field for segregating populations of wheat over single plant glasshouse resistance screening experiments is the ability to simultaneously screen plants for tolerance to P. thornei. Full article

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), represents a major global threat to wheat (Triticum aestivum. L). Planting varieties with adult-plant resistance (APR) is an effective approach for long-term management of this disease. The Chinese winter wheat variety Lantian 25 exhibits moderate-to-high APR against stripe rust under field conditions. To investigate the genetic basis of APR in Lantian 25, a set of 219 F₆ recombinant inbred lines (RILs) was created from a cross between Lantian 25 (resistant parent) and Huixianhong (susceptible parent). These RILs were assessed for maximum disease severity (MDS) in Pixian of Sichuan and Qingshui of Gansu over the 2020–2021 and 2021–2022 growing seasons, resulting in data from four different environments. Genotyping was performed on these lines and their parents using the wheat Illumina 50K single-nucleotide polymorphism (SNP) arrays. Composite interval mapping (CIM) identified six quantitative trait loci (QTL), named QYr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS and QYr.gaas-4BL, which were consistently found across two or more environments and explained 4.8–12.0% of the phenotypic variation. Of these, QYr.gaas-2BL, QYr.gaas-2DS, and QYr.gaas-3BS overlapped with previous studies, whereas QYr.gaas-2BS, QYr.gaas-2DS, and QYr.gaas-4BL might be novel. All the resistance alleles for these QTL originated from Lantian 25. Furthermore, four kompetitive allele-specific PCR (KASP) markers, Kasp_2BS_YR (QYr.gaas-2BS), Kasp_2BL_YR (QYr.gaas-2BL), Kasp_2DS_YR (QYr.gaas-2DS) and Kasp_2DL_YR (QYr.gaas-2DL), were developed and validated in 110 wheat diverse accessions. Additionally, we identified seven candidate genes linked to stripe rust resistance, including disease resistance protein RGA2, serine/threonine-protein kinase, F-box family proteins, leucine-rich repeat family proteins, and E3 ubiquitin-protein ligases. These QTL, along with their associated KASP markers, hold promise for enhancing stripe rust resistance in wheat breeding programs. Full article

Integrated application of chemical fertilizers with organic manure might improve crop yields and N-use efficiency (NUE, grain yield per unit N uptake), but the underlying physiological mechanisms are unclear. In this study, we aimed to examine the effects of combined inorganic and organic fertilizers on wheat biomass allocation, root growth, water-soluble carbohydrates (WSCs) translocation, leaf senescence, N uptake, and their relationship with yield and NUE. We established a 2-year factorial field experiment with five nutrient treatments with ratios of inorganic: organic fertilizers from 0 to 1, and three varieties—two new: Weilong169 and Zhongmai578; and one reference: Xiaoyan22. The yield ranged from 3469 to 8095 kg ha⁻¹, and it generally declined in response to a higher proportion of organic fertilizer. The NUE increased when there was a higher proportion of organic fertilizer. Weilong169 exhibited higher NUE than Zhongmai578, and both new cultivars outperformed the reference variety in the N harvest index. The yield correlated with leaf senescence traits and harvest index, and NUE was associated with WSC translocation and N uptake. The combination of fertilizers with a low portion of organic maintained yield and improved NUE; Weilong169 had the highest yield, NUE, and N harvest index. A low portion of organic manure substitution for chemical fertilizer suited all varieties. A new variety with a higher yield, N harvest index, and NUE highlights the importance of N traits in breeding programs. Full article

Pre-harvest sprouting of wheat is the premature germination of ripened wheat (Triticum aestivum L.) kernels in the spike before harvest and is influenced by a combination of environmental and genetic factors, and their interaction. This greatly affects grain yield and quality, thus posing a threat to food security and sustainable agriculture. Pre-harvest sprouting has been studied for over 30 years in South Africa and remains a trait of interest in our wheat breeding programs amid climatic change. This paper therefore provides a comprehensive review of the progress made, as well as the challenges and limitations encountered, in breeding wheat for pre-harvest sprouting tolerance in South Africa. Future prospects and research directions are also discussed. Conventional breeding has been the main breeding strategy used in the country, with the success of breeding commercial wheat cultivars with durable pre-harvest sprouting tolerance for deployment in the three main wheat production regions of South Africa. Therefore, augmenting conventional breeding with molecular markers and modern genomic breeding technologies is anticipated to speed up breeding locally adapted, climate-resilient wheat varieties that balance tolerance to pre-harvest sprouting with high yield potential. This is key to realizing sustainable development goals of food security and sustainable agriculture. Full article

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) resistance and agronomic traits are crucial determinants of wheat yield. Elucidating the quantitative trait loci (QTLs) associated with these essential traits can furnish valuable genetic resources for improving both the yield potential and disease resistance in wheat. Lantian 31 is an excellent Chinese winter wheat cultivar; multi-environment phenotyping across three ecological regions (2022–2024) confirmed stable adult-plant resistance (IT 1–2; DS < 30%) against predominant Chinese Pst races (CYR31–CYR34), alongside superior thousand-kernel weight (TKW) and kernel morphology. Here, we dissected the genetic architecture of these traits using a total of 234 recombinant inbred lines (RILs) derived from a cross between Lantian 31 and the susceptible cultivar Avocet S (AvS). Genotyping with a 15K SNP array, complemented by 660K SNP-derived KASP and SSR markers, identified four stable QTLs for stripe rust resistance (QYrlt.swust-1B, -1D, -2D, -6B) and eight QTLs governing plant height (PH), spike length (SL), and kernel traits. Notably, QYrlt.swust-1B (1BL; 29.9% phenotypic variance) likely represents the pleiotropic Yr29/Lr46 locus, while QYrlt.swust-1D (1DL; 22.9% variance) is the first reported APR locus on chromosome 1DL. A pleiotropic cluster on 1B (670.4–689.9 Mb) concurrently enhanced the TKW and the kernel width and area, demonstrating Lantian 31’s dual utility as a resistance and yield donor. The integrated genotyping pipeline—combining 15K SNP discovery, 660K SNP fine-mapping, and KASP validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, offering a cost-effective model for QTL resolution in common wheat. This work provides breeder-friendly markers and a genetic roadmap for pyramiding durable resistance and yield traits in wheat breeding programs. Full article

Fusarium head blight (FHB) is a major devastating wheat fungal disease. Mycotoxins act as virulent factor for FHB progression, including deoxynivalenol (DON), 15-acetyl deoxynivalenol (15-ADON), 3-acetyl deoxynivalenol (3-ADON), deoxynivalenol-3-glucoside (D3G), and zearalenone (ZEN). To identify resistant germplasm against FHB and mycotoxin accumulation, we evaluated 99 wheat cultivars for FHB severity using point inoculation by three FHB isolates under greenhouse and field conditions. FHB severity of selected varieties evaluated in the fields were correlated with that in greenhouse (p < 0.01). Inoculated spikes from 20 varieties were examined for mycotoxin accumulation, employing an LC-MS/MS method that differentiated five mycotoxins. Five cultivars exhibited resistance to both FHB and mycotoxin accumulation, with FHB severity averaging from 13.36% to 33.37%, and DON accumulation below 2400.0 µg/kg, across various conditions. Seven dominant varieties exhibited moderate resistance to FHB and mycotoxin accumulation. FHB severity was significantly positively correlated with DON accumulation, but negatively correlated to the D3G to DON ratio, across distinct groups of FHB resistance (p < 0.01) after inoculation of three distinct isolates, although no correlation was observed within-group. In the present study, Shannong20, Huaimai20, and Sunlin were identified with resistance to both FHB and mycotoxins with superior agronomic performance, providing promising materials for improving disease resistance in breeding programs. Full article

High grain quality is a key target in wheat breeding and is influenced by genetic and environmental factors. This study evaluated 94 recombinant inbred lines (RILs) from a Pamyati Azieva × Paragon (PA × P) mapping population grown in two regions in Kazakhstan to assess the genetic basis of six grain quality traits: the test weight per liter (TWL, g/L), grain protein content (GPC, %), gluten content (GC, %), gluten deformation index in flour (GDI, unit), sedimentation value in a 2% acetic acid solution (SV, mL), and grain starch content (GSC, %). A correlation analysis revealed a trade-off between protein and starch accumulation and an inverse relationship between grain quality and yield components. Additionally, GPC exhibited a negative correlation with yield per square meter (YM2), underscoring the challenge of simultaneously improving grain quality and yield. With the use of the QTL Cartographer statistical package, 71 quantitative trait loci (QTLs) were identified for the six grain quality traits, including 20 QTLs showing stability across multiple environments. Notable stable QTLs were detected for GPC on chromosomes 4A, 5B, 6A, and 7B and for GC on chromosomes 1D and 6A, highlighting their potential for marker-assisted selection (MAS). A major QTL found on chromosome 1D (QGDI-PA × P.ipbb-1D.1, LOD 19.4) showed a strong association with gluten deformation index, emphasizing its importance in improving flour quality. A survey of published studies on QTL identification in common wheat suggested the likely novelty of 12 QTLs identified for GDI (five QTLs), TWL (three QTLs), SV, and GSC (two QTLs each). These findings underscore the need for balanced breeding strategies that optimize grain composition while maintaining high productivity. With the use of SNP markers associated with the identified QTLs for grain quality traits, the MAS approach can be implemented in wheat breeding programs. Full article

Modern high-yielding crop cultivars are known to have narrow genetic bases, making them vulnerable to biotic and abiotic stresses. However, little is known about the extent of deleterious genetic variants (or mutation burden) present in these cultivars. An attempt was made using RNA-Seq to screen genome-wide deleterious genetic variants in 141 oat and 142 wheat cultivars released through Canadian breeding programs over the past century. The screening identified 5726 and 3022 deleterious genetic variants across all 21 chromosomes of both the oat and wheat genomes, respectively. These deleterious variants were largely harbored in a few cultivars and were involved with diverse biological processes, cellular components, and molecular functions. More highly deleterious variants were predicted in oat, than in wheat, cultivars, and different gene expression profiles at the early seedling stage were observed between oat and wheat cultivars, illustrating different genetic impacts of the oat and wheat breeding programs. Estimating mutation burdens for each cultivar revealed large variations among both the oat and wheat cultivars. These mutation burdens were found to increase from early to recent oat and wheat cultivars and were associated with higher cultivar yields. Genetic analyses also revealed genetic shifts and expansions from early to recent oat and wheat cultivars. These findings provide the first empirical evidence of elevated mutation burdens in Canadian oat and wheat cultivars and are useful for advancing plant breeding programs to minimize genetic risk. Full article

Cytokinins play an important role in plants and are targets of wheat breeding, particularly in terms of flowering and yield. The objective of this study was to determine relative synonymous codon usage (RSCU), molecular weight (g/mol), theoretical isoelectric point, instability index, aliphatic index, and hydrophobicity for the wheat cytokinin sequences from two different databases. The methods employed involved different formulas for calculations. The relative synonymous codon usage values were calculated as the ratio of the observed frequency to the expected frequency for the particular codon. The theoretical isoelectric point was calculated based on dissociation constant for groups of carboxylic acid and amino acids groups. The results showed that values of the relative synonymous codon usage divided amino acids of wheat into two groups. In the first group, values were above 1.6 (significant overrepresentation), such as those for phenylalanine (TTC), and Leucine (TTA). In the second group, values were below 0.6 (underrepresentation) such as those for leucine (CTA) and valine (GTT). In addition, the theoretical isoelectric point (pI) ranged from 4.81 to 6.6, and the instability index values were 34.3 and 38.16. A high degree of instability was observed at 1D and 5D of wheat genomes with values of 54.16 and 50.36, respectively. Principal component analysis (PCA) of the RSCU revealed that the main variation was attributed to PC1, accounting for a total variation of about 72.11%. The amino acids contributing to this variation included isoleucine, leucine, lysine, aspartic acid, and serine. PCA of the theoretical isoelectric point results found that the main variation was attributed to PC1, with a total variation of about 58.88%, and these chromosomes included 5D, 4D, 1A, 4B, and 3D of wheat genomes. Understanding the importance of RSCU in plant breeding helps breeders understand the mechanisms and functional aspects of wheat genomes, thereby enabling the development of wheat genomes for environmental adaptations. These results will provide a reference for nutrition and industrial applications, as well as supporting breeding programs. Full article

Genomic selection plays a crucial role in breeding programs designed to improve quantitative traits, particularly considering the limitations of traditional methods in terms of accuracy and efficiency. Through the integration of genomic data, breeders are able to obtain more accurate predictions of breeding values. In this study, we proposed and evaluated four deep learning architectures—CNN-LSTM, CNN-ResNet, LSTM-ResNet, and CNN-ResNet-LSTM—that are specifically designed for genomic prediction in crops. After conducting a comprehensive evaluation across multiple datasets, including those for wheat, corn, and rice, the LSTM-ResNet model exhibited superior performance by achieving the highest prediction accuracy in 10 out of 18 traits across four datasets. Additionally, the CNN-ResNet-LSTM model demonstrated notable results, showcasing the best predictive performance for four traits. These findings underscore the efficacy of hybrid models in identifying complex patterns, as they integrate skip connections to mitigate the vanishing gradient problem and enable the extraction of hierarchical features while elucidating intricate relationships among genetic markers. Our analysis of SNP sampling indicated that maintaining SNP counts within the range of 1000 to the full set significantly influences prediction efficiency. Furthermore, we conducted a comprehensive comparative analysis of predictive performance among random selection, marker-assisted selection, and genomic selection utilizing wheat datasets. Collectively, these results provide significant insights into crop genetics, enhancing breeding predictions and advancing global food security and sustainability. Full article

Given the increasing demand for wheat and the challenges of climate change, it is essential for breeding programs to adapt their strategies to reach the maximum biological potential of new varieties faster. Our study investigates the relationship between wheat yield, protein content, and starch accumulation over five years of Romanian winter wheat varieties. This study included a total of 25 wheat varieties, comprising 16 newly developed ones and 9 varieties registered and cultivated in Romania. The experiment was conducted in three replications over a period of five years. To monitor the equilibrium pattern, the Glosa variety was used as a reference, known for its optimal balance of yield and protein across Romania, as reported in several studies and farmers’ reports. Our research results indicate an inverse correlation between protein content and yield, whereas starch content exhibits a positive correlation with yield among the wheat varieties analyzed. K-means and Principal Component Analyses (PCA) identified Glosa, Lovrin02, Lovrin08, and Boema as the most balanced varieties regarding yield and grain quality stability. The equilibrium model revealed in the results offers information on trait inheritance and heritability, as similar equilibrium patterns were observed across the 25 analyzed varieties over a five-year testing period. Furthermore, integrating an equilibrium model into computational breeding could provide a framework for enabling breeding programs to optimize yield and grain composition while eliminating low-potential varieties. Full article

Plant breeding is considered to be the science and art of genetically improving plants according to human needs. Breeders in this context oftentimes face the difficult task of selecting among thousands of genotypes for dozens of traits simultaneously. Using a breeder’s selection decisions from a commercial wheat breeding program as a case study, this study investigated the possibility of implementing a recommender system based on the breeder’s preferences to support early-generation selection decisions in plant breeding. The target trait was the retrospective binary classification of selected versus non-selected breeding lines during a period of five years, while the selection decisions of the breeder were predicted by various machine learning models. The explained variance of these selection decisions was of moderate magnitude (${\mathsf{\rho }}_{\mathrm{S}\mathrm{N}\mathrm{P}}^2$ = 0.45), and the models’ precision suggested that the breeder’s selection decisions were to some extent predictable (~20%), especially when some of the pending selection candidates were part of the training population (~30%). Training machine learning algorithms with breeders’ selection decisions can thus aid breeders in their decision-making processes, particularly when integrating human and artificial intelligence in the form a recommender system to potentially reduce a breeder’s effort and the required time to find interesting selection candidates. Full article

The allelic diversity within genes controlling the vernalization requirement (VRN1) and photoperiod response (PPD1) determines the ability of wheat to adapt to a wide range of environmental conditions and influences grain yield. In this study, allelic variations at the VRN-A1, VRN-B1, VRN-D1 and PPD-D1 genes were studied for 89 accessions of Triticum compactum from different eco-geographical regions of the world. The collection was evaluated for heading date in both field and greenhouse experiments under a long photoperiod and without vernalization. Based on heading date characteristics, 52 (58.4%) of the genotypes had a spring growth habit, and all of them carried at least one dominant VRN1 allele, while 37 (41.6%) accessions had a winter growth habit and carried the triple recessive allele combination. The photoperiod-sensitive Ppd-D1b allele was detected in 85 (95.5%) accessions and the insensitive Ppd-D1a allele in four (4.5%) accessions. A total of 10 phenology gene profiles (haplotypes) were observed at four major genes in the T. compactum germplasm collection. The LSD test revealed significant differences in the mean heading date among the different spring phenology gene profiles, both in greenhouse and field conditions. In addition, 21 microsatellite markers (simple sequence repeats, SSRs) were used to assess the genetic diversity in the collection. The 21 SSR markers amplified a total of 183 alleles across all the genotypes, with a mean of 3.2 alleles per locus. The polymorphic information content ranged from 0.49 to 0.94, with a mean of 0.84. The results of this study may be useful for both T. compactum and common wheat breeding programs as a source of agronomic traits. Full article

The productivity and resilience of durum wheat have been enhanced through the selection of accessions, optimizing agronomic and quality traits to address environmental challenges. This study evaluates the performance of 219 durum wheat accessions, including 120 elite lines from a national breeding program (G1 to G120), 63 international lines (G121 to G183), 27 Moroccan varieties (including Faraj, Karim, Tomouh, Marzak, Amria, Chaoui, IRDEN, and others), and nine landraces (G211 to G219, from Imilchil, Rich, and Taounate regions). Trials were conducted at the Jemâa Shaïm experimental station (INRA-Morocco) with an “Alpha lattice” design and two replications. Significant correlations were observed between spike length (SL) and number of spikelets per spike (SPS) (r = 0.950; p < 0.001), and between grain yield (GY) and thousand-kernel weight (TKW) (r = 0.530; p < 0.01), while no correlation was found between quality parameters and GY (r = 0.010; p > 0.05). Principal component analysis (PCA) revealed that agronomic traits explained 77.12% of variability, while quality traits accounted for 95.54%. Elite lines exhibited a high yellow pigment index (14.90), important for technological quality. Traditional landraces performed well in spike length (8.78 cm), thousand-kernel weight (50.23 g), protein content (17.07%), and gluten content (36.90%). Moroccan varieties such as Faraj achieved a grain yield of 6.12 t/ha, while international lines showed the highest SDS value (9.39 mL). These findings highlight the potential of diverse accessions for developing high-yielding, high-quality durum wheat. Full article