Bread Wheat Genotypes Research Articles

Least absolute shrinkage and selection operator regression used to select important features when predicting wheat yield from various genotype groups

Abstract Bread wheat and durum wheat genotypes were grown in field experiments at two locations in New South Wales, Australia across several years and using two sowing times (‘early’ v. ‘late’). Genotypes were grouped based on genetic similarity. Grain yield, grain size, soil characteristics and daily weather data were collected. The weather data were used to calculate water and heat stress indices for four key growth periods around flowering. Least absolute shrinkage and selection operator (LASSO) was used to predict grain yield and to identify the most influential features (a combination of index and growth period). A novel approach involving the crop water supply–demand ratio effectively summarized water relations during growth. LASSO predicted grain yield quite well (adjusted R2 from 0.57 to 0.98), especially in a set of durum genotypes. However, the addition of other important variables such as lodging score, disease incidence, weed incidence and insect damage could have improved modelling results. Growth period 2 (30 days pre-flowering up to flowering) was the most sensitive for yield loss from heat stress and water stress for most features. Although one group of bread wheat genotypes was more sensitive to water stress (drought) in period 3 (20 days pre-flowering to 10 days post-flowering). Evapotranspiration was a significant positive feature but only in the vegetative phase (pre-flowering, period 1). This study confirms the usefulness of LASSO modelling as a technique to make predictions that could be used to identify genotypes that are suitable candidates for further investigation by breeders for their stress-tolerance ability.

Estimation of Combining Ability for Earliness and Morpho-Physiological Traits of some Bread Wheat Genotypes under Optimum and Late Sowing Dates

Estimation of Combining Ability for Earliness and Morpho-Physiological Traits of some Bread Wheat Genotypes under Optimum and Late Sowing Dates

Characterizing grain quality in bread wheat (Triticum aestivum L.) genotypes under heat stress conditions

Characterizing grain quality in bread wheat (Triticum aestivum L.) genotypes under heat stress conditions

Metabolite profiling in ten bread wheat (Triticum aestivum L.) genotypes in response to drought stress

Metabolite profiling in ten bread wheat (Triticum aestivum L.) genotypes in response to drought stress

Estimation of Genetic Parameters in Bread Wheat (Triticum aestivum L.) Genotypes Evaluated Under High Temperature Yield Trial in Ethiopia

The study was carried out to estimate genetic parameters of 49 bread wheat genotypes and standard check evaluated at Kulumsa and Melkasa using alpha lattice design with two replications. The analysis of variance result showed highly significant differences among the genotypes for all traits (P< 0.001), implying the presence of considerable genetic variability for these traits. Out of 50 genotypes, four genotypes such as EBW2113062, EBW2113039, EBW2113037 and EBW2113056 were the top yielding genotypes across the locations. Furthermore, 30 of the 50 genotypes gave grain yield above grand mean whereas 14 genotypes had grain yield above the check, Dursa(1295.05kg/ha). In the other word, about 60% of genotypes were with mean grain yield above the overall mean and 30% of them provided mean grain yield above the check, Dursa, variety. High and moderate heritability estimates were found for most of traits showing that the variation observed was mainly under genetic control. The highest PCV and GCV values were observed for grain yield at both locations indicating better opportunity for improvement in this trait via selection. The phenotypic coefficient of variation (PCV) was generally higher than the genotypic coefficient of variation (GCV) for all characters at both locations. The difference between PCV and GCV was large in TKW followed by PHT and Grain yield indicating that these traits are influenced by the environment. However, differences between them were small for most of the traits indicating low effect of environment on the expression of characters at both locations. The genotypic correlations between grain yield with thousand kernel weights and hectoliter weight were highly significant showing their important contribution to grain yield. Therefore, the identified genotypes with better performance could be utilized in advanced bread wheat yield trial targeted for high temperature condition in the country.

Graphical Analysis of Multi-environmental Trials for Bread Wheat (Triticum aestivum L.) Grain Yield Based on GGE Bi-Plot Analysis

Bread wheat (Triticum aestivum L.) is a crucial crop in Ethiopia, and breeders test newly developed elite lines for superiority to existing cultivars to boost national productivity. The study was undertaken during the 2021–22 to 2022–23 cropping seasons at seven environments in optimum moisture areas of Ethiopian using 36 diverse and advanced bread wheat genotypes to evaluate the GEI by the graphical method of GGE biplot and to identify the genotypes with high mean yield performance and stability. Field experiments were conducted at the Adet, Asasa, Kulumsa, and Sinana research centers in Ethiopia. The experiments were planted in an alpha lattice design replicated three times in six rows of 2.5m long. Row-to-row distance and distance between blocks were 0.2m and 1.5m, respectively. The analysis of variance revealed that genotype, environment, and their interaction showed a highly significant effect on the yield as reflected in the GGE model and the GGE model indicated the suitability of the genotypes EBW202136 (33), Boru (1), and EBW202172 (12), with high mean yield and stability, whereas the genotypes EBW202185 (16) and Deka (36) produced high mean yield, but unstable. Likewise, the genotypes EBW202164 (27) and EBW202192 (29) produced low mean yield and unstable. The AMMI analysis of variance for grain yield across the environments showed that 17.26% of the total variation was attributed to genotypic effects, 64.03% to environmental effects, and 18.71% to GEI effects. Two mega environments were identified based on GGE biplot analysis and the which-won–model indicated the adaptation of genotypes Boru (1), EBW202159 (4), EBW202172 (12), EBW202171 (19), and EBW202136 (33) to first mega-environment and genotypes EBW202157 (3), EBW202166 (5), EBW202160 (6), EBW202162 (9), EBW202185 (16), Dursa (17) and Deka (36) in the second. These approaches allowed the identification of stable and high-yielding genotypes (EBW202136 (33) and EBW202172 (12)) which can be included in the national verification program, with a plan to release a new variety, and other genotypes with high yield could be utilized in breeding programs to further improve grain yield in bread wheat.

Drought Stress, Elevated CO2 and Their Combination Differentially Affect Carbon and Nitrogen in Different Organs of Six Spring Wheat Genotypes

This study aimed to analyze the combined impact of CO2 and drought stress at the flowering stage on carbon (C), nitrogen (N), and CN ratios in leaves, stem, and grains of bread wheat. Six diverse bread wheat genotypes, comprised of two commercial checks, two landraces, and two synthetics derivatives, were grown at two levels of CO2, i.e., 400 ppm and 800 ppm, and drought stress was imposed at the flowering stage through progressive soil drying. Stem, leaf, and grain samples were taken at maturity and concentrations of C and N were determined. Our results indicate that the threshold value of fraction of transpirable soil water (CFTSW) at which it diverges towards closure of stomata was different among genotypes and a higher range of values was estimated under elevated CO2. Drought significantly increased C levels in leaves and N levels in grains but decreased N levels in leaves, which increased CN ratios in leaves. In contrast, drought significantly reduced CN ratios in grains. Genotypes differed significantly in N content in grains, where the landrace derivative L2 maintained the highest N content. Moreover, pronounced changes in leaf N and CN ratios were induced by the combination of elevated CO2 and drought stress. Additionally, combined correlation and biplot analyses indicate a strong positive association of grain CN (GCN) with grain number, weight, and grain yield. These effects possibly interact with drought to strongly interfere with the impact of elevated CO2. The differential performance of the tested genotypes shows that selection of appropriate germplasm is essential to maintain agricultural production.

Characterization of Bread Wheat Genotypes Using SSR Markers for Terminal Heat Tolerance

Wheat is a major global food crop, but its productivity is increasingly threatened by terminal heat stress due to climate change. This study aimed to characterize the genetic diversity and heat tolerance of widely grown bread wheat genotypes using SSR markers to identify heat-tolerant cultivars adaptable to various regions in Bangladesh. A total of 15 genotypes were screened, and 13 polymorphic SSR (Simple Sequence Repeats) markers were used to determine the genetic similarity and categorize genotypes based on their heat tolerance. The molecular analysis revealed 13 polymorphic SSR markers that produced distinct PCR (Polymerase Chain Reaction) bands across the different genotypes. By the conclusion of the study, bread wheat genotypes were categorized as either tolerant or sensitive to heat, and the genetic similarity among the varieties was assessed using molecular markers. The genetic similarity coefficients obtained from the SSR primer screening ranged from 0.00 to 0.925. The lowest genetic distance (0.000) was found in Nadi 2 vs BAW1147 variety pair indicating that they are genetically similar to each other. Comparatively higher genetic distance (0. 925) was observed between BAW 1290 vs BARI Gom 28. The dendrogram divided the fifteen genotypes into two main groups, A and B, both formed at a similar coefficient of 0.05. Group A included seven genotypes and was further divided into two clusters, while Group B comprised eight genotypes, which were also divided into two clusters. The categorization of the genotypes was based on the average Heat Susceptibility Index (HSI), Thousand Grain Weight (TGW), grain yield, and the relative reduction in TGW and grain yield under stress conditions compared to timely sown conditions, aligning with the molecular data. Among the fifteen genotypes, BARI Gom 25, BARI Gom 26, BARI Gom 27, BARI Gom 28, BARI Gom 29, BARI Gom 30, and BARI Gom 31 demonstrated their adaptability to late sown conditions. The heat tolerance observed in these genotypes, as indicated by their SSR marker scores, is anticipated to provide valuable insights for molecular breeding studies focused on heat resistance.

Tolerance Evaluation of Some Bread Wheat Genotypes to Water Deficit through Exploratory Factor Analysis

Tolerance Evaluation of Some Bread Wheat Genotypes to Water Deficit through Exploratory Factor Analysis

Morphological Characterization of Bread Wheat (Triticum aestivum L.) Genotypes Grown in the Sudan Savanna of Nigeria

Morphological Characterization of Bread Wheat (Triticum aestivum L.) Genotypes Grown in the Sudan Savanna of Nigeria

IMPACT OF NITROGEN FERTILIZATION ON BREAD WHEAT: SCREENING FOR CHANGES IN QUALITY, ANTIOXIDANT AND ESSENTIAL AMINO ACID CONTENT

Wheat grain has a unique nutritional value and contains health-promoting and essential components in the daily human diet. Increasing consumer awareness of health and nutrition has led to a greater focus on sustainable and healthy wheat production in the face of climate change. The aim of this study was to determine the effect of nitrogen on yield and protein characteristics as well as antioxidant capacity and essential amino acid profile of bread wheat genotypes adapted to different ecological conditions. Different nitrogen doses (0, 60, 120 and 180 kg ha-1) were applied to 15 genotypes (3 lines, 1 hybrid and cultivars) with different growth habit to determine yield, quality, antioxidant and amino acid composition parameters. As a result of this study, total phenol content, antioxidant activity and gluten index of wheat decreased although grain yield potential increased in genotypes. In the results where the genetic factor is the primary focus, it was established that the responses to nitrogen fertilizer doses exhibited variability across different years particularly the case during the dry season. With regard to the YearxNitrogenxGenotype interaction, a notable increase was observed in total phenol content and antioxidant activity, while a decline was evident in yield, protein, and wet gluten parameters, particularly in the nitrogen dose applied during the dry season. The increase in protein content contributed significantly and positively to the essential amino acid composition. However, increasing the amount of some amino acids negatively affects others. The objective of this study is to identify and contribute insights into the impact of nitrogen factor on product quality, health and nutrition issues, grain yield potential of genotypes, plant breeding and agronomic studies.

Identification of Climate-Smart Bread Wheat (Triticum aestivum L.) Germplasm for Optimum Moisture Areas of Ethiopia

Ethiopia's Bread Wheat Breeding Program conducts annual multi-environment yield trials to develop advanced wheat genotypes for Ethiopian wheat cultivation, ensuring a steady supply of new and improved varieties to meet production and marketing challenges. The objective of this research was to assess potential yield and the interactions between genotype and environment in wheat across multiple environments, as every cultivar has a distinct response to soil and climate. The BLUP analysis reveals that the 22AA and 22KU trials in 2022, along with 21KU trials in 2021 yielded high grain production, indicating optimal testing locations for distinguishing bread wheat genotypes and agroecologies. The study found that seven out of sixteen trials exhibited a higher genetic variance for yield, indicating high genotype discriminating power, with estimates ranging from 0.043 to 0.989 for genetic variance, 0.084 to 1.147 for error variance, and 72.7 to 96.4 for heritability. EBW202471 and EBW202473 are stable genotypes with good yield performance across correlated locations, with EBW202471 showing the highest yield (4.98 t/ha) and Deka showing a lower yield (4.07 t/ha). Three wheat genotypes, EBW202471, EBW202472, and EBW202473, were found to be moderately resistant to moderately susceptible to stem and yellow rust among 20 wheat genotypes. Finally, the two genotypes, EBW202471 and EBW202473, were advanced to National Performance Trials to evaluate their performance alongside top genotypes from regional federal research centers and to be released as new varieties.

Screening of drought tolerance indices for selection of resistance wheat (Triticum aestivum L.) landraces under drought stress conditions

Abstract During the cropping season 2016-2017, an experiment was conducted in a split plot design to study the response of 25 wheat genotypes to drought stress under irrigated and minimal irrigation conditions. Different drought tolerance indices for 25 bread wheat (Triticum aestivum L.) genotypes were evaluated. The calculation drought tolerance indices was based on the grain yield of wheat under irrigated and water stress conditions. The result indicated a significant effect of drought stress on the yield of different wheat genotypes based on mean values of different drought tolerance indices. Among the studied different indices, mean productivity (MP), stress tolerance index (STI), and geometric mean productivity (GMP) were more efficient to discriminate between drought sensitive and drought tolerant genotypes based on the calculation of correlation coefficient and multivariate analysis. Twenty-five genotypes were classified into tolerant and susceptible groups through drought tolerance indices using cluster analysis. Among the genotypes, C-306, WH 1236, WH 1235, and GW 477 having higher yields under drought conditions which showing their stability under stress conditions. The most yield stable genotypes under adverse environment were identified by multivariate analysis of drought tolerance indices individually or in combination. From the result, we concluded that GMP, MP and STI are more efficient drought tolerance indices among other indices to identify stable genotypes under stress conditions.

Genetic dissection and genomic prediction of drought indices in bread wheat (Triticum aestivum L.) genotypes.

Drought constitutes the main obstacle to agricultural productivity in the Central and West Asia and North Africa (CWANA) region, notably leading to substantial reductions in wheat yields due to terminal water stress. The adoption of drought-resistant wheat varieties appears to be a vital strategy to maintain wheat production in the face of climatic challenges. In this context, a study was conducted utilizing a set of 198 elite bread wheat genotypes developed at the International Center for Agricultural Research in the Dry Areas (ICARDA). This set of elite genotypes was evaluated at the Sidi Al-Aidi station in Morocco over two years (2021-2022), under rain-fed and irrigated conditions. Phenotypic assessments for grain yield and drought indices were performed, alongside genotyping the population using 15k SNP markers. These preparatory steps facilitated a genome-wide association study (GWAS) and genomic prediction, leveraging the Mixed Linear Model (MLM) to pinpoint marker-trait associations (MTAs) and candidate genes pertinent to grain yield and drought indices. The results manifested substantial variations in both grain yield and drought indices among the genotypes tested. Grain yield performance ranged from 0.34 to 2.57 t/ha under rain-fed conditions and 1.12 to 4.57 t/ha under irrigated scenarios. The comprehensive analysis identified 39 significant MTAs (p < 0.001) and 14 putative genes associated with drought indices and grain yield. Noteworthy is the marker “wsnp_Ex_c12127_19394952” on chromosome 5B, which displayed a significant correlation with grain yield in rain-fed environments. Furthermore, the most prominent marker linked to tolerance index (TOL) was “BobWhite_c42349_99”, situated on chromosome 5A and associated with the TraesCS5A02G498000 gene. This gene plays a critical role, encoding for catalase protein crucial for response to hydrogen peroxide. These markers could be used for marker-assisted selection in wheat breeding programs targeting drought tolerance.

Evaluation of Bread Wheat (Tritium aestivum L.) Genotype in Multi-environment Trials Using Enhanced Statistical Models

In varietal selection field trials, spatial variation and genotype by environment (GxE) interaction are frequent and present a major challenge to plant breeders comparing the genetic potential of several cultivars. To consistently select superior cultivars that increase agricultural production, bread wheat breeding studies must be evaluated using efficient statistical techniques. By modeling the interactions of geographical field trends and genotypes by environment interaction, this work aimed to forecast the genetic potential of bread wheat varieties across settings and improve selection tactics. The dataset utilized in this investigation consisted of sixteen multi-environment trials (MET) that were carried out using a randomized complete block design (RCBD), with two replications arranged in plot arrays of rows and columns. The findings showed that the factor analytical and spatial models were effective ways to analyze the data for this study under the linear mixed model. By ranking average Best Linear Unbiased Predictions (BLUPs) within clusters, the 16 bread wheat environments were grouped into three mega environments (C1, C2, and C3) based on yield. This served as a selection indicator. Ranking average BLUPs helped in the selection of superior and stable genotypes. The first cluster (C1)'s mean BLUP values were used to score the genotypes' performance; C2 and C3 were excluded because of their limited genetic variety and low genetic connection with the other trials. The genotypes with the highest potential based on this cluster were EBW192346 and EBW192347, chosen for a subsequent verification study to release a variety. The estimates for variance component parameters ranged from 0.013 to 3.024 for genetic variance and from 0.072 to 0.37 for error variance. Hence, scaling up the use of this efficient analysis method will improve the selection of superior bread wheat varieties.

Evaluation of the extent of genetic variability and associated traits of bread wheat (Triticum aestivum L.) genotypes under heat and drought stress environment conditions

Evaluation of the extent of genetic variability and associated traits of bread wheat (Triticum aestivum L.) genotypes under heat and drought stress environment conditions

Evaluate the Genetic Divergence and Principal Component Analysis in Bread Wheat (Triticum aestivum L.)

The current investigation was carried out on some bread wheat (Triticum aestivum L.) genotypes throughout spring season to evaluate their heat tolerance via Cluster Analysis and principal component analysis (PCA). The experiment was accomplished in an augmented block design with 60 genotypes and three replications. Evaluations were carried out on 26 quantitative traits. Cluster analysis showed five clusters, cluster I with 56 genotypes and clusters II, III, IV and V with only one genotype each. The clusters II, III, IV and V have only one genotype each, so their intra-cluster distances were zero. The intra-cluster distance for cluster I was 57.879. The maximum and minimum inter cluster distance was found between cluster II and III (267.377) and between cluster I and II (86.469), respectively. Cluster I showed the earliest (76.689 days) average for early maturity (days to 50% heading) and cluster III showed the maximum (27.664) average for grain yield (grain yield per plant). PCA indicated that the five principal components (PC1 to PC5) accounted for 65.61% of the total variance. PC1 accounted for 11.51% of the total variance and showed positive factor loading for almost traits. Harvest index, grain yield per plant, flag leaf width and leaf rolling showed the highest factor loadings for PC1. As a result of the foregoing data and analysis, it is possible to conclude that there is great potential for effective genetic improvement for grain yield and correlated traits in the present wheat genotypes.

Inheritance and Stability of Grain Yield Traits and Its Components under Salt and Normal Conditions of Bread Wheat Genotypes (Triticum aestivum L.)

Inheritance and Stability of Grain Yield Traits and Its Components under Salt and Normal Conditions of Bread Wheat Genotypes (Triticum aestivum L.)

Morphological and molecular characterization of some bread wheat (Tritium aestivum L.) genotypes

Morphological and molecular characterization of some bread wheat (Tritium aestivum L.) genotypes

EVALUATION OF SPRING WHEAT GENOTYPES UNDER WATER STRESSED CONDITION

Pakistan faces severe challenges in wheat production annually due to the devastating effects of drought stress. Therefore, present research was carried out to evaluate 15 exotic bread wheat genotypes along with the local check variety, Khirman for their performance under drought stress. Analysis of variance revealed that all the traits were significantly different (P&lt;0.01) among the cultivars. Based on mean performance, genotype V-18 showed better performance for all the studied characters, while genotype V-14 showed desirable performance for different traits such as early growth vigor, number of grains spikelet-1, number of grains spike-1, number of spikelets spike-1, spike length, peduncle length, and grain yield plant-1. The local check Khirman also produced desirable values for four different traits, namely early growth vigor, number of grains spike-1, peduncle length, and grain yield plant-1. The cluster analysis divided all the genotypes into three distinct clades. The first cluster comprises V-14, V-18, and the local check Khirman, which performed very well under drought conditions compared to the other genotypes. The presence of these genotypes with the local check Khirman is regarded as indicative of drought-tolerant genotypes. The second cluster comprises nine genotypes, namely V-10, V-11, V-12, V-13, V-16, V-19, V-20, and V-23, which performed moderately compared to the genotypes found in the drought-tolerant cluster. The last cluster comprises four genotypes, namely V-09, V-15, V-17, and V-22, which performed very poorly under drought conditions. Overall, the two exotic lines, V-14 and V-18, which were in the cluster with the drought-tolerant variety Khirman, performed very well and can be considered as drought-tolerant genotypes