جستجوی مقالات مرتبط با کلیدواژه « bread wheat » در نشریات گروه « زراعت »

This study aimed to investigate the effect of sowing date and enviromental factors during different growth stages on some phenological characterisitcs and grain yield of commercial bread wheat cultivars. The experiment was carried out as split-plot arrangements in randomized complete block design with three replications at the Darab reaesrch field station in 2018-19 and 2019-20 cropping cycles. Five sowing dates: October 27, 11, and November 26, December 11, and 26, were assigned to the main plots. Five commercial wheat cultivars: Mehregan, Barat, Khalil, Sarang, and Setareh, were randomized in the subplots. Results showed that the late maturity cultivars, Khalil and Brat, had higher grain yield in earlier sowing dates. Early maturity cultivars, Setareh and Mehregan, had less yield reduction in later sowing dates. The highest and lowest mean grain yield obtained from November 11 (6934 Kg ha-1) and December 26 (5775 kg ha-1), respectively. Number of days and required growing degree-days (GDD) decreased with delaying sowing date. The decrease of required GDD to reach commencement of stem elongation, anthesis and maturity stages from the first to fifth sowing date was 181, 282 and 528 GDD, respectively. Simultaneous effect of weather variables and sowing date on some characteristics revealed that the first two components explained approximately 41% of total variation. Results showed that temperature was the most important factor controlling the phenological stages duration. Despite the importance of temperature, changes in sowing date can alter the required GDD for phenological stages due to other environmental factors. In general, the results of this study can provide an insight into bread wheat cultivars responses to different climatic conditions and development of new bread wheat cultivars adapted to target environments.

As one of the most important cereals, bread wheat is an essential part of food security in the world, which supplies one-fifth of the total calories of the world population. Nowadays, the yield of wheat has been affected by climate change-driven drought as one of the most important abiotic stresses that has become an important threat to food security in the world. Root and stomatal traits are especially important in breeding plants to withstand drought stress. Stomata play a key role in controlling carbon dioxide uptake and water loss through transpiration. Therefore, stomatal characteristics are used as indicators of water status and plant growth, especially in drought stress conditions. Having a wide range of physiological and morphological characteristics, roots play an essential role in absorbing water and nutrients. They are also the first organ that sends signals to control the stomata in response to dryness. Therefore, the difference in the structure of the root system can cause the difference between the performance in different cultivars. This study was conducted to investigate stomatal characteristics and their relationship with the root system and plant performance in 24 bread wheat lines and cultivars.

To investigate the relationship between stomatal dimensions and density with the root system, an experiment was conducted on 24 bread wheat genotypes in the form of a randomized complete block design with three replications in the rainfed conditions of the research farm at Zanjan University Faculty of Agriculture in the crop year 2018-2019. In this experiment, PVC pipes were used to study the root system. Twelve seeds were planted in each tube, which were thinned to seven after germination. In each experimental unit, there were two tubes for each genotype, one of which was used to evaluate traits and final yield, and the second tube was used for root studies. Stomatal traits, including the length and width of stomata and number of stomata per unit area, root traits including root length, root diameter, root volume, root surface, and root biomass, and seed yield were measured in the end. The resulting data from the measured traits were analyzed in the form of a randomized complete block design, and the averages were compared using the LSD method. The data were analyzed using multivariate statistical analyses, including regression analysis, path analysis, and factor analysis, and cluster analysis was used to group genotypes. Statistical calculations were done using SAS 9.0 and SPSS 21 software.

The results of analysis of variance and mean comparison showed high variability among genotypes for all measured traits. The results of the mean comparison of genotypes showed that genotypes 2, 5, 8, and 16 had the highest yield, and genotype 23 had the lowest yield among the examined genotypes. The highest number of stomata on the upper and lower leaf surfaces belonged to genotypes 5 and 2. In terms of root traits, the highest diameter, volume, length, root surface, and root dry weight at a depth of 0-25 cm were recorded for genotypes 2, 3, 18, and 5, respectively. There was a high and significant correlation between the yield and the number of stomata on the upper and lower leaf surfaces, the length and width of  the stomata on the upper leaf surface, diameter, volume, dry weight, and root surface at a depth of 0-25 cm in the soil. Based on the results of stepwise regression analysis, two variables, the number of stomata on the lower leaf surface and root dry weight at a depth of more than 25 cm explained 91.4% of the changes in grain yield. According to the results of the causality analysis of the number of stomata on the lower leaf surface, the most direct effect had a positive effect on seed yield. The results of factor analysis grouped the studied traits into three factors with 82.48% variability justification. The shares of the first, second, and third factors to explaining data changes were 48.86%, 24.62%, and 8.99%, respectively. Based on the plot obtained from factor analysis, genotypes 2, 5, 8, and 16 had high values for the first and second factors. According to the coefficients of the factors, it can be claimed that the genotypes located in this area have high performance, a high number of stomata, and strong root traits, which were found at the soil depth of 0-25 cm. For this reason, these are the genotypes that could produce high yields by absorbing water from the surface layers of the soil by having a large number of stomata and carrying out more photosynthesis. Moreover, the investigated genotypes were divided into three groups from cluster analysis by the ward method and Euclidean distance. Genotypes 2, 5, 8, and 16 were placed in the first group and had the highest mean values for grain yield traits, number and width of stomata on the upper and lower leaf surfaces, and root traits including diameter, volume, and dry weight at a soil depth of 0-25 cm, and root diameter at a depth greater than 25 cm. The lowest values for stomatal length were observed in both leaf surfaces. These were the best genotypes for cultivation in dry conditions.

A strong superficial root system can provide the plant with water from scattered rains that occur with low frequency at the end of the growth period. On the other hand, the increase in the number of stomata along with their smaller size reduces leaf pores and enables a faster response of the stomata, and the rapid response of the stomata maximizes water use efficiency. Therefore, having a strong superficial root system along with high stomatal density can increase seed yield in dry conditions.

 Drought is one of the most important global threats to food production, in addition to that, climate change and the increase in the global population also widen the dimensions of this problem. One of the ways to solve this problem is to create new cultivars with greater tolerance to drought stress. Wheat has been one of the most important sources of human food all over the world and it is used in various food products and processing industries. Wheat together with rice and corn provide more than 60% of calories and protein needed for human nutrition. In areas like Iran, where most of the rain occurs in winter and early spring, wheat will face water shortage and drought stress at the end of the growing season. In crops, one of the effective methods that can minimize the effect of this phenomenon in combination with other methods of water deficit management is the use of high-yielding and drought-tolerant cultivars. Despite the numerous scientific sources published in this field, there are still many gaps in these studies, so studying the effects of drought stress is always a research priority. Ilam province, as one of the irrigated wheat production areas, suffers from the lack of cultivars that are resistant or tolerant to low irrigation conditions, so investigating the response of different wheat genotypes in low irrigation conditions as low input production systems is very important and is addressed in this study. 

In order to evaluate some bread wheat genotypes under normal and drought stress co ditions, 36 wheat genotypes were evaluated in the form of a randomized complete block design in three replicates in the crop year of 2019-2019 in Darehshahr city located in Ilam province. The examined traits include spike length, spike number per plant, spike length, peduncle length, sub-peduncle axis, flag leaf length, flag leaf width, number of stem nodes, plant height, number of spikes per plant, number of seeds per spike, number of seeds per plant. plant, number of tillers, hundred seed weight, single plant seed weight and seed yield. Based on performance under stress (Yp) and normal (Ys), drought tolerance indices such as average productivity tolerance index, harmonic mean, geometric meanproductivity (GMP), stress sensitivity index, stress tolerance index, performance stability index (YSI) and Relative Stability Index (RSI) and Performance Index (YI) were calculated. The mean comparison test was performed using Duncan's method and using R software. Simple correlation (Pearson), decomposition into components, decomposition into factors were also performed between the tested traits. SAS 9.1 statistical software was used for statistical analysis of traits. 

The results of the analysis of variance in drought and normal stress conditions showed that there was a significant difference between genotypes in all traits at the probability level of 1%. The most important significant correlation coefficient in both conditions between seed yield was related to the seed weight of a single plant and the number of seeds per plant. Considering the high and significant correlation of grain yield under stress and non-stress conditions with drought tolerance indices, higher productivity indices, geometric mean productivity (GMP), geometric mean  and stress tolerance index  as the best indicators. were chosen. It seems that in order to evaluate stress tolerance, the selection of genotypes should be based on several indicators. Factor analysis at the drougth stress condition indicated that the two first factors expalined a total of 97. 57% of the variance. The first factor was called the performance stability factor and the second factor was named theStability Factor. The biplot diagram also showed that the genotypes of no. 13 and 47 were placed in the vicinity of the ranges related to drought resistance indices (STI, MP, GMP, and HM) and were introduced as superior genotypes. 

According to the data obtained from analysis of variance in both normal and drought stress conditions, the genotypes were significant in terms of all traits. The significance of the studied traits indicates the existence of diversity between genotypes in terms of the studied traits, and some of these traits can be used to evaluate stress tolerance. The best genotypes had the best averages for peduncle length of genotype 33, for the number of seeds per plant of genotype 5, for seed weight of a single plant and seed yield of genotype 1. The heat map shows the relationship between drought tolerance based on different yield and drought stress toleranceindices. Considering the high and significant correlation of grain yield under stress and non-stress conditions with drought tolerance indices, average productivity indices, GMP, geometric mean and stress tolerance index were selected as the best indices that are able to distinguish tolerant genotypes from other Screen the genotypes. The yield index (YI) had the highest correlation coefficient with grain yield under stress conditions. Based on biplot results, genotypes No. 13 and 47 were the most tolerant genotypes under drought stress conditions more than other genotypes and were introduced as superior genotypes.

Branding of commercial bread wheat cultivars for producing baking products with uniform and acceptable quality by cconsumers is related to sufficient knowledge of different environmental conditions of whaet growing areas in Iran, as well as baking quality properties of grain and dough. Therefore, the aim of this research wwas to investigate grain and dough rheological quality properties including quantity and quality of protein and gluten of the grain samples as well as farinograph and extensograph characteristics and grouping based on various products in the baking industry of 22 irrigated commercial bread wheat cultivars collected from 30 provinces in Iran in 2015-2016. The results showed that the highest and lowest grain protein content was recorded for cv. Mehregan and cv. Uroum with 12.7% and 11.4%, respectively. The wet gluten varied from 20.5% (cv. Sisatan) to 30.9% (cv. Gonbad), zeleny sedimentation value ranged from 18.9 ml (cv. Arg) to 25.5 ml (cv. Mehregan), and SDS sedimentation height varied from 51.3 mm (cv. Sivand) 69.6 mm (cv. Mehregan). The dough prepared from cv. Mehregan (15.5 minutes), Soissons (10.3 minutes) and Chamran 2 (10.1 minutes) showed high dough stability, respectively. The lowest dough stability, among the examined cultivars, was related to cv. Uroum (1.3 minutes) and Sistan (0.2 minutes), respectively. Similar results were observed in extensograph test, cv. Mehregan and cv. Soissons were identified as semi-strong, while cv. Uroum, cv. Ehsan and cv. Heydari had the lowest dough energy. Finally, according to the results of this research some characteristics as growth habit, grain colour, grain hardness, grain protein content, farinograph and extensograph, the studied irrigated commercial bread wheat cultivars were grouped based on end-use products, in four groups, Voluminous breads (industrial breads) and suitable for blending with weaker flours, semi-voluminous breads, flat breads (Iranian breads) and confectionary, cakes, cookies and related industries.

In crop season 2012-2013 wheat genotype "Frncln/Rolf07" was introduced to Iran within an international nursery received from CIMMYT and was studied in experiment of evaluation of yield and agronomic characteristics of spring wheat genotypes in international nurseries in temperate regions. Then in 2013-2014 crop season, it was selected in a preliminary regional wheat yield trial under normal irrigation with an average yield of 8114 kgha-1 compared to the check cultivars Parsi, Sirvan, Pishtaz and sivand, respectively, with grain yield of 8.035, 8.022, 6.914 and 7.985 kgha-1. This cultivar was further investigated in the advanced regional wheat yield trial of temperate regions of the country during 2014-2015 and with average grain yield of 7093 kgha-1 compared to 6495 and 6423 kgha-1 yield of check cultivars Parsi and Sirvan, respectively, and was selected for adaptation evaluation. The average yield of M-94-15 line in temperate climate adaptation experiment during the 2015-2017 crop season under normal conditions was 7231 kgha-1 verses 6688 kgha-1 of Parsi cultivar and 6574 kgha-1 of Baharan cultivar and in general, total mean grain yield was 3% higher than the average of whole genotypes. Due to the good condition of M-94-15 line reaction to stripe rust (O-30MR) and leaf rust (O-30MSS) diseases, as well as the resistance to grain shattering and good bread making quality, this line was selected for study at the level of farmers' fields. Wheat line M-94-15 based on its favorable agronomic characteristics, suitable earliness and good bread making quality was released in 2019 as Farin for cultivation in temperate agro-climatic regions.

Salinity impacts on crop production is further increasing as the global demand for food means agriculture extends into naturally salt-affected lands. Chlorophyll retention and the low sodium traits were associated with salt tolerance in wheat and barley under salinity conditions. Saline soils limit plant growth due to osmotic stress, ionic toxicity, and a reduced ability to take up essential minerals. Barley and wheat have different salt tolerances capacities and are grown as major grain crops in both saline and non-saline soils. The net sodium uptake for a plant growing in 150mM NaCl with perfect osmotic adjustment is similar to actual rates measured for wheat and barley. Our hypothesis is that salinity reduces the growth of wheat more than barley by reducing chlorophyll content. The aims of this study were to analyse the effects of salinity on the growth and yield of barley and wheat cultivars to explore the links between the sodium accumulation and chlorophyll content.

Tow bread wheat cultivars differing in salt tolerance (Arg and Tajan) and a barley cultivar (Nik) were used to assess the change in the chlorophyll content and sodium accumulation over time under saline conditions. Two levels of NaCl (0 and 150 mM NaCl) were imposed as the salinity treatments when the leaf 4 was fully expanded. At 21 days after salt treatment plants were harvested and shoot and root dry weight, root length and sodium root were measured. Sodium accumulation rates and chlorophyll content examined between days 14 and 42 after salt added. Na+ and K+ flag leaf were measured in days 49 after salt treatment started.

Results showed that the rate of sodium accumulation initially was the same for both wheat cultivars in leaf. After 30 days of salinity, the rate of sodium accumulation rose in Arg compared with Tajan. In Nik barley cultivar, shoot sodium concentration was higher than bread whit cultivars. Salinity caused degradation in chlorophyll content in both bread wheat cultivars and at the determination of this experiment Tajan had lower chlorophyll content than Arg cultivar. Nik barley cultivar showed much longer chlorophyll retention than tow bread wheat cultivars. Salinity decrease K+ flag leaf, K+/Na+ flag leaf, shoot and root dry weight, seminal root length, yield and increase Na+ flag leaf and Na+ roots compared to control. Flag leaf K+/Na+ ratio was higher in salt tolerance cultivar (Arg) compared to Tajan and Nik, despite the similar roots sodium concentration. Flag leaf Na+ concentration was the same in tow wheat cultivars and barley under salinity stress and there was no relationship between Na+ exclusion and salt tolerance in cultivars in our experiment. Yield loss of 35 percentages was found in wheat cultivars on average and in barley did not observed remarkable decrease in seed yield. There was may be no beneficial effect of the low Na+ trait at 150 mM NaCl (high salinity level) in all cultivars. Root length reduction in cultivars was due to osmotic stress of salt solution out of the roots. A significant correlation between shoot dry weight and sodium flag leaf showed that sodium concentration in leaf can be used as an index for evaluating salt tolerance.

Given the effect of salinity on shoot growth, it seems that other factors may have influenced net carbon gain before any reduction in the concentration of chlorophyll. It implies that osmotic and tissue tolerance in bread wheat and barley contributed to the salt tolerance in tolerant cultivars and preferential sodium accumulation and maintains in roots and old leave relative to young leaves can caused an increase in salt tolerant. The low shoot sodium concentration was not associated with chlorophyll content in wheat cultivars.

In order to compare 25 genotypes of bread wheat in terms of morpho-physiological and biochemical traits, an experiment was conducted in a randomized complete blocks design with three replications in the rainfed and irrigated conditions at Razi University, Iran, in 2016-2017. GT-biplot was used to evaluate genetic diversity and to identify stable genotypes with high yield and drought tolerance. Combined variance analysis showed that there was high variability among genotypes for the most of traits. Examining the correlation of traits in two environmental conditions showed that morpho-physiological traits; especially yield components, were the most related to yield. The results of the GT-biplot method showed that the first and second principal components explain 41.7% and 40.1% of the total changes in rainfed and irrigated conditions, respectively. Based on the GT-biplot analysis diagrams of genotypes 10, 15, 6, 13, 2, 14, and the Pishtaz cultivar in terms of physiological traits, yield and its components and the traits related to stem and spike in irrigated conditions, and genotypes 10, 15, 6, 18, and 17 in terms of biochemical traits, yield and its components, and traits related to stem and spike in rainfed conditions were recognized as superior genotypes. The genotypes 2 and 6 in irrigated conditions and the genotype 6 in rainfed conditions had the lowest genotype×trait interaction. Finally, the genotypes 10, 15, and 6 were superior in two environmental conditions and the genotype 6 had the least interaction effect in both conditions. Therefore, these genotypes can be used in breeding programs.

IntroductionProduction of high-yielding and stable cultivars is the most important objective of crop breeding programs, including wheat. The final yield of each plant is determined by the potential of genotype (G), the effect of environment (E) and the interaction effect of genotype × environment (GE). Several methods have been presented to study the genotype × environment interaction and determine stable genotypes, which can totally be divided into two main categories, univariate and multivariate. Univariate methods do not provide a complete view of the complex and multidimensional nature of GE interaction, therefore, the use of multivariate methods is suggested to solve this problem. Among the multivariate methods, AMMI and GGE-Biplot methods are more important. The objective of the current experiment was to investigate the interaction between genotype and environment for grain yield of 20 wheat genotypes and to identify stable and high-yielding genotypes.Materials and methods The plant materials of this experiment were 20 wheat genotypes including 18 irrigated wheat lines along with two control cultivars, Rakhshan and Baharan. The experiment was carried out in a randomized complete block design with three replications in five temperate regions (Karaj, Kermanshah, Zarghan, Boroujerd and Mashhad stations) during two cropping years 2019-2020. Two multivariate methods, AMMI and GGE-Biplot, were used to investigate the interaction effect of genotype × environment and to evaluate the stability of genotypes. R software was used to analyze the experimental data using the AMMI method, and Genstat software was used to analyze the data using the GGE biplot graphic method.Research findingsThe results of combined analysis of variance showed that the interaction effect of genotype × year and genotype × year × location were significant at the 1% probability level. Based on the results of AMMI analysis, the effect of environment, genotype and genotype × environment interaction were significant. Based on AMMI1 and AMMI2 models, AMMI stability value (ASV) parameter and genotype stability index (GSI), genotype 12 with an avearage grain yield of 8.27 tons per hectare was determined as the best genotype. The study of GGE-biplot polygon led to the identification of three mega-environments, that Boroujerd had the highest power of representation and differentiation among different environments. Genotypes 12 and 9, in addition to having high yield, had higher yield stability. Genotypes 12 and 9 were placed in the center of the circle as the ideal genotype and genotypes 5, 7 and 18 were ranked next. Based on the results of both methods, genotype 12 was identified as the most stable genotype.ConclusionThe results of AMMI, AMMI stability index (ASV) and genotype stability index (GSI) compared to GGE biplot results showed that all these indices have a good potential to evaluate the performance stability of genotypes. Nevertheless, GGE biplot results are more effective and practical in examining the compatibility and stability of genotypes' performance in different environments due to the ease of interpreting graphical results.

Salt stress affects 20% of global cultivable land and is increasing continuously owing to the change in climate and anthropogenic activities. Globally, wheat is cultivated on non-saline and saline soils, covering an area of approximately 214.79 million hectares (Becker-Reshef et al., 2020). Salinity stress negatively affects the growth and development of wheat leading to diminished grain yield and quality. For this reason, it is important to develop effective strategies to improve yield through salt tolerance. The breeding of salinity-tolerant cultivars through selection and breeding techniques is one of the effective methods in the production and exploitation of saline soil and water.

In order to study the effects of salinity stress on grain yield, phenological and morphological traits and salinity tolerance indices among bread wheat elite lines, two separate experiments in a randomized complete block design with three replications were conducted in two saline and normal environments during two cropping years of 2019-2021. 20 wheat cultivars and elite lines cultivated at the South Khorasan Agricultural and Natural Resources Research and Education Centre. After determining the grain yield in both conditions, MP, GMP, TOL, HARM, STI and SSI indices were calculated and using SAS software, their correlation with grain yield was investigated and using STATISTICA software, the three-dimensional distribution of each cultivar and line was plotted. Combined analysis of variance was performed to determine the main and interaction effects in the two years of the experiment and the means were compared by Duncan's multiple range test at the level of 5% probability. Bartlett's uniformity test was performed before the combined analysis of variance. Analysis of variance and mean comparison was performed using SAS-9.0 software and cluster analysis was performed by Ward method through StatGraphics program.

The reaction of wheat lines were different in two environments and salinity stress reduced grain yield. The experimental results showed that different wheat lines react differently to salinity stress. Salinity stress decreased grain yield and morphological traits in all lines compared to normal conditions. Salinity stress shortens intermediates and reduces plant height and consequently leaf and shoot dry weight by reducing cell proliferation and reducing dry matter accumulation (Dura et al., 2011).The difference between cultivars and lines in terms of all phenological, morphological and grain yield in two years of the experiment was significant, which indicates the existence of appropriate diversity in the wheat elite lines. The existence of this genetic diversity can be very useful for selecting high-yielding wheat cultivars in salinity conditions. In the first year of implementation, Narin, line No. 3 and Barzegar with an average of 6494, 6227 and 6072 kg/ha, respectively, in normal conditions and Barzegar, line No. 18 and Narin with an average of 6361, 6166 and 5805 kg/ha respectively, had the highest grain yield under salinity stress. In the second year of the experiment, line number 16, 10 and 4 with an average of 5388, 5305 and 5155 kg/ha in normal condition and Narin, Barzegar and line No. 3 with an average of 4930, 4611 and 4180 kg/ha respectively, had the highest grain yield under salinity stress. Naturally, wheat lines grain yield under salinity stress was lower than their yield under normal conditions. Under these conditions, the plant leaf area of is greatly reduced, which reduces the photosynthetic capacity of the plant, and as a result, the amount of dry matter produced and ultimately the grain yield of the plant is reduced (Munns et al., 2002).

For selecting wheat cultivars and lines in the areas that are most exposed to salinity stress, YI, HM, GMP, STI, MP, RSI and YSI indices and in areas not exposed to salinity stress, MP and STI indices are suggested. Barzegar and Narin check cultivars and line number 10 were determined as the most tolerant and lines No. 14, 13 and 20 as the most sensitive lines to salinity stress by different indices. Cluster analysis of lines based on STI index led to the placement of Barzegar and Narin cultivars and lines No. 3, 4 and 18 in the first cluster in which the mentioned lines have fewer days to heading and in contrast more days to maturity, grain filling period, thousand-grain weights and higher grain yield.

Salinity stress is one of the most important abiotic stresses that have harmful effects on plant performance and quality. So that according to the predictions made until 2050, 50% of agricultural lands will lose their ability to be cultivated due to salinity. Due to the complexity of salinity resistance traits, there is little information about the number of genes, their chromosomal location, and the relative contribution of each gene in the incidence and phenotypic distribution. Locating quantitative genes can break down this complex genetic model into individual genetic components, in which case quantitative traits will also be investigated like monogenic traits.

In order to identify QTLs controlling some root and shoot traits under salinity stress in bread wheat, 148 recombinant inbred lines of spring bread wheat obtained from the cross of Yecora Rojo cultivar (early and dwarf as a parent of American origin) and genotype No.49 (late and tall as a parent originating from Sistan and Baluchestan) were studied with the parents. This research was carried out in 2020 in the research greenhouse of Mohaghegh Ardabili University under salinity and non-stress conditions in pitmas and perlite culture medium and factorial based on a completely randomized design with five replications. Traits measured in this experiment included root length, root fresh weight, root dry weight, fresh and dry weight of shoots. In this study, linkage map was used based on 202 markers (177 SSR markers and 51 Retro transposon Markers). The map length was about 691.36 cM with the average distance of 3.42 cM in every marker pair, and 21 chromosomes covered in bread wheat. QTL analysis was done based on composite interval mapping (CIM) method, and additive effects were estimated for the identified QTLs.

The results of QTL analysis showed that in stress-free conditions, one QTL for root dry weight and shoot dry weight, two QTL shoot fresh weight and three QTL for root wet weight and root length were identified. Under salinity stress conditions, one QTL was identified for root dry weight and root length, two QTLs for shoot dry weight and three QTLs for shoot fresh weight. Among the QTLs identified, QRFW6A.n had the highest additive effect under normal conditions and QSFW2A.s under salinity stress conditions. For shoot dry weight and root fresh weight under normal conditions and shoot fresh weight under salinity stress, the positive additive effect of the located QTL s showed the inheritance of the desired allele at this site from Yecora Rojo's parent. The phenotypic variance justified by these QTLs varied from 5.43 to 8.97 under normal conditions and from 5.51 to 7.43 percent under salinity stress.

In this study, the number of QTLs identified for root and shoot-related characteristics was low, which could be due to the high number of low-impact QTLs, interactions, and environmental effects.

To determine the optimal sowing date for new bread wheat cultivars as well as to investigate the relationship between grain yield and agro-climatic indices, a field experiment was carried out as split plots layout in randomized complete block design with four replications in two cropping seasons (2020-2021 and 2021-2022) in Gorgan agricultural research station, Gorgan, Iran. Seven sowing dates (from 01 November to 31 December, with 10-day intervals) were assigned to main plots and four spring bread wheat genotypes (cv. Araz, cv. Arman, cv. Taktaz and N-93-9 promising line) were randomized in subplots. Combined analysis of variance showed that the effect of sowing date was significant on grain yield, biological yield and spike no. m-2. While there was no significant difference between cultivars for the aforementioned traits. The highest grain yield obtained from 11 November (6235 kg.ha-1) and 21 November (6105 kg.ha-1) sowing dates, respectively. In delayed sowing dates (11 December, 21 December and 31 December), grain yield of cv. Taktaz was greater than other genotypes. The three sowing dates, 01 November, 11 November and 21 November, were not significantly different for grian filling duration (42.5, 42 and 40.3 days, respectively). However, grian-filling duration significantly decreased in delayed sowing dates (33, 34.1 and 35.6 days, respectively). The highest cumulative growth degree-days (GDD) for grain filling period was calculated for sowing dates 11 November  and 21 November  (782 and 773 GDD, respectively). In conclusion, the results of this experimebt showed that the highest grian yield and maximum energy use efficiency may obtain from the sowing date window of 11 November to 21 November for Gorgan region in Iran.

Bread wheat is one of the most important nutritional products throughout the world. Wheat, like other crops, faces many environmental constraints during the growing season, such as iron deficiency in the soil. Iron is one of the essential micronutrients in plants that act as a catalytic cofactor in several key processes including photosynthesis and respiration.

to investigate the expression pattern of genes encoding transcription factors WRKY1, bZIP56 and NAM-B1 under soil Fe deficiancy, a factorial experiment was conducted in a completely randomized design (CRD) with three replications. Pishtaz (Fe-efficient) and Falat (Fe–inefficient) bread wheat cultivars were planted under Fe deficiency (less than 1.5) and adequacy (5 mg Fe / kg soil) conditions and the relative expression of genes was measured in roots and leaves of the plants at vegetative (one month after germination) and reproductive (30% of heading) stages using real time PCR technique.

the results revealed the considerable enhanced expression of WRKY1 in the roots of Fe-efficient (Pishtaz) and -inefficient (Falat) cultivars at vegetative stage. The highest increased expression of bZIP56 and NAM-B1 genes was observed in the leaves and roots of Fe-efficient cultivar (Pishtaz) at vegetative and reproductive stage, respectively. The bZIP56 expression was also considerably enhanced in the leaves of Fe-inefficient cultivar in both stages.

Due to the increased relative expression of WRKY1 gene in leaves and roots of both cultivars at vegetative stage, this gene is likely involved in activating and inducing the expression of genes participating in iron uptake and transport in the early stages of plant growth. Also, the increased relative expression of bZIP56 gene in the roots of both cultivars in the reproductive stage indicates that this gene might be participated in activating the transcription of genes involved in iron absorption from the soil at the end of plant growth stages.

Protein patterns of SDS-PAGE have been widely used to determine genetic variation in cereals. This study was carried out at The Payame-Noor University of Asadabad to study genetic diversity and protein pattern in bread wheat cultivars before and after flowering. 13 bread wheat cultivars were applied to prepare protein patterns based on SDS-PAGE electrophoresis. The highest genetic distance before bolting was between Zare and Gascogen (8 units). The lowest genetic distance before flowering was between cultivars with a distance equal to zero. This result indicates high genetic similarity between wheat cultivars. The most similarity between the cultivars is the value of one, such as Pishgam and Sayson (one means one hundred percent similarity) or Pishgam and Bezustaya (with one). The least similarity is 0.2 between Zare and Gascogen. Based on cluster analysis these 13 bread wheat cultivars were divided into three groups. The results after bolting were largely similar to the protein pattern before blooming. The most similarity between the cultivars is the value of one. Pishgam and Sayson was one hundred percent similar, and Pishgam and Bezustaya as well. The lowest similarity was observed between Zare and Gascogen cultivars with zero and 0.25 between Zare and other cultivars. Based on cluster analysis, 13 wheat cultivars were grouped into four clusters. Zare, Gascogen and Omid cultivars were placed in separate clusters and the rest of the cultivars were classified in one group. Increasing one group indicates the effect of some proteins that are effective in the developmental stages before and after wheat flowering.

Wheat bread is one of the most important food products in the world. In terms of area under cultivation and production it ranks second among different products. Therefore, Genetic advances in sustainable wheat production can play a large role in global food security. The average wheat production in the world is reported Nearly 3.425 and its average production in Iran is 2.164 tons per hectare. Given the importance of wheat, Production of this product should be increased by cultivating modified genotypes with high grain yield. Wheat grain yield is affected by environmental conditions, genetic potential and its interaction. Identifying genotypes that have good performance and stability in different environmental conditions seems to be complex due to the strong interaction of genotype and environment. The change that occurs in the relative performance of genotypes in different environments is called genotype × environment interaction.Genotype × environment interaction is one of the most important issues in plant breeding which is of great importance in introducing and releasing modified varieties. Cultivation of genotypes in test environments during different years and places it has determined the stability of performance. And genotypes with less genotype × environment interaction are selected. Usually in breeding programs, Genotypes are known as compatible that the variance of their interaction with the environment is small. Among the multivariate methods, GGE biplot method is one of the most important methods for investigating the interaction of genotype × environment and determining stable genotypes.Water scarcity is the most essential limiting element of agricultural production, particulary in arid and semi-arid areas throughout the world. Evaluation of the bread wheat genotypes under different environmental conditions would be useful to identify stable and high yield potential genotypes.

15 new bread wheat lines along with Aftab cultivar were evaluated in a randomized complete block design with three replications in four experimental field stations (Gachsaran Khoramabad, Moghan and Gonbad) during three crop seasons (2017-2020). GGE biplot statistical method (genotype effect + genotype × environment interaction) was used to study stability of genotypes in the studied environments.

Results of combined analysis of variance indicated that the effects of environments, genotypes and genotype × environment interaction were significant. The results indicated that 91.49, 1.54 and 5.03 percent of total variation were related to the environment, genotype and genotype × environment interaction effects, respectively. The polygon-view of GGE biplot recognized five superior genotypes and four mega-environments so that the best genotypes within each environment were determined. Based on the hypothetical ideal genotype biplot, the line G7 with 3818 Kg ha-1 grain yield was the better genotype than other genotypes. Also this genotype showed the most stability and had the high general adaptation to all environments. Biplot of correlation among environments revealed that environmental vectors of Gachsaran and Gonbad were near to 90◦ so, these locations were different environments. The results showed that all environments had high discriminating ability so that could able to show differences between genotypes.

Generally, the results indicated that the line G7 with suitable mean seed yield and high broad adaptability was selected as superior line for further investigation to introduce the new commercial wheat cultivar under dryland conditions. Also, the Moghan environment was the nearest environment to ideal environment that had the highest discriminating ability and representativeness.

The interaction of genotype × environment complicates performance prediction and is a challenge for crop and breeding programs. Performance stability is critical to achievingg high and uniform performance across a wide range of environments. The aim of this study was to investigate the interaction between genotype × environment and to study the compatibility and stability of advanced seven-line grain yield of bread wheat (BC2F6) resulting from cross-breeding of Tabasi local cultivar and modified Typhoon European variety using AMMI model and some stability statistics.

The experiment was conducted in a randomized complete block design with three replications during the cropping years (2017-2018 ) and (2018-2019) in Gorgan, Tehran and Kermanshah and stability analysis was performed for 6 environments. In the field, each plot was planted with a density of four hundred seeds per square meter. Each line was planted in plots with eight four-meter lines with 25 cm line spacing. At the end of the growing season, eight rows of four-meter spikes from each plot were harvested and threshed by hand, and the weight of the obtained grains was measured by a digital scale and reported in square meters.

The results of analysis of variance of the main effects of collectible and multiplicative interaction (AMMI model) showed a significant difference in the level of one percent probability for the environment and the interaction of genotype × environment, which indicates different performance of genotypes in different environments. Therefore, sustainability can be examined. Genotype × environment interaction was divided into two main components by AMMI model. The first two components together accounted for 81.36% and the remaining components in the model accounted for 18.63% of the total variation of genotype × environment interaction. According to AMMI1 model, L4 and L6 lines and according to AMMI2 model, L4 and L7 lines were introduced as high performance and stability lines. Based on the results of Amy Stability Value Index (ASV), L4 and L5 lines and based on Genotype Selection Index (GSI), L4 and L6 lines were introduced as stable lines. The results of Rick equivalence method showed that lines L4, L7 and L3 had the lowest value of this index. According to AMMI1 model, L2 and L7 lines with E1 environment (Gorgan, 2017-2018), and E4 (Tehran, 2018-2019) and L1, L5 and L3 lines with E3 environment (Tehran, 2017-2018) and According to the AMMI2 model, L2 line with E1 environment (Gorgan, 2017-2018), E2 (Gorgan, 2018-2019) and E4 (Tehran, 2018-2019) and L3 and L5 lines with E3 environment (Tehran, 2017-2018) And L1 line had private compatibility with E6 (Kermanshah, 2018-2019) and E5 (Kermanshah, 2017-2018) environments.

Based on all methods of measuring stability in this study and considering the grain yield potential, L4 line had the highest general stability to the evaluated environments and was introduced as a stable line with high yield. Therefore, this line can be suggested for use in future breeding programs to introduce new cultivars. According to both AMMI1 and AMMI2 models, L2 line with E1 and E4 environments and L3 and L5 lines with E3 environment had the most private compatibility. If the cause of the interaction of genotype × environment is predictive factors such as soil type, cultivation operation, the interaction of genotype × environment can be reduced by selecting genotypes with their private and specific adaptation to the environment, and have maximum production.

To study drought tolerant in rainfed winter bread wheat genotypes, 48 genotypes (lines and cultivars) were evaluated under two rainfed and supplementary irrigation conditions at Maragheh research field station, Maragheh, Iran, in2018-19 and 2019-20 cropping cycles. The results of combined analysis of variance showed that effects of years, genotypes and year × genotype interaction on day to heading, day to physiological maturity, grain filling duration, plant height, 1000-grainweight, biological yield, grain yield and harvest index were significant. The average grain yield of genotypes under rainfed conditions was 1707 kg ha-1. The highest grain yield under rainfed conditions related to genotypes no. 4, 23, 20 and 26, respectively, with 2080, 2066, 2035 and 1999 kgha-1.under supplementary irrigation conditions genotypes No. 13, 7, 11 and 25 with 3044, 3014, respectively, with 2943 and 2914 kgha-1 had the highest grain yield. Supplementary irrigation increased mean grain yield by 738 kg ha-1, mean plant height by eightcm, mean 1000 grain weight by three grams and mean harvest index by four percent. Drought stress reduced grain yield of all genotypes. No significant correlation was observed between grain yield of genotypes under rainfed and supplementary irrigation conditions. Positive and significant correlations were observed between MP, GMP, HM, STI and YI with grain yield (Ys) under rainfed and supplementary irrigation (Yp) conditions which indicated the suitability of these indices for selection of genotypes with reasonable grain yield under either conditions. Based on the results of principal component analysis and three-dimensional diagram, genotypes 20, 23 and 26 were identified as drought tolerant genotypes with reasonable yield in both rainfed and supplementary irrigation conditions. Genotypes 13, 7, 11, 25 and 32 were also identified suitable for supplementary irrigation conditions.

Obtaining genetic information on how to control traits and becoming aware of the genetic potential of breeding populations is the most important prerequisite for success in cultivar breeding projects. Graphic analysis of the data obtained from the diallel design by means of the (GGE biplot) biplot method allows the breeders to obtain a larger volume of comprehensive genetic information with higher resolution than the conventional methods. The aim of this study was to obtain genetic information and create various breeding materials with high potential in terms of grain yield and its components in bread wheat.

This study started with identifying and collecting 10 bread wheat cultivars with various and complementary characteristics in terms of grain yield and other related and important economic and agronomic traits. The crossing of parental cultivars and the evaluation of the progeny diallel crosses were carried out in 2018 and 2019, respectively. The progenies of the 10×10 full diallel were studied in a randomized complete block design with three replications and examined for grain yield, 1000-seed weight, plant height, spike length, number of seeds per spike and spike weight.

Based on the results of analysis of variance, the mean squares of genotypes were significant for all traits (α≤ 1%), indicating the existence of sufficient diversity among the studied genotypes. Effects of general combining ability for the parents on plant height, spike length, 1000-seed weight and grain yield and effects of specific combining ability for crosses on plant height, spike length, number of seeds per spike and grain yield was significant. Also, the difference of reciprocal crosses was significant for plant height, spike length, number of seeds per spike and 1000-seed weight. The results of bioplot analysis showed that Ehsan had the highest general combining ability among the parents for grain yield, 1000-seed weight, plant height, spike length. Accordingly, the highest specific combining ability for grain yield was observed between Ehsan against both Gonbad and Shoush cultivars. Also, the spesific combining ability of Ehsan in crosses to Kalateh, Barat, Shoush, Sirvan and Gonbad cultivars had the highest value for 1000-seed weight, plant height, spike length and spike weight. The highest narrow sense heritability was observed for spike length however, for plant height, number of seeds per spike, grain yield, 100-seed weight and flag leaf area, the narrow sense heritability was low.

In general, cultivars Ehsan and Gonbad were able to transfer most of the characteristics to their offspring, therefore they can be used in breeding programs to improve grain yield and yield components in bread wheat. Due to the greater importance of the dominance component in control of grain yield and its components, can be used to determine suitable parents for crossbreeding and production of new varieties.

This study was conducted to evaluate the performance of different herbicides options for weed control in chickpea and their residual effect on bread wheat performance in crop rotation under rainfed conditions. The experimental design was randomized complete block with four replications conducted in Mahidasht Agricultural Research Center located in Kermanshah province, Iran during 2018-2019 and 2019-2020. The experimental treatments included: pre-plant sulfentrazone (Espartan 50% WP); 100 and 300 g.ha-1, pre-emergence sulfentrazone; 100 and 200 g.ha-1, pre-emergence pyroxasulfone (Sakura 85% WP); 100 g.ha-1, pre-emergence flumioxazine (Shato 50% WP); 100 g.ha-1, pre emergence metribuzine (Sencor 70% WP); 200 g.ha-1, pre-emergence of sulfentrazone (100 g.ha-1)+metribiozin (200 g.ha-1), pre-emergence of sulfentrazone (100 g.ha-1)+pyroxasulfone (100 g.ha-1), preemergence of sulfentrazone (100 g.ha-1)+flumioxazine (100 g.ha-1) and hand weeding. The results showed that application of sulfentrazone+pyroxasulfone at flowering stage of chickpea reduced 95% and 94% weed biomass and density, respectively and sulfentrazone+flumioxazin reduced 93% and 82% of weed biomass and density, were the most effective treatments. The highest increase in chickpea seed yield (67% and 60%, respectively) after hand weeding was achieved by these treatments. The pre-emergence treatment of sulfentrazone 300 g.ha-1 had the least positive effect (10%) on the increasing of chickpea seed yield. The results related to the effect of herbicide residues on the wheat yield in rotation showed that wheat grain yield as a result of applying preplant sulfentrazone (200 g.ha-1) was reduced by 32% compared to the control (untreated). The residues of pre-emergence sulfentrazone (300 g.ha-1) also had the most negative effect on both plant height and wheat grain yield  by 8.2% and 32.7% reduction, respectively. In conclusion, results of this experiment showed that, sulfonetrazone (Spartan)+flumioxazin (Shato) and sulfonetrazone (Spartan)+pyroxasulfone (Sakura) herbicides can be suggested for weed control in rainfed chickpea, because of their high efficiency in weed control and improving chickpea seed yield and minor negative residues effect on bread wheat performance in in crop rotation.

Crop simulation models are valuable tools for prediction of crop performance under various weather conditions and allow designing methods to limit the negative impacts of adverse environmental constraints. Agricultural Production Systems sIMulator (APSIM) is a comprehensive model that simulates the performance of a wide range of crops in response to climatic, soil and management factors. In this study, the performance of APSIM-Wheat model in simulating dryland wheat phenology and grain yield was evaluated for the first time in the dryland wheat belt of west and northwest of Iran. Model calibration and evaluation was performed using information of 91 experiments from 11 research field stations in five western and northwestern provinces of Iran from 2001 to 2016. Results showed that the mean observed and simulated days to flowering and physiological maturity were 215 and 218, and 252 and 252 days after sowing (DAS), respectively. These were further supported by an acceptable range of statistical indices of nRMSE (0.29 and 0.16%), CRM (-0.018 and 0.002) and D-index (0.091 and 0.013), for flowering and physiological maturity, respectively. The observed and the simulated mean grain yield were 2245 and 2249 kg.ha-1, respectively. The values of nRMSE (7.21%), CRM (-0.002) and D-index (0.037) showed that APSIM-Wheat performed quite satisfactorily and could be considered in planning to increase dryland wheat production in west and northwest of Iran. The overall results of this study showed that the APSIM-Wheat model can be used to determine the best crop management practices, yield gap analysis, climate change impact assessment and climate change adaptation strategies in dryland wheat fields in western and northwestern of Iran.