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Showing 11 results for Shariati

Dr Hadi Darzi Ramandi, Dr Hamid Najafi Zarini, Dr Vahid Shariati, Dr Kadijeh Razavi, Dr Seyed Kamal Kazemitabar,
Volume 10, Issue 26 (9-2018)
Abstract

Water deficit is one of the most important abiotic factors limiting growth, which adversely affect growth and crop production. In order to study the relationship between kernel size and phenological characteristics on grain yield, 46 local bread wheat genotypes along with four varieties were evaluated in randomized complete block design with three replications under irrigation and water deficit stress conditions. Phenological characteristics including day to heading, day to flowering, day to maturity and grain filling duration, and kernel size traits including kernel length, kernel width, kernel thickness and kernel length/width ratio were measured. Analysis of variance revealed significant differences among genotypes for the studied traits. Results showed drought led to decreased grain yield (0.49), thousand grain weight (0.29), spike weight (0.28), peduncle weight (0.20), grain filling duration (0.17), kernel width (0.16) and increased kernel length/width ratio as compared with irrigated condition. Stepwise regression analysis revealed that under irrigated condition, spike weight, spike length and plant height justified the majority of grain yield variation, whiles under drought stressed condition grain filling duration and kernel width showed the highest impact on grain yield variation. Factors analysis identified four factors which explained 75.4% of the total variation. On the basis of these results, it is concluded that criteria such as grain filling duration, kernel width, peduncle weight and thousand grain weight could be considered as effective criteria for selecting to improve grain yield in water-limited environments.
 


Hossein Ahmadi-Ochtapeh, Hassan Soltanloo, Sayede Sanaz Ramezanpour, Ahad Yamchi, Vahid Shariati,
Volume 11, Issue 29 (3-2019)
Abstract

In current research, the expression level of Dx2 and Dy12 genes on Glu-D1 locus that encoding the high-molecular-weight glutenin subunits (HMW-GSs), with negative impact on quality of bakery in genotype mutant bread wheat called RO-3 with high quality of bakery and its parent (Roshan) with low quality of bakery was investigated. For this purpose, sampling was performed grains at intervals of 5, 10, 15, 20 and 30 days post-anthesis (DPA). The gene expression results showed that RO-3 genotype had the highest gene expression decreasing for Dy12 genes at 5 DPA compared to parental genotype, and for Dx2 gene the highest gene expression decreasing was 10 DPA compared to parental genotype. Generally, during seed development both genes in mutant genotype had gene expression decreasing than the parental genotype. The most dry weight accumulation rates occurred in 10 to 15 DPA in mutant genotype. So, the early stages of seed development for reducing the expression of these genes and rates dry weight accumulation is critical in mutant genotype. The grain-filling rate and the maximum grain weight were higher in mutant genotype than the parental genotype. Therefore breeding the cultivars with higher grain filling rate and also selection of varieties with low expression for Dx2 and Dy12 genes play important role in the selection of varieties with high yield and quality of bakery.

Hassan Amiri Oghan, Amir Hossein Shirani Rad, Farnaz Shariati,
Volume 12, Issue 35 (10-2020)
Abstract

     To study of inheritance of oilseed rape quality traits in normal and late sowing date conditions, 31 genotypes including 7 winter lines as females, and 3 winter testers and their 21 F1 generation were grown under normal sowing date (early October) and late sowing date (early November) conditions in two separate RCB designs with two replications at the field of Seed and Plant Improvement Institute, Karaj (2011-12). Combined analysis of variance showed significant differences between treats of oil seed content and most fatty acids traits in both sowing dates. Therefore, significant genetic variation existed for all traits among the genotypes studied. Estimates of broad and narrow heritability of most traits under late sowing date were less than the normal sowing date and this was mainly due to less esti mation of variance components under late sowing date conditions. In addition, broad heritability was estimated to be generally medium to high (between 72.01 to 100) in both normal and late sowing date conditions. The narrow heritability of traits in both sowing conditions ranged from 20.81% to 80.20%. Therefore, selection for traits with moderate to low narrow heritability in early generations would not be much useful, and it is preferable to use heterosis to improve these traits. In both sowing dates non-additive effect was more evident in control of quality traits. Therefore, selection for these traits would not be effective without using the effect of gene dominance.

- Rasoul Khodavirdivand Keshtiban, Dr Hassan Soltanloo, Dr Seyedeh Sanaz Ramazanpour, Dr Vahid Shariati,
Volume 12, Issue 36 (12-2020)
Abstract

 
Understanding the reaction form and biochemical response of wheat cultivars about the salinity stress can help to better understand the defense mechanisms and identify the indicators and biomarkers of tolerance screening for salinity stress in this strategic plant and other field crop. For this purpose, biochemical traits related to salinity tolerance of wheat cultivars were evaluated as a factorial experiment based on a completely randomized design with tree replications. Experimental factors included wheat cultivars (Sarc 6 as tolerant cultivar and Chinese spring as susceptible cultivar) and sampling time series (control, 6, 12, 24, 48, 72 and 96 hours) after salinity stress. Salinity stress with a concentration of 250 mM of sodium chloride was applied to uniform 10-day seedlings in the two-leaf stage and sampling of shoot and root was performed. The studied traits included the ratio of potassium to sodium (K+/Na+), malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), peroxidase (POX), and polyphenol oxidase (PPO). The results of analysis of variance showed that the effects of the cultivar (excluding peroxidase), the effects of time and the interaction of cultivar and time in all the studied traits, were significant. In one hand, the interaction results of cultivar and time indicated that the trend of changes in the studies traits were different, depending on the type of cultivar, the studied plant part and the sampling time. On the other hand, they also specified that the salinity stress was generally reduced the K+/Na+, increased the MDA and surged the activity of antioxidant defense enzymes in shoot and root of the studied cultivars as compared to control conditions (zero time). The results of group comparisons not only confirmed the efficiency and dominance of the Sarc 6 tolerant cultivar antioxidant defense system against the sensitive cultivar of Chinese springs, but it also emphasized the benefits of K+/Na+, SOD, and CAT biomarkers for wheat screening.

Amir Gholizadeh, Mehdi Ghaffari, Farnaz Shariati,
Volume 13, Issue 38 (7-2021)
Abstract

Production of high yielding hybrid cultivars is the main objectives of breeding programs in sunflower. Therefore, the selection of high yielding hybrids is essential in this plant. In this regard, 24 new sunflower hybrids and Golsa cultivar were evaluated in a simple lattice design with two replications in the Gorgan Agricultural Research Station during 2020 cropping season. In this study, the selection index of ideal genotype (SIIG) and factor analysis was used to select new sunflower hybrids and finding interrelationships among them. Based on the SIIG index, the genotypes G5, G10, G2, G12, G3 and G19 with the highest SIIG values (0.747, 0.689, 0.660, 0.641, 0.640 and 0.572, respectively) were the best genotypes. On the other hand, G23, G15, G24, G25 and G18 genotypes with the least amount of SIIG value (0.233, 0.264, 0.277, 0.278 and 0.285, respectively) were the weakest genotypes for most studied traits. The genotypes of G5, G19, G2, G10, G3, G9 and G11 with high SIIG value and higher seed yield that total average were recognized as superior genotypes from the point of yield and other agronomic traits. Therefore, these genotypes can be used for further testing, including adaptation tests in warm wet areas. Also, the results of factor analysis indicated a positive relationship between stem diameters, head diameter and seed number per head with seed yield. Generally, it can be concluded that traits of stem diameter, head diameter and seed number per head could be used as suitable criteria in selecting for increased seed yield in sunflower breeding programs.

Mehdi Ghaffari, Amir Gholizadeh, Seyyed Abbasali Andarkhor, َasadolah Zareei Siahbidi, Seyed Ahmad Kalantar Ahmadi, Farnaz Shariati, Abbas Rezaeizad,
Volume 13, Issue 39 (10-2021)
Abstract

The genotype × environment interaction is a major challenge in the study of quantitative traits because it reduces yield stability in different environments and also it complicates the interpretation of genetic experiments and is difficult to makes predictions. In this regard, to analysis of genotype × environment interaction and determine the yield stability of sunflower genotypes, 11 new sunflower hybrids along with 4 cultivars were evaluated in a randomized complete block design with four replications in four experimental field stations (Karaj, Sari, Kermanshah and Dezful) during two cropping seasons. In order to analysis of genotype × environment interaction was used the multivariate method of additive main effects and multiplicative interaction (AMMI). The results of combined analysis of variance indicated that 57.68, 7.60 and 16.93 percent of total variation were related to the environment, genotype and genotype × environment interaction effects, respectively. Also, the results showed that the first five principal components of AMMI were significant and described 97.64% of the variance of genotype × environment interaction. Based on biplot graph of mean seed yield and the first interaction principle, the genotypes G3 and G5 were identified as a high yield and stable genotypes. Also, the Dezful and Kermanshah environments due to their high interaction were recognized as the most ideal environments for distinguishing and separating sunflower genotypes. The cluster analysis of the studied environments was divided into two groups. According to the results of cluster analysis, Karaj, Sari, Kermanshah and Dezful locations were located in a group that indicates these locations had the high predictability and repeatability power.

Amir Gholizadeh, Mehdi Ghaffari, Hamid Jabbari, Morad Cheshmehnoor, Fathollah Nadali, Kamal Payghamzadeh, Farnaz Shariati, Shahriar Kia,
Volume 14, Issue 41 (3-2022)
Abstract

Extended Abstract
Introduction and Objective: The sunflower is one of the most important oilseed plants in the world and its oil has nutritional and high economic value. Identification and selection of high-yielding genotypes with desirable characteristics are especially important in this plant. Evaluating sunflower genotypes under different environmental conditions would be useful to identify genotypes with high stability and yield potential. Therefore, this study was conducted to the selection of the best sunflower hybrids.
Material and Methods: In this study, 24 new sunflower hybrids along with Golsa cultivar were evaluated in a simple lattice design with two replications in four experimental field stations (Karaj, Boroujerd, Shahroud, and Gorgan) during the 2020 cropping season. GGE biplot statistical method (genotype effect + genotype × environment interaction) was used to study the stability of genotypes in the studied environments.
Results: Results of combined analysis of variance indicated that the effects of environments, genotypes, and genotype × environment interaction were significant, suggesting that the genotypes responded differently in the studied environment conditions. So, there was the possibility of stability analysis. Results of stability analysis using the GGE biplot method indicated that the two first and second principal components of the GGE biplot explained 67.7% of the total seed yield variation. Based on the polygon view of biplot, the genotype G13 in shahroud environment, the genotype G6 in Karaj and boroujerd environments, and genotypes G5 and G19 in Gorgan environment were superior genotypes with the high specific adaptation. Based on the hypothetical ideal genotype biplot, the genotypes G6, G14, G3, and G4 were better than the other genotypes for seed yield and stability and had the high general adaptation to all environments. Also, the results showed that all environments had high discriminating ability so that could able to show differences between genotypes. The Boroujerd environment was the nearest environment to the ideal environment that had the highest discriminating ability and representativeness.
Conclusion: Consequently, the genotypes G6, G14, G3, and G4 were better than the other genotypes for seed yield and stability. Therefore, these genotypes can be used for further testing, including adaptation tests.

Azim Khazaei, Farid Golzardi, Mohammad Shahverdi, Leyla Nazari, Ahmad Ghasemi, Seyed Ali Tabatabaei, Abdollah Shariati, Hasan Mokhtarpour,
Volume 14, Issue 42 (8-2022)
Abstract

Extended Abstract
Introduction and Objective: Due to the spread of droughts and fodder shortages in the country, it is necessary to introduce new cultivars of forage sorghum. Investigating the genotype-environment interaction to select the superior genotype is one of the most important steps of breeding programs. In these programs, evaluating the compatibility of different genotypes to various environmental conditions is important.
Materials and Methods: Ten promising lines of forage sorghum were studied in a randomized complete block design with three replications at seven regions of Iran (Boroujerd, Zabol, Sanandaj, Shiraz, Karaj, Gorgan, and Yazd) for two years (2018-2019). The AMMI method was used to evaluate the yield stability and compatibility of genotypes.
Results: The results of combined analysis of variance showed that the effects of year, place, year × place, genotype, year × genotype, place × genotype, and year × place × genotype on the fresh and dry forage yield were significant (p≤0.01). The significant interaction of environment × genotype indicates different reactions of genotypes in different environments. The results of AMMI analysis showed that the six main components of the interaction of environment × genotype were significant for fresh and dry forage yields (p≤0.01). For fresh forage yield, the first main component of interaction (IPCA1) had the largest contribution (26.6%) in the expression of genotype-environment interaction and the second to seventh main components were in the next ranks of importance with 18.4, 17, 15.7, 10.5, 7.5 and 4.3%, respectively. For dry forage yield, the first main component of interaction (IPCA1) had the largest contribution (21.8%) in the expression of genotype-environment interaction and the second to seventh main components were in the next ranks of importance with 19.8, 14.7, 14, 11.1, 10.1 and 8.5%, respectively. In total, the cumulative contribution of the seven main components was 98% for fresh forage yield and 97% for dry forage yield. In terms of fresh forage yield, the KFS10, KFS12, and KFS17 lines had the lowest IPCA1 values, which are introduced as stable lines with high general compatibility. In terms of AMMI stability value (ASV) for fresh forage yield, the KFS10 line was determined as the most stable line. In terms of dry forage yield, the KFS2, KFS3, KFS9, and KFS17 lines had the lowest IPCA1 values, which are introduced as stable lines with high general compatibility. The KFS2 line had the lowest amount of ASV in terms of dry forage yield.
Conclusion: Overall, the KFS18 line with high fresh and dry forage yields (121.1 and 32.04 t.ha-1, respectively), low IPCA1, and also optimal forage production in most environments (according to the Biplot model of AMMI) is recognized as a superior genotype.

Mohamadreza Nazari, Farnaz Shariati, Hamid Sadeghi Garmaroodi, Hamid Jabbari,
Volume 14, Issue 44 (12-2022)
Abstract

Extended Abstract
Introduction and Objective: Safflower (Carthamus tictorius) is one of the oldest domesticated plants in the world, which is mainly cultivated as an oil seed in arid and semi-arid regions of the world. Given the climatic conditions of the world where water scarcity is always limiting cultivation, the importance of drought tolerant plants such as safflower will be very high. The basis of genetic modification of cultivars is based on creating diversity and using genetic diversity. In this study, we will investigate the genetic diversity of genotypes collected from different parts of the world in order to identify superior genotypes and identify effective relationships between traits.
Material and Methods: This study aimed to investigate 273 diverse safflower genotypes collected from different parts of the world during the crop season 2020-2021, in the form of augmented design with five controls of Goldasht, Sofeh, Parnian, Faraman and Golmehr, which are all introduced cultivars. Various traits such as seed yield, plant height, 1000-seed weight, oil percentage, number of sub-branches, flowering date, boll diameter, prickly and flower color were recorded.
Results: The results showed the existence of high diversity in terms of all traits evaluated so that genotypes with more than 40% oil (genotypes 190, 226 and 227) and genotypes with more seed yield and earlier than the controls were observed. For example, code 187: with 100 days until flowering, code 167: with 105 days until flowering and code 37: with 106 days until flowering, were earlier than Goldasht with 113 days until flowering. The results of principal component analysis showed that the first three components were able to explain more than 50% of the changes. The first component explained 21%, the second component 18% and the third component 12%. The results of component correlation analysis showed that there is a significant relationship between many traits that can be used in the modification process. The most important of them are the relationship between flower color and oil percentage, as well as the relationship between 1000-seed weight and oil percentage.
Conclusion: In general, the results showed that the diversity of safflower genetic material can provide targeted breeding activities.

Behnaz Shahbaz, Mehdi Soltani Howyzeh, Vahid Shariati,
Volume 15, Issue 46 (7-2023)
Abstract

Extended Abstract
Introduction: The medicinal plant Yarrow (Achillea millefolium L.) due to its medicinal and industrial functions is one of valuable pastureland plant in Iran and the world.
Materials and methods: In this study the Illumina Hiseq 2500 platform used to identify the microsatellites markers by transcriptome sequencing of the leaf and inflorescence of Yarrow.
Results: According to the de novo sequencing results of the medicinal plant Yarrow cultivated in the Research Institute of Forests and Rangelands, 9450 single transcript sequences (6920 single gene sequences) containing 10,570 potential microsatellites were identified. The most common types of microsatellites were dinucleotides (62%), followed by trinucleotides (2748, 26%), and mononucleotides (7%), respectively. In total, 69% of the microsatellites were classified as second class (10 to 20 nucleotides), and 31% were first class (more than 20 nucleotides). The frequency of microsatellites in the transcriptome of inflorescence was one per10 kb assembled sequences. According to unigenes annotation results, totally 1,762 (22.3%), 4723 (53.3%), 3714 (47.5%), 4517 (51.3%) and 5189 (60.7%) unigenes annotated from all databases of KAAS, Arabidopsis, UniProt, NCBI database Non-redundant proteins and sunflower respectively. Among 8542 clustered unigenes containing microsatellite, 38440 unigene sequences (45%) were classified as functional and categorized as 52 clusters.
Conclusion: Among all the categorized monomers, 3220 (65%) belonged to the "metabolic process" category, of which 90 (3%) belonged to the "secondary metabolic process" category. The introduction of these markers can be used for future studies of selection using markers, genetic diversity, and genetic maps in this medicinal plant breeding programs.

 

Bahram Masoudi, Amir Gholizadeh, Parastoo Majidian, Ebrahim Hezarjaribi, Nasrin Razmi, Farnaz Shariati,
Volume 16, Issue 4 (11-2024)
Abstract

Extended Abstract
Background: Oilseeds are among the most important sources of energy all over the world. Soybean (Glycine max L.) is an important crop and its oil has nutritional and high economic value. As an annual, self-pollinating, diploid plant belonging to the Leguminosae pea family, soybean falls into the most important oil plants in the world, containing 18-22% oil and 40-50% protein, depending on the genotype and environmental factors. Soybean has been the food of Asian people, especially China, for centuries, and Chinese people consume it along with rice as their main food. The United States of America is the largest producer of soybeans and produces almost two-thirds of the world's crop. Improving seed yield is always a major goal in soybean breeding programs. The economic performance of soybeans can be increased by using new and high-yield varieties. It is essential to evaluate promising advanced soybean genotypes under different environmental conditions for identifying and selecting superior genotypes with high and stable yield potential. Genotype × environment interaction effects are important limiting factors in the introduction of new cultivars. The genotype × environment interaction is a major challenge in the study of quantitative characters because it reduces yield stability in different environments and complicates the interpretation of genetic experiments, making predictions difficult. Therefore, it is crucial to know the type and nature of the interaction effect and reach the verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The GGE-biplot graphic method is a technique with suitable efficiency to investigate the genotype × environment interaction effect and provides good information about the studied genotypes and environments graphically. This study aimed to investigate the genotype × environment interaction effect using the GGE-biplot graphic method to evaluate genotypes, environments, and relationships between genotypes and environments. Finally, this research seeks to identify stable soybean genotypes with high grain yields under different environmental conditions.
Methods: In total, 27 new soybean lines along with Saba and Amir cultivars were evaluated under different environmental conditions in a randomized complete block design with three replications in four experimental field stations (Karaj, Gorgan, Sari, and Moghan) during the 2022 cropping season. The plots consisted of four rows of 5 m in length with 50 cm spacing between the rows. The GGE biplot statistical method (the genotype effect + genotype × environment interaction) was used to study the stability of genotypes in the studied environments. Plants were harvested at maturity, and then the seed yield was recorded for each genotype at each test environment.
Results: The results of the combined analysis of variance indicated that the effects of environments (E), genotypes (G), and genotype × environment (G×E) interaction were significant for seed yield, suggesting that the genotypes responded differently in the studied environmental conditions, making the stability analysis possible. The results of the genotype × environment interaction analysis using the GGE-biplot method indicated that the two first and second principal components of the GGE-biplot explained 84.8% of the total seed yield variation, indicating the high validity of the biplot in explaining the variations of genotypes and the genotype × environment interaction (G + GE). This study identified two mega-environments, the first of which included Gorgan and Mughan, and the second mega-environment included Sari and Karaj. Based on the polygon view of the biplot, the genotype G1 in Sari and Karaj environments, and the genotypes G21 and G22 in Gorgan and Moghan environments were superior genotypes with high specific adaptation. The results of the average environment coordinate biplot showed that the G1, G22, G5, and G9 genotypes produced the highest seed yield, respectively. On the other hand, the G28, G25, G16, and G19 genotypes produced the lowest seed yield, respectively. Based on the hypothetical ideal genotype biplot, the G22, G5, G16, G12, G14, and G9 genotypes were better than the other genotypes for seed yield and stability and showed high general adaptation to all environments. Moreover, the Karaj and Moghan environments were the nearest environments to the ideal environment with the highest discriminating ability and representativeness. Therefore, the Karaj and Moghan environments can be used as a suitable test location for selecting superior soybean genotypes.
Conclusion: Based on the results of this study, the G22, G5, G16, G12, G14, and G9 genotypes are superior for seed yield and stability in this study. Therefore, these hybrids can be used for further testing, including adaptation tests. Besides, the results show that the Karaj and Moghan environments can be used as suitable test locations for selecting superior soybean genotypes. Generally, our results demonstrate the efficiency of the GGE-biplot graphical method to investigate the G × E interaction effect and provide good information about the studied genotypes and environments.

 


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