پژوهشنامه اصلاح گیاهان زراعی

Extended Abstract Background: The expression of genes changes under the influence of different developmental stages and various environmental factors. Drought stress at the flowering and seed-filling stage, which is known as end-of-season drought stress, can lead to a sharp decrease in yield or complete failure of crop production. Genetic analysis of drought resistance in the reproductive stage is necessary to understand the mechanism of plant response to drought conditions in the face of the challenges of maintaining food security. Assessment of the transcript profile of genes in different tissues and developmental stages under different conditions of environmental stress can provide insight into the molecular mechanisms and plants’ reactions to stress. Barley is known as a model plant for deciphering the mechanisms of drought tolerance, and the study of molecular mechanisms of barley is important for breeding crops because it can tolerate water limitations at the flowering and grain-filling stages. This research aimed to identify differentially expressed genes in barley under end-of-season drought stress using the RNA-Seq technique. Based on the study of Amini et al. on 13 genotypes of spring two-row barley under drought stress, the Dayton/Ranney genotype (modified by ICARDA) was identified as a drought-tolerant genotype. Thus, they were used in this study to investigate the gene expression profile of barley under end-of-season drought stress. Methods: The Dayton/Ranney spring barley genotype was subjected to drought stress treatment (70% available water depletion) at the stage of flag leaf emergence. Total RNA was extracted from the leaves of the control and drought-treated plants, followed by qualifying the extracted RNA. After sequencing and analyzing, the expression profiles of differentially expressed genes were obtained under end-of-season drought stress. Moreover, the differentially expressed genes were functionally investigated using gene ontology enrichment analysis. The binding site of transcription factors in the promoter sequence of differentially expressed genes was identified using PlantPAN 3.0 online software, and the frequency of binding sites was reported as a percentage of all identified sites. Results: Under end-of-season drought stress, 2920 and 2290 genes showed significant increases and decreases in expression, respectively, in barley plants. The identified genes were involved in the processes of photosynthesis, carbohydrate and lipid metabolism, regulatory processes, response to abiotic stimuli and stress, seed development, and maturation. Based on gene ontology analysis, these genes were involved in the metabolic and biosynthetic processes of carboxylic acid, sucrose, and glucan cellular metabolism, proteolysis, phosphorylation, RNA metabolism and biosynthesis, and serine family amino acid metabolism. Among the genes with the highest increase in expression under drought stress are the family of abundant proteins in late embryogenesis, a phenylpropanoid pathway gene called anthranilate N-benzoyltransferase protein 1, the xyloglucan-endotrans-glucosylate/hydrolase gene, protein serine/threonine-phosphatase, a mitochondrial arginine transporter, an endonuclease gene, laccase enzyme, and several transcription factors. Besides, the genes that showed the most significant decrease in expression under drought stress include an L-type lectin-containing receptor kinase (Hv-LecRK), a ribonuclease III-like gene, the HEC1-like transcription factor, methyljasmonate II -inducible lipoxygenase, glucan endo-1,3-beta-glucosidase GIII, PIP2;5 aquaporin, 70-kDa heat shock protein (HSP70), and an aspartic proteinase nepenthesin-1 gene. Moreover, two unknown genes 2HG0195510 and 4HG0389440 showed significant increases in expression. These genes are involved in the metabolic and biosynthetic processes of carboxylic acid, response to abiotic stimuli and stress, response to endogenous stimuli, proteolysis, phosphorylation, RNA metabolism and biosynthesis, the protein metabolic process, and serine family amino acid metabolism and transport. At the level of molecular function, the groups of catalytic activity and connection assigned the largest number of genes to themselves for all the genes with differential expression. Other molecular functions identified for genes responsive to drought stress include protein binding, nucleotide binding, transport activity, DNA binding, transferase, kinase, hydrolase, and pyrophosphatase activity. In addition, these increased genes expressed specifically had the functions of message transmission, transcription factor, enzyme regulation, molecular transport, and receptor activities. The binding positions of transcription factors in genes with differential expression were classified into 64 families. The highest percentage of binding sites in the up-expressed genes belongs to ERF/AP2 transcription factors, followed by the most abundant binding sites belonging to the transcription factor family of bZIP, bHLH, DOF, and GATA. Furthermore, the most abundant binding sites in the down-expressed genes included AP2/ERF, BES1, EIL, TCP, Myb/SANT, GATA, and DOF. Conclusion: By evaluating the gene expression under end-of-season drought stress, aspects of the resistance mechanism of barley to drought stress were identified that are related to the metabolic and biosynthetic activities of the plant in the reproductive stage. The results show that diverse and complex gene networks play a role in the response of the barley plant to end-of-season drought stress, which mainly decreased the biological processes related to photosynthesis and the production of precursor metabolites and increased the metabolic processes. Additionally, the response process to the stimulus was observed in both sets of increased and decreased expressed genes.

Extended Abstract Background: As one of the most influential cereals, wheat is among the most important food sources in Asian countries, including Iran, which has more cultivated area than other plant crops in Iran. Durum wheat is a type of tetraploid wheat that is particularly important for use in the food industry, especially pasta production. Durum wheat is a good source of dietary fiber, protein, and a wide range of vitamins and minerals such as iron, magnesium, and B vitamins, making it a healthy and nutritious food. This product also has a special economic importance for Iran and is a strategic product that has a significant impact on the country's agricultural economy. Based on the stability and productivity of plants in changing environmental conditions, plant breeders can develop products that are more flexible and have good stability even in the face of climate change and other environmental challenges. The upcoming study aims to investigate the durum wheat genotypes produced by Iranian breeders and their response to environmental changes to make it possible to introduce these genotypes as cultivars that can be planted by farmers. Methods: To verify the feasibility of introducing new durum wheat varieties with high yields and stable performance in different environmental conditions, 18 genotypes of durum wheat along with two control varieties (Hana and Parsi) were studied in four crop years at the research station of the Agricultural Research and Training Center and The natural resources of Kermanshah Province (Islamabad West Agricultural Research Station) based on a completely randomized block design in three replications and four consecutive years from 2013 to 2016. After adjusting the data, composite variance analysis was performed considering year × genotype in relation to grain yield. Due to the significance of the genotype × environment interaction effect, the averages were compared for genotypes and the environment, as well as for their interaction, and stability analysis was calculated by univariate and multivariate methods. The univariate methods included environmental variance parameters (S2), coefficient of environmental changes related to all investigated environments (CV), Rick's equivalence (W2), Shukla's stability variance (Shukla-Var), regression coefficients based on the Eberhart-Russell model to analyze the genotype × environment interaction effect on the regression components (b), the standard error value or deviation from the regression line in the Eberhart-Russell model (Sd), and the explanatory coefficient value of the regression model in the Eberhart-Russell model (R2). Moreover, multivariate methods, including the AMMI method, the GGE method, and the heat mapping method, were used to analyze the stability of genotypes. SAS software was used for calculations related to composite analysis of variance (ANOVA) and mean comparison. Univariate stability calculations were done using the codes written by the authors in the matrix language of SAS software, which is known as Interactive Matrix Language. R software and the agricolae library were used for calculations related to multivariate methods in AMMI and GGE models. Heat mapping was also done in R software with the ggcorrplot library. Results: The composite ANOVA in this research showed the significance of the main effects of genotype and environment alone and the genotype × environment interaction effect in grain yield. Due to the significant genotype × environment interaction effect, the response of genotypes to different environments is different. Thus, analysis of stability was carried out by univariate and multivariate methods to allow for the introduction of new durum cultivars with high potential in terms of grain yield and production stability in different environments. The heat mapping results showed that this method could separate the three environmental groups and confirmed the average comparison results. The number of separated groups of genotypes based on experimental environments also included four different groups. The different stability methods used in this research also showed differences in relation to the stability and sensitivity of genotypes. Therefore, the ranking method was used based on different sustainability models. Accordingly, genotypes 3, 13, 14, and 16 produced high final yields and good stability (above average), and genotypes 18 and 19 showed high stability and good total yields based on all stability methods. The first four genotypes, with good stability, produced a higher average yield than both controls, but the next two genotypes, with high stability, showed a higher yield than the Hana variety and less than the Parsi variety. Conclusion: Different methods of univariate stability, including environmental variance, coefficient of environmental change, Shokla variance, the regression sum of squares method, regression coefficient, the residual of the regression model, and explanatory coefficient, along with multivariate methods, including AMMI and GGE models as well as the heat mapping method were examined to estimate the stability and the response of 18 durum wheat genotypes along with two control varieties (Hana and Parsi). It was found that heat mapping had a good performance in assessing the response of the genotypes to environmental conditions and could separate three environmental groups, which confirmed the results of the average comparison. The number of separated groups of genotypes based on experimental environments included four different groups. Based on the stability analysis results, genotypes 14, 16, 13, and 3 produced high final yields and good stability (above average) based on all stability methods, and genotypes 19 and 18 showed high stability and good total yields (above average). The first four genotypes, with good stability, produced higher average yields than both controls, but the next two genotypes, with high stability, showed higher yields than the Hana variety and less than the Parsi variety. Finally, it is suggested that these six genotypes enter the regional research-promotion tests for further investigation so that the most suitable ones are finally introduced as a new variety of durum wheat.

Extended Abstract Global food security has become an urgent concern due to rapid climate change. Plants, the foundation of the food chain, are constantly under environmental pressures such as drought, salinity, and extreme and low temperatures. These stressors threaten plant growth and productivity, jeopardizing global food supplies. Plants can sense environmental stimuli and activate defense mechanisms through various regulatory networks, including small RNAs, to combat abiotic stressors. These changes trigger a cascade of defense responses, including the utilization of small RNAs, to protect themselves from damage. MicroRNAs (miRNAs) were first identified in plants less than two decades ago and have since been recognized as crucial controllers of various developmental processes. These processes include leaf morphogenesis (the formation of leaves), vegetative phase change (the transition from vegetative growth to flowering), flowering time, and the ability to respond to environmental signals. miRNAs, recognized as one of the most crucial RNA molecules, play a pivotal role by modulating gene function through post-transcriptional and translational mechanisms. RNA interference is a group of 18-25 nucleotide sequence-specific RNAs that are found abundantly in plant genomes. These RNAs play an important role in various processes, including plant growth and development, cell behavior, biochemical and physiological activities, defense against threats to the genome, and tolerance to abiotic stresses. Despite their small size, they wield immense power in regulating gene expression networks. miRNAs negatively regulate the expression of a wide range of genes at the transcription levels (DNA methylation), post-transcription, and translation. They act as post-transcriptional regulators, binding to specific sequences on messenger RNA (mRNA) molecules. This binding cleaves the target mRNA, effectively silencing the gene it encodes, or inhibits its translation into protein. Short interfering RNAs (siRNAs) are derived from the processing of long double-stranded RNAs (dsRNAs). Then, a specific guide strand is chosen and integrated into the RNA-induced silencing complex (RISC). Once this complex is inside RISC, a member of the Argonaute (AGO) protein family binds with the guide strand, directing RISC to target RNAs with complete sequence complementarity. This interaction leads to the precise cleavage of the target RNAs by the Argonaute protein. This process, known as RNA interference (RNAi), plays a fundamental role in gene regulation and defense responses in plants. Plants employ a sophisticated regulatory system called gene silencing, which controls gene expression by inactivating specific genes. Two key mechanisms in this system are post-transcriptional gene silencing (PTGS), which inactivates genes by targeting RNA molecules, and transcriptional gene silencing (TGS), which prevents RNA production from the DNA template. miRNAs can influence PTGS by promoting the degradation of specific mRNA transcripts and TGS by recruiting DNA methylation machinery to target genes. PTGS acts in the cytoplasm, targeting messenger RNA (mRNA) molecules. PTGS can be triggered by dsRNAs or miRNAs. These dsRNAs can originate from viral infection, transgene insertion, and inverted repeats within plant genes. Dicer, an RNase III enzyme complex, recognizes and cleaves relevant dsRNAs into small interfering RNAs (siRNAs) for RNA interference (RNAi). The siRNAs then guide a protein complex called RISC (RNA-induced silencing complex) to complementary mRNA sequences. RISC cleaves the targeted mRNAs, silencing them and preventing their translation into proteins. Similar to siRNAs, miRNAs can also regulate gene expression in PTGS by targeting mRNA molecules, although they often function through imperfect base pairing. TGS operates by modifying DNA in the nucleus, making it less accessible for transcription and thereby preventing mRNA production. TGS relies on mechanisms such as DNA methylation and histone modifications to silence gene expression in the nucleus. These modifications create a repressive chromatin environment that hinders RNA polymerase from accessing and transcribing the DNA. While the primary role of miRNAs lies in PTGS, some studies suggest that they might also influence TGS. Some miRNAs could interact with proteins involved in DNA methylation or chromatin remodeling, indirectly leading to transcriptional silencing. The interplay between PTGS and TGS is intricate. While they are distinct pathways, they can be interconnected. In some instances, PTGS might influence TGS through mechanisms. Degraded mRNAs from PTGS might serve as signals that guide DNA methylation machinery to homologous DNA sequences, potentially leading to long-term transcriptional silencing. Conversely, TGS-mediated gene silencing could prevent the formation of dsRNAs or aberrant transcripts that trigger PTGS. miRNAs act as molecular switches by strategically targeting specific mRNAs and fine-tuning the production of proteins essential for environmental stress tolerance. This precise control allows plants to adapt to a dynamic environment, tailoring their gene expression to meet the specific challenges they face. Plant miRNAs act as mediators for silencing or direct cleavage of target mRNAs. While some miRNAs perfectly match their mRNA targets, others can function with some mismatches. miRNA families are grouped into conserved and non-conserved miRNAs based on conserved spots and variation during processing. Each group of these miRNAs has its targets. Today, RNA interference (RNAi), triggered by dsRNA, is a widely used and valuable tool for researchers to specifically silence genes and understand their function in various biological processes. Despite ongoing research in genetically engineering plants to manipulate miRNAs for improved tolerance to biotic and abiotic stresses, knowledge remains limited regarding their functional and regulatory networks in this context. Understanding the regulatory function of this group of RNAs opens up new avenues for applied research in genomic fields, enhancing resistance to plant diseases, bolstering tolerance to various stresses such as drought, salinity, heat, and cold, as well as improving product quality and increasing food production. The review's objective is to assess the existing knowledge concerning plant small RNAs and elucidate their significance in enhancing resilience to abiotic stressors.

Extended Abstract Background: Considering that a major part of Iran is part of arid and semi-arid regions, obtaining stable genotypes with good yield stability is one of the ways to deal with drought stress. Due to the genotype × environment interaction effect, however, it is difficult to identify cultivars and genotypes that have good stability and acceptable yields in various environmental conditions. Many methods are known to determine the genotype × environment interaction effect to identify stable cultivars, which are divided into two univariate (parametric and non-parametric) and multivariate groups. Each of these methods shows different aspects of the stability of genotypes, and one method alone cannot investigate the yield of a genotype in different environments from different aspects of stability. This research aimed to select promising bread wheat genotypes with high yields and suitable stability in the water deficit conditions in the cold climate of Iran using various univariate and multivariate stability analysis methods. Methods: Fourteen wheat genotypes along with Mihan, Heydari, Zarineh, and Zare cultivars (18 genotypes) were investigated under water deficit conditions in a randomized complete block design (RCBD) with three replications in the research stations of Karaj, Mashhad, Miandoab, Arak, and Zanjan in crop years 2020-2022. The stability of genotypes was examined using some parametric and non-parametric univariate methods, AMMI multivariate analysis, and AMMI analysis parameters. Moreover, parametric and non-parametric univariate methods and AMMI stability parameters were integrated using the selection index ideal genotype (SIIG). Results: The location, genotype, year × place, and genotype × year × place interaction effect at 1% and the genotype × place interaction effect were significant at a 5% probability level. The main effect of the environment, the genotype × environment the interaction effect, and the main effect of the genotype explained 43.61%, 22.92%, and 8.03% of the sum of squares of the experiment, respectively. In parametric methods, G17, G5, G13, and G1 genotypes based on the regression coefficient of Finley and Wilkinson, G9, G7, and G1 genotypes based on the variance of deviation from the regression line, G9, G1, G7, G17, and G4 genotypes based on Wrick's equivalence indices and Shokla stability variance, G9, G1, G17, G4, and G7 genotypes based on Plaisted and Peterson's method, G9, G1, G17, and G4 genotypes based on Plaisted's method, and G9, G1, G7, and G4 genotypes based on Kang's total rank method were known as stable genotypes. In non-parametric methods, G9, G15, and G7 genotypes based on Si(1) and Si(2), G9 and G1 genotypes based on Si(3) nd Si(6), G9, G1, and G7genotypes based on NP(1), G3, G9, G17, and G1 genotypes based on NP(2) statistics, and G9 and G1 genotypes based on NP(3) and NP(4) statistics were regarded as stable genotypes. In AMMI analysis, the first and second components showed the largest contribution (57.8%) in explaining the genotype × environment interaction effect according to the significance of the six main components from the first to the sixth. Based on the AMMI1 biplot, G9 and G17 genotypes, and Zanjan1 and Arak2 environments were recognized as the most stable genotypes and environments due to higher than average grain yield and very low value of the first component. Based on the AMMI2 biplot, a specific genotype cannot be introduced as a genotype with high general compatibility due to its lack of proximity to the coordinate origin. However, G9 and G17 genotypes showed somewhat better general compatibility than the others, and they could be recommended because of their higher yields than the average. Genotypes G18, G17, G15, G9, and G16 based on ASV, G9, G1, G7, G4, and G17 genotypes based on WAAS, G9, 33, G1, and G17 genotypes based on SIPC, G9, G15, and G17 genotypes based on ZA, G9, G1, G3, and G7 genotypes based on EV, G9 and G1 genotypes based on ASTB, G17, G18, G15, G9, and G16 genotypes based on ASI, G9, G1, G17, and G7 genotypes based on FA, G9, G3, G1, and G7 genotypes based on DZ, G9, G1, and G7 genotypes based on DA, G9, G17, G18, and G16 genotypes based on MASI, G9, G1, and G4 genotypes based on MASV, and G9, G1, and G7 genotypes based on the AVAMGE index were selected as the most stable genotypes. Conclusion: Based on the SIIG index in both univariate and multivariate methods, genotypes G9, G1, and G17 have the closest value to one, and these genotypes produced yields above the average; therefore, they were selected as the most stable genotypes. Furthermore, the use of the SIIG index in both univariate and multivariate methods showed somewhat the same results; therefore, it is better to use this general index to summarize all the information obtained from different methods.

Extended Abstract Background: Strawberry (Fragaria × ananassa) is a perennial shrub of the Rosaceae family that has become one of the most significant fruits globally due to its unique characteristics, ease of care, and delicious flavor. This plant thrives particularly well in temperate regions, although it can also be cultivated as an annual. These traits have made strawberries popular not only in home gardens but also in commercial agriculture. It has emerged as an important economic crop in many countries because of its tasty and nutritious fruits. Given the economic and nutritional significance of strawberries, it is crucial to assess their genetic diversity and identify various genotypes. Genetic diversity in this plant enables researchers to develop newer, higher-quality varieties that are more resistant to pests and diseases while yielding greater outputs. Therefore, the use of morphological markers is highly beneficial in distinguishing and identifying different strawberry cultivars and populations. Consequently, this study was conducted to investigate genetic diversity and identify relationships between domestic and imported strawberry genotypes and clones. Methods: The present study was carried out in Mazandaran Province, Sari City, from November 2020 to June 2021. Transplants of imported cultivars were sourced from the Kurdistan Agricultural and Natural Resources Research Center. This selection was made due to the high diversity of cultivars and their specific characteristics, allowing for an accurate assessment of their yields and quality. The plants were grown in pots filled with a substrate of cocopeat and perlite in a 70:30 ratio. Due to its favorable physical and chemical properties, this substrate promotes better root growth and enhances the absorption of water and nutrients, thereby providing optimal conditions for plant growth. The comparison stage of cultivars was conducted through detailed studies at the Sari University of Agricultural Sciences and Natural Resources, aiming to investigate genotypic and phenotypic diversity. The experiment utilized a completely randomized design with 23 treatments, including mother cultivars in three replications and daughter cultivars in four replications, all within a hydroponic medium. Measurements were taken on fertile plants, and various data points, including growth habit, leaf density, and growth vigor based on international descriptors, as well as traits such as leaf length and width, leaf area, the number of individual flowers, the number of inflorescences, and total flower count, were analyzed quantitatively. Results: The examined genotypes exhibited significant differences in reproductive and vegetative traits. The highest genetic diversity coefficient was associated with the number of fruits per plant, the number of flowers per plant, and plant yield, all of which showed variations exceeding 50%. In contrast, a narrower range of variation was noted in traits related to vegetative growth, likely due to environmental influences and cultivation conditions. The correlation analysis of the growth habit trait revealed that a more erect plant positively impacted the growth of leaf components, which in turn enhanced fruit length and width. This is a crucial discovery as it can aid in the selection and breeding of superior cultivars. Factor analysis successfully identified several main factors representing qualitative and quantitative traits, facilitating a better understanding of the relationships among these traits. The Camarosa cultivar, the predominant cultivar in Mazandaran Province, along with the cultivars Merck, Tan Beauty, Missionary, and Queen Eliza, demonstrated positive vegetative growth but negative reproductive growth. However, the selected clone from Ghaemshahr excelled in both vegetative and reproductive growth, placing it in the fourth quadrant and positive section. The evaluated values for strawberry traits indicated that phenotypic variance surpassed genotypic variance, highlighting the environmental impact on the studied traits. The maximum phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were attributed to plant yield (67.25 and 65.67), followed by leaf area (38.92 and 39.47), respectively. Furthermore, high heritability was observed in the traits of leaf area (97.3%), plant yield (95.35%), and the number of flowers per inflorescence (90.59%). Conclusion: The results of the correlation of morphological traits indicate that the plant's growth habit has a positive and significant correlation with various traits, including leaf length, leaf width, leaf area, petiole length, and fruit length and width. The correlation results for the descriptive trait of growth habit in three forms (erect, semi-erect, and creeping) demonstrate that a more erect plant positively influences the growth of leaf components, leading to improvements in both fruit length and width. Additionally, the correlation findings suggest that an increase in shoot density and leaf number can negatively and significantly impact the plant's growth habit. Therefore, shoot density may decrease as the plant grows, resulting in a more open structure with fewer leaves. Finally, considering the genetic distance among the cultivars, it appears that crossing these genotypes could yield greater heterosis, which can be leveraged to produce new cultivars and enhance orchard yields. Utilizing genetic and phenotypic diversity and incorporating these traits into breeding programs can significantly improve the quality and yields of strawberries in Iran.

Extended Abstract Background: Many efforts have been made to combine the diverse capabilities of different plant species into a unique plant to increase the quantity and quality of the food product. Accordingly, scientists succeeded in producing triticale as a new pathogen by using a cross between wheat (Triticum spp.) and rye (Secale cereale), which aims to increase the ability of wheat, as one of the most important food sources among grains in the world. It was to withstand harsh environmental conditions such as drought stress. Various studies show that this grain has a high potential to be used as a multipurpose product for direct human use or as a fodder product. Therefore, triticale can be considered a potential product with special genetic conditions, whose yield is still far from its potential. According to scientists of breeding science, creating diversity, whether natural or synthetic, in agricultural products and selecting genotypes with the highest yields and stability in different environments are among the main goals of studies in the field of breeding. It is also reported that the stress tolerance of triticale genotypes is usually higher than wheat genotypes, triticale is less affected by stress conditions, and its yield will be higher than wheat. Resistance to drought stress is a complex process that includes a network of plant responses at the physiological and molecular levels that have not yet been properly discovered and understood. However, creating diversity, selecting genotypes, and studying different traits will help scientists in this direction. In the current study, different triticale genotypes produced by domestic scientists were cultivated and tested under different irrigation conditions to consider the possibility of introducing new cultivars resistant to drought stress and changing environmental conditions. In addition, the relationship between morphological and agronomic traits related to seed yield was evaluated in this research using some advanced statistical methods to find possible traits suitable for indirect selection. The amount of different genetic, phenotypic, and environmental indicators was also investigated to examine the effect of the environment and genetics on the traits. Methods: To reflect the effect of water deficit on triticale and the probability of screening some suitable genotypes tolerant to drought stress, a study was carried out on nine triticale genotypes under four irrigation regimes during two years. These genotypes included Senabad, Pag, Juanillo, ET-85-4, ET-92-15, ET-92-18, ET-83-20, ET-85-17, and ET-83-18. In each year, four different irrigation regimes were applied with interruption of irrigation in three stages, including the flowering stage, the seed milky stage, and the seed pulp stage, along with the control condition. In each year, a split-plot design based on a randomized complete block design with three blocks (replication) was used every two years of the experiment (the growing season 2018-2019) in the research station located in the research complex of the Zarghan Agriculture and Natural Resources Research and Training Center, Fars, Iran. Different traits, including plant height, leaf angle, leaf weight, total dry matter, spike length, spike weight, spike number, grain number, straw yield, harvest index, and grain yield, were measured for all applied genotypes in this study. The data obtained from this experiment were first subjected to the composite analysis of variance, and year variance, environmental variance, genotypic variance, phenotypic variance, and test error variance were estimated based on these calculations. The analysis was performed in SAS-9.4-M6 software using a programming code stored on the GitHub website. Results: The results showed that a lower number of irrigation and earlier withholding of water from the triticale plants can lead to a high decrease in the productivity of triticale genotypes. Consequently, irrigation treatments and water availability are significant factors in determining the type of breeding programs. Moreover, some genotypes showed a high potential for being considered for releasing cultivars. ET-83-20 and ET-85-04 showed better performance under normal and severe water deficit, respectively, than the other genotypes. Estimation of genotypic features, such as heritability and coefficient of variation, showed a high possibility and potential of producing cultivars with high productivity under either normal or stressed conditions. Conclusion: Overall results indicated that high heritability and the significant association with grain yield for some traits, such as spike weight, spike number, and grain number, suggest that they are suitable traits for indirect screening and selection criteria. In addition, higher variation for triticale is required to find genotypes with the best quality and quantity traits to be released as a new and proper cultivar to be cultivated in environments with changing conditions.

Extended Abstract Background: Black seed (Nigella sativa L.) from the Ranunculaceae family is one of the natural useful antioxidants, and the oil prepared from its seeds has various medicinal properties, including anti-cancer, anti-microbial, anti-hypertensive, anti-diabetic and increased immunity has been reported. Nigella sativa, like other plants, is constantly exposed to abiotic or biotic stresses. The main abiotic stresses that plants are exposed to include extreme temperature, drought, high salinity and heavy metals. Environmental pollution caused by heavy metals is increasing. Among heavy metals, cadmium is one of the most toxic elements for living organisms, which has received much attention due to its increase in the environment in recent decades. This element is toxic to most plants even in very low concentrations, while in concentrations higher than five to ten micrograms per gram of dry leaf weight, it can lead to the death of the plant. The presence of this element in the growth environment of plants causes a lot of poisoning, including disruption of water-plant relations, disruption of chlorophyll biosynthesis and formation of free ions. Therefore, it is necessary to adopt appropriate environmental methods to reduce or eliminate the negative and irreparable effects of this metal in agriculture. Seed priming is known to be an effective method to improve plant performance by increasing plant tolerance to stress. One of the types of priming methods is the use of chemicals such as chitosan. Chitosan is a non-toxic and environmentally adaptive substance that is very important due to its antioxidant activity in dealing with oxidative damage resulting from environmental stress. Therefore, in this study, the effect of chitosan priming on reducing the harmful effects of cadmium on germination and biochemical characteristics of black seed was investigated. Methods: In this study, in order to investigate the effect of chitosan priming on cadmium chloride stress on the germination and biochemical characteristics of Nigella sativa, the experiment was carried out as a factorial design based on completely randomized design with 4 replications in sterile petri dishes in the laboratories of Gonbadkavos Agricultural University in 2023. For seed priming with different concentrations of chitosan (0.2, 0.4, 0.6, 1.0%), the seeds were immersed in the desired solutions for 3 hours under dark conditions and after drying, they were placed in Petri dishes on Whatman paper bed. Then 5 ml of solutions prepared with different concentrations of cadmium chloride (control, 1000, 750, 500, 250 μmol) were added to them. Distilled water was used for control treatment. Finally, the samples were placed for 10 days in the germinator in dark conditions with a temperature of 25±1 oC. At the end of the experiment, the characteristics of germination percentage, germination rate, seedling vigor index, root and shoot length were measured. Then the biochemical traits of seedlings such as catalase, peroxidase, phenol, soluble sugar and proline were measured after 14 days. Statistical analysis of data was done using SAS 9.1 and MSTAT-C software. Results: The results of analysis of variance indicated the significant simple effects of priming with chitosan and cadmium stress on all investigated traits. Also, the interaction effects of priming × cadmium stress were also significant for all traits at the 1% level. The comparison of average data showed that with the increase of cadmium concentration, germination rate and percentage, radicle length and seedling vigor index decreased significantly, so that the highest amount of these traits was in the control and 250 μmol cadmium and the lowest amount of these traits was observed at a concentration of 1000 μmol cadmium. The external application of chitosan in the form of priming improved germination traits, root and shoot length and seedling vigor index in 0.2 and 0.4% chitosan treatments compared to the control, while with the increase in the percentage of chitosan (0.8 and 1 percent) the amount of these traits decreased significantly. The results of the comparison of average traits under the interaction of chitosan ×cadmium showed that seed priming with chitosan was able to reduce the negative effects of cadmium chloride stress on the traits of percentage germination, root and shoot length and seedling vigor index. Thus, the highest amount of these traits was observed in the treatment of 0.2 and 0.4% chitosan and 250 and 500 μmol cadmium stress. Also, the results of the present study showed that increasing the concentration of cadmium chloride causes an increase in the activity of antioxidant enzymes such as catalase and peroxidase and non-enzymatic antioxidants such as proline and phenol. So that peroxidase enzyme at the treatment of 750 μM of cadmium (0.0053 μmol per gram of fresh tissue) with an increase of 178.2% compared to the control and phenol in the treatment of 1000 μM of cadmium (3.2 mg/g of extract) with an increase of 211.7 % compared to the control showed the highest level of activity. Also, the use of seed priming technique with chitosan could significantly increase the content of these proteins in plants under cadmium stress. So that, the highest amount of peroxidase enzyme is observed in the treatment of 500 μM cadmium in the priming treatment with 0.4% chitosan (0.0083 μmol Bergam of fresh tissue) and in the tratment of 750 μM cadmium chloride in the priming treatment 0.2% chitosan (0.0082 μmol Bergam) fresh tissue). That this amount was about 64 and 57.6% more than their controls, respectively. Conclusion: The results of this research showed that cadmium stress leads to a decrease in germination characteristics and weakens the plant's defense system. To deal with these changes and reduce the adverse effects of the produced ROS, the plant increased the activity of antioxidant enzymes, but the adverse effects of cadmium had an inhibitory effect on these changes. Conversely, the use of chitosan in the form of priming prevented the harmful effects of cadmium and increased the activity of antioxidant enzymes and protected the germination process against the toxicity of this heavy metal. Although the application of chitosan up to 0.6% improved these mechanisms, its beneficial effects decreased with the increase in the concentration of this substance. Based on the results of the present study, it can be stated that the application of chitosan caused the activation of some biochemical and physiological mechanisms in the black seed plant under cadmium stress. Therefore, seed priming with chitosan can be suggested as an effective strategy to increase Nigella sativa tolerance to cadmium stress.

Extended Abstract Background: Oilseeds are one of the most important sources of energy all over the world. As an important crop, rapeseed oil has high nutritional and economic value. Rapeseed is one of the most important sources of vegetable oil in the world, and its seed contains more than 40% oil. The meal obtained from oil extraction contains more than 35% protein, and currently it ranks third among oil plants after soybean and oil palm in the world. The economic yield of rapeseed can be increased by using new and high-yield varieties. Evaluating promising advanced lines of soybean under different environmental conditions is essential in identifying and selecting superior lines with high and stable yield potential. The genotype × environment interaction is a major challenge in the study of quantitative traits because it reduces yield stability in different environments, complicates the interpretation of genetic experiments, and makes predictions difficult. Therefore, it is very important to know the type and nature of the interaction effect and achieve 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 multivariate method of additive main effects and multiplicative interaction (AMMI) is a method with suitable efficiency to investigate the genotype × environment interaction effect and provides good information about studied genotypes and environments. This study aimed to investigate the genotype × environment interaction effect using the AMMI method to evaluate genotypes, environments, and relationships between genotypes and environments. Finally, this study sought to identify stable rapeseed genotypes with high grain yields under different environmental conditions. Methods: Nine lines and six cultivars were evaluated in a randomized complete block design with three replications in six experimental field stations (Karaj, Kermanshah, Isfahan, Hamadan, Zarghan, and Qazvin) during two cropping seasons. The genotype × environment interaction was analyzed using the AMMI method. Plants were harvested at maturity, and then the seed yield was recorded for each genotype at each test environment. Results: Results of the combined analysis of variance (ANOVA) indicated that the effects of environments (E), genotypes (G), and the genotype × environment (G × E) interaction were significant on seed yield. The results of the ANOVA indicated that 77.56, 3.96, and 18.48% of total variation were related to the E, G, and G × E interaction effects, respectively. The results showed that the first four principal components of AMMI were significant and described 80.35% of the variance of the G × E interaction. The results showed that the average yield of the studied genotypes was in the range of 2669-3398 with a total average of 3065 kg.ha-1. Genotypes G1 and G15 produced the lowest and highest seed yields, respectively, and the average seed yields of genotypes G3, G4, G6, G7, G8, and G9 were higher than the total average seed yield. Based on the average of sum ranks (ASR), G2, G11, G6, and G9 genotypes with the lowest ASR values were the most stable, while G10, G12, G3, and G13 genotypes with the highest ASR values were the most unstable genotypes. Among the stable genotypes, G6 and G9 were recognized as genotypes with good seed yield and general compatibility due to their higher average seed yields. Furthermore, the Zarghan location was recognized as the most ideal environment for distinguishing and separating rapeseed genotypes due to its high interaction. The cluster analysis classified the studied environments into three groups. The Isfahan, Hamedan, Zarghan, and Karaj locations were placed in a group in both years, indicating that these locations had high predictability and repeatability power. Conclusion: Based on the results of the AMMI method, G6 and G9 were better than the other genotypes for seed yield and stability and showed high general adaptation to all environments. Additionally, the Zarghan location was recognized as the most ideal environment due to its high interaction for distinguishing and separating rapeseed genotypes. Generally, the results showed the efficiency of the AMMI method in investigating the G × E interaction effect and providing good information about the studied genotypes and environments.

Extended Abstract Background: Artemisia absinthium, commonly known as Afsantin, is an important perennial medicinal herb native to Asia, the Middle East, Europe, and North Africa. During the evolutionary process, plants have developed mechanisms that not only allow them to survive under the most severe radiation doses but also respond effectively to small changes in radiation intensity through physiological adjustments. One of the plant defense mechanisms against radiation is evolutionary changes in gene expression levels. Among these genes, farnesyl diphosphate synthase (FDS) is a key enzyme in the terpenoid metabolic pathway that catalyzes the synthesis of sesquiterpenoid compounds from the farnesyl pyrophosphate (FPP) precursor and plays an important role in regulating plant growth and development. The present study investigated the effects of radiation from radioactive waste in an abandoned uranium mine on the expression changes of the FDS and squalene synthase (SQS) genes in A. absinthium, grown for many years in the radioactive sampling site environment. Methods: Plant material was sampled from the altitudes of Kojanaq village located 18 km northwest of Meshginshahr City with the geographical coordinates of 38° 29' 17.7" N and 47° 30' 15.1" E. All calculations related to the geographical position were performed using a Garmin satellite positioning device (Oregon model, 650). For complete access to radiation contamination information in the study area, a point-by-point radon radiation map was prepared at 10 points using a radiation meter over two consecutive years with a Victoreen 451 radiation meter (Fluke Biomedical Company, USA). These measurements included points at the same altitude on two opposite mountains (mountains with radioactive material points A and non-radioactive B). A. absinthium shoots were sampled systematically in three different biological replicates. Total RNA was extracted from the sampled plant leaves, and the first cDNA strand was synthesized afterward. The Primer 3 Plus online software was used to design qPCR primers, which were then analyzed using the Oligo Analyzer tool and the NCBI/Primer-BLAST plugin in the NCBI genetic database. Initially, the gene regions controlling the farnesyl diphosphate and squalene synthase enzymes were amplified using the synthesized cDNA for all control and non-control samples as templates to ensure the accuracy of the designed primers. Quantitative analysis of the target gene expression was performed by the Real-Time PCR method using the Corbett Real-Time PCR (3000) and the CyberGreen kit (Sinaclon Company). The gene expression pattern changes in all synthesized cDNAs from the studied samples were measured using the Amplicon SYBR Green High ROX master mix. Results: Statistical analysis using GraphPad Prism 10 software showed that the expression levels of both studied genes were higher in samples collected from radioactive points than in non-radioactive points. The highest relative increase in gene expression was observed in the squalene synthase-controlling gene, which is one of the key genes in the biosynthetic pathway of the isoprenoid metabolite group. Statistical comparison of the relative expression pattern of the SQS gene in non-radioactive (Bsqs) and radioactive (Asqs) samples showed a significant difference in the SQS gene expression levels between samples collected from radioactive and non-radioactive areas at a 99% probability level. Furthermore, statistical analysis of the relative expression pattern of the FDS gene in non-radioactive (Bfds) and radioactive (Afds) samples revealed no significant difference in FDS gene expression levels between samples collected from radioactive and non-radioactive areas at a 99% probability level. Additionally, the P-value for the relative expression of the SQS gene in radioactive and non-radioactive area samples was calculated as 0.0077, and it was 0.6039 for the FDS gene. Conclusion: Considering that the expression level of the SQS gene was highest at an altitude of 860-900 m with an average radiation intensity of 0.567 mSv, and at an altitude of 910-930 m with the highest radiation level (1.25 mSv), the squalene gene expression level showed a severe decrease. It can be inferred that the optimal radiation intensity for inducing the SQS gene expression is around 0.5 mSv, and an increase in radiation intensity leads to a significant reduction in the expression of this gene. Presumably, with an increase in radiation intensity and ionizing rays, the plant intelligently modulates the biosynthetic pathway of squalene and directs the biosynthetic pathway toward the synthesis of sesquiterpenoids, which compete with the SQS enzyme for the common precursor farnesyl diphosphate. Since the mutagenic effect of radioactive elements has been proven, it can be concluded that long-term exposure of perennial plants to radioactive radiation leads to genetic changes. These mutations alter the structure and behavior of enzymes involved in the biosynthetic pathways of secondary metabolites and likely represent a genetic-biochemical protective response of the plant to combat the damage caused by free radicals generated by radioactive materials.

Extended Abstract Background: Sugar beet (Beta vulgaris L.) is one of the most important root crops and the main source of sugar. It has the greatest ability to be cultivated in the temperate regions of Iran. One of the main centers for cultivating this crop in Iran is West Azerbaijan Province, which accounts for a major share of its production in the country. Rhizomania disease is among the most important factors limiting the growth and reducing the yield of sugar beet. Given that the use of some agricultural methods, such as planting date, irrigation methods, crop rotation, chemical methods, and biological methods, are not very useful in fighting the disease, the use of resistant cultivars is suggested as the best and only way to fight this disease. So far, several studies have been conducted on obtaining disease-resistant cultivars. The first prepared and cultivated hybrid, called Rizor, was a relatively resistant monogerm diploid hybrid that significantly increased the yield of sugar beet in contaminated fields. Studies on the genetic diversity of this strategic plant help breeders identify genetic resources resistant to rhizomania disease with breeding objectives, including yield and yield components. It is crucial to be aware of the differences and diversity between different genotypes of sugar beet and the associations of these differences with their potential performance in improving the yield of new cultivars. Since there are mutual effects among the variables in multivariate regression, a variable may be significant next to some variables, but not significant next to some other variables. For this reason, it is necessary to select important variables that have a significant effect on yield. In this regard, this research aimed to evaluate domestic and imported modified varieties of sugar beet under the presence of rhizomania disease in the climatic conditions of Miandoab City. Methods: An experiment in the form of a completely randomized block design with four replications was conducted at the Miandoab Agricultural and Natural Resources Research Center in the geographic location of 46° 90' E and 36° 58' N with at an altitude of 1314 m above sea level. The experimental materials included 12 sugar beet genotypes (10 domestic genotypes with one imported resistant genotype and 1 domestic sensitive genotype). In this study, the studied genotypes were exposed to the natural infection of the region. After determining the percentage of cultivars, the level of resistance and sensitivity of each genotype was determined based on the percentage of infection. Before the experiment, land preparation operations included plowing, disking, leveling, and plotting the field in the same way. Phosphorus and potash fertilizers were applied based on the results of the soil decomposition test at the time of land preparation, and nitrogen fertilizer was used as a starter in the form of plant feet. The seed distances between and on the rows were 60 cm and 15 cm, respectively. The size of each plot included three planting lines with a length of 8 m. Agricultural operations, including irrigation, pest and disease control, and cultivator application, were carried out as needed. Root yield traits, pure sugar percentage by the polarimetric method, gross sugar percentage, pure sugar yield, gross sugar yield, extraction percentage, and molasses sugar percentage were measured after harvest. Results: Based on the results of variance analysis of data, significant differences were observed between genotypes in terms of all traits. According to the results of comparing the average traits, genotype 31914 (domestic number) with 11.97% was the least infected and, at the same time, the most resistant variety, and genotype SBSI010 (susceptible-domestic control) with 79.37% was the highest contamination and the most sensitive variety to rhizomania disease among the studied genotypes. In this study, the correlation coefficients of the infection percentage index had negative and significant relationships with root yield traits, gross sugar percentage, pure sugar percentage, gross sugar yield, pure sugar yield, and the extraction coefficient at the probability level of 1%. However, this parameter showed a positive and significant relationship with the molasses sugar trait at the probability level of 1%. Moreover, the infection severity index showed a positive and significant relationship with the yield traits, namely pure sugar, molasses sugar, potash, and harmful nitrogen at the level of 1%. Based on the results of step-by-step regression analysis, the percentages of root infection, sugar extraction, and gross sugar explained 68.7% of the changes in pure sugar yield. Besides, the percentage of root infection had a negative direct effect and the percentages of sugar extraction and gross sugar had a positive direct effect on the yield changes of white sugar. Conclusion: Although genotype SBSI030 showed the maximum quantitative and qualitative traits in this study, the lowest percentage of root infection was recorded for genotype 31914. After additional tests, genotype 31914 can be used as a genetic source resistant to rhizomania. This investigation showed that gross sugar percentage had the most positive effect on white sugar yield. Thus, selecting genotypes with a high gross sugar percentage can lead to obtaining cultivars with high white sugar yield.

Extended Abstract Background: Oilseeds are one of the most important sources of energy in the world. As one of the most important oilseed plants in the world, rapeseed has nutritional and economic value, with its seeds containing 40% oil and its oilseed meal containing more than 35% protein. This plant has higher adaptability to diverse climatic conditions. Given the need to supply edible oil in Iran, the selection of high-yielding genotypes with desirable characteristics in this plant is very important for sustainability in production. Moreover, examining the relationship between yield and other agronomic traits improves the efficiency of breeding programs by determining appropriate selection criteria, such that some breeders prefer to select varieties indirectly using yield-related traits to achieve high yield. Among the methods that provide more appropriate characteristics of the status of genotypes and traits are graphical methods that allow for visual examination of correlations and relationships between traits and evaluation and identification of desirable genotypes based on the values of yield-trait combinations. Therefore, this study aimed to compare different genotypes of rapeseed in terms of several traits and analyze the correlation between their different traits, as well as to select superior rapeseed genotypes based on the combination of agronomic traits with oil yield using genotype × trait biplot and genotype × yield × trait biplot methods. Methods: In this study, 15 new lines along with two cultivars were evaluated in a randomized complete block design with three replications in the Agriculture Research Station of Gonbad during 2019-2020. The phonological, morphological characteristics, and yield components including days to flowering starting, days to physiological maturity, plant height, the number of lateral branches, the number of pods per plant, the number of seeds per pod, 1000-seed weight (TSW), oil content, and oil yield were measured in the sample plants. In this study, the genotype × trait (GT) and genotype by yield × trait biplot (GYT) methods were used to identify interrelationships between different traits and selection of the best rapeseed genotypes. Results: The results showed that the genotype by yield × trait biplot method was more efficient than the genotype × trait biplot method. Based on the biplot and the genotype by yield × trait biplot index, a positive correlation was observed between all yield-trait combinations, and genotype 17, followed by genotypes 11 and 4, respectively, were identified as the best genotypes in the combination of oil yield with days to flowering, days to physiological maturity, plant height, the number of lateral branches, the number of pods per plant, the number of seeds per pod, TSW, and oil percentage. Genotypes 2 and 15, respectively, were identified as the weakest genotypes by being located at the end of the horizontal axis of the average tester coordinate diagram. Moreover, the results of the genotype by yield × trait biplot showed a high positive correlation between oil yield × the number of lateral branches, oil yield × the number of seeds per pod, oil yield × TSW, oil yield × plant height, oil yield × oil percentage, oil yield/days to flowering, and oil yield/days to physiological maturity, indicating the usefulness of combining the number of lateral branches, the number of seeds per pod, TSW, oil percentage, plant height, and maturing time (the number of days to flowering and maturing) with oil yield to increase the production of genotypes in rapeseed. Conclusion: In general, the results showed that the genotype by yield × trait biplot method was a more suitable tool for investigating relationships between traits and evaluating, comparing, and selecting different rapeseed genotypes in terms of multiple traits than the genotype × trait biplot method. Based on the display of the average tester coordinates of the genotype × yield × trait biplot, genotypes 17, 11, and 4 were identified as the best genotypes with genotype × yield × trait biplot values of 2.22, 1.33, and 1.01, respectively, and genotypes 2 and 15 were identified as the weakest genotypes with genotype × yield × trait biplot values of -1.78 and -1.01, respectively, in terms of oil yield and other agronomic traits. Furthermore, the number of lateral branches, the number of seeds per pod, TSW, plant height, and maturing time (the number of days to flowering and maturing) are the traits that can be used as appropriate indicators in breeding programs to select high-yielding genotypes in rapeseed.

Extended Abstract Background: The sustainable development of rapeseed cultivation areas, especially in Iran, requires the introduction of new cultivars with higher grain and oil yields and compatibility with different regions through breeding programs. The genetic diversity of rapeseed genotypes should be evaluated based on a set of quantitative and qualitative traits. Evaluation of genotypes using a set of traits increases the probability of finding ideal genotypes. The ideal genotype selection index is one of the multivariate statistical methods that identifies the desired genotypes based on a set of different traits or indices. Besides, factor analysis is another multivariate statistical method that is used to categorize traits, determine the importance and relevance of each of them in creating changes in the total data, and identify traits that affect yield. Identifying traits that affect yield enables the breeder to focus on specific traits that have caused variation. Accordingly, the ideal genotype selection index and factor analysis approaches were applied to study the agronomic characteristics and quantitative and qualitative traits of seeds in different canola lines and finally select the superior genotypes from the viewpoint of high seed and oil yield along with the highest amount of essential fatty acids. Methods: In this study, 21 genotypes obtained via breeding programs were evaluated in a randomized complete block design with three replications in the Gorgan Agricultural Research Station. Various 23 quantitative and qualitative traits, including phenological traits [the number of days to the beginning of flowering, the number of days to physiological maturity], agronomical traits [plant height (cm), the number of lateral branches, branching height (cm), main stem length (cm), pod length (cm)], and yield and its components [the number of pods per main stem, the number of pods per lateral branches, the number of pods per plant, the number of grain per pod, thousand-grain weight (g), grain yield (kg ha-1)], as well as qualitative traits [oil content (%), oil yield (kg ha-1), the amount of glucosinolate in the grain (micromol/g of grain), and the percentage of fatty acid composition (orosic acid, linolenic acid, linoleic acid, oleic acid, stearic acid, palmitoleic acid, and palmitic acid) were determined during the growth season. The analysis of variance (ANOVA) was applied to examine differences between genotypes, the factor analysis was exploited for indirect selection for grain yield through other dependent traits as well as the ideal genotype selection index was used for the two important traits including grain yield and oil yield based on abovementioned 22 traits. Results: The results of ANOVA showed that the genotypes were statistically different (P < 0.01) in all the studied traits, except for the number of lateral branches and the number of grains per pod, which indicates the existence of genetic diversity between the studied genotypes. The results of the ideal genotype selection index depicted that the genotypes G20, G12, G16, G1, G7, G10, and G11 with the ideal genotype selection indexes of 0.621, 0.584, 0.673, 0.633, 0.591, 0.728, and 0.673 and grain yields of 3258.67, 3140.67, 2941.33, 2763.33, 2712.67, 2575.33, and 2548 kg ha-1, respectively, were identified as genotypes with high grain yield potential and other desirable agronomic traits. Furthermore, the genotypes G20, G12, G16, G2, G1, G10, and G11 with the ideal genotype selection indexes of 0.622, 0.584, 0.673, 0.589, 0.633, 0.727, and 0.672 and oil yields of 1218.28, 1201.42, 1109.54, 1102.27, 1056.45, 987.40, and 961.27 kg ha-1, respectively, were identified as genotypes with high oil yield potential and other desirable agronomical traits. Hence, these genotypes can be used in compatibility test trials. In this study, the 23 measured traits were applied for factor analysis. The obtained Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy values and the significance of Bartlett's sphericity test indicated the adequacy of the correlation values of the primary variables for factor analysis and the adequacy of the factor analysis model. In this research, seven factors were identified based on factor analysis. These factors explained 82.13% of the total data variation. The values of the first to seventh factors were estimated at 20.86, 15.99, 13.99, 10.65, 8.80, 6.27, and 5.57%, respectively. The first to seventh factors are recognized as factors affecting oil quality, morphology and appearance, vegetative attributes, physiological sinks, economic grain yield, and oil quantity and quality as well as phenology and ripening characteristics. In addition, the results of factor analysis showed that the number of pods per main stem, the number of pods per lateral branch, and the number of pods per plant were the traits with a positive relationship with grain yield and grain yield with oil yield. Conclusion: In general, the results of this experiment showed that the ideal genotype selection index and factor analysis approaches were identified as an extremely powerful tool for selecting superior rapeseed genotypes based on the aforementioned quantitative and qualitative traits. Based on the ideal genotype selection index, G20 and G12 genotypes were among the excellent genotypes in terms of grain and oil yields with higher ideal genotype selection indexes. In addition, the number of pods per main stem, the number of pods per lateral branch, and the number of pods per plant are the traits that can be used as an ideal selection index for the selection of grain yield and grain yield for the selection of oil yield to select high-potential genotypes in breeding programs.

Extended Abstract Background: Sonchus arvensis L. is a medicinal plant from the Asteraceae family. The valuable medicinal properties of this plant are due to the presence of important and valuable phenolic acids, such as chlorogenic acid. Reducing the risk of various diseases, such as heart disease, diabetes, and cancer, following the consumption of chlorogenic acid has been proven in clinical and research studies. Therefore, more research in the field of medicine and pharmacy on this plant will be considered by researchers in the future. Moreover, there is little information about the genetics of secondary metabolism in medicinal plants. Thus, the genes of many secondary metabolite biosynthesis pathways have not been identified, and little information exists about their regulation and function. Therefore, identifying biosynthetic pathways, knowing how the genes involved in these pathways are regulated, and analyzing their phylogeny are particularly important. On the other hand, examining the phylogenetic relationships of genes in different plant species and determining the evolutionary relationships between them can help better understand the evolution of species. Furthermore, knowledge of the nucleotide sequence of genes and the frequency of different nucleotides is essential for estimating the divergence time of species and reconstructing the evolutionary relationships between different species. The present study aimed to sequence part of the coding region of some genes involved in the chlorogenic acid biosynthetic pathway, such as cinnamate 4-hydroxylase (C4H), P-coumarol-ester 3'-hydroxylase (C3'H), and hydroxycinnamoyl coashimate/quinate hydroxycinnamoyl transferase (HCT), and to investigate their evolutionary and phylogenetic relationships in S. arvensis. Methods: Since the sequences of C4H, HCT, and C3'H genes were not identified in S. arvensis, their sequences were recovered from plants that are evolutionarily close to S. arvensis, such as Cynara cardunculus var. scolymus and Cichorium. intybus. First, the sequences of these genes in plants phylogenetically close to S. arvensis were collected from GenBank and aligned using Clustal Omega software, followed by identifying conserved regions. Then, specific primers were designed based on the conserved regions using Fast PCR 4.0 and Gen Runner 3.05 software. In the next step, DNA from leaf samples was extracted by the CTAB method, and the studied gene fragments in S. arvensis were amplified using the designed specific primers and polymerase chain reaction (PCR). Electrophoresis of the resulting products was performed using a 1.5% agarose gel at a voltage of 80 V for one to two hours. After staining with ethidium bromide, a photograph was taken using a Gel Doc device (INFINITY, France). Given the specificity of the amplified products, the PCR products were sent directly to Microsynth Company (Switzerland) for sequencing part of the coding regions of the C4H, C3'H, and HCT genes. To ensure reliability, all PCR products were sequenced in both forward and reverse directions, and alignment (BLAST) of the sequenced fragments against DNA, RNA, and protein databases was performed to verify the accuracy of the sequenced fragments. Then, phylogenetic relationships and the frequency of nucleotide mutations were examined and analyzed in these genes. MEGA5 and BLAST software were used to examine phylogenetic relationships (the maximum likelihood method) and analyze nucleotide sequences (including frequency and substitution). Clustal Omega software was used to examine the alignment of nucleotide and protein sequences. Amino acid analysis (the percentage and weight of amino acids and inferred proteins) was performed with Bio Edit and MEGA5 software, and the Neutrality test was performed with MEGA5 software. Results: For the first time in this research, a portion of the coding sequence of the C4H, C3'H, and HCT genes was identified in Sonchus arvensis and registered in GenBank with accession numbers ON014597.1, ON014595.1, and ON014596.1, respectively. The results of the analysis of nucleotide sequences showed that nucleotide frequency for C4H, C3'H, and HCT genes were the highest for adenine (28.1), guanine (28.4), and thymine (1.1), respectively, and the lowest nucleotide frequency belonged to thymine (13.2), thymine (20.1), and cytosine (19.7), respectively. Moreover, the neutrality test results showed the directional selection of these genes during evolution. The transition substitution mutation was more frequent than the transversion substitution mutation. The results of phylogenetic analysis based on C4H, HCT, and C3'H gene sequences showed a close phylogenetic relationship or a low genetic distance between S. arvensis and lettuce (L. sativa). The results of the sequence blast at both the nucleotide and protein levels showed a high similarity to evolutionarily close plants, such as L. sativa. Conclusion: The results of this research positively evaluated the process of natural selection during evolution for the studied C4H, C3'H, and HCT genes, which indicates the effects of genetic drift or the balancing effects of population evolution throughout history, and a low difference between the frequencies of the polymorphisms. The BLAST results of sequenced C4H, HCT, and C3'H gene fragments in S. arvensis at the nucleotide and protein levels showed the highest percentage of similarity (lowest genetic distance) to plants such as L. sativa and Cichorium intybus, which confirmed the accuracy of the sequence results. Additionally, phylogenetic analysis based on the sequencing of C4H, C3'H, and HCT genes showed a close phylogenetic relationship between S. arvensis and L. sativa.

Extended Abstract Background: Green pea (Pisum sativum L.) is the fourth most important legumes in the world, which is consumed as dry, green, and fodder peas. It is an annual, self-pollinating, and diploid (2n = 2x = 14) plant that is widely cultivated as a garden and field crop throughout the temperate regions of the world. Although this plant has been cultivated in Iran for a long time, few studies are available on the genotypes collected in Iran and their characteristics and genetic diversity. Between 2005 and 2009, there was a program to collect the vegetable genotypes of the country with the efforts of researchers and experts from all over the country aiming to preserve the native populations. The accessions in the country have been severely eroded due to the desire of farmers to cultivate foreign cultivars, and many of the accessions in the vegetable collection of the gene bank are unique; hence, it is not possible to find these accessions in the country anymore. These accessions are usually adapted to the weather conditions, pests, and diseases of the country and are very important in the development of sustainable cultivation. In green peas, foreign cultivars are most welcomed by farmers. Therefore, the accessions of the green pea collection of the Gene Bank are of special importance. Methods: In this study, 63 green pea accessions, along with five commercial varieties Utrillo, Wando, Mr. Big, Alderman, and Rondo, were cultivated and evaluated in seven blocks in an augment design in the research field of the National Plant Gene Bank of Iran (Seed and Plant Improvement Institute) in 2020-2021. Each accession was cultivated in a 2-meter line with a row distance of 60 cm and a plant distance of 10 cm. Then, 38 agronomic and morphological traits were evaluated according to the UPOV descriptor in traits related to leaves, flowers, pods, and seeds. The Shannon index (Hˊ) was used to determine the diversity of qualitative traits. Data were analyzed using SPSS and SAS statistical software, and the correlation was calculated using Pearson's method. The genotypes were grouped using cluster analysis. Results: According to the results, the highest coefficient of variation (CV) in quantitative traits is respectively for the peduncle length between the first and second pods (1.30 cm) and the spore length (0.85 cm). The lowest CV was obtained for the standard petal width (0.14 cm) and the total length of the petiole, including tendrils (0.15 cm). The highest Shannon's coefficient in qualitative traits was observed in the density of flecking stipules (1.33), stipule size (1.09), and pod curvature (1.04). The lowest Shannon's coefficient was observed in having leaflets (0.09). The strongest positive correlation was obtained between the weight of one-hundred seeds and the length and width of the pod, as well as between the length and width of the pod. The principal component analysis showed that the first four components included 65% of the total changes. In the first component, which accounted for 33% of the observed changes, the most important traits affecting this component were one-hundred dry seed weight, length, and width of pods. The second component justified 15% of the data changes and had a strong and positive relationship with the leaflet length and the petiole length. The third component justified 10% of the data changes and had a strong and positive relationship with the length from the peduncle to the first pod and the number of seeds per pod. The fourth component accounted for 7% of the observed changes and had a strong and positive relationship with the length of the distance from the length between the first and second pods and the stipule length from the axil to the tip. In cluster analysis, the genetic accessions were classified into seven separate groups, respectively, 8, 26, 6, 1, 2, 13, and 12. The grouping of genetic accessions was independent of their geographical origins. The different genetic accessions of the investigated green peas had a wide range of morphological characteristics, which indicates the high genetic diversity of this crop. Conclusion: The results showed a range of 32 days in the number of days to flowering, a range of 90 cm in the plant height, and a range of 24 g in one hundred seed weight. In this research, genetic accessions 38, 79, 83, and 82 were the earliest flowering genotypes, genetic accessions Mr. Big and 81 had the largest pod length, and genetic accessions 81 and 83 had the largest pod width. Genetic accessions 80, 82, and 58 had the highest one-hundred seed weight. Many genetic diversities were observed in the characteristics of the type of bracket and the margin of the stipule in an Iranian accession; thus, it seems necessary to include these characteristics in the international descriptor of green peas. In this study, a high genetic diversity was observed among green pea accessions in the country, and this diversity can be used in breeding programs to obtain cultivars compatible with Iran's cultivation areas.

Extended Abstract Background: One of the main elements of sustainable development of any country is to provide enough food at a suitable price for the people of that society. Cereals and their products are the main part of most human diets in developed and developing countries, which constitute a major part of dietary energy and nutrients. Wheat (Triticum aestivum L.) is one of the most widely used crops in the world and has the second highest production in grains following corn. Wheat provides approximately 20% of calories and protein to 4.5 billion people in various forms. Climate change poses a significant threat to most agricultural products in tropical and subtropical regions worldwide. Drought stress is one of the consequences of climate change that negatively affects the growth and yield of wheat. The predictions of climate change models show that the average global temperature will increase between 0.5 and 3.7 °C by the end of 2100. The simultaneous effects of increasing temperature and decreasing rainfall are expected to increase the intensity and frequency of drought. It is also expected that the effects of climate change on agricultural products will be more severe in arid and semi-arid regions, such as Iran. Hence, it is necessary to create new cultivars with high yield in regions exposed to drought. Thus, agro-morphological traits affecting grain yield under dry conditions were evaluated in winter wheat cultivars of 24 lines and cultivars of bread wheat. Methods: The experiment was conducted in a complete randomized block design with three replications under rainfed conditions. In this study, 12 advanced lines along with the WAZ line and 11 autumn wheat cultivars, named Sardari, Homa, Azar2, Takab, Ouhadi, Rasad, Hashtrood, Baran, Sain, Sadra, and Cross Sabalan, were evaluated in the Research Field of the Faculty of Agriculture, Zanjan University, during the agricultural year 2017-2018. For this purpose, traits such as days to booting, days to heading, days to anthesis, days to physiological maturity, relative leaf water content (RWC), canopy temperature difference, plant height, spike length, peduncle length, peduncle extrusion, number of spike per m2, spikelets per spike, number of grain per spike, thousand kernel weight, grain yield, biomass, and harvest index were measured in this study. Data were analyzed after measuring the traits, and the averages were compared using Duncan's method. The relationships between traits were investigated using multivariate statistical analyses, including correlation analysis, regression analysis, and principal component analysis (PCA). Results: The results of the analysis of variance and mean comparisons revealed high variability among genotypes for most of the measured traits. There was a significant difference between the genotypes in terms of all traits, except for RWC, canopy temperature difference, number of spikes per square meter, and thousand-kernel weight. The results of Duncan's mean comparison showed that the highest grain yield belonged to the Hashtrood variety. The Cross Sablan variety was identified as the latest tern variety, and line 8 as the earliest genotype in this study. Among the investigated genotypes, line 2 was the highest genotype. The results of correlation analysis showed a high and significant positive correlation between grain yield and the number of seeds per spike and a negative and significant correlation between yield and spike length. The number of seeds per spike had a positive and significant correlation with the harvest index. Moreover, the number of seeds per spike had a negative and significant correlation with the thousand kernel weight and the number of spikes per square meter. RWC showed a positive and significant correlation with peduncle length. The results of stepwise regression analysis, considering grain yield trait as a dependent variable and other traits as independent variables, showed that four variables (the number of seeds per spike, the number of spikes per square meter, thousand kernel weight, and spike length) accounted for 93.8% of grain yield changes. The results of PCA showed that the first five components had an eigenvalue higher than one and accounted for the largest amount of variance, so that the first five components had 80.21% of the total variance. In addition, the first, second, third, fourth, and fifth components accounted for 22.03, 19.12, 17.46, 13.05, and 8.55% of the total variance, respectively. Based on the PCA results, the number of seeds per spike, grain yield, and harvest index were positively related to the second component. Conclusion: In rainfed conditions, high vegetative growth and high biomass production cause the complete drainage of moisture in the early growing season, and the plant faces severe stress after the pollination stage, severely reducing the yield. On the other hand, genotypes with a short spike length but with a more number of spikes per square meter and a more number of seeds per square meter showed a higher grain yield, and these genotypes can be used for crossing in future breeding programs.

Extended Abstract Background: Considering the diversity in climatic conditions, agricultural management, the extent of barley cultivation areas in Iran, and observing the different reactions of different cultivars to environmental conditions, it is of particular importance to introduce high-yielding cultivars with wide adaptability to different conditions. Due to the genotype × environment interaction effect, it is difficult to identify cultivars that have good stability and acceptable yield in various environmental conditions. Therefore, cultivars should be studied in a wide range of environmental changes in different locations and years so that the information obtained from the estimation of compatibility and yield stability of genotypes is a more reliable criterion for recommending cultivars and their efficiency. The methods for determining the genotype × environment interaction effect are divided into two groups: single variable (parametric and non-parametric) and multivariable. Each of these methods shows different aspects of the stability of genotypes, and one method alone cannot investigate the yield of a genotype in different environments from different aspects of stability. This research aimed to select promising barley genotypes with high yield and suitable stability in dry conditions in the cold climate of Iran using parametric and non-parametric univariate stability analysis methods. Methods: In this study, 25 advanced and promising lines of barley, along with Ansar, Abider, and Sararoud1 (check cultivars), were studied in dry conditions in a completely randomized block design with four replications in research stations of Maragheh, Kurdistan (Qamlo), Zanjan (Qidar), Ardabil, Kermanshah (Sararoud), Shirvan, and Hamedan for three crop seasons from 2016 to 2019. The stability of the genotypes was explored using parametric and non-parametric univariate methods. Parametric and non-parametric univariate methods were integrated using the selection ideal index genotype (SIIG) method. Finally, the correlation of the parameters with yield and the SIIG was also calculated in this research. Results: Separate analysis of variance in each of the environments showed that the genotype effect was significant in 12 out of 19 environments, which indicated the fluctuation of the yield of each genotype from one environment to another. Combined variance analysis showed that the interaction effects of year × location and genotype × year × location were significant at 1%, the year effect at 5%, and the location and genotype effects were significant at 10% probability levels. The main effect of the environment and the genotype × environment interaction effect had the largest share in the total sum of squares observed in the experiments, with 69.98% and 10.83%, respectively. Eberhart and Russel's analysis identified genotypes G1, G4, G5, G8, G9, G10, and G26 as the most stable genotypes due to having the lowest deviation from regression and a regression coefficient close to one. Considering the yield, G9 and G10 genotypes were introduced as stable genotypes with high yields. According to Finley and Wilkinson's linear regression coefficient, genotypes G4, G6, G9, G11, G12, G15, G17, G20, G27, and G28 had a regression coefficient close to one, which shows that these genotypes have general adaptability to environments. Based on Wrick's equivalence index and Shukla’s stability variance, genotypes G8, G19, G10, G20, G9, G4, G26, and G1 were identified as stable genotypes. Based on the coefficient of environmental variation, genotypes G10, G1, G8, G23, G13, G2, and G5 had the lowest coefficient of variation. Based on the Plasted and Peterson method, genotypes G10, G20, G19, and G9 were selected as stable genotypes with high yields. In the Plaisted method, genotypes G10, G20, G19, and G9 with the least contribution in creating interaction and having the desired yields were introduced as stable and high-yielding genotypes. Based on Lin and Bains, genotypes G15, G6, G21, G19, G20, G7, and G9 had the least amount of this statistic and were introduced as the most stable genotypes. Based on Kang's total rank method, G20, G19, G10, G9, and G22 genotypes with the lowest total rank were selected as stable genotypes. Based on the parameters of Nassar and Huhn, genotypes G8, G9, G10, G1, G20, G19, and G21, and based on the parameters of Thenarasu, genotypes G8, G9, G10, G1, G19, and G22 with the lowest rank were selected as stable genotypes. Finally, based on the SIIG, genotypes G10, G9, G19, G22, and G20 had the closest value to one and produced higher yields than the overall average; therefore, they were selected as the most stable genotypes. Conclusion: Based on the SIIG, genotypes G10, G9, G19, G22, and G20 had the closest value to one and produced yields above the average; therefore, they were selected as the most stable genotypes. Moreover, the use of the SIIG is recommended due to its high correlation with all the indices used to summarize the results of parametric and non-parametric stability indices.

Extended Abstract Background: Sugarcane (Saccharum officinarum L., from the family Poaceae) is one of the most economically important crops globally, widely cultivated in tropical and subtropical regions due to its production of sugar, ethanol, bioenergy, and bagasse. Given its key role in providing renewable energy and derived products, sugarcane is a major focus of agricultural and industrial research. However, salinity stress is one of the most significant challenges impacting sugarcane production, especially in saline areas. Soil salinity is one of the most critical environmental stresses, leading to reduced plant growth and yield, posing a serious global threat to agricultural production. Salinity stress negatively affects sugarcane growth and development in several ways, including reduced water uptake, disruption of metabolism, and accumulation of sodium in plant tissues. As a result, the severe decline in yield and product quality in saline areas has become a major concern for both farmers and researchers. This review aims to examine the challenges posed by salinity in sugarcane and to present innovative remedial strategies for enhancing the crop's resistance to salinity. Methods: This review study was conducted using a systematic search in reputable scientific databases, such as PubMed, Scopus, and Web of Science. Initially, over 100 articles related to salinity and sugarcane were reviewed in this overview. The criteria for selecting the articles included publication in peer-reviewed journals, relevance to the topic of salinity, and a focus on innovative remedial methods. Articles specifically addressing novel approaches for improving sugarcane resistance to salinity were selected and analyzed after an initial review. The extracted data were qualitatively analyzed and categorized to identify key challenges and trends. Results: The results of this study show that salinity has widespread negative effects on sugarcane's physiological and biochemical processes. In the early stages of salinity stress, the plant experiences osmotic stress due to reduced water uptake and stomatal closure, which leads to a decrease in photosynthesis and, ultimately, a reduction in plant growth. Sodium accumulation in cells causes ionic stress, resulting in cell membrane damage and decreased enzymatic activity. These processes lead to premature leaf senescence and a significant reduction in sucrose concentration in sugarcane stalks, directly affecting the quality of the final product. Various methods have been employed globally to address these challenges. One of the primary approaches is the genetic improvement of sugarcane through traditional methods, such as selecting salinity-tolerant parents and performing hybridization. These methods enable the development of varieties that show greater tolerance to saline conditions. However, due to the complexity of the sugarcane genome, which includes multiple chromosome sets, this process is highly time-consuming, often requiring 7 to 12 years to produce a salinity-tolerant variety. Additionally, this genetic complexity makes each hybridization event unique and unpredictable, complicating the breeding process. In addition to traditional methods, modern molecular approaches have emerged as critical strategies for improving sugarcane's resistance to salinity. Molecular tools, such as PCR-based markers and genome-editing technologies (e.g. CRISPR), can target key salinity-tolerance genes and eliminate or modify sensitive genes, aiding in the development of salinity-resistant sugarcane varieties. These methods not only shorten the time required for resistance improvement but also provide a more precise and reliable way of genetic modification. Beyond genetic modification, the use of plant growth-promoting microorganisms (PGPBs) has been introduced as an effective approach for mitigating the effects of salinity. These microorganisms enhance salinity tolerance by producing plant hormones, such as indole-3-acetic acid (IAA) and cytokinins, improving nutrient exchange, and regulating osmoprotectant compounds, such as total soluble sugar (TSS) and proline. Additionally, these microbes protect plants against diseases and environmental stressors by producing antibiotics, hydrogen cyanide, and other pathogen-inhibiting compounds. Research has shown that the use of these microorganisms can significantly reduce the negative effects of salinity and improve sugarcane performance under saline conditions. Omics technologies, such as transcriptomics, proteomics, metabolomics, and ionomics, have also proven to be effective tools in identifying genes and molecular pathways associated with salinity tolerance. These techniques allow researchers to identify gene expression patterns under saline conditions and propose new strategies for improving sugarcane's salinity resistance. Specifically, next-generation sequencing (NGS) technology has played a vital role in accelerating transcriptomic studies of sugarcane tissues under salinity stress. Conclusions: In conclusion, this review demonstrates that salinity is one of the major challenges in sugarcane production, having extensive negative effects on the growth and yield of the crop. However, employing innovative remedial methods, such as traditional and molecular genetic improvement, the use of plant growth-promoting microorganisms, and omics technologies, can significantly enhance sugarcane's resistance to salinity. Given the critical importance of sugarcane in the global industry, future research should focus on optimizing these methods and developing new strategies to simultaneously increase the efficiency and sustainability of sugarcane production in saline areas and improve the quality of the final product.

Extended Abstract Background: As one of the most important oilseed crops all over the world, increasing the seed oil content of canola, along with higher genotypic and phenotypic potential of its yield, is among the significant goals of this crop for achieving large-scale production in different countries. The basis of plant breeding programs is diversity, and the success rate of such programs depends on the presence of genetic variability for screening and selection. The current study aimed to estimate heritability and the degree of heterosis of different traits in canola compared to the superior parent, and to assess the responses of these traits to hybrid lines. In addition, the best general and specific combining ability in parental lines with the highest heterosis and heritability were investigated using the full diallel cross method in spring canola. Methods: Seven canola cultivars were subjected to a full cross diallel (forward and backward crosses + parental lines) in 2020-2021. The first-generation (F1) hybrids with their parental lines (49 genotypes in total) were evaluated in a randomized complete block design with three replications in 2021-2022. The studied traits included the number of days to flowering, the number of days to maturity, plant height, the number of pods per plant, the number of seeds per pod, the weight of 1000 seeds, and seed yield. According to the Griffing and Heyman analytic methods, phenotypic and phenotypic properties were estimated using R-Software and the Library “DiallelAnalysisR. Results: ANOVA (analysis of variance) results for the traits showed that the difference between genotypes regarding all traits was significant at the 1% probability level. This result indicates the existence of a high diversity among the genotypes. The first Griffing method (full diallel) and Heyman's numerical method were used to analyze the diallel data. The results of the diallel analysis showed significant effects regarding general and specific combining ability and mutual effects for all investigated traits, which indicates the important effects of both additive and non-additive genes on controlling these traits. Moreover, the significance of the ratio of general to specific combining ability for all traits, except for the number of days to flowering and the number of days to ripening, indicated a higher significance of additive effects than non-additive effects in controlling such traits. Furthermore, it turned out that the cross of Safar × Dalgan lines could be efficient in the canola breeding program due to the positive and significant general combining ability in terms of seed yield, and negative general combining ability in terms of the number of days to maturity to achieve high-yielding and early-maturing genotypes for tropical regions. The range of heterosis compared to the superior parent for seed yield ranged from -33.8 to 30.3 in this study. The average degree of dominance for all traits, other than the number of days to flowering (relative dominance), indicated the presence of an over-dominance effect in controlling the traits; therefore, the phenomenon of heterosis can be used to increase and improve these traits. Dominance-direction was significant for all desired traits, except for the number of seeds per pod and the weight of 1000 seeds. Conclusion: The estimation of general combining ability showed that the parental lines, including Safar, Zafar, and Dalgan, were the best general combinations to increase seed yield. The two heterotic combinations RGS.003 × Dalgan and Roshana × Zafar can also be the most productive due to their positive and significant specific combining ability in terms of yield, and negative specific combining ability in terms of the number of days to maturity. Therefore, the single-cross canola hybrids of these crosses could be considered for release as varieties and distributed among the canola farmers. Finally, due to the highest grain yield of the hybrid lines resulting from Dalgan × Saffar, which was equal to 3754 kg per hectare (the average table is not given), it is suggested to directly include this hybrid in breeding programs and test it for stability.

Extended Abstract Background: Barley (Hordeum vulgare L.) is an ancient and significant cereal crop, ranking fourth in production after wheat, rice, and maize globally. Barley is recognized from other crops due to characteristics such as resistance to various biotic stresses, broad adaptability, and short growth duration. Genetic improvement is accelerated through the investigation of genetic diversity in genetic materials across various environments. Since grain yield is a quantitative and inherited trait, it is largely influenced by genotypic and environmental factors. Hence, indirect selection using other agronomic traits may be useful in identifying superior genotypes. The selection index of ideal genotypes (SIIG) can be used to better rank and compare different genotypes, select the best genotypes, and determine distances between genotypes and their clustering. With the increase in the number of traits or indices, it becomes difficult to select the appropriate genotype. In the SIIG index, all indices or traits become one index, and it becomes easier to rank and identify superior genotypes. Methods: To evaluate the genetic diversity and early screening of superior barley genotypes, an experiment was performed with 108 pure genotypes, along with four check genotypes (Armaghan, Rehan 03, Furat 03, and V Morales) in an augmented design in the Darab Agricultural and Natural Resources Research Station in the 2022-2023 cropping year. The SIIG index and principal component analysis (PCA) were used to select the superior genotypes in terms of grain yield and other measured traits. The genotypes tested were planted in three genotypes of 2.5 m long and 15 cm apart. Seed density was determined as 300 seeds per square. The measured traits included grain yield (GY), thousand-grain weight (TGW), grain filling rate (GFR), plant height (PLH), number of days to heading (DHE), and number of days to physiological maturity (DMA). ACBD software was used to estimate the variance components and the mean comparison test. The SIIG index and PCA were computed with R software. Results: The results of restricted maximum likelihood (REML) analysis showed that the lowest heritability values belonged to TGW (60%) and DMA (66%), while the highest values were found for PLH (96%) and GFR (91%). The grain yield varied between 1600 and 7833 kg ha-1 across investigated genotypes, indicating a significant difference and a high level of genetic diversity among them. The highest grain yield was recorded for genotypes 83, 57, and 27 with values ​​of 7833, 7300, and 7100 kg ha-1, respectively. The highest and lowest TGW values were measured for genotypes 17 (67.1 g) and 56 (36.2 g), respectively. As a result, two-row genotypes showed the highest TGW; thus, the average TGW varied between 52.6 g in two-row genotypes and 45.8 g in six-row genotypes. The average GFR in two-row genotypes (120.7 kg ha-1) was higher than that in six-row barley (110.3 kg ha-1). Moreover, DHE ranged from 131 to 144 days. On the other hand, the average of DMA was 139 days in two-row barley and 141 days in six-row barley. PCA was used to group genotypes and investigate the relationship among the measured traits. The first and second components justified 0.43 % and 29.7 % of the total phenotypic variation, respectively. In the first PC, the SIIG index and GY and GFP traits had the largest contribution, respectively. In the second PC, DMA, DHE, TGW, and PLH showed the largest contribution. As a result, GY and GFR showed a strong correlation with the SIIG index. Based on the PCA-based biplot, all investigated genotypes were divided into four groups. The first group consisted of the superior genotypes (57, 83, 63, 66, 25, 68, 60, 61, 48, 27, 23, 1, 3, 34, 25, 12, and 20) with an SIIG index greater than 0.6. The fourth group consisted of genotypes with an SIIG index less than 0.4. Conclusion: The results of this study revealed a high level of genetic diversity among the evaluated barley genotypes. The results show that the SIIG index is a suitable tool for the initial screening of genotypes in the preliminary tests of performance comparison using different traits. Based on the PCA results, the genotypes categorized in the first group (with SIIG values above 0.6) were identified as superior genotypes and can be used for additional tests. Moreover, a high association was found between the results of the SIIG index and PCA in grouping the genetic materials.

Extended Abstract Background:Sunflower is a cash crop with widespread cultivation worldwide due to its high adaptability to various climatic conditions. The cultivation of sunflower has accelerated due to the production and introduction of hybrid varieties that exhibit the phenomenon of heterosis. In Iran, the sunflower cultivation system has recently focused on second cropping, which requires tolerance to low temperatures during seed filling stage. The formation of yield in crop plants results from the interaction between two components: carbon-producing organs, source, and storage organs, sink. Identifying these components and regulating their relationships aids breeders in the direction of plant variety improvement. Although studies have been conducted on the relationships between source and sink and their interactions in sunflowers worldwide and in Iran, there is no report on the involvement of molecular components determining hybrid performance. Additionally, no study has been conducted on the physiological changes of hybrids during the hybrid breeding of sunflowers in Iran. This research aimed to identify strategies used in sunflower hybrids for yield formation under second cropping conditions, that is exposure to ambient temperature of 15̊ C, and to investigate the physiological molecular changes associated with yield formation in hybrids that have been bred and introduced over a 30-year period in Iran. Methods: The research was conducted over two experiments (in different years and locations) on three hybrids: Azargol, Farrokh, and Ghasem under second cropping conditions. The cultivation conditions were set so that the seed filling period would be exposed to temperatures of 15˚ C. At the onset of pollination, leaf number, leaf area, dry leaf weight, dry weight of receptacle base, and five uppermost stem nodes were measured; at physiological maturity, capitulum dry weight, capitulum diameter, dry weight of five uppermost stem nodes, 1000 seed weight, number of achene (filled and unfilled) per capitulum, and yield per plant were measured and counted. Eight days after pollination began, invertase enzyme expression levels in the receptacle base tissue were measured using Real-Time PCR technology. Data analysis was performed through combined analysis and mean comparison after ensuring normality. Results: The results from combined analysis indicated no significant interaction effects between experiments and hybrids for all traits studied. Regarding source-related traits, the Ghasem hybrid was significantly higher than the other two hybrids, while Azargol hybrid had significantly lower dry leaf weight. Thus, in terms of source strength, Azargol hybrid had the lowest value among the three hybrids. The dry weight of receptacle base and upper stem nodes in Azargol hybrid were equivalent to Farokh hybrid and significantly higher than Ghasem hybrid. Additionally, there was no significant difference in the number of achenes per head between Azargol and Farokh hybrids. However, 1000 seed weight and seed yield for Azargol hybrid were significantly higher than for Farokh hybrid. The amount of non-structural carbohydrates stored in the receptacle base and five uppermost stem nodes in Azargol hybrid was significantly higher than in the other two hybrids, while the contribution of remobilization from receptacle base and the five uppermost stem nodes to seeds as well as current photosynthesis contribution to yield formation was statistically equal among all three hybrids. Invertase gene expression levels eight days after pollination began were significantly higher in Azargol hybrid compared to the other two hybrids. Despite having higher source strength in Ghasem hybrid, the dry weight of the receptacle base and the five uppermost stem nodes were lower than those of the other two hybrids, likely due to some resistance in translocating assimilates from leaves to sink. The equal number of akene and dry matter weights in receptacle base and the five uppermost stem nodes at pollination onset for Azargol and Farokh hybrids alongside a higher 1000 seed weight in Azargol hybrid likely resulted from greater invertase enzyme activity in its receptacle base tissue. This enzyme facilitates sustained phloem sap flow toward the capitulum as a temporary sink, ultimately leading to increased 1000 seed weight. One function of this enzyme is to protect tissues against low temperatures; therefore, special attention to high levels of this enzyme's expression in capitulum tissue could enhance breeding programs in second cropping system of sunflowers. On the other hand, examining physiological components affecting yield formation in hybrids introduced over a 30-year period indicates a focus on early maturity that has led to reduced yields. If performance formation relationships are considered from both physiological and molecular point of view as a roadmap for sunflower breeding, it will be possible to create early-maturing hybrids while maintaining yield. Conclusion: Focusing on molecular physiology aspects of biological processes leads to a shift in breeders' perspectives and increases the efficiency of breeding programs. Considering the activity of enzymes involved in starch and sugar metabolism, such as invertases, can increase yield despite low source strength while enabling tolerance to low temperatures during seed filling.