جستجوی مقالات مرتبط با کلیدواژه "تجزیه کلاستر" در نشریات گروه "زراعت"

Considering the limitation of arable land, the most effective factor in increasing the production of beans is to conduct research in the field of agronomic and breeding in order to increase the yield per unit area. In order to determine the effect of genetic or environmental factors on a trait, different genotypes should be studied in multiple environments. The varying responses of genotypes in different environments, coupled with the interaction effects of genotype in the environment, render the selection of genotypes from one environment to another challenging. Therefore, examining genotypes in diverse environments holds significant importance in determining the appropriate breeding strategy for the release of adapted cultivars to the target environments. Considering the role of genetic diversity in the advancement of breeding programs, the study of morphological and phenological characteristics that determine yield is a suitable method to achieve selection criteria for improving yield and improving and introducing compatible and high-yielding cultivars. Seed yield is a complex trait that is controlled by a large number of genes, and selection based on yield alone is often not successful. For this reason, one of the ways to identify high-yielding genotypes is to study traits that have a significant relationship with seed yield, so that by selecting or removing them, the accumulation of desirable genes in improved cultivars can be done. Considering the climatic conditions of different regions of Iran, this research was conducted in order to investigate the yield and yield components of red beans (Phaseolus vulgaris L.) in 4 major bean growing regions in the country.

14 red bean genotypes along with Yaghout, Ofogh and Dadfar varieties (Controls) were studied in randomized complete block design with three replications in four research stations of Khomein, Broujerd, Shahrekord and Zanjan for 2 crop years (2018-2019). At the time of harvest, each plot was harvested separately and the yield of each plot was weighed after threshing. After collecting data related to yield and its components, combined variance analysis, simple variance analysis related to each location and mean comparisons were performed. Also, correlation analysis and step-by-step regression were used to investigate the relationship between yield and its components.

The results showed that there is a significant statistical difference between the studied locations, years and genotypes in terms of all traits at the probability level of 1%. The significance of genotype × location interaction for all traits made it necessary to analyze the variance separately in each investigated location. The significance of double interactions indicates the relative instability of the traits of different genotypes in different times and places. The highest seed yield was observed at Khomein station in G12, Yaghot and G4 genotypes, Borujerd in G14 and G13 genotypes, Zanjan in Yaghot and G12 genotypes and Shahrekord in G12 and G16 genotypes. Based on the days to maturity the Ofogh variety, G9, G16 and to some extent G4 genotypes, and based on its yield and yield components, the G12 genotype and Yaghuot and Dadfar varieties were introduced as desirable genotypes. Correlation analysis showed that there is a positive but non-significant correlation between seed yield and number of pods per plant, number of seeds per pod and number of seeds per plant. Regression analysis showed that the traits of number of seeds per pod, days to maturity, number of pods per plant and 100 grain weight are included in the regression model as effective traits and among these traits, days to maturity with a negative coefficient and the number of pods per plant with a positive coefficient were more effective in seed yield.

This study showed that according to the yield and its components in red beans, it is better to introduce a specific variety for each region. Based on the number of days to maturity, Ofogh (check) and G9, G16, and to some extent G4 genotypes, and based on its yield and components, genotypes G12 and G5 can be reported as favorable genotypes. Besides the seed yield, the yield components including the number of pods per plant, the number of seeds per plant, and the 100 grain weight also played a role in selecting better lines; therefore, indirect selection through the selection of these traits can be effective in increasing seed yield. Finally, it can be concluded that apart from seed yield, yield components including the number of pods per plant, the number of seeds per plant, and the weight of 100 seeds can also be effective in selecting superior genotypes; therefore, indirect selection through these traits can be effective in increasing grain yield.

Chickpea (Cicer arietinum L.) is a legume grown in cool season areas. It is one of the main sources of protein and energy and plays a major role in improving soil fertility. Peas are divided into two classes, Desi and Kabali. The Desi seed is smaller, wrinkled, and darker while Kabli has a lighter, whiter seed color, larger seed size, and smooth surface. The chickpea yield is 1199 kg per hectare in America, 1261 kg per hectare in India, and 409 kg per hectare in Iran. Until 2005, this plant was called an orphan plant due to the insufficient genetic resources in chickpeas, but the plant was known as a plant with a rich genomic resource after many efforts at national and international levels. Further studies on chickpea genetic diversity are important to improve the yield. Chickpeas have plenty of diversity in different geographical regions, and the genetic pattern and the amount of variation within and between these populations should be known to progress breeding programs and effectively use these germplasm collections. The evaluation of genotypes faces two key challenges. The first is the genotype-environment interaction, and the second is the interaction between the studied traits. This study aimed to investigate the genetic diversity in the Desi chickpea germplasm under autumn cultivation conditions, analyze the relationships of morphological-agronomical traits, and select superior genotypes in terms of all morphological-agronomical traits.

This study was conducted on 416 genotypes, including 335 landrace of Iran, 1 ICARDA genotype, and 78 ICRISAT genotypes, along with two checks named Kaka and Pirouz cultivars in the experimental farm of the Dryland Agricultural Research Institute (Kermanshah). The cultivars were evaluated in terms of morphological-agronomic traits, including the number of days to flowering, the number of main branches, the number of secondary branches, the number of pods per plant, plant height, the end number of days to maturity, seed yield, and 100-seed weight (HSW). The experiment was conducted during 2020-2021 under autumn sowing conditions and as an augmentation based on a randomized complete block design with nine blocks. The variance, heritability, and genetic advance were analyzed with the R software packages (augmentedRCBD).  The R software package (metan) and (GGEBiplotGUI) were used for the biplot analysis of the genotype by trait. Data were grouped using the K-mean algorithm, single method, and Euclidean distance with R software. The R software package (NbClust) was used to calculate the number of appropriate groups resulting from the cluster analysis. Using the R software package (metan) with the selection index (MGIDI), the top genotypes were ranked based on several traits.

The results of the analysis of variance were significant for the number of days to maturity, HSW, and plant height. The highest and the lowest coefficients of variation belonged to the number of secondary branches and days to maturity, respectively. The plant height and HSW traits had high values of heritability and genetic advancement. According to the results of the genotype by trait biplot, genotypes 148, 327, 391, and 277 were in the best conditions in terms of HSW, days to maturity, plant height, and days to flowering. Genotypes 6, 400, 18, 42, 26, 168, 15, and 2 were in the best conditions for the number of pods per plant, seed yield, the number of main branches, and the number of secondary branches per plant. According to the findings of the genotype by trait biplot, most of the selected genotypes were from the landrace of the Iranian chickpea. Clustering was performed using the K-means method, which divided the genotypes into two groups. In the second group, genotypes 6, 18, 148, 327, and 91 had more distances (according to the center of the group) than the other genotypes. Then, 62 genotypes were ranked as the best genotypes in terms of all traits using the MGIDI index.

The high genetic diversity of the traits studied in this research indicates the possibility of selection among the genotypes. Plant height and HSW traits have high heritability and genetic advance values, indicating the additive effects of the gene. In studies of the Desi chickpea populations, the breeding method of selection can be used to improve these traits. According to the biplot results, the number of pods per plant had important effects on seed yield in autumn sowing conditions, and it is important in terms of selecting genotypes related to the desired traits. On the other hand, the weight of HSW had a high correlation with the plant height in the Desi chickpea, which is very important in the mechanical harvesting of chickpeas. The superior genotypes selected in this research can be used as parents in future breeding programs of the Desi chickpea under autumn cultivation conditions.

Salinity is one of the major abiotic stresses and the most limiting factor in agricultural production worldwide, affecting the growth, development, and final yields of crops. Rapeseed is one of the most important sources of oilseeds in the world, and its seeds contain more than 40% of oil. Moreover, the meal obtained from oil extraction has more than 35% protein, hence it currently ranks third among oil crops in the world after soybean and oil palm, making it necessary to identify the genotypes that tolerate salinity stress. The development and improvement of rapeseed cultivars with salinity tolerance and acclimation offer promising prospects for improving sustainable production in this area. Therefore, the current study aimed to investigate the responses of rapeseed genotypes to salinity stress through analyses of agronomic and biochemical traits.

The genetic diversity between rapeseed lines in terms of agronomic, morphological, and physiological traits in saline soils was investigated in an experiment based on a randomized complete block design with 17 autumn rapeseed genotypes with three replicates in the research farm of East-Azarbaijan Agricultural and Natural Resources Research and Education Center. The measured traits were plant height, the number of fertile pods, number of seeds per pod, pod length, pod area, plant growth rate, 1000-seed weight (TSW), seed yield, oil content, and oil yield. The relationships between yield, yield components, and morphological traits were explored using the analysis of variance (ANOVA), comparison of averages, correlation analysis, cluster analysis, and biplot to understand the relative importance of traits affecting the yield of the studied genotypes.

The studied genotypes were significantly different from each other in pod length, pod area, number of fertile pods, number of seeds per pod, plant growth rate, seed oil percentage, plant height, TSW, grain yield, and oil yield. However, there were no significant differences between the studied genotypes in terms of harvest index and number of actual pods to potential pods. According to the mean comparisons, genotypes 5, 11, and 15 can be introduced as salinity-tolerant lines, and genotypes 2, 4, 6, 9, and 12 can be considered salinity-sensitive lines. According to the other traits, genotype 11 produced a high pod length, number of fertile pods, oil percentage, and oil yield, genotype 5 had a high growth rate and oil percentage, and genotype 15 presented a high height and number of fertile pods. According to the cluster analysis, the second and third groups contained tolerant and susceptible genotypes, respectively. The genotypes in the second group had the highest percentage of positive deviation from the overall mean for grain yield, plant height, harvest index, seed oil percentage, pod length, pod area, and number of fertile pods. Based on the biplot analysis, Karaj 8 and 14 genotypes had a strong relationship with the number of  fertile pods, number of seeds per pod, pod length, pod area, and plant growth rate. Based on the obtained results, the plant height, TSW, seed yield, and oil content traits were closely correlated with Karaj 5, 7, 11, 10, and 15 genotypes. Based on the results of correlation analysis, the correlation coefficient of seed yield was positive and significant for three traits, i.e., plant height, oil percentage, and number of fertile pods, and the highest correlation coefficient (r = 0.879) was obtained for seed yield with seed oil percentage. Positive and significant correlations were measured for the number of seeds in pods with pod length (r = 0.699), pod area (r = 0.555), number of fertile pods (r = 0.678), and number of actual pods. Therefore, genotypes characterized by longer and more abundant pods play a crucial role in improving seed quantity, a key component of grain yield in saline environments. Consequently, the size and number of pods per plant serve as indicators of high-yield potential under such conditions. Based on the results of the principal component analysis (PCA), the first and second components had the highest relative variances, accounting for 44.66% and 31.22% of the total variance, respectively. Together, these two components accounted for 75.88% of the total variance. Factor loadings showed that traits such as number of fertile pods, seed yield, oil yield, and seed oil content had the highest factor loadings in the first component. Similarly, the plant growth rate had the highest factor load in the second component among all the studied traits. Cluster analysis divided the genotypes into four groups, and its dendrogram showed that all the studied genotypes were divided into four separate groups based on all the measured traits. The first group comprised three Karaj 1, 13, and 16 genotypes, the fourth group (like the first group) contained three Karaj 5, 11, and 15 genotypes, and the third group had five genotypes, namely Karaj 3, 7, 8, 10, and 14. The remaining genotypes were assigned to the second group.

The results of the present study demonstrate acceptable genetic diversity among rapeseed genotypes in terms of the evaluated traits in saline lands. This shows the importance and the possibility of using these genetic resources to achieve promising and superior genotypes in breeding programs.

Tomato (Solanum lycopersicum) is one of the most important economic and widely used crops in horticulture. It is a self-fertilizing and diploid plant and has 24 pairs of chromosomes (2n=2x=24). The life cycle of this plant is one year, and it is cultivated in greenhouses and fields. There are many varieties of tomatoes that differ from each other in terms of plant growth, quality, fruit shape, and other traits. Tomato fruit has a high nutritional value, consisting of minerals, vitamins, fibers, citric acid, β-Carotene and ascorbic acid. Diversity and selection are the two main pillars of any reformation program, and choosing is based on the existence of desirable diversity in the reformation materials under discussion. To produce varieties of tomatoes with high productivity, quality and resistance, breeders need evaluation of genetic diversity, identification and introduction of new genotypes. In other words, systematic study and evaluation of germplasm is of great importance for current and future agronomic and genetic improvement of the crop. Different methods are used to estimate genetic diversity and group genotypes, and the evaluation of morphological and physiological characteristics can be considered as the first step in the investigation of genetic diversity. Different genotypes of tomato differ in terms of morphological and physiological traits, and fruit yield is influenced by some of these traits. Therefore, the selection of criteria other than fruit yield, which have more stability than fruit yield, can be considered as a selection guide in the selection of desirable cultivars. Accordingly, this study was conducted with the aim of investigating the genetic diversity and grouping of tomato genotypes (53 genotypes) based on morphological and physiological traits.

In the present study, 53 genotypes of tomato plants were investigated using a randomized complete block design with three replications under greenhouse conditions at the Gorgan University of Agricultural Sciences and Natural Resources. After disinfecting and planting the seeds in the pot, sampling of the seedlings was performed. Morphological traits such as plant height, stem diameter, fresh and dry weight of the plant, number of side branches, number of leaves, root length, fresh and dry weight of the organ air, fresh and dry weight of roots, fruit number, fruit yield, and physiological traits including proline content, photosynthetic pigments (including chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid), and total phenolic and flavonoid compounds were measured. Furthermore, the obtained data were subjected to variance analysis, mean comparison, correlation coefficient, factor analysis, and cluster analysis using suitable software.

After analyzing the data, the results of the evaluation of variance showed that the difference of the studied genotypes in terms of all traits except proline trait was significant at the probability level of 1%. Estimation of the correlation coefficients between the studied traits showed a significant correlation between most of the studied traits and fruit yield. Further, the results of the investigation into factors showed that 6 factors explained more than 77% of the total variance, so that the contribution of the first to sixth factors was 24, 18, 14, 9, 7, and 6% of the total changes, respectively. For better interpretation, larger factor coefficients for each factor were considered significant. Because the largest factor coefficients among the coefficients of each factor indicate the attribute or attribute that plays the greatest role in those factors, the factors were named accordingly. In this way, the first factor was named the fruit yield factor, the second the photosynthesis factor, the third the phenolic factor, the fourth the root weight factor, the fifth the proline factor, and the sixth the stem diameter factor. Based on the results of the cluster analysis, it was observed that the genotypes were significantly different in terms of the measured morphological and physiological traits and they were placed in 3 different groups, each of which had 30, 19, and 4 genotypes, respectively, and the genotypes in the group Third, in terms of studied traits, they were better to other groups.

In general, based on the analysis, the genotypes were significantly different in terms of the measured traits. This article shows that there is a suitable diversity among the studied genotypes and it is possible to select based on these characteristics among the studied genotypes and the selection can be effective in their improvement programs. By estimating the phenotypic correlation coefficients, it was found that the fruit yield trait had the most positive and significant correlation with the number of fruits and the amount of photosynthetic pigments. Therefore, these traits can be considered in tomato fruit yield genetic improvement programs. Considering that the average of most of the traits studied for the genotypes belonging to the third cluster (13, 15, 45 and 46) was higher than the total average and the said genotypes were excellent in terms of developmental and physiological parameters compared with other genotypes, the top genotypes identified in this research can be considered and used in future breeding studies in this valuable plant.

Considering the increasing population growth worldwide, including in Iran, increasing the yield and improving the traits and characteristics of landrace and improved rice varieties are among the most important rice research programs. Crossbreeding between local and improved cultivars is a primary strategy employed by breeders to achieve these goals. This study was conducted to evaluate the performance of different breeding lines that are the result of backcrossing in the previous years. An experiment was conducted with 36 rice genotypes derived from direct and backcrossing of landrace and improved cultivars, along with four selected control cultivars (Anam, Hashemi, Demsiah, and Hasansarai). The experiment was designed as a randomized complete block with three replications at the Rice Research Institute of Iran in Rasht during the 2022 cropping year. Sixteen morphological, phenological, and yield-related traits were evaluated. Data were recorded, and analysis of variance, mean comparison, and cluster analysis were performed after ensuring the assumptions of variance analysis tests were met. The analysis of variance revealed significant differences among the genotypes for all studied traits, except for the number of spikelets per panicle at the 1% probability level. These differences indicate substantial genetic diversity within the studied collection, necessitating selection within the collection. Based on the mean comparison results, Genotype BC3F4-38-13-1 (line 36) demonstrated a significant yield advantage, averaging 6689 kg/ha compared to the landrace control cultivars. In terms of desirable traits such as short plant stature and early ripening, Genotype BC3F4-15-11-4 (line 23) had the shortest plant height, averaging 84.46 cm. Genotypes BC2F4-37-2 (line 30) and BC2F4-37-3-1 (line 31) exhibited early ripening, with average maturation periods of 102 and 101 days, respectively, significantly earlier than the local control variety Demsiah, which had the longest maturation period of 130 days. According to the cluster analysis results of the third group(includes 19 lines), this group exhibited the highest averages for key traits such as the number of filled grains per panicle, panicle length, Number of total grains, panicle fertility percentage, and grain yield. Additionally, they had the lowest number of unfilled grains per panicle. The average yield of this group was calculated to be 13.81% higher than the overall average, with 20.04% fewer unfilled grains. Given the relative superiority of this group in terms of yield and yield components, the best genotypes from this group can be considered in variety introduction experiments as high-yielding new candidate varieties. Based on the results, several breeding lines had significantly higher grain yield than the control varieties. Additionally, these genotypes exhibited short plant stature and early ripening, which are promising traits. These genotypes can be further investigated in trials to introduce them as new candidate varieties.

Grass pea (Lathyrus sativus L.), an annual pulse crop belonging to the family of Fabaceae is under grown for food and feed purposes. Lathyrus genus is a sum of 187 species and subspecies, are cultivated for grain and forage purposes. The world demand for legume proteins is increasing for animal feeding. Grass pea would be a nice alternative for cropping systems in marginal lands and environments. This crop is relatively tolerant to several abiotic stresses; making it a reliable candidate for expansion in the semiarid areas of the world which are predicted to become more drought-prone due to climate change.

This research was carried out in Plant Production and Breeding Department, Faculty of Agriculture, University of Maragheh, Maragheh, East Azerbaijan Province, Iran. The twenty-five grass pea genotypes were provided by ICARDA. In order to evaluate genotypes in terms of salinity tolerance, genotypes were studied at factorial experiments in completely random design with two replications in 2017. Salinity treatments were applied at four levels (0, 40, 80 and 120 mM of NaCl). Different seedlings traits in the laboratory and agronomic trait in pots in the field of were evaluated. The evaluated morphological and physiological traits were root length, stem length, seedling length, root dry weight, shoot to root ratio, shoot to root ratio, height shoots, number of pods, number of seeds, number of branches, number of leaves, fresh weight of fruit, dry weight of fruit, fresh weight of shoots, dry weight of shoots, leaf length, leaf width, branch location, leaf angle, number of rhizobium, depth of rhizobium, length root, flowering date, germination percentage, germination rate, podding and stability under salinity stress. SPSS software applied for analysis.

The genotypes had significant differences in most of the studied traits. With increasing salinity levels plant height, shoot weight, number of branches, shoot dry weight, leaf width, leaf number, first branch location and seedling time, root length, length of shoots, seedling length, root dry weight and stem dry weight were decreased. The cluster analysis of high-yielding genotypes based on the standardized mean with Euclidean distance and Ward algorithm divided the studied genotypes into three clusters. The first cluster included genotypes 19 and 20. The genotypes 24, 25, 8, 16, 10, 2, and 5 were located into the second cluster, and finally, the third cluster included genotypes 3, 6, 1, 7, 23, 15, 4, 22, 18, 14, 13, 12, 11, 21, 9 and 17. Principal component analysis (PCA) reduced the traits in three main components with 70.25 % of variation, which according to the results the first component was named the grain yield component and the second component as the number of leaves. These components can be used in breeding programs for the selection of genotypes and breeding goals in resistance to salt stress.

With the increase in salinity levels, the yield significantly decreased compared to the control. Genotypes 21 and 18 had the highest and lowest germination rates, respectively, and genotypes 8 and 15 had the highest and lowest germination percentages, respectively. In terms of the durability of genotypes to salinity, genotypes 8, 9, 10, 12, 13, 14, 23, and 24 were the best genotypes and the most sensitive genotypes to salinity with low performance were genotypes 19 and 20. Genotypes 5, 14, 10, 16, 21, 24 and 25 (control) had the highest yield.

Bread wheat is the first grain and the most important annual crop in the world. Like other crops, wheat faces many environmental constraints such as a lack of trace elements during its growth period. Zinc deficiency is a common micronutrient disorder in wheat-growing areas of the world. The growing degree-days (GDD) index is reliable compared to the time calendar due to its stability. These indices are important for comparing genotypes whose physiological developmental stages do not match. Temperature is an important meteorological variable in the study of plant growth and development processes and therefore its study on short time scales leads to a more accurate estimate of thermal need due to the relatively wide range of temperature changes in different phenological stages, setting the planting date. Studying the effect of temperature on wheat genotypes should be based on sufficient time and temperature to complete the phenological stages in which grain yield components are formed.

To study the phenological stages, cumulative growing degree-days, and grain yield and its components in 64 spring wheat cultivars under optimal and zinc deficiency conditions, a study was conducted in the 2019-2020 cropping season based on a simple lattice design in the research field of Urmia University, Iran. Phenological stages include the number of days to germination, the number of days to booting, the number of days to pollination, the number of days to physiological maturity, and the grain filling period with their GDDs during the growing season in each pot based on 50% of the samples were determined to have reached the relevant vegetative stage. In addition to phenological stages along with the number of grains per spike, thousand-grain weight, and grain yield were examined.

Analysis of variance revealed that there is a statistically significant difference among all cultivars in terms of all studied traits except the number of days to pollination under optimal and zinc deficiency conditions. According to the results of descriptive statistics, grain yield, the number of grains per spike, and thousand-grain weight decreased and phenological traits increased under zinc deficiency conditions compared to optimal conditions. Among phenological traits, not only the number of days to spike showed relatively high variability but also had a significant relationship with grain yield under zinc deficiency based on the results of correlation and regression analyses. The factor analysis showed that under optimal conditions, the first four components explained 87.81 percent of the total variation, so that the contribution of the first to fourth components were 38.38, 21.52, 15.88, and 12.3 percent. Under zinc deficiency stress conditions, the first five components explained 95.68 percent of the total variation, so that the first to fifth components explained 34.62, 18.48, 17.51, 14.66, and 10.40 percent, respectively. Cluster analysis classified all spring wheat cultivars into three and four clusters under optimal and zinc deficiency stress conditions.

Based on the results of cluster analysis under optimal and zinc deficiency stress conditions, Neishabour, Golestan, and Gahar cultivars were identified as desirable and tolerant cultivars that can be used in future breeding programs. The results of cluster analysis were confirmed by results of canonical discriminant function results

This research was done to study the grain yield stability of 11 groundnut genotypes based on a randomized complete blocks design with three replications at three different research stations in Guilan province, Iran, during two growing seasons of 2020 and 2021. The combined analysis of variance indicated that the main effects of genotype (G), environment (E), and their interactions (G×E) were highly significant (p<0.01). The principal component analysis (PCA) based on the rank correlation matrix indicated that the first two PCAs explained 76.6% of the variance of the original variables. Based on the biplot analysis, the non-parametric stability statistics were classified into four groups. The clustering of the genotypes according to the mean yield and non-parametric stability statistics showed four main clusters. The ideal genotype selection indicator (IGSI) results, calculated based on all non-parametric methods, indicated that the genotypes 178, 128, 201, 176, and 115 having the maximum IGSI values, were the most stable genotypes. In addition, according to the multi-trait genotype-ideotype index (MGIDI), genotypes 178 and 176 were introduced as the most stable genotypes, and the 115, 201, and 128 genotypes followed the next.

Lentils are one of the most important crop plants in rotation.Lentil seed yield is strongly influenced by environments and breeders often determine the stability of high yield genotypes across environments before recommending a stable cultivar for release. Genotypial adaptability to environmental fluctuations is important for the stabilization of crop production over regions and years.Identification of high- yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. The challenge of the interaction of genotype × environment is one of the main issues in plant breeding. Various statistical methods to estimate the interaction of genotype × environment and choice the stable and productive genotype(s) have been introduced. One of the applications of Non-Parametric methods is determination of genotypes rank in different environments, which is also used as a measuring stability. A stable genotype shows similar ranks across different environments and has minimum rank variance in different environments. Non-Parametric Stability Statistics require no statistical assumptions about the distribution of the phenotypic values and are easy to use.

This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with 3 replications.

The combined analysis of variance indicated that the main effects of genotype (G), environment (E) and their interactions genotype and environmen (G×E) were highly significant (p < . ). The principal component analysis (PCA) based on rank correlation matrix indicated that the first two PCAs explained . of the variance of original variables. Based on bi-plot analysis, the stability parameters were classified into four groups. Clustering of the genotypes according to the mean yield and nonparametric stability statistics showed that there were two main clusters. Overall, according to mean rank of nonparametric stability parameters, G17 , G3 , G9 and G2 had the lowest variations and were recognized as the most stable genotypes. Genotypes G7 , G11 and G13 had the highest values of mean rank of parameters and therefore, would be considered to be the most unstable. According to the present study, the stability measures Ysi, and TOP were associated with mean yield (MY) and the dynamic concept of stability. Therefore, these procedures were suitable for selecting stable and high yielding genotypes

Therefore, these procedures were suitable for selecting stable and high yielding genotypes. Based on these parameters, genotypes G13 (340 t/ha) and G11 (305 t/ha) were identified as high yield stable genotypes.

Despite the importance of the eggplant, few breeding studies have been conducted in relation to this plant in Iran. Therefore, it requires more studies, especially in relation to the study of new lines and native genotypes of the country. The aim of this study was to character association and identification of direct and indirect effects of quantitative traits on yield in 40 eggplant lines at F4 segregating population.

This experiment was performed in the research farm of Sari University of Agricultural Sciences and Natural Resources in the 2021 cropping season. In this study, 40 breeding lines in F 4 generation along with their parents were used. Traits studied in this study included plant height (centimeter), number of fruits per plant, fruit length (centimeter), fruit weight (gram), fruit diameter (millimeter) and fruit yield (gram / plant). In order to analyze the data, descriptive statistics, correlation, path analysis and cluster analysis were used.

The results of correlation showed that fruit yield had positive and significant relationship with fruit weight. Results obtained from path analysis indicated that fruit weight and after that fruit number in plant had greatest direct effect on fruit yield in eggplant. The greatest indirect effect of fruit weight is through the diameter of the fruit. These traits could be used as selection index for yield improvement in eggplant breeding programs. According to cluster analysis studied lines were grouped in three different clusters based on studied traits.

Cluster analysis showed the existence of favorable diversity between the studied genotypes and grouped the studied lines in three different groups. Fruit weight and fruit number had greatest direct effect on fruit yield in eggplant. These traits could be used as selection criteria for yield improvement in segregating population of eggplant.

Maize is one of the most important cereals that is cultivated in many parts of the world and it is one of the most important cereals for the production of food for people all over the world. The most common environmental stress is drought, which limits the growth and survival of plants in arid and semi-arid areas. The selection of tolerant genotypes to drought can help to improve the performance of maize hybrids under these conditions.

In this research, to investigate the tolerance of maize hybrids to drought stress, 18 maize hybrids were evaluated in an experiment in the form of the split-plot design based on a randomized complete block design with three replications. In the control conditions, irrigation was done after 70 mm and under drought stress conditions, after 120 mm of evaporation from the class A pan. Based on the grain yield under water-deficit stress and normal conditions, the indices including the stress tolerance index (STI), stress susceptibility index (SSI), tolerance (TOL), mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HARM), reconnaissance drought Index (RDI), drought resistance index (DI), yield stability index (YSI) and selection index of ideal genotype (SIIG) were calculated for the studied hybrids and the most tolerant and sensitive hybrids were identified. Also, the grouping of hybrids was done based on cluster analysis and principal component analysis.

In this research, yield under normal and water-deficit stress conditions had a low correlation with the TOL index, a negative and significant correlation with SSI, and a positive and significant correlation with MP, GMP, STI, HARM, YSI, RDI, DI and SIIG and therefore, hybrids with higher values for these indices had higher yield in the water-deficit stress and normal conditions. Thus, MP, GMP, STI, HARM, YSI, RDI, DI, and SIIG were suitable indices for identifying hybrids with higher yield in both conditions due to their higher correlation with the grain yield in water-deficit stress and non-stress environments.

In normal conditions, SC704, has the highest (18.57 tons/ha) and SC703 (11.81 tons/ha), SC702 (11.76 tons/ha), SC720 (12.66 tons/ha), SC701 (11.77 ton/ha), K19/2×K3651 (11.09) and AR66 (11.43 tons/ha) had the lowest yield. Also, under water stress conditions, SC704 had the highest (15.9 tons/ha) and AR66 had the lowest (6.16 tons/ha) yield. Based on the results of the studied indices, SC500 and SC704 were identified as water deficit tolerant hybrids and SC670 and AR66 were also identified as sensitive hybrids to water deficit stress. The results of cluster analysis and principal component analysis and biplot diagram also confirmed this issue.

In order to identify cold tolerant cultivars of rapeseed (Brassica napus L.) using stress tolerance indices under the influence of humic acid application, an experiment was conducted as factorial split plot based on randomized complete block design with three replications in 2017 and 2018 at Seed and Plant Improvement Research Institute, Karaj, Iran. Factorial combination of cold stress as planting date factor in two levels including 20 October and 20 November, and humic acid factor in two levels including non-application (foliar spraying with pure water) and application (foliar spraying with a concentration of 1.5 per mil at 4-6-leaf stage) were assigned to the main plots and the cultivars were allocated to the sup-plots. The results showed that rapeseed cultivars differed significantly. Based on the results of means comparison, the cultivar WRL-95-07 showed higher yield in both stress and non-stress environments as well as the application and non-application of humic acid than the other cultivars. The correlation of drought tolerance indices with grain yield under stress and non-stress conditions was used to determine the most suitable indices. Arithmetic mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HARM) and stress tolerance index (STI) had the highest significant correlation with yield under normal and stress conditions. Principal component analysis differentiated indices introducing tolerant cultivars and indices introducing susceptible cultivars, and on this basis, the 10 rapeseed cultivars were divided into three groups using cluster analysis. Finally, WRL-95-07 cultivar performed well under stress and non-stress conditions with the use of humic acid, followed by WRL-95-12 cultivar which displayed better performance than the other cultivars under stress conditions when treated with humic acid.

Knowledge of the amount of genetic diversity in germplasms provides plant breeders with valuable information for the effective preservation of genetic resources and their use. More knowledge about genetic diversity and genetic factors of diversity is very beneficial for exploring new genes. Maintaining such diversity and using it in breeding programs is one of the main principles of biological conservation and genetic breeding of crop plants.

This research was conducted to evaluate the genetic diversity in 20 different durum wheat genotypes, including landraces, improved cultivars, and breeding lines using RAPD and ISSR molecular markers. In this research, 31 RAPD primers and 13 ISSR primers were used to evaluate the genetic diversity in durum wheat genotypes.

Based on the results, the studied genotypes had significant diversity based on both molecular markers. In RAPD analysis, 31 primers amplified 319 bands, of which 204 bands were polymorphic and the percentage of polymorphic bands was estimated at 63.94%. In ISSR markers, 13 primers produced 125 bands, of which 88 bands were polymorphic and the total percentage of polymorphic bands was estimated at 70.4%. Genetic similarity and cluster analysis of RAPD and ISSR were estimated using the Jaccard coefficient. For RAPD, the similarity index values ​​ranged from 0.22 to 0.90, and for ISSR from 0.22 to 0.94, which indicated the presence of high genetic diversity at the molecular level for the studied genotypes. The results of cluster analysis and principal coordinate analysis based on each of the RAPD and ISSR markers grouped genotypes into four groups. The results of the research showed that RAPD and ISSR markers are suitable markers for genetic diversity studies in durum wheat. But the ISSR marker is preferable due to its greater compatibility with the geographical origin, high reproducibility, and the similar cost as RAPD. The results showed that the grouping patterns of durum wheat genotypes are not mainly due to their geographical origins. The results indicated that the grouping of populations in different geographical regions in similar groups is probably due to the gene flow between regions through the gradual exchange of grains between farmers. This could also be due to the previous selection for sum agronomical traits in the populations for tolerance to environmental stresses.

Based on both markers, genotype # 20 (Stj3//Bcr/lks4) showed a different response from the other genotypes, so it was placed in a separate group in the analysis based on each of the markers. Therefore, this genotype can be used as one of the parents in crossing with other genotypes in subsequent studies.

 Foxtail millet, as a multi-purpose crop, enjoys nutritious and remedial properties. This research was aimed at identifying diversity and the investigated based on 14 agronomic traits in a wide range of foxtail millet germplasms (134 genotypes).

 In this research a total of 134 seeds of foxtail millet genotypes corresponding to a wide range of foxtail millet germplasms were procured by Research and Technology Institute of Plant Production (RTIPP) affiliated to the Shahid Bahonar University of Kerman. This experiment was designed as a randomized complete block with three replications under normal condition in 2017. Agronomic traits include: seed germination percentage, plant height, number of leaves per plant, flag leaf length, flag leaf width, number of tillers, panicle length, seed yield, number of plants per line, forage yield, seed weight of superior plant, 1000-seed weight , Harvest index and biological yield were measured  and the data were then analyzed.

 Analysis of variance (ANOVA) indicated that the differences between the studied genotypes were significant for all traits except for flag leaf width and the number of plants on the line was significant. According to the phenotypic correlation coefficients, the seed and forage yields had positive and significant correlations with all investigated traits except for the flag leaf width.
Also, the seed yield had the highest correlations with forage and biological yields (0.97 and 0.94, respectively). Then, principal components analysis showed that the first four main principal components could justify explained more than 75.62% of the total variance of the traits, and the first to fourth components explained 49.89, 9.87, 8.32, and 7.54% of the total variance, respectively. Based on the cluster analysis, all genotypes were categorized into four groups. Compared to other groups, the first group of genotypes had superior seed and forage yields.

 In general, genotypes had significant differences in terms of the investigated traits. These results indicated the presence of a wide range of diversity in the investigated germplasm of foxtail millet. Besides, the common genotypes held in the first group (G160, G68, G15, G23, G72, G73, G39, G170, G57, G122) had significant superiority in terms of seed and forage yields under condition.Therefore, they can be considered and used for future studies of plant breeding as superior genotypes in breeding and selection programs in order to increase the forage and grain yield of fox tail millet.

Salinity stress is one of most important factors limiting the growth and production of plants in arid and semi-arid regions of the world such as Iran.

In order to evaluate the response of some bitter vetch (Vicia ervilia L.) ecotypes to salinity stress at germination stage an experiment was conducted as a factorial experiment in a completely randomized design with three replications in the laboratories of Faculty of Agriculture at Vali-e-Asr University of Rafsanjan in 2019. Eight bitter vetch ecotypes were evaluated at four salinity levels (30, 50, 70 and 90 mM of NaCl). Shoot length, root length, shoot fresh weight, root fresh weight, shoot dry weight, root dry weight, germination percentage, germination rate and seed vigor index were measured.

The results of variance analysis showed significant effects of salinity and ecotype on the most evaluated traits. According to the results of mean comparison of the studied traits, with increasing salinity from the 30 mM to 50, 70 and 90 mM, all traits showed significant decrease. Principle components analysis based on the evaluated traits for salinity stress showed 76.7, 82.5, 88.6 and 89.5 percentages of the changes by the first and second components, respectively, at the 30, 50, 70 and 90 mM NaCl. Cluster analysis based on the measured traits at 30, 50, 70 and 90 mM levels classified the studied ecotypes in separate groups.

Regarding to byplot and cluster analysis, Dashbolagh ecotype in terms of tolerance to stress in different levels of salinity were superior to other ecotypes in this experiment and could be used in breeding programs.

Yield of hybrid cultivars is 20 to 30% higher than conventional cultivars. On the other hand, the most important challenge for hybrid breeders, especially in Iran, is the selection of parental genotypes that have fertility restorer genes and ultimately lead to heterosis.

The present study was performed by evaluating the morphological traits of 19 rice genotypes and the linked of three SSR molecular primers related to Rf3 and Rf4 genes. These genotypes were planted in 2019 in the research farm of Genetics and Agricultural Biotechnology Institute of Tabarestan in a randomized complete block design with three replications. Quantitative and agronomic traits, especially paddy yield, were evaluated. DNA extraction was performed by CTAP method with modification from leaf samples. Three SSR markers linked with two major RF3 genes including RM490 and RM 3148 markers and RF4 gene linked with RM171 marker were used to identify fertility restorer genes in rice.

The results of comparing the mean of rice genotypes showed that P15-6 genotype with 118.33 was the earliest and all foreign genotypes with a maturity of 150 days were the latest. The highest yield of genotypes (above 700 g / m2) is related to Neda genotypes, IR 86403-5-5-2-1-1-1-1-1-1R, P15-6, P12-5-3-3-2- 2-1, P12-5-3-3-2-1-1 and P8-7-2-1-4-2-1-1, which due to the number of fertile tiller, the number of fertile panicle, 1000-seed weight and panicle fertility has been high. In the results of cluster analysis, parental cultivars were divided into three groups: in the first group (medium yield, long cluster length, high number of full seeds, and long grain length) the Jelodar cultivar, in the second group (maximum cluster fertility, 1000-seed weight and high paddy yield) Neda cultivar along with four other lines and all foreign cultivars are in the third group (late, short grain length and high grain density). Principal component analysis divided the studied traits into four main components with eigenvalues ​​above one, which in total explained 82.61% of the data changes, which these four components are more valuable and express the relationship between the traits. In total, the band pattern of three markers showed that IR 68078-15-2-1-2-2-R, IR65622-151-1-2-2-2-R and NSIC RC434 genotypes had fertility restorer genes.

Summary of all 3 SSR markers showed that genotypes P9-7-1-1-1, P11-6-2-1-1-1, P14-1 and P15-2 with two markers RM3148, RM490, have Rf3 gene and haven’t Rf4 genes and the reason that some genotypes have been identified as Rf gene with RM3148 marker but not detected with RM490 marker may be due to crossover between the desired gene and marker, so genotypes with fertility restorer gene are fertility restorer lines and can be used in hybrid rice program.

Chickpea is one of the most important legumes in Iran and accounts for almost 84% of dietary legumes. Chickpea seed yield is strongly influenced by environments, and breeders often determine the stability of high-yielding genotypes across different environments before being introduced as a cultivar. Accurate study of the nature of genotype × environment allows breeders to identify stable and compatible genotypes and has always been one of the important issues in the production and release of new stable and high-yielding cultivars in breeding programs. . Adaptation of chickpea genotypes to environmental conditions is important for crop production stability in different years and places. Existence of the interaction of genotype and environment affects the value of genotypes in different places. The present study was conducted to investigate the effect of genotype by environment interaction on grain yield of chickpea genotypes and cultivars in four environments and to identify stable and high-yielding genotypes under rainfed conditions as autumn planting.

In this study, twelve cultivars and advanced genotype of chickpea were planted during two cropping years (2016-2018) in a randomized complete block design with three replications in semi-warm (Kuhdasht) and temperate (Khorramabad) areas of Lorestan province. Various nonparametric methods such as non-parametric statistics of Si (1), Si (2), Si (3) and Si (6), Thennarasus statistics of NPi (1), NPi (2), NPi (3) and NPi (4), mean rank stability statistics (R), stability statistics of Ketata et al (σr, σmy), Kang stability statistics (Ysi), Fox stability statistics (TOP, MID and LOW) and Genotype Stability Index (GSI) were used for estimating the stability of genotypes. the principal component analysis method was used to better understand the relationships between different statistics..

The results of combined analysis of variance showed that the main effects of environment (including location, year and location ×year) and genotype ×environment were significant at the 1% probability level and the main effects of genotype, location × genotype and year × genotype were significant at the 5% probability level. The effects of genotype, environment and the genotype by environment interaction accounted for 6.48, 77.4 and 13.03% of the total squares, respectively.The biplot of the first principal component (PC1) versus the second principal component (PC2) classified the studied nonparametric stability statistics into three groups.Based on the statistics of NPi (1), NPi (2), NPi (3) and NPi (4), the genotypes with the lowest values are considered as stable genotypes. According to NPi (1) statistics, G1, G6 and G9 genotypes were identified as the most stable and G3 and G5 genotypes as the most unstable genotypes. Based on NPi (2) and NPi (4) parameters, G1, G10 and G9 genotypes were the most stable and G5, G12 and G4 genotypes were the most unstable. Based on the results, the first two principal components explained 68% (42% and 26%, respectively), of the variance of the main variables). Cluster analysis using mean seed yield and non-parametric statistics, placed chickpea genotypes in two main groups. The first cluster included mean seed yield, TOP, MID, σr and σmy. The second cluster consisted of four sub-clusters .

Based on Si (1), Si (2), Si (3) and Si (6) statistics, G1, G10 and G9 genotypes with the lowest values were identified as the most stable genotypes. G1 and G9 genotypes with the lowest GSI were recognized as the best genotypes in terms of grain yield and stability. Based on the parameters with the dynamics concept of stability, genotypes G1, G10 and G9 were identified as stable genotypes with high yield.

Every year new cultivars of Chrysanthemums modified with a high economic value. In order to study the genetic variation of some chrysanthemum cultivars using morphological markers, 17 quantitative trait were evaluated 20 varieties of chrysanthemums accordance with standard methods. The results of the data analysis for morphological traits showed that studied cultivars in most traits were significant differences in the level of one percent. The average comparison showed that "Elika" cultivar had a highest plant high, "Ramtin" cultivar had a highest number of flowers and "Gol-Giss" cultivar had a highest flower head diameter. Principal component analysis showed five main factors that had Eigen values greater than one, could be 77/10% of the total variation. Cluster analysis to determine how far and near these were drawn that into two main groups were divided, the "Farid", "Nadia 2" and "bolur" and "Ramtin" highest genetic similarity in the first group and also the "Fariba 2" and " kimia 3" in the second group had the highest genetic similarity. The results of this study showed that the number of lateral branches, number of flowers and leaves during the length of the petiole highest diversity was observed. The results showed that cultivars diversity of these figures are very high and can be used in programs of breeding chrysanthemums in the future.