فهرست مطالب reza sekhavat

Mung bean is a suitable plant to enrich the agricultural systems diversity and to benefit from positive ecological effects. A total 47 mung bean lines along with control genotypes (Parto cultivar and 6173 line) were planted in Latis square design (7 × 7) in two replications at three different environments conditions . The most important agronomic traits including grain yield, pods and racemes number per plant and pod length were evaluated and different lines compared to each others. The results indicated existence of diversity in the under-studied lines and emphasized that it would be possible to perform selection the appropriate one for utilization in the future breeding programs. Inconsistent performance of lines across three different environments necessitate that appropriate line selection was done in each environment separately. Generally based on lines performance at three different environments, lines number 24, 25 and 41 from pod length point of view, lines number 23 and 42 from pod number per plant, lines number 43 from grain number per pod and lines number 5, 11 and 42 from raceme number per plant point of view ranked as appropriate lines at all three environments, The high genetic diversity in these lines make possible the introduction of new cultivars and the expanding the cultivated area of this plant at different regions with different climate conditions.

Faba bean (Vicia faba L.) is a cool‐season and annual seed legume crop used as an important cheap plant protein source for human food (green or dried, fresh or canned) and livestock feed. It is a very valuable legume crop that contributes to the sustainability of cropping systems with ability of biological nitrogen fixation. The aim of this study was to determine genotype × environment interaction on seed yield and to identify high yielding with yield stability of faba bean genotypes adapted to target environments.

Seed yield and yield stability as well as adaptability of 15 faba bean promising lines were evaluated using randomized complete block design with three replications in four agricultural research field stations of Gorgan, Dezful, Brojerd and Iranshahr in Iran in 2018-19 and 2019-20 cropping seasons. Plant height and branch number.plant-1 in each plot was measured before harvesting. Plots were harvested by hand at harvest maturity stage and seed number.pod-1, number of pod.plant-1, hundred seed weight and seed yield were measured. Data were analyzed using SAS software and the means were compared using LSD test. GGE-Biplot was used to analyse genotype × environment interaction and yield stability of faba bean genotypes.

Combined analysis of variance showed that environment, genotype and genotype × environment interaction (GEI) were significant with contribution 60.07%, 19.8% and 20.07% to the total variation of seed yield, respectively. Yiled stability 15 faba bean genotypes was stdied using GGE biplot method across eight environments. GGE biplot analysis using a genotype × environment interaction (GEI) model explained 76.5% of the total variation. GGE biplot components PC1 and PC2 explained 58.7% and 17.8% of the total variation, respectively. The GGE biplot analysis of the tested environments and genotypes revealed that the eight test environments comprised two mega environments and the adapted genotypes were determined for each mega-environment. In Gorgan, G10, G12, G13 and G3 genotypes were adapted, and in the second mega-environment, G6 genotype was adapted. The genotypes G6, G10, G7 and G9 with average seed yield of 2905, 2715, 2607 and 2552 kg.ha-1 had higher seed yield and yield stability, respectively. Based on GEI and GGE biplot analysis, Gorgan experimental environments had good discrimination ability. The polygon view of biplot indicated genotypes; G1, G3, G4 and G14 were adapted to the tested environments according to the closest distance from biplot origin. The simultaneous study of the effect of genotype and GE interaction by average tester coordinate view of Biplot illustrated that genotypes; G6, G10, G7, G9 and G4, in addition to high seed yield had also higher yield stability compared with other genotypes. Ideal genotype view of Biplot indicated that G6 and G10 were the closest genotypes to the ideal genotype and identified as the most desirable genotypes.

Based on the GGE biplot analyses, the G6 (Barkat × New mammoth) genotype with high seed yield and yield satbilty across all environments. Also G9 (ILB1266), G2 (Barkat × ILB 5284) and G4 (Barkat × Giza Blanka) genotypes had significantly higher seed yield and yield stability compared to control cv. Barakat (G11), G12 (Feyz), G13 (Shadan) and G14 (Mahta).

To investigate stability, pattern of G×E interaction, 10 faba bean genotypes (G1-G10) as well as four control cultivars; Barekat, Saraziri, Baloochi and Zereshki were evaluated using randomized complete block design with three replications in four agricultural research field stations of Gorgan, Dezful, Brojerd, and Iranshahr, for two cropping seasons (2014-15 and 2015-16). The results of composite variance analysis showed that the main effect of year, the interaction of year × location and the triple effect of year × location × genotype on grain yield were significant at the probability level of 1%. GGE -biplot analysis (genotype effect+ genotype×environment interaction) revealed that the two first and second principal explained 84.7% and 6.6% of total variation, respectively, and 91.3% of the grain yield variation. Based on a hypothetical ideal genotype biplot, the genotype G9 was better than the other genotypes across environments for stability and grain yield. View of polygon graph revealed superior mega-environments and the compatible genotypes were determined for each mega-environment; Gorgan- Brojerd (G9) and Iranshahr (G14). G9, G1, and G4 genotypes with average grain yield of 3479, 2808 and 2739 kgha-1, respectively, had the highest grain yield. Based on GEI and GGE-biplot analysis, Gorgan and Brojerd experimental environments had good differentiation ability. Finally, genotypes G1, G5, G9, and G10 were the most stable genotypes and can be used in breeding programs.

Accurate study on the nature of genotype by environment interaction enables the identification of stable and adaptable genotypes for breeders and it has always been an important issue to address by breeders for the production and release of new sustainable and high-yielding varieties in breeding projects. To study the stability of yield and yield components of seven promising lines of mungbean as well as the check (Parto), three experiments were conducted in an RCBD with three replications in three regions of the country, i. e. Khuzestan (Agricultural and Natural Resources Research and Education Center of Safi Abad, Dezful), Golestan (Agricultural Experiment Station of Gonbad) and Fars (Agricultural Research Station of Zarghan) in 2014-2015 for two years. Each plot consisted of four four-meter-long rows. The traits studied were: the number of branches per plant, pods per plant, seeds per pod, 100-seed weight, plant length, and seed yield. A combined analysis of variance was performed. Because of the significant genotype by environment interaction and, as a result, the different responses of genotypes to various environments, stability indices were calculated to determine the stability of genotypes. To do this, Romer's environment variance, Francis and Kannenberg's environmental CV, and the regression coefficient of Finley and Wilkinson were determined. AMMI analysis was also performed. Based on Francis and Kannenberg's environmental CV and coefficient of Finley and Wilkinson genotypes VC6368 (46-40-4) and VC6371-94, and VC6469 and VC3960 were stable, respectively. Based on the CV of intra-location, VC3960-88 and VC6368 (46-40-4) were stable. According to stability analysis results and considering seed yield, seed weight and other suitable characters, genotypes VC6371, VC6368 (46-40-4) and VC3960-88 were selected for further studies.

In order to evaluation the genetic diversity of agronomical traits, determine the relationships between traits and the contribution of each trait in the diversity, a study was conducted on 49 mung bean accession’s in the field of the National Plant Gene Bank of Iran, in the 2019-20 growing season and the most important phenological and agronomical traits were recorded. Based on the results, grain yield, biomass, plant weight, number and weight of grains and pods per plant and number of cluster per plant had the highest coefficient of variation. The results of the factor analysis showed that plant weight, number and weight of grains and pods per plant and number of cluster per plant had the highest coefficients in the first component; Grain yield and harvest index had the highest coefficients in the second component and pod length and 100 grain weights had the highest coefficients in the third component. Cluster analysis using Ward’s method divided accessions into 3 distinct clusters.  Discriminant analysis showed that grain yield, biomass, harvest index and pods number per plant had maximum coefficient in the first function, which has the most effective role (75%) to discriminant clusters. Based on the Wilk’s Lambda values, except grains per pod, pod length and hundred grains weight, other traits had significant effect on dividing accessions into 3 clusters. High GCV, PCV, coupled with medium to high heritability of plant weight, number of grains and pods per plant, pods and grains weight per plant, cluster number per plant, 100 grain weights and harvest index, indicating that selection will be effective for these traits. Path analysis demonstrated the direct effects of biomass, harvest index and pod weight per plant on mung bean grain yield.  These results clearly elucidate that these traits had more diversity among mung bean accessions. The existence of such diversity makes possible the selection of appropriate accessions based on breeder’s desire.

Faba bean (Vicia faba L.) is one of the most important multi-purpose legumes with a wide range of adaptation, high nutritional value, medicinal effect and biological nitrogen fixation. In recent years, the area under Faba bean cultivation has declined due to the spread of diseases and other tensions, increasing production will be possible by introducing cultivars resistant to biological and abiotic stresses.

To access the field resistance of 64 Faba bean genotype to fungal diseases and select suitable genotypes, genotypes were evaluated for disease severity in the field, based on simple lattice design (8 × 8) with two replications in both Gorgan and Dezful research stations in the 2015-2016 cropping season. To calculate the area under the disease progress curve (AUDPC), sampling was done in five steps from the occurrence of leaf spot diseases. Combined analysis of variance and correlation analysis was performed for 10 physiological, morphological, phenological traits and diseases severity. also conducted two graphical multipurpose selection procedures GT biplot in combination with cluster analysis for simultaneous improvement of quantitative traits and disease resistance in two environment. Clustering of genotypes and traits traits separately in each experiment using Ward method and Square Euclidean Distance were performed and the corresponding heatmap was plotted using metaboanalyst 3.0 software.

Based on combined analysis of variance, highly significant differences (P ≤ 0.01) were observed among the faba bean genotypes for agronomic traits and diseases resistance. Number of grains in pod and 100sw indicated positive and significant correlation with yield among of traits. Based on Heatmap graphical mapping assigned the faba bean genotypes into three and four groups in Gorgan and Dezful, respectively. The different groups obtained can be useful for deriving the genotypes with diverse features and diversifying the heterotic pools. The biplot vector view indicates that there was a strong positive association between Number of seed per Pod, 100sw and Plant Height with seed yield in two conditions. Correlation analysis confirmed these results. It seems that Number of seed per Pod, 100sw and Plant Height traits can be used as selection criterion for improving of seed yield in faba bean. Results of the GT biplot in the present study indicated that G52, G56 and G48 genotypes were identified as superior genotypes in Gorgan, and G47, G51 and G56 were identified as superior genotypes in Dezful.

Several genotypes were selected for potential use as parents, The G48 genotype were recognized as superior genotypes regarding yield and traits related to yield and Ascot cultivar can be considered as resistance resource to chocolate spot for faba bean breeding program. G47, G51, G52, G55, G56 and G58 genotypes were chosen for further cultivar release consideration.

To evaluate the yield stability of faba bean genotypes among 19 genotypes, an experiment was conducted in randomized complete block design with three replications in two cropping years (2015-2017) at four areas (Gorgan, Dezful, Boroujerd and Iranshahr). The effect of environment, genotype and genotype by environment interaction were significant on all traits. Nominal yield plot identified genotypes G13, G12, G2, G9, G6 and G4 as more stable genotypes. Based on biplot analysis, genotypes G12, G16, G14, G9, G6 and G11, in addition to having the highest seed yield, had higher yield stability. Based on different values for seed yield and weighted average of absolute scores of best linear unbiased predictions (WAASB), genotypes G11, G9, G18, G10, G13, G12, G16, G14 and G6 were high yielding and stable. The superior genotypes based on multi-trait selection index (MTSI) were G2, G18 and 6. The harmonic mean, and of the relative performance of genotypic values (HMRPGV) introduced G14, G6 and G9 as genotypes that in addition to high seed yield, also had high stability and compatibility. Overall, based on all analyzes and indices, genotype G6 identified as the most stable genotype and could be a candidate to introduce a new cultivar.

Faba bean (Vicia faba L.) is one of the most important legumes for its seed high protein content and nutritional value, and is still considered to have great potential as rainfed crop. Faba bean is a very valuable legume crop that contributes to the sustainability of cropping systems through its ability of biological N2 fixation, diversification of cropping systems leading to decreased disease, pest and weed. The decrease in area under cultivation in Iran, mainly because of high yield instability. This can be attributed to biotic and abiotic stresses Faba bean 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. The purpose of this study is the distinguishing the superior genotypes in terms of yield and yield stability in 15 selected faba bean lines from preliminary yield test.

15 selected lines obtained from crosses between ICARDA lines and Iranian improved and landrace varieties and resulted from preliminary yield test of 2013-2014 cropping season, along with control cultivar Barekat, Saraziri, Zereshki and Baluchi were evaluated in a Gorgan, Dezful, Borojerd and Iranshar at two cropping seasons (2015-2017) in a randomized complete block design with three replications. Stability analysis were performed with Eberhart-Russell analysis of variance, Shukla's variance (2i), Wrick equivalence (Wi), environmental variance (S2i), coefficient of environment variation (CVi), coefficient of determination (R2), Finlay and Wilkinson regression coefficient (bi), Lin and Binns superiority index (Pi), yield stability index (YSi) and nonparametric methods such as , , Z1, Z2 and TOP and mean and standard deviation of rank.

Combined analysis of variance was performed after Bartlett test and not significant of it and assurance of uniformity of experimental errors. Combined analysis of variance indicated a significant effect of genotype, environment and genotype × environment interaction on seed yield. Based on Wrick equivalence, Shukla variance and RMSE indices, genotypes 5, 13, 14 and 15 were more stable. Genotype 9 had lowest environmental variance and coefficient of environmental variation and was stable than the other genotypes. genotypes 9 and 11 had the highest R2and the lowest deviation from regression. The coefficient of regression in genotypes 6, 9 and 16 were lower than one and their seed yield were higher than total average seed yield and therefore were the stable genotypes. Genotypes were stable genotypes. According to the priority index in all of environments and favourable environments, genotypes 11, 12, 14 and 15 were adapted to the unpredictable high yielding environments(1, 3, 5 and 7), while 6, 9, 14, 16 and 12 were adapted to low yielding environments(2, 4, 6 and 8).Simultaneous analysis based on seed yield and stability (YSi) indicated genotypes 6, 7, 9, 11, 12, 13, 14, 15 and 16 were as stable genotypes. Based on Top statistic, genotypes 12 and 14 and based on and , genotype 11 were stable than the other genotypes. Results of Selection index of ideal genotype (SIIG) method, Based on all non-parametric methods, showed that 14 and 15 genotypes whit 3478 and 3439 kgha-1 grain yield were the most stable genotypes. ConclusionBased on all indices, genotypes 9 and 11 were the most stable genotype in terms of seed yield and could be considered a good breeding material stock in any future breeding program.

All breeding programs and the development of new superior cultivars around the world are based on germplasm genetic diversity. In order to identify the phenotypic diversity and the morphological and agronomical traits relationship among 57 cowpea accessions,  the study was implemented in the field of the National Plant Gene Bank of Iran,in the 2019-20 growing season, The most important phenological, morphological and agronomic traits were recorded. Analysis of variance showed the existence of genetic diversity between the understudied accessions in terms of all quantitative traits except the number of pods per peduncle. The emphasis that it is possible to find out the desired trait among these accessions. Biomass, number of pods per plant, number of seeds per pod, pod length and 100-seed weight had the highest coefficient of variation. The range of phenological traits of day to 50% flowering (43-103) and day to maturity (69-177) showed that these accessions could be categorized as early, medium and late- maturing biotypes. Grain yield and harvest index had a significant negative correlation (P <0.01) with phenological traits. The 100-seed weight and pod length (P <0.01) were determined as traits affecting grain yield. The results of the principal component analysis showed that the three components explain seventy-two percent of the variability between the accessions. Plant height, number and weight of pods per plant, seed number in pod and grain weight per plant had the highest coefficients in the first component and day to flowering, day to maturity and grain yield had the highest coefficients in the second component. A bi-plot drawing of components and grouping genotypes based on  the traits showed that seventeen accessions are noticeable from yield component point of view. Also, seventeen accessions categorized as early-mature accesssins with high grain yield These results in one hand provide useful information about the agronomical traits diversity among local cowpea landraces and on another hand enable the selection of promising genetic resources for use in future breeding programs.

This experiment was performed to evaluate the feasibility of Lima bean cultivation in Guilan province and to evaluate the effect of planting date and plant density on its yield and growth.

The experiment was conducted as split plot in a randomized complete block design with three replications and two factors of sowing date (April 9, April 24, July 27, August 11) in main plots and plant density (plant distances 10, 15 and 20 cm) in sub plots in 2016 and 2018. Morphological traits and yield and yield components as well as phenological stages were evaluated. Combined analysis of variance showed that the effect of year on the studied traits was significant. Therefore, annual analysis of variance of the experiment was performed.

In the first year, the results of analysis of variance showed that in exception the grain yield per unit area and percentage of grain protein, other traits were significantly affected by the interaction of sowing date and plant density. The effect of sowing date on yield and grain protein percentage was significant, but these two traits were not significantly affected by plant density. Comparison of means showed that the first sowing date had the lowest grain yield per unit area. The sowing date of April 24 showed the highest yield and percentage of grain protein. In the second year, the results of analysis of variance showed that in exception the percentage of grain protein, other traits were significantly affected by the interaction between sowing date and plant density. According to the mean comparison of the traits, the highest grain yield was related to the sowing date of August 11, with a distance of 15 and 10 cm plant spacing, respectively. The lowest grain yield per unit area was obtained from the sowing date of April 9, with a plant distance of 15 cm.

According to the results of two years of experiment, a plant distance of 15 cm is suitable for planting lima beans. Considering the fixed distance of planting rows, in both spring and summer sowing dates, 24 April and 11 August are preferred. Also, due to rice cultivation in Guilan province as the main crop, cultivation of Lima beans after rice harvest in early August is recommended.