Iranian Journal of Crop Sciences
Year:2018 | Volume:20 | Issue:2|Papers Count:6

Enough information about genetic parameters, including heritability and gene action, is the first step in breeding of a trait. Among different methods, generation mean analysis, with lower estimation error, is one of the best methods for estimation of genetic parameters. The present experiment was carried out to estimate heritability, number of genes and gene action for some agro-morphological traits in maize. The seeds of the generations of P1, P2, F1, F2, BC1 and BC2 were prepared during two successive years and were evaluated based on randomized complete block desine in Golestan Agricultural and Natural Resources Research and Education Center, Iran during 2015. Results of weighted ANOVA showed significant differences between the generations for all traits, therefore, generation mean analysis was performed. While, additive effect and relative dominance controlled ear length, number of row. ear-1, cob diameter and cob percentage, the additive, dominance and epistatic effects controlled the other traits simultaneously. Difference between dominance and additive components and the average of gene dominance was greater than unity which indicated the role of non-additive and the importance of heterosis effects in expression of these traits. The maximum heterosis and heterobeltiosis belonged to ear biomass and grain yield respectively. The broad and narrow sense heritability of the traits was ranged from 62. 41 to 90. 06 and 3. 46 to 60. 40, respectively. The average number of genes was ranged from 0. 03 to 4. 74 for different traits. In general, unlike grain yield, selection in early generations for yield-related traits with high narrow sense heritability such as ear length, cob diameter, 250-grain weight and number of grain. row-1, may improve grain yield in advanced generations. In addition, due to the high narrow sense heritability for cob percent (60. 4%), selection in early generations for reduction in percentage of cob, with no significant increase the overall weight of the ear, may increase the ear harvest index and improving grain yield of maize.

Leaf rust (Puccinia triticina) and yellow rust (Puccinia striiformis) are known as the most important and prevalent diseases of wheat worldwide, causing significant losses in the world’ s wheat production. Transfer of leaf and yellow rusts resistance genes to wheat cultivars is one of the most economical and effective methods to control of diseaseses. Lr34/Yr18 is a resistance gene which confers a durable resistance to wheat leaf and yellow rusts. In the recent years, several molecular markers linked to Lr34/Yr18 have been identified. In this experiment, presence of Lr34/Yr18 in some Iranian wheat cultivars and promising lines was evaluated under field condition along with some recently developed molecular markers. Evaluation of plant resistance of wheat genotypes to yellow rust and leaf rust was conducted under artificial inoculation in disease nurseries of Cereal Research Department, SPII, Karaj and Golestan station in Ahvaz, Iran respectively, in 2014. Results of molecular assays indicated that three markers caSNP4, caSNP12 and Cssfr1 predicted presence of Lr34/Yr18 with more confidence compared to csLV34. These markers may be easily used in the genetic laboratories with limited equipments. Based on the results of caSNP4 and caSNP12 markers, from 85 wheat genotypes, 18 genotypes had linked alleles to Lr34/Yr18 gene. Comparison of the field evaluation with results of molecular assay indicated that most of the wheat genotypes with Lr34 gene had resistance and moderately resistant to moderately susceptible infection responses to leaf rust and yellow rust.

To evaluate of non-parametric methods for identification of high yielding and stable durum wheat genotypes, 18 durum wheat promising lines along with two commercial durum (Behrang) and bread wheat (Chamran) as check cultivars, were evaluated in four warm and dry locations of Iran including Darab, Ahvaz, Khoramabad and Dezfoul stations during two cropping seasons (2013-2014). The experiments were conducted in a randomized complete block design with three replications. Results showed that the effect of environment (E), genotype(G) and interaction of GE were significant in Bredenkamp (except for genotype) and Hildebrand for non-crossover interaction (without change in rank) and de Kroon/van der Laan (except for interaction of GE) for non-crossover interaction (with change in rank) methods. Results of SIIG (Selection Index of Ideal Genotype) method, based on all non-parametric methods, showed that DW-92-17 and DW-92-20 genotypes (with 6095 and 6215 kg. ha-1 grain yield) were the most stable genotypes. According to SIIG method, the majority of non-parametric methods may identify the stable genotypes considering the static (biological) concept, so the selected genotypes may not necessarily produce high grain yield. Genotypes DW-92-17 and DW-92-20 were selected as stable lines with higher yields (compared to control) and DW-92-4 and DW-92-5 genotypes were selected as high yielding lines for complementary experiments, especially for resistance to diseases and quality characteristics evaluation.

In order to investigate the relationship among amylose content, gelatinization temperature and paste viscosity properties and identifying the discriminator parameters of intermediate and high amylose groups in rice genotypes, 40 pure lines and cultivars from two groups of high and medium amylose content were evaluated in a randomized complete block design with three replications at Rice Research Institute of Iran during 2015 and 2016. Physicochemical characteristics of grain (amylose content, gelatinization temperature) and paste viscosity properties including peak viscosity, trough viscosity, breakdown viscosity, final viscosity, setback viscosity and consistency viscosity were measured by Rapid Visco Analyser in RVU unit. Results of cluster analysis with WARD method showed that all selected rice genotypes from high and intermediate amylose groups were classified into two groups based on paste viscosity characteristics and gelatinization temperature. The first group consisted of 19 genotypes with high amylose content and the second group included 21 genotypes with intermediate amylose content. In fact, the classification of the genotypes based on the viscosity parameters and gelatinization temperature was similar to the classification of the cultivars based on the amylose content of grain. Discriminant function analysis showed that only the final viscosity and gelatinization temperature completely (100%) separate the high and intermediate amylose groups and identified as the best and most effective discriminators (with an eigenvalue of 56. 35) that are easier, less cost and time consuming, compared to direct measurement of amylose content of grain. Evaluation of starch viscosity characteristics and gelatinization temperature of rice grain in combination with multivariate statistical methods may be considered as an easier and less costly method suitable for the classification of rice genotypes and may be used in breeding programs to identify good grain quality rice cultivars. According to the fitted regression model, it is possible to predict the intermediate to high amylose groups of rice genotypes in regard to final viscosity value between 290. 50 and 493. 25 RVU with an adjusted R square of 97%.

In order to investigate the effect of different levels of zeolite and farmyard manure, as environmental friendly fertilizers on soil properties and yield and quality of sunflower, a field experiment was carried out in a split-factorial layout based on completely randomized blocks design in three replications in the faculty of agriculture, Tarbiat Modarres University, Tehran, Iran, during 2014 and 2015. Treatments included irrigation regimes (irrigation after depleting 40, 60 and 80% of soil water content) as main factor and the combinations of nutrition systems (100% organic, 50% organic + 50% chemical and 100% chemical fertilizer) and zeolite (0, 5 and 10 ton. ha-1 of zeolite) in factorial layout. Results showed that using organic sources increased organic carbon, nitrogen, phosphorus, potassium, and electrical conductivity of soil, while decreased bulk density at the end of the growth season. Due to the high amount of organic carbon, organic sources accompanied with zeolite improved the organic carbon content of the soil and led to the highest seed yield (1781 kg. ha-1) and water productivity (3. 01 and 3. 3 kg. ha-1. mm-1 in the first and second years, respectively). In first year, the highest oil content of seed (37. 9%) was obtained in 10 ton. ha-1 zeolite with 50% farmyard manure + 50% chemical fertilizer under full irrigation treatment. At all irrigation regimes, application of 100% organic sources or combined chemical and organic sources with 5 or 10 ton. ha-1 of zeolite led to greater seed yield and water productivity. Overall, the results of this experiment revealed that under the most irrigation regimes, application of farmyard manure and zeolite may increase the availability of water and nutrients for plant and may led to increase yield and oil content of seed and water productivity in sunflower.

To evaluate the relationship between seed yield and its components in peanut (Arachis hypogaea L. ), 78 genotypes of peanut were grown in a randomized complete block design with three replications at Takatoo research station, Sari, Iran, in 2016 and 17 plant traits related to seed yield were measured. Analysis of variance showed that there were significant differences in all traits (except for seed width), that indicated a considerable variation between peanut genotypes. Based on the results of multiple stepwise regression analysis, first, second and third ranked variables were evaluated by considering the contribution in seed yield variation and minimum co-liner and the seed length and number of pod. plant-1 were selected as first ranked variables (76% of variation of seed yield). Results showed that the seed length and number of pod. plant-1 had a negative (non significant) relationship with seed yield. The results of sequential path analysis showed that the direct effect of number of pod. plant-1 (r = 0. 815**) and seed length (r =-0. 810**), were the most effective component in seed yield. Based on the correlation analysis result, number of pod. plant-1 may be used as selection index to promote the seed yield in peanut.