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Introduction: Sesame is one of the oldest crops and probably the oldest oilseed in the world. In most regions, the landrace and local masses of sesame are used. To increase production and yield, the production of modified cultivars for different agricultural climates is extremely important. Material and Methods: Seven genotypes included Isfahan, Sirjan, Fars, Oltan, Jiroft, Sabzevar, TS-3 and 21 hybrids that were obtained from them were studied in the research farm of the Faculty of Agriculture of the University of Birjand under the drought stress conditions during 2015-2018. The experiment was conducted in a randomized complete block design with three replications as a 7 × 7 one-way diallel. In this study, several traits were measured. These traits were including plant height, height to the first fruiting capsule, number of capsules per plant, number of sub-branches, number of leaves, leaf length, number of seeds per capsule, capsule length, capsule weight, capsule width, days to 50% and 90% flowering, days to physiological maturity, thousand seed weight, oil percentage, protein percentage, amount of chlorophyll a, chlorophyll b, total chlorophyll, biological yield, economic yield and harvest index. Results: The investigation of the adequacy of the additive-dominance model showed that the model was sufficient in the traits including plant height, capsule length, capsule weight, number of leaves, number of sub-branches, number of capsules per plant, economic yield, biological yield, days to 50 flowering, days to 90% flowering and days to physiological maturity, and therefore diallel analysis was done on these traits. Hayman's variance analysis showed that were significant component a (additive effects of genes) in all traits and component b (dominant effects of genes) in all traits except plant height. Also, were significant the component b1 (mean dominance effects) in most traits except plant height, number of auxiliary branches, number of capsules and seed yield, the component b2 (other dominance deviation due to the parents) in most traits except plant height, number of auxiliary branches and number of capsules, and the component b3 (residual dominance variation) in all traits except plant height. The investigation of genetic parameters showed significant additive genetic component (D) and dominanant genetic components (H1 and H2) in most traits. Also were significant the component F (average covariance of additive and dominance effects) and the component h2 (the overall dominance effect of heterozygous loci) in half of the traits. The average degree of dominance (√ (H1/D)) in different traits was observed as additive, incomplete, and over dominance. In all characteristics, except capsule weight, the ratio of genes with positive and negative effects (H2/(4H1)) was not equal to 0.25; therefore, in all traits, increasing and decreasing genes did not have symmetrical distribution among parents. The ratio of dominant and recessive genes in parents ((√(4DH1)+F)/(√(4DH1)-F)) was more than unity in most of the traits, so there was an uneven distribution of dominant and recessive genes in most of the traits. The number of dominant gene groups (h2/H2) was obtained from 0 to 2.04; therefore, all traits were controlled by one or two gene blocks. Broad sense (hb 2) and narrow sense (hn 2) heritability were high in all traits. Conclusion: In the traits studied, the type of action of genes controlling the traits, the ratio of dominant and recessive genes, the ratio of genes with increasing and decreasing effects, additive effects and dominance were variable and were different in most of the traits. Generally, most traits were controlled by genes with additive and dominant effects. The high heritability estimate indicates the promising news of the studied genetic materials in future studies. Therefore, among these materials, better genotypes can be selected for the climatic conditions of Birjand, so that it can be further investigated in the future. [ABSTRACT FROM AUTHOR]

Introduction Considering the lack of food in the world, increasing the production of rice is one of the demands of the global market and one of the important goals of many countries producing this crop plant. The final performance of each organism is affected by the genotypic potential, the environmental effects and the interaction between genotype and environment. The interaction of genotype and environment causes that different genotypes do not have the same reaction under different environmental conditions. Genotypes that can produce higher yields in different regions or under different environmental conditions and maintain their performance stability are considered as successful genotypes. In this study, nine promising rice lines originating from the Hashemi variety, along with two varieties Hashemi and Gilaneh, were evaluated for grain yield in two regions during two years. The objective of this study was to evaluate the stability of the studied lines and introduce the most stable ones in order to introduce the new varieties. Materials and methods The plant materials of this experiment were nine promising rice lines originating from the Hashemi variety, as a Iranian local variety with good quality, along with two varieties Hashemi and Gilaneh as control varieties. The experiment was conducted in a randomized complete block design with four replications in two regions, Rice Research Institute of Iran (Guilan province, Iran) and Chaparsar Research Station (Mazandaran province, Iran), in two years, 2017 and 2018. The studied traits included grain yield, days to 50% flowering, head rice percentage, milling efficiency, grain length, amylose content and gelatinization temperature. For data statistical analysis, simple analysis of variance was firstly performed for grain yield, and then Bartlett's test was done to check the uniformity of the experimental errors. Combined analysis of variance and comparison of means by Duncan's method was performed with SAS software. To evaluate the stability of the studied lines, Lin and Binns and GGE-biplot methods were used. Research findings The results of combined analysis of variance showed that the effects of genotype and year as well as the interaction of year×place and year×place×genotype on grain yield were significant. Therefore, grain yied stability of the studied genotypes was evaluated using Lin and Binns and GGE-biplot methods. The results of Lin and Binns method indicated that two genotypes Gilaneh and 19603 (Hashemi/IR74720-85-1-2-1), with the lowest intra-location variance, were the most stable genotypes in this experiment. The results of GGE-biplot graphical method also showed that the genotypes 19607, Hashemi and Gilaneh, which formed the vertices of the polygon in the grain yield biplot, were the best or the weakest genotypes in some environments or in all environments. Also, the simultaneous evaluation of stability and grain yield of the studied genotypes identified the promising line 19603 as the best genotype. The graph of ideal genotype also showed that the promising line 19603 had the smallest distance from the hypothetical ideal genotype compared to other genotypes, so it was the best genotype of this experiment. Conclusion The results of stability analysis of rice genotypes using Lin and Binns and GGE-biplot methods introduced genotype 19603 as the most stable genotype of this experiment. This promising line along with the promising line 19607 produced the highest average paddy yield in all studied environments. These genotypes with the number of days to 50% flowering less than 95 days, grain length more than seven mm, and medium amylose content and gelatinization temperature, were considered as genotypes with mid-maturing, long-grain (Sadri) and good cooking quality. Therefore, two promising lines 19603 and 19607 are suggested for cultivar introduction programs. [ABSTRACT FROM AUTHOR]

Background and Objectives: Determining the minimum number of samples and parameters required for acceptable results is crucial in rangeland vegetation studies. The common methods for determining Article history: sampling intensity are graphical methods and statistical characteristics. This RReecveisievde:d:101.00.40.32.2020222 study aims to compare these two methods in desert ecosystems dominated Accepted: 16.04.2022 by Salsola richteri and Ammotamnus lehmannii in South Khorasan. Methodology: An area of 100 hectares was randomly sampled using 10 Keyods: initial plots of 1010 meters. The number of sampling units was determined Sampling intensity, species accumulation curve, Cochran's sample size formula, coefficient of variation. using conventional graphical methods and the species accumulation curve (SAC). Statistical methods including the first and second Cochran's sample size formula, Yamane's sample size formula, confidence interval, and coefficient of variation (CV) were also used. All statistical calculations were performed in the biotools package in R software environment. Results: The appropriate number of sampling units determined using the SAC and conventional graphical method were 40 and 50, respectively. The first and second Cochran's sample size formula with an acceptable error rate of 10% required 78 to 92 plots, respectively. The range method suggested 53 to 160 plots, with an optimal number of 75. The CV method indicated that 10 plots had the lowest CV and were the most appropriate number of plots in the study area. The optimal sampling design was determined to be 75 plots, providing maximal information with minimal effort. Conclusion: The SAC method is suggested for determining sampling intensity in the desert ecosystems in this region due to its lower cost. The study revealed no significant relationship between the CV and the number of initial plots, and it is suggested not to use graphical methods or the CV method if the number of initial plots is less than 40. [ABSTRACT FROM AUTHOR]