جستجوی مقالات مرتبط با کلیدواژه « شرایط دیم » در نشریات گروه « زراعت »

The interaction between the genotype and the environment creates complexity in yield prediction and is a challenge for breeding programs. The aim of this study was to investigate the genotype × environment interaction and study the grain yield stability of 21 barley genotypes using the GGE biplot model. The experiment was carried out in randomized complete block designs with two replications during 2014-2015, 2015-2016, 2016-2017 growing seasons under rain-fed and irrigation conditions (a total of six environments). The combined analysis of variance for grain yield showed a significant difference for year, genotype, genotype × year, year × location and year × location × genotype. The results of stability analysis by GGE biplot showed that the two first components of GGE biplot explained 72.6% of total grain yield variation. The polygon view of GGE biplot showed three superior genotypes and suitable genotypes in each mega-environment. Based on the biplot patterns, the genotypes 19 was the most unstable accession, whereas genotypes 9 and 1 were identified as stable genotypes, which suggests the superiority of these genotypes compared to the other genotypes. The irrigation environment in 2014 was identified as the most distinctive and representative environment due to its proximity to the average environment.

Lentil (Lens culinaris Medik.) is one of the main food legume crops in Iran, where it is grown as a Rainfed crop in the spring season in cold regions. One of the obstacles of autumn cultivation in cold regions is the negative effects of cold and frost. So, in order to expend autumn cultivation, introducing cold varieties are needed. But until now, a cold tolerant lentil variety has not been introduced. Assessment of cold tolerance, introducing autumn cultivated cultivars and production stability are important goals of crop breeding programs in cold regions.

This study was carried out during the (2021-2022) growing season at the Dryland Agricultural Research Center. Plant materials consisted of 13 Lentil landraces that were collected from Iran and a check variety Sana. Experiments were conducted at rainfed conditions using a complete block design with two replications. Plants were evaluated for cold tolerance screening in the field under natural conditions with a cold tolerance rating (CTR: cold tolerance score) scale. observations of five randomly selected plants from each plot were recorded for plant height and seed number per plant. Green seeker calculated the normalized difference in the vegetative index using red and near infra-red light. Cold tolerance of landraces was also evaluated under controlled conditions (cold room).

According to the field trial results, none of the landraces had cold damage effects. Considering yield, NDVI index, plant height, biomass and seed number per plant, landraces 4 (Ardebil- Nir- Dash Boulagh) and 1 (Ardebil- Nir- chehre bargh) were the best. These landraces had 41% and 31% higher yields than the Sana check variety. Controlled condition results showed that landraces 2 (Ardebil- Namin- Nane Karan), 3 (Ardebil- Namin- Dodran), 9 (Varzegan- Orangh) and 11 (Varzegan- Somedel) had 91-100 survival percentage and selected as highly tolerant. Also, landraces 1 and 5 had 81.5- 82.5 survival percentages and were considered as tolerant.

Totally, results showed highly significant differences between landraces. some landraces such as number 1(Ardebil- Nir- chehre bargh) and 4 (Ardebil- Nir- Dash Boulagh), had suitable agronomic attributes and could be used in lentil breeding programs. Comparing field and controlled condition results showed accuracy of evaluating cold tolerance under controlled condition.

Wheat is one of the main cereals in cultivated areas and production rate worldwide. This product is the primary source of carbohydrates and protein in the human diet, and almost half of Iran's agricultural land is under wheat cultivation. On the other hand, drought stress stimulates a wide range of plant responses, from physiological and biochemical to molecular, and causes oxidative damage in plants. Plants use antioxidant enzymes to deal with these stresses. Regarding the role and importance of antioxidant enzymes, the activity of these enzymes in irrigation and drought conditions was investigated in some wheat genotypes. In this research, the activity of peroxidase, catalase, superoxide dismutase enzymes and grain yield for 20 advanced bread wheat genotypes under drought stress conditions was carried out. The experiment was laid out in a randomized complete block design with three replications in two conditions, irrigated and rainfed conditions. The present research was carried out in the Research Field of the Department of Plant Production and Genetics, Campus of Agriculture and Natural Resources, Razi university. Based on the simple analysis of variance, genotypes showed significant differences in the activity of all three enzymes, peroxidase, catalase, and superoxide dismutase. The effect of environment, genotype, and the interaction effect of environment × genotype were significant for catalase, peroxidase, and superoxide dismutase enzyme activity, where the data were analyzed in the form of combined analysis. In irrigation conditions, the highest activity of peroxidase enzyme was observed in Genotype 12, catalase in Genotype 10 and superoxide dismutase in Genotype 15. In this condition, the lowest activity of peroxidase enzyme was observed in Genotype 11, catalase in Genotype 11 and superoxide dismutase in Genotype 7. Also, in dryland conditions, the highest level of peroxidase enzyme activity was observed in Genotypes 6, catalase in Genotype 2 and superoxide dismutase in Genotype 15, and the lowest level of peroxidase enzyme activity was observed in Genotypes 4, catalase in Genotype 8 and superoxide dismutase in Genotype 1. In terms of seed yield trait, the highest amount in irrigation conditions is related to Genotypes 10, 7, and 8, and the lowest amount is related to Genotypes 12, 13, and 11. In dryland conditions, the highest yield is related to Genotypes 4, 10, and 17, and the lowest level is related to Genotype 9. The results showed that the activity level of peroxidase, catalase, and superoxide dismutase enzymes is higher in drought environment than in irrigated conditions, and different genotypes show different responses to drought stress. In fact, the activity of antioxidant enzymes increased with drought stress. In fact, plants increase the activity of their antioxidant enzymes to deal with drought stress, eliminate oxygen free radicals, and deal with the oxidative stress that has occurred and affects the grain yield by spending energy. Based on this, knowing more about antioxidant factors and the factors affecting them, valuable solutions can be adopted to deal with drought stress in plants.

The primary goal of the plant breeding program is to evaluate the genotypes based on different traits and select the best genotypes based on the studied traits. The aim of this study was investigation of durum wheat genotypes diversity based on agro-physiological traits and study the interrelationships between the traits using the genotype x trait (GT) biplot technique.

In this study, 86 durum wheat genotypes, including 82 breeding lines received from CIMMYT along with four check genotypes were examined as an augmented design in the Dryland Agricultural Research Sub-Institute (Sararoud Station) during 2017-18 crop season. Genotypes were evaluated based on 22 different agronomic, morphological and physiological traits. Analysis of variance and comparison of genotypic means were performed based on the best linear unbias prediction (BLUP) method and then based on the BLUP data, the GT biplot analysis was performed.

Based on the results, a significant difference was observed between the studied genotypes in terms of all studied traits except for canopy temperature and spike length, which indicates a significant genetic diversity between genotypes for the studied traits. Based on the representation of polygon view of the GT biplot, the genotypes were divided into eight groups and the traits into six groups. Genotype #17 had the highest value in terms of combination of grain yield, biological yield, harvest index, 1000-grain weight and relative chlorophyll content index (SPAD-reading). Genotype #3 had the best combination of plant height, number of grains per spike, initial growth rate, spike length, relative leaf water content and flag-leaf length. Genotype #27 had the highest values ​​in terms of canopy temperature and peduncle length and genotype #76 had the highest value in terms of canopy temperature compared to other genotypes. Genotype #4 had the highest combination of traits number of days to booting and external peduncle length. Genotype #10 had high values ​​in terms of number of days to physiological maturity and number of spikes per square meter, which is a late genotype in this regard. Based on the results of correlation analysis and GT biplot analysis, biological yield, harvest index, 1000-kernel weight, SPAD-reading, number of spikes per square meter were identified as the most important traits affecting grain yield.

Based on selection criteria, genotypes # 75, 17, 72, 13, were identified as ideal genotypes under rainfed condition and are recommended for further studies in durum wheat breeding program.

In order to investigate the effect of zeolite on growth indices, yield and grain yield components and protein of lentil in dryland and supplementary irrigation conditions, a field study was conducted in Shahrekord University, Shahrekord, Iran. The experiment was performed as a split plot in a randomized complete block design with three replications. The main factor included three levels of irrigation (rainfed, one stage of supplementary irrigation and two stages of supplementary irrigation) and the second factor included the application of three levels of zeolite (0, 10 and 20 tons ha-1). The results showed that supplementary irrigation increased the grain yield. Application of zeolite moderated the effect of drought stress. Zeolite improved grain yield, this improvement occurred under both supplementary irrigation and rainfed conditions. Though, the interaction of supplementary irrigation and zeolite on yield and yield components was not statistically significant. Supplementary irrigation and zeolite had a significant effect on growth indices and improved growth indices during the growing season. The highest grain yield (1741 kg ha-1) was obtained when supplementary irrigation was applied at two stages. Application of 20 tons ha-1 of zeolite increased grain yield by 50% compared to the control. Therefore, according to the findings of the present study, in conditions of water restriction, application of 20 tons ha-1 of zeolite may benefit lentil cultivation in Shahrekord, Iran.

Safflower is an important drought and salt tolerant plant adapted to the climate conditions of Iran. Multi-environment trials play an important role in crop breeding programs to identify genotypes with high and stable yield. In the present study, yield stability of 17 safflower genotypes were tested under the rainfed condition in a three years trials based on randomized complete block design with 3 replications at Gachsaran Agricultural Research Station during 2004-2006 cropping seasons. The results of the combined analysis of variance showed that main effects of genotype and environment on the stability of Safflower Seed Yield were significant at 1%, and GEI was significant at 5% probability level. The results of analysis of variance showed that 45.2% of total variation was due to environment while 26.0% of variation was belonged to genotype and G×E interaction. GGE (G plus GE) biplot model was used to evaluate seed yield stability in safflower genotypes. The first two principle components (PC1 and PC2) together explained 94.2% of the total variability, therefore most of the information could be graphically displayed in the PC1 vs. PC2 biplot. The biplot of comparison of the safflower genotypes with the ideal genotype revealed that Sina, Syrian, Cyprus Bergon and Cw-4440 were the closest genotypes to the ideal cultivar, and Esfahan, Cw-74 and Hartman had the most distance from the ideal cultivar.

Legumes are a second important food source for humans and a valuable supplement with high protein quality. Chickpea has the highest harvested area and yields within legumes. However, the yield of chickpea is low and there is a gap between the expected and observed yield of this crop. In order to access high yielded genotypes with suitable agronomic characteristics, genetic diversity of 40 ICRISAT originated desi chickpea genotypes and two check varieties (Kaka and Pirouz) were evaluated in complete block design with two replications in dryland agricultural research institute in Maraghe station during 2017-2018 and 2018-2019. Agronomic traits were recorded. Combined analysis results showed that there were significant differences between genotypes at 1% for yield, 100sw, pod number in plant and main branch numbers. For plant height at 5%. High heritability was observed for pod number in the plant (0.90) and main branch number (0.85). Cluster analysis categorized genotypes into 4 groups. Group 4 had desirable characteristics for yield, 100SW, biomass and main branch numbers. Group 2 was desirable for plant height and pod number in the plant. Principal component analysis results showed that the first four PCs explained the 71.22% of differences. The first and second PCs could be named yield and yield attributes. Results showed that ICCV 16116, ICCV 08102, ICCV 13107, ICCX-110054-F3-BP-P30-BP, ICCX-110050-F3-BP-P1-BP and ICCX-110050-F3-P28-BP were suitable to use as parents in chickpea breeding programs to access high yielded genotypes.

Knowledge of genetic diversity in crop species can play an important role in exploiting genetic diversity and lead to the development and expansion of crop cultivation in drought-prone environments. In this regard, identifying and utilizing informative markers related to agro-physiological traits will be necessary for application in breeding programs and marker-assisted selection.

This study was performed to investigate the relationship between SCoT markers and agro-physiological traits in the durum wheat breeding germplasm. For this purpose, 220 durum wheat genotypes were evaluated for agronomic, phenological, and physiological traits. They were received from the International Center for Agricultural Research in the Dry Areas (ICARDA) and International Maize and Wheat Improvement Center (CIMMYT) during two consecutive cropping seasons (2017-18 and 2018-19). The germplasm was also genotyped using five SCoT markers. In order to identify the informative markers related to each trait, the regression analysis method was used.

According to the results, considerable variation for agro-physiological traits was observed in the studied germplasm. The majority of ICARDA germplasms that most favored by grain yield, 1000-kernel weight (TKW), normal difference vegetative index (NDVI), plant height (PH), and peduncle length (PL) well separated from the majority of CIMMYT germplasm that most favored late in the heading (DH) and maturity (DM) and higher canopy temperature (CT). These findings indicate that the breeding lines originally developed from ICARDA might possess traits of tolerance to drought conditions absent in those developed in CIMMYT. 13 SCoT loci were associated with at least three traits based on trait-marker association analysis. These markers would enhance the efficiency of parental selection in the durum wheat breeding programs. Six informative SCoT loci (SCoT16-845, SCoT16-965, SCoT33-780, SCoT24-1400, SCoT16-845, and SCoT25-680) were identified as repeatable markers that can be considered as candidate markers for assessment of other wheat germplasm collections and scanning the genome for the related traits.

This study based on phenotypic data and SCoT markers revealed a high level of diversity in durum wheat breeding germplasm that may be useful in breeding programs. This information is valuable for germplasm grouping and determination of different phenotypic and genotypic groups, developing high-yielding genotypes, and using cross-breeding programs.

Water scarcity is the most essential limiting element of agricultural production, particulary in arid and semi-arid areas throughout the world. The line × environment interaction is a major challenge in the study of quantitative characters because it reduces yield stability in different environments and also it complicates the interpretation of genetic experiments and makes predictions difficult. In this regard to analysis of line × environment interaction and determine the yield stability of bread wheat genotypes, 15 new bread wheat lines along with Aftab cultivar were evaluated in a randomized complete block design with three replications in four experimental field stations (Gachsaran, Khoramabad, Moghan and Gonbad) during three cropping seasons. Results of combined analysis of variance indicated that the effects of environments, line and line × environment interaction were significant, suggesting that the lines responded differently in the studied environment conditions. So, there was the possibility of stability analysis. According to mean rank of nonparametric stability parameters, the lines G1, G3, G7 and G15 with the lowest value for mean rank were stable, whereas lines G2, G6, G8 and G10 with highest values were unstable. Also, the results indicated that the nonparametric statistics Si(3), Si(6), NPi(2), NPi(3), NPi(4), KR and Top were associated with mean seed yield and the dynamic concept of stability. Therefore, these methods were suitable for selecting stable and high yielding lines in bread wheat. Finally, G7 line with average grain yield and high general stability was the top line of this test, which after additional tests can be a candidate for a new cultivar to introduce.

Food security reduction due to climate change is one of the most important challenges in the 21st century. This study was carried out to predict the potential yield and production of the country’s strategic crops examining various climate change scenarios. In this study, the potential yield & production of 17 crops (Wheat, barley, rice, common bean, rapeseed, chickpea, grain maize, cotton, lentil, potato, sesame, soybean, sugar beet, sugarcane, sunflower, alfalfa and Silage maize) were estimated under current conditions (period 2005-2014) & two climatic scenarios (optimistic:1.5 ° C increase in temperature with 14% increase in precipitation period 2005-2014; pessimistic: 1.5 ° C increase in temperature & 14% decrease in precipitation period 2005-2014) applying SSM-iCrop2 model. The results showed that the pessimistic scenario reduced the potential production of wheat & legumes (about 1%) & the optimistic scenario increased the potential production of these crops (4 & 2%, respectively). Both climate change scenarios reduced the potential production of rice, potato, oilseeds & sugar crops (4, 10, 5 & 7%, respectively). Furthermore, the potential production of Silage maize increased in both climate change scenarios (2% & 3%, respectively). The results showed that the major factors which alter crop yield could be the growing season duration, radiation use efficiency and transpiration efficiency. In general, wheat, barley, potato, and sugarcane were more affected by climate change than other crops.

The most important goal in all crop breeding programs is to increase yield, and yield improvement requires the use of efficient statistical methods to identify superior genotypes. In determining the superiority of genotype, in addition to high yield, yield stability in different environments must also be considered.Biplot analyses are good tools for selecting superior genotypes and to increase efficiency in selection. In this study, GGE biplot method was used to evaluate the stability of grain yield of 205 lines and lentil cultivar in augmented design during three cropping years in the Faculty of Agriculture of Zanjan University under rainfed conditions. The results of combined analysis of control cultivars showed that the effect of year and year × cultivars interaction were significant for grain yield. Thus, the lines were examined using GGE biplot graphic method. The results showed that the first component and second component explained 68.3 and 28.5 percent (in total 96.8 percent) of total variation respectively, which indicates the high validity of the bipod in the explain. The results also showed that lines 170 and 164 were the best lines in the first year and lines 157 and 183 were the best lines in the third year. Line 167, in addition to having high yield, had lower stable yield. This line was placed in the center of the circle as the ideal line and the lines 164, 170, 147, 122 and 7 were placed in the next ranks. Lines 147, 128, 7, 160, 51, 148, 156 and 160, in addition to having higher yield than the average, had a short distance from the stability axis and had low unstable yield. Lines 8, 57, 157, 86, 186, 83, 140, 164 and 170, despite having high performance, had high unstable yield. Biplat polygonal analysis led to the identification of two mega-environments, among which the first year had the most discriminating ability among the years. Existence of 90º angle between the first and second year showed no correlation between these two years and their conditions were different and greater than 90º angle of the second year with these years showed its negative correlation with the first and second year.

In order to study the effects of various rates of starter nitrogen, methanol, and bio fertilizers on nodulation, grain filling period, and yield of lentil (Lens culinaris L.) under rainfed condition, an experiment has been carried out as factorial based on randomized complete block design with three replications under field condition in Ardabil in 2018-2019. The factors include starter nitrogen in three levels (no nitrogen and N application of 25 and 50 kg/ha) by urea, bio fertilizers in four levels (without bio fertilizers, application of Rhizobium legominosarum, mycorrhiza and both application of mycorrhiza with Rhizobium legominosarum), application of methanol at three levels (foliar application with water and methanol applications of 15 and 30 volume percent). Means comparision show that the maximum  number and weight of nodules per plant (12.72 and 11.59 mg per plant, respectively), grain filling rate (1.45 mg/day), grain filling period and effective grain filling period (35.17 and 29.91 days, respectively), number of pod per plant (34.43), and grain yield (1530 kg/ha) have been obtained at both applications of mycorrhiza with Rhizobium legominosarum, foliar application of 30 volume percent of methanol, and 50 kg/ha of starter nitrogen. The treatments display an increase of about 210%, 25.64%, 45.76%, and 103% in the number of nodules per plant, grain filling rate, effective grain filling period, and grain yield, respectively, in comparison with the control (no application of nitrogen, methanol, and bio fertilizers). Based on the results from this study, both applications of bio fertilizers (mycorrhiza with Rhizobium legominosarum) and foliar application of 30 volume percent of methanol with 50 kg/ha starter nitrogen are recommended to improve grain yield of lentil under rainfed condition.

Barley (Hordeum vulgare L.) After wheat, maize and rice is the fourth grain, which is cultivated for grain use and has a perennial diploid and polyploid, and has been dispersed throughout the world. The adaptation of cultivars in different environmental conditions in plant breeding programs is of particular importance. Reactions between genotypes and environmental effects are referred to as genotype and environment interaction.The interaction between the genotype and the environment creates complexity in yield prediction and is a challenge for plant production and breeding programs. Methods for reducing the interaction between genotype and environment and increasing performance can be used to select and introduce high-performance and sustainable lines in different regions. Therefore, the aim of this study was to investigate the genotype × environment interaction and adaptability and performance stability of 21 barley genotypes using the analysis of the main and multiplicative effects (AMMI) model. Data related to location and years in the form of integrated environment and data analysis were carried out based on six environments. Then AMMI analysis and calculation of the main components of the interaction effect for all genotypes and drawing of the plot and calculation of ASV stability index was performed using IRRISTAT software.

The present experiment was carried out in randomized complete block designs with two replications during 2014-2015, 2015-2016, 2016-2017 under rain-fed and irrigation conditions (a total of six environments) at the research farm of Faculty of Agriculture, Razi University, Kermanshah, Iran.

The combined analysis of variance for grain yield showed significant differences for year, genotype, genotype × year, year × location and year × location × genotype effects. The results of the analysis of AMMI model showed a significant difference between genotype and environment and four components of the interaction for grain yield were significant. The first and second components in AMMI model accounted for 52.78% and 26.00% of the interaction sum of squares, respectively. Genotypes with high values of the first major components (positive or negative) have a high interaction with the environment, while the genotypes with the first major component near zero have lower interaction. Genotypes 2, 5, 8, 10, 13 and 20 with fewer values of the first component of interaction were more stable than the other genotypes. The value of ASV was obtained from the ratio of sum of squares of IPCA1 (the first component of interaction) to IPCA2 (the second component of the interaction) for each genotype. According to the stability Index, the genotypes 9, 12, 15 were selected with the lowest values of AMMI stability as most stable genotypes. In order to determine sustainable genotypes with general and specific adaptation, AMMI Biplot was used for different locations. The results showed that genotype 2, 5, 8, 10, 13, which are at the center of biplot, have general stability and the genotypes that are closer to any environment the environment have specific adaptability to the environment. Among stable genotypes, genotypes 10 (Roho / 4 / Zanbaka / 3 / ER / Apm / Lignee131 / 5 / Otis), 8 (Baladieldawaia / 5 / AwBlack / Aths // Arar / 3 / 9Cr279-07 / Roho / 4 / DD-14 / Rhn-03) and 2 (Zarjau/80-5151//Skorohod/3/Robur/WA2196-68//DZ40-66) had higher mean grain yield. Therefore, these genotypes can be proposed for using in future breeding programs to introduce new cultivars.

Combined analysis of variance showed significant effect of year, genotype and genotype × year interaction for grain yield. The significant effect of genotype indicates the diversity of studied genotypes in terms of grain yield. Among the stable genotypes, genotypes 2, 8 and 10 had also higher grain yield, therefore, it can be suggested that the genotypes can be introduced as new cultivars or for use in future breeding programs. However, it is not appropriate to use a stablity method to identify high-performance and stable genotypes, so, it is recommended to use different methods to assess the stability.

Selection of high yielding and stable genotypes is especially important for rainfed conditions. The objective of this study was to use the genotype by yield × trait (GYT) biplot method to select superior bread wheat genotypes based on yield-trait combinations under rain-fed conditions. To this end, 16 bread wheat genotypes were assessed in a randomized complete block design with four replications in two cropping seasons, 2017-2019. Comparison of average grain yield of genotypes in the experimental years showed that genotypes G1 (Aftab), G15 and G8 had the highest grain yield with an average yield 3433, 3269 and 3233 kg/ha, respectively. The result of polygon view of GYT biplot showed that G8 was the best genotype in combining grain yield with 1000-kernel weight, number of grain per spike and spike length. Similarity, G1 also had a relative superiority in combining grain yield with number of spikelet per spike, awn length and early maturity. Average tester coordinate (ATC) view of GYT biplot indentified genotypes G8, G1 and G15 with all positive yield-trait combinations as the best genotypes and genotypes G14, G4, G13 and G7 as the weakest genotypes. Genotypes G15 and G16 were also balanced for yield- trait combinations. Ranking of the genotypes based on GYT index showed that genotypes G8, G1 and G15 had the best genotypes in combining grain yield with the evaluated traits in the experimental years. Based on the results of this study, high correlations were observed between 1000-kernel weight, number of grain per spike and grain weight per spike in combination with grain yield, indicating high efficiency of combining these traits with grain yield to improve productivity of bread wheat genotypes under rainfed conditions.

In order to evaluate the productivity potential of some barley varieties and promising lines under no-till condition an experiment was conducted in cold (Sonqor) and warm (Sarpol-e Zahab) dryland regions of Kermanshah province during 2017-18 cropping season. In the cold condition, seven winter genotypes and in the semi-warm condition seven spring genotypes were evaluated for grain yield and some agro-physiological traits. The results of ANOVA in the cold condition indicated significant differences (P<1%) days to heading, chlorophyll content (SPAD), days to physiological maturity and grain yield. In the semi-warm condition the genotypes were significantly differed (P<5%) for normalized difference vegetation index (NDVI) and canopy temperature (CT). In cold condition, grain yield of genotypes varied from 2818 (Sahand variety) to 5864 kgha-1 (belong to breeding line G4). In the semi-warm condition, due to severe drought and terminal heat stress the grain yield of genotypes varied from 208 (Faraz cultivar) to 367 kgha-1 (local variety). Based on genotype × trait biplot analysis, in cold region genotypes G4 and G6 was the best for grain yield (YLD) with 1000-kernel weight (TKW), number of grain per spike (NGPS) and days to heading; and in semi-warm condition genotype G3 had the best results for both YLD and TKW. The profiles of trait associations were relatively different in cold and semi-warm conditions. The positive correlations of NGPS and TKW with grain yield showing the importance of these traits to enhance yield productivity under dryland conditions.

In order to evaluate the productivity potential of some bread wheat varieties and promising lines under no-till rainfed condition two different on-farm trials were conducted in cold (Sonqor) and warm (Sarpol-e Zahab) regions of Kermanshah province during 2017-18 cropping season. In the cold condition, 12 winter genotypes and in the warm condition 32 spring genotypes were evaluated for grain yield and its components, morphological traits, canopy temperature, relative chlorophyll content (SPAD) and normalized difference vegetation index (NDVI). In the cold condition, the genotypes were significantly different for peduncle extrusion length, number of grain per spike, number of spike per m2 and thousand-kernel weight, peduncle length and gain yield. Grain yield of genotypes varied from 2849 (Sardari) to 4274 (G10) kgha-1 and four genotypes (G2, G4, G10 and G12) had higher yield than check variety (p < 0.05). In the warm condition, the genotypes were different for SPAD, plant height, peduncle extrusion length, peduncle length, 1000-kernel weight and days to heading. Grain yield of genotypes varied from 364 (G22) to 1363 (G8) kgha-1, and G8 and G10 were superior to the check variety (Aftab) by 89% and 61%, respectively. The profiles of trait associations were relatively different in cold and warm conditions. NDVI was positively correlated with grain yield, number of kernel per spike and 1000-kernel weight and negatively correlated with canopy temperature in the warm region. These results showing the importance of NDVI in identifying productive wheat genotypes for dryland conditions.

To investigate the effects of different sowing dates and irrigation regimes on agronomic traits and yield of quinoa (Chenopodium quinoaWilld.) as a new plant, a field experiment was conducted at Haftkel, North East of Ahvaz, Iran. The experiment was conducted as split plot based on a randomized complete block design with four replications. Four sowing dates (31 October, 15 and 30 November and 15 December) considered as main plots and five irrigation levels (full-irrigation, once irrigation at sowing time, two irrigations at sowing and flowering stages and no irrigation conditions) were subplots. Results showed that period between flowering and maturity was shortened with the shortening of the growing season due to the late sowing dates. Dry matter accumulation increased in plant with an increasing the growing season or increased irrigation water. Water could increase plant height, stem diameter, number of ears per plant, number of grains per panicle, grain weight and grain yield and biological yield. The highest grain and biological yield of quinoa was found in sowing date of October 31. Quinoa planted at December 15 had the lowest plant high, the number of ears per plant, number of grain per panicle, seed weight and yield, compared to the other sowing dates.

In this study, in order to display the crop capacity and production potential of durum wheat breeding lines and internal and external cultivars to farmers and identifying the best adapted genotypes under no-tillage condition, 26 durum genotypes selected from durum wheat breeding program of Dryland Agricultural Research Institute (DARI) along with two local bread wheat as checks at inovation platform of Iran-ICARDA food security project in warm region of Sarpol-e Zahab, Kermanshah, Iran in farmers' fields under conservaton agriculture (no-tillage) during 2017-18 cropping season. During the experiment the genotypes were evaluated for grain yield and agro-physiological charactristics. The results of ANOVA and mean comparison for the studied traits in inovation platform indicated significant dfferences among genotypes for grain yield and agro-physiological characteristics. Mean yields among genotypes varied from 327 kg/ha (corresponding for G23) to 926 kg/ha (corresponding for G16) and superior genotypes had increasing yileds between 6 to 51% than the local check. In general, according to the yield productivity, agro-physiological charactristics and agronomic scores, six durum wheat genotypes (G24, G21, G7, G18, G16 and G25) were superior to the local check. These well performing genotypes, were charactrized for high grain yield and 1000-kernel weight, early heading, high SPAD-reading and NDVI (normal difference vegetative index) and cooler canopy under rainfed condition.

The effect of drought and salinity stress in view of water deficiency are similar to each other, but under long term-salinity stress, in addition to drought stress the plant experiences increased osmotic and high ion stress. There are different levels of salinity (more than 38% of Golestan’s total land area is salt-affected) and various farming conditions (rain-fed and irrigation) in Golestan Province, Iran. The purpose of this study was to evaluate the growth, water use efficiency and sodium and potassium concentrations of plant in irrigated and rain-fed wheat genotypes (selected from the first year of the experiment). The experiment was under greenhouse conditions and was conducted to physiologically compare genotypes selected in the first year in a factorial arrangement with two irrigation regimes (5 and 75 % water lost from soil available water), four levels of soil salinity (0, 4.5, 6.5, and 8 ds/m) and two tolerant genotypes (selected from the first year) in a completely randomized design with three replications. The greenhouse is located in Gorgan city of Iran. Two genotypes selected from the first year of the experiment at moderate salinity (9 ds/m) and under rain-fed condition i.e. N- 87- 20 and Karim were the experimental material, respectively. In this experiment leaf area, number of stomata, sodium and potassium concentrations for leaf and stem, total water use from sowing to maturity, water use efficiency (WUE) for grain and biomass and yield were measured. The results showed that genotype n- 87- 20 had higher leaf area but lower stomata density than those of Karim. Genotype n- 87- 20 in 25% soil available water, i.e. drier condition had similar yield (1.20 vs. 1.16 gr/plant) to Karim. In the wetter condition the yield of N- 87- 20 was higher than Karim (2.00 vs. 1.64 gr/plant). In drier condition, Karim had higher WUE than in wet condition but for N- 87- 20 genotype, it was reverse and it had higher WUE in dry than in wet condition. The sodium concentration in stem was twice as bigger than that of leaf (0.58 and 0.32%, respectively) and with increase in unit salinity of soil to 8 ds/m sodium concentration in leaf and stem increased 0.068 and 0.025 %, respectively. There was not any difference between two genotypes for Na+/ k+ in leaf and stem but with an increase in soil salinity the Na+/ k+ for leaf and stem decreased. N- 87- 20 was better genotype in irrigated conditions with no or moderate salinity stress and Karim was better genotype under rain-fed condition. Up to 8 ds/m of soil salinity Na+/k+ ratio could indicate the difference between genotypes.

Durum wheat (Triticum durum desf.) is one of the most important cereal crops used to make pasta, macaroni and other foods. Understanding the complexity of the genotype × environment interaction (GEI) and its impact on determining the most stable genotypes, mega environments and other adaptation goals has been a special concern for the plant breeders. Various methods exist for the stability analysis of grain yields based on different sustainability concepts that can be grouped into parametric, nonparametric and multivariate methods. In this research, 20 genotypes of durum wheat (19 advanced genotypes and Dehdasht commercial variety) were evaluated in five regions during four years (2009-2013). Experiments were carried out in a randomized complete block design with four replications in each environment (year × location). Based on the results of grain yield stability assessment using 13 nonparametric methods in the methods of mean rank, standard deviation and adaptability percentage, genotypes 9, 10 and 12, in the methods of Nassar and Huhn and sum rank of Kang, genotypes 4, 5, 10, 11 and 17 and in the Thennarasu and Fox methods, genotypes 6, 9, 10, 12, 13 and 17 were selected as the most stable genotypes. Finally, based on summarizing the results of all methods genotypes 10 and 12 were selected as the most stable genotypes. According to the previous studies of the authors, it is suggested that in the next researches, in order to better evaluate the stability of genotypes, one of the sustainability methods such as AMMI, spatial regression or mixed models, along with nonparametric methods, must be considered.