جستجوی مقالات مرتبط با کلیدواژه « تجزيه به مولفه هاي اصلي » در نشریات گروه « زراعت »

AbstractThis research was done in the form of random complete block statistical design using split-factorial method with three replications in Agricultural Sciences and Natural Resources University of Khuzestan in the year 2022-2023. Three controltreatment, interruption of irrigation at the beginning of flowering until 50% of podding and interruption of irrigation at the podding stage until harvest were compared in the main plots.Two genotypes of Hyola 4815 and Aram and three densities of 80, 110 and 140 plants.m-2 were investigated in sub-plots. The results showed that the interaction of irrigation*genotype*density on the number of ranches, insoluble content in acidic detergent, ash, digestible dry matter, lactation specific energy and metabolizable energy was significant. The highest and lowest content of insoluble fibers was obtained from the control treatment, density of 140 plants and Hyola4815 genotype, and interruption of irrigation, density of 80 plants per square meter and Aram genotype, which showed a significant difference with other treatments. gave In general, the highest dry forage yield was obtained in the full irrigation treatment (3722 kg.ha-1), which showed a significant difference with the other levels of irrigation. Also, the Aram genotype showed a significant superiority with fodder yield equal to 3482 kg.ha-1 compared to Hyola 4815 genotype. The highest and lowest yield of dry fodder (respectively 3471 and 3226 kg.ha-1) was related to the density of 140 and 80 plants, respectively, which had significant differences with each other, but did not show significant difference with the density level of 110 plants.m-2. Based on this, in addition to the Aram genotype as the superior genotype, the plant density of 110 plants per square meter can be considered as the superior density in this experiment, which, in addition to the higher forage quality, also has a lower seed consumption cost compared to the density of 140 plants per square meter.IntroductionIrrigation is one of the most important factors affecting the quality and quantity of fodder plants. Also, the digestibility of fodder depends on the chemical composition of fodder. Plant density is a factor that affects the distribution of plant dry matter. In the study of Nasirpour and Zakirnejad (2018), the effect of four densities of 20, 30, 40 and 50 plants per square meter on the yield of pearl millet fodder was investigated and the results showed that the highest yield of millet fodder was obtained at a density of 50 plants per square meter and the lowest at a density of 20 The plant was obtained in square meters. Also, the research findings of Eskandari et al. (2017) increased the yield of dry fodder and the amount of hemicellulose-free cell wall with the increase in corn plant density, and then the forage quality was estimated to be higher. The presence of water-rich and profitable plants such as corn, whose cultivation has been developed regardless of water resource limitations in all provinces, is one of the reasons for the lack of attention to plants such as canola, which can be used as grazing, storage and silage for livestock. On the other hand, the scientific investigation of the fodder aspects of rapeseed has remained far away, and in Khuzestan province, livestock are facing a shortage of fodder in the winter season. Rapeseed cultivation can be one of the basic solutions to provide the fodder needed by livestock in this season.Materials and MethodsThe research was carried out with the aim of investigating the qualitative characteristics and performance of canola genotypes under the treatment of irrigation interruption and plant density in the agricultural year 2022-2023 at Khuzestan University of Agricultural Sciences and Natural Resources in the form of a split factorial design in the form of a randomized complete block design with three replications. The main factors include (1. control without interruption of irrigation, 2. interruption of irrigation at the beginning of flowering (phenology code 60) to 50% of fruiting (phenology code 75) and interruption of irrigation in the phase of fruiting until harvest (phenology code 71-99)), canola genotypes (Hyola 4815 and Aram) and plant density (80, 110 and 140 plants per square meter) were considered as secondary factors.Results and DiscussionThe results of the analysis of variance showed that the interaction between the treatments of irrigation interruption, and genotype in plant density on the traits of the number of branches, insoluble content in acidic detergent, ash content, total digestible nutrients, digestible dry matter, lactation specific energy and metabolizable energy was significant. The highest amount of total digestible nutrients, amount of metabolizable energy, digestible dry matter and milking specific energy were assigned to Aram genotype and the density of 80 plants per square meter and the treatment of irrigation interruption from seeding to harvest. The highest and lowest content of insoluble fibers in acidic detergent was obtained from the control treatment combination (optimal irrigation), density of 140 plants per square meter and Hyola 4815 genotype, and interruption of irrigation in the third stage, density of 80 plants per square meter and Aram genotype.ConclusionThe results of this experiment showed that between the experimental treatments in terms of performance of fresh fodder, dry fodder and quantitative and qualitative indicators including morphological traits, insoluble fibers in neutral and acidic detergent, total digestible nutrient, dry matter consumption, specific energy of lactation, there was a significant difference in metabolic energy and relative nutritional energy. The highest yield of dry fodder was observed from the treatment with the density of 140 plants per square meter and the Aram genotype, and the lowest amount was from the Hyola 4815 genotype and the density of 140 plants per square meter. Also, the highest total digestible nutrient, amount of metabolizable energy, digestible dry matter and lactation specific energy were observed according to the Aram genotype and the density of 80 plants per square meter and the conditions of stress from tillering to harvest.

Environmental disorders that significantly disturb the growth and yield of plants are considered as stress conditions and cause disturbances in biological. Drought stress is one of these environmental conditions which has been increased as a result of climate change and has been a negative effect on the yield of crops in the world. Every year about 12 million hectares of productive land has become dry and barren due to human activities and climate. More than 6000 varieties of quinoa are cultivated by farmers in the worlds. Quinoa is a plant responds to drought stress through escape, tolerance and avoidance of drought and has an extraordinary capacity for cultivation in dry and low-water soils because of its capabilities such as low inherent need for water, the maintenance of leaf surface and the ability to resume the speed of photosynthesis after drought stress. Titicaca, Redcarina and Giza-1 are three quinoa cultivars. Titicaca and Redcarina, were registered on December 14, 2009 and January 31, 2005, respectively, and are native to Denmark and Netherlands, respectively, and Giza1 is native to Egypt. Increasing yield in water deficit conditions requires the identification of genotypes resistant to drought stress. Different quantitative indicators have been provided to evaluate the reaction of genotypes in environmental conditions and also to determine their tolerance and sensitivity.

In order to evaluate the indicators of drought stress tolerance of quinoa cultivars, a factorial experiment with four stress levels (100, 75, 50 and 25% of water requirement) and three varieties of quinoa (Titicaca, Giza-1 and Redcarina) were conducted with three replications in two locations (Birjand and Sarbisheh region) and two planting dates, spring (March) and summer (July) in 2018 and 2019. Evaluation of cultivars in terms of drought tolerance was done using stress sensitivity indices, such as tolerance (TOL), mean productivity (MP), stress tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM). Decomposition into main components on yield under stress and non-stress conditions and drought stress tolerance indices were displayed in the form of a biplot diagram using STATISTICA software.

The results showed that in both regions the highest amount of STI, MP, GMP and HM indices, were recorded for Redcarina variety in all three levels of drought stress at spring cultivation, but they were belonged to Giza-1 at summer cultivation. Due to the dispersion of the results, SSI and TOL indices had less diagnostic power to evaluate the drought tolerance of quinoa cultivars. Principal components analysis showed that Redcarina cultivar was collinear with yield vector in stress condition and MP, GMP, STI and HM indicators and was located in yield potential and tension tolerant area in bi-plot diagram in two regions (Birjand and Sarbisheh) at spring cultivation. In summer cultivation, Giza-1 variety was located at sensitive to stress area and yield potential in bi-plot diagram and was collinear with grain yield vectors in non-stress conditions and MP, GMP, STI and HM indices in two regions. This showed the more yield of this variety in non-stress condition. In most of the planting dates and places were studied, Titicaca cultivar had collinearity with SSI vector or located at the closest position to this vector, which indicated that this cultivar was sensitive to stress.

In general, in July, Giza-1 variety and in March Redcarina variety were the most tolerance varieties and Titicaca was most sensitive cultivar to drought stress.
Keywords

Barley is the fourth most common cereal crop in the world after wheat, maize, and rice, which is used for animal and human feed and malt production. This plant stands out among crops due to its unexpectedly wide range of adaptation and distribution compared to other cereals, earning it recognition as a model species.  Determining the variation in the morphological and physiological traits of roots and shoots in the collection of barley genotypes can provide the basis for breeding new cultivars with suitable traits for better adaptation to specific environments. So in this study, some morphophysiological characteristics of roots and shoots of commercial barley cultivars were studied to identify cultivars with a higher root-to-shoot ratio as donor parents for breeding projects.

In this study, 21 barley cultivars were grown in a randomized complete block design with six replications in greenhouse conditions. Morphological and physiological traits related to roots and shoots were measured during the tillering and heading stages. Also, some traits affecting photosynthesis and yield during reproductive growth and harvesting stages were measured. Analysis of variance, mean comparison by LSD test at 5% probability level, and multivariate statistical analyses including principal components analysis, cluster analysis by Ward method, correlation analysis, and path analysis were performed by JMP and R statistical software.

Significant genetic diversity was observed for most of the traits among cultivars (P < 0.05). At the tillering stage, Behrokh and Mehtab cultivars and in the heading stage, Jolgeh cultivar showed the highest dry weight of root to shoot ratio. Reyhan variety showed the lowest dry weight of root-to-shoot ratio in both stages. The carbohydrate content of the root in the tillering stage and leaf proline, root volume, and the ratio of chlorophyll a to carotenoid in the heading stage had the highest significant correlation coefficients with dry weight of root to shoot ratio (P < 0.05). Path analysis revealed that the root carbohydrate content in the tillering stage and the ratio of chlorophyll to carotenoids and proline in the heading stage are the most effective traits of the dry weight of root-to-shoot ratio. Principal components analysis showed that the first and second principal components explain 33.63% and the first seven principal components explain 72.66% of the total changes. Also, the first principal component showed a positive and significant correlation with root to root-to-shoot ratio in the heading stage, and the second principal component showed a negative and significant correlation with this ratio (P < 0.05). The studied cultivars were classified into four groups based on cluster analysis so that the fourth and second clusters in the tillering stage and the third and second clusters in the heading stage had the highest and the first cluster in both stages had the lowest dry weight of root to shoot ratio.

Based on the results, Jolgeh and Reyhan cultivars can be used in breeding programs to improve and produce cultivars with higher root-to-shoot ratio, optimal yield, and more adapted to specific environments. These cultivars had the highest and the lowest dry weight of root-to-shoot ratio in both stages, respectively. Also, they were placed in different dimensions of the biplot drawn based on the first two principal components. In addition, these cultivars were observed in different classes based on the cluster analysis.

Oat, as a dual-purpose cereal, has an important role to provide human food and animal feed and fodder regarding to its high amounts of beta-glucan, protein, vitamins, minerals, fatty acids and valuable antioxidants. Oat breeding programs have been steadily decreasing compared to other cereals due to decrease in cultivated area. Therefore, identifying and studying sources of diversity in oats is critical and valuable regarding to release new cultivars with better quality and higher grain yield per unit area. Thus, this experiment was carried out with the aim of evaluating different genetic parameters and principal component analysis in order to determine the amount of genetic diversity in oat genotypes.

In this study, 361 oat genotypes of seven species belong to 50 countries from five continents which were received from Australian Grain Genebank (AGG) and kept in the genebank of the Campus of Agriculture and Natural Resources, Razi University were investigated. Estimation of the genetic parameters related to plant height, panicle length, days to 50% flowering, days to 50% physiological maturity, biological yield, grain yield, straw yield, harvest index, thousand seed weight, number of seeds per panicle and number of panicle per square meter of the genotypes were performed. This experiment was conducted in a simple square lattice design with two replications under normal irrigation condition, in two cropping years 2017-2019 in the research farm of the Agriculture and Natural Resources Campus, Razi University, Kermanshah.

Based on the results of the one-year variance analysis, there was a highly significant difference between genotypes regarding all the measured traits which indicates the presence of considerable genetic diversity between these genotypes. The results of mean comparison based on LSD method showed (NILE), (KENT), (LA PREVISION), (ZLATAK), SDO-185), OX87:080-2), (ACACIA), AND (DUNNART) genotypes had the highest grain yield for two years, while, Genotypes (LIGOWA), (NILE), (VENTURA), (YULAF), (NMO-712), (SDO-185), (VDO-931.1), (SLAVUGE), and (no.9278) had the highest mean for biomass in two cropping years. The results of the descriptive statistics showed the wide range of changes for the most of the investigated traits, as it was variable for grain yield from 56.30 to 789.81 g/m2 in the first year and from 39.59 to 627.28 g/m2 in the second year. Based on the results of correlation analysis, the most positive and significant phenotypic correlation was calculated between biological yield and straw yield in both years. The result of phenotypic and genotypic correlation also, showed a significant relationship between grain yield and all studied traits except plant height, panicle length, days to heading, and days to maturity in the first year. Also, it had a significant phenotypic correlation with all traits except plant height and straw yield in the second year. The traits of 1000- kernel weight, plant height, days to heading, and number of panicles per square meter had the highest genetic variance in both years. The range of general heritability in the first year was variable from 70.06 to 95.87%, respectively, for the traits of days to physiological maturity and 1000 seed weight, and in the second year, from 77.85 to 94.91% for biological yield and 1000 seed weight. Grain yield, biological yield, straw yield, number of panicles per square meter, and number of grains per panicle had a high percentage of heritability and genetic advance simultaneously. Based on the principal component analysis the first two main components explained 63.3 and 67.8 percent of the total changes in each year, respectively.

The results of variance analysis of the data obtained from this study indicated the existence of significant genetic diversity among the evaluated genotypes in terms of all measured traits, which can be attributed to the existence of different species with different geographical origins. Comparing the average data, genotypes 336, 349, 356 and 360 were introduced as the genotypes with the highest average grain yield in both years. Based on the results of Principal Component Analysis and Correlations Analysis, it can be found that the attributes of the number of panicles per square meter, the number of grains per panicle, 1000-kernel weight, and biological performance are very effective in breeding programs to achieve superior varieties. The genotypes NILE, LA PREVISION, OX87:080-2 and DUNNART were the superior genotypes in terms of the mentioned traits and grain yield. The estimation of genetic parameters showed that the selection based on the number of panicles per plot, the number of grains per panicle, and plant height plays a significant role in improving grain yield because of having a high broad heritability and significant genetic advance at the same time. According to the results of this study, it is possible to separate the superior genotypes in terms of grain yield and biological yield, and perform subsequent tests for grain and fodder genotypes, separately. Also, valuable traits for easier access to this important issue in subsequent oat improvement programs could be identified.

Lathyrus sativus L. is an annual plant from the legume family, used as a very valuable protein source for livestock and poultry, as well as for human nutrition. This genus has several useful agronomic characteristics such as high grain yield capacity and high protein content of its grains. Legumes produce economic performance in different environmental conditions and have a high potential for use in marginal areas with low rainfall. In fact, this has made it a popular crop in subsistence agriculture, especially in developing countries. The greatest importance of grass pea is related to the high resistance of this plant to harsh environmental conditions, such as drought, low soil fertility, and resistance to pests and plant diseases, which makes its production and cultivation economical. Salinity stress is an important abiotic stress that has harmful effects on plant performance and product quality and is a limiting factor for plant growth. Although salinity stress can occur in all growth stages of the plant, but considering that the initial establishment of the plant has a great impact on the final performance. Salinity stress in the seedling stage can be one of the most harmful stages for the plant. To improve the salinity tolerance in crops, genetic diversity between and within species can be used through selection and breeding. The purpose of this experiment was to investigate the response of early-maturing grass pea genotypes to different levels of salinity by evaluating some agronomic traits and identifying salinity-tolerant genotypes.

In order to evaluate the response of grass pea early maturing genotypes to salinity stress, 26 genotypes were studied as factorial experiment on based randomized complete block design with two replications at Research Farm of Plant Production and Genetics Department, Faculty of Agriculture, University of Maragheh. The salinity treatments were applied to four levels (0, 40, 80, 120 mM) of NaCl and different seedling and agronomic traits such as shoot fresh weight, shoot dry weight, fruit fresh weight, fruit dry weight, number of grains, number of grains per pod, plant height, leaf angle to the stem, leaf length, leaf width, number of leaves, number of shoots, location of the first shoot from the soil surface, root length were evaluated. Also, during the experiment, the date of flowering, the date of pod formation, the date of pod filling and the date of grain maturity were also recorded for each pot. Before data analysis, the assumptions of data variance analysis were checked with tests of normality and homogeneity of variances, and mean comparisons were made using Duncan's method at the 1% probability level. For the grouping of genotypes, cluster analysis was done by Ward's method and Euclidean distance measure using standardized variables. In order to determine the contribution of each trait in the total variation, reduce the amount of data and better interpret the relationships, principal components was used.

The difference between genotypes and salinity levels was significant in most seedling traits and with increasing salinity, the dry forage yield was decreased. Genotypes 19, 14, 13, 21, 10, 7, 25, 15, 24 and 12 were the best genotypes in terms of dry forage yield in seedling stage. Also, in the agronomic traits, differences between genotypes and salinity levels were significant in most traits. In general, the yield attribute decreased with increasing salinity. In cluster analysis with Ward’s alghorithm, the genotypes were divided into three clusters. The first cluster with the genotypes 8, 23, 11, 21, 7, 20, 2, 22, 3, 10 and 26 had the best genotypes for yield improvement. In principal component analysis, the first four principal components explainaed 82.08% of total variation. Based on the results, the first component could be identified as a component of biological yield and the second component as a forage yield. Thus traits of shoot length, root length, seedling length and the ratio of shoot length to root length were significant for the effect of genotype, salinity and the interaction of genotype × salinity at the probability level of 1%. The traits shoot dry weight, root dry weight and seedling dry weight had a significant effect of salinity at the probability level of 1%, and the trait of the ratio of shoot dry weight to root dry weight had not significant difference for any of the effects. Genotypes 19, 14, 13, 21, 10, 7, 25, 15, 24, and 12 were the best genotypes in terms of dry forage yield in seedling stage. In field traits, the difference between genotypes and salinity levels was also significant in most of the traits. In cluster analysis by Ward's method, the genotypes were divided into three clusters. The first cluster with genotypes 8, 23, 11, 21, 7, 20, 2, 22, 3, 10 and 26 had the best genotypes for yield improvement. In principal components analysis, the first three main components explained 82.08% of the total variation. The first component accounted for 38.31%, the second component for 25.31% and the third component for 19.74% of the total variation. Based on the obtained results, the first component can be named as the biological yield component and the second component as the forage yield.

The difference between genotypes and salinity levels was significant in most seedling traits, and dry forage yield decreased with increasing salinity. Thus, the characteristics of shoot length, root length, seedling length, and the ratio of shoot length to root length were significant for the effect of genotype, salinity, and the interaction of genotype in salinity at the probability level of 1%. The traits dry weight of shoot, dry weight of rhizome and dry weight of seedling had a significant effect of salinity at the probability level of 1%, and the trait of the ratio of dry weight of shoot to root had no significant difference for any of the effects. The results of seedling stage showed that genotypes 2, 6, 10, 13 and 26 (local) had high yield and genotypes 1, 3 and 5 had the lowest forage yield. The field results showed with the increase of salinity levels, a decrease in yield was observed.

Generally, with increasing salinity, forage yield decreased. The genotypes 10, 20, 22 and 23 the most tolerant genotypes and genotypes 16, 17, and 18 were identified as the most sensitive genotypes.

In the Mediterranean climates with mild winters like Khuzestan province, Iran, wheat is planted in autumn, and heat stress occurs only during the reproductive growth stage of wheat. In these regions, delayed planting causes the flowering and grain filling stages to be exposed to high temperatures, and the quantitative and qualitative performance of wheat decreases. Genetic improvement is one of the strategies to combat heat stress. Considering the importance of genetic resources for tolerance to environmental stresses tolerance, the present research was conducted to screen the wheat genetic collection of the National Plant Gene Bank of Iran for tolerance to terminal heat stress and to identify tolerant accessions.

In plant materials of this experiment were 236 bread wheat accessions along with three control varieties (Chamran, Chamran2 and Aflak), which were planted in an augmented design in the research field of Agricultural and Natural Resources Research Center of Khuzestan province, Ahvaz, Iran, in 2015-2016 crop year. The experiment was carried out in two planting dates, on-time planting date according to the region's custom at late November as normal conditions, and delayed planting at early January with the aim of heat stress during the reproductive growth stage of wheat. The measured traits included spike length, 100-grain weight, plant height, number of grains per spike, number of spikelets per spike, number of florets per spikelet, number of days to heading, number of days to maturity, grain filling duration, and five spikes grain weight. For data statistical analysis, descriptive statistics were firstly estimated under both normal and heat stress conditions, and then the relationships among traits were investigated using correlation coefficients. Principal component analysis was used to reduce the volume of data and cluster analysis was perfomed to group the studied genotypes.

The results of this experiment showed that terminal heat stress reduced the average of all studied traits, so that the highest decrease was observed in five spikes grain weight and the number of grains per spike. Based on the results of correlation coefficients under both normal and heat stress conditions, a positive and significant correlation was observed between five spikes grain weight and yield components traits, and a negative and significant correlation between five spikes grain weight and days to heading and days to maturity. Based on the results of principal component analysis, 72.54% and 80.53% of the total variance were explained by two and three main components under normal and heat stress conditions, respectively. The results of principal component analysis also indicated that the wheat accessions KC12977, KC12980, KC13013, KC13043, and KC13087, with the characteristics of early flowering and early maturity and higher values of five spikes grain weight, number of grains per spike, grain filling duration and number of florets per spike, were valuable accessions and have the sufficient potential to be used in breeding programs for heat stress tolerance. The results of cluster analysis separated the studied accessions into six group, and the fourth group including 62 accessions along with the control cultivars, had the highest average for number of florets per spike, number of grains per spike, and five spikes grain weight, as well as the lowest average for days to heading and days to maturity under both normal and heat stress conditions. and were recognized as the most tolerant group to heat stress. by three main components. In addition, the studied accessions were divided into six groups using cluster analysis.

The results of this study showed that there was a high genetic diversity among the studied bread wheat accessions in terms of terminal heat stress tolerance. Some genetic samples such as KC12977, KC12980, KC13013, KC13043 and KC13087, were valuable genotypes for the traits of early flowering and early maturity, as well as grain yield and yield components. The high diversity in these genetic resources, especially the tolerant accessions identified in this experiment as above mentioned, can be used to improve heat stress tolerance in future breeding programs.

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.

Drought stress constaints crop production in the world. Terminal season drought stress is one of the important environmental factors of yield reduction in durum wheat in semi-arid regions. Therefore, high yielding genotypes with drought tolerance is an efficient approach to mitigate its adverse effects. With declining resources of water and escalating intensity of drought, yield loss is an alarm in semi-arid regions. However, development of drought tolerance depends on complex traits and their interaction with environmental factors. Likewise, choosing genotypes with drought tolerant is a tricky task. Alternatively, some statistical parameters as well as drought tolerance indices can be employed to compare the changes in grain yield in normal and drought stress conditions for identification of high yielding genotypes with drought tolerance.

To identify terminal season drought-tolerant genotypes, 17 promising genotypes of durum wheat were evaluated at the Darab Agricultural Research Station, Iran. The evaluation was conducted in randomized complete block design with three replications and over two cropping seasons (2020-2022), both under non-stress conditions and terminal drought stress conditions by irrigation withdrawal at the flowering stage (GS 60). The indices of drought tolerance studied were yield under non-stress conditions (Yp); yield under stress conditions (Ys); tolerance index (TOL); stress susceptibility index (SSI); mean productivity (MP); geometric mean productivity (GMP); stress tolerance index (STI); harmonic mean (HM); percentage of yield decrease (R%); yield index (YI); yield stability index (YSI); relative drought index (RDI); abiotic-stress tolerance index (ATI); stress susceptibility percentage index (SSPI); stress non-stress production index (SNPI). SIIG (selection index of ideal genotype), CSI (combination of significant indices) and MGIDI (multi-trait genotype-ideotype distance index) indices were used in order to integrate different indices of drought tolerance and better selection of drought tolerant genotypes.

The results of combined analysis of variance for grain yield under non-stress and terminal season drought stress conditions indicated that the effects of year, environment and genotype on grain yield were significant. Additionally, the heatmap analysis revealed that the lowest observed grain yield was associated with terminal season drought stress conditions in the 2020-2021, while the highest observed grain yield occurred in the 2021-2022 under non-stress conditions. Furthermore, the highest grain yield (kg.ha-1) under normal irrigation conditions (Yp) was observed for genotypes 2 (8178), 1 (7938), 17 (7698), 19 (7662), 18 (7659), 14 (7451), and 10 (7413), respectively. On the other hand, the highest grain yield (kg.ha-1) under drought stress (Ys) was related to genotypes 18 (5639), 4 (5489), 8 (5479), 10 (5473), 13 (5434), and 6 (5404), respectively. Moreover, based on the TOL, ATI, and SSPI indices, genotypes 9, 4, 12, and 15 with the lowest values of these indices were identified as stress-tolerant genotypes. In addition, based on the SSI and %R indices, genotypes 4 and 8, which had the lowest values of these indices, respectively, were also classified as stress-tolerant genotypes. Examining the MP, GMP, and HM indices revealed that genotypes 2, 18, 1, 17, and 10 exhibited the highest values and were identified as the best-performing genotypes, respectively. Similarly, based on the SNPI index, genotypes 4, 8, 18, 13, and 6 demonstrated the highest values and were among the drought tolerant genotypes. The results also showed that the genotypes 18, 4, 8, 10, and 13 had the highest values of the YI index, respectively. The results revealed that the SIIG and CSI indices had positive and significant correlation with Yp and Ys. Conversely, MGIDI index had negative and significant correlation with Yp and Ys. The results of principal component analysis (PCA) revealed that the investigated genotypes were placed in four areas of the biplot diagram. The genotypes of area one (5, 7, 9, 12 and 15) exhibited low yield potential under both non-stress and stress conditions. The genotypes of the second region (1, 2, 14 and 19) showed high grain yield potential under non stress conditions. The genotypes of the third region (6, 10, 13, 17 and 18) demonstrated high yield potential under both non-stress and stress conditions, leading to their selection as superior genotypes. Therefore, MP, GMP, HM and STI indices were positioned within the area of the three PCA diagrams, proved suitable in identifying high yielding and drought tolerant genotypes. Furthermore, genotypes in fourth area (3, 4, 8, 11, 13, 15 and 20) displayed higher grain yield under terminal season drought stress conditions.

The results of this experiment showed that MGIDI, CSI and SIIG indices had sufficient efficiency in selecting high yielding and tolerant durum wheat genotypes. Efficiency of SIIG, MGIDI and CSI indices in selection of high yielding terminal drought tolerant genotypes were similar, and genotypes 2, 10, 17 and 18 were selected. However, based on all three indices, only genotype 18 ranked first. Therefore, genotype 18 which was located in the third area of PCA diagram and performed higher than average grain yield under both and non stress and stress conditions, was identified as adapted drought tolerant genotype for the Darab region and similar areas.

Due to the droughts of the last few years, the low need of barley crop to water and rich soil, the need of the country in the supply of Community Food and the importance of barley in the food industry, therefore, it is necessary to introduce high-yielding and drought-resistant genotypes.

The research was conducted at the Ilam Agricultural Research Station in 2020-2021. Identification of tolerant and sensitive genotypes was based on grain yield and drought tolerance indices. Accordingly, 16 barley genotypes were implemented in the form of random complete blocks with four repetitions in two conditions: dim and supplementary irrigation. After harvesting, grain yield was measured and stress tolerance indices were calculated.

The results of correlation between drought tolerance indices and grain yield in rainfed and irrigated conditions showed that tolerance index (STI), mean productivity (MP), harmonic mean (HM) and geometric mean productivity (GMP) were positively correlated, and had significance with grain yield traits in both environmental conditions. So, they were suitable indicators for selecting high yielding genotypes in both rainfed and irrigated environments. Based on SIIG index, genotypes 11 and 9 show the highest values, while genotypes 3 and 4 had the lowest values. Also, factor analysis based on principle component analysis showed that the first two factors explain 98.5%((the first factor 68.7% and the second factor 29.8%) of the total diversity.

Based on the obtained results, genotypes No. 9 and 11 have the highest resistance to drought stress and yield, which are suitable for cultivation in areas under moisture stress, and genotypes No. 3 and 13 are suitable for planting in areas without moisture stress.

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.

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.

IntroductionMaize is one of the most important sources of energy supply to feed poultry, livestock, as well as humans, and the primary and raw material for industrial and food products. This valuable crop plant in terms of world production ranks third after wheat and rice. Since knowing the genetic diversity in germplasm collections and determining the genetic relationships between breeding materials is the first and most important step in breeding researches, so identifying high diversity and suitable genetic potential lines is one of the goals of plant breeders to product and introduce new varieties. The objective of this study is to investigate the genetic diversity of 18 maize inbred lines using microsatellite (SSR) markers, to evaluate the efficiency of the studied markers, and to introduce the most appropriate ones in determining the genetic diversity of maize lines.Materials and methodsThe plant materials of this research included 18 inbred lines of maize prepared from the Agriculture and Natural Resources Research Center of Khorasan-Razavi province, Iran. DNA extraction was carried out by CTAB method from fresh and young leaf samples after the three-leaf stage of seedlings. Polymerase chain reaction (PCR) was performed in a final volume of 10 μl, and horizontal electrophoresis on 3% agarose gels as well as vertical electrophoresis on 6% polyacrylamide gels were used to observe the amplified fragments. For data analysis, first the amplified fragments (bands) on the gels were valued and quantified, so that the numbers 1 and 0 were considered for the presence and absence of each band in each maize line, respectively. To evaluate the genetic diversity, different diversity indices including number of effective alleles, polymorphic information content (PIC) and Nei’s gene diversity were estimated using POPGEN software, and the most suitable markers were introduced. To group the studied maize lines, cluster analysis and principal coordinates analysis were performed and the corresponding graphs were drawn using NTSYSpc 2.0 software.Research findingsAssessing the genetic diversity of maize lines based on microsatellite markers showed that 20 SSR markers used in this research amplified a total of 81 scorable loci, whose size ranged from 65 to 200 bp. The average number effective alleles, polymorphism information content and Nei’s gene diversity were calculated as 2.05, 0.71 and 0.62, respectively, indicating that there was a considerable genetic diversity among the studied maize lines. Evaluating the polymorphic information content (PIC) index showed that the markers used in this study had highly variable PIC from 0.28 (for Phi024) to 0.91 (for Phi038) with an average of 0.71. Cluster analysis by UPGMA method using Jaccard similarity coefficient grouped 18 maize inbred lines into three distinct clusters with 1, 6 and 11 lines, respectively. Molecular analysis of variance based on three groups derived from cluster analysis showed that 11% and 89% of the total variance was between and within population, respectively. The results of principal coordinate analysis and grouping if maize lines based on the bi-plot of the first and second vectors confirmed the grouping of the cluster analysis.ConclusionThe results of the current study showed that there was a significant genetic diversity among the studied maize lines, which can be used in breeding programs. Also, microsatellite markers (SSRs) had the ability to assess the genetic diversity and separation of maize genotypes from each other. Evaluating the different diversity indices for the studied markers in this research showed that the markers Phi034, Phi038, Phi076, Phi084, and Phi092 were more suitable markers for determining genetic diversity. Therefore, it is recommended to use these informative markers to determine genetic diversity as well as to identify heterotic pattern in maize breeding programs.

To evaluation and selection of different genotypes of sugar beet for winter cultivation in Razavi Khorasan province, a randomized complete block design with four replications was conducted separately in two regions (Jovin and Torbet-Jam) in 2018-19.In the Jovein region, 94.11 percent of the total variation in the data was explained by three components. Based on these findings, the characteristics of molasses sugar, sodium content, sugar extraction coefficient, and root yield are the most appropriate selection criteria for winter planting genotypes. Using Ward's method, cluster analysis revealed that the investigated genotypes were distributed into three clusters in both regions. FDIR19B3021 genotype in the first cluster of the Jovin region and FDIR19B4028 genotype in the Torbet-Jam region, SBSI-6 and SVZA2019-JD0402 genotypes in the second cluster as desirable genotypes for the Jovin and Torbet-Jam regions, and SVZA2019-JD0400 genotype in the third cluster. The Perfekta variety was selected as the Torbet-Jam representative for the Jovin region. The results of the experiment demonstrated that the genotypes used in the two regions are distinct, and that the increase in root impurities is a problem associated with winter cultivation, despite the fact that the root yield is maximized. The FDIR19B3021 genotype is recommended in the Jovin region, while the FDIR19B4028 genotype can be suggested in the Torbet-Jam region.

Drought stress is known as one of the main factors limiting agricultural production. Investigation of the effect of drought stress on grain yield and other agronomic and physiological traits can be useful in identifying drought-tolerant cultivars. The aim objective of the present study was to study the effect of terminal drought stress on some of the agronomic and physiological characteristics in a set of promising barley lines.

This study was carried out at the Cereal Research Station located in Seed and Plant Improvement Institute, Karaj, Iran during 2020-2021 cropping seasons. The plant material consisted of 17 promising genotypes of barley along with a commercial cultivar (cv. Jolgeh). All genotypes were investigated in two separate experiments based on a randomized complete block design with three replications under two control and drought stress conditions.

The results of combined analysis of variance showed a significant difference between control and drought stress conditions in terms of all measured traits except spike length and the number of seeds per spike. Furthermore, a significant difference was observed among the tested genotypes in terms of all measured traits except initial chlorophyll fluorescence, maximum quantum yield of PSII, and maximum primary yield of photochemistry of PSII. However, the interaction effect between drought stress conditions and genotype was only significant for the number of days to physiological maturity, grain filling period, main spike length, and chlorophyll content.The results of principal component analysis (PCA) revealed that the first five components accounted for 84.80% of the total phenotypic variation, under drought stress condition. Considering the angle among trait-vectors indicated that some of traits such as number of days to anthesis and to physiological maturity, awn length, plant height, leaf area index, chlorophyll content, and number of seeds per spike positively correlated with grain yield in the drought stress condition. In general, our results showed that genotypes G2, G3, G6, G7, G12, and G18 were identified as the best genotypes compared with other tested genotypes.

According to results, genotype G7 due to its highest grain yield and ideal agronomic and physiological features can be candidates for further complementary investigations in multi-environmental trials with the aims of realization of a new commercial cultivar.

The main usage of durum wheat is the production of semolina (pasta flour) for pasta products due to its high protein and strong glutamine. The development of the pasta industry, along with the increase in its demand and the favorable weather conditions in many parts of Iran, requires more research, especially in the field of durum wheat breeding with knowledge of the genetic diversity of the studied genotypes.

The plant material used in this experiment included 18 winter durum wheat genotypes that were evaluated in dryland conditions in a randomized complete block design with four replications at Moghan Dryland Agricultural Research Station located in Pars-Abad of Ardabil province. The 32 phenomorphological and agronomic traits were measured in laboratory and field.

The difference between the studied genotypes was significant for most of the traits. Mean comparison of traits for durum wheat genotypes in important traits such as total grain yield, total biomass, yield of fertile tillers, weight of main spike, number of leaves, length of spike and length of peduncle, introduced two genotypes as prior genotypes. Total grain yield had a significant positive correlation with some traits such as main spike weight, number of spikelets, number of grains per spike, number of grains in fertile tillers, yield of fertile tillers and awn weight. Cluster analysis classified 18 durum wheat genotypes to three groups. The first cluster included seven genotypes, the second cluster contained three genotypes, and finally the third cluster included eight genotypes. The third cluster in terms of plant height, spike length, peduncle length, number of leaves, stem diameter, number of fertile tillers, weight of single plant, weight of main spike, number of spikelets, number of grains per spike, number of grains per fertile tiller, fertile tiller yield, awn length, awn weight, straw yield, flag leaf length, flag leaf width, total grain yield, total biomass and total straw yield were higher than average. Therefore, the genotypes of this group can be used to improve grain yield. In principal component analysis, the first three components explained for 68.28% of the total variation. For the first component, single plant weight, spike weight, fertile tiller yield, straw yield, total grain yield and total biomass had high positive coefficients. According to the analysis of the main components, the first component, grain yield component, the second component, maturity-related traits and the third component, leaf-related traits were named. These components can be used in the selection of durum wheat genotypes in breeding programs.

Among durum wheat genotypes in terms of studied traits, considerable diversity was found, and this diversity can be used in breeding programs for resistance to biotic and abiotic stresses and other breeding purposes.

In order to select suitable parents for breeding purposes, one must have sufficient knowledge of genetic diversity and germplasm classification. It was for this reason that a study was conducted in 2019 at the Seed and Plant Research Institute in Karaj in order to identify and classify 17 eggplant genotypes based on the randomized complete block design. This stud measured 19 morphological traits such as number of days to flowering, plant height, number of stems per plant, number of nodes, and internodes, weight, and fruit yield as well as total phenol content, total anthocyanin content and glico-aldeid solasonin. The results of the analysis of variance revealed a significant difference for all the traits (p≤0.01). The range of variation showed great genetic diversity among cultivars, which can be useful for different breeding purposes, lower plant height to prevent dormancy. Greater number of stems and flowers are important to achieve higher yield, wherein 13321 genotypes showed lower height among genotypes. Cluster analysis classified the studied genotypes into three groups, and separated white eggplants from colored ones correctly. The PCA also confirmed the results of cluster analysis, showing that the color eggplants had more fruit yield, lower levels of solasonine, and lower days to maturity than white eggplants. However, the color eggplants that were used in this research were breeding cultivars; therefore, the use of breeding methods would be important to improve the quality and quantitative of eggplant genotypes.

In order to study of source limitations on traits related with wheat grain yield, an experiment was carried out in split plot design based on RCBD with four replications and 24 genotypes as the main plot factor and source limitation as subplot factor in Research Station of Dryland Agricultural Research Institute (DARI) at 2016-2017. The measured traits were spike length, number of spikelets per spike, spike weight, number of grains per spike and 1000 grains weight. The difference between the compared genotypes was significant in terms of the measured traits. Spike weight had a significant positive correlation with the number of grains per spike. The principal component analysis in control conditions, showed that all traits were placed in one principal component, that number of grains per spike was evaluated as the most effective trait. While, principal component analysis in source limitation conditions indicated that the traits are placed in two principal components, the first principal component represents the number of grains per spike and the second component represents the 1000 grains weight. Generally, both control and source limitations, the number of grains per spike was evaluated as the most effective trait. On the other hand, among the source limitations studied, flag leaf removal had the highest decrease in grain yield related traits.

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.

Wheat (Triticum aestivum L.) is the most important crop and staple food of three quarters of the world's population. Therefore, the study of genetic diversity of this strategic plant helps breeders to identify the genetic potential and capacity of traits related to breeding goals, including yield and yield components. Knowing the differences between different wheat genotypes and how these differences relate to their potential yield is crucial in improving the yield of new cultivars.

In order to achieve the desired wheat genotypes, study of genetic diversity of yield, yield components and interaction of genotype × treat of 21 promising wheat lines in terms of 14 important agronomic traits in a randomized complete block design (RCBD) in three replications with important commercials cultivars of the region (Tirgan and Kalateh) as controls, was performed. The experiment was planted in the Agricultural Research Station of the Ardabil Agricultural and Natural Resources Research and Education Center (Moghan). Among the existing methods for evaluating diversity, multivariate analysis is one of the most important and widely used methods.

The results of analysis of variance at the probability level of 0.01 and 0.05 indicated that the studied wheat lines had significant differences in all traits except the number of grains per spike. Comparison of the mean performed by Duncan method also showed that G17 and G15 lines were selected as desirable lines in terms of all measured traits; while, G3 and G19 lines also had the lowest rank in this analysis. The results of correlation analysis also showed that the grain yield had a positive and significant correlation with all the evaluated traits except the number of tillers, peduncle length and number of grains per spike. Based on the principal component analysis performed on the experimental data, the first 5 components explained more than 75% of the variance of the data. According to the grouping diagram of the lines in terms of the first and second components, the lines were grouped into four groups. Based on the graphical analysis of the line ranking chart, the promising wheat lines G15 and G17 had better performance in the evaluated traits than the other studied lines, and the G4 line in terms of stability in the traits, as stable line, was selected. The multidimensional diagram also identified G15, G17, G18, G23, G6, G10 and G12 lines as desirable genotypes, and in terms of line ranking diagram based on the ideal line, G15 and G17 lines were also identified as the top ranking line.

Lines with high yield potential and other desirable agronomic traits identified in this study can be used to create superior populations and compatible with the characteristics of hot and humid zone in the north of the country.

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.