stepwise regression

It is necessary to delineate the relationship between crop yield and climatic and nutritional parameters in order to predict crop production. The current research was designed with the aim of suitable fertilizer recommendation and carried out according to the climatic conditions of the Lorestan area in two years, 2017-2018 and 2018-2019.

The statistical model used was split-factorial plots in the form of a randomized complete block design with 3 replications. The main plot included: the type of planting (irrigated – Non- irrigated) and the sub plot included the date of planting (in three levels, October 25 (early), November 15 (optimum) and December 5 (late) for two type of cultivation and the type of nutrition (at two levels of biofertilizers: Nitroxin and NPK based on the soil test and integrated fertilization of chemical fertilizer + chemical NPK with Phosphorus biofertilizers).

Traits related to yield components, such as the number of spikes per square meter and the number of seeds per spike, were affected by the dual effects of planting date× type of cultivation and planting date × type of nutrition. The double effect of type of cultivation× type of nutrition was significant only for biological yield traits and the harvest index. The highest seed yield was observed under the conditions of irrigated cultivation, early planting date, and full chemical nutrition. This research demonstrated that employing a combination of NPK chemical treatment (at 50% of the soil test recommendation) and biofertilizers can effectively reduce the consumption of chemical fertilizers in both irrigated and rainfed agriculture for the Kohdasht variety of wheat. Additionally, implementing early planting dates alongside the use of biofertilizers can help address nutritional gaps, thereby enhancing growth and yield under conditions that involve a reduction in chemical fertilizer use for wheat crops.

The results of the stepwise regression of the atmospheric parameters showed that there is a positive and significant regression relationship between the grain yield and the amount of GDD.

Cumin (Cuminum cyminum L.) is one of the most important and economic medicinal plants from the Apiaceae family with a considerable distribution in different regions of Iran. The cumin plant is one of the most important medicinal plants in Iran, which needs a lower irrigation to complete the growth stages. Therefore, cumin is one of the most valuable plants for cultivation in arid and semiarid regions of the world. The variety of cultivars is considered one of the important factors affecting the performance of plants. Therefore, the accurate and correct identification of the genotypes and landraces is very useful, in addition to being necessary for crop improvement programs of these plants; it is also very effective in preserving genetic reserves. The objectives of this research were to identify the superior cumin ecotypes based on grain yield and some agronomical traits using the selection index of ideal genotype (SIIG) method, classify cumin ecotypes using the cluster analysis method, and determine the most important traits affecting the essential oil yield trait using stepwise regression.

To evaluate cumin ecotypes using the SIIG, an experiment was conducted on 12 cumin ecotypes based on a randomized complete block design with three replications in the 2022-2023 cropping season. The studied ecotypes were collected from Yazd (Ardakan, Abarkouh, Ashkzar, Bafgh, and Khatam), Fars (Shiraz and Abadeh), Isfahan (Isfahan and Semirom), and Kerman (Kerman, Rafsanjan, and Sirjan). Agronomical traits, including plant height, number of branches per plant, number of umbels per plant, number of seeds per umbel, 1000-seed weight (TSW), grain yield, biological yield, harvest index, essential oil percentage, and essential oil yield, were measured in this research. The SIIG method and cluster analysis were used to select superior cumin ecotypes.

The results of the analysis of variance (ANOVA) revealed that ecotypes significantly affected all studied traits at the 1% probability level, except for TSW. Mean comparisons showed that the Sirjan ecotype produced the maximum value of grain yield (642.3 kg/ha), followed by Kerman, Khatam, and Ardakan ecotypes (634, 614.2, and 594 kg/ha, respectively). The minimum values of grain yield were seen in Ashkzar (456.3 kg/ha) and Bafgh (467.11 kg/ha) ecotypes. Mean comparisons showed that Sirjan, Khatam, Kerman, and Ardakan ecotypes attained the highest values in the most traits. The minimum values of plant height were recorded in Kerman and Sirjan, and the maximum value belonged to Bafgh and Ashkzar ecotypes. Sirjan, Kerman, Khatam, and Ardakan ecotypes showed the minimum distance from the ideal genotype (di+), the maximum distance from the non-ideal genotype (di-), and the maximum SIIG value (0.937, 0.926, 0.769, and 0.667, respectively); thus, they were introduced as favorable ecotypes. Ashkzar, Bafgh, and Shiraz showed the maximum distance from the ideal genotype (di+), the minimum distance from the non-ideal genotype (di-), and the minimum SIIG value (0.059, 0.094, and 0.166, respectively); hence, they were introduced as the weakest studied ecotypes. Cluster analysis on significant traits in ANOVA based on the Ward method and using Euclidian distance classified the studied ecotypes into three groups. Sirjan, Kerman, Khatam, Abadeh, and Ardakan ecotypes were placed in the first group, Ashkzar, Shiraz, and Bafgh ecotypes in the second group, and Abarkouh, Isfahan, Semirom, and Rafsanjan in the third group. Grain yield and the most studied traits were higher in the first group ecotypes than in the other groups and the whole mean. Ecotypes of the second group produced the least grain yield and the other studied traits, except for the plant height trait. The third group ecotypes showed average values of the studied traits. The result of the distance between centers of groups obtained from cluster analysis showed that the maximum genetic distance was between ecotypes in the first and second groups. Thus, it could be claimed that the cross between ecotypes in the first and second groups probably produces higher heterosis and genetic variation. For stepwise regression, the essential oil yield trait was selected as the dependent variable, and the other studied traits as independent variables. The result of stepwise regression showed that four traits, including the number of umbel per plant, the number of branches per plant, the number of seed per umbel, and essential oil percentage, were entered the stepwise regression model and could explain 99.5% of the variability among the essential oil yield trait.

The results of cluster analysis using the studied traits are similar to those of ecotype ranking based on the SIIG method. The present study showed that the SIIG method could properly classify the ecotypes. The result of cluster analysis and the SIIG method showed that Sirjan, Kerman, Khatam, Abadeh, and Ardakan were the best ecotypes, which can be used in breeding programs and the cultivation development of this plant. Ashkzar, Shiraz, and Bafgh were the worst ecotypes according to cluster analysis and SIIG values.

Lentil (Lens culinaris Medik) is a cool season seed legume and a good source of nutrients needed by humans, including protein, carbohydrates, vitamins, and minerals. The production of high-yielding and high-plant-height varieties is one of the lentil improvement goals. For this purpose, it is necessary to collect and evaluate germplasm as a base population, along with identifying and utilizing lines with high potential and other desirable traits. The environment has a significant effect on the crop production of this plant. Therefore, direct selection is important for seed yield. Since seed yield depends on the yield components, the yield and its components must be regarded as a group at the selection time to improve the yield. To properly increase yield and economic efficiency, we need to collect desirable lines with desirable genes and transfer these genes to cultivated lines to produce desirable cultivars. Consequently, sufficient information is necessary on accessible genetic materials, which is possible by evaluating different traits.

To assess the model of the simultaneous effect of traits on the lentil seed yield for determining the selection procedure in native lentil lines of Zanjan province, an experiment was conducted in the research farm of the Faculty of Agriculture, Zanjan University, during two cropping years 2017-2018 and 2018-2019. In both years of the experiment, improved cultivars, such as Kimia, Sabz Kohin, Gachsaran, Maragheh, and Bilehsavar, were used as control cultivars. The first-year experiment was conducted in an augmented design based on a randomized complete block design with 200 lines. Each experimental unit included a 1-m row. The distance between the rows was 25 cm, the distance between plants in a row was 5 cm, and the planting depth was 5 cm. Two rows of Kohin-Sabz lentils were planted as margins at the beginning and end of each block. Due to obtaining a sufficient amount of seeds from the first year, the second-year experiment was carried out as a simple lattice design with two replications and larger experimental units for the lines selected from the first year. Each experimental unit included two 1-m lines. The distance between the rows, the distance between plants in a row, and the planting depth were similar to the first-year experiment. Two rows of Kuhin green lentils were planted as margins at the beginning and end of each incomplete block. The measured traits included phenological and morphological traits, yield, and yield components per plant and unit area.

Among the studied traits, the highest coefficient of variation was obtained for the number of seeds, biomass, straw yield, and seed yield. The coefficient of correlation showed that the number of seeds and seed yield were positively and significantly correlated with phenological traits, such as the podding period, physiological maturity, and seed-filing period, as well as morphological traits such as plant height and first branching height, respectively. A positive and significant correlation was observed between the number of seeds and seed yield with the number of pods per plant and biomass per plant. In regression analysis by the stepwise method, plant height was the first trait entered into the model, which could explain 46.8% of the variation related to seed yield per plant. Then, the number of seeds per plant, 1000-seed weight (TSW), straw yield per plant, and the seed-filling period were entered into the model, respectively, which could totally explain 67.5% of the variation related to seed yield per plant. The results of the path analysis showed that the number of seeds per plant had the most considerable direct and positive effect on seed yield, followed by the direct effect of the TSW, plant height, and seed-filling period, respectively. Therefore, these traits would be recommended as the most important and significant traits in the indirect selection of seed yield in lentils. Most of the indirect effects of the traits on seed yield were positive, and the most indirect effects were related to seed-filling period, plant height, and straw yield through the number of seeds per plant. Besides, the seed-filling period through plant height and the plant height through the number of seeds had an indirect effect on seed yield. In factor analysis based on principal component analysis and varimax rotation, six factors explained about 76% of the data variation. The first three factors included the most considerable volume of data variation. The first factor was identified as phenology and height, and the second and third factors were identified as yield and yield components. Results showed that the selection based on these factors would lead to the genesis of the high-yield lines.

The highest coefficient of variation belonged to these traits: the number of seeds, biomass, straw yield, and seed yield. Seed yield per plant had a positive and significant correlation with the phenological traits of the podding period, seed-filling period, and physiological maturity, as well as morphological traits, namely plant height and the height of the first branch. The number of seeds per plant had the most direct effect on seed yield, followed by TSW, plant height, and seed-filling period. Therefore, these traits can be considered the criteria for selecting superior lines. According to the factor analysis results, six factors could justify 77.306% of the data variations.

Cotton yield and most important traits in terms of economic and breeding values are polygenic traits, and direct selection for them has not been very successful. This study was conducted to identify the relationships between yield and its related traits and to determine the most important traits affecting cotton lint-yield.

an experiment including nine genotypes with two commercial varieties of Fars province (Bakhtegan and Golestan) as controls, in a randomized complete blocks design with four replications, was carried out at Darab Agricultural Research Station during two years of 2017 and 2018. In this study, the traits of plant height, monopodial length, monopodial number, sympodial length, sympodial number, number of boll per plant, boll weight, earliness percentage and lint-yield were investigated.

The combined variance analysis results for the studied traits showed that the genotype had a significant effect on all traits except for the monopodial length and the sympodial number at the 1% probability level. The comparison of genotype means showed that the genotypes A-NB414 and A-NBK had the highest lint-yield of 5445 and 5154 kg/ha, respectively. The lint-yield of these two genotypes were significantly different from those of the other genotypes. The genotypes A-NB414 and A-NBK also had higher values for plant height, sympodial number, number of boll per plant, and earliness percentage than the other genotypes. The phenotype correlation analysis showed a significant positive correlation between lint-yield and number of boll per plant (r= 0.80**), boll weight (r= 0.36**), and plant height (r= 0.60**) at the 1% probability level. The stepwise regression analysis results showed that the traits of number of boll per plant, boll weight, plant height, and sympodial length had the most significant effects on cotton lint-yield (R2=0.77). According to the results of the path analysis, the number of boll per plant had the most direct effect on lint-yield (P=0.78). The indirect effect of plant height on lint-yield was exerted through the number of boll per plant. The lint-yield of these two genotypes was significantly different from other genotypes. A-NB414 and A-NBK genotypes were superior to other genotypes in plant height, sympodial number, number of boll per plant, and earliness percentage. The phenotypic correlation showed a high and significant correlation at 1 % level of probability respectively between the lint-yield and the number of boll per plant (r= 0.80**), boll weight (r= 0.36**) and plant height (r= 0.60**). The results of step-by-step regression analysis showed that the traits of boll number, boll weight, plant height and sympodial length explain the most lint-yield changes (R2 = 77.59). According to the results of the path analysis, the most direct effect on the lint-yield trait was related to the number of boll per plant (P=0.78). The most indirect effect of plant height was exerted on lint-yield through the number of boll per plant.

Considering the very high correlation between the lint-yield and the number of boll per plant, it can be concluded that the number of boll per plant is the main factor causing genotype differences in lint-yield. Since boll weight, number of boll per plant and plant height have the largest direct effects on cotton lint-yield, these traits can be used as selection criteria. Additionally, since the number of boll per plant has the most direct and indirect effect on lint-yield, it can be used to increase lint-yield in breeding programs.

Soybean seed contains about 20% oil and 40% protein and is considered as a strategic oilseed plant. Identification of the relationship between morphological traits and seed yield and improving the traits that have strong associtation with seed yield can increase the efficiency of the soybean breeding programs for seed yield improvement.

To determine the suitable indirect selection index for seed yield in soybean, the important morphological traits were evaluated in 10 soybean cultivars in randomized complete block design with three replications and multivariate statistical methods in research farm of Sari University of Agriculture Sciences and Natural Resources, Sari, Iran, in two growing seasons (2020 and 2021).

The results showed that there was significant differences between soybean cultivars for the morphological traits which indicates considerable variation among Iranian soybean cultivars. The results also showed that cv. Telar with the highest number of branches, number of pods plant-1, number of seeds pod-1 and pods weight plant-1 had the highest seed yield (5400 kg.ha-1) in the 2020 and cv. Katol with the tallest plant height, the highest number of branches, pods weight plant-1 and the 100-seed weight had the highest seed yield in 2020 and 2021 (5200 and 7688 kg.ha-1, respectively). The results of multivariate analysis showed that among the studied traits, pods weight plant-1 and plant height directly, the number of pods plant-1 with a direct effect on the pods weight plant-1 and also the 100 seed weight with a direct effect on plant height had highly positive effects on seed yield in soybean. Furthermore, the number of pods plant-1 showed negative relationship with 100 seed weight. Moreover, the results of cluster analysis showed that cv. Telar and cv. Parto were distinguished from other cultivars for short plant height and high number of pods plant-1, cv. Katol for tall plant height and high 100-seed weight and cv. Tapur for high number of seeds pod-1.

Since pods weight plant-1, plant height, number of pods plant-1 and 100 seed weight showed high positive direct effects on seed yield, therefore, cv. Prato and cv. Telar with the highest number of pods plant-1 and cv. Katol with the tallest plant height and the highest 100 seed weight can be considered for seed yield improvement in soybean breeding programs.

The effect of heat stress on yield, yield component and some agronomic traits of barley, was evaluated during the growing season of 2022-2023 using a randomized complete block design with three replications under normal and heat stress conditions. Eight barley cultivars including Nik, Mehr, Khatam, Reyhan, Nosrat, Fajr 30, Yoosef and Afzal were grown in Abarkouh, Yazd, central Iran. The results of combined analysis of variance revealed that cultivar effect was significant in all traits except 1000 grain weight and peduncle length. Heat stress × cultivar interaction was significant for spikes/m2, grains/spike, and grain yield. Heat stress led to a significant decrease in days from sowing to physiological maturity, plant height, peduncle and spike length, spikes/m2, grains/spike, and grain yield and a significant increase in days from sowing to tillering. Grain yield under both conditions had significant negative correlation with days from sowing to tillering. Grain yield had significant positive correlation with spikes/m2 under normal condition and with spikes/m2, and grains/spike under heat stress condition. Stepwise regression results showed that grains/spike and plant height could be used as criteria for increaseing grain yield under heat stress condition. Mean comparison of data for studied cultivars showed that Reyhan and Nosrat genotypes could be suggested for cultivation under both conditions.

Cotton (Gossypium hirsutum) is an important industrial crop where increasing fiber yield is one of the main breeding goals. Several traits are considered in plant breeding, most of which are highly correlated with each other and with yield. This study was conducted to investigate the correlation and path coefficient analysis (causal relationship) between traits and yield components in cotton. The aim of this study was to identify the traits that affect yield, to better understand the relationship between the traits, and to establish a relationship between yield and its components in new cotton varieties.

Seeds from seven of the best cotton hybrids and commercial varieties (as controls) were planted in a four-replication randomized block experiment at the Hashemabad Research Station. Plant height, length and number of unipodial branches, length and number of sympodal branches, number of bolls per plant, boll weight, cotton seed and early maturity were examined. After analysis of variance and comparison of mean traits using Duncan’s method, the correlation coefficient between traits was calculated and stepwise regression analysis and path coefficient analysis were used to identify and determine the traits affecting performance.

The results in terms of quantitative traits showed that the Golestan variety had good quantitative and qualitative traits and gave a high yield. In addition, the SB26 variety was superior to the other varieties in terms of lint content and fiber fineness. The results of the simple correlation between the traits showed that the performance showed a positive and significant correlation with the number of sympodial branches and the number of bolls (0.7), but showed no significant correlation with other traits. The results of the stepwise regression for yield showed that boll number, boll weight and number of sympodial branches were the most important characteristics in determining yield and explained 83.8% of the variance in yield. In addition, the cluster analysis used to group the varieties divided them into 4 separate groups.

In general, the results of the mean comparison of the examined varieties showed that the genotypes TJ82 and SB7 can be proposed for future breeding projects due to a number of characteristics, although there is no significant difference between the varieties in terms of yield of traits, such as e.g. B. a yield of more than 3 tons. In addition, the early maturity, the high proportion of straw and fiber fins makes the SB26 genotype an attractive genotype as an entry genotype for future breeding projects.

In order to investigate the effects of nitrogen rate and time of irrigation on the grain yield and grain yield components of wheat, one experimental as split plot was carried out as split plot design based on randomized complete block design with four replications in research farm of Aliabad Katoul Emam Khomeini agriculture high school during 2018-2019 and 2019-2020. Irrigation time was in main plot (no irrigation, irrigation at stage 33 zadoks, irrigation at stage 70 zadoks) and nitrogen rate was in sub plot (zero, 57.5 kg N/ha, 115 kg N/ha from urea source). Significant interaction wasn’t observed between irrigation treatments and nitrogen rates in almost all traits. The highest yield was obtained by using a supplementary irrigation in stage 70 of Zadox and consumption of 115 kg of pure nitrogen. Grain yield had a positive correlation with biological yield, spike length, spike weight, number of seeds per spike and seed weight per spike. Factor analysis revealed that the first two factors explained 74.5% of the total variation. The results of stepwise regression analysis showed that only the spike weight trait entered the model and alone justified 80.7% of the grain yield variation.

Fenugreek (Trigonella foenum-graecum) is an annual plant belong to Fabaceae and is one of the traditional medicinal plants worldwide. It can provide seed and protein suitable for human's nutrition as well as animals. Water scarcity is a key threat in twenty-first century. On average, 40% of the world land surface are drylands, while this surface area is 90% in Iran. Supplying water requirement of Fenugreek through irrigation is an important factor affecting its growth and yield.

The experiment was conducted as split plots based on randomized complete block design with three replications at the Research Farm, Faculty of Agriculture of shahed university, Iran, in 2014 and 2016. The main-plot was three levels of drought stress, included severe drought stress (20% field capacity), moderate drought stress (40% field capacity), mild drought stress (60% field capacity) and non-drought stress (80% field capacity) as control. Sub plots were nine Fenugreek ecotypes including Neyshabur, Shirvan, Mashhad, Tabriz, Roudsar, Isfahan, Hamadan, Ardestan and Shiraz. At maturity, and the plants were harvested from the soil surface and the plant height and number of lateral branches, number of pod per plant, number of seed per pod, 1000 seed weight, seed yield and aboveground biological yield were measured in the lab. Statistical analysis carried out using SPSS version 16 software. Significant difference was set at p ≤ 0.05 by using Duncan’s multiple range test.

Results of stepwise regression showed that the traits including biomass, harvest index, branch length and number of pods per plant explained 96.7% of grain yield variation, respectively. Factor analysis for morphologic, yield and component yield traits showed the first three independent factors explained 93.48% of total variance in all genotypes. Days to maturity with 36.47% of total variance had the highest amount in the first factor, while, number of seeds per plant and seed yield with 29.74% and 27.07% of total variance were ranked as second and third factors, respectively. Cluster analysis by Ward’s minimum variance, clustered ecotypes into three groups including 1- Isfahan, Ardestan, Hamedan and Shiraz 2- Mashhad and Tabriz 3- Shirvan, Rudsar and Neyshabur. The results showed that, the plant height, Internode length, number of pod and seed per plant, 1000 seed weight, biological and seed yield and harvest index significantly affected by drought stress and ecotypes. The highest plant height, number of pods, 1000 seed weight, biomass, seed yield and harvest index was recorded in Shirvan ecotype while, the longest day to maturity and height of first pod were observed in Neyshabur ecotype at 80% FC. The highest plant height, the first formed pod, 1000 seed weight, seed yield and harvest index in Shirvan ecotype were observed in the 40% FC.ConclusionDrought stress reduced all studied traits in all Fenugreek ecotypes in this experiment. For seed yield, the performance of shirvan ecotype was the best compare to other ectypes in control and mild and moderate stress condition. The highest distance of the first pod from the soil surface in the control condition was observed in the Neyshabur ecotype but in the moderate stress condition in Shirvan ecotype, this trait is important for the mechanized cultivation. Based on the results, there is a reliable variation amongst different Iranian Fenugreek ecotypes and they could use for breeding programs against drought stress. It also seems that Shirvan ecotype of Fenugreek can be considered for stable seed and biomass production under moderate drought stress and normal conditions.

Due to the increasing need of the country to imported edible oil and rapeseed importance among oilseeds, efforts to increase its grain yield and oil content are of high importance. Therefore, recognizing the traits that increase grain yield of rapeseed has an important role in the success of breeding programs. Thus, sixteen rapeseed genotypes were evaluated in a randomized complete block design with three replications in three regions with different climatic conditions in Iran, including Karaj, Isfahan, and Hamadan in 2016-2017. Traits such as number of pods per plant, number of seeds per pod, grain yield, 1000-grain weight, plant height, height of the first branch, stem diameter, oil percent, number of days to flowering, number of days to the end of flowering, duration of flowering, and number of days to maturity were measured. Stepwise regression analysis showed that number of grain/pod, number of days to maturity and number of pods/plant (R2 = 97.7), number of pods/plant and number of days to maturity (R2 =78.4) and number of days to maturity and number of grains/pod (R2 = 45.5) accounted for total variations of grain yield in Karaj, Isfahan and Hamadan, respectively. The results showed that the number of days to maturity, number of pods/plant, number of grain/pods, stem diameter and plant height had the greatest positive effect on grain yield and oil content. Therefore, these traits can be used as suitable selection tools for increasing grain and oil yield in winter rapeseed breeding programs

Pests and their controlling pesticides are among the most serious threats to the health of agricultural products. The present study was aimed to investigate the effect of genotype and the possibility of replacing chemical pesticides controlling fruit borer by some compounds of natural origin for plant traits improvement and damage reduction of tomato fruit borer. Factorial experiment was done in the template of randomized complete block design with three repetitions.

Factors include 9 levels of pest control compounds and 5 varieties. Compounds involves Salicylic acid (5 and 15 mM), Jasmonic acid (50 and 100 μM), Abamactin (750 and 1500 mg/L), chlorpyrifos (1250 and 2500 mg/L) and control. Measured traits involve morphological traits (fruit yield, fruit weigh, numbers of fruit per cluster, plant height, chlorophyll index), phonological traits (days to flowering and days to physiological maturation), phytochemical traits (TA, TSS, and Vitamin C) and relative properties to evaluating resistance to fruit borer (the percentage of leaf and fruit damage).

Results of analysis of variance and mean comparison test present significant variation between varieties. The maximum fruit yield per plant was related to PA-136 variety with applications of two-levels of Chloropyrus and Jasonic acid, PA-162 variety with application of first level of Abamactin, second level of Salicylic acid and PA-135 and PA-688 varieties with the second level of Chloropyrus. Reducing pest damage on leaf and fruit in applying Salicylic acid, Jasonic acid is suitable and evaluated the same level of chemical control use. The highest significant positive correlation with yield related to single fruit weight (r=0.48**) and the highest significant negative correlation was related to days to flowering (r= -0.52**).

In stepwise regression analysis of single plant yield as a dependent variable, three traits including days to flowering, single fruit weight, and a percentage of pest damage on leaf as an most important traits introduced in the model that totally explained 49% of variation. Path analysis results indicated that the highest positive direct effect(0.42) was related to single fruit weight, and the highest indirect effects(-0.047) was also related to this trait via days to flowering. Four first components were chosen in principal component analysis which verifying totally 62.5% of phenotypes variation. The results can be used in the design of breeding programs for plant trait improvement and integrated pest management of tomato fruit borer.

To evaluate 38 maize hybrids, an experiment based on randomized complete block design with three replications at the Moghan Agriculture Research Station during the 2020 growing season. The results indicated that a significant difference had among maize hybrids for ear yield, plant height, ear height, leaf temperature, chlorophyll index, maximum fluorescence (Fm), variable fluorescence (Fv) and maximum quantum yield of PSII (Fv/Fm). K74/2-2-1-4-1-1-1 × K3640/3 hybrid (No. 9) with high ear yield and photosynthetic system introduced the best hybrid to comparing with other hybrids. The range of heritability was from 3% for minimum fluorescence (Fo) to 71 % for ear height. Path analysis revealed that minimum fluorescence (Fo) and leaf temperature had the highest and positive direct effects on ear yield. The cluster analysis, with ear yield, plant height, ear height, leaf temperature, chlorophyll index, and quantum yield, was classified 38 maize hybrids in three different groups, and the third group with 9 (K74/2-2-1-4-1-1-1 × K3640/3) was the most desirable.

Path analysis is one of the oldest methods of knowing the direct and indirect effects of traits on yield, but the widespread application of this approach is limited by the problem of multi-collinearity, that has been addressed in the present study. A total of 298 bread wheat genotypes were evaluated during the two cropping years in the lattice design and the path analysis of grain yield was studied by simple and ridge methods. The highest direct effect on grain yield in the first year were related to spike weight, number of seeds and 1000-seed weight, respectively, and in the second year were related to number of seeds, 1000-seed weight and spike weight, respectively. Spike weight and number of seeds in the first year had an indirect effect on yield through each other as well as through spike length and plant height. In the second year, the number of seeds and 1000-seed weight through the weight of spikes showed the most indirect effect. Day to booting and day to flowering traits in both years and spike weight in the second year had a high multi-collinearity that the use of constant k =0.10 in ridge causal analysis overcame this problem. Finally, in contrast to simple path analysis, ridge path analysis showed that the spike weight through the number of seeds had an indirect effect on grain yield in the second year. According to the results, it is recommended to consider the issue of multi-collinearity between traits in future path analysis studies.

This study was conducted to evaluate the relationships among some of the agronomic and physiological traits of twelve Thymus daenensis subsp. daenensis ecotypes under normal and salt (120 mM NaCl) stress conditions in a factorial experiment using randomized complete block design with three replications. Shoot dry weight under both conditions had significant positive correlation with chlorophyll a and b, potassium, relative water content, canopy area, leaf length and number of stems in plant and had significant negative correlation with sodium to potassium ratio and ion leakage. According to stepwise regression results, canopy area and carotenoid under normal condition and leaf length and number of stems in plant under salt stress condition were entered to the model. The result of path analysis showed that canopy area had the most positive direct effect on shoot dry weight under normal condition and leaf length and number of stems in plant had positive effects on shoot dry weight under salt stress condition.

Coneflower herbal medicinal plant is from the Asteraceae family, native to North America. Because of its immune-boosting properties, it is used to treat a variety of pathogens. The seed germination stage is one of the crucial and crucial stages in the growth cycle of plant species that can play an important role in the production process by optimal establishment of seedlings. Seed of Coneflower germinates and grows very slowly and weakly. Therefore, the use of some plant growth regulators, such as the gibberellin hormone, can play an important role in improving seed germination. The aim of this study was investigate the effect of hormone seed priming using gibberellin on seed germination quality of Coneflower.

A factorial experiment was conducted based on the complete randomized design arranged with three replications. The experiment was conducted at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan, 2018. Experimental treatments were different concentrations of gibberellin (0, 50, 100, 200, 400, and 800 mg/l) as the first factor and the durations of seed priming (12, 24, and 48 hour) as the second factor.

Results of in vitro studies showed that the interaction of gibberellin in priming time on percentage, rate and mean germination time, root and shoot length, seed vigor index, peroxidase activity at 1% and Seed soluble protein content was significant at 5% level. Seed germination quality and protein content increased by the application of 200 mg/l gibberellin for the 24 hours, whereas at the concentrations of 400 and 800 mg/l, gibberellin reduced germination quality and antioxidant enzymes activities. Results of stepwise regression models of antioxidant enzymes activity and protein content with germination indices showed that these traits were significantly entered into the prediction model. It was observed that in all traits except for the rate and the mean germination time, the amount of protein entered the prediction equation. In general, stepwise regression models predicted stem length and power index better than other traits and showed the highest coefficients in these traits with values of 0.85 and 0.83. Also, catalase and peroxidase activities were significantly correlated with rate and mean germination time only. The amount of soluble protein had a positive and significant correlation with all studied traits except germination rate and mean germination time. The highest correlation coefficients for protein content were obtained from longitudinal power index with correlation coefficient (r = 0.856).

Based on the obtained results, the best hormone priming treatment was 200 mg/l gibberellin for the durations of 24 hour. 

1- The role of gibberellin hormone on seed germination traits Coneflower was evaluated2- The effect of gibberellin hormone on the activity of antioxidant enzymes and soluble proteins during seed germination was investigated.

In order to identification of effective traits on root yield and also determination of cause-and-effect relationships between in 20 different sugar beet cultivars, an experiment was carried out in West Azarbaijan Agricultural and Natural Resources Research and Education Center, Miandoab Research Station based on RCB design with four replications in 2017 crop season. The assayed traits included root yield, sugar yield, white sugar yield, sugar content, white sugar content, extraction coefficient of sugar, root α-amino nitrogen, sodium and potassium, alkalinity coefficient and molasses sugar. The results of analysis of variance showed that difference between studied cultivars for amino nitrogen (α-N) all traits was significant at the 0.05 probability level and for other traits was significant at the 0.01 probability level. Phenotypic and genotypic coefficients of variation for most traits were high, indicating relatively high variability in studied cultivars for evaluated traits. Correlation coefficients between traits showed that there is the most negative and significant correlation between root yield trait with sugar content (-0.62), white sugar content (-0.53), alkalinity coefficient (-0.52), potassium (-0.49), sodium (-0.45) and also molasses sugar content (-049) traits, and the most positive and significant correlation with sugar yield (0.95), white sugar yield (0.90) and extraction coefficient of sugar (0.58) traits, respectively. In multiple regression analysis by stepwise method, sugar content and white sugar content, amino nitrogen and alkalinity coefficient traits were entered into model, respectively, that explained 82 percent of root yield variations. Based on correlation, stepwise regression and path analysis results, among the studied traits, amino nitrogen (0.35) and white sugar content
(-0.31) traits with most direct effect were effective on root yield and will be useful in identifying genotypes.

Determination of genetic diversity level is fundamental for identification of desirable parents to be used in different breeding programs, and molecular markers have been succssfully taken for the analysis of genetic diversity in various crops. The objective of this study was to inversitgate genetic diversity among 28 genotypes of barley using root and shoot characters and 14 ISSR primers through two separate experiments (greenhouse and molecular experiments).

The greenhouse experiment was carried out as randomized complete block design with two replications in the research greenhouse of Faculty of Agriculture, University of Tabriz, Iran. The traits measured in the greenhouse were root dry weight, root volume, shoot dry weight and ratio of root to shoot dry weight. The molecular experiment was conducted to study the diversity of barley genotypes using 14 ISSR primers. The polymorphic information content and marker index were calculated for each ISSR primer.

Analysis of variance showed significant differences among the genotypes under study for all traits. According to the mean comparisons, genotypes 3, 5, 9 and 20 had higher mean in terms of all characters. The cluster analysis, based on Ward 's algorithm and Euclidean distance, grouped genotypes in four clusters. Group 3 had the highest mean in terms of all of the studied characters. Out of 14 ISSR primers used, 11 primers generated scorable and appropriate banding pattern. A total of 559 polymorphic bands with 80-3000 bp were produced. Polymorphic information content was estimated to be between 0.116 and 0.252 with the average of 0.187. The marker index ranged from 3.528 to 27.972 with the mean of 9.704. Classification of the studied barley genotypes was conducted by molecular data using neighbor joining algorithm based on distance coefficient of number of differences, which assigned the genotypes into four groups. There was a concordance between the grouping of genotypes based on molecular data and the characters in the greenhouse, but this concordance was not complete. Association analysis of ISSR markers with measured characteristics of barley genotypes showed that ISSR1 and ISSR5 had significant relationship with most of the root and shoot traits.

Highgenetic diversity was observed among barley genotypes with respect to root and shoot traits. The results showed that ISSR primers have the ability to separate barley genotypes from each other. Also, it seems that ISSR markers under study can be used in marker assisted selection of barley genotypes in breeding programs.