JWSS - Journal of Water and Soil Science

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Astracantha adscendens is an endemic species in Iran growing on alpine and above alpine timberline habitats on the Zagross Mountain Range. These habitats are characterized by steep slopes, heavy snowfalls and long ice formation periods. The present study was carried out in Chelgerd, Bakhtiari, and Fereidan, Isfahan. Slopes, elevation above sea-level, and magnetic north azimuth were measured. The canopy cover was also measured along four radii in upward, downward, left and right directions. Regression analysis was performed for the measured values of plant and environmental factors.

The results revealed that the upward radius had a high negative correlation with slope changes while the downward radius showed no relationship with slope variations. The two left and right radii had a high and positive relationship with each other, both reducing in length as the slope steepness increased. Shrub volume decreases with increasing slope steepness. Plant shape was classified into seven groups using Sorenson similarity index and constructing the dendrogram. Snow pressure bends the stem toward the soil surface. Snow gliding pressure scratches stem and its base buds above the bent stem. Soil and debris move downward the slope as a result of snow gliding and rainfall runoff as well as wildlife and domestic animals. Snow gliding along with other natural factors have various effects on A. adscendens plant form which can be grouped under three categories: direct mechanical effect of snow, physiological effect of snow, and indirect effect of precipitation and wildlife. The environmental factors and plant physiological responses to them change the A. adscendens plant form from a funnel or ob-conical shape to a semi-funnel or semi ob-conical form.

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In order to evaluate the morphological and agronomic characteristics of 19 land races of onions and one foreign cultivar (Yellow Sweet Spanish), an experiment was conducted in 1998 at the Research Farm of the College of Agriculture, Isfahan University of Technology.

 Analysis of variance showed significant differences among genotypes for all of the morphological and agronomic traits. Dry weight and number of days to emergence had the highest and lowest coefficients of genetic variability, respectively. Plant fresh weight, yield of 30 plants and total yield also had high coefficients of variability. Broad sense heritability estimates were high for all of the traits, indicating low environmental affects them. Based on cluster analysis and plot of the first two canonical variables, the genotypes were classified in four groups with different agronomic traits. Canonical discriminant analysis based on nine agronomic traits introduced three canonical variables which justified 99.9 percent of the total variation among characters. Principal component analysis revealed four components while factor analysis showed three factors which explained 87.3 and 95.5 percent of the total variation among characters, respectively. The first and second factors were related to adaptation and assimilate translocation, respectively. Bulb diameter, bulb height and bulb weight in positive directions and sensitivity to Fusarium in negative direction had greater loads in the third factor.

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This experiment was conducted to study genetic variation for electrophoretic seed protein patterns and their relations with some seed characteristics such as protein and oil percentages, chemical compositions and 100-seed weight among 270 soybean (Glycine max L. Moench) genotypes.

Among different electrophoresis procedures examined, 10% and 4.5% concentrations of acrylamide for resolving and stacking gels, respectively, 13.5 mg/ml concentration of protein buffer extraction, injection of 10 microlitre sample injection into gel hollows, 2.5 miliamper and 2-hours staining period were determined as the best combination to achieve clear bands and good separation. Based on relative mobility on gel, 30 protein bands were observed, of which only 5 varied among genotypes. In general, 8 electrophoretic patterns were recognized. Cluster analysis based on qualitative evaluation of patterns grouped the genotypes in 8 clusters and classified different bands in three groups. Simple concordance (matching) coefficients between protein bands with relative mobilities of 2.5% and 49.5% were zero, which is an indication of their independent occurrence. Probably, these bands are coded with one gene that in dominant and recessive homozygous genotypes appear as a single band at different positions on the gel. Analysis of variance revealed significant differences (P<0.05) among protein patterns for protein and oil percentages. Correlation coefficients between variable protein bands and studied traits showed a positive and significant relation (P<0.05) of bands with relative mobility of 3.5 and 49.5 with protein and phosphorous contents of the seeds, respectively. Protein patterns having band with relative mobility of 49.5 had the highest phosphorous content. Black hilum color of seeds was related to protein band with relative mobility of 52.

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Genetic variation of 300 genotypes of durum wheat comprising CIMMYT/ICARDA and Iranian germplasm was evaluated in 1999-2000 at Researh Farm of College of Agriculture, Isfahan University of Technology located at Lavark, NaJaf-Abad. Days to heading, days to maturity, plant height, spike length, grain weight per spike, number of grain per spike, number of spikes per m², 1000-grain weight, test weight, grain yield, biological yield, and harvest index were recorded. Coefficients of correlation, step-wise regression, factor analysis and cluster analysis of characters and genotypes were conducted using the studied traits. Results indicated that considerable genetic variations exist for the traits and, in particular for grain yield, harvest index, number of spikes per unit area and number of grain per spike. Grain yield had a positive and significant correlation with days to heading, days to maturity, number of grain per spike and grain weight per spike. Factor analysis for the genotypes detected 6 factors, which explained 76.7 percent of the total variation among data. These factors basically involved potential of assimilate distribution, different aspects of plant storage, source-sink relationships, plant height and tillering potential. Cluster analysis was similar to factor analysis in grouping the characters. According to cluster analysis, the genotypes were calssified into 6 clusters with significant differences among all groups. Mean comparisons of traits in these groups showed that genotypes of groups 5 and 6 were superior in grain yield and harvest index and are beneficial to the local durum breeding objectives.

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To study the genetic diversity in 100 genotypes of rice, an experiment was conducted at the research farm of Rice Research Institute of Iran. The experimental design was a 10x10 simple lattice. The genotypes, mostly belonging to Isfahan Province and north of Iran, were evaluated on the basis of morphological traits and yield components. The results of analysis of variance demonstrated that the differences among genotypes were highly significant (p < 0/01) for all traits. High values of phenotypic and genotypic coefficients of variation were obtained for most traits, indicating high variability in the traits under study. Factor analysis revealed three factors which determined 90 percent of yeild variation and were named “grain number”, “plant type and structure” and “grain shape”, respectively. Cluster analysis by “Cubic Clustering Criterion” and “Pseudo Hotelling T² Test” grouped genotypes in four clusters. Analysis of variance showed that the differences among clusters were highly significant for most traits.

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Agropyron is one of the most resistant plants to biotic and abiotic stresses. It plays an important role in forage yield in rangelands. Genetic variability based on different markers is the important step in crop improvement. In order to evaluate the genetic variation of different Agropyron species based on morphological and chemical traits, this experiment was carried out in the Agriculture and Natural Resources Research Center of Kermanshah. The tiller numbers, spike length, spikelet numbers, length of flag leaf, width of flag leaf, plant height, peduncle length, ash percentage, organic matter, fiber, dry matter, fat and crude protein were registered. Statistical analysis of data was done by SPSS software. According to cluster analysis the tetraploid genotypes were classified into 5 clusters. Based on principal components analysis the length of flag leaf, spike length and plant height, and among the chemical traits of the ash percentage, organic matter, and crude protein had the highest portions of variance. The genetic parameters such as PCV, GCV, ECV, Hb and Ga for length of flag leaf were 0.274, 0.169, 0.215, 0.382, 3.05 and for spike length were 30.96, 21.64,22.139, 0.48, 5.786 and for plant height were 0.16, 0.084, 0.136,0.276, 6.054, respectively.

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Potato (Solanum tuberosum L.) has relatively weak root system and requires high nitrogen fertilizer which is costly and may pose environmental pollution. This study was conducted to compare root morphological characteristics and nitrogen uptake of some potato cultivars growing in Iran. A greenhouse experiment using a completely randomized design with 3 replications and 8 potato cultivars including: Arinda, Agria, Premiere, Diamant, Concord, Marfona, Marodana and Nevita was conducted at Isfahan University of Technology, Isfahan. Virus-free seed tubers were planted and grown up to flowering stage. The plants were then harvested and their root length (RL), root average diameter (RAD) and root surface area (RSA) were determined using a Delta-T Scan image analysis system and Windias software. Root length density (RLD), root length and shoot weight ratio (R/S) were also calculated. Dry mater production and nitrogen accumulation (total nitrogen uptake) (PNA) were also determined. Soil inorganic nitrogen was measured before planting and after harvest. All measured parameters, except RAD, were significantly (p<0.05) affected by cultivar. Large differences observed between cultivars for all traits indicated genetic diversity among the studied potato cultivars. The highest and the lowest values of RL, RLD, RSA, R/S, RDW and PNA were found in Marfona and Nevita respectively. Based on cluster analysis, cultivars were divided into four different groups. Under the condition of this study, Marfona was superior whereas Arinda, Nevita, Marodana and Agria were inferior. Due to the high differences in root morphological characteristics and nitrogen uptake among potato cultivars, plant breeders may produce cultivars with larger root volumes and high nitrogen uptake.

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To facilitate the interpretation of data from a genotype by environment experiment (GE), a cluster method is proposed to group genotypics according to their response to the environments especially when the GE interaction is large. The interaction structure of two-way classification data often can be identified if the data stratified into homogeneous subsets. In this paper four GE interaction cluster methods are proposed for this purpose. The stability of the 10 maize hybrids including 9 hybrids that were the best hybrids in yield trials and KSC 301 (check hybrid) were evaluated for 2 years in 4 locations of Iran. The randomized complete block design with 4 replications was conducted for each environment with different layouts. Simple analysis of variance revealed significant genetic differences between hybrids for grain yield. The results of combined analysis of variance indicated that genotype × year, genotype × location, and genotype × year × location interaction effects were significant (P < 0.01). Results also showed that models 1 and 3 and models 2 and 4 had the same responses. Hybrids 8 (K1263/1 × KE8212/12) with high yield stability in both models 1 and 3 were in one group and other hybrids were in another group. In models 2 and 4 results led to 3 groups: Group1 included hybrids 3, 7 and 9 that were very stable and had high yield group 2 included hybrid 1 alone that had medium stability and yield and group 3 included other hybrids that had low stability and yield.

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In order to determine the most important quantitative and qualitative characteristics of pomegranate fruit and its components for categorizing the genotypes, a study was carried out using 24 genotypes. In this study 28 quantitative and qualitative characteristics of pomegranate fruit and seed were evaluated. Analysis of variance showed that all of the characteristics in examined genotypes were significant, showing high variability in characteristics. Results of simple correlation analysis showed the existence of significant, positive and negative correlations among some important characteristics. Also, factor analysis showed that most of fruit juice, aril and seed characteristics constituted the main factors. Effective characteristics categorized in seven factors accounted for 89% of total variance. For each factor, eigen value more than 0.7 was considered significant. Cluster analysis was performed using these seven factors and genotypes, in the distance of 9, were divided into 5 main clusters. These groups were mainly distinct in fruit flavor and soft seededness. Furthermore, by using three main factors, genotypes positions determined in 3-plot analysis, which distinguished sweeter genotypes from sweet-sour and sour genotypes.

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In order to study the genetic diversity of 75 Iranian rice genotypes (45 Iranian land race, 25 improved cultivars, and 5 exotic cultivars) with respect to their salinity tolerance at seedling stage and to determine tolerance indices, based on biomass, genotypic code and Na⁺/K⁺ ratio a factorial experiment in randomized complete block design with three replications was conducted under control and salt stress(1.2, 4 and 8 dSm^-1) conditions at Rasht Rice Research Institute. Root and shoot length, root and shoot dry weight, Na⁺ and K⁺ concentrations, and genetic score were studied. Significant differences were detected among genotypes for all traits. Shoot length and K⁺ concentration had the highest and lowest heritability estimates, respectively. Genetic score under salinity stress showed that Tarom-mahalli, Gharib, Shahpasand Mazandaran and Ahlami-Tarom with more biological yield root and shoot lenghes, and low Na⁺/K⁺ ratio were tolerant. Khazar, Speedroud, IR28 and IR29 were the most sensitive cultivars. Tarommahalli, Ahlamitarom, Rashti and Chparsar had low tolerance index, mean productivity, stress sensitive index, geometric mean index, stress tolerance index and harmonic mean for genetic score, whereas Khazar and Speedroud had high values for theses indices. Cluster analysis, based on seedling traits at 4 and 8 dS.m^-1 divided the genotypes to three groups. Tolerante group had low genetic score and Na⁺/K⁺ ratio, but high root and shoot dry weight, biomass, root and shoot length.

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This experiment was conducted to investigate the genetic diversity, identify traits explaining yield variation, recognize relationships between traits and classify accessions in a Iranian and forign germplasem of tall fescue. Forty six Iranian and foreign tall fescue accessions were surveyed for Phenological, morphological and agronomical characters in a randomized complete block design with three replications in field for 2 years. Significant differences were observed for all of the characters, indicating broad variation in this germplasm. Iranian accessions had a better performance for most of the traits in both years indicating their high potential for developing commercial varieties in breeding programs. Basis on stepwise regression analysis, crown width justified the majority of hay yield variation, followed by establishment rate, percentage of dry matter, height and number of stem. Hence, these characters could be used for selecting high yielding cultivars. Factor analysis revealed 4 factors which explained more than 80 percent of the total variation and confirmed the results of regression analysis. Using UPGMA method, cluster analysis revealed five groups. Accessions with similar country of origin or same ecological conditions were grouped in same cluster. Regarding the morphological characters the best accessions were identified to be used in the further breeding projects.

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Discrimination function analysis is a method of multivariate analysis that can be used for determination of validity in cluster analysis. In this study, Fisher’s linear discrimination function analysis was used to evaluate the results from different methods of cluster analysis (i.e. different distance criteria, different cluster procedures, standardized and un-standardized data). Furthermore, Hotelling T2, CCC plot and multivariate analysis of variance were used to support the results. To achieve the goals, 8 rapeseed genotypes were planted in a randomized complete block design with three replications in Rice Research Institute of Iran, Rasht, durin 2005-2006, and 14 characteristics were measured. Analysis of variance based on the randomized complete block design showed significant differences between genotypes for all the studied traits. Comparison of means between genotypes indicated that the genotype Hyola401 for grain yield and most of the measured characteristics was better than the other genotypes. Evaluation of phenotypic and genotypic coefficient of variations showed that most of the traits had high variability in the population. Discrimination function analysis showed that the Euclidean distance criterion was better than others and a desirable clustering was obtained by this criterion. Also, all of the data standardization methods produced similar clusters and were better than un-standardized data. Based on evaluation of dendrograms derived from different methods of cluster analysis determined that the UPGMA, complete linkage and Ward’s minimum variance methods were better than the other methods, and grouped the genotypes into three clusters. Fisher’s linear discrimination function analysis showed that UPGMA and Ward's minimum variance methods with clustering validity of 87.5 percent, was more suitable than other cluster analysis methods however, discrimination analysis grouped genotypes into two clusters. Tests of Hotelling T2, CCC plot and multivariate analysis of variance supported the results from the discrimination function analysis. It seems that the UPGMA and Ward's minimum variance procedures based on Euclidean distance criterion of standardized data function better in grouping genotypes, yet, the use of discrimination function analysis is recommended to confirm the results and determine the actual groups.

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Canola (Brassica napus L.) as one of the oilseed crops has recently received lots of attention due to its suitable oil quality and high oil percentage. To evaluate the effect of water deficit stress on canola genotypes with regard to yield, drought tolerance quantitative indices and identify drought tolerant genotypes, an experiment was conducted in research farm of seed and plant improvement Institute (Karaj) using completely randomized block design with four replications, and 25 genotypes under two stress and non stress conditions. Genotypes were evaluated regarding drought tolerance. Drought tolerance quantitative indices include MP, GMP, STI, SSI and TOL. Result of variance analysis showed significant differences among genotypes as regards all indices and seed yield of genotypes in both conditions at 1% probability level. MP, GMP and STI indices were selected as the best indices for selection of tolerant genotypes in regard to analysis of correlation between seed yield in two stress and non stress conditions and drought tolerance indices. Results indicated that Genotype Vectra was the best genotype, because of its proper mean yield in both stress and non stress conditions. Multivariate biplot figure display showed that MP, GMP and STI indices had high correlation coefficient with each other, and tolerant genotypes were located near tolerance indices. Also results of three dimensional scatter plot and cluster analysis indicated that genotypes Modena, Jura, Eshydromel, Vectra, Dante, Zarfam, Esbetty and Olano were tolerant to drought stress, and genotypes Olpop, GKHelena, RG4504 and Olphi were sensitive genotypes.

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In order to classify and determine the plant communities in Karkas mountainsides, central Iran, quantitative data of 46 environmental characteristics including climate (12 characteristics), soil (26 characteristics), geology and physiology (8 characteristics), were analyzed based on partial Euclidean distance indicator using minimum variation method. The results showed the clustered separation of studied sites at 68% similarity level with three different growth places. Of these 46 factors, 24 factors (8 climate characteristics and 16 soil characteristics) were effective in this classification at 95% certainty level. Only 24 of these 46 factors were effective in this classification at 95% certainty level. These 24 effective factors were divided into 8 climate and 16 soil characteristics. In another classification, combinational percentage index of 17 plant species were investigated as an effective factor in separating growth place and determining the plant communities. Result of cluster classification indicated that the studied sites cold be classified to 3 habitats.

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The purpose of this study was to compare the physical and chemical characteristics of soils covered with vegetation and soils without vegetation in Dagh-e- Sorkh Ardestan area.To achieve the goal, first the vegetation was classified using physiognomic method, and for each vegetation type, the distinctive area was specified for soil and vegetation sampling. Vegetation sampling was done by stratified random sampling. Alongside pursuing the case, twenty two soil physical and chemical factors were investigated also for each growth type and area without vegetation. In the next step, to investigate the similarities and dissimilarities of the soils of desert areas by means of PC-ORD software, the cluster analysis was performe. After simplifying the one-way ANOVA, the most important soil factors which were effective in causing differences in the area’s soils were identified. Results show that the soils of area covered with vegetation differed much from the soils without vegetation physically in such a way that, the soil texture became heavier and gravel percentage became less in the areas without vegetation. Regarding the chemical characteristics, the frequencies of sodium, magnesium, calcium and chlorines and electrical conductivity were highly different. Because of topographic condition of land without vegetation, runoff is directed to this place and deposits salts there. Also, high groundwater level and capillary flowing salts are the important reasons for the salinity of this place. These are the limiting factors for the vegetation establishment in the desert areas of Ardestan.

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The temporal and spatial vegetation dynamics is highly dependent on many different environmental and biophysical factors. Among these, climate is one of the most important factors that influence the growth and condition of vegetation. Of the abiotic factors affecting the geographic distribution of vegetation type, climate is probably the most important. Ecological research has traditionally aimed to generalize vegetation types that are assumed to be homogenous. Most of climatic classifications related to bioclimate are focused on limited climatic factors such as temperatue, precipitation and combination of them. As climate is a compound phenomena using limited factors cannot show the climate of a region, and as a result most climatic factors must be considered in bioclimatic classification. Therefore, a climatic study using various climatic factors could reveal the effective factors in distribution of vegetation. In order to determine bioclimatic zones in Chahar-Mahal & Bakhtiari province using multivariate statistical method, 71 climatic variables, which were more important in plant ecological conditions, were selected and evaluated by the factor analysis. The factor analysis revealed that the first three factors which explain %91.8 of total variance among the selected variables were temperature, precipitation, and radiation. According to results and using hierarchical cluster analysis in Ward’s method, bioclimatic classification in Chahar-Mahal province was carried out and 5 bioclimatic zones were found. In addition, Chahar-Mahal province was classified by 4 traditional climatic classification methods (Koppen, Gaussen, Emberger and De Martonne) and those classes were compared to climatic classes obtained by multivariate statistical method. The latter comparison was suggestive of the fact that multivariate statistical method provides a more appropriate classification in comparison to the traditional methods, specially because more dominant vegetation species could be defined for each of the newly described climatic classes. Furthermore, dominant species were determined for each climatic region.

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The aim of the study was to investigate the effects of land use on soil quality parameters using multivariate statistical analysis. Soil samples (0-25 and 25-50 cm depths) were taken from three land uses in forest area of Marivan including forest, rangeland, and cultivated land. Soil characteristics of pH, EC, sand, silt, clay and CaCO3 content, water-stable aggregates and their organic carbon content were measured. Principal component, cluster and discriminant analyses were used to evaluate the soil quality. Principal component analysis classified soil properties into five factors. The most important factors were soil aggregates organic carbon content and aggregate stability indices. Schematic distribution of factors and also cluster analysis showed the same pattern. Soil aggregates organic carbon content, water-stable aggregates and aggregate stability indices were the most sensitive factors to land use changes. These soil properties and factors had the same pattern in forest and rangeland, but significantly reduced in the cultivated land use. Land use change from forest to cultivated land resulted in significant decrease of aggregates organic carbon content, water-stable aggregates and also an increase of pH. The results showed the usefulness of multivariate statistical methods for integration of the soil properties and determination of different soil quality indices.

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