جستجوی مقالات مرتبط با کلیدواژه « مولفه های اصلی » در نشریات گروه « کشاورزی »

Soil has various tasks or functions, including the ability to produce crops, store carbon, store water, cycle nutrients and purify water. Soil functions have a high correlation with soil quality. Soil quality indices are often regional and to determine it, it is not possible to consistently use a set of idicators and indices in all regions. In this research, Additive Soil Quality Index (SQIa), the Weighted Additive Soil Quality Index (SQIw) and the Nemero Soil Quality Index (NQI) and the effect of effective characteristics on soil quality in surface soil (0-30 cm) and in the yield of 206 wheat field of East Azarbaijan Province (Tabriz Plain) in 2017 was investigated by measuring physical and chemical properties of soils and wheat grain yield. Organic carbon, bulk density, aveilble potassium and aveilble phosphorus and electrical conductivity were selected as The minimum data set (MDS) using principal component analysis (PCA). Then SQIa, SQIw and NQI were determined using TDS and MDS. The results showed that there is a correlation between wheat yield and soil quality indices using MDS (r=0.60-0.63) and using TDS (r=0.56-0.60) also there was a significant correlation (p <0.01) between the use of TDS and MDS in NQI (r=0.81), SQIw(r=0.84) and SQIa (r=0.88) (p<0.01). Therefore, all three investigated indices are suitable for the study area and using MDS is more suitable than the method of using TDS due to relatively higher correlation and number of features and lower cost.

Pigeon pea (Cajanus cajan (L.) Millspaugh) is the sixth most important legume crop in the world. This plant is multi-purpose which is used as unripe seeds and pods, splits and fodder, it is also suitable for cultivation in tropical and subtropical regions and it is compatible with poor soil and dry areas. The seeds of this plant are rich in protein (containing more than 30 percentage of seed weight). In this study, the genetic diversity of different Pigeon pea genotypes has been investigated using morphological traits.

This study was carried out in order to investigate agronomic and morphological characteristics of different genotypes of pigeon pea collected from Sistan and Baluchistan province in 2019. 27 Agronomical and morphological traits related to leaves, flowers, pods and seeds were investigated in 30 different genotypes of pigeon pea available in the collection of the Iranian National Plant Gene Bank. the data were analyzed using SPSS and STAR statistical softwares. Correlation and principal components analysis were done and, cluster analysis was done by Ward's method for classifing genotypes.

The results showed that the number of seeds per pod, number of secondary branches, and number of seeds per plant had the highest coefficient of variation, and among the investigated qualitative traits, the highest Shannon index was observed in the pod color, petal vein color, and seed color, respectively. Correlation analysis showed that there was a significant correlation between most of the measured traits. According to the results, the highest correlation was observed between the weight of the plant with the weight of pods and the number of days until the beginning of flowering with the number of days until maturity. In the cluster analysis, the 30 studied genotypes were divided into four main clusters at distance of five. The results of principal components analysis showed that five components which justified 89.4% of the variation. The biplot diagram obtained from the principal components for the evaluated traits was consistent with cluster analysis grouping. In this diagram, the four groups from the cluster analysis were well separated. totally, the results of principal component analysis and cluster analysis confirmed the existence of high genetic diversity between the studied genotypes.

The results of this research showed that different pigeon pea genotypes had a wide range of morphological characteristics, which shows the diversity and high genetic potential of this product. In this research, genotype 19, with 95 days, and genotype 23, with 193 days, were the earliest and the latest maturity genotypes. Genotype 5 had the highest amount with 230 pods per plant and genotype 30 had the lowest amount with 33 pods. Genotype 11 had the highest amount with 968 seeds per plant and genotype 30 had the lowest amount with 132 seeds.By collecting different populations of this plant in the country and identifying its high genetic capacity, it can be used in the breeding programs and agricultural system of the country. Also, by considering that pigeon pea is one of the most drought-tolerant legumes and has eleven different maturity groups, it is possible to develop the feasibility of its cultivation in country

Introduction:

The genotype × environment interaction is one of the most important factors in limiting breeding programs. The compatibility of a given genotype determines its ability and genetic capacity to produce high production and yield stability in different environments. Therefore, it is necessary to study the genotype × environment interaction in order to introduce stable genotypes in different environments. The current research was carried out to determine the compatibility and stability of yield for 10 tobacco genotypes and estimate the most stable genotype for tobacco growing areas in Iran (i.e. Guilan, Mazandaran and Golestan provinces). 

Materials and Methods:

In this study, 10 male sterile flue cured tobacco genotypes, which they completely tested in terms of quality and taste, including 7 internal modified hybrids named RVH5, RVH6, RVH8, RVH27, RVH30, RVH48, RVH70 along with 3 imported genotype DVH2101, PVH19 and NC100 in 6 tobacco growing regions of Guilan, Mazandaran and Golestan in two years of experiment (2018-2019). In total, 12 environments were studied in a randomized complete block design with 3 replications. Combined analysis was performed by considering the environments as a random factor and genotypes as a fixed factor. Then the stability analysis of genotypes was done by 10 stability statistics and the first 3 components of AMMI (Additive Main effects and Multiplication Interaction) analysis including IPCA1, IPCA2 and IPCA3. Analysis of variance was done using SAS.9 software, AMMI analysis and related graphs were performed using IRRISTAT software. 

Results and Discussion:

The results of combined analysis of variance showed that the effect of location and year × location interaction, the effect of genotype and genotype × year × location interaction were significant at the 1% probability level for yield. Genotype × environment interaction analysis using the first three main components of the AMMI analysis justified 69.47% of the total variance. The lowest coefficient of variation was related to DVH2101 and RVH27 genotypes. RVH30, RVH27 and RVH8 genotypes were selected as the most stable genotypes. According to Rick equivalence and Shoklaʹs stability variance parameters. The least squares deviation from the regression line were related to RVH27, RVH30 and RVH8 genotypes. In terms of regression coefficient, RVH27, RVH30 and DVH2101 genotypes had a line slope close to 1. Based on the coefficient of determination and Jenkins and Perkins statistics, RVH27, RVH30 and RVH8 genotypes were in the same rank in terms of stability. RVH27 and RVH30 were the most stable genotypes with superiority index. RVH27, RVH30 and DVH2101 genotypes were selected as the most stable hybrids based on the AMMI first model due to their proximity to the plot center, low interaction and high yield. Based on the second model of AMMI analysis, RVH27 and DVH2101 genotypes were selected as stable genotypes. In the third AMMI model, the RVH27 genotype was selected as the stable genotype due to its closeness to the biplot center and high yield. 

Conclusion:

Considering most of the stability statistics and AMMI analysis, the most stable genotype was RVH27 hybrid. RVH30 and DVH2101 hybrids were placed in the next categories of stability. In addition, genotypes RVH6 and NC100 showed high private compatibility to Tirtash tobacco growing area and genotype RVH27 to Rasht region.

Given the shortcomings regarding lentil cultivars compatible with temperate and semi-temperate rainfed regions of the country, identifying genotypes with potential to be introduced as cultivars is very important. Due to genotype × environment interaction, selection of genotypes with wide adaptation to different environments is difficult. In addition to high yield, these genotypes must have yield stability in different regions, in other words, general stability. In GGE model (G+GE), the selection of stable genotypes is based on both genotype (G) and genotype × environment (GE) interaction effects.

in order to evaluate yield stability of rain-fed lentil genotypes, the present study was conducted based on randomized complete block design with three replications with 14 advanced genotypes along with two local cultivars including G15 and G16 (Gachsaran and Sepehr respectively) over two years (since 2018). The experiment’s locations were Gachsaran, Khormeh Abad, Ilam and Moghan. After collecting data from eight environments, the genotype × environment interaction for grain yield was evaluated by using GGE biplot method.

Principal component analysis in the GGE biplot model showed that 47.1% of the variations caused by G and GE is justified by the first two components (PC1, PC2). The mosaic plot revealed that the contribution of diversity due to genotype × environment interaction was significantly higher than the diversity caused by genotype (G) alone. Using GGE biplot model and based on representativeness and discriminating ability, Gachsaran region was identified as a desirable environment to identify variation among genotypes. G11 was the closest genotype to the ideal genotype in terms of grain yield. This genotype had the highest yield among genotypes and was in a moderate position in terms of stability. Genotype 9 was in the second place in terms of yield but had high yield stability since was the closest genotype to the ideal genotype in terms of stability. Genotypes 10 and 1 were also in the next ranks considering both yield and stability. These four genotypes had considerable advantage in terms of both average yield and yield stability compated to control cultivars (G15 and G16). In addition, G5 showed the least yield stability among all genotypes. G15 and G16 as local cultivars showed relatively low grain yield and stability compared to the most of advanced genotypes.

G9, G11, G10, G1 were considered as genotypes with potential to be introduced as new cultivar(s) following further experiments in private farm lands.

Analysis of statistical relationships and quantitative factors and parameters affecting the production of sediment and soil loss is one of the problems of the watershed. The purpose of this study is to model the relationship between sediment production rate using MPSIAC experimental model factors and observed sediment rate using geomorphic parameters and their relationship with sediment yield in the watershed. Rastamabad watershed of Ilam province was selected by a simple random method with four sub-watersheds identified and equipped with a hydrometric station from the southern basins of Ilam province. In this study, an experimental model was used to estimate the sediment yield. Flow and sediment data of four hydrometric stations and 12 meteorological stations from 1991 to 2020 for 30 years were prepared by the Regional Water Company and the General Meteorological Office of Ilam Province. Physiographic information of the sub-watersheds was calculated from topographic maps with a scale of 1.25000 and the geomorphic features of the sub-watershed were extracted from the digital elevation model. Using factor analysis and cluster analysis, influential factors and variables were identified and sub-domains were classified and divided into homogeneous regions. In order to investigate the correlation between independent and dependent variables, the data normality test was performed by Shapiro-Wilk and Kolmogorov-Smirnov tests in SPSS software. The statistical multiple regression method was used to analyze the relationship between experimental model factors and geomorphic variables with sediment yield of each watershed. The results showed that the sediment yield had a positive correlation with geological factors, land use, upland erosion, river erosion and topography of the watershed and was significant (P≤ 0.001). The amount of observed sediment had a positive correlation with slope, circulatory ratio, rainfall, topography, and area of the watershed and was significant (P≤ 0.001). In order to influence the factors and variables on the amount of sediment in the sub-watersheds, the method of principal component analysis and cluster analysis were used. The results showed that the land use explained 25.24% of the variance of all research variables. Finally, the three factors of land use, upland erosion, and geology, and two parameters of circulatory ratio and slope were explained at 86%. Of the variance of all research variables.

Changes in different solute compounds in edaphic factors affect the spatial distribution of plant species, especially hemicryptophytes.Soil salinity is one of the most common desertification factors in arid and semi-arid regions that contributes to the degradation of the soils of regions susceptible to desertification and eventually leads to a decreased soil ecological potential which is considered as one of the most significant factors that intensifies desertification. In order to explore the impact of principal components of soil on the diversity of plant types in the forest regions scattered along the coastal belt of the Persian Gulf and Oman Sea, current research was conducted on saline soils in Hasan Langi Village. Analysis of correlation coefficient between different traits of the plants in the respective vegetation (percentage of coverage, height and density and diversity) and the soil parameters of the habitats indicated that these vegetative parameters were mostly correlated with acidity, texture, and total calcium and magnesium. Principal component analysis (PCA) demonstrated that components 1 and 2 explained a total of 85% variance suggesting the largest impact of soil factors on differentiation of vegetation. In total, the factor of diversity was most correlated with calcium and magnesium in the second depth while other vegetative characteristics were directly correlated with the amount of sodium and potassium as well as electrical conduction in the first depth and the amount of calcium in the second depth.

Chickpea (Cicer arietinum L.) is one of the most important legumes in the world after pea and bean and is rich in protein (21.7-23.4%), minerals (iron, phosphorus, calcium, zinc, potassium and magnesium), carbohydrates (41.1-47.4%) and vitamins (B1, B2, B3, B5, B6, B9, C, E, K). The interaction of genotype by environment, as a response of genotypes to the environmental variation is a source of complexity for breeding programs and preparation of high yielding and stable genotypes. One of the most important ways to discover the nature of genotype by environment interaction is stability analysis, which identified the stable or compatible genotypes. Different methods for investigation of genotype by environment interaction and determination of stable genotypes have been reported, which generally include uni-variate and multivariate methods. One of the multivariate methods is AMMI analysis. The purpose of present study is the evaluation of the stability of chickpea genotypes using AMMI indices and biplots. 

Eighteen selective advanced genotypes of chickpea from ICARDA with two check verities (Arman and Azad) evaluated across four locations (Gachsaran, Ilam, Gonbad and Khoramabad) at three growing seasons, in a completely randomized block design with three replications. The data of 3rd year in Gonbad were lost and therefore, the analysis of data performed on 11 environments. Average seed yield of genotypes estimated at each environment (combination of location and growing season) and used for analysis. Statistical analyses including simple analysis of variance, combined analysis of variance and stability analysis carried out by metan (Multi environment trial analysis) R package. Five AMMI stability indices including ASV (AMMI stability value), SIPC (Sum of IPCs scores), EV (Eigenvalue stability parameter of AMMI), Za (Absolute value of the relative contribution of IPCs to the interaction), WASS (Weighted average of absolute scores) and simultaneous selection index (ssi) of these parameters was used for stability evaluation of genotypes. 

Combined analysis of variance indicated environment, genotype and genotype by environment interaction accounted 79.2, 2.4 and 10.0% of the phenotypic variation of seed yield, respectively. The significant effect of genotype indicated the wide genetic background of genotypes, while the significant effect of genotype by environment interaction is indicated the diversity of genotypes in test locations and growing years and exhibited the necessary of evaluation of genotypes in multiple environments. According to the significant effect of genotype by environment interaction, AMMI analysis was carried out by principal components analysis and the results indicated the significant effects of five principal components on seed yield. The first two principal components contributed to 42.5 and 19.4% of genotype by environment interaction. Genotype G3 (1663 kg ha-1) followed by G1, G17, G20 and G5 had the highest seed yield. According to the ASV and WAAS indices, G3, G4 and G13; EV and ZA indices, G3, G14, G16 and G6; and SIPC, G14, G3, G11, G4 and G16 were the most stable genotypes. Selection of these genotypes was done only on stability aspect of genotypes, therefore simultaneous selection index (ssi) based on any of these parameters was used to evaluate the simultaneously selection of genotypes based on seed yield stability and performance. Genotypes G3, G1, G4, G13 and G16 selected as superior genotypes by ssiASV, ssiZA and ssiWAAS indices; while based on ssiSIPC and ssiEV, G3, G16 and G20 were as the best genotypes. The other applications of AMMI stability analysis are selection of best genotypes in any of environments. According to this procedure, genotype G3 was placed in the first order in E1, E5 and E7; in the second order in E2, E3 and E9; in the third order in the E6 and E7; and in the fourth order in the E5. The AMMI1 biplot (IPCA1 vs grain yield) identified G1, G3, G17 and G13 as high yielding and stable genotypes with seed yield higher than total mean and lowest IPCA1 values. This biplot was also indicated environments E1, E9, E5, E2 and E3 had the lowest contribution in genotype by environment interaction interaction. The first principal components explained only 42.5% of genotype by environment interaction, and therefore, it seems that using the AMMI2 biplot is more efficient to identify the superior genotypes. In AMMI2 biplot (IPCA1 vs IPCA2), genotypes G4, G3, G13, G1 and G10 had high general stability. The environments E3, E4 and E10 with long vectors, had high discriminating ability and can estimate the relative efficiency of genotypes well.

In general, based on different indices, G3, G1 and G13 had high yield in most of environments, and in most methods had good stability and could be candidates for introduction of new cultivars.

Nepeta binaludensis Jamzad is an endemic and rare perennial plant that grows in a limited area in Binaloud Mountain in northeast of Iran. The aerial parts of 20 populations of N. binaludensis, were collected during their flowering stage and seven morphological traits and essential oil yield were evaluated. Results showed significant differences in all of traits between populations (p<0.01). The highest and lowest aerial fresh weight were obtained in Zoshk1 and Grineh populations with average values of 378.2 and 58.2 g/plant, respectivel. The highest and lowest essential oil yield were obtained in populations of Darood and Friezy1 with average values of 4.91 and 1.2%, respectively. The results of correlation analysis showed that plant height was positively correlated with stem diameter, aerial fresh and dry weights. Climatic factors such as rainfall, altitude and slope percentage were positively correlated with morphological traits and essential oil yield. Morphological traits and essential oil yield were positively correlated with climatic factors, such as rainfall, altitude and slope percentage and negatively correlated with temperature of the habitat, indicating that mean of mentioned traits were increased by increasing altitude and decreasing of temperature. Cluster analysis using Ward method, the studied populations were splited into two groups. The populations of cluster 1 (seven populations adapt to high altitude and cold) had higher mean values for morphological traits, i.e. plant height, aerial fresh and dry weights. Results indicate the presence of high diversity among populations of N. binaludensis that could be used for domestication and breeding improved varieties of this species.

This investigation was conducted to study of diversity and distinction of Garra rufa in some aquatic ecosystems located in Fars province. So, 208 samples were collected from five aquatic ecosystems located in Fars province (Rudbal river, Babasheikh Khalil subterranean, Qaderabad subterranean, Doudabad subterranean, Khargheh river) and 24 morphological traits were measured. Before data analysis, morphometric traits were standardized to reduce or eliminate of size and algometric growth effect. The results showed that studied population have significant differences in all of relative morphometric traits except of pelvic fin length, which indicates a high phenotypic diversity in Gara. According to principal component analysis, population of Babasheikh Khalil are very different with Qaderabad and Kharqeh population. On the other hand, a little separation was observed for Kherghe and Rudbal populations with Qaderabad and Dodabad. Based on results, the most important traits for identification and differentiation of G. rufa population are dorsal fin height, anal fin height, barbell length, disc length and disc width in the studied ecosystems.

In order to selection of soybean genotypes under different amounts of sulfur, 30 soybean genotypes were evaluated at three levels of sulfur (control, 5 and 10 g/Kg soils) concentration of sulfur was 98 % and it was added as 0, 0.1 and 0.2 % of evaluated soils. The experiment was lay out as a factorial arrengment in a randomized complete block design with three replications at Sari Agricultural Science and Natural Resources University in 2016. Evaluated traits included height of main branch, height of first sub branch, number of main branch pods, number of sub branch pods, 100 seed weight, total chlorophyll content, chlorophyll a content, chlorophyll b content, carotenoid content, sulfur content, Oil percentage, protein percentage and grain yield per plant. The results of analysis of variance of studied traits showed that sulfur application has a significant effect (P<0.01) on the studied traits. According to the results of means comparisons, the highest amounts of oil and protein percentage were obtained in Dayr and Williams genotypes at the third level of sulfur. The highest and lowest grain weights were observed in Hill and Vabash genotypes in the second level of sulfur, respectively. The results of the cluster analysis using Ward method, divided the soybean genotypes into two distinct groups. The genotypes were grouped using principal component analysis and biplot, too. According to the results of the cluster analysis, genotypes of the first group, which had high mean for the studied traits, were selected. Therefore, these genotypes can be used to select high-yielding genotypes and desirable agronomic traits that have the ability to absorb more sulfur in future breeding programs.

The present experiment has compared the resistance of different mycorrhizal pistachio rootstocks to salinity and drought stress in a completely randomized design with three replications. It has used Funneliformis mosseae and four pistachio species, Badami-e Riz Zarand, Qazvini, Sarakhs, and UCB1. In addition, the experiment of water stress in 4 levels (100%, 80%, 60%, and 40% FC), and experiment of salinity stress in 4 levels (0.91, 7.57, 16.12, and 24.63 dSm-1), have been applied for 60 days. At the end of the experiment, different characteristics such as total biomass, leaf area, tissue moisture percentage, and electrolyte leakage have been measured. Also, during the experiment, total chlorophyll, carotenoids and anthocyanin pigments have been surveyed and analyzed. The results indicate that mycorrhizal symbiosis has improved total biomass and leaf moisture content under both drought and salinity stress conditions, wherein tissue moisture content and total leaf chlorophyll content have decreased and anthocyanin content and electrolyte leakage increased. As for the lowest leaf, stem and root moisture content have been observed at the highest drought and salinity levels with UCB1 having the highest biomass and moisture under salinity stress and the highest leaf and stem moisture content and lowest electrolyte leakage are observed in Sarakhs rootstock under drought stress. It seems UCB1 and Sarakhs symbiotic with mycorrhiza can be useful for salinity and drought stress, respectively.

Production of low-fat or high-fat products in order to reduce the amount of calories in excess of the body's consumption needs, is one of the developing circles in the food industry. Hydrocolloids are among the compounds that can be used to improve the properties of these low-fat products. Hydrocolloids extracted from the native seeds of Iran, such as Cydonia Oblonga and seed gum Lallemantia, have a good ability to be used in these cases. Therefore, without the use of data analysis methods, it is not possible to fully understand these studies and achieve practical results. Sensory evaluation and consumer play an important role in the development of food science and industry. Sensory evaluation studies provide extensive data. In sensory evaluation of food, the analysis of the main components provides a way to visualize the relationship between the product or sample and its sensory characteristics or traits. In fact, the analysis of the main components is used to create a simplified view of the multidimensional data set. The data set becomes smaller data due to the correlation of the main variables, and as a result, the main components are formed. Each major component is a linear combination of the main variables. Analyzing the main components is a useful way to evaluate data, as many researchers have used this method to analyze the results of sensory evaluation. In fact, the application of this method has been measured for a large number of the main variables (called the main components) are obtained, which include the highest varians of the observed variables. Therefore, with this method, the number of the main variable is reduced, and a smaller number of artificial variables (called the main components) are obtained, which include the highest variance of the observed variables. However, the effect of Cydonia Oblonga and Lallemantia native gums on the sensory properties of low- fat milky dessert has not been studied. Therefore, this study was conducted to investigate the effect of different levels of two types of grain gum Cydonia Oblonga and seed gum Lallemantia as a tissue healing agent and fat replacement on the sensory characteristics of low-fat milk dessert and another goal was to determine the correlation coefficient between sensory parameters so that the factors that had the greatest impact on overall acceptance were identified.

In this study, native gums of Cydonia Oblonga and Lallemantia in the from of a completely radomized design at the levels 0.1, 0.2 and 0.3% gums concentrations were used as the low-fat milky dessert as a textur improver and fat replacer. Then, the method of analying the main components was used to determine the relation ships of sensory parameters and to obtain the main components.

The results of comparing the mean related to sensory testing showed that the amount of Scent and Taste and softness in different samples did not differ much (P <0.05). However, sensory evaluators were more interested in softness in samples containing 0.3 ,0.2 Lallemantia gum. The lowest amount of softness was related to the full fat control sample. The degree of porosity in different samples did not differ significantly (P <0.05). Congelation in the full fat control sample was more appropriate. Samples containing 0.3 Lallemantia gum and 0.3 Cydonia Oblonga gum were the best in terms of jelly. The being oily in the full fat control samplewas more adeguate. Scent and Taste were best in samples containing 0.3 Lallemantia gum and 0.3 Cydonia Oblonga gum. In general, overall acceptance on the amount of gum, sensory evaluators liked the samples with more Lallemantia and Cydonia Oblonga gums. Also, the results of the analysis of the main components showed that the highest correlation was between the general acceptance with the color parameter, which showed a correlation coefficient of 0.702. Softness with a coefficient of 0.659 and being jelly with a coefficient of 0.560 were also closely related to general acceptance. The Selection of the main components based on the specific value showed that the slope of the line is higher in the first 3 components (scent and taste, sweetness, softness) than the other components. The higher the absolute value of these coefficients, the more important the measured properties in the construction of the main component. Therefore, color is the most important component in the first factor, being oily and sweet are the most important components in the second and third factors, respectively. The product coordinates in PCA indicate the relevance of the parameters. For example, pastry and scent and taste were located in close proximity to each other, indicating a close connection between these parameters.

In sensory evaluation of food, principal component analysis provides a way to visualize the relationship between sample and sensory characteristics. In this study, in order to achieve a product withe a suitable structure in different amounts of 0.1, 0.2 and 0.3 gums concentrations were used as the low fat milky dessert, as a texture improver and fat replacer. In the production of samples, low fat milky dessert samples containing 0.3 Lallemantia native gum and 0.3 Cydonia Oblong native gum had the highest rate of sensory acceptance among the evaluators. Also, using principal component analysis, it was found that the overall acceptance of the samples had high correlation with color, softness and gel content. This study showed that Cydonia Oblonga and Lallemantia native gums could be used as a fat replacer and also as a dessert texture improver.

Cadmium is an important pollutant of heavy metals, which is very toxic to plants and animals. Rice is the most popular food among Iranians and the presence of heavy metals in trace level in rice has received special attention because they are directly related to health. In order to evaluate the tolerance of rice genotypes to cadmium, 40 rice genotypes under hydroponic conditions were used for seedling tolerance and absorption of cadmium in different levels of stress (control, 100, 200 and 300 μm cadmium) and in a split plot experiment in a completely randomized design template was examined. The results showed a significant difference between genotypes. In terms of cadmium adsorption, genotypes of Mirtarom, Sangtarom, F12L49-3، 229R and KOSHIHIKARI had the lowest cadmium adsorption. Principal components analysis based on the traits evaluated for cadmium show 70.160, 70.357, 72.641 and 66.305 percent of the changes by the first and second components, respectively, at the control levels of 100, 200 and 300 micromolar of cadmium. Cluster analysis based on the studied traits at control, 100, 200 and 300 micromolar of cadmium classified the genotypes in two, five, three and two clusters, respectively. In sum, genotypes of Sangtarom, Mirtarom, F12L49-3, 229R and KOSHIHIKARI as genotypes tolerant to cadmium and genotypes of M30, ARIAS HALUS and Kinan Dang Patong as genotypes classified as Noncompliant were determined according to biplot analysis and cluster analysis. The generations obtained from crossing between tolerant and susceptible cultivars could be used as segregating population in genetic and molecular studies.

Ghost crabs are the largest invertebrates on sandy beaches around the world. The one of type of ghost crabs is Ocypode rotundata which is distributed on sandy beaches of Persian Gulf and Oman Sea. The aim of this study was discrimination of O. rotundata population using 33 morphometric characteristics selected of carapace, walking legs, abdomen, major chela by principle component analysis (PCA) in software of R. For this purpose, samples were collected at low tide by excavating (20-150 cm) in four zones of south and south western of Qeshm Island (Sakoo naft, Souza, Salakh, Kani). According to results, there were differences between individuals of some population in terms of investigated morphometric characteristics. On the other hand, most of the population showed overlapping which could not be separated together completely. Among the obtained morphological index traits are third walking leg length, body height, abdomen length, first part of abdomen width, fifth part of abdomen width, chela and merus length which can be reason for variety between individuals.

The objective of this study was to evaluate the genetic variation of 26 selected genotypes of Phalaris aquatica L. based on important agronomic traits. Each selected genotype was divided into four clones and they were space planted according to a randomized complete block design with four replications under irrigation conditions in the Khalatposhan research station of Tabriz University, Iran. Data collection was started in March 2017 for two years. The results of analysis of variance showed significant differences among the studied genotypes for most traits (P<0.01). Accordingly, the mean comparisons of the traits among genotypes were conducted. Using principal component analysis (PCA), the first two components were accounted 66% of the total variation. The traits like forage yield in both cuts, crown diameter, plant height, and seed yield had the most important role in determining the first component. Based on cluster analysis, the 26 genotypes were grouped into four distinct groups. Based on the mean comparison results, principal component, and cluster analyses, 12 genotypes with the highest forage and seed yields in both years were selected as superior genotypes. Therefore, this population provided a suitable genetic source for breeding improved varieties using polycross progeny tests and breeding improved synthetic variety.

Beech trees is one of the most important species of Hyrcanian forests that plays an important role in the process of forest ecosystem succession and the ectomycorrhizal fungi play an important role in forest health and sustainability and protecting trees against pathogens in forest ecosystems. This study was conducted to classify beech habitat with environmental factors and ectomycorrhizal fungi in Sangedeh forest. A total of 45 sample plots of 1000 square meters were randomly assigned to three 300 m altitude classes, namely altitude range of 1200 to 2100 m above sea level and elevation factors (m), slope, slope direction, breast diameter, tree height, Degree of canopy cover, litter type, litter depth, stand type, soil acidity, electrical conductivity, phosphorus, carbon, nitrogen, potassium were investigated. The results of correlation of variables with components were determined and ectomycorrhizal fungi with first principal component included variables such as altitude, nitrogen, potassium, phosphorus, carbon, electrical conductivity and tree height and the second principal component of altitude variables, canopy cover, depth Litter, nitrogen, carbon and stand type had a significant positive correlation (1%). Principal component analysis results showed that first floor height (1800 to 2100 m) with sea level elevation, soil acidity, litter depth, phosphorus and potassium, second floor height (1500 to 1800 m) with forest cover canopy percentage, litter depth There was a positive correlation between mass type, nitrogen and carbon and height of third class (1200 to 1500 m) with stand type, tree height and electrical conductivity.

The purpose of this study was to evaluate the indices of drought tolerance and find out the relationships between them and their application in wheat screening programs. In order to proper screening of genotypes, the principal component analysis and biplot were analyzed and genotypes were placed in biplot based on factor scores. An experiment was conducted using alpha lattice design with two replications in rainfed and irrigated conditions using 132 bread wheat genotypes in the Gonbad-e-Kavos Agricultural Research Station in 2015-2016. Based on yield in no stress (YP) and stress (YS) conditions, drought tolerance indices such as stress susceptibility index (SSI), stress tolerance index (STI), tolerance index (TOL), mean production index (MP), Harmonic Index (HM), Yield Index (YI), Sensitivity Drought Index (SDI), Relative Drought Index (RDI), Stress Susceptibility percentage Index (SSPI), Drought Resistance Index (DRI) and yield Stability Index (YSI) Were calculated. Tolerance indices such as STI, GMP, HM, MP and YI had a positive and significant correlation with yield in normal conditions as well as with yield in stress conditions. Therefore, genotypes with large numerical values for these indices had high yield under stress and no stress conditions. TOL, SSPI, DSI and SSI Indices identified genotypes with high yield under normal conditions but sensitive to stress conditions (Group B Fernandez). Also, YSI and RDI indices differentiated genotypes with high yield under stress conditions and low yield under favorable conditions (Group C Fernandez) from other genotypes.

Seperated experiments were carried out at Motahari Research Station of Karaj, in order to ranking and grouping the different fullsibs and hybrids obtained from sugar beet breeding programs under drought stress and normal conditions. Accordingly, 17 and 28 different fullsib and hybrids respectively, along with resistant and sensitive cultivars, were examined for different yield, qualitative and physiological traits in separate experiments in dry and normal conditions. The results of the ranking showed that fullsibs 1, 2, 4 and control cultivars 18, 22 and 25 in drought conditions and and fullsib 16 and control cultivars 18 and 22 were superior in normal conditions compared to the rest of the full sibs. Each population of Fullsibs and hybrids was divided into two distinct groups. Fullsibs grouping were very similar in two conditions. But in hybrids, there was no significant association between the grouping of normal and stressed conditions. Based on principal component analysis, under stress conditions, fullsibs 3, 4, 5, 9, and 14, and under normal conditions, fullsibs 10, 18, 16, 1, 2, 6 and 8 were better in terms of yield traits. In hybrids, under stress conditions, hybrids 7, 10, 20, 5 and 11 were somewhat better in terms of root and sugar yield. In contrast, in normal conditions, hybrids 2, 17, 6, 25, 7, 9, 21, 27, 4, 13, 19 and control 30 were somewhat weaker in terms of yield traits, but for leaf area and relative water content traits, were superior.

An olfactory machine system based on eight MOS sensors was designed to detect pure cow ghee from the adulterated with various proportions of vegetable oil and animal fat. Designed system includes data acquisition system, sensors, sensors chamber, sample box, power supply, connections, electric valves, air pump and air filter. The sensor array was consisted of the 8 MOS sensors that each of them react to specific volatile compounds. These sensors are widely used in olfactory machines because of their high chemical stability, high durability, low response to moisture and affordable prices. These are the most commonly used sensors in electronic nose system. To prepare samples with different percentages of adulteration, animal body fat and refined vegetable oils were added to pure cow ghee. In order to carry out the experiments, the sample was placed in sample box and in the baseline correction step (200 seconds), clean air was passed through the sensors to transmit the response of sensor array to steady state. At the injection step (180 seconds), the sample headspace was transmitted and passed through sensors chamber.  Output voltage of each sensor depends on the type of sensor and its sensitivity. At the cleaning step (120 seconds) the clean air was passed through sensors to get the sensor array responsive to a stable state. Also, at this step the pump removed the odor remaining inside the sample container and system was prepared for the next test. The signals obtained from the sensors were recorded and then pre-processed.

An eight-sensory olfactory machine system (MOS) was designed to detect pure cow ghee from the presence of vegetable oil and animal fat oil. In PCA analysis, the variance between samples was 97% and 98%, respectively. According to the results the radar graph of PCA analysis, it can be concluded that the sensors No 2 (TGS822), 3(MQ136), 4(MQ9) and 8(TGS2620) have the highest and sensor 6 (MQ135) has the lowest ability in classification. The MQ135 sensor reacts to the detection of ammonia, benzene, and sulfide. In other words these gases did not play important role in separating of cow ghee from other mixed oils.

Process control and monitoring in operation of biogas production require various parameters to be measured. Therefore, the methods that express the effect of combination of parameters via robust and inexpensive equipment for fast and accurate measurement have high value.  In this research, the relationship between the indicator of daily production of biogas and the signals of the gas sensor array in an electronic nose system designated for biogas has been investigated to analyze and predict the condition of biogas digester in laboratory scale. To produce biogas, 1 liter batch digesters were fed by different combinations of two substrates at mesophilic condition. The Sensor array signals of each digester were divided into two groups of 1 and 2 by the clustering analysis (CA) method, which correspond to the balanced and imbalanced groups, respectively.  By analyzing score plot and also correlation loading in the PCA, MQ-4 and MQ-136 sensors were determined as main indicators for detecting the two groups and rest of sensors also contribute to interpret conditions of digesters. At final, to predict the conditions, a pattern recognition was defined by sensor array signals of all digesters in linear discriminant analysis (LDA) that the classification accuracy and resubstitution error were 100%   and 0.0476 respectively, also the accuracy of the prediction pattern was 81.25%.