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The 1:100,000-scale Porang sheet in South Khorasan province is prone to skarn, massive sulfide, and sedimentary mineralization due to the presence of intermediate to ultrabasic volcanic and plutonic rocks and the variety of sedimentary rocks. This paper introduces the Principal Coordinate Analysis (PCoA) method. The PCoA method, along with the Principal Component Analysis (PCA) and Correspondence Analysis (CA) methods, has been used to identify the possible type of mineralization in the study area. Geological and mineralogical data and the analysis results of 25 elements from 314 stream sediment samples, taken from the study area, have been used for this purpose. The results of the data analysis show that the D1 coordinate, PC1 score, and location in the first cluster maps of the samples are most likely related to the mineralization in ultrabasic, basic, and listivinite rocks. After that, the D2 and D3 dimension maps, the PC2 and PC5 score maps, and the sample location map in the fifth cluster related to sedimentary rocks attribute the most probability to sedimentary mineralization, especially of Mn and Fe mineralization types, in the study area. Finally, there is the possibility of skarn and massive sulfide mineralization, whose locations can be predicted by the D4 dimension maps, the PC3 score map, and the sample location maps in second, third, and fourth clusters. Also, the comparison of data analysis results with two multivariate statistical methods shows that by choosing the number of dimensionality reductions, the principal components method can cover more variability than the principal dimensions method. While connecting the principal coordinate maps to the mineralization is easier and more reliable than the principal component score maps. Therefore, the proposal of this paper is the simultaneous use of PCoA and PCA methods to analyze geochemical data in an exploration region. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to comprehensively investigate fluoride concentration in the Maku-Bazargan-Poldasht area, located in the north of West Azerbaijan province. In October 2021, 60 samples were collected from various water resources in the region. The fluoride concentration ranged from 0.39 to 9.89 mg/L, with more than 50% of the samples exceeding the World Health Organization's standard. This study investigated into the correlation between fluoride and other elements, assessed various processes influencing fluoride levels, investigated its effects on humans and plants, and utilized multivariate statistical techniques to determine contributing processes and factors. Moreover, it examined fluoride concentration fluctuations over the past 15 years across different water resources (Deep wells, Shalow well, Springs, Qanats, and Surface water) for the first time. The assessment of fluoride included multiple dimensions related to this element. Comparing fluoride levels across various water sources revealed that Deep wells exhibited the highest fluoride concentrations due to the long residence time of water within the aquifer matrix. This study also highlighted, for the first time, the correlation between high fluoride concentrations and plant diseases such as necrosis and chlorosis in specific parts of the study area. Bivariate plots indicated that processes involving carbonate dissolution and ion exchange contributed to increased fluoride and carbonate concentrations in the area. Furthermore, an analysis of changes in fluoride concentration in 12 sampling stations indicated an eightfold average increase in anomaly intensity over the past 15 years in these stations. Employing Principal Component Analysis (PCA) and Factor Analysis (FA), the research identified three groups and three factors, confirming that fluoride anomalies are natural, while nitrate anomalies originate from human activities within the study area. [ABSTRACT FROM AUTHOR]

Background: Alfalfa is one of the key fodder plants due to its species diversity and high stresstolerance range. In addition to producing significant palatable fodder, this plant stabilizes air nitrogen through symbiosis with rhizobium and causes soil fertility in addition to meeting its own needs. For fodder production in the hot and dry region of Sistan as the hub of animal husbandry in the province, it is inevitable to investigate and introduce high-yielding alfalfa cultivars. Therefore, the present research aimed to evaluate tropical alfalfa cultivars and identify high-yielding and more compatible cultivars in terms of yield production and selection of stands with suitable potential for selection. Methods: The phenological, morphological, and functional traits of 10 tropical alfalfa genotypes (Zabol local purified alfalfa, Zabol local mass, Baghdadi, two Afghani masses, Nikshahri, Omid, and lines 473, 472, and 471) were investigated in the Zahak Agricultural and Natural Resources Research Station, located 20 km from Zabol city. An experiment was conducted in a statistical design of randomized complete blocks with three replications during 2017-2018. The bed preparation, including plowing, disk, and leveling, was operated exactly the same for the replications. The distance between the plots in each block was 75 cm, and the distance between the blocks in each replication was 1 m. After preparing the bed on November 15, 2016, furrows were created at a distance of 30 cm (four lines of 6 m) in the plots, and seeds with 95-100% germination capacity were planted at a rate of 15 kg per hectare. Seeds were sown in a row manually by opening grooves to a depth of 1 cm using the method of Hiramkari. During the experiment, the operation consisted of irrigation every 15 days in winter, spring, and summer (once a week) according to the needs. Weeds were mechanically weeded in the early stages of growth. In each year, eight plants were harvested at the 20% flowering stage. Days to greening, days to flowering, plant height, leaf-to-stem percentage, stem diameter, stem number, dry matter percentage, and wet and dry fodder yields were the traits measured during the experiment. At the end of the experiment, data on the fodder yield and morphological and phenological traits of alfalfa cultivars were analyzed using MSTAT-C software. The correlation was calculated using SPSS 16 software. Analysis into principal components and the biplot were done using the Past software. The means of traits were compared with Duncan's test at the probability level of 5%. Results: The fodder yields were significant among the genotypes at the 1% probability level. The highest average fodder yield (107.589 tons per hectare) was obtained in the Omid cultivar, with greater fodder yield than the other cultivars due to the number of stems, plant height, and stem diameter. Baghdadi alfalfa and Zabul purified alfalfa cultivars ranked next in terms of producing more fodder yield with averages of 103.513 and 102.463 tons per hectare, respectively. The lowest fodder yield was observed in the native mass of Zabul alfalfa with an average of 86.511 tons per hectare. The purified local alfalfa of Zabul showed an increase in yield by 18.43% compared to the native mass. The cultivars were significantly different in dry fodder yield at the probability level of 1%. The highest average dry fodder yield (28.323 tons per hectare) was obtained in the Omid variety. Baghdadi alfalfa and purified Zabul alfalfa ranked next with average yields of 26.419 and 27.322 tons per hectare, respectively. The increased dry fodder yield in alfalfa is considered an advantage because farmers store excess alfalfa in the form of dry fodder for their livestock in winter. The relationship between the examined traits showed that most of the traits were significantly correlated with each other. Fodder yield had a positive and significant correlation with the number of stems per plant and plant height, but there was a non-significant correlation with the number of days to flowering, leaf-to-stem ratio, and stem diameter. The dry fodder yield had a positive and significant correlation with the wet fodder yield, leaf-to-stem ratio, the number of stems, and plant height, and it showed a negative correlation with the number of days to flowering. Statistically significant differences were observed between the genotypes in terms of all studied traits. Based on the clustering, the genotypes were divided into two groups, and the first group, including Omid, Baghdadi, and the purified local alfalfa of Zabol, was superior to the others. In the mmean comparisons by Duncan's test, the Omid variety ranked first with the average wet and dry fodder yields of 107.589 and 28.323 tons per hectare, respectively. The Baghdadi variety and the local purified line of Zabol ranked second and third, with average yields of 103.513, 102.463, 26.419, and 27.322 tons per hectare, respectively. These genotypes were in good conditions in terms of other traits (plant height, the number of stems, and the leaf per stem percentage). Conclusion: Considerable variation was observed between genotypes in terms of the studied traits. The highest seed yield was observed in the genotypes of Omid, Baghdadi and the purified local alfalfa of Zabol. In favorable conditions, a significant area of land in Sistan and Baluchistan province and similar regions can be dedicated to alfalfa cultivation, including Omid, Baghdadi, and the purified local genotype of Zabol. [ABSTRACT FROM AUTHOR]

Background: Wheat is the key crop in many parts of the world that has the largest cultivated area. As much as 30% of all grains produced in the country belong to wheat, which is known as the main food of half of the world's people. At the same time, environmental stresses, including biotic stresses, have been one of the most important factors in reducing wheat yield in recent years. Powdery mildew (Blumeria graminis f.sp. tritici) is one of the important diseases of wheat that causes great losses to wheat production every year. On the other hand, the resistance of resistant wheat genotypes is not constant over time, and the resistance of almost all resistance genes commonly used in the world has been broken by new pathogenic strains of powdery mildew. This is because research has shown that the high pressure imposed by resistance genes on disease-causing populations has caused the rapid evolution of new pathogenic races, resulting in the loss of resistance. For this reason, one of the most effective and logical methods of controlling this disease, which is most compatible with the environment and sustainable agriculture, is the identification and production of resistant cultivars. Methods: In the present study, 32 different bread wheat genotypes (Triticum aestivum L.) available in the Genetics Research Department and National Plant Gene Bank of Iran, Seedling and Seed Breeding Research Institute, exposed to 10 different pathotypes (Maghan 1, Maghan 2, Maghan 3, Maghan 4, Mughan 5, Gorgan 1, Gorgan 2, Sari 1, Sari 2, and Gonbad) of this mushroom were assessed for their resistance level in the two-leaf stage under greenhouse conditions. The investigated pathotypes of powdery mildew, collected from disease-prone areas of Iran, included five pathotypes from Mughan, two pathotypes from Gorgan, two pathotypes from Sari, and one pathotype from Gonbed Kavus. The disease isolates were propagated on the sensitive Bolani variety, which lacks the Pm gene. Genotypes were inoculated with single-cloned isolates by the rubbing method. One week after inoculation, the reaction of differential cultivars toward the disease was examined based on a scale of 0-4 according to the Mains and Dietz method. Based on this scale, pollution types zero, one, and two are in the resistant group, and pollution types three and four are in the sensitive group. In this research, the Bolani variety was determined as a sensitive control to powdery mildew disease. Results: Among the 10 powdery mildew pathotypes collected from important contamination centers in Iran, the examined genotypes showed the highest resistance to the Mughan5 pathotype. Genotypes TN127, TN79, TN7, TN180, and TN72 showed the highest resistance to 10 pathotypes on average. In total, the comparison of different powdery mildew pathotypes revealed that the Mughan5 and Sari1 pathotypes showed the lowest and the highest pathogenicity, respectively. In addition, the correlation between pathotypes was estimated to identify pathotypes with similar pathogenic power, indicating that the Mughan5 pathotype showed the lowest correlation with the other pathotypes, which probably uses a different mechanism for pathogenicity. Mughan2 presented the highest significant correlation, with Mughan3 (0.87) and Gorgan2 (0.81), which indicates the similarity of the pathogenic mechanism in these three pathotypes. On the other hand, the results of the cluster analysis divided the genotypes into two separate groups in terms of resistance to powdery mildew, and many of the investigated genotypes were included in the susceptible Bolani cultivar group. In addition, cluster analysis for powdery mildew pathotypes showed that the Mughan5 pathotype was in one group, and the rest of the pathotypes were in another group. Bi-plot and three-dimensional analyses based on the data analysis into principal components for the first and second components (87.95% of the total variance changes) showed that the Moghan 5 pathotype had a lower correlation with the other pathotypes. The negative side of the first component and the negative side of the second component showed the resistance of the genotypes. Thus, the resistant genotypes were placed in area 1. Conclusion: The genotypes examined in this research have not been evaluated so far for resistance to powdery mildew. Therefore, sources of resistance identified in this way are reported for the first time. In general, a potential variation was observed among the genotypes with respect to different pathotypes. In terms of pathogenicity, the Mughan5 pathotype showed the least pathogenicity among the examined genotypes. Resistant genotypes in this research can be used as promising genotypes in wheat breeding programs. Overall, the findings of this research indicate a desirable diversity among the genotypes studied in terms of resistance to various strains of the disease. However, since identifying the resistance of mature plants requires screening the genotypes under field conditions and takes a considerable amount of time, it is suggested to utilize molecular markers associated with resistance to powdery mildew in future research. [ABSTRACT FROM AUTHOR]

Background: 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. Methods: 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. Results: 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 seedfilling 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

1-Introduction Soil erosion is one of the most important environmental hazards. Investigating the impact of soil erosion on soil quality is possible through the evaluation of soil quality indices in eroded and non-eroded points. Studying the severity of soil erosion in order to protect the soil and investigate and evaluate its risks is of particular importance. There is a significant relationship between increasing soil erosion and decreasing soil quality, therefore soil quality and erosion are closely related phenomena. The main prerequisite for dealing with all types of erosion, including gully erosion, is to predict the risk of gully formation and its effects in different places. The purpose of this study in the south of Ardabil city is to calculate the soil quality indicators and investigate the effect of soil erosion on the quality indicators, compare the correlation between the most important characteristics affecting the soil quality (MDS) and the total characteristics affecting the soil quality (TDS) and provide an index distribution map. The quality of the soil is determined with the help of geostatistical methods. 2-Methodology The studied area is a part of Mullah Ahmed watershed near Amin Lo village, 10 km south of Ardabil city. A part of this area was selected with an area of about 50 hectares, which had active Gullies. After identifying and investigating the study area, 48 samples were taken from the depth of 0 to 30 cm of the soil surface, including 24 non-eroded and 24 eroded points. Sampling from each point was done based on the change of topographical conditions and variety of soil characteristics, especially soil color, and in the form of paired points. After laboratory analysis, the total of the measured features was considered as the total data set (TDS) and the principal component analysis (PCA) method was used to select the minimum data set (MDS) (Doran and Parkin, 1994). The contribution of each feature (COM) was calculated by factor analysis (FA) in TDS and MDS sets (Shukla et al; 2004). Then, soil quality indices were calculated using IQI and NQI relationships (Doran and Parkin, 1994). After calculating the soil quality indices at the sampling points in the region, continuous maps of the distribution of soil quality indices were obtained using two methods, Kriging and IDW, with the help of GS Plus 5.1 and Arc GIS 10.8 software. 3-Results According to the results of PCA test, Sand, Clay, pH and Ec variables in eroded points and BD, Sand, Clay and n variables in non-eroded points were selected as MDS set. Pearson's correlation for soil quality indices in two sets of TDS and MDS in eroded and non-eroded points was significant at 5% level. According to the significant results, the use of the MDS set can optimally calculate the soil quality indices in non-eroded points instead of the TDS set. According to the distribution maps of soil quality and the findings of Qi (2009), the studied area is in grade III to II in terms of soil quality. In eroded points, in IQI and NQI indices, Kriging method was the best in TDS set and IDW method was the best in MDS set. While in the non-eroded points, except for the NQI index in the TDS set, in the rest of the soil quality indices, the Kriging method showed a better and more accurate performance. 4-Discussion & Conclusions Due to the significant correlation in non-eroded points, the use of MDS can acceptably calculate the soil quality indices (IQI and NQI) in non-eroded points, and in these points the IQI and NQI indices calculated using TDS are much superior. It is not compared to MDS. In general, in the studied area, based on the coefficient of explanation (R2) and the mean square error, the kriging method was more effective in showing the distribution of soil quality indices compared to the IDW method. The results of all these researches show that the optimal and appropriate method for estimation and estimating data can be different depending on the variable. The limited size of the studied area, sample intervals, the number of samples, the heterogeneity of the area in terms of variables and the existence of a trend can also influence the selection of estimation methods. According to the results obtained from the studied area, soil erosion has a significant effect on some soil quality characteristics. According to this research, conducting similar researches in other parts of Iran under different soil and climate conditions, along with a wide range of erosion effects on soil quality, general modeling of soil quality is important. The result of this can help to develop and create a national index of soil quality, and the existence of this index can provide the possibility of permanent monitoring of the soil condition at the level of agricultural and natural areas of the country and predict the possibility of soil destruction and erosion. [ABSTRACT FROM AUTHOR]

Purpose: This research aimed to identify the behavioral Models of stakeholder groups in corporate governance within Iran's Social Security Organization and its affiliated companies. In other words, it explored corporate governance from a behavioral perspective. Methodology: To conduct the research, a theoretical behavioral model was developed based on a review of the literature. This model identified six common behavioral indicators among stakeholders. Subsequently, a questionnaire with 36 questions was designed and distributed to experts in the field of corporate governance. A total of 207 responses were received, and the instrument's reliability was confirmed with a Cronbach's alpha of 0.933. Furthermore, exploratory factor analysis using the principal component method was employed to explain the factors of the model, which represented a classification of stakeholder groups. To validate these findings, confirmatory factor analysis was used to evaluate the proposed theoretical model. Findings: The results yielded a CMIN value of 2.694, which is below the critical value of 3. The root mean square error of approximation (RMSEA) was 0.097, falling within the acceptable range of 0.05 to 0.1. The Akaike Information Criterion (AIC) was 1812, closer to the saturated model index (1404) compared to the independent model (5660), indicating a good fit of the model. Originality/Value: Overall, six stakeholder groups were identified in the corporate governance of companies affiliated with the Social Security Organization: institutional stakeholders, government, political stakeholders, social networks, economic stakeholders, and shareholders. Additionally, six common behavioral indicators were identified among stakeholder groups: conflict resolution, building trust in the board of directors, political bargaining, power-politics relationships, goal setting, and decision-making processes. To assess the impact of each behavioral indicator, a parametric t-test and mean comparisons were used. The results showed that institutional stakeholders, the government, and political stakeholders had a significant and greater impact on governance in the Social Security Organization compared to others. Moreover, government interventions in goal setting, political bargaining, building trust in the board of directors, and conflict resolution had a significant and above-average impact on the governance of the studied companies. On the other hand, political groups had a significant and above-average impact on the corporate governance of companies affiliated with the Social Security Organization in terms of decision-making processes, goal setting, and power-politics relationships. The evaluation of behavioral indicators among stakeholder groups revealed that the shared focus of these groups was primarily on three indicators: goal setting, decision-making, and power-politics relationships. [ABSTRACT FROM AUTHOR]

IntroductionBarley is the fourth most common cereal crop in the world after wheat, maize, and rice, which is used for animal and human feed and malt production. This plant stands out among crops due to its unexpectedly wide range of adaptation and distribution compared to other cereals, earning it recognition as a model species. Determining the variation in the morphological and physiological traits of roots and shoots in the collection of barley genotypes can provide the basis for breeding new cultivars with suitable traits for better adaptation to specific environments. So in this study, some morphophysiological characteristics of roots and shoots of commercial barley cultivars were studied to identify cultivars with a higher root-to-shoot ratio as donor parents for breeding projects.Materials and MethodsIn this study, 21 barley cultivars were grown in a randomized complete block design with six replications in greenhouse conditions. Morphological and physiological traits related to roots and shoots were measured during the tillering and heading stages. Also, some traits affecting photosynthesis and yield during reproductive growth and harvesting stages were measured. Analysis of variance, mean comparison by LSD test at 5% probability level, and multivariate statistical analyses including principal components analysis, cluster analysis by Ward method, correlation analysis, and path analysis were performed by JMP and R statistical software.Results and DiscussionSignificant genetic diversity was observed for most of the traits among cultivars (P < 0.05). At the tillering stage, Behrokh and Mehtab cultivars and in the heading stage, Jolgeh cultivar showed the highest dry weight of root to shoot ratio. Reyhan variety showed the lowest dry weight of root-to-shoot ratio in both stages. The carbohydrate content of the root in the tillering stage and leaf proline, root volume, and the ratio of chlorophyll a to carotenoid in the heading stage had the highest significant correlation coefficients with dry weight of root to shoot ratio (P < 0.05). Path analysis revealed that the root carbohydrate content in the tillering stage and the ratio of chlorophyll to carotenoids and proline in the heading stage are the most effective traits of the dry weight of root-to-shoot ratio. Principal components analysis showed that the first and second principal components explain 33.63% and the first seven principal components explain 72.66% of the total changes. Also, the first principal component showed a positive and significant correlation with root to root-to-shoot ratio in the heading stage, and the second principal component showed a negative and significant correlation with this ratio (P < 0.05). The studied cultivars were classified into four groups based on cluster analysis so that the fourth and second clusters in the tillering stage and the third and second clusters in the heading stage had the highest and the first cluster in both stages had the lowest dry weight of root to shoot ratio.ConclusionBased on the results, Jolgeh and Reyhan cultivars can be used in breeding programs to improve and produce cultivars with higher root-to-shoot ratio, optimal yield, and more adapted to specific environments. These cultivars had the highest and the lowest dry weight of root-to-shoot ratio in both stages, respectively. Also, they were placed in different dimensions of the biplot drawn based on the first two principal components. In addition, these cultivars were observed in different classes based on the cluster analysis.AcknowledgmentThis project related to the Ph.D. thesis was financially supported by the Vice President for Research of the Faculty of Agriculture, Ferdowsi University of Mashhad, and the seeds of the cultivars used in this study were provided by the Karaj Seed and Plant Improvement Institute, the authors are thankful for this cooperation.

The negative and destructive impact of climate change on the efficiency and productivity of agricultural inputs has been demonstrated in many regions of the world, particularly in arid and semi-arid areas. In this context, the adoption of innovative strategies to increase farmers' flexibility and adaptability to climate change has increased. Hence, understanding the impact of climate adaptation strategies on agricultural efficiency and yields is crucial. This study examined the effects of climate change adaptation strategies, input utilization, and external factors beyond farmers' control on technical efficiency using the Endogenous Modified Stochastic Frontier (EMSF) model. Data were collected from 265 questionnaires distributed among wheat farmers during the 2022-2023 cultivation period, using a stratified random sampling approach. The climate adaptation strategy index was formulated using the Principal Component Analysis (PCA) technique. The PCA revealed that changes in farm size (0.812), adaptation of conservation tillage (0.797), and adjustments in planting dates (0.619) were the most influential factors. Conversely, rainwater harvesting (0.219) and biofertilizer application (0.327) emerged as the adaptation strategies with the lowest factor loadings among farmers. In this study, the average technical efficiency of wheat farmers was calculated to be 82%. The model estimation results showed that labor input, chemical pesticides, chemical fertilizers, water, and machinery significantly and positively contribute to wheat production efficiency. Additionally, the implementation of climate adaptation strategies by farmers reduces technical inefficiency. Variables such as education level, farming experience, access to climate information, and access to credit also effectively reduce technical inefficiency.

Background: The increased demand for cereals that are consumed by humans and livestock can be met through the development of planting drought-tolerant genotypes. Due to the interaction of genotypes × environment, the best genotype in one environment may not be the best in other environments, and therefore, this interaction provides valuable information about the yield of each genotype in different environments and plays an important role in evaluating yield stability. Genetic modification of drought tolerance in crops is one of the most stable and cost-effective approaches to increase production and yield stability. Examining the compatibility and stability of grain yield based on various parametric and non-parametric stability statistics and evaluating tolerance to drought stress based on stress indices in promising barley genotypes of the country's temperate climate are among the goals of this research. Methods: To assess grain yield adaptation and stability and to select high-yielding barley genotypes suitable for terminal drought stress in the temperate climate of Iran, 16 barley genotypes were cultivated during two crop years 2021-2023 in a randomized complete blocks design with three replications in three research stations including Varamin, Birjand, and Yazd under two none-stress and drought stress conditions at the end of the season (12 environments). After determining the grain yield, stress indices, including MP, GMP, TOL, HARM, STI, YI, YSI, RSI, and SSI, and the correlation of each with grain yield were calculated in this study. Stability statistics included Nassar and Huehn’s stability statistics (S(1-6)), Thennarasu’s stability statistics (NP(1-4)), deviation from regression (S²di), regression coefficient (b), Shukla’s stability variance (σ²ᵢ), environmental variation coefficient (CV), variance component (θᵢ), coefficient of variance (θ(i)), Wricke’s ecovalence (Wᵢ²), and Kang’s sum of ranks (KR). Their relationships were calculated based on Pearson’s correlation. Analysis of variance (ANOVA), mean comparison, and simple correlation were calculated using the SAS-9.0 program, stability statistics were calculated using STABILITYSOFT and principal component analysis (PCA). Stress indices and the correlation of each of these indices with grain yield were calculated using iPASTIC. The three-dimensional distribution diagram of genotypes in the ranges of A, B, C, and D was drawn using Grapher software. Results: The results of the combined ANOVA indicated the significance of the genotype × environment interaction. According to S(1-2) statistics, G7, G10, G11, and G3, and according to S(3-6) statistics, G7, G3, and G9 were the most stable genotypes. Among the non-parametric Thennarasu’s stability statistics according to the NP(1) criterion of G9, G3, and G5, according to NP(2) G5, G3, and G8, and according to NP(3) and NP(4) criteria, G7, G3, and G9 were recognized as the most stable genotypes. Based on Wricke (W²) and Shukla (σ²) equivalency stability statistics, G3, G9, and G13 were the most stable genotypes. Based on Eberhart and Russell's regression method, G9, G7, and G3 genotypes, with high yields, had general compatibility and good yield stability. Based on Francis and Kannenberg (CVi), genotypes G1, G2, and G15 had the lowest coefficients of environmental variation. Based on the average rank of each genotype in all stress indices (AR), G2, G7, and G3 genotypes were the most tolerant, and G14, G11, and G10 were the most sensitive genotypes to drought stress at the end of seasons, respectively. In the drought stress conditions at the end of the season, grain yield had positive and significant correlations with YI, HM, GMP,  STI, MP, YSI, and RSI indices and negative and significant correlations with the SSI index. In non-stress conditions, grain yield had positive and significant correlations with MP, GMP, STI, HM, and YI indices, but no significant correlations were observed between grain yield and SSI, TOL, YSI, and RSI indices. The PCA revealed that the first and the second principal components explained 69.71% and 30.27% of the variance of the main variables, respectively. The first main component had a positive and high correlation with yield in both stressed and non-stressed environments, as well as MP, STI, GMP, and HM indices. The second component showed a positive and high correlation with grain yield in the non-stressed environment and TOL and SSI indices; it also had negative and high correlations with RSI and YSI indices. Based on the biplot diagram, G3, G7, G8, G9, G12, and G13 presented higher grain yield potential and are more tolerant to drought stress. Conclusion: In this study, grain yield had negative and significant correlations with NP(3), KR, NP(2), NP(4), S(6), and S(1) statistics, respectively, therefore these statistics can be used for identifying stable genotypes. G3, G7, and G9 with averages of 6732.9, 6730.6, and 6608.1 kg/ha, respectively, not only produced the highest grain yield but also showed the highest grain yield stability and tolerance to terminal drought stress among the studied genotypes based on the total ranking of all studied stability statistics and stress indices. Therefore, they can be used as new cultivars in drought-affected regions in temperate climates or as desirable genetic materials in barley breeding programs for drought tolerance.   [ABSTRACT FROM AUTHOR]

Background : Khuzestan, as one of the most important corn-producing provinces of Iran, lacks improved cultivars compatible with extremely hot and dry conditions and relies on foreign cultivars, including the old single cross 704 variety. To prepare suitable cultivars for Khuzestan, lines should be produced and evaluated in the region that can be used in the production of hybrid and open-pollinated cultivars. Methods: To identify and improve the important and effective traits on maize grain yield, 289 corn lines, which were bred in Khuzestan, were crossed with the hybrid single cross 704 and evaluated in two cropping seasons (summer 2016 and spring 2017). The experiment was carried out with a simple lattice square design of 17 × 17 and two rep l ications at the Safi-Abad of Dezful Agricultural Research Center in 2016 and 2017. The traits measured from the growing stage to harvest were plant height, tassel length, tassel branch number/plant, stem diameter, number of leaves /plant, ear diameter, grain depth, ear length, number of rows/ear, grain number/row, 100-grain weight, grain yield, biological yield, and harvest index based on the guidelines of the corn and fodder plant department of the Iranian seed breeding and preparation research institute. The yield based on 14% seed moisture along with other traits was measured and calculated from the two middle lines of each experimental plot. The genetic parameters in this research were calculated using the mathematical expectation of the mean square as the basic design of random complete blocks in the form of genetic relationships. To analyze the correlation between the traits and to identify the common factors affecting the studied traits, decomposition into factors was used with the principal component analysis and varimax rotation. Eventually, the analysis of variance (ANOVA) of data and calculation of correlation coefficients between variables were done using SAS Ver 9.20 software and analysis into factors with StatGraphics Ver 19.0 software. Results: The results of ANOVA showed an acceptable genetic diversity among promising maize lines in terms of all studied traits, except for ear length, number of rows/grain, and number of grain/row. The results of the composite analysis in two cropping seasons revealed that the effect of genotype was significant on all studied traits at the level of 1%, suggesting significant genetic diversity among the studied genotypes for all traits. The significance of the genotype × season interaction effect for all studied traits at the 1% level indicates the different response s of genotypes in summer and spring. The highest and the lowest genetic and phenotypic variance s in summer and spring belonged to biological yield and seed depth traits, respectively. The range s of genetic diversity in the studied traits in summer and spring ranged from 1.96 to 32.72 and from 7.63 to 29.88, respectively. Among the studied traits, the highest genetic and phenotypic diversities were observed in the number of tassel branches/plant trait (32.72 and 33.35, respectively). The highest heritability rate s in spring were observed for biological yield (97.69%), grain yield (97.43%), grain depth (97.06%), ear length (96.30%), and plant height (95.74%). On the other hand, the highest amount of heritability along with the highest amount of genetic improvement was observed for the biological yield and grain yield traits, both of which can be considered the most important criteria for selecting parental lines in breeding programs based on this study. The results of the analysis of correlation coefficients for the studied traits in summer indicated that the grain number/row (0.81), biological yield (0.72), ear diameter (0.62), and grain depth (0.52) produced medium to high grain yield s among the studied traits. In spring, the biological yield (0.86), 100-grain weight (0.65), grain number/row (0.64), ear length (0.64), and ear diameter (0.63) had medium to high effect s on the seed yield. The results of analysis in the factor analysis in summer and spring revealed that five hidden and independent factors justified 71.40 and 72.27 % of the total data changes, respectively. Five hidden factors for summer were the share of grain yield from the total dry matter (33.10 %), plant height factor (15.80), ear diameter component factor (8.80), tassel height factor (7.50), and grain weight factor (7.20). Conclusion: The two factors, namely the share of grain yield from total dry matter and the plant height factor, account for more than 61% of the total justifiable variation of 14 traits in 289 lines. These two factors enable us to define and recognize differences and similarities between the lines that grow in spring conditions in Khuzestan. [ABSTRACT FROM AUTHOR]

Background : Lentil is a popular legume crop in the Mediterranean region, widely grown for its nutritious seeds and improving soil fertility. Interest in legumes is increasing as a protein source to replace meat in the future. Identification of high-yield genotypes with adaptation to a wide range of environments is one of the major goals in crop and lentil breeding programs. Combining the best linear unbiased predictions (BLUP), additive main effects, and multiplicative interaction (AMMI) methods in multi-environment experiments and multi-trait stability selection (MTSI) helps to better evaluate plant genotypes and achieve more accurate results. Additive main effect and multiplicative interaction (AMMI) and BLUP are two methods for analyzing multi-environment trials. The linear mixed effects model (LMM) and the restricted maximum likelihood (REML) estimator methods are among the important methods that have been proposed to analyze the data of multi-environmental experiments. In this regard, the BLUPs obtained from the interaction of genotype and environment are performed with principal component analysis or single value analysis on the matrix. This method uses the stability index of the weighted average of absolute scores of the best unbiased linear forecasts (WAASB), the weighted average of the stability index of WAASB, and the dependent variable (WAASBY). Researchers have also proposed an MTSI based on factor analysis, in which grain yield, other traits, and the stability of each are simultaneously used to identify stable genotypes. This research aimed to identify stable and high-yielding lentil genotypes in autumn cultivation. Methods: To evaluate the seed yield stability of 12 lentil genotypes along with three check genotypes, including Kimia, Bileh Sawar, and local landrace, an experiment was conducted as a randomized complete block design with three replications at Agricultural Research Stations of Khorramabad (Lorestan), Zanjireh (Ilam), and Sararoud (Kermanshah) in three cropping years (2019-2022). Each plot consisted of four lines with a length of 4 m and a distance of 25 cm from each other. iIn addition to the usual crop care such as weeding and pest control, the desired traits and characteristics, such as the number of days to 50% flowering, plant height, and number of days to maturity, were measured during the growing season. Hundred-seed weights and the yield of each plot were measured after the maturity and harvesting of experiments. Combined analysis of variance (ANOVA) was performed using SAS software, and the average traits of the treatments were compared using the LSD test. For statistical analyses, the Metan Ver.1.9.0 (multi-environment trial analysis) package was used in the R software environment. To estimate stability quantities, singular value decomposition (SVD) was applied to the matrix of BLUPs obtained from genotype-by-environment interactions with an LMM. Variance components were estimated by the REML method. After analyzing the variance of the data, the stability parameters of WAASB and WAASBY (for simultaneous selection based on average performance and stability) were estimated using the eigenvalues obtained from the AMMI analysis on BLUP, and the best genotypes were selected with these two indicators. Genotypic stability values were obtained from the Harmonic Average of the Genotypic Values (HMGV) index. The compatibility of genotypes was evaluated based on the relative performance index of genotypic values (RPGV). The harmonic mean index and relative performance of genotypic value (HMRPGV) were used to simultaneously evaluate stability, compatibility, and seed yield. Results: The effect of environment, genotype, and genotype × environment interaction were significant on seed yield, plant height, days to flowering, days to maturity, seed filling period, seed filling ratio, seed yield formation rate, rainfall efficiency, and single seed weight. The genotype effect was significant on all traits, except for the seed-filling period. Based on the biplot analysis, genotypes 4, 6, 7, 9, and 10 had higher yield stability in addition to the highest seed yield. The Scree test showed that the first three principal components explained 45.41, 19.13, and 14.34% of the genotype × environment interaction variation obtained from BLUP for grain yield, respectively; in total, they justified 78.87% of the variation. Based on a weighted average of absolute scores of WAASB, genotypes 6, 10, and 12 were high-yielding and stable. Genotypes 1 and 10 were superior based on the (MTSI). The harmonic mean and HMRPGV introduced genotypes 10, 9, 4, and 12 as the genotypes that had high stability and compatibility in addition to high seed yields. Conclusion: Based on all the analyses, genotype 10 was the most stable genotype, which, in addition to seed yield, was superior to other genotypes in terms of the other measured traits and can be a candidate for introduction as a new cultivar. [ABSTRACT FROM AUTHOR]

This research aims to assess the concentration of potentially toxic elements (PTEs) in the soils around the Shahid Rajaei Combined Cycle Power Plant, located 25 km from Qazvin. For this purpose, 25 topsoil samples (0 to 10 cm) were collected, and after sample preparation, the physico-chemical parameters of the samples (including soil’s texture, pH, organic matter, calcium carbonate and cation exchange capacity) were measured. The concentrations of PTEs were determined using an ICP-OES device after strong acid digestion. The obtained results indicate that the average concentration of PTEs decreases in the following order: Mn > Zn > V > Cu > Cr > Pb > Ni > Co > As > Sb > Cd. Enrichment factor values showed that the studied soils are slightly enriched in Cd, Cr and Cu, and are significantly polluted with Pb, Sb, and Zn. Correlation coefficient values, cluster analysis, and principal component analysis show that Cu, Ni, Pb, and Zn are mainly from industrial activities, while As and Cd are probably entered into the soil through agricultural practice (i.e., application of chemical fertilizers and pesticides). Indeed, the highest concentrations of Cu, Ni, Pb, and Zn are recorded in the soil samples collected close to the power plant station in the downwind direction (S-N and NW-SE), indicating that the power plant activity is a possible source of these elements in the studied soils. The health risk assessment of PTEs indicates that As, Cr and Ni cause a cancer risk to children through ingestion. The carcinogenic risks of As, Ni, Cr, Pb, and Cd through all the three exposure routes are higher for children than for adults. [ABSTRACT FROM AUTHOR]

Increasing population growth and thereby increasing exploitation of ground water resources has led to not only decreased quantity but also reduced quality of these valuable resources. Therefore, necessity of studying the quality of water in these areas can help proper management of these water resources. The aim of this study was to determine the groundwater quality variables using principal component analysis and then to evaluate the efficacy of the three kriging models namely simple kriging, universal kriging, and ordinary kriging in interpolation of the most important qualitative variables defined in Bam plain. For this purpose, of the 60 existing wells, 40 wells with good distribution in the study area were selected randomly as for training and the remaining wells were used to test the models. Results of principal component analysis showed that the two variables EC and TDS as the main variables explained the highest changes in variance of other water quality variables. Results of interpolation based on these two parameters showed that ordinary and universal kriging were relatively same in estimating the salinity in the training step, but in the testing step, in the KO method, the RMSE and MAE coefficients are 24.422 and 35.153 microsiemens per centimeter, respectively. These values have differences of 1.22 and 0.52 µs/cm less than the KU method, and consequently, they are superior to Universal Kriging. In interpolation of variable TDS in both the training and testing steps, ordinary kriging had the best performance compared to the two other methods. Interpolation results based on these two variables also showed that the salinity in the north and northeastern parts of the plain in two ordinary and universal kriging was higher than other places indicating a good conformity with changes in land use. [ABSTRACT FROM AUTHOR]

Introduction: Powerful and practical statistical packages have simplified the analysis and thus developed the application of data science in all research fields. Accordingly, regression has been applied to almost all aspects of the life sciences. However, misuse of this model has been reported in the past decades. This article aims to examine modeling with this important statistical method and introduce readers to the correct use of this method. Materials and methods: This review article uses real data, and the supplementary materials provide the method for performing the regression analysis in SAS and R statistical software and their related codes. Results: In the required assumptions of the regression model, the residuals of the model must be normally distributed, but performing the normality test for the actual values of the response variable or any of the explanatory variables is not mandatory. Therefore, researchers should not obsess more than necessary about the normal distribution of real data. On the other hand, almost all normality test methods, such as Kolmogorov-Smirnov, are designed for large numbers of data, typically more than a thousand samples. This suggests that using such methods to test the normality of model residuals estimated from a small number of data, mostly less than a hundred cases, would be inaccurate. Another issue regarding applying the regression model is related to the co-linearity of the explanatory variables. There are still signs of correlation in a data set where all variables are generated separately and randomly in a statistical package. This means that it is very hard to find a correlation coefficient equal to zero (r = 0) even between any pair of separate, random variables. Therefore, in all regression models, there are some kinds of correlation between explanatory variables, but the important issue here is that only high correlation causes severe problems in the model. For collinearity test it would be better to use specialized methods such as Variance Inflation Factor (VIF) or Principal Component Analysis (PCA). The linearity of the model is one other assumption of regression model. Data transformation might be helpful under the situation of non-linearity of the model. However, transformation changes the variables unit, altering the array direction in a geometric space. Researchers should be careful regarding the use of modeling a large number of data affects the probability values in variance analysis due to increasing the value of the degree of freedom of the model. Conclusion: As the number of data points increases, the degree of freedom of the error term increases rapidly. Therefore, the final error mean squared significantly reduces. In contrast, the scatter of data points around the regression line may be too wide. For this reason, using the coefficient of determination, usually called (R-Squared), is a suitable criterion for testing the model's fit. High coefficient values indicate a suitable model for the data set used. It should be noted that in a multiple regression model, the higher the number of explanatory variables used in the model, the higher the value of this coefficient increases. For such conditions, when the number of explanatory variables is large, another form of this coefficient, called the adjusted coefficient of determination (adjusted R²), has been introduced. The use of this coefficient in the approximations creates a limit on the number of variables used in the regression model. Accordingly, the number of variables in the model as explanatory variables should not exceed the number of samples (or the number of tens) in a set, and researchers should avoid using more variables than the number of samples. [ABSTRACT FROM AUTHOR]

Introduction: Drought stress is one of the most significant limiting factors in agricultural production. Numerous quantitative indices have been proposed to assess plant drought tolerance. These indices, which compare plant performance under both stress and non-stress conditions, are valuable tools for evaluating drought-resistant plant varieties. Materials and methods: Eight wheat cultivars were evaluated in the Dashtestan region of Bushehr Province to assess the impact of drought stress on yield using drought stress indices. The trial was conducted on two adjacent fields, utilizing two irrigation regimes and implementing a 50% drought stress. The experiment was arranged in a randomized complete block design with three replicates during the 2023-2024 growing season. The grain yield per plant was measured using the standard method. After confirming the normality of the data distribution with the Kolmogorov-Smirnov test, an analysis of variance was conducted using SAS software (version 9.4). R software was employed to conduct correlation analysis, principal component analysis, and create scatter plots of the data. Furthermore, a biplot analysis was performed based on the results of the principal component analysis. Results: The analysis of variance indicated that the imposition of drought stress significantly decreased the grain yield per plant across all cultivars. Under irrigated conditions, Chamran (18.29 g/plant) and Mehrgan (17.96 g/plant) demonstrated the highest grain yields. Conversely, Koohdasht (11.90 g/plant) and Aftab (8.70 g/plant) yielded the most significant amounts under drought stress. Various drought tolerance indices, including TOL, MP, HM, STI, YI, GMP, SSI, YSI, and RSI, were utilized to evaluate the drought tolerance of the cultivars. Correlation analysis revealed a negative relationship between grain yield and the indices TOL, MP, GMP, HM, and STI under well-watered conditions. Furthermore, a negative correlation was also observed between yield and both TOL and SSI. The 3D plot analysis utilizing the studied indices indicated that the cultivars Karim, Dehdasht, and Savarez are not well-suited for cultivation in the Dashtestan region of Bushehr. The Koohdasht cultivar was situated in Region C, adjacent to Region A, as illustrated in the diagram. This positioning suggests that it can endure stress while also thriving under irrigated conditions. Factor analysis of the stress indices revealed the identification of two components that collectively accounted for 99.8% of the total variation. These components were designated as 'yield adaptation to stress' and 'yield adaptation to irrigation'. The biplot of drought tolerance indices indicated that the Karim cultivar was situated in close proximity to the SSI vector, further confirming the cultivar's sensitivity to drought stress. Additionally, the correlation between yield under drought stress and the harmonic mean (HM), relative stress index (RSI), and yield index (YI) suggests that these indices can be considered for cultivar selection in stress conditions. Conclusion: The results indicated that drought stress significantly reduced grain yield across all wheat cultivars. Chamran and Mehrgan cultivars exhibited the highest yields under well-watered conditions, whereas Koohdasht and Aftab cultivars demonstrated superior performance under various levels of drought stress compared to other cultivars. There was a negative correlation between grain yield and the indices TOL, MP, GMP, HM, and STI under well-watered conditions. Furthermore, a negative correlation was also observed between yield and both TOL and SSI under stress conditions. Due to their sensitivity to drought stress, the cultivars Karim, Dehdasht, and Savarez are unsuitable for cultivation in the Dashtestan region of Bushehr. Performance, harmonic, and relative stress indices are recommended for the selection of drought-tolerant cultivars. [ABSTRACT FROM AUTHOR]

Introduction: Wheat is the most important food crop in the world in terms of cultivated area, commercial value and human nutrition. It plays the biggest role in providing food security in the world compared to other agricultural products. Drought is one of the major environmental factors which threaten wheat production worldwide. Drought and heat stress are two main factors reducing wheat productivity worldwide. Therefore, it is inevitable to improve and release new wheat cultivars adapted to adverse climate change. Drought stress during sensitive growth stages of wheat, including grain filling, decreases kernel weight and the number of grains in the spike, which results in a considerable drop in wheat yield. In recent years, numerous studies have focused on identifying wheat genotypes that are wellsuited to dry conditions. Local varieties and wild relatives are being explored as primary sources of drought tolerance. The results of these studies serve as a foundation for further research into specific species found within wheat germplasm. Materials and methods: Nineteen genotypes were studied in this research to identify the tolerant genotypes to drought stress. Nineteen indicators were used to assess the genotypes regarding sensitivity and resistance to drought stress. Due to the difference in the indicators' results, the RS rating was used for more accuracy, which is based on the average and standard deviation of the ratings. Finally, the top genotypes were recognized by this ranking. Results: Considering all indicators, Genotypes 11, 4, and 5 were ranked highest and recognized as drought-resistant genotypes. Principal component analysis was conducted for drought resistance indices, revealing that the first two components made the largest contribution in explaining the variance of the data. The first component accounted for 66.78% and the second component accounted for 32.50% of the total variance. Based on the calculated indices, genotypes were categorized into four distinct groups. Genotypes 11, 4, and 5, which were identified as the best genotypes based on RS, were grouped together. Through cluster analysis, genotypes were further classified into four groups: resistant, semi-resistant, semi-sensitive, and sensitive. Conclusion: The results showed that Genotypes 4, 5, 11, and 14 had the highest YS, HAM, and YI indices under drought stress conditions. In contrast, Genotypes 1, 6, 7, and 10 had the lowest YS and YI values. These findings align with previous research showing that grain yield in stress and non-stress conditions is the best criterion for evaluating drought resistance. [ABSTRACT FROM AUTHOR]

Introduction: Sunflower (Helianthus annuus L.) is one of the most valuable agricultural products, mainly cultivated for edible oil. As an oilseed plant, the sunflower has the fifth place in the world after soybeans, rapeseed, cotton and peanut. Due to climatic changes, reduction of water received from rains and incorrect management of water consumption, the crop production experienced severe drought stress during the growth period which causes the fluctuation and decrease of the product. Considering the importance of studying and selecting cultivars tolerant to abiotic stresses such as drought stress, investigating the genetic diversity for adaptive responses in sunflower cultivars and genotypes, as well as identifying QTLs are necessary for breeding programs. The aim of this study is to investigate genetic diversity and identify markers related to drought tolerance in the inbred lines population of oilseed sunflower using the REAMP (retrotransposon microsatellite amplified polymorphism) markers. Materials and Methods: In the present research, the genetic diversity of an oilseed sunflower population including 100 inbred lines was evaluated in terms of morpho-physiological traits using a 10x10 simple lattice design with two replications under two normal and limited irrigation conditions during two consecutive years. Different morpho-physiological traits were measured under both conditions. DNA extraction was done from 78 lines out of 100 investigated genotypes by CTAB method. Then, in order to evaluate the quality and quantity of extracted DNA, 1% agarose gel electrophoresis and spectrophotometry were used. The molecular profile of genotypes was prepared using 7 REAMP primers combinations. Based on molecular data and Neighbor Joining algorithm in DARWin 6.0.21 software the studied genotypes were grouped in three groups. Cluster and population structure analyses as well as analysis of molecular variance were performed with GenAlEx and Structure 2.3.3. The number of possible sub-populations (optimal K) was determined based on the delta K (ΔK) method. For optimal K, the Qst matrix was calculated. Using mixed linear model (MLM) related to Q + K matrices (matrix of population structure coefficients + matrix of kinship relations) molecular markers associated with studied morpho-physiological traits were identified. Results and Discussion: Based on the results of cluster analysis, the genotypes were grouped into 3 groups. Each group included genotypes from different geographical areas. The results of principal component analysis showed that the first three components explain 71.32% of the total changes. Principal coordinate analysis was not able to completely separate the genotypes into separate groups. Molecular analysis of variance showed that 91% of the variation are within group and the rest 9% are between the groups, which indicates high genetic diversity within the groups. According to the mixed linear model, totally 20 molecular markers showed a significant relationship (P≤0.01) with the studied morpho-physiological traits under both normal and limited irrigation conditions. "6181810" marker with oil content and "cf8267" marker with two leaf length and leaf width traits showed a significant relationship (P≤0.01) under limited irrigation conditions. "658268" marker showed a significant relationship with yield and leaf width traits under both normal and limited irrigation conditions. Observing the relationship between one marker and several traits can be derived from the effects of pleiotropy or the linkage of genomic regions involved in the control of these traits. Conclusion: The results obtained from this study present valuable information on the genetic basis of studied traits that can be used for breeding and developing high performance varieties in sunflower. In this research some common markers were identified. Identification of markers that showed linkage with several traits in both conditions, such as "658268" and "cf8267" markers, are more important in the breeding program due to the possibility of simultaneous breeding of several traits. [ABSTRACT FROM AUTHOR]

The advancements in the field of information and communication technology have paved the way for economic and societal progress and development. The penetration of technology into various aspects of life and society has led to the emergence of the concept and method of the digital economy, which has increased economic productivity. In this research, the Digital Economy Infrastructure Index (DEII) has been used to examine the position and performance of the digital economy. The performance of this index in the provinces of Iran is composed of components such as the number of fixed telephone users, the number of mobile phone users, the number of internet users, and internet bandwidth, considered for the period from 2013 to 2023. This research has been conducted using an analytical-descriptive method, and the ranking of the Digital Economy Infrastructure Index (DEII) in the provinces of Iran has been completed using the method of principal component and cluster analysis. According to the research findings, the provinces of Tehran, Isfahan, and Razavi Khorasan ranked first to third, respectively, while the provinces of North Khorasan, Ilam, and Kohgiluyeh and Boyer Ahmad ranked twenty eighth to thirtieth, respectively. Additionally, the performance of the provinces in the field of the digital economy was divided and categorized into three clusters: very suitable, suitable, and very unsuitable. Based on the examination of the digital economy performance of the provinces and the categorization of the provinces, the path for digital economy policy making and planning in the country can be facilitated. [ABSTRACT FROM AUTHOR]

Introduction and Objective: The genetic diversity of plant species and their relationship with wild species is very important to improve the yield of crops. The first step in the improvement of medicinal plants is to identify and collect endemic genotypes. Endemic genotypes are very important in the selection of cultivars due to their adaptability to the climate of the region. Mentha longifolia is one of the important endemic medicinal plants of Iran, which is used in various pharmaceutical, food and cosmetic industries. Essential oil, phenolic compounds, flavonoids and other compounds such as steroids and ceramides are important chemical compounds in oregano plant. In this study, morphological diversity, essential oil and antioxidant activity of 20 Mentha longifolia genotypes in West and East Azerbaijan provinces were investigated. The aim of this research, on the one hand, is to know the potential and range of diversity of Menta longifolia genotypes in its natural habitats in West Azarbaijan and East Azarbaijan provinces. On the other hand, the introduction of regions with superior genotypes in terms of these traits is for use in breeding programs. Material and Methods: The collection of plant samples from some areas of two northwestern provinces of Iran (West Azerbaijan and East Azerbaijan) was done in the spring of 2022. In order to evaluate the morphological traits of the plant in the flowering season, 11 quantitative traits of the plant including plant height, inflorescence length, crown diameterstem diameter, internode length, leaf length, leaf width, number of leaves, number of inflorescences, fresh weight, dry weight and the number of sub-branches were evaluated. After drying the plant samples, essential oil extraction was done using a clonger, and the essential oil samples were transferred to Urmia University Jihad to identify compounds by gas chromatography. Extraction of plant samples was done by ultrasonic method. Antioxidant activity was evaluated by DPPH method. All the obtained data were analyzed with three repetitions and based on a completely random design using SPSS software. LSD test was used to compare the mean data. Data clustering was done based on Ward's method and Euclidean distance square measure. Principal component analysis was performed on the data. Also, in this study, correlation between studied traits was done by R software. Results: The results of analysis of variance showed that the genotypes collected from different regions have significant differences in terms of plant height, inflorescence length, crown diameterstem diameter, internode length, leaf length, leaf width, number of leaves, number of inflorescences, fresh weight, dry weight and the number of sub-branches are investigated (P < 0.01). The results of the analysis of the percentage and chemical composition of the essential oil showed that the type of genotype had a significant effect on the amount of these compounds in different genotypes of Mentha longifolia (P < 0.01). Among the studied genotypes, the highest percentage of essential oil and the amount of Trans-Caryophyllene and Germacrene D compounds were found in G18 of Iranq region of Tabriz, also the highest amount of Alpha-Terpineol and Spathulenol was found in G16 of Aghajari region of Maragheh. Also, there was a significant difference between different genotypes of mint in terms of antioxidant activity. The maximum amount of antioxidant activity (80.81%) was observed in G3 of Hachesu area in Shahindej. Based on Ward's cluster analysis, the genotypes were divided into three main groups. G1 alone was placed in a separate group due to the high content of Spathulenol and high antioxidant activity. The second group, which includes most of the genotypes (G2, G3, G5, G16, G19, G17, G20, G12, G14, G4, G6, G8, G11, G13, G9, G7 and G10), has a moderate amount of morphological traits, essential oil components and antioxidant activity. G15 and G18 genotypes were placed in the third group. The prominent features of these genotypes were high values of length and number of inflorescences, length and width of leaves, number of leaves, fresh and dry weight of the plant, number of sub-branches, percentage of essential oil, alpha-Humulene, trans-Caryophyllene and GermacreneD and antioxidant activity. Using principal component analysis, 21 primary variables were determined in the form of two principal components. The first component explained 40% and the second component 19% of the total variance. The results of correlation analysis showed that there was a positive and significant correlation between the percentage of essential oil and some morphological traits, the percentage of essential oil and the amount of Germacrene D, trans-Caryophyllene, beta-Farnesene and isomenthon, as well as antioxidant activity and morphological traits. Conclusion: The findings of this study showed that G15 belonging to Maragheh with an altitude of 1776 m had the highest number of leaves, length and width of leaves, fresh weight, dry weight and number of subbranches, internode length and number of inflorescences compared to other genotypes. Therefore, it can be said that this genotype has priority for breeding, domestication and crop cultivation projects and is suitable for its introduction to the market as a medicinal plant. In addition, the results showed that the highest percentage of essential oil and the amount of compounds such as Germacrene D, Trans-Caryophyllene, Spathulenol, Beta-Farnesene, Alpha-Terpineol were obtained in genotypes with high altitudes. [ABSTRACT FROM AUTHOR]

Introduction and Objectives: Lathyrus sativus L. is an annual plant from the legume family, used as a very valuable protein source for livestock and poultry, as well as for human nutrition. This genus has several useful agronomic characteristics such as high grain yield capacity and high protein content of its grains. Legumes produce economic performance in different environmental conditions and have a high potential for use in marginal areas with low rainfall. In fact, this has made it a popular crop in subsistence agriculture, especially in developing countries. The greatest importance of grass pea is related to the high resistance of this plant to harsh environmental conditions, such as drought, low soil fertility, and resistance to pests and plant diseases, which makes its production and cultivation economical. Salinity stress is an important abiotic stress that has harmful effects on plant performance and product quality and is a limiting factor for plant growth. Although salinity stress can occur in all growth stages of the plant, but considering that the initial establishment of the plant has a great impact on the final performance. Salinity stress in the seedling stage can be one of the most harmful stages for the plant. To improve the salinity tolerance in crops, genetic diversity between and within species can be used through selection and breeding. The purpose of this experiment was to investigate the response of early-maturing grass pea genotypes to different levels of salinity by evaluating some agronomic traits and identifying salinity-tolerant genotypes. Materials and Methods:In order to evaluate the response of grass pea early maturing genotypes to salinity stress, 26 genotypes were studied as factorial experiment on based randomized complete block design with two replications at Research Farm of Plant Production and Genetics Department, Faculty of Agriculture, University of Maragheh. The salinity treatments were applied to four levels (0, 40, 80, 120 mM) of NaCl and different seedling and agronomic traits such as shoot fresh weight, shoot dry weight, fruit fresh weight, fruit dry weight, number of grains, number of grains per pod, plant height, leaf angle to the stem, leaf length, leaf width, number of leaves, number of shoots, location of the first shoot from the soil surface, root length were evaluated. Also, during the experiment, the date of flowering, the date of pod formation, the date of pod filling and the date of grain maturity were also recorded for each pot. Before data analysis, the assumptions of data variance analysis were checked with tests of normality and homogeneity of variances, and mean comparisons were made using Duncan's method at the 1% probability level. For the grouping of genotypes, cluster analysis was done by Ward's method and Euclidean distance measure using standardized variables. In order to determine the contribution of each trait in the total variation, reduce the amount of data and better interpret the relationships, principal components was used. Results:The difference between genotypes and salinity levels was significant in most seedling traits and with increasing salinity, the dry forage yield was decreased. Genotypes 19, 14, 13, 21, 10, 7, 25, 15, 24 and 12 were the best genotypes in terms of dry forage yield in seedling stage. Also, in the agronomic traits, differences between genotypes and salinity levels were significant in most traits. In general, the yield attribute decreased with increasing salinity. In cluster analysis with Ward's alghorithm, the genotypes were divided into three clusters. The first cluster with the genotypes 8, 23, 11, 21, 7, 20, 2, 22, 3, 10 and 26 had the best genotypes for yield improvement. In principal component analysis, the first four principal components explainaed 82.08% of total variation. Based on the results, the first component could be identified as a component of biological yield and the second component as a forage yield. Thus traits of shoot length, root length, seedling length and the ratio of shoot length to root length were significant for the effect of genotype, salinity and the interaction of genotype × salinity at the probability level of 1%. The traits shoot dry weight, root dry weight and seedling dry weight had a significant effect of salinity at the probability level of 1%, and the trait of the ratio of shoot dry weight to root dry weight had not significant difference for any of the effects. Genotypes 19, 14, 13, 21, 10, 7, 25, 15, 24, and 12 were the best genotypes in terms of dry forage yield in seedling stage. In field traits, the difference between genotypes and salinity levels was also significant in most of the traits. In cluster analysis by Ward's method, the genotypes were divided into three clusters. The first cluster with genotypes 8, 23, 11, 21, 7, 20, 2, 22, 3, 10 and 26 had the best genotypes for yield improvement. In principal components analysis, the first three main components explained 82.08% of the total variation. The first component accounted for 38.31%, the second component for 25.31% and the third component for 19.74% of the total variation. Based on the obtained results, the first component can be named as the biological yield component and the second component as the forage yield. Findings: The difference between genotypes and salinity levels was significant in most seedling traits, and dry forage yield decreased with increasing salinity. Thus, the characteristics of shoot length, root length, seedling length, and the ratio of shoot length to root length were significant for the effect of genotype, salinity, and the interaction of genotype in salinity at the probability level of 1%. The traits dry weight of shoot, dry weight of rhizome and dry weight of seedling had a significant effect of salinity at the probability level of 1%, and the trait of the ratio of dry weight of shoot to root had no significant difference for any of the effects. The results of seedling stage showed that genotypes 2, 6, 10, 13 and 26 (local) had high yield and genotypes 1, 3 and 5 had the lowest forage yield. The field results showed with the increase of salinity levels, a decrease in yield was observed. Conclusion:Generally, with increasing salinity, forage yield decreased. The genotypes 10, 20, 22 and 23 the most tolerant genotypes and genotypes 16, 17, and 18 were identified as the most sensitive genotypes. [ABSTRACT FROM AUTHOR]

Introduction: Oat, as a dual-purpose cereal, has an important role to provide human food and animal feed and fodder regarding to its high amounts of beta-glucan, protein, vitamins, minerals, fatty acids and valuable antioxidants. Oat breeding programs have been steadily decreasing compared to other cereals due to decrease in cultivated area. Therefore, identifying and studying sources of diversity in oats is critical and valuable regarding to release new cultivars with better quality and higher grain yield per unit area. Thus, this experiment was carried out with the aim of evaluating different genetic parameters and principal component analysis in order to determine the amount of genetic diversity in oat genotypes. Materials and methods: In this study, 361 oat genotypes of seven species belong to 50 countries from five continents which were received from Australian Grain Genebank (AGG) and kept in the genebank of the Campus of Agriculture and Natural Resources, Razi University were investigated. Estimation of the genetic parameters related to plant height, panicle length, days to 50% flowering, days to 50% physiological maturity, biological yield, grain yield, straw yield, harvest index, thousand seed weight, number of seeds per panicle and number of panicle per square meter of the genotypes were performed. This experiment was conducted in a simple square lattice design with two replications under normal irrigation condition, in two cropping years 2017-2019 in the research farm of the Agriculture and Natural Resources Campus, Razi University, Kermanshah. Results: Based on the results of the one-year variance analysis, there was a highly significant difference between genotypes regarding all the measured traits which indicates the presence of considerable genetic diversity between these genotypes. The results of mean comparison based on LSD method showed (NILE), (KENT), (LA PREVISION), (ZLATAK), SDO-185), OX87:080-2), (ACACIA), AND (DUNNART) genotypes had the highest grain yield for two years, while, Genotypes (LIGOWA), (NILE), (VENTURA), (YULAF), (NMO-712), (SDO-185), (VDO-931.1), (SLAVUGE), and (no.9278) had the highest mean for biomass in two cropping years. The results of the descriptive statistics showed the wide range of changes for the most of the investigated traits, as it was variable for grain yield from 56.30 to 789.81 g/m2 in the first year and from 39.59 to 627.28 g/m2 in the second year. Based on the results of correlation analysis, the most positive and significant phenotypic correlation was calculated between biological yield and straw yield in both years. The result of phenotypic and genotypic correlation also, showed a significant relationship between grain yield and all studied traits except plant height, panicle length, days to heading, and days to maturity in the first year. Also, it had a significant phenotypic correlation with all traits except plant height and straw yield in the second year. The traits of 1000-kernel weight, plant height, days to heading, and number of panicles per square meter had the highest genetic variance in both years. The range of general heritability in the first year was variable from 70.06 to 95.87%, respectively, for the traits of days to physiological maturity and 1000 seed weight, and in the second year, from 77.85 to 94.91% for biological yield and 1000 seed weight. Grain yield, biological yield, straw yield, number of panicles per square meter, and number of grains per panicle had a high percentage of heritability and genetic advance simultaneously. Based on the principal component analysis the first two main components explained 63.3 and 67.8 percent of the total changes in each year, respectively. Conclusion: The results of variance analysis of the data obtained from this study indicated the existence of significant genetic diversity among the evaluated genotypes in terms of all measured traits, which can be attributed to the existence of different species with different geographical origins. Comparing the average data, genotypes 336, 349, 356 and 360 were introduced as the genotypes with the highest average grain yield in both years. Based on the results of Principal Component Analysis and Correlations Analysis, it can be found that the attributes of the number of panicles per square meter, the number of grains per panicle, 1000-kernel weight, and biological performance are very effective in breeding programs to achieve superior varieties. The genotypes NILE, LA PREVISION, OX87:080-2 and DUNNART were the superior genotypes in terms of the mentioned traits and grain yield. The estimation of genetic parameters showed that the selection based on the number of panicles per plot, the number of grains per panicle, and plant height plays a significant role in improving grain yield because of having a high broad heritability and significant genetic advance at the same time. According to the results of this study, it is possible to separate the superior genotypes in terms of grain yield and biological yield, and perform subsequent tests for grain and fodder genotypes, separately. Also, valuable traits for easier access to this important issue in subsequent oat improvement programs could be identified. [ABSTRACT FROM AUTHOR]

Introduction and Objective: Yield under stress conditions has never been an accurate criterion for selecting drought-tolerant genotypes, and the goal of preparing drought-tolerant cultivars has always been to create cultivars that relatively tolerate stress better compared to other genotypes and in the same agricultural conditions, they show less yield loss. In most studies, only the seed yield is considered for the field selection of crops, while some researchers believe that in order to be more efficient in breeding compatible and superior cultivars in arid and semi-arid regions, the indicators that are effective in identifying the stability of cultivars under drought stress conditions should be identified and used them as selection index in addition to seed yield, therefore, the relative uield status of genotypes in drought stress conditions and water conditions is a starting point for identifying and selecting genotypes for improvement in dry environments. In semi-arid regions where the distribution of rainfall is not proportional, the yield potential in stress conditions is not considered the best criterion for drought tolerance, but in addition to yield stability, the comparison of yield in stress and optimal conditions is a more suitable criterion for the reaction of genotypes to moisture stress. Due to the fact that most of the studies related to indicators in crop species and especially wheat are done only in one place and one year and finally in a specific environment and the results are generalized to all environments and the variable effects of year and place are not taken into account in the calculation of indicators. In this regard, this research was carried out to evaluate the genotypes of autumn wheat in terms of drought tolerance, to select the best drought tolerance indices and to identify drought stress tolerant cultivars in different regions of the country's cold climate. Material and Methods: In this research project, 20 genotypes under normal irrigation and water deficit conditions in the form of randomized complete block design (RCBD) with three replications in the research stations of Karaj, Mashhad, Miandoab and Arak, in the crop years of 2017-2018 and 2018-2019 were investigated. In order to investigate the drought tolerance of the genotypes, different tolerance and stress sensitivity indices were determined for the genotypes under investigation and the genotypes were grouped based on the sensitivity and tolerance to drought by each of these indices. Principal component analyzing was also used in order to summarize the data and draw a diagram based on the first two components and identify the desired indicators. Finally, biplot analysis was used to group genotypes and indices based on drought tolerance criteria. Results: Stress decreased the Yield of genotypes, but the amount of reduction was different in different genotypes. The average grain yield for all genotypes under normal irrigation conditions and drought stress at the end of the season was 7.002 and 5.215 tons per hectare, respectively, which showed that the stress conditions caused a decrease of about 25% in grain yield compared to normal irrigation conditions. The environmental and agricultural conditions of different regions and the studied years caused differences in the estimated indices so that the ranking of genotypes changed based on different indices in different years and regions therefore, it is better to carry out studies on stress tolerance indices in several places and several years so that the process of functional changes of different cultivars and genotypes is correctly determined and as a result, there is more confidence in the calculated tolerance and sensitivity indices. Genotypes G4, G2, G16 and G5 showed higher yield in both conditions. STI, MP, GMP, MSTI1, MSTI2, YI, HM, and RR had a positive and significant correlation with grain yield under normal and stress conditions, and therefore, they can be used for more favorable selection of drought tolerant genotypes. Principal component analysis showed that indicators can be grouped using the first two components. The first principal component explained 53.16% of the changes in the total data and had a positive and significant correlation with yield in normal and stress conditions as well as MP, STI, GMP, YI, MSTI1, MSTI2, HM and RDY indicators. Due to the high correlation of this component with yield under normal and stress conditions, this component was named as the yield potential component under normal and stress conditions. The second estimated component justified 42.33% of the total data changes and showed a positive and significant correlation with yield in normal conditions and SSI, TOL, ATI, SSPI and RR indices. It seems that this component is able to identify genotypes that have high yield under stress conditions. Biplot analysis showed that HM, MP, STI, MSTI1, MSTI2, GMP, RDY, YI, and SNPI indices had a positive and high correlation with performance under stress and normal conditions. So that the sharp angles between these indices showed their positive and very high correlation with each other. RDI and YSI indices had a negative correlation with performance in normal conditions and RR, SSI, TOL and SSPI indices had a negative correlation with performance in stressful conditions. Conclusion: In order to achieve varieties resistant to drought stress by using indices, in order to prevent the mutual effects of the environment in the genotype, the experiments should be carried out in many years and places so that the effects of the environment in the calculated indices can be reduced and more reasonable results can be obtained. Finally, G4, G2, G16, G5 and G17 genotypes can be selected as genotypes with high performance under normal and stress conditions. [ABSTRACT FROM AUTHOR]

This article proposes a new approach for identifying damage in structures through model updating. The approach is based on principal component analysis (PCA) of strain-based power spectral density (PSD) data. The proposed method detects damage, identifies damage location, and quantifies damage severity using an innovative sensitivity equation of strain-based data on a least square optimization. The data is obtained from incomplete measured structural responses, and the approach utilizes frequency domain data where changes in stiffness matrix of elements model damage. One of the crucial components for successful model updating is evaluating an accurate sensitivity relation. Highly sensitive structural indices such as PSD data require a valid sensitivity relation to yield satisfactory results. The PCA technique provides an advantage by transforming PSD data to PCs with the most significant changes and ignoring PCs that correspond to low changes caused by measurement errors. The presented approach embeds the PCA of incomplete PSD data and measured strain data for a damaged structure into a mathematical formulation to obtain an appropriate sensitivity equation. To prevent weakening the sensitivity equation, the proposed formulation does not employ derivatives of the PCs. The proposed method is applied to two steel structures, a 2-D truss and a 2-D two-story two-bay frame, to demonstrate its performance as a strong damage identification algorithm, even in the presence of measurement errors. Comparative observations indicate that the results obtained by the provided sensitivity equation and strain-based PSD data are more appropriate than the results of other strain-based methods such as PCA-FRF or using only PSD data.

The present survey was conducted to investigate the ecological distribution range of woody species and the most important factors affecting their distribution in the Zagros forests of Ilam province. physical and chemical characteristics of soil, as well as topographical factors, were assessed in 109 circular sampling plots with an area of 500 m² n four forest areas with an altitude range of 800-2400 m. The vertical distance of the plots on the slope aspect was 100 m, and the distance of the sampling routes varied from 500-1000 m. ecological distribution range index was calculated based on the most important factors affecting species distribution. Based on the Principal Component Analysis (PCA), the most significant factors include: the percentage of theclay, Potassium, nitrogen, carbon, sand, phosphorus, and altitude. species such as Amygdalus orientalis, Lonicera nummularifolia, Daphne mucronata and Cerasus mahaleb and Acer monspessulsnum were found at hight altitudes with the highest levels of carbon, nitrogen, potassium and phosphorus. In addition, Quercus brantii along with Acer monspessulanum and Daphne mucronata showed the highest ecological distribution range while Pistacia atlantica, Amygdalus arabica and Amygdalus orientalis species respectively has the lowest values. Overal, results indicate that topography and soil factors play an important role in the distribution of woody species in the studied areas. [ABSTRACT FROM AUTHOR]

Introduction and Objective: Due to the droughts of the last few years, the low need of barley crop to water and rich soil, the need of the country in the supply of Community Food and the importance of barley in the food industry, therefore, it is necessary to introduce high-yielding and drought-resistant genotypes. Material and Methods: The research was conducted at the Ilam Agricultural Research Station in 2020-2021. Identification of tolerant and sensitive genotypes was based on grain yield and drought tolerance indices. Accordingly, 16 barley genotypes were implemented in the form of random complete blocks with four repetitions in two conditions: dim and supplementary irrigation. After harvesting, grain yield was measured and stress tolerance indices were calculated. Results: The results of correlation between drought tolerance indices and grain yield in rainfed and irrigated conditions showed that tolerance index (STI), mean productivity (MP), harmonic mean (HM) and geometric mean productivity (GMP) were positively correlated, and had significance with grain yield traits in both environmental conditions. So, they were suitable indicators for selecting high yielding genotypes in both rainfed and irrigated environments. Based on SIIG index, genotypes 11 and 9 show the highest values, while genotypes 3 and 4 had the lowest values. Also, factor analysis based on principle component analysis showed that the first two factors explain 98.5% ((the first factor 68.7% and the second factor 29.8%) of the total diversity. Conclusion: Based on the obtained results, genotypes No. 9 and 11 have the highest resistance to drought stress and yield, which are suitable for cultivation in areas under moisture stress, and genotypes No. 3 and 13 are suitable for planting in areas without moisture stress. [ABSTRACT FROM AUTHOR]

Background: Fire is one of the most significant ecological elements that can alter the functioning of natural ecosystems, as well as one of the most significant natural disasters that endangers the ecosystem of forests. The intensity and frequency of forest fires are increasing daily due to the consequences of global climate change and population growth in sensitive areas. This factor not only damages individuals and property but also poses a serious risk to environmental preservation and the well-balanced ecological conditions of vegetation. Worldwide, thousands of fires in natural areas result in unquantifiable and unfathomable calamities each year. For many years, this problem has been the subject of investigation. The investigation of the fire that occurred in 2021, the conditions of its creation, and its effect on the soil and vegetation characteristics of the Qara Qeshlaq Lagoon are the most important goals of this research. Methods: An area of approximately four hectares of the Qara Gheshlagh Lagoon was burned twice on April 16, 2021, in two different time frames (hours) at 15:30 and 19:30. This area was chosen to investigate the effect of fire on the geological characteristics and vegetation of the wetland. Furthermore, a control area (unburned) was chosen to be close by, of the same size and at the appropriate distance from the burned region. The vegetation was sampled along a transect that ran along these regions. Given that the vegetation in both the burned and control areas is densely covered by Tamarix, 40 rectangular sample plots (a total of 80) with an approximate area of 10 m2 (5 x 2 m) and a distance of 20 m from each other were used to record the height, collar diameter, dbh, small and large diameters of the crown, the number of sprouts, and stem health traits. The percentage of grass cover was determined using a 1-m2 sample plot in the center of the sample plots. Additionally, five randomly selected sample plots were used from the center to measure the soil physicochemical characteristics, including its acidity, electrical conductivity, organic carbon, percentage of lime, percentages of clay, silt, and sand, and absorbable potassium and phosphorus. A soil sample was taken from a depth of 0-10 cm. After determining the normality of the data distribution with the Kolmogorov-Smirnov test, the Mann-Whitney and independent t-tests were used to compare the average quantitative characteristics of the vegetation cover and soil characteristics in the two burned and control areas. In addition, the principal component analysis (PCA) was utilized to explore the most essential fire-related elements in vegetation cover and soil. Results: At the 99% confidence level, the average collar diameter in the burned region was significantly higher at 4.41 cm than in the control area (3.17 cm). The average dbh (1.64 vs. 1.24 cm) and the number of sprouts (20.05 vs. 14.76) varied significantly in the burned and control areas, with a 95% confidence level. Additionally, a significant difference was observed between the average tree height (1.96 vs. 1.36 m), the percentage of grass cover (70.19 vs. 50.28%), and the stem health (all healthy stems versus all burnt stems) in the control and burned areas at the 99% confidence level. After about a year of the fire, there was a difference in pH characteristics (7.12 vs. 6.73) and sand (27.10 vs. 22.90%) in the two burned and control areas, with a significant difference at the 95% confidence level . A significant difference in the properties of organic carbon (2.86 vs. 1.71%), phosphorus (71.63 vs. 34.28 mg/kg), and potassium (921.40 vs 606.60 mg/kg) was seen in these two areas at the 99% confidence level. The PCA results revealed an effect of fire on the organic carbon, phosphorus, and available potassium parameters. Among the vegetation cover characteristics, the most effects belonged to the dbh, the collar diameter, tree height, and the large and small diameters of the crown with a factor load greater than 0.8. Conclusion: According to the current study, the quantitative features of the trees in the wetland were impacted in the burnt area, and changes occurred in vegetation and soil characteristics. As a result, all of the soil properties were significantly higher in the burned region than in the control area. Other than the collar diameter factor, other plant features in the burned region dropped dramatically. Thus, careful management and conservation of such areas following the fire is critical to restore the strength and potential of ecosystems to ensure the continuance of survival and sustainability. Therefore, it is advised to investigate the long-term impacts of fire on vegetation alterations and to accelerate the reconstruction process of the region by protecting such ecosystems and carrying out restoration operations. [ABSTRACT FROM AUTHOR]

Introduction: Festuca species are forage grasses that are very important in terms of fodder supply and soil protection. The seeds of these plants have internal dormancy (physiological) and are unable to germinate easily. Therefore, they must be subjected to various treatments to germinate. In nature, this dormancy is broken during the cold period of winter (chilling). The purpose of this research is to investigate different methods of dormancy breaking in Festuca species for large-scale production and accelerate the germination process. Materials and methods: In this research, three species of Festuca (Festuca arundinacea, F. ovina, and F. rubra) were subjected to different treatments of chilling (4°C, 14 days), osmo-priming with potassium nitrate (KNO3) 1.5% and gibberellic acid 150 and 200 ppm. After 14 days of germination test, various germination indices including percentage and rate of germination, mean germination time, seed vigor index, length of radicle, shoot and seedling, and the ratio of radicle to shoot length were calculated. Results: The results of the analysis of variance showed a significant difference between species (except for germination percentage and root length traits) and treatments (for all traits). The interactions between the species and treatment were also significant for all traits (except for the length of radicle and seedling). Among the three species, the percentage of germination varied from 26.67 to 30.67% and the value of the germination rate varied from 1.92 to 3.31 n/d. The average time required for germination varied from 3.75 to 4.36 days and the seed vigor index varied from 26.74 to 43.02. The radicle length was between 37.22 and 45 mm and the shoot length was between 37.34 and 81.33 mm. Based on principal components analysis (PCA), percentage and rate of germination, seed vigor index, and length of radicle and seedling were introduced as the most important factors in creating diversity in Festuca species. In determining the correlation between traits, a high correlation of 70% was observed between germination percentage, germination rate, and seed vigor index. Conclusion: Among the three species, Festuca rubra was superior to the other two species by having the highest percentage and rate of germination, seed vigor, radical length, and the shortest time required for germination. Among the applied treatments, 1.5% potassium nitrate (KNO3) with chilling (4°C, for 14 days), had a positive effect on the percentage and rate of germination, radical length, and gibberellic acid (150 ppm) treatment had a positive effect on the length of shoot and seedling. The presence of high germination percentage and rate indicated higher seed vigor. [ABSTRACT FROM AUTHOR]

1-Introduction Carbon dioxide is one of the main greenhouse gases that affect the world's air temperature. Small changes in the amount of carbon dioxide emissions from the soil have a significant effect on the concentration of this gas in the atmosphere. Soil respiration, the process that emits carbon dioxide from the soil to the atmosphere, is one of the most important carbon flows in the ecosystem and includes two components of heterotrophic respiration (microbial respiration) and autotrophic respiration (root respiration). Researchers measure the rate of soil respiration for every 10 degrees Celsius of temperature change with an index called temperature sensitivity of soil respiration (Q10). The evidence shows that the Q10 value of the soil is not constant and has a negative correlation with temperature and a positive correlation with soil moisture. Also, the amount of soil organic carbon, incubation temperature and the interaction of these two have a significant effect on soil organic carbon decomposition. Accordingly, this research measures the temperature sensitivity (Q10) in soil under tea cultivation and investigates its relationship with some soil chemical characteristics and topographic indices. 2-Methodology After surveying the east and west tea gardens in Guilan province in the north of Iran, 200 samples were taken at a depth of 0 to 40 cm. The experiments were conducted to determine Organic Carbon, Labile carbon, Bulk density, PH, Cation Exchange Capacity, Microbial Biomass and soil microbial respiration. To measure Q10, two temperature treatments of 25 and 35 °C were used. Elevation, slope and aspect were obtained using a DEM map in ArcGIS 10.5 and other topographical indicators such as wetness index, slope length, relative slope position, catchment area, channel network base level, vertical distance to channel network, convergence index, profile curvature and plan curvature were extracted from DEM map in Saga GIS 2.1.0. Pearson correlation was used to investigate whether there is any relationship between soil temperature sensitivity with other soil properties. Then, principal component analysis (PCA) was performed to determine a minimal data set. All the statistical analyses were done with SPSS 24. Regression charts were also drawn using Excel software. 3- Results The Q10 values varied from 1.19 to 1.58. This index has the most negative correlation with organic carbon (-0.863), Labile carbon (-0.863), microbial biomass (-0.837), respiration at 25 °C (-0.831) and 35 °C (-0.8) at 1% level and negative correlation with elevation at 5% (-0.159). The principal component analysis showed that the first six components (PC1, PC2, PC3, PC4, PC5 and PC6) have special values of more than one and were able to describe 73% of the total variance. The first main component (PC1) describes 23.125% of the total variance and includes soil organic carbon, labile carbon, microbial biomass and Q10 which have the highest factor loading in this component. The second one (PC2), which explains about 12.99% of the total variance, has the highest factor loading with the vertical distance to the channel network (0.880). The third component (PC3) explains about 12.22% of the total variance. In PC3, clay has the highest factor loading. In the fourth component catchment area, convergence profile and slope length have the highest factor loading, respectively. Finally, the fifth and the sixth components are related to the elevation, slope and plan curvature. 4- Discussion & Conclusions The highest positive factor loading is related to soil organic carbon (0.981). Therefore, the first main component can be "part of the role of organic carbon in microbial biomass, labile carbon and temperature sensitivity". The results showed that Q10 has the highest negative correlation with soil microbial biomass and organic and labile carbon. In other words, the higher the soil organic and microbial biomass carbon, the lower the amount of Q10. Also, the second component can be considered as topographic indicators related to the channel network. Topographic indices can be used very strongly to model making soil organic carbon. The third component is related to clay properties. Several studies have indicated that the amount of clay has a high relationship with cation exchange capacity and it is a good indicator to determine the quality of soil. According to the results, although the correlation between some characteristics obtained from soil topographical analysis can prove the possibility of using them as auxiliary variables in predicting soil organic carbon, this point should be taken into account that other factors also play a role in the process of soil formation and development. [ABSTRACT FROM AUTHOR]

Background and objectives: Plant species performance and productivity in rangeland ecosystems depend on their interactions with environmental factors. Understanding these interactions helps predict species distribution and guides rangeland management practices. This study aimed to identify the environmental factors influencing the distribution of Ferulago armena (DC.) Bernardi in Kileh Shin and Gardneh Khan pastures of Baneh, Kurdistan province. This knowledge can inform strategies for protection, restoration, and potential uses of F. armena in mountain rangeland management. Methodology: Stratified random sampling was employed to collect soil and vegetation data within vegetation types containing F. armena. Two transects of 50 meters each were established, containing 120 plots of 1.75 m². Soil samples were collected within plots to a depth of 30 cm. Plant characteristics, soil properties (acidity, electrical conductivity, nitrogen content, organic matter), and topographical features (elevation, slope, direction, coordinates) were recorded for each plot. Principal Component Analysis (PCA) identified the most influential factors for F. armena distribution. Multiple regression analysis further explored the relationships between species and environmental variables. Results: The typical habitat of F. armena had a 44.22% slope facing north (northwest to northeast), an average elevation of 2095 meters, and a species cover of 43%. Plant species richness reached 10.3, while diversity was 1.946. Dry forage production averaged 513 kg/ha. Soil characteristics included a pH of 6.4, 18.6% gravel cover, an electrical conductivity of 0.13 dS/m, approximately 0.20% nitrogen, and 2% organic matter. Soil depth averaged 36 cm, with a texture dominated by sand (over 50%). Deep gravel content measured 54%. PCA analysis revealed that the first axis explained over 78% of the variation in F. armena plant traits. Species cover and production exhibited a positive and significant relationship (p < 0.05) with organic matter, slope, clay content, nitrogen, elevation, calcium, litter cover, and pebbles. Stepwise multiple regression identified the most influential factors for cover percentage estimation as direction and elevation (R² = 0.905 and 0.952, respectively). For production estimation, the most significant factors were direction and soil depth (R² = 0.845 and 0.873, respectively) (p < 0.01). Conclusion: The study found that F. armena had the highest cover percentage at an elevation range of 2200-2400 meters. Northwesterly and northerly aspects supported higher cover and production. Areas with higher gravel cover (18.6%) and deep gravel content (54%), lighter soil texture (loamy sand), and accumulated plant litter on top of stones and debris provided the most suitable habitat for production and cover of this species. These findings suggest that such locations offer the optimal conditions for the presence and distribution of F. armena within the study region. [ABSTRACT FROM AUTHOR]

1-Introduction One of the important issues in the sustainable management of soils in order to optimize the agricultural production and preserve natural resources is the assessment of soil quality. Soil quality is the capacity of a specific kind of soil to function to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation. It is also considered one of the most important factors investigated in the assessment of soil management. Knowledge of quality changes is necessary for sustainable soil management. Since soil quality cannot be measured directly, it must be obtained from the relevant characteristics. Soil quality characteristics are sets of measurable soil characteristics that are sensitive to land use change, management, or conservation operations. Using soil quality indicators is a useful tool to determine and compare soil quality. The purpose of this research is to quantify the soil quality index using multivariate analysis in different soil types in Urmia Plain. 2-Methodology In this research, according to the semi-detailed soil studies of Urmia plain, 24 soil profiles from different soil units of this area, which are mostly under garden and agricultural use, were excavated, described, sampled, and classified, and 96 samples were also collected from soil solum. 2 profiles in Typic Haploxerepts (TH1) soil type, 4 profiles in Fluvaquentic Endoaquepts (FE) soil type, 6 profiles in Typic Calcixerepts (TC) soil type, 2 profiles in Typic Endoaquepts (TE) soil type, 5 profiles in Fluventic soil type Haploxerepts (FH) and 2 profiles were located in Typic Halaquept (TH2) soil type. At a certain distance from the excavation site of the profiles, four soil samples were taken from four directions of the profile. Using principal component analysis (PCA), among 22 characteristics affecting soil quality (TDS), the minimum characteristics affecting soil quality (MDS) were determined. Then the soil quality in different soil types of region was evaluated using two cumulative soil quality indices (IQI) and Nemuro Quality Index (NQI) and each of them was evaluated in two sets of TDS and MDS in different soil types. 3-Results Among the measured parameters, pH had the lowest (2.5%) and salinity (EC) had the highest coefficient of variation (154.6%) in the region. Among the 22 measured soil properties, sodium absorption ratio (SAR) in the first component, nickel element (Ni) in the second component, cation exchange capacity (CEC) in the third component, sand percentage in the fourth component, active lime (ACCE) in the fifth component and absorbable phosphorus (PAW) in the sixth component were selected as MDS. The examination of the soil quality index showed that the soils of this region mainly have quality grade II (57%). The highest average value of selected soil quality index related to MDS mode in IQI model was calculated with a value of 0.79 in Fluventic Haploxerepts soil type and the lowest average value related to TDS mode in NQI model was calculated with 0.28 value in Typic Halaquepts soil type. The correlation coefficient between the soil quality index with the total category and minimum data in both IQI and NQI models was equal (R2=0.48). 4-Discussion & Conclusions The sequence order of both soil quality indices (IQIa, NQI) in both TDS and MDS conditions in the types of the studied area was as FE>TE>TH1>TC>FH>TH2. Therefore, the highest soil quality was observed in the Fluventic Endoaquepts type and the lowest soil quality was observed in the Typic Halaquepts type. Based on the results, both indicators were classified in three classes (good, medium and poor) in TDS and MDS sets. In the case of TDS, 57.83% of land (equivalent to 19731 hectares) had good class (II), 30.48% of land (equivalent to 10400 hectares) had medium class (III) and 11.69% of land (equivalent to 3990 hectares) they had poor class (IV); (very good (I) and very poor (V) class were not observed). In MDS mode, 18.56% of lands (equivalent to 6333 hectares) had very good class (I), 27.15% of lands (equivalent to 9264 hectares) had good class (II) and 54.29% of lands (equivalent to 18524 hectares) They had medium class (III); (weak class (IV) and very weak (V) were not observed). The degrees of IQIa and NQI indices were similar and were divided into three classes (good, medium and poor). As a result, 39.3% of land (equivalent to 13412 hectares) was in good class (II), 24.59% of land (equivalent to 8392 hectares) was in medium class (III) and 1.36% of land (equivalent to 12317 hectares) was placed in poor class (IV); (very good (I) and very poor (V) classes were not observed). In general, the soils of the region were limited in terms of the studied indicators in the parts leading to the lake, and there was a significant correlation between IQITDS and IQIMDS, and between NQITDS and NQIMDS. This shows that the determined MDS set can be a good representative of TDS in soil quality assessment in Urmia Plain. [ABSTRACT FROM AUTHOR]

In this study some physical and geometrical properties of 11 superior apricot genotypes were determined. These properties such as respiration rate, Mass, fruit dimensions, perimeter, surface area, volume, geometric mean diameter, projected area, shape factor, circularity, compact factor, length to width ratio, length to thickness ratio, and length to mass ratio were measured at harvesting moisture content ranging from 75.19 to 87.67 %. Then the correlation among average values of the attributes was performed and the genotypes were classified using principal component analysis (PCA). The results showed that all the genotypes had significant differences in terms of all the studied attributes (P<0.01). There was a significant and positive correlation between fruit length and weight and fruit length and moisture content. Fruit shape factor and compression factor showed a positive and significant correlation, while these attributes had negative and significant correlations with circularity. This study showed that Iranian apricot genotypes could be discriminated by differences in their geometrical characteristics using principal component analysis. Based on the PCA results, the first two components account for the most of the variation in the data (91%) and five distinct groups were observed. Overall, the results of this study can be beneficial for the design of equipment for harvesting, transportation, separating, packaging, and processing of apricot fruit. [ABSTRACT FROM AUTHOR]

The geomorphic characteristics of the watersheds are interrelated and the temporal and spatial scale in the form of season and sub-basins affect the concentration of suspended sediment. One of the objectives of this study was to investigate the relationship between suspended sediment concentration and watershed characteristics of Kan River using principal components regression and to recognize the effect of seasons and sub-basins on sediment concentration. The concentration of suspended sediment during four rainfall-runoff events in three seasons and in sub-basins was measured and calculated. The sixteen physiographic and land use characteristics were determined in the sub-basins and the main factors were identified and the scores of each factor for each feature were calculated using principal component analysis (PCA). The results of variance analysis showed that the concentration of suspended sediment was significant in terms of time scale and spring had the highest rate of sedimentation. Redundancy analysis and canonical analysis on the properties that participate in the first factor (PC1) showed the characteristics of the percentage of erodible formation, relatively erodible formation, and percentage of free construction activity, respectively. Road (slope leveling) and stream length are the most essential attributes of sub-basins in the production and concentration of suspended sediment in the study area. [ABSTRACT FROM AUTHOR]

One of the goals of natural resource management is to preserve biodiversity in natural ecosystems. In this research, the effect of topographical factors on species diversity in the elevation gradient of Grain mountains rangeland in Delfan County in 2022 was investigated. In this elevation gradient, five habitats were selected. Vegetation typing was done by the physiognomic method and in the Key area of each plant type, vegetation sampling was done by a random-systematic method. The sampling plot area was determined by the minimum area method (one to four square meters) and the number of plots was determined by statistical method for each habitat, 30 plots. Three transects with a length of 100 m were deployed in each habitat and 10 plots were sampled along each transect (30 plots per habitat). Species were collected from the surface of the plots, identified and their vegetative form was determined. The Biodiversity of plant species was calculated using dominance, Shannon-Wiener and Simpson diversity indices, Margalf and Mannhing richness index and homogeneity index Hill using PAST software. A One-way analysis of variance was used to compare the differences between sites and the Duncan test was used to compare the means. In order to determine the most important factors affecting species diversity changes, principal component analysis was used. The results showed that changes in height, slope and direction had a significant effect on the indices of diversity, richness, homogeneity and dominance at the level of all plants. At the total level of plants, the highest values of richness and diversity indices were observed at an altitude of more than 2600 meters and dominance at an altitude of 1850 meters. In low slope (0-15%) the dominance index had the highest value and the indices of diversity, richness and uniformity in slopes higher than 30% had higher values. Most indices in northern, northwestern and western geographical directions had higher values than in other directions and the difference was significant (P <0.01). The results of the principal component analysis showed that high altitude and slope and north, west and northwest directions have the most impact on species diversity in the study area. In general, it can be concluded that due to the number of livestock exceeding the grazing capacity and human activities in the lower elevations of the studied area, species diversity and richness have decreased. [ABSTRACT FROM AUTHOR]

Introduction Tomato is a product with a wide range of genotypes with different yields and selection based on this trait and its components can accelerate the breeding programs of this plant. The most important goals of tomato breeders have been to increase yield, disease resistance, early maturity, and improve the quality characteristics of the fruit. Therefore, awareness of genetic diversity in the population is an important step in plant breeding, and to achieve this goal, the studied genotypes must first be identified in terms of genetic potential and favorable agronomic traits. The usual approach for describing and evaluating populations requires cultivating sample populations and evaluating their morphological and agronomic characteristics. In this regard, multivariate statistical methods play an important role in studying genetic diversity and selecting appropriate parents. Unfortunately, the tomato cultivars used in Iran are often not at the favorable level in terms of important traits such as the number of days to fruit ripening, fruit weight, fruit yield, fruit length, and width, and few studies have been done on these traits. Therefore, this study was conducted to investigate the morphological diversity, evaluate the yield and its components among some imported tomato lines using analysis of variance, cluster analysis, and principal component analysis. Materials and Methods This study was performed in Sari University of Agricultural Sciences and Natural Resources, Mazandaran, Iran in 2020. The plant material included 24 tomato lines imported from the Canadian Plant Gene Bank and one check variety. The experimental design used for morphological analysis was a randomized complete block design with three replications. Evaluated characteristics were included of the number of days to first flowering, number of days from germination to first fruit coloring (early ripening), plant height (cm), number of fruits per plant, average fruit weight per plant (g), plant yield (g), length and width of the fruit (cm). After measuring the characteristics at the farm and recording the data, analysis of variance was performed to examine the diversity between lines in terms of the studied variables, and Duncan test was used to compare the means and SAS software was used to test the correlation coefficients of the variables. Cluster analysis for grouping of tomato lines was performed based on the mean of the main data of standardized traits, which was determined by Euclidean distance to determine the distance between the lines, and the UPGMA method was used to merge the clusters. Principal component analysis was performed based on the mean of the main data of morphological traits. Results and Discussion The results of the analysis of variance showed that there was a significant difference between all lines in terms of the studied characters. Also, principal component analysis based on morphological traits showed that the first two main components accounted for 75% of the total phenotypic variation in the data and the number of days from germination to first fruit coloring (-0.606), the number of days to first flowering (-0.516), fruit weight per plant (0.492), fruit width (0.480), fruit length (0.472), plant height (-0.445), fruit yield per plant (0.395) and the number of fruits per plant (-0.367) had the highest contribution in yield changes. Therefore, these variables might be taken into consideration for effective selection of parents for hybridization programs for broadening the genetic base in the population as well as to develop elite lines or F1 hybrids. UPGMA cluster analysis also divided the studied lines into nine groups. Group IX lines were in good condition in terms of yield traits and components, group VIII lines in terms of maturity and flowering, and group IV lines in terms of fruit number per plant. And the lines in groups I and V were in moderate condition for all traits. According to these results, the cross of the lines in the more distant groups can produce hybrids with high diversity and maximum heterosis. Conclusion According to the main purpose of this study, which was to evaluate the yield and its components and according to the analysis performed, lines 8, 11, and 17 due to showing the least number of days to flowering and early, lines 10 and 14 due to having the highest yield, the highest fruit weight, and highest fruit length and width and lines 2, 9, 15, 21, and 24 due to having the highest number of fruits per plant and the favorable height are also recommended for use in tomato breeding programs.

This study was conducted to compare the morphological characteristics of wild and farmed common carp. In total 70 samples of common carp, including 25 samples of wild from Torkaman port and 45 samples of farmed common carp from silver carp center in Gilan province were collected. Morphometric results were standardized using Elliott formula, and then principal component analysis (PCA) and discriminant function analysis (DFA) were used. Independent t-test was used to evaluate the significance of traits between these two populations. The results of this study revealed that the two populations of wild and farmed common craps were completely separated from each other, using PCA and individuals were assigned to their true population with high accuracy (98%) based on DFA. Among the 33 truss distances that were analyzed, 16 distances showed a significant difference between two populations (p<0.05). The results showed that the studied populations can be distinguished by many morphological differences, especially by dorsal fin length, pectoral fin length, pelvic fin length, anal fin length, dorsal fin width, body width, tail stem width, distance between pectoral and pelvic fin, distance from mouth to dorsal fin and the distance from the mouth to the anal fin. Overall, the results showed that the population of wild carp was significantly different from the population of farmed common carp from the morphological point of view. [ABSTRACT FROM AUTHOR]

In this study, the principal component analysis method was used to evaluate the relationships between quantitative and qualitative parameters of muffin with reduced sugar. The principal component analysis (PCA) method is a useful tool for interpreting and finding relationships in a set of parameters with various dimensions and characteristics in each observation. This tool provides useful help in increasing the interpretability of data and multidimensional visualization of the relationship between them. In order to replace sugar, a formulation based on three levels of maltodextrin (0, 25 and 50%) and four levels of ghavoot (0, 3, 6 and 10%) was used in a completely random design. Based on the study of the principal component analysis plot, it was determined that the relationships between the studied parameters are influenced by changes in the sugar substitute formulation. Based on this, new relationships between the studied parameters on muffins are formed by changing the level and type of sugar substitute composition. The evaluation of the change in the relationship between the parameters under the influence of the replacement of maltodextrin and ghavoot in the muffin formulation with reduced sugar shows the changes made in the structural substrates and the influence of a set of parameters on each other under the applied treatment. The results of this research show the efficiency and importance of using data mining methods to create an understanding of the relationships between quantitative and qualitative parameters of baking products with changes in formulation. [ABSTRACT FROM AUTHOR]

Early diagnosis of plant diseases before the occurrence of symptoms can reduce the loss of the yield and increase the quality of agricultural crops. It also reduces the consumption of pesticides, environmental risks, and the cost of production. For this reason, the objectives of the present study were non-destructive diagnosis of early blight of tomato plant and discrimination of the most important agents of early blight (A. solani and A. alternate) in the primary stages of incidence of the disease before appearing visual symptoms using Vis-NIR spectroscopy (400-900 nm). The spectral data were acquired from the leaves of the plants infected with A. solani and A. alternate, 48 hours, 72 hours, 96 hours, and 120 hours after inoculation. To develop the recognition model based on the spectral data, principal components analysis (PCA) coupled with artificial neural network (ANN) was used. The results showed that the PCA-ANN model could diagnose the infected plants and pathogen species with accuracy of 93-100% for test set samples. In 96 hours after inoculation, in addition to the simpler model (8 PCs and 3 neurons in hidden layer), accuracy of 100% was obtained. At all times after inoculation, there was no error in diagnosis of the plants infected with A. solani that is more pathogenic and aggressive than other species, from healthy plants. Early blight in tomato plant and the type of pathogen before visual symptoms, without any plant sample preparation, could be diagnosed non-destructively (with accuracy of 93-100%) using Vis-NIR (400-900 nm) spectroscopy coupled with PCA-ANN. It was concluded that this technology could be used for rapid, low-cost, and early diagnosis of this disease in tomato plant instead of time-consuming, expensive, and destructive laboratory methods.

One of the effective factors regarding the impact of natural resource rents on financial development is the role of institutional quality. Existence of natural resources can increase corruption through rent-seeking behaviors if there is no strong institutional framework. Therefore, the role of the institutional quality factor is undeniable. In the present study, the role of institutional quality in the impact of natural resource rents on the financial development of Iran in the period 1984-2019 has been investigated. For this purpose, first to extract the indicators of institutional quality and financial development from the model of principal component analysis and then from the Markov switching model to investigate the effect of natural resource rents on financial development in the country in two cases with and without considering Institutional quality index has been used. Increasing the rent of natural resources has had a negative and significant impact on financial development in low regime of the financial development. Economic growth and trade openness have also had a positive and significant impact on all levels and regimes of financial development. Increasing the rent of natural resources in terms of improving the institutional quality index has had a positive and significant effect on financial development in a low regime. Increasing the inflation has had a negative and significant effect on financial development in all regimes of financial development. [ABSTRACT FROM AUTHOR]

Expansion of cities on the fringes has caused the loss of natural landscapes, agricultural lands and environmental problems. Restoring and improving these effects based on the principles of environmental design is a necessary matter. Considering the current state of development of Arak city on the eastern edge, it is very important to pay attention to this part due to the value of high-quality soil, the existence of rural areas, gardens and agricultural lands. In this paper, a part of the eastern fringe of Arak was studied by satellite data and remote sensing-based ecological Index (RSEI) that includes four sub-indices: built-up area, vegetation cover, land surface temperature and land surface moisture. Integrating them was done by principal component analysis. The results showed that the lower ecological quality in different areas was caused by the development of infrastructures, impervious urban surfaces, industrial lands and in general the spaces resulting from the pressure of human activities and the ecological quality was higher in gardens, active rural agricultural lands and scattered parks and green spaces. Then, the results were analyzed in the pressure-state-response framework, and a part of the land named "Qanat Naseri" was redesigned in order to maintain and expand the existing ecological values based on the results and analysis. [ABSTRACT FROM AUTHOR]

Kope cheese is one of the traditional Iranian cheeses. In this study, the effect of ripening time on its physicochemical properties was investigated during 187 days of ripening. The results showed that ripening index and pH increased significantly, while "salt in dry matter" decreased (p <0.05). The maximum delta tangent (tan δ) ranged from 0.35 to 0.4. The Differential Scanning Calorimetric (DSC) curves showed two exothermic peaks for cheese -extracted fat ripened on days 7, 37, 67, and 97; three exothermic peaks for the sample ripened on 127 days, while two exothermic and endothermic peaks were observed for the sample ripened on 187 days, in the cooling phase. The results of principal component analysis (PCA) showed that PC1 and PC2 divided cheeses into four different groups, and PC3 identified only one group, including cheese day 127, with a high correlation with "moisture in the non -fat dry matter ", "salt in dry matter," and "fat in dry matter". Also, they showed a significant correlation with tan δ (p<0.05). These chemicals had the most important impact on the physical properties of Kope cheese. [ABSTRACT FROM AUTHOR]

Pomegranate is one of the important and an oldest fruit that is grown in vast regions. In recent years pomegranate juice is became a popular beverage. This study was carried out to investigate the mineral elements and some biochemical properties of juice in eight local Iranian pomegranate cultivars. The results showed a significant difference in the studied traits in all cultivars. The potassium content in pomegranate juice was higher than other elements, followed by calcium, sodium, phosphorus, magnesium, iron, manganese, zinc and copper. Potassium, calcium and iron was found the highest in 'Golabi', meanwhile the highest amount of magnesium and sodium measured in 'Sorahi' cultivars. 'Aliakbari' had the highest amount of manganese and zinc and 'Lopsorkhi' and 'Mirzaei' had the highest value of phosphorus and copper, respectively. The lowest amount of potassium and iron was observed in 'Lopsorkhi' and 'Aliakbari' cultivars, respectively. For other elements, 'Gar' had the lowest concentration. In terms of biochemical properties such as total soluble solids (TSS), maturity index (MI) and acidity (pH) of juice, 'Golabi, Lopsorkhi and Sorahi' cultivars had the highest value. 'Sorahi' and 'Aliakbari' cultivars with the highest amount of titrable acid were sour and suitable for industries pomegranate production, which require sour taste. Other cultivars were introduced due to the proper amounts of mineral elements and sweet and sour taste for fresh consumption and pomegranate juice production industry. The two-dimensional graph, based on the principal components analysis, confirmed the results of grouping the cultivars based on the comparison of the mean. [ABSTRACT FROM AUTHOR]

Today, the increasing process of food waste and agricultural products is one of the serious challenges in the most countries, especially in developing countries, so one of the serious policies of governments in the food security is to reduce the waste and maintain the quality of agricultural products. So far, several methods have been used to measure the quality of agricultural products, only some of which are technically and industrially justified. Vis / NIR Spectroscopymethod is one of the methods that has been considered and used in evaluating the qualitative characteristics of agricultural products due to its high speed and accuracy. In this regard, in the present study, visible/near infrared Spectroscopywas used to measure the qualitative changes and classification of K-Lime samples of lemon during the storage period (10, 20 and 30 days). In order to analyze the qualitative characteristics and classify the data extracted from NIR, the pattern recognition methods including principal component analysis (PCA), linear Discriminant analysis (LDA) and support vector machine (SVM) were used. The results showed that Visible/Near Infrared (Vis/NIR) Spectroscopywas able to differentiate its lemon samples based on storage time. Although PCA, LDA and SVM methods were able to classify lemon samples with good accuracy according to qualitative characteristics, but LDA and SVM methods with 100% accuracy had better accuracy and fit. Also, according to the results, the quadratic function has been determined and introduced as the best function for constructing classification models by LDA and SVM methods. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine the most important environmental factors (topography, climate, and soil) affecting changes in production and canopy cover of plant variations and to prepare prediction maps, based on the most important factor, in semi-steppe rangelands of Hir-Baghrou, Ardabil province, Iran. First, by detecting the vegetation types and different classes of environmental factors, the production and canopy cover were estimated in 1-m2 plots at full flower stage of dominant species. Then, to determine the most important environmental factors, affecting the production and canopy cover changes, the principal component analysis (PCA) was used. For modeling, first, the correlation between the most effective environmental factors was obtained from the PCA. Then, the highly correlated factors were eliminated and the quadratic polynomial models were obtained. Finally, the obtained models were simulated in GIS. The results of the PCA showed that the first six components with 71.65% had the greatest effect on the production and canopy cover changes. Based on the root mean squared error (RMSE), simulating maps of production (RMSE=0.76) and canopy cover (RMSE=0.48) by effective factor (annual precipitation) showed the highest accuracy. The results of this study can be used to manage the rangelands of Ardabil province to create a balance between supply and demand of production and also to balance carbon. [ABSTRACT FROM AUTHOR]

In the present study, in the first step, the effect of Aloe vera gel (75% v/v) coating containing different concentrations of hemp seed oil (1-5% v/v) on some physicochemical properties of cherry tomatoes during storage at room temperature was investigated. The results revealed the ability of hemp seed oil to improve the physicochemical properties of cherry tomatoes during storage, although no significant difference was observed between 3 and 5% levels of hemp seed oil (p> 0.05). Slope change in the ripening index trend occurred for A. vera gel (75% v/v) coated sample on day 12 and for A. vera gel containing 3% hemp seed oil coated sample on day 16. Using an image processing system, the changes of the coated samples were evaluated based on the color statistical and color texture features extracted from the images and were graded through different procedures. The results showed that the principal component analysis (PCA) and artificial neural network (ANN) methods were able to divide the cherry tomatoes into intact and blemished grades which the ANN method was graded samples using color texture features with higher accuracy (97.41%). The adaptive neuro-fuzzy inference system (ANFIS) method had higher diagnostic power than the other two methods and was able to grade the samples into three grades including intact, grade 2 and unusable with accuracy of 98.96%. [ABSTRACT FROM AUTHOR]

Soil is one of the most important natural resources of countries in which erosion occurs. In this research, the effect of soil characteristics on the amount of erosion at the suborder level was studied. For this purpose, 77 soil samples (0-30 cm) were prepared and the parameters were determined in the laboratory. The semi-variograms of soil parameters and their spatial distribution maps were prepared with GS+ and GIS, respectively. The study area was divided into work units by combining land use and geology maps and water erosion was estimated at each unit by the EPM method. By drilling profiles in different parts of study area, soil suborders were determined by Soil Taxonomy and the average values of parameters in each suborder was estimated. The principle components analysis (PCA) was then used for data analysis. The results showed that three parameters of silt, organic carbon and electrical conductivity could account for 30.384% as the first main component; clay, sand and vegetation could explain 11.189% as the second main component; and slope and height covered 15.330% as the third main component; in total, 63.805% percent of erosion variation could be justified by three main components. The lowest and highest amounts of erosion (69.12 and 343.57 m3/km2, respectively) were estimated in Xeralfs and Fluvents suborders. The erosion class of suborders at the study area was determined to be “few” and “medium”.

Objective: The Financial Crisis of 2007–2009 has created a renewed interest in systemic risk. The systemic risk is the result of a systemic relationship among financial institutions (Banks, Brokers, and Insurers). Recognition of systemic relationships among financial sub-systems of each country is an indispensable necessity for the purpose of preventing systematic failure. Method:The present study seeks to assess the relationship among the financial sub-systems in Iran, including banks, investment, and insurance companies during 2011-2017, using the Principal Components Analysis method. Then, the causal relationship between them is explained, applying the nonlinear Granger method. Results:According to the results, banking and insurance sectors have the highest and lowest systemic risk, respectively. It is also found that the systemic relationship alters from one financial institution to another over time. The results of this study can be useful for both regulatory bodies in order to optimize the regulation of the financial system and, on the other hand, for investors to effectively manage the portfolio risk.

Abstract The Fagaceae family is comprised of 8 genera with over 1000 different species. Despite many advances in understanding phylogenetic relationships based on molecular data, the existence of hybrids and/or the presence of ambiguous sequences justify careful observation of morphological, anatomical, and ecological characters of the Fagaceae. Therefore, the present study was conducted with the aim of investigating the morphological and anatomical characteristics the leaf of existing taxa in different habitats in Iran to identify and establish their similarities and dissimilarities relationships between them. Thus, 52 quantitative and qualitative characters from the leaf were studied. Cluster Analysis and Principal Components Analysis (PCA) were done based on Euclidean distance and covariance characteristics, respectively. The results obtained from PCA were consistent with cluster analysis. The results showed that the presence or absence of grooves in the petiole, petiole length, leaf width, leaf outline, the presence of trichomes between the midrib and secondary veins behind the leaf, the presence of cilia on the leaf margins were important morphological traits in the Fagaceae family. Some leaf anatomical characters such as venation density, midrib thickness, the presence or absence of trichomes, different shapes and sizes of trichomes, trichomes density, thickness and variety of epicuticular waxes and their shapes, stomatal size and density would be taxonomically useful for species.

Introduction: Today, we observe a decline in groundwater quality due to the factors such as population growth, industrial expansion, and agricultural development and so on. Considering that human health is affected by the quality of groundwater, conservation of the quality of groundwater is very important in water resources management. Therefore, many quality indicators such as Water Quality Index (WQI) have been developed all around the world to determine the water quality of a region. The purpose of this study was to determine the parameters affecting on water quality in Zanjan Plain using entropy theory and main components analysis, determining susceptible points of contamination and finally, ranking the areas in terms of quality of drinking water with the combination of Topsis method and EWQI index. Material and methods: This study was conducted in Zanjan Plain with an average rainfall of 323 mm per year and a maximum temperature of 40 °C and a minimum temperature of -29 °C. The parameters that are studied in order to determine the groundwater quality of Zanjan Plain were sulfate, chloride, bicarbonate, acidity, total dissolved solids, sodium adsorption ratio, electrical conductivity, potassium, sodium, magnesium, calcium, and total hardness. Principal Component Analysis (PCA) was used to determine the main components of the water quality in the area. Then, using the EWQI index, the results of this method were explained. The water quality index is defined as a scoring method for investigating the combined effects of the independent parameters on the total water quality. In order to prevent the expert judgments, the weight of each parameter in calculating the water quality index was determined using the entropy method. Ultimately, the ranking of areas in terms of water quality was applied using the combination of the TOPSIS method and the EWQI. TOPSIS method as a multi-criteria decision-making method is a simple and efficient method for prioritization. Results and discussion: According to the statistical characteristics of the quality parameters, the electrical conductivity and total hardness were higher than the WHO standards, which can be attributed to the geological structure, the presence of calcareous layers, and many evaporate sediments in the plains. The results showed that chloride was the most effective parameter on the groundwater quality in Zanjan Plain. Investigating the groundwater quality changes in Zanjan Plain during 2003-2016 showed that the wells of Koushkan and the suburbs of Zanjan were determined as potentially contaminated points, and the degradation factors of the groundwater quality in these areas were determined chloride (Cl) and sodium adsorption ratio (SAR), respectively. According to the results of the analysis method of the principle components and the diagram of Scree Kettel, total hardness parameter (TH) and Cl were most effective on the water quality of Zanjan Plain, respectively. More than 80 percent of the groundwater quality changes in Zanjan Plain can be evaluated with three factors. The first factor was the most responsible with more than 57 percent of the change. Then the second factor with more than 12 percent of variation and the third factor with 9 percent of the changes were the most important factors affecting the quality of groundwater of Zanjan Plain. In order to prioritize the Zanjan Plain in terms of groundwater quality, the combination of TOPSIS method and EWQI index was used. According to the results of this method, Yengijeh station was selected as the best station with excellent quality and Koushkan station was selected as the worst station with undesirable quality. Conclusion: Chloride parameter with low entropy and high entropy weight was the most effective parameter in the plain. Also, Yengijeh and Koushkan stations were selected as the best and worst stations, respectively.

In this study, the relationship between the precipitation over the southern areas of Iran and zonal wind over the Middle East was investigated. The monthly zonal wind data at 200hPa over the Middle East was selected from reanalysis NCEP-NCAR. The principal components analysis was applied to extract the signal modes of the winter (JFM) wind variations. The first empirical orthogonal function was spatially plotted and those grid points with high loading, which had the important role in the first principal component, were determined. These grid points are located in 15 to 22.5 and 27.5 to 42.5. The average of zonal wind within this area was considered as a regional index and the relationship between this index and winter precipitation for 11 synoptic stations in the south of Iran for 1968-2010 was investigated. The results indicated that there is a positive significant correlation at 5% level between wind index and precipitation over the most stations. The constructed wind index has stronger relationship with precipitation over the study area in comparison with southern oscillation index and Persian Gulf sea surface temperature.