جستجوی مقالات مرتبط با کلیدواژه "multivariate statistics" در نشریات گروه "کشاورزی"

Cowpea is a multiple-purpose drought-tolerant leguminous pulse crop grown in several dry tropical areas. However, detailed genetic information is lacking in many Asian countries, limiting the success of breeding programs. In this research, in order to evaluate the drought tolerance of 30 cowpea genotypes, an experiment was conducted in the form of a completely randomized block design with three replications in two conditions without stress (60 ml evaporation from the evaporation pan) and drought stress (120 ml liter of evaporation from the evaporation pan) was done in field conditions. The genotypes were significantly different from each other in terms of agro-morphological traits. The cluster analysis grouped the genotypes into four clusters. In general, based on bi-plot analysis, cluster analysis and correlation, genotypes 4, 6, 14, 28 and 29 in normal conditions and in drought stress conditions genotypes 5, 6, 14, 28 and 29 have the highest yield. They had the seed. Due to the fact that genotypes 28, 29 and 14 have a lower yield under drought stress than normal, they were identified as tolerant genotypes, which had higher yields than the control cultivars. Which might represent promising cowpea genetic resources for improved drought tolerance breeding.

Lentil is a rich source of protein, fiber, minerals, antioxidants, folate, zinc, selenium, iron, and low amounts of fat and carbohydrates. Increasing water shortage and drought stress will be a major threat to global lentil production. The present study was conducted to determine the morphophysiological traits and grain of yield under normal and drought stress conditions, investigate tolerance indices and identify drought tolerance in some lentil genotypes.

In this experiment, twenty - four lentil genotypes were evaluated in the research farm of Shahrekord Faculty of Agriculture in two drought-stress environments and the normal conditions of the region in two separate randomized complete block designs with three replications experiments. In the 50% flowering stage, drought stress was done by completely stopping irrigation for the genotypes. Sampling was done at the end of the growing season. In this experiment, morphophysiological and yield traits were measured.

The results of composite data analysis showed that the effect of environment, genotype and the interaction effect of genotype × environment were significant on most traits. The share of these sources of variation in diversity of triats was different and environment placed on the most role in the diversity of seed yield (55.27%), genotype in the diversity of 100 seed weight (64.6%) and the number of single seed pods (53.9%). Seed yield in normal agricultural conditions has a positive correlation with most of the traits. In addition, under stress conditions, more traits had a significant correlation with grain yield. STI and GMP indices were highly correlated with yield in both environments and these indices can be used to select the superior genotype. Examining the main components of the indicators showed that the first component and two components justify 97.66% of the changes, the first component was introduced as a semi-tolerant component and the second component as a tolerant component. The results of the cluster analysis put the genotypes in three general groups. The results of cluster analysis based on STI and GMP indices put the genotypes in three separate groups.

One of the main goals of production programs in arid and semi-arid regions is the screening of germplasm in different stages of plant growth. The results of the present research showed that drought stress in the reproductive stage reduces the morphophysiological traits and yield of lentil genotypes. Based on the results of seed yield, Kimia genotype with the lowest yield loss is known as the tolerant variety and C113 variety with the highest yield loss is known as the sensitive variety. Based on the results of seed yield, Kimia genotype with the lowest yield loss is known as the tolerant variety and C113 variety with the highest yield loss is known as the sensitive variety.

In recent years, soil contamination with potentially toxic elements (PTEs) has become a major problem in most parts of the world. PTEs are naturally generated from the pedogenesis in the soil and are formed mainly by rock weathering. Nevertheless, the natural content of metals, i.e., Cr, Zn, Ni, Pb, Cd, used to be low in the soil, but due to anthropogenic activities such as industrial emissions, atmospheric transportation, sewage irrigation, and application of pesticides and fertilizers, there is an increase in the content of PTEs. PTEs in soil are one of the most important environmental pollutants due to their toxicity, durability, easy absorption by plants and long half-life. Therefore, the assessment of soil health is very important for the sustainable development of agriculture and the rehabilitation of soils contaminated with PTEs. The present study was conducted to quantify PTEs pollution for soil environmental assessment using a flexible approach based on multivariate analysis and using pollution indicators in a part of the central lands of Khuzestan province.
 
For this purpose, in February 2021, 200 surface soil samples (0-10 cm) were taken using stratified random sampling. The collected soil samples were cleaned by removing plant materials and other pebbles, and air dried, powdered, and sieved by using a 2 mm sieve size. The interest in soil's physical and chemical properties i.e., pH was determined with a digital pH meter. Soil textural particles were measured by the hydrometer method, soil organic carbon (SOC) content was estimated by following Walkley and Black method, bulk density (BD) was measured by the Clod method, and total metal content was determined using the aqua-regia solution digestion method and analyzed using Inductively Coupled Plasma-Optical Emission spectrometry (ICP-OEC). The level of Pb, Ni, Zn, Cr pollution was estimated based on environmental indicators including contamination factor (CF), enrichment factor (EF), geo-accumulation index (Igeo), pollution index of individual metals (PI), and modified pollution index of individual metals (MPI). Multivariate statistical methods including correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to find the source of metals in the soil. All statistical methods were performed using SPSS (26 version) software.
 
Measurement of soil pH showed that the soil of the studied area tends to alkalinity. Also, the soil texture in this area is loam. The results showed that the SOC in these soil samples is 0.71%, and the range of EC (between 0.18 and 60.5 dS/m) indicates the distribution of saline and non-saline soils in the studied area. The total average concentration of Zn, Ni, Cr, and Pb were 60.26, 50.96, 50.38, and 12.67 mg/kg, respectively. The order of average for heavy metals was Zn> Ni> Cr> Pb. The highest amount of standard deviation and concentration changes were observed in Zn and Pb elements. These two elements also showed a high degree of variation coefficient in the studied area, which can indicate the high impact of human activities on the content of these elements. The results obtained from the application of multivariate statistics showed that there is a positive correlation between the elements such as Zn, Ni, and Pb in the study area, indicating that these metals probably have the same source. Whereas the absence of correlation of Cr with these elements indicates a separate source for this element compared to Pb, Zn, and Ni. There was also a strong relationship among these elements based on the PCA and CA classification. Based on the multivariate statistical analysis the source of pollution for the metals studied was mainly from both anthropogenic and geogenic activities. The results showed that the soil samples taken from the study area are in the low pollution category based on the individual element indices of CF and Igeo, but in the moderate pollution class based on the EF index. In addition, the evaluation based on the cumulative and multi-element indices of PI and MPI showed that 100% of samples have high pollution.
 
The present study concludes that the average values of Zn, Ni, Cr, and Pb were found to be below the guidelines set by the IEPA (Iran Environmental Protection Agency) as well as the Earth's crust values. The results indicate existing relationships among the studied variables, revealing that the heavy metals Zn, Ni, and Zn share the same source in the study area. Additionally, it was observed that the source of Cr is primarily geogenic in nature. These findings highlight the significance of utilizing multivariate statistical methods and pollution indicators in tandem, as they prove to be valuable tools for evaluating and quantitatively determining the potential pollution risk.

To determine the ideal genotypes in terms of the quantity and quality of fruit, 32 genotypes of greengage were evaluated in a randomized complete block design with three replications at the research station of Horticultural Research Institute in Karaj during two cropping seasons 2018 and 2019. To evaluate the genotypes and to determine the ideal genotype, 26 traits related to fruit, fruiting and yield were used. Combined variance analysis of data showed that the genotype source of variation was significant for all studied traits at the level of 0.01 probability level. ASIIG index showed that the genotypes CodR, Cod100, Malayer, and Gojeh Siah are the best and most desirable genotypes with an index higher than 55%, respectively. Also, Cod98, Cod99, Gojeh Baghi Qasr Dasht, Gojeh Qomi, and Gojeh Holandi with ASIIG index higher than 49% were ranked next. The grouping of genotypes using ASIIG method diagrams, the genotypes CodR, Cod100, Cod98, Cod99, Gojeh Malayer, Gojeh Siah, and Gojeh Baghi Qasr Dasht were located in the ideal quartile. Using cluster analysis, the genotypes CodR, Cod100, black, and Malayer as well as completely ideal hypothetical genotype (+) were placed in a group at a distance line of 0.018. According to the results of this study, seven genotypes CodR, Cod100, Cod98, Cod99, Gojeh Malayer, Gojeh Siah, and Gojeh Baghi Qasr Dasht were selected as the ideal genotypes in terms of fruit quantity and quality. Finally, due to the high benefits of the ASIIG index, it was suggested that this index can be used in other horticultural products to determine the ideal genotype.

To assess salt tolerance of 20 wheat genotypes, a randomized complete block design (RCBD) experiment with four replications under salinity (10 ds/m) and non-stressed conditions in a field experiment was conducted. Analysis of variance showed the significant differences among genotypes for tolerance indices and grain yield under salinity and non-stressed conditions. The result of correlation between stress tolerance indices and yield means showed that Mean Productivity (MP), Geometric Mean Productivity (GMP), Stress Tolerance Index (STI) and Harmonic Mean (HM) were the most suitable indices for selection of productive genotypes. HM was selected as the best indices for salt tolerance due to its higher correlation with grain yield under salinity stress conditions. The result of factor analysis based on these indices explained 99.87% of data changes. Genotypes were categorized into four clusters by cluster analysis. Totally, based on Bi plot, cluster analyses and tolerant indices, 7 and 8 genotypes having the highest yield (4725 and 4716 kg/ha, respectively), were determined as tolerant genotypes under salinity stress conditions.

In the present study, 18 lines and cultivars of chickpea were evaluated in three cold dryland stations including Maragheh, Kurdestan and Shirvan for three years (2014-2016). Results showed that the environments, genotypes and genotype × environment interaction effects were significant. Interaction analysis using the AMMI model indicated that the two principal components (IPCAs) significantly accounted for 67.9% of the total variation. However, these two components accounted for about 65% of the changes in the GGE biplot method. Evaluation of genotype yield stability using AMMI statistics were very similar to AMMI2 biplot. This similarity was also partially observed between the AMMI and GGE biplot methods. In both models the environments were subdivided into groups with separate superior genotypes and the behavior of some sites in the selection of genotypes was similar across years, while in some other sites it was different. Therefore, it is concluded that the reproducibility pattern of superior genotypes in each site is challenging under dryland conditions. Control cultivars of Samin, Gazvin and Jam showed good grain yield and stability. Although, the ability to select high yielding and stable genotypes among the lines was poor compared to control cultivars. However, genotypes 1, 3, 6, 12 and 14, due to their high yield, can be used in specific adaptation and suitable genetic sources for introducing drought and cold tolerant cultivars in the studied fields.

Inter and intra-specific crossing is a useful technique to introduce characteristics from wild plants to commercial cultivars of asparagus. In this research, Inter and intraspecific crosses between Iranian wild asparagus and European commercial asparagus was carried out at university of Cordoba (Spain) during 2015-2018. Specific allele for each parental species and accessions was detected with help of molecular markers. The genetic nature of hybrid plants was then confirmed by detecting of parental specific alleles in progeny. Thereafter, some of the most important morphological properties were evaluated in parental and progeny plants populations. Successful interspecific hybridization was obtained between Asparagus breslerianus and A. officinalis. Specific allele (1086 bp in length) was detected by TC6 primer in A. persicus. Morphological analysis showed that the highest coefficient of variation (CV %) was related to number of spear, main stem diameter, length of primary and secondary branches and number of cladode. The number of spear, number of secondary branch and number of cladode were higher in hybrids obtained by crossing between A. persicus × A. officinalis than parental plants. Diameter and height of main stem, number of primary branch, diameter and length of primary and secondary branches, width and length of spear scale, leaf diameter and internode length of primary and secondary branches played an important role to create morphological variability in parental and hybrid asparagus populations.

Eggplant (Solanum melongena L.) is one of the most important crops in tropical and subtropical areas. Study of variation among existing varieties is essential for development of new varieties. This study was conducted to investigate the quantitative characteristics and trait correlations in 14 eggplant genotypes. The cultivars and genotypes were grown in a randomized complete block design with three replications at research farm of Sari Agricultural Sciences and Natural Resources University during 2018. Various traits including plant height, fruit weight, number of fruits per plant, day to 50 % flowering, number of branches per plant, fruit length, fruit diameter and fruit yield were measured. The results showed that there were significant differences among the genotypes for all measured traits at 1 % probability level. According to the results of mean comparisons AVF1 was identified as the best genotype with high fruit yield per plant. The study of trait correlations revealed that fruit yield had a positive and significant correlation with fruit weight, number of fruit per plant, number of branches per plant and fruit length. Using the stepwise regression analysis number of fruits per plant and fruit weight were selected as the significant variable in the model. The biplot analysis based on the first two components showed that there is a suitable genetic diversity among the studied genotypes, which can be used in eggplant breeding programs. Also, according to the direct relationship between the number of fruits per plant and the weight of fruit with fruit yield, these two characteristics can be used as a selection indicator to improve yield in eggplant.

The mixing of freshwater and salty water in saline playas, high dissolution of calcareous stones, agricultural activities, industrial effluents and municipal and rural waste landfills are the most important sources of groundwater threats that threat human health. In this study, 46 water samples were taken from Arak plain and their physical and chemical variables were determined. Multivariate statistical analysis including stage factor analysis on the physical, chemical and chemical variables of groundwater in Arak aquifer have an important role in distinguishing between different pollutants in the region. The stage factor analysis gave five factors in the hydrochemistry variables of Arak aquifer. In the first factor, the EC, TDS, Cl, SO4, Ca, Mg and Na variables have a natural origin, which is the mixing of saline water from Mighan playa and freshwater aquifer. In the second factor, HCO3 is a natural origin due to the dissolution of limestones in southern Arak and HNO3, originating from humans and as a result of the influence of urban absorption wells and agricultural activities. The origin of the elements in factor three and four, mainly Zn, Cu, Fe and Mn, is mainly due to industrial activities and landfill, and F, is also due to agricultural activities, i.e, the use of phosphate fertilizers. This study also showed that stage factor analysis is a suitable method for separating source of contaminants. Therefore, appropriate measures should be taken by organizations and companies to control human pollution from sources such as Arak municipal wastewater, agricultural and industrial wastewater.

In order to evaluate and select drought tolerance genotypes in common bean and identify the best indices for drought tolerance, an experiment was conducted at research field University of Tehran in Karaj in 2015-2016 growing season. In this study, 102 common bean genotype were evaluated in an augment design under normal irrigated and drought stress (non-irrigation from flowering stage until the end of growing season) condition. Average values of grain yield and drought tolerance indexes and simple correlation coefficients of indexes with irrigation and dry farm yield showed that indices including MP, GMP and STI were the most suitable criteria for screening bean’s genotypes. In 3-dimensional graphs, referring to MP, STI, and GMP indexes and grain yield under dry farming and irrigation condition, 100,63,47,88 and 76 genotypes were identified as genotypes with high production and tolerant to intensive drought in A group. Actually these genotypes yielded most under both irrigation and dry farming conditions. Cluster analysis based on investigating indices and yield under drought stress and non-stress conditions showed that genotypes was grouped in three clusters and most of drought tolerant genotypes with high yield were grouped in third cluster, while most of sensitive genotypes to drought stress were grouped in the second cluster.

In order to evaluate and select drought tolerance genotypes in common bean and identify the best indices for drought tolerance, an experiment was conducted at research field University of Tehran in Karaj in 2015-2016 growing season. In this study, 102 common bean genotype were evaluated in an augment design under normal irrigated and drought stress (non-irrigation from flowering stage until the end of growing season) condition. Average values of grain yield and drought tolerance indexes and simple correlation coefficients of indexes with irrigation and dry farm yield showed that indices including MP, GMP and STI were the most suitable criteria for screening bean’s genotypes. In 3-dimensional graphs, referring to MP, STI, and GMP indexes and grain yield under dry farming and irrigation condition, 100,63,47,88 and 76 genotypes were identified as genotypes with high production and tolerant to intensive drought in A group. Actually these genotypes yielded most under both irrigation and dry farming conditions.
Cluster analysis based on investigating indices and yield under drought stress and non-stress conditions showed that genotypes was grouped in three clusters and most of drought tolerant genotypes with high yield were grouped in third cluster, while most of sensitive genotypes to drought stress were grouped in the second cluster.

Multi-variate statistical methods such as principal component analysis (PCA) and regressions could be used to facilitate the interpretation of complex relationships. The objective of this study was to determine the most important soil fertility properties affecting rice yield in the paddy fields. For this purpose, soil samples were taken from the plow layers of 119 points with suitable distribution in the paddy fileds located in Shaft and Fouman cities of Guilan province. Then after, physical and chemical properties of the soil fertility were measured and analysed using descriptive statistics, principal component analysis and regression methods. Results showed that three PCs with eigen values greater than one named as “k and it’s preservation factors”, ”Total N and it’s provider factors” and ”P and Thickness of plow layer” are respectively explained more than 67.4% of the variability in the soil physical and chemical properties and 55% of the yield variability. In addition, the corresponded properties to the PCs explained 80% of the yield variability. Consequently, in order to increase the yield, management practices such as proper fertilizer applications of nitrogen, potassium and phosphorous and proper tillage for creating suitable plow layer are recommended.

In order to monitor the changing water table in the field, determination of the main sampling points is very important to reduce sites and save time and cost. Principal Component Analysis (PCA) is one of the data reduction techniques used to extract the important components that explain the variance of a system. In this paper, the PCA was used to identify the effective wells of Qheidar Aqufer, Zanjan, to determine the groundwater level and remove the less important ones. From the study region which an area of about 920 km2, 48 wells (sites) were investigated. Using PCA, the relative importance of each well was calculated between 0 (for completely ineffective well) to 1 (for the very effective wells). The study showed the elimination of wells whose relative importance was less than 0.5 (i.e. half the total number of wells), coefficient of variation of groundwater level relative to the use of all wells did not greatly increase, and the error to determine the level of groundwater was less than 13 percent.

Genetic diversity is necessary for breeding program and increasing genetic gain of selection in crop plants. With the onset of spring growth, Spring cold stress is a problem for wheat crops at heading and also may be damaged some other parts of this plant. The aim of this study is the investigation of genetic diversity duo to artificial cold stress on the physiological traits, chlorophyll a, chlorophyll b, total chlorophyll, carotenoid and cytoplasmic membrane stability at the reproductive stage. For this purpose an experiment with 20 cultivars of bread wheat and four levels of cold stress, (8 (control), +2, 0 and -2 Celsius) was performed in factorial arrangement in a completely randomized design. Results of variance analysis showed the effects of interaction between cultivars and cold stress levels is significant at the 5% level which showed the existence of genetic diversity between studied cultivars.. There were significant correlations between chlorophyll a, b, total and carotenoid. In order to determination of genetic relation between cultivars, cluster analysis using was performed Ward method and cultivars were divided into 5 groups at -2 °C and 4 groups at +8 °C. Discriminate function and principal component analysis confirmed the results of cluster analysis. The third group of -2 °C including of GHODS, TAJAN and PISHTAZ had the lower level of ion leakage and higher level of plant pigments.