Showing 7 results for Principal Components
R. Amiri, A. Rezai, M. Shahedi, S. Dokhani,
Volume 3, Issue 3 (10-1999)
Abstract
This study was conducted to evaluate the capability of reversed-phase high performance liquid chromatography (RP-HPLC) of wheat (Triticum aestivum L.) storage proteins, and their genetic variability in different winter and spring isolines, cultivars and landraces. Gliadin proteins were extracted from the flour of five randomly selected seeds of each genotype. In this method, Nucleosil C18 300 A column (250×4.6 mm ID), equipped with a guard column and acetonitrile containing TFA as mobile phase was used.
All selected conditions for RP-HPLC such as suitable velocity and resolution were sufficient to achieve the objectives of this study. Under these conditions, the number of gliadin components by RP-HPLC analysis was more than electrophoresis subunits. In addition, quantitative results of RP-HPLC facilitated the data analysis. Also gliadin analysis by RP-HPLC had a high potential in detecting rye (Secale cereale L.) genes, so that the presence of ω-secalins in the genome of Falat variety was easily detected. Therefore, it was concluded that RP-HPLC analysis of gliadin proteins is as efficient as electrophoresis, and could even replace it in some cases. The result of cluster analysis for gliadin polypeptides indicated the gradual increase of genetic variation from isolines to landraces. Generally speaking, among the landraces, Ali Abad, Aghda, Sefid Bafghi, Ghermez Bafghi, Shahdas and Sorkheh had greater genetic variations.
R. Amiri, A. Rezai,
Volume 5, Issue 2 (7-2001)
Abstract
In order to evaluate the relationship between SDS-sedimentation value and breadmaking quality of wheat (Triticum aestivum L.), glutenin subunits of different genotypes (foreign and Iranian cultivars) were analyzed by reverse-phase high performance liquid chromatography (RP-HPLC). SDS-sedimentation value was used as an indirect criterion for breadmaking quality.
Correlation coefficients revealed a closer relationship between low molecular weight (LMW) glutenin subunits and variation in SDS-sedimentation value. Principal component analysis confirmed the presence of association between some of the glutenin subunits and SDS-sedimentation value. Based on the stepwise regression analysis, two LMW and four high molecular weight (HMW) peaks (subunits) were selected which accounted for 70.2 and 18.7% of variability in SDS sedimentation values, respectively. On the basis of the results of the stepwise regression analysis, a discriminant function was developed. The great efficiency of discriminant function in correct classification of completely different genotypes (Iranian landraces and cultivars) showed that the observed relationship between glutenin subunits and SDS-sedimentation value has a genetic basis and the effects of LMW and HMW glutenin subunits on SDS-sedimentation value are additive. Therefore, it seems that this method based on more protein components (rather than only on HMW glutenin subunits) can be used to predict breadmaking quality of wheat against many genetic backgrounds.
S. A. Maybodi, A. R. Amini Hajiabadi, J. Khajeddin,
Volume 6, Issue 2 (7-2002)
Abstract
A number of halophytic species as Salicornia europea, Halocnemum strobilaceum, Aeluropus lagopoides, and Aeluropus littoralis were found to occupy a significant portion of the total vegetation of the surrounding area at the Zayande-Roud inlet to Gavkhoony wetland. However, their ecological demands and bioenvironmental factors by which vegetation community composition has been affected is not undestood. A compehensive knowledge of the establishment is essential for future improvements in using the above species on salanized regions. In this paper, using the ordination method. The establishment pattern of these four species in a range of varied habitats is evaluated based on the recongition of the relative significance of habitat soil chemical properties and vegetion crown cover to the establishment of the four species. For this purpose, 48 plants meansurements were taken along a transect, having more species variation in term of vegetation cover percentage. Furthermore, 48 soil samples were taken from the plot along the same transect in a one-year period in 1999. The soil samples were analysed for PH, EC, available Na, K, Ca and Mg as well as clay, and silt contents. The ground and field vegetation data were analysed using the Principlas Components Analysis (PCA), and Canonical Correspondence Analysis (CCA) to produce summary vectors (PCA axes) of both the soil chemistry and habitat vegetation structure datasets. The summary of ordination method quantified the degree to which soil variables and species cover were related to variability in ground vegetation composition. variation in community composition (type and percentage) was significantly related to gradient of the aforementioned soil factors. Generally, the vegatation community composition in this experiment could be considered as a key component to expand the growth and development patterns of these species to similar salinised regions.
S. M. J. Nazemosadat, B. Baigi, S. Amin,
Volume 7, Issue 1 (4-2003)
Abstract
The study of geographical extent of precipitation pattern is important because of its impact on agriculture, water resources, tourism, industry, dams, and irrigation. The principal component analysis (PCA), as an elegant mathematical tool, was applied for the regionalization of winter precipitation in central south Iran (Fars, Boushehr, and Kohgiloye and Boyerahmad Provinces). Averaging monthly rainfall data of Dey, Bahman and Esfand (20 December to 20 March) produced the time series of winter rainfall. In each individual station, correlation matrix of the normalized data was then performed for the computation of the standard PCA. Eigenvalues, eigenvectors, PC time series and the loading of the principal components were then computed. The Screet test technique was applied as a trial for addressing the problem of determining the number of PC modes that should be retained. Two of the first PCs, which account for 68.1% of total variance in the rainfall data, were kept and used for the regionalization of rainfall data. The rotation solution was then selected as a suitable tool for delineating the rainfall region associated with the retained PCs.
The results indicated that for the first PC, loading became high over most part of the study area. Therefore, the time series of PC1 that accounts for about 60.4% of the variance in raw data, could be used as the regional time series of winter rainfall over most parts of the provinces studied. The second PC revealed a high loading over a small area in northern part of the regions studied (Bavanat in Fars Province). Rainfall in this station showed poor correlation with the precipitation over the neighboring station in Fars Province. It seems that the rainfall in Bavanat is mostly influenced by the Mediterranean air masses entering the area through the northern and western districts. For the other parts of the regions studied, Sudan current which encroaches the country through southwestern borders (Persian Gulf regions) make up an essential portion of winter rainfall.
M. Yousofi Azar, A.m. Rezai,
Volume 11, Issue 42 (1-2008)
Abstract
This study was conducted at Research Farm of Isfahan University of Technology to evaluate drought tolerance potential of 23 F2:4 wheat lines derived from the cross of Virmarin (susceptible line) and Sardari (tolerant line). A randomized complete block design with three replications was used in each irrigation treatment (i.e. irrigation after 70±3 and 120±3 mm evaporation from class A pan for non-stress and stress conditions, respectively). Drought tolerance and susceptibility indices were calculated for yield, and principal components analysis was performed on the basis of indices. Rosielle and Hambline tolerance index and Fisher and Maurer stress susceptibility index had positive and significant correlation, but their correlations with drought yield and the first two principal components were negative. High value of these components indicates low sensitivity to drought. The first component had high and positive correlations with geometric mean productivity, stress tolerance index and harmonic mean. Lines number 4, 17, 11 and 14 with high yields in drought condition, showed high values for these indices. Line number 2 with high yield in non-stress condition and in spite of high sensitivity to stress, was a superior genotype based on these indices.
Mohammad Hossein Noori Gheidari,
Volume 17, Issue 64 (9-2013)
Abstract
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.
Sh. Ahmadi-Qolidaraq, A. Abbasi-Kalo, A. Esmali-0uri,
Volume 23, Issue 4 (12-2019)
Abstract
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”.
