جستجوی مقالات مرتبط با کلیدواژه « تجزیه به مولفه های اصلی » در نشریات گروه « محیط زیست »

This research was occurred to investigate some morphometric characteristics of Clupeonella cultriventris in Amirabad port, Babolsar and Anzali port in the South Basin of the Caspian Sea during summer 2019. A total of 90 fish including 30 specimens from each station were caught and 23 morphometric Characteristics were studied. Mean difference coefficients of morphometric characteristics for common kilka in Amirabad port, Babolsar, and Anzali port were 9.34, 8.77 and 11.03, respectively. Morphometric data before analysis were standardized to reduce errors of allometric growth. Results of 23 morphometric characteristics in three stations indicated significant differences between stations (P≤0.05). Bandar Anzali station differs in 23 morphometric characteristics with Babolsar port and in 20 characteristics with Bandar Amirabad. Babolsar and Bandar Amirabad station differed only in 3 characteristics. The principal component analysis was performed on 7 factors which concluded 74.924% of the characteristics. Results of fish morphometric characteristics showed an overlapping between Babolsar station with two stations of Amirabad port and Bandar Anzali port, but stations of Bandar Amirabad and Bandar Anzali were not overlapped. In this study, geographical separation can be considered as the most influential factor in morphological differences between the fish of three studied areas.

Environmental factors such as humidity and temperature varying at different altitudes of the forest and affect on plant distribution, species types and leaf morphology. Altitude is one of the important factors affecting environmental factors. In this study for evaluate the morphological changes of the leaf along the elevational gradient, five oak populations were surveyed in different altitudes of zagros forest in kermanshah province. At each altitude, five trees were selected and from each tree, 20 leaves were collected. Then in each population, leaves were mixed and fourteen leaf traits were measured. Results of duncanʼs analysis showed that there was a significant difference among five populations in all studied leaf characteristics and traits sush as area, perimeter, length, width, Ave Radial, Radial var, CMRV, S Factor, Width in X and Height in Y, had the highest values in high altitudes. two parameters of leaf area and perimeter with the highest amount of cumulative variance (67%) had the most role in grouping. Based on cluster analysis Five oak populations were divided into three groups and Population 2 and 3, as well as population 1 and 4, showed the most similar in morphological traits. The population 5 showed less similarity with populations 1 to 4 which this issue might demonstrate genetic diversity in this population.

Chickpea contains a high level of protein and plays very important role in the food security cycle in the worldwide, especially in the developing countries such as Iran which is one of the most important Asian countries in terms of chickpea production. Indeed, Iranian chickpea is planted in 33 countries and its area of cultivation in Iran is approximately 650000 hectare (Ahmed Khan, 2009). Low grain yield is the most basic problem of chickpea in Iran and plant breeding is a economic and permanent solution for solving this problem. Genetic diversity, heritability and intensive selection are three effective factors for responding to selection of traits. As a consequence, multivariate statistical methods are conventional and suitable for identifying genetic diversity in plant breeding programmes; principal component analysis, factor analysis, cluster analysis and discriminate function are the most important multivariate methods generally used for different plants. Many researchers have used multivariate statistical methods in rice (Gholipour and Mohammad-Salehi, 2003), potato (Rabie et al., 2008), wheat (Zaki Zadeh et al., 2010), chickpea (Jeena and Arora, 2002), and Identifying the most effective genotypes and traits in chickpea and assessing the genotype diversity were the main objectives of the current research.
In order to assess genetic diversity and identify the most important and effective traits of grain yield in 19 chickpea genotypes, the current experiment was conducted based on a randomized complete block design with three replications under well water conditions. The experiment was carried out in the Bu-Ali Sina University research field growing season and laboratory of Payame Noor University. The traits of chlorophyll index, plant height, branch number per plant, pod number per plant, seed number per plant, seed number per pod, 100-kernel weight, economic yield per unit area, biological yield per unit area and harvest index were measured. After trait measurement, principal component analysis (PCA), factor analysis (FA), cluster analysis (CA) and discriminate function analysis (DFA) were carried out in order to reach the aims of the research.
The results showed that the maximum coefficient of variation belonged to the traits of pod number per plant and harvest index, while the trait of 100-kernel weight had the minimum coefficient of variation. The results of principal component analysis showed that the three first components explained 68.9 percent of the total variance of the traits. The first and second components were known as the “grain yield” and “harvest index” components, respectively. In addition, factor analysis identified the three factors of “grain yield, “harvest index” and “plant vigour”. Cluster analysis based on the WARD method grouped the genotypes into four clusters. Meanwhile, discriminate function analysis confirmed the cluster analysis groups. The results showed a high genetic diversity among the lines. Lines number 12 and 18 were recognized as generally the best and the worst genotypes. In addition, the traits of pod number per plant, 100-kernel weight and harvest index had maximum effect on grain yield, while the trait of branch number per plant had a negative effect on grain yield in the current research.
According to the results obtained in the research, multivariate statistical methods are suitable and efficient methods for data reduction and indirect selection of grain yield that could successfully separate the efficient genotypes and the traits. The main objective was to assess the genetic diversity of 19 chickpea lines for their application in the new plant breeding programmes. According to the total results, the traits of pod number per plant were recognized as the most suitable traits for indirect grain yield selection. Line number 12, as a suitable line, had a maximum amount of the traits of pod number per plant, 100-kernel weight and harvest, while line number 18 (an unsuitable line) included the maximum amount of the trait of branch number per plant.

Productivity as one of the most important concepts in recent decade applied to improving production. The most common definition of productivity is theratio of outputs to inputs. Although more precise definitions of productivity have been provided by different authors and organizations in different countries. Agricultural productivity is also measured as the ratio of agricultural outputs to agricultural inputs. Generally, the market value of the final output is a tool for measuring output. Different indices are measured in agricultural productivity including total factor productivity, land index, labor index, machinery index, production index, capital index, etc. In this study 9 productivity indices were measured and analyzed in the agronomy and horticultural sub-sector which is the biggest and the most important sub-sector in the agricultural sector. Data were collected from different Iranian official sources for 11 years from1992-2001. Also, the data collected were used to explore the trend of different productivity indices in the sub-sector during the studied years.Furthermore, the indices were analyzed and interpreted using advanced statistical methods (principal component analysis).