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Articles by M. Ranjbar
Total Records ( 3 ) for M. Ranjbar
  A. Almodares , M.R. Hadi , M. Ranjbar and R. Taheri
  Due to the population increase, about 1.5 million tons of sugar is needed annually in Iran. Half of this amount is provided by sugar beet and sugarcane industries and the other half is imported. These two crops are facing many problems such as: high cost of planting and harvesting, long growing season and high water requirement. Whereas, sweet sorghum is well adapted to tropical and sub-tropical regions, highly biomass production, low water and fertilizers requirements and short growing season. So obtained sugar from this plant may replace imported sugar from aboard. This study was carried out, at Isfahan University Research Station, to evaluate the effect of three nitrogen treatments, three sweet sorghum cultivars and three harvesting stages on the stalk yield and sugar content. The results showed the effect of nitrogen treatments on stalk yield, brix value and sucrose content were not significant, but the effects of cultivars and harvesting stages on the above measurements were significant. Among sweet sorghum cultivars, cv Rio had the highest stalk yield, brix value and sucrose content. These measurements were not significant for cv Vespa and IS2325. The effect of harvesting stage was significant for the stalk yield, brix value and sucrose content. Harvested plant at physiological maturity had the highest stalk yield, brix value and sucrose content and lowest at flowering stage. Based on these results, the highest stalk yield, brix value and sucrose content were obtained by planting cv Rio and harvested at physiological maturity stage.
  M. Ranjbar and M. Saadatseresht
  Laser scanners directly measure 3D coordinates of huge amounts of points in a short time period, so that it has a well-known solution in 3D object modeling. The abundant data of laser scanner can be efficiently utilized to model the scene, however in many cases; the object has to be scanned from different viewpoints due to accuracy occlusion field of view and range limitations. Because each scan has its own local coordinate system, all the different point clouds must be transformed into a common coordinate system. This procedure is usually referred to ‘registration’. There are many methods for registration problem including Target based, Image based and surface based registration methods. Surface based registration techniques give the highest registration accuracy and automation. This dissertation addresses refinement issue of surface based registration by use of an accurate and fast ICP algorithm. In the ICP algorithm, every point in one surface should be matched to a point on the other surface so that the matched surfaces have minimum deflection error. In our research, we compared both distant and normal vector thersholding and proposed a combined method in 3D surface matching. Analysis and experimental results demonstrated the proposed combined method gives better registration accuracy than the other standard approaches. Also in the research, different factors in accuracy and efficiency of registration algorithm are tested such as mathematical criterion function, using respectively Singular Value Decomposition (SVD) or eigen system computation based on the standard (R, T) representation and the eigen system analysis of matrices derived from quaternion forms of the transform, simple/complex surface geometry, initial values, surface overlapping and data conditions (ideal or noisy). The examinations demonstrate that accuracy of registration is not significantly different for the both mathematical computation methods of SVD and quaternion. It also shows that efficiency of registeration diminish for tough breaking surfaces and by low approximation of initial values. Registration has higher accuracy for more overlapping surfaces and lower level of noise in data. Therefore determination of initial overlap area especially for noisy data is so important.
  M. Ranjbar , M.R. Naghavi , A. Zali and M.J. Aghaei
  Abstract: Principal component and cluster analyses were used to evaluate the pattern of morphological variation in 122 accessions of Aegilops crassa for 14 quantitative characters. With the principal component analysis, the first five principal components with eigenvalues more than 1 contributed 69.5% of the variability amongst accessions, whereas PC6 to PC14 were less than unity. Plant height, stem diameter, spike length and number of spikelets per spike were the most important characters in the first principal component. The germplasm was grouped into five clusters using cluster analysis. Although each cluster had some specific characteristics of its own, but clusters were not clearly separated when plotted by the first two principal components. Mahalanobis distances (D2) determined that plant height, stem diameter, spike length, number of spikelets per spike, node width, seed length, seed width and flowering date characters as the most important characters in differentiating the accessions. The morphological variation of Aegilops crassa accessions obtained in this study provides useful information for the future collection and makes these genetic resources more accessible to breeders.
 
 
 
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