Salinity of soil or irrigation water is one of the most important obstacle towards crop production and productivity, especially with the increasing scarcity of fresh water in Iraq and the Arab countries. The impact of salinity will be alleviated with the increasing temperature due to global warming. The objectives of this article was to shed some light on traits more related to salinity stress tolerance in oats, and to identify genetic variation of these traits. A split-plot arrangement experiment with RCBD was applied through 2011-2013 on the farm of Dept. of Field Crops/Coll. of Agric./Univ. of Baghdad. The oats cultivars; Hamel, Pimula and Genzania were set in sub-plots, whereas water quality was set in main-plots. Water quality had two treatments, fresh water (1.5 ds.m-1 ) and saline irrigation water (6.0 ds.m-1 ). The results revealed that Genzania cv. oat yielded the other two cultivars. This cultivar elapsed 121 d to flowering, 152 d to maturity, and gave 379 racemes.m-2 , 47 kernel. raceme-1 , 32.1% harvest index, 17740 kernel.m-2 and 5.3 t.ha-1 grain yield across both years. Salinity of irrigation water did not affect any of plant height, days to flowering and maturity, stems.m-2 , racemes.m-2 , dry matter yield, kernel filling period, kernel growth rate, or kernel weight. On contrary, water salinity reduced each of crop growth rate, fertility (kernel/raceme), kernel.m-2 , and grain yield. Each one ds.m-1 above 1.5 ds.m-1 reduced grain yield by 3.8%. Highest traits in genetic/environmental variance were kernel weight, and number of stems.m-2 . However, this ratio was similar in traits of harvest index, kernel filling period, and days to flowering and maturity. There was no absolute relationship between trait genetic variance and its response to salinity. Kernel weight and number of stems.m-2 were the best traits to select for salt tolerance in oats. It was recommended to study flowering syndrome including fertility under salinity stress. Crop growth rate should be determined for each of vegetative and reproductive phases of that crop.
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This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and
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Static reservoir modeling is the interacting and analysis of the geological data to visualize the reservoir framework by three-dimensional model and distribute the static reservoir properties. The Petrel E&P software used to incorporate the data. The interpreted log data and core report used in distribution of petrophysical properties of porosity, water saturation and permeability for Zubair reservoir in Luhais oil field.
The reservoir discretized to 274968 cells in increments of 300, 200 and 1 meter in the direction of X, Y, and Z respectively. The geostatistical approach used in the distribution of the properties of porosity and water saturation overall the reservoir units. The permeability has been calculated
... Show MoreSolid waste is considered to be one of the rescuers of pollution in case of neglecting conditions and procedures relating to specific processes of laws, systems, and contracts requirements in addition to recommendations of organizations concerned with environment issue. The environments auditing groups of intosai have taking into account the environments control by various conference and recommended that the Board of supreme audit have and environments controlling taking into consideration auditing procedures on waste management ,and also offered on evidences for experiences of members of countries in order to exchange their knowledge's and experiments .the definition of solid waste and their resources ,risks ,man
... Show MoreIn the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used
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