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.
Most of the big companies and especially the intillictual ones become a ware of an important fact, and That is, The intillictual capital in new global economy, is a new source for Them & This Valuable source exceed in importance. The other company's sources.
The Traditional disclouser systemes are unable to supply the decisions makers with the Fundimental information require to handel the on going operations which are based on Knowledge and intangible source. But the measuring of this source and the disclose for it in the financial Statements will lead to gain features Statements which will benefit all the parties and lead to make the value of the company great.
And as a resul
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The current study has beenconduced to evaluate the effect of extracted crude terpens at the concentrations of 6,8% of seeds of Eucalyptuscamaldulensison the 4th larval instar oftheCallosobruchusmaculates and the percentage of the cowpea seed germination.The Results showed that the terpens extract of the concentration of 8% increases the mortality rate of the fourth larval instar and it reach to 63.3%, and then decrease of to 26.6,20% at concentration of 6%and forcontrol treatment respectively The percentage of adult emergence reduces to 0% at the concentration of 8% compared with control treatment in which it reach to 66.6%. The extraction atbothconcentrations 6,8% does not affect the germination rate
The research aims at introducing the principles of six sigma and if it had any effect of the dimensions of six sigma to improve the performance of the dentists and the availability of an appropriate environment in the center Specialist respondent to the application of six sigma principles and how to adopt Specialized Center under the dimensions of the six sigma and if there informed enough with the management methodology six sigma, and if you can adopt six sigma as one of the entrances to reduce medical errors. So Search creating six sigma five dimensions and are (the commitment and support of senior management, the focus on the patient, continuous improvement, training and civil, and infrastructure) as a variable int
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The MTS-88. c trainer is a training system targeting students in the microprocessors course. It has a built in single-line assembler allowing the users to enter programs in assembly. It has the problem that long programs cannot be traced and tested efficiently. A simple error may cause all the code to be erased and the system to stop responding. Also, this system lacks the ability to be connected to the PC. The aim of this work is to modify the system to make it possible to be connected to the PC through the parallel port. This gives the capability to download long programs to the system after being developed in the PC. The 8255 Programmable Peripheral Interface available in the teaching system is interfaced to the parallel port and used as
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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