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.
Imam al - Karji replies to some Islamic groups
In his book the jokes of the Koran
ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021
It can be said that the Security of water in Basra from the visual task vital strategic issues of concern to the attention of researchers in various attributions and those interested in water, environmental, economic, social, cultural and political affairs ... etc. This view of the great importance of the issue of water in the occupied Basra, which is characterized by parochialism and scarcity, When looking at the sources of our daily lives and in our reality today. We find that millions of people living on the two main exporters Tabaaan oil and water. And depleted oil wealth However Manfred him the most attention because we entered it surpasses all other sources of income, but is not it a littl
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Statistical methods of forecasting have applied with the intention of constructing a model to predict the number of the old aged people in retirement homes in Iraq. They were based on the monthly data of old aged people in Baghdad and the governorates except for the Kurdistan region from 2016 to 2019. Using BoxJenkins methodology, the stationarity of the series was examined. The appropriate model order was determined, the parameters were estimated, the significance was tested, adequacy of the model was checked, and then the best model of prediction was used. The best model for forecasting according to criteria of (Normalized BIC, MAPE, RMSE) is ARIMA (0, 1, 2)
Statistical methods of forecasting have applied with the intention of constructing a model to predict the number of the old aged people in retirement homes in Iraq. They were based on the monthly data of old aged people in Baghdad and the governorates except for the Kurdistan region from 2016 to 2019. Using Box-Jenkins methodology, the stationarity of the series was examined. The appropriate model order was determined, the parameters were estimated, the significance was tested, adequacy of the model was checked, and then the best model of prediction was used. The best model for forecasting according to criteria of (Normalized BIC, MAPE, RMSE) is ARIMA (0, 1, 2).
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