Showing 7 results for Behbahani
A. Rahimi Khoob, S.m.r Behbahani , M.h. Nazarifar,
Volume 11, Issue 42 (winter 2008)
Abstract
Air temperature prediction models using satellite data are based on two variables of land surface temperature and vegetation cover index. These variables are obtained by atmospheric corrections in the values for the above data. Water vapor, ozone, and atmospheric aerosol optical depth are required for the atmospheric correction of visible bands. However, no measurements are available for these parameters in most locations of Iran. Using the common methods, land surface temperature can be measured accurately at 2 ° C. Given these limitations, efforts are made in this study to evaluate the accuracy of predicting maximum air temperature when uncorrected atmospheric data from the NOAA Satellite are used by a neural network. For this purpose, various neural network models were constructed from different combinations of data from 4 bands of NOAA satellite and 3 different geographical variables as inputs to the model in order to select the best model. The results showed that the best neural network was the one consisting of 6 neurons as the input layer (including 4 bands of NOAA satellite, day of the year, and altitude) and 19 neurons in the hidden layer. In this structure, about 91.4% of the results were found to be accurate at 3 ° C and the statistical criteria of R2, RMSE, and MBE were found to be 0.62, 1.7 ° C, and -0.01 ° C, respectively.
A Rahimi Khob, M Behbahani, M Jamshidi,
Volume 13, Issue 50 (winter 2010)
Abstract
Daily solar radiation intercepted at the earth’s surface is an input required for water resources, environmental and agricultural studies. However, the measurement of this parameter can only be done in a few places. This has led researchers to develop a number of methods for estimating solar radiation based on frequently available meteorological records such as hours of sunshine or air temperature. In this study two empirical Angestrom and Hargreaves- Samani models, which are respectively based on air temperature and sunshine duration were calibrated and evaluated for estimating solar radiation in southeast of Tehran, Iran. Also, two neural networks models were presented using similar inputs and above-mentioned empirical models. The results showed that the both empirical and neural network models provided closer agreement with the measured values, but the models based on sunshine hours gave better estimates than the models based on air temperature. The neural network model based on sunshine hours with a R2 of 0.97 and a RMSE of 1.34 MJ m-2 d-1 provided the best results
A. Rahimikhoob, P. Saberi, S. M. Behbahani, M. H. Nazarifar,
Volume 15, Issue 56 (sumer 2011)
Abstract
In this study, the remote sensing statistical approach was used to determine the global solar radiation from NOAA-AVHRR satellite data in southeast of Tehran. This approach is based on the linear correlation between a satellite derived cloud index and the atmospheric transmission measured by the clearness index on the ground. A multiple linear regression model was also used to convert the five AVHRR data channels and extraterrestrial radiation to global solar radiation. The results of this study showed that multiple linear regression model estimated the solar radiation with an R2 of 0.93 and a root mean square error (RMSE) of 5.8 percent, which was better than the statistical approach.
S. Moradi Behbahani, M. Moradi, R. Basiri, J. Mirzaei,
Volume 20, Issue 78 (Winter 2017)
Abstract
Salt cedar is widely spread out in most part of the country but there is lack of information about its symbiosis with arbuscular mycorrhizal fungi. Then, the main objective of this study was to evaluate the symbiosis of AMF with salt cedar and its affectability by distance from river and soil physiochemical properties. For this purpose, riparian Maroon forest width was divided to three locations including riverside area, intermediate area and the area far from river with 200-hundred-meter interval. In each site 10 salt cedars were randomly selected and soil plus hair root samples were gathered from the salt cedar rhizosphere. Our result indicated that root colonization and spore density in the intermediate distance had the lowest and highest values, respectively. These values were significantly different compared to the other two sites. The average root colonization percent in the riverside area, intermediate area and the area far from river sites were 82.37, 73.77 and 80.17, respectively. While the average spore density in the riverside area, intermediate area and the area far from river were 189, 245.5 and 188.8 in five gram soils, respectively. Root colonization had significant positive correlation with soil potassium while spore density had significant correlation with studied soil physiochemical properties. Also, soil nitrogen, organic carbon, potassium and clay showed 52.6, 51.19, 50 and 23.4% decreasing trend from the riverside area to the area far from river. Regarding this research results, salt cedar showed high level of symbiosis with arbuscular mycorrhizal fungi but this symbiosis could be affected by distance from river in riparian forest.
N. Salamati, H. Dehghanisanij, L. Behbahani,
Volume 23, Issue 1 (Spring 2019)
Abstract
In order to investigate the effect of water quantity in subsurface drip irrigation on water use efficiency of palm yield and yield components, and determining suitable irrigation treatments for three different date cultivars, a split plot experiment design in a randomized complete block design with three replications were applied for three cropping years (2013-2016), at Behbahan Agricultural Research Station. The applied irrigation water in three levels based on 75, 100 and 125 percent of water requirement in the main plots and three cultivars of Kabkab, Khasi and Zahidi dates were compared in sub plots. The irrigation level of 75% with 0.646 kg of dates per 1 cubic meter of water in terms of water use efficiency as compared to the other two levels of irrigation showed a significant superiority. The Khasi cultivar with 83.9 pips and 29.2929 fruits in the cluster ranked first. The irrigation level of 125% with 11.1% were higher in fruit moisture, and 100% and 75% irrigation levels with 9.6% and 7.8% moisture content were the next. The irrigation level of 125% for Kabkab cultivar with a volume of 11.1 cubic centimeters were ranked first. Optimizing water use and reducing it to 10606 cubic meters per hectare in irrigation level of 75% water treatment will save water consumption. If the basis for comparing the amount of water used in 100% water treatment is considered, then the use of subtropical drip irrigation reduces water consumption by 2509.6 and 5019.2 cubic meters per hectare, respectively, compared to 100 and 125% water requirements.
N. Salamati, A. Danaie, L. Behbahani,
Volume 25, Issue 2 (Summer 2021)
Abstract
To investigate and evaluate the effects of different levels of drip irrigation on grain yield and yield components, oil yield, seed oil percentage, and seed water use efficiency, an experiment was performed at Behbahan Agricultural Research Station during two crop years 2018-19 and 2019-20. The experiment was conducted in split plots based on a randomized complete block design with 3 replications. The amount of water in tape drip irrigation was compared at four levels of 40, 60, 80, and 100% water requirement in main plots and two sesame cultivars Local of Behbahan and Shevin in subplots from the beginning of flowering. Comparison of mean interaction effects of irrigation levels and cultivars showed that the treatment of 100% water requirement in the Behbahan local cultivar with the yield of 1218.0 kg/ha was ranked first and foremost. Water consumption in the highest treatment (100% water requirement and Behbahan local cultivar) was calculated to be 5389.4 m3/ha. Treatments of 100% and 80% of water requirement in superior cultivar (local Behbahan) with water use efficiency of 0.226 and 0.210 kg/m3 had no significant difference, respectively, and were in the first place. Pearson correlation coefficient calculated for the measured traits showed that the highest correlation of water volume was calculated (r = 0.9271) with the weight of one thousand seeds. Significant correlations of water volume with grain yield and yield components indicated that sesame was susceptible to drought stress and attention to optimal water management in sesame cultivation. Therefore, decreasing the volume of water consumed and consequently drought stress in sesame reduced yield and yield components.
N. Salamati, H. Dehghanisanij, L. Behbahani,
Volume 26, Issue 2 (ُSummer 2022)
Abstract
Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.
