Showing 7 results for Hoseini
M. Shabanian, H. Masomi, A. Hoseinipour, J. Heidarnejad, Z. Azami,
Volume 11, Issue 1 (spring 2007)
Abstract
Cucumber cultivars, grown in greenhouse in the Jiroft region, were surveyed for the relative incidence of Zucchini yellow mosaic virus (ZYMV), Watermelon mosaic virus-2 (WMV-2), Cucumber mosaic virus (CMV) and Tomato spotted wilt virus (TSWV) from 2001 to 2004. Samples from 1294 plants representing different cultivars were analysed by Enzyme-linked immunosorbent assay (ELISA) and Dot immunobinding assay (DIBA). The data showed that green-house cucumbers are infected by CMV, ZYMV, TSWV and WMV-2. However, ZYMV was the most prevalent virus. Mixed infection including double and triple infection was identified in some samples. Transmission of aphid-borne viruses (CMV, ZYMV and WMV-2) by Aphis gossypii, A. fabae, A. craccivora and Myzus persicae revealed that ZYMV is most efficiently vectored by these aphids and, A. craccivora transmitted these viruses with more than 60% efficiency. In addition, WMV-2 was not transmitted by A. gossypii. In RT-PCR, ZYMV infection was confirmed by amplifying a PCR product of the predicated size 458 bp, using total RNA extracted from infected plants. All ZYMV infected samples reacted with monoclonal antibodies (705-1, 705-2 and 705-4) in TAS-ELISA test. These results showed that ZYMV isolate collected from Jiroft belongs to group A, cluster 1 or 2. In electron microscopy study, normal length of ZYMV flexuous particles in partial purified preparation was calculated as 790 nm. The molecular weight of coat protein of ZYMV was estimated at 36 KDa., using SDS-PAGE and western blotting. This is the first report of these viruses in greenhouse grown cucumber in the Jiroft region.
M. Gholamhoseini, M. Aghaalikhani, M.j. Malakouti,
Volume 12, Issue 45 (fall 2008)
Abstract
In order to study the effect of various amounts of nitrogen (N) and Iranian natural zeolite on the quantitative and qualitative forage yield of winter canola (Brassica napus L.) in light soil, a field experiment was conducted on research farm of Tarbiat Modares University, Tehran, during 2006-2007. Treatments were arranged in the form of RCBD with 3 replications. The experimental treatments were based on factorial various levels of zeolite (0, 3, 6 and 9 t.ha-1) and nitrogen (90, 180 and 270 kg ha-1) in urea form. Seeds of canola (Brassica napus L. cv. Okapi) were sown on October 2, and fresh forage was harvested at the time of silique formation (170 DAP). Results showed that the effect of N and zeolite on forage quantitative attributes including biomass, leaf and stem dry weight and leaf area index were statistically significant. In addition, forage qualitative traits including crude protein percentage and calcium percentage in plant mass were significantly affected by N and zeolite. Increasing application of N fertilizer caused increase in N leaching, and with increasing zeolite application, N leaching reduced. The interaction of two factors for all parameters was not significant. The most increasing effects on forage yield and quality were gained using 270 kg N ha-1 in combination with 9 t. Zeolite ha-1. More detailed studies are strongly recommended to investigate the effects of integrated application of chemical fertilizer and natural zeolite.
R Rajabi-Kanafgourabi, R Ebadi, M Fazilati, S.z Mirhoseini,
Volume 13, Issue 47 (4-2009)
Abstract
The effect of mulberry leaves enrichment with riboflavin in 7, 37, 77 and 127ppm concentrations on larval growth and cocoon characteristics of Bombyx mori L., hybrid 103×104 was studied. Silkworm larvae were fed on fresh mulberry leaves of shin inche nevise enriched with riboflavin once a day. All biological and economical parameters were determined by using standard techniques in sericulture. The results showed that larval weight was greater in 77ppm among treatments on the 7th day of the fifth instar which had 47% increase compared to control. Maximum amount of female cocoon weight and female pupal weight were recorded 1.622g and 1.169g, respectively, in 127ppm while male cocoon weight and pupal weight were greater in 37ppm and recorded to be 1.169g and 0.895g, respectively. Maximum amount of cocoon shell weight and cocoon shell ratio were recorded in 77ppm for male (0.311g and 26.06%) and female (0.318g and 21.46%). Maximum weight of 50 eggs (0.027g) was recorded in 127ppm while high fertility and hatchability was recorded in 77ppm concentration. Effective rate of rearing was maximum in control treatment (72%) with no significant difference compared with other treatments. The overall results showed that riboflavin can be used at 77ppm concentration for the significant increase of cocoon weight, cocoon shell ratio and egg production of silkworm, Bombyx mori L.
H. Hajihoseini, M. Hajihoseini, S. Morid, M. Delavar,
Volume 19, Issue 72 (summer 2015)
Abstract
One of the major challenges in water resources management is the operation of trans boundary watershed. This has been experienced in case of Helmand River between Iran and Afghanistan since the last century. For such a situation, application of a conceptual rainfall-runoff models that can simulate management scenarios is a relevant tool. The SWAT model can be a relevant option in this regard. However, the required hydro-climatic data for them is a serious obstacle. Especially, this problem gets exacerbated in the case of Afghanistan with poor infrastructures. So, application of this type of model would be more problematic. This paper aims to investigate capabilities of SWAT for the simulation of rainfall-runoff processes in such a data-scarce region and the upper catchment of Helmand River is used as the case study. For this purpose, discharge data of Dehraut station from 1969 to 1979 along with some metrological data were prepared and used to calibrate and validate the simulations. The results were acceptable and the coefficients of determinations (R2) during calibration and validation periods were 0.76 and 0.70, respectively. Notably, with respect to snowy condition of the basin, the elevation band option of the snow module of model had a significant effect on the results, especially in the base flows. Moreover, two Landsat satellite images during February 1973 and 1977 when the basin was partly covered with snow was prepared and compared with the SWAT outputs. Similarly, the results showed good performance of the model such that R2 were 0.87 and 0.82, respectively.
N. Ganji Khorramdel, S. M. R. Hoseini,
Volume 23, Issue 2 (Summer 2019)
Abstract
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficiency with respect to the existing data. The daily data of two meteorological stations of Shahrekord and Farrokhshahr airport in the dry and cold zones of Shahrekord during the period 2013-2004 was used; these included the minimum and maximum temperature, the average nominal humidity, wind speed at 2 meters height and sunshine hours. %75 of the data were validated, and %25 of the data was used for testing the models. Designed network is a predictive neural network with an active sigmoid tangent function hidden in the layer. In the next step, different wavelets including Haar, db and Sym were applied on the data and the neural network-wavelet was designed. To evaluate the models, the method was used by the Penman-Montith Fao and for all four methods, RMSE, MAE and R statistical indices were calculated and ranked. The results showed that the wave-let- neural network with the db5 wavelet had a better performance than other wavelets, as well as the artificial neural network, multivariate regression and the Hargreaves method. The results of wavelet network modelling with the db5 wavelet in the Farrokhshahr station were calculated to be 0.2668, 0.2067 and 0.998, respectively; at the airport station, these were equal to 0.2138, 0.14 and 0.9989, respectively. The results, therefore, showed that the neural network-wavelet performance was more accurate than the other models studied in this study.
N. Ganji Khorramdel, M. Abdoos, S. M. Hoseini Mooghaari,
Volume 23, Issue 3 (Fall 2019)
Abstract
Due to water use increasing, attention to optimal water resources allocation is needed. In recent decades, the use of intelligent evolutionary methods for optimization of water allocation was focused more by researchers. The aim of this study is to development on water resources planning model that determined the proper cultivation, optimal exploitation of groundwater and surface water resources although water allocation among crops is a way to minimize the adverse effects of dehydration and increase its revenue. In this study, for maximizing profits, estimating crop water requirements at different periods to optimize the management of cropping patterns and irrigation management in cultivation in Varamin irrigation network using a new evolutionary algorithm was called the water cycle. Then for validation of this method is that a new approach and ensure the integrity of its performance Its results are compared with a genetic algorithm model and linear programming as our base (R2=0.9963). The results showed that the area cropping pattern was not optimal and the area under cultivation of crops such as wheat, barley, tomatoes, Bamjan, melon, alfalfa reaches zero and the new paradigm of the largest area under cultivation to industrial goods and then was assigned cucumbers. While our revenues have increased about 11 percent. In addition to amount of water in different months remain in the network that can be used for many that such as injection into underground aquifers or other crops based on the amount of water available.
H. Alizadeh, A. Hoseini, M. Soltani,
Volume 24, Issue 3 (Fall 2020)
Abstract
The construction of irrigation network and the water transfer from Karkheh Dam to Dashte-Abbas, due to neglecting the groundwater resources has increased groundwater level and waterlogging of the agricultural land in the recent years. The aim of this study was, therefore, to optimize the conjunctive use of surface and groundwater resources in Dashte-Abbas to minimize waterlogging problems and achieve the maximum net income. For this purpose, the behavior of groundwater was simulated using the system dynamics (SD) approach. The conjunctive use of surface and groundwater resources was then optimized using the Vensim multi-criteria optimization method with the objective function of maximizing the net income of the plain. The SD model calibration was done using climatic, hydrological, agricultural, and environmental data from the 2001-2009 time period; then it was validated based on the information from the 2009-2016 period. Evaluation of the developed SD model showed that the model had high accuracy in simulating key variables such as groundwater levels (ME=60cm, R2=97%, RMSE=47cm) and groundwater salinity (RMSE=100μS/cm, R2=74%, and ME=123μS/cm). Furthermore, the results of the optimization model showed that the optimum use of surface and groundwater resources for the agricultural demand was 65% and 35%, respectively. To sum up, it could be concluded that with the optimization of the conjunctive use of surface and groundwater resource, s about 10 MCM of water consumption could be annually saved to irrigate almost 800 ha of the new lands.
