Showing 6 results for mousanejad
Volume 2, Issue 1 (Spring & Summer 2025 2025)
Abstract
The political and social unrest that began with protests in Tunisia and quickly spread across North Africa also brought about rapid changes in Libya’s political landscape. Although these protests resulted in the overthrow of Muammar Gaddafi’s regime in 2011, the chaos did not end there. Libya descended into a period of political instability and armed conflict. During this turbulent time, the Muslim Brotherhood emerged as one of the key political and social actors. In the post-Gaddafi era, the Brotherhood exploited the absence of a strong centralized authority and benefited from foreign support, particularly from Qatar and Turkey. They expanded their influence by establishing the Justice and Construction Party, which initially achieved success in early elections. However, competition with nationalist and secular forces curtailed its political gains. With Turkish military backing, the Muslim Brotherhood openly supported the Government of National Accord during the second wave of conflict in 2014. Conversely, the Libyan National Army (LNA), led by Khalifa Haftar and supported by regional states opposed to the Brotherhood—such as the UAE, Egypt, and Saudi Arabia—targeted the group through both political and military means, intensifying the conflict.
Volume 2, Issue 4 (12-2013)
Abstract
Rice blast, caused by Pyricularia grisea, is one of the most important diseases of this crop in Iran and all over the world. To evaluate the relationship between spore population (SP) and meteorological factors, SP was measured daily using spore trap during growing seasons of 2006-2008 in Rasht and Lahijan regions (Guilan province, Iran). Weather data including precipitation, daily maximum and minimum temperatures, daily maximum and minimum relative humidity and duration of sunny hours were obtained from weather stations which were five kilometers away from the fields. The relationship between spore population and metrological factors was evaluated by Neurosolution 5.0 software. Weather data and spore population were considered as input and output data, respectively. In this study, multilayer perceptron neural network, regression model and Log(x + 1) transformation were performed. To evaluate the model efficiency, correlation coefficient and mean square error were used. The results showed that the correlation coefficient (r) and mean square error (MSE) parameters were 0.55 and 0.03 in Rasht and 0.1 and 0.03 in Lahijan, respectively. The results also showed the potential of this model for modeling SP using meteorological factors; however more data is needed for validation of this model. There has been no previous report on modeling the relationship between SP and meteorological data using artificial neural network in Guilan province (Iran).
Volume 6, Issue 2 (6-2017)
Abstract
Stem rot with the causal agent Sclerotium rolfsii is a major disease of peanut in Guilan province, Iran. The aim of this investigation was to determine the inhibitory effect of native isolates of peanut root nodulating symbiotic bacteria on this fungus based on in vitro and in vivo studies. Several bacterial strains were isolated and purified from peanut roots collected from different fields. Eight of them were detected as the main symbiotic nodulating strains. These eight isolates were identified as Bradyrhizobium based on 16S rDNA gene analysis and different biochemical tests. The inhibitory effect of these strains on the radial growth of S. rolfsii was studied in vitro using sealed plate and dual culture methods. Strains significantly inhibited radial growth of the fungus on the PDA medium. Br9, Br18 and Br16 were recognized as strong inhibitors and Br14 as weak strain in dual culture method and used in greenhouse experiments. Ability of the selected strains in controlling the stem rot disease, reducing the disease parameters and enhancing the peanut growth parameters was investigated in greenhouse conditions. The strains significantly decreased the white rot index and increased peanut dry matter (P ≤ 0.01) in greenhouse.
Volume 9, Issue 4 (8-2020)
Abstract
Sheath blight disease of rice caused by Rhizoctonia solani AG-1 IA, has become one of the major diseases in some rice- growing areas in recent years. Primary inoculum density seems to be a major factor in disease outbreak. The aim of the current study was to determine the relationship between the primary inoculum density and type and the disease intensity, grain yield and yield loss. Field experiments were conducted in both years of 2017 and 2018 in Guilan province, Iran. Disease incidence and severity were significantly higher when the highest inoculum densities (mycelial and sclerotial) were tested. When sclerotia were applied as the primary inoculum, disease developed more quickly. Based on the results of the current study, in a temperate lowland rice system in Guilan province, sclerotia floating on the water surface after puddling can be the primary source of inoculum and play a major role in sheath blight epidemics whereas mycelia in plant debris probably lose their viability in winter. These results suggested that control of sheath blight disease in order to prevent sclerotia production and reduce the main disease inoculum can be a promising strategy for suppressing this disease in the rice fields of Guilan province.
Volume 11, Issue 1 (1-2022)
Abstract
Downy mildew is one of the most important diseases of cucurbits in the world and Iran. The development of the disease was investigated in a commercial variety (Sakata® F1 Hybrid Saso), three hybrids and eight pure lines of cucumber, four pure squash lines, and one commercial cultivar of watermelon (Sakata® F1 Charleston Gray 243) in two consecutive years (2017 and 2018 spring and summer) at the experimental field of the University of Guilan, Iran to identify the sources of resistance. Plants were regularly inspected until the downy mildew symptoms appeared. The disease was measured using standard scale and Image J software at five stages in the plant growing season. Comparison of disease progress curves, final severity of the disease, and area under the disease progress curve (AUDPC) showed that cucumber B10 and A12 pure lines were the most susceptible and resistant in both years, respectively. None of the squash lines were infected in the first year, but in the second year, two lines showed the disease symptoms, and the severity of the disease in these lines was close to each other. The commercial cultivar of watermelon was not infected in both years.
Volume 12, Issue 3 (Number 3 - 2010)
Abstract
Grain yield loss in rice (Oryza sativa L.) caused by blast disease, Magnaporthe grisea (Hebert) Barr, is a major concern of rice growers worldwide. Blast is considered as the most injurious disease of rice in Iran, resulting in severe loss especially to susceptible rice cultivars. In order to assess yield loss caused by blast pathogen and develop an appropriate model, different disease onsets and levels were simulated in the experimental field in a split-plot experimental design. Independent variables including early diseased leaf area (X1), final diseased leaf area (X2), early neck blast index (N1), final neck blast index (N2), area under leaf blast disease progress curve (AUDPC1) and area under neck blast disease progress curve (AUDPC2) were taken as predictors and regressed to the loss in yield. Statistics as coefficient of correlation (r), coefficient of determination (R2), adjusted coefficient of determination (aR2), standard error (SE), F and Durbin-Watson were considered in evaluating the resulting models. The most appropriate model was the one which predicts rice yield loss based on final diseased leaf area and final neck blast index.