Showing 23 results for dehghani
S. Dehghanian, M. Ghorbani,
Volume 7, Issue 3 (fall 2003)
Abstract
In this study, efficiency of apple producers in Khorasan Province was determined by a cross sectional data of 212 apple producers.
Mean technical, allocative, and economic efficiencies were estimated to be around 31, 28, and 9 percent, respectively. A high potential was also detected for increasing these efficiencies. Apple producers’ age and education had positive effects and risk aversion had a negative effect on technical efficiency. Waste reduction, optimal use of inputs, introduction of technical-extension services, and apple insurance are suggested to increase efficiencies.
H. Hokmabadi, K. Arzani, Y. Dehghani-Shooraki, B. Panahi,
Volume 7, Issue 4 (winter 2004)
Abstract
To determine the effects of salinity and boron excess in irrigation water on relative growth rate (RGR), net assimilation rate on a leaf weight basis (NAR), and leaf weight ratio (LWR) of pistachio, three pistachio rootstocks (Badami -Zarand, Sarakhs and Ghazvini) were used. Rootstocks were grown in soil in eight-liter polyethylene pots. Sodium chloride treatments were 0, 75,150 and 225 mM NaCl and boron treatments were 0, 20 and 40mg liter-1. Treatments were applied to the one-year old pistachio rootstock seedlings in three-day intervals with irrigation water. Some plants were randomly selected and destructively harvested before (day 0) and after applying treatments (30 and 60 days after treatments started). Growth and physiological characters were then measured as follows: number of leaves, leaf area, plant height and root length, fresh and dry weights of stem, root and leaf, proline accumulation in the leaf, total chlorophyll, and leaf relative water content (RWC). Results indicated that relative growth rate decreased with time for all treatments and in all rootstocks. Salt treatment significantly reduced both RGR and NAR, whereas LWR showed no significant differences. In all rootstocks, NAR, but not LWR, was significantly correlated with RGR, indicating that NAR was an important factor underlying the salinity-induced differences in RGR among the pistachio rootstocks. Salinity did not affect leaf water potential (ψ), chlorophyll content, and Fv:Fm ratio but increased NaCl concentration and time correspondingly increased proline accumulation in leaves. In addition, Ghazvini rootstock accumulated more proline compared to other rootstocks and was more resistant to salinity treatments. Different boron treatments did not show any significant effect on growth rate nor on measured parameters after two months of exposure to treatments.
M.r. Dehghani, M.j. Zamiri, E. Rowghani, Z. Banihashemi,
Volume 8, Issue 3 (fall 2004)
Abstract
The aim of this research was to study the effect of treatment with oyster mushroom (Pleurotus sajor-caju) on digestibility of Glycyrrhiza glabra L. pulp. Pleurotus sajor-caju was inoculated on sterilized wheat grains. Two weeks after growth at 25 °C it was added to the sterilized Glycyrrhiza glabra L. pulp in nylon bags. After two weeks (at 25 °C), mycelia grew on the pulp and were used for treatment. Digestibility coefficients were measured in 12 Ghezel rams. Dry matter, crude protein (CP) and nitrogen free extract (NFE) increased, but ash content, cell wall (NDF) and lignin (ADL) decreased significantly in fungal-treated as compared with non-treated pulps. Crude fiber (CF) and ADF contents were not significantly affected by the treatment. There was a tendency for crude fat (EE ether extract) to decrease by fungal treatment (p=0.08). Mean dry matter intake and digestibility coefficient of dry matter were higher in sheep which were fed the fungal-treated pulp compared with the control group. Digestibility coefficients of CP, CF, organic matter (OM), EE, NFE, NDF, ADF and ADL were significantly greater in fungal-treated pulp than in control group. Treatment with P. sajor-caju increased the nutritive value and digestibility of Glycyrrhiza glabra L. pulp (P<0.05), but culture of this fungus was not possible on non-sterilized pulp, which hinders its field application.
M. N. Gholami-Rouchi, J. M. Sadeghi, A. Dehghani,
Volume 9, Issue 1 (spring 2005)
Abstract
This research was conducted to measure the total factor productivity (TFP) of the rural small industries in Isfahan province comprising six types of industries: food, textile, metal, non-metal mineral, chemical, and cellulose. Among the 166 rural small industries sponsored by Jihad-Agriculture Organization of Isfahan in 2001(1380), 60 plants were selected. Cross-section information collected from the 60 plants by a questionnaire in that year confirmed the body of data for this study. The distribution of the types of the 60 selected plants followed the distribution of the types in the plant population. The analytical part of this research consisted of two sections. In the first section, the TFP of the rural small industries was established by applying Cobb-Douglas production function in which the value of the plant production was the dependent variable and the investment costs, total hours of labor, costs of raw materials, and the costs of energy and water were the independent variables. Factors affecting TFP were analyzed in the second section. The estimated coefficients of the first section and the actual data of the variables, were used to calculate the TFP for each plant. Then, another regression model was worked out in which the calculated TFPs were the dependent variable. The independent variables included the mean of the number of the employees' children, the percentage of the production employees with at least primary school level of education, annual number of the off days, dummy variable for the members of the cooperative association, and a few other variables.
The results of the first section showed that the TFP of food industries was higher than that of other types of industries and there was no significant difference between the TFP of textile, metal, non metal mineral, chemical and cellulose industries. The results of the analysis for determining the factors affecting the TFP, showed that the existence of a research section in the plant, the insurance of the employees and the mean of the number of employees' children had a positive effect on the TFP. But, the level of the education of the production workers, the area of the plant buildings, and the number of the days off in plant had negative effects.
M. Shahmohamadi, H. Dehghani, A. Yousefi,
Volume 9, Issue 1 (spring 2005)
Abstract
To determine yield stability and to evaluate genotype interaction with environment interaction, 18 genotype of barley (Hordeum vulgare L.) and a control group were evaluated in a randomized complete block design with 4 replications in 3 successive years (1997-2000) at 10 research stations. Simple and combined analysis of variance revealed significant genetic differences between yield genotypes for grain yield. The results of combined analysis of variance indicated that genotypic and genotype were significant through interaction with environment. Therefore, different stability parameters including, environmental variance (S2i), environmental coefficient of variation (C.Vi), mean of variance of interaction (θi), interaction variance (θi), equivalence ( W2i), stability variance (σ2i), linear regression coefficient (bi, βi), mean of squares of deviation from regression (S2 di) and years within location MS for a genotype, averaging over all locations (MSy/l) were determined. Based on all the stability parameters, genotype 18 was known as the most stable one and genotypes 17 and 11 ranked lower. Genotype 5 with the highest yield was known to be the most adaptable one at fertile environments and is recommended for these locations. In addition, genotype 9 with good yield and low yield variance (1.58) and regression coefficient of less than 1 is suggested for unfertile locations.
R. Karimizadeh, H. Dehghani, Z. Dehghanpour,
Volume 10, Issue 3 (fall 2006)
Abstract
To facilitate the interpretation of data from a genotype by environment experiment (GE), a cluster method is proposed to group genotypics according to their response to the environments especially when the GE interaction is large. The interaction structure of two-way classification data often can be identified if the data stratified into homogeneous subsets. In this paper four GE interaction cluster methods are proposed for this purpose. The stability of the 10 maize hybrids including 9 hybrids that were the best hybrids in yield trials and KSC 301 (check hybrid) were evaluated for 2 years in 4 locations of Iran. The randomized complete block design with 4 replications was conducted for each environment with different layouts. Simple analysis of variance revealed significant genetic differences between hybrids for grain yield. The results of combined analysis of variance indicated that genotype × year, genotype × location, and genotype × year × location interaction effects were significant (P < 0.01). Results also showed that models 1 and 3 and models 2 and 4 had the same responses. Hybrids 8 (K1263/1 × KE8212/12) with high yield stability in both models 1 and 3 were in one group and other hybrids were in another group. In models 2 and 4 results led to 3 groups: Group1 included hybrids 3, 7 and 9 that were very stable and had high yield group 2 included hybrid 1 alone that had medium stability and yield and group 3 included other hybrids that had low stability and yield.
A. Dehghani, A. Fotovat, Gh. Haghnia, P. Keshavarz,
Volume 11, Issue 41 (fall 2007)
Abstract
E. Feyzian, M. Jalali Javaran, H. Dehghani, H. Zamyad,
Volume 11, Issue 41 (fall 2007)
Abstract
Germplasm collection is the base of plant breeding. Iran is one of the most important centers of genetic diversity due to different climates and the old civilization.In this study we decided to collect melon accessions. The north and center of Iran were selected for this purpose. Fifteen qualitative and six quantitative traits were measured on thirty eight accessions. The cluster analysis by the use of UPGMA method and Jaccard coefficient helped separate the horticultural groups of Cucumis melo L. (Cantaloupensis, Inodorus, Flexousous, Reticulatus). The relationship between 30 of these accessions was assessed using 10 RAPD primers. The polymorphism was determined to be19%. The cluster analysis could not separate the horticultural groups of Cucumis melo L., showing that these groups are closely related. However, VB84 primer separated the tow Snakemelon.
M. Dehghanian, M. Madandoost,
Volume 12, Issue 45 (fall 2008)
Abstract
In order to investigate the effect of zinc - chelate on drought tolerance of Azadi cross wheat, a randomized complete block design was conducted as split plot with three replicates in the Kherameh during 1383 - 1384. The main plot was four drought levels (control and drought stress in the stages of flowering, seed milk stage and two phases, together), and sub plot was zinc - chelate rates 0, 5, 10 & 15 kg per hectare. The results showed that zinc application under drought conditions increased spike per square meter significantly at the 5% level. Drought stress decreased 1000 - seed weight. Least of 1000 - grain weight was in two phases of flowering and seed milk stage together (29.78 g). The application of 15kg zinc -chelate fixed 1000 - seed weight. Treatments of drought stress decreased seed yield significantly (14.17% in the proportion of control), but zinc - chelate application increased wheat tolerance to seed yield decrease. Zinc - chelate application prevented from seed number decrease per wheat spike under drought conditions that was caused to tolerance of seed yield and harvest index decrease. The application of 15 kg zinc - chelate increased harvest index in comparison of control amount of 22%.
Gh Dehghani, F Malek Shhi, B Alizadeh,
Volume 13, Issue 48 (7-2009)
Abstract
Canola (Brassica napus L.) as one of the oilseed crops has recently received lots of attention due to its suitable oil quality and high oil percentage. To evaluate the effect of water deficit stress on canola genotypes with regard to yield, drought tolerance quantitative indices and identify drought tolerant genotypes, an experiment was conducted in research farm of seed and plant improvement Institute (Karaj) using completely randomized block design with four replications, and 25 genotypes under two stress and non stress conditions. Genotypes were evaluated regarding drought tolerance. Drought tolerance quantitative indices include MP, GMP, STI, SSI and TOL. Result of variance analysis showed significant differences among genotypes as regards all indices and seed yield of genotypes in both conditions at 1% probability level. MP, GMP and STI indices were selected as the best indices for selection of tolerant genotypes in regard to analysis of correlation between seed yield in two stress and non stress conditions and drought tolerance indices. Results indicated that Genotype Vectra was the best genotype, because of its proper mean yield in both stress and non stress conditions. Multivariate biplot figure display showed that MP, GMP and STI indices had high correlation coefficient with each other, and tolerant genotypes were located near tolerance indices. Also results of three dimensional scatter plot and cluster analysis indicated that genotypes Modena, Jura, Eshydromel, Vectra, Dante, Zarfam, Esbetty and Olano were tolerant to drought stress, and genotypes Olpop, GKHelena, RG4504 and Olphi were sensitive genotypes.
Sh. Ghorbani Dashtaki, S. Dehghani Baniani, H. Khodaverdiloo, J. Mohammadi, B. Khalilmoghaddam,
Volume 16, Issue 60 (Summer 2012)
Abstract
Saturated hydraulic conductivity (Kfs) and macroscopic capillary length of soil pores are important hydraulic properties for water flow and solute transport modeling. Measuring these parameters is tedious, time consuming and expensive. One way is using indirect methods such as Pedotransfer functions (PTFs). The objective of this research was to develop some PTFs for estimating saturated hydraulic conductivity and inverse of macroscopic capillary length parameters (*). Therefore, the coefficients, Kfs and * from 60 points of Azadegan plain in Shahrekord were measured using single ring and multiple constant head method. Also, some of the readily available soil parameters from the two first pedogenic layers of the soils were obtained. Then, the desired PTFs were developed using stepwise multiple linear regression. The accuracy and reliability of the derived PTFs were evaluated using root mean square error (RMSE), mean error (ME), relative error (RE) and Pearson correlation coefficient (r). The highest correlation coefficients of 0.92 and 0.72 were found between Kfs-bulk density and *-bulk density, respectively. There was no significant correlation between soil particle size distribution and Kfs and *. This can be related to the fact that most of the soil samples were similar in texture and macro pores. The most efficient PTFs in predicting Kfs and * could explain 85 and 66 percent of the variability of these parameters, respectively. All the derived PTFs underestimated the Kfs and * parameters.
M. Abdi Dehkordi, A. A. Dehghani, M. Meftah, M. Kahe, M. Hesam, N. Dehghani,
Volume 18, Issue 68 (summer 2014)
Abstract
In many water resource projects such as dams, flood control, navigability, river aesthetics, environmental issues and the estimation of suspended load have great importance. The complexity of sediment behavior and mathematical and physical model inability in simulation of sedimentation processes have led to the development of new technologies such as fuzzy logic which has the ability to identify nonlinear relationship between input and output variables. In this study, the application of fuzzy clustering algorithm in estimating the annual amount of sediment was studied. So, the corresponding data of flow and sediment discharge of Valykben station in kasilian basin during 1349-1350 till
1353-1354 period was daily determined. The data was divided in two groups i. e. 75% as training data and 25% for test data. Then, the efficiency of model was obtained by using statistical parameters such as correlation coefficient, nash-satklyf coefficient, mean square error root and variance ratio. The result showed that the classification of data on the annual time scale and use of fuzzy clustering algorithm can estimate 0.49 values of the measured annually suspended sediment transport. Furthermore, on the same scale of classification, i.e. annual scale, this value was obtained 0.19. Thus, using fuzzy clustering algorithm can lead to higher accuracy and reliability than rating curve method, which is suggested for estimating suspended sediment transport.
N. Dehghani, M. Vafakhah,
Volume 18, Issue 69 (fall 2014)
Abstract
Sediment is as one of problems related to water resources utilization. Numerous formulas have been developed for bed load estimation in rivers. In this study, eleven common formulas including hydrologic and hydraulic methods such as Einstein Tofalti Meyer, Peter and Muller Van Rayne Modified Van Rayne Yalin Bagnold Fraylink Habibi and Sivakumar and Samaga were used for selection of the most suitable bed load estimator formula in Kharajgil hygrometry station on Navrud river. The results showed that Habibi and Sivkumar formula is the most suitable with the mean computed to observed data=1.35, standard deviation computed to observed=1.96, RMSE=1.63 and ill sorted ratio(computed transportation ratio to observed)=33.82% within the range of 0.5 to 2.
B. Khalili Moghadam, M. Afyuni, A. Jalalian, K. C. Abbaspour, A. A. Dehghani,
Volume 19, Issue 71 (spring 2015)
Abstract
With the advent of advanced geographical informational systems (GIS) and remote sensing technologies in recent years, topographic (elevation, slope, and aspect) and vegetation attributes are routinely available from digital elevation models (DEMs) and normalized difference vegetation index (NDVI) at different spatial (watershed, regional) scales. This study explores the use of topographic and vegetation attributes in addition to soil attributes to develop pedotransfer functions (PTFs) for estimating soil saturated hydraulic conductivity in the rangeland of central Zagros. We investigated the use of artificial neural networks (ANNs) in estimating soil saturated hydraulic conductivity from measured particle size distribution, bulk density, topographic attributes, normalized difference vegetation index (NDVI), soil organic carbon (SOC), and CaCo3 in topsoil and subsoil horizon. Three neural networks structures were used and compared with conventional multiple linear regression analysis. The performances of the models were evaluated using spearman’s correlation coefficient (r) based on the observed and the estimated values and normalized mean square error (NMSE). Topographic and vegetation attributes were found to be the most sensitive variables to estimate soil saturated hydraulic conductivity in the rangeland of central Zagros. Improvements were achieved with neural network (r=0.87) models compared with the conventional multiple linear regression (MLR) model (r=0.69).
N. Dehghani , M. Vafakhah, A. R. Bahremand,
Volume 19, Issue 73 (fall 2015)
Abstract
Rainfall-runoff modeling and prediction of river discharge is one important parameter in flood control and management, hydraulic structure design, and drought management. The goal of this study is simulating the daily discharge in Kasilian watershed by using WetSpa model and adaptive neuro-fuzzy inference system (ANFIS). The WetSpa model is a distributed hydrological and physically based model, which is able to predict flood on the watershed scale with various time intervals. The ANFIS is a black box model which has attracted the attention of many researchers. The digital maps of topography, land use, and soil type are 3 base maps used in the model for the prediction of daily discharge while intelligent models use available hydrometric and meteorological stations' data. The results of WetSpa model showed that this model can simulate the river base flow with Nash- Sutcliff criteria of 64 percent in the validation period, but shows less accuracy with flooding discharges. The reason for this result can be the small and short Travel time noted. This model can simulate the water balance in Kasilian watershed as well. The sensitivity analysis showed that groundwater flow recession and rainfall degree-day parameters have the highest and lowest effect on the results, respectively. Also, ANFIS with the inputs of rainfall 1-day lag and evaporation 1-day lag, with Nash-Sutcliff criteria of 80, was superior to WetSpa model with Nash-Sutcliff criteria of 24 percent in the validation period.
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.
Z. Eshkou, A. Dehghani, A. Ahmadi,
Volume 23, Issue 3 (Fall 2019)
Abstract
Stilling basins have been used as an energy dissipater downstream of hydraulic structures. Dimensions of the stilling basins depends on hydraulic jump characteristics. In this research diverging hydraulic jump with an adverse slope using baffle blocks and an end sill have been studied experimentally and effect of diverging angle of the walls, adverse bed slope and baffle blocks on the hydraulic jump characteristics have been evaluated. Tests have been done for rectangular stilling basin with different bed slopes (0.025-0.05-0.075) and different diverging angle (3-5-9) degree and using baffle blocks. Discharge and Froude numbers considered to range from 39 to 81.7 lit/s and 4.44 to 8.56 respectively. Results have been indicated that the baffle blocks have been reduced sequent depth ratio and relative length of the jump 12% and 18% respectively (in comparison to diverging stilling basin with adverse slope without block). It was also found that baffle blocks and end sill could considerably improve the general condition and features of an expanding hydraulic jump with an adverse slope and could stabilize the position of this type and bi-stable situation of the flow.
A. M. Ghaeminia, M. A. Hakimzadeh, R. Taghizadeh-Mehrjardi, F. Dehghani,
Volume 23, Issue 4 (winter 2020)
Abstract
One of the reasons for soil salinization is the accumulation of salts in it by transmission through water and wind. In order to investigate the phenomenon of transfer of salts with dust in the arid regions of the north of Yazd- Ardakan plain, field samples were taken using 32 MDCO sediments traps with uniform dispersion in an area of 20,000 hectares at some stage in 4 seasons of 2017. After washing the sediment collector with a liter of distilled water in the field and transferring the samples to the laboratory, for the quantitative analysis of saline dust, similar to measuring the Water Electrical Conductivity (ECw), the Total Soluble Solids (TDS) were additionally measured through evaporation technique. The form and distribution of the dust particle size were additionally investigated using a Scanning Electron Microscope (SEM) tool. Within the qualitative examine of salts, effective cations and anions in salinity including Na+, K+, Ca++, Mg++, C1-, HCO-3 and SO-4 were measured The results confirmed that, in general, the fallout was 11.1 g.m-2 of soluble material with dust particles (13.28%) in the course of only 12 months. Particles with a diameter of 5 to 10 microns were the most frequent. Considering the high correlation between C1- and Na+ in the spring, autumn and winter, due to the high correlation between Ca++ and SO-4 in summer dust, sodium chloride (NaCl) and gypsum (CaSO4) 2H2O)), the most abundant composition of dust- containing salts could be expected in these seasons. By determining the percentage of solutes in the fallout dust, it was observed that the impact of the amount of the deposited salt from dust was slight and insignificant in the short time period; with the assumption of no change in the rate of subsidence, it was anticipated that it would explain the poor salinity in non- saline mass soils for up to 10 cm in 72 years. In general, the capability of airborne salt in increasing the soil salinity in the study area can be in long- term periods. Therefore, it is recommended to investigate other environmental effects of this phenomenon in order to identify its hazards.
J. Meshkavati Toroujeni, A.a. Dehghani, A. ٍemadi, M. Masoudian,
Volume 25, Issue 3 (Fall 2021)
Abstract
One of the crucial problems that exist in the irrigation networks is the fluctuation of the water surface flow in the main channel and changes in the flow rate of the intake structure. One of the effective methods to decrease these fluctuations is increasing the weir crest length at the given width of the channel with the use of the labyrinth weirs can be achieved for this purpose. The labyrinth weir is the same linear weir that is seen as broken in the plan view. In this study, a labyrinth weir with a length of 3.72 m, three different heights of 15, 17, and 20 cm, three different shapes of dentate (rectangular, triangular, and trapezoidal), and a linear weir were used in a recirculating flume with 15 m length and 1 m width. The result showed that for a given length and height of weir, with the increasing of the upstream water head to the weir height ratio (
), the discharge coefficient decreases. The results showed that by increasing weir height, the discharge coefficient decreases for a given length of the weir. Linear weir and labyrinth weir without dentate create more water depth at the upstream by 3.3 and 1.2 fold compared with dentate labyrinth weir.
K. Ghaderi, B. Motamedvaziri, M. Vafakhah, A.a. Dehghani,
Volume 25, Issue 4 (Winiter 2022)
Abstract
Proper flood discharge forecasting is significant for the design of hydraulic structures, reducing the risk of failure, and minimizing downstream environmental damage. The objective of this study was to investigate the application of machine learning methods in Regional Flood Frequency Analysis (RFFA). To achieve this goal, 18 physiographic, climatic, lithological, and land use parameters were considered for the upstream basins of the hydrometric stations located in Karkheh and Karun watersheds (46 stations with a statistical length of 21 years). The best Probability Distribution Function (pdf) was then determined using the Kolmogorov-Smirnov test at each station to estimate the flood discharge with a return period of 50-year using maximum likelihood methods and L-moments. Finally, RFFA was performed using a decision tree, Bayesian network, and artificial neural network. The results showed that the log Pearson type 3 distribution in the maximum likelihood method and the generalized normal distribution in the L moment method are the best possible regional pdfs. Based on the gamma test, the parameters of the perimeter, basin length, shape factor, and mainstream length were selected as the best input structure. The results of regional flood frequency analysis showed that the Bayesian model with the L moment method (R2 = 0.7) has the best estimate compared to other methods. Decision tree and artificial neural network were in the following ranks.
