Mashad Farahbakhsh; Mehdi Sarai tabrizi; Hossin Babazadeh
Abstract
It is very important to estimate the actual water requirement of the plant for irrigation planning and hence effective water management in the field. The purpose of this study was to evaluate the conventional methods of estimating crop water demands and the actual water requirement of basil plant under ...
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It is very important to estimate the actual water requirement of the plant for irrigation planning and hence effective water management in the field. The purpose of this study was to evaluate the conventional methods of estimating crop water demands and the actual water requirement of basil plant under field conditions. For this purpose, an experiment was carried out on three separate hectares, with three different methods of estimating basil water requirement, including the method of Standard Class A evaporation pan, the method of TethaProbe soil moisture set, and a proposed weighing micro-lysimeter method. Besides, the study compared four irrigation treatments including full irrigation (FI) and deficit irrigation at (DI 80%), (DI 60%), and (DI 40%) of water requirement for two consecutive years in 2017 and 2018. The results showed that the highest amount of basil evapotranspiration was measured at 11.2 mm/day, 53 days after planting. Also, basil crop coefficient values at the initial stages, development, middle, and end of growth were 0.63, 1.08, 1.12, and 0.97 respectively, and the highest basil coefficient in the 25th of July was equal to 1.26. The highest yield of fresh matter in the direct method of estimating water demand was obtained at 5998 and 5966 kg ha-1, respectively, in 2016 and 2017 in full irrigation. Also, the results of this study showed that the proposed lysimeter method improved the method of Class A pan and soil sampling by, respectively, 10% and 8% water consumption, and yields by 10% and 5%, respectively. Also, with this method, the maximum economic return was 4186 Rials per cubic meter of water.
khadije fattahi dolatabadi; hosin babazadeh; payam najafi; hossin sedghi
Abstract
To prevent water stress in plants and have sustainable water management in the field, fast and accurate determination of irrigation time is one of the most important issues. Measuring soil moisture and leaf surface temperature are two methods of determining time of irrigation. In this research, by combination ...
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To prevent water stress in plants and have sustainable water management in the field, fast and accurate determination of irrigation time is one of the most important issues. Measuring soil moisture and leaf surface temperature are two methods of determining time of irrigation. In this research, by combination of these two methods, a model for planning and management of forage maize irrigation (cultivar SC-701) is presented. The air relative humidity (RH) and temperature (Ta), leaf surface temperature (TL), and soil moisture content (SM) were measured in 2013 and, by using artificial neural network model and multiple stepwise method, a regression model was developed. Experiments were carried out in 2014 with five treatments including 100%, 85%, 75%, 65%, and 35% total available water (TAW), with four replications, Irrigation was carried out when soil moisture content reached the treatments moisture level. Measurements of the previous year were repeated and the model was calibrated. The results of the first year showed a correlation (R2=0.87) between the parameters RH, Ta, TL, Ta-TL as independent variable and SM as the dependent variable. Then, using three input parameters of air temperature, leaf surface temperature, and relative humidity, Determination Coefficient of soil moisture content model was calculated as R2= 0.92. In this model, soil moisture has an inverse relation with (Ta) and (TL-Ta) variables, but a direct relation with RH. Soil moisture content was compared using the model for the second year treatments and compared with the measured values. The difference in soil moisture content measured and estimated by the model at the peak solar radiation time (at noon) was less than ±10%. The model estimated 75% TAW treatment data well, with very small difference compared to the measured value.
hossin babazadeh; Ali Abdzad Gohari; Arash Khonok
Abstract
Proper and efficient use of water and fertilizers, in addition to increasing productivity, increase crop yield. In order to study the effects of drip irrigation management and nitrogen fertilizer levels on yield of peanut, an experimen was conducted in Astaneh Ashrafiyeh, Guilan province, in 2012 and ...
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Proper and efficient use of water and fertilizers, in addition to increasing productivity, increase crop yield. In order to study the effects of drip irrigation management and nitrogen fertilizer levels on yield of peanut, an experimen was conducted in Astaneh Ashrafiyeh, Guilan province, in 2012 and 2013 using split plot in a randomized complete block design with three replications. The main plot included water treatments consisting of no irrigation and application of 60%, 80%, and 100 percent water requirement. Sub plots included nitrogen fertilizer levels i.e. 0, 30, 60 and 90 kg.ha-1. The results showed that pod yield were similar in treatments of %80 and 100 percent crop water requirement corresponding to 2385 and 2452 kg.ha-1 in 2012. In 2013, the yields were, respectively, 2383 and 2448 kg.ha-1. The highest pod yield was obtained in 60 kg.N.ha-1 treatment in 2012 and 2013, amounting to, respectively, 2351 and 2667 kg.ha-1. Seed yields in 2012 and 2013 were obtained in 100 percent crop water requirement, with 1885 and 1877 kg.ha-1, respectively, which were significantly higher compared to the treatment without irrigation. In the fertilizer treatments, the average yield of 60 kg N.ha-1 in 2012 and 2013 was, respectively, 1829 and 2012 kg.ha-1. In water treatments, water productivity based on biomass yield varied between 1.03 and 1.68 kg.m-3 and, based on pod yield, it was observed between 0.37 and 0.63 kg.m-3, in 2012 and 2013. The water productivity values of seed yield in the 100% water requirement in the crop years 2012 and 2013 were 0.28 and 0.40 kg.m-3, respectively. Therefore, considering the results of yield and water productivity, management practice of 100% water requirement and 60 kg.N.ha-1 is the most appropriate method for peanut cultivation in the study area.
Hassan Ebrahimi rad; hossin babazadeh; ebrahim amiri; hossin sedghi
Abstract
It is necessary to optimize productivity and usage of available water resources due to shortage of these resources and low irrigation efficiency in rice fields. In order to study the effect of different irrigation managements and planting densities on rice, cv. Hashemi, an experiment was conducted in ...
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It is necessary to optimize productivity and usage of available water resources due to shortage of these resources and low irrigation efficiency in rice fields. In order to study the effect of different irrigation managements and planting densities on rice, cv. Hashemi, an experiment was conducted in a randomized complete block design (RCBD) with three replications at Koshal-Lahijan, in north of Iran, during cropping seasons of 2014 and 2015. There were 5 levels of irrigation treatments in this research including: I1 = Submerged irrigation, I2 = Saturation, I3 = Irrigation with 8 days interval before anthesis, I4 = Irrigation with 8 days interval after anthesis, I5= Irrigation with 8 days interval throughout the growing season). Also, there were 3 levels of planting density including, D1=15×15, D2=20×20, and D3=25×25 cm. Combined variance analysis showed that the effect of water stress and plant density on measured traits were significantly different (p<0.01). I1 had the highest yield in all treatments during the growth season, which was equal to 4151kg. Yields of I2, I3, I4, and I5 were equal to 4054, 3949, 3244, and 2787, respectively. Water productivity values of I3 and I5 were equal to 1.90 and 1.45 kg.m-3, which were the maximum and minimum (irrigation + rain) water productivity based on biomass. The results also showed that irrigation with 8 days interval before anthesis decreased water use by 16%, but it caused only 4% yield reduction. Analyzing different crop densities showed that yield components increased in high density (D1), while yield per unit area and water productivity decreased when plant densities decreased (D3). So, (D2) is the optimum spacing and is recommended.
y h; h b; b kh
Abstract
Various mathematical models are available for estimating the response of plants to combined drought and salinity stress and the share of each component in water uptake. The reduction functions are classified as additive, multiplicative, and conceptual models. In this study, 5 different macroscopic reduction ...
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Various mathematical models are available for estimating the response of plants to combined drought and salinity stress and the share of each component in water uptake. The reduction functions are classified as additive, multiplicative, and conceptual models. In this study, 5 different macroscopic reduction functions, namely, Van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, and Homaee, were evaluated in greenhouse conditions using pepper data. This experiment was performed based on a completely randomized design with 3 replicates and 3 levels of salinity (2.5, 4.5, and 6.5 dS/m). Drought levels were carried out as matric potential during the experiment at 3 levels (50%, 60%, and 70% of field capacity). The results of this study indicated that the crop response to drought and salinity stress was additive at low salinity level (2.5 dS/m) and multiplicative at 4.5 and 6.5 dS/m salinity levels. Also, reduction function of Van Genuchten (average RMSE=3%, ME=0.15) had the best fit at low salinity level (2.5 dS/m). Among the multiplicative models, reduction functions of Dirksen model at 4.5 dS/m with average RMSE=5% and ME=0.09 was in better fit to the measured data than the other functions.Homaee (average RMSE=9%, ME=0.12) and Vandam models (average RMSE=9%, ME=0.11) at higher salinity level (6.5 ds/m) were in better fit to the measured data than the other functions.
H B; A A; A KH
Abstract
In order to investigate the effect of irrigation and straw mulch on yield andyield components of bean, a split-plots experiment with randomizedcomplete block design in three replications was conducted in AstanehAshrafiyeh city during 2012. In this study, irrigation managementtreatments including ...
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In order to investigate the effect of irrigation and straw mulch on yield andyield components of bean, a split-plots experiment with randomizedcomplete block design in three replications was conducted in AstanehAshrafiyeh city during 2012. In this study, irrigation managementtreatments including no irrigation, irrigation frequencies of 6, 12, and18days, and different amounts of straw mulch as 0, 1, 2, and 3 cm thicknesswere examined. The results of the analysis of variance revealed thatirrigation management and different levels of mulch had significant effectson seed yield. But, their interaction was not significant on seed yield. Thetrend of variations indicated that the highest seed yield with 2431.3 kg ha-1was associated with irrigation frequency of 6 days. [n response to the maineffects of mulch levels, the highest average seed yield (1585.6 and 1518.4kg ha-1) was obtained in the 2 and 1 cm treatments, respectively. Also,using straw mulch in irrigation conditions prevented severe seed loss incomparison with no mulch condition. The highest water use efficiencywas in irrigation frequency of 18 days with an average of 0.58 kg m-3.Water use efficiency at straw mulch levels of 1 and 2 cm was observed as0.63 and 0.6 kg m-3, respectively.
Arash Tafteh; Niazali Ebrahimipak; Hossin Babazadeh; Fereydoon Kaveh
Abstract
Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions ...
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Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions using different methods including, minimum, average, multiplicative, Raes method, and product with yield response factor (Ky) power as applied by FAO and Najarchi yield response factors. To estimate tomato yield under different deficit irrigations and evaluation of empirical methods, a study was conducted by using randomized complete block design with irrigation interval treatments including T1, T2, T3, and T4 representing, respectively, 60, 90,120, and 150 mm evaporation from class A pan between consecutive irrigations. The study had three replications and was carried out at the Faizabad Agricultural Research Station, in Qazvin. The results showed that maximum water requirement of tomato plant was 1073 mm, T1 treatment had the maximum yield with 88500 kg/ha and T4 treatment had the minimum yield with 57000 kg/ha. Also, according to statistical comparisons, the proposed method that estimated the plant response factor based on monthly power had the minimum root mean square error (RMSE) and normal root mean square error (NRMSE), while it had the highest agreement index and coefficient of determination (R2).The plant yield response factors were determined in June, July, August, September, and October as, respectively, 0.7, 1.1, 1.1, 1.14 and 0.4. The value of this factor for initial growth, plant development satge, mid-season, and late-season were, respectively, 0.7, 1.1, 1.14, and 0.4, while the average for the whole growing period was determined as 0.89 by using the proposed method. As a result, the proposed method is suggested as a convenient method.