Irrigation
A,. Uossef gomrokchi; J. Baghani; F. Abbasi
Abstract
Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results ...
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Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results of prediction models and field information analysis. Tree models (decision trees) along with decision rules are one of the data mining methods. Tree models are a way of representing a set of rules that lead to a category or value. These models are made by sequentially separating data into separate groups, and the goal in this process is to increase the distance between groups in each separation. Research shows that plant yield is a function of various plant, climatic, and water, and soil management conditions. Therefore, calculating the amount of plant yield and related indices follows complex nonlinear relationships that also have special difficulty in modeling. Considering that the response of irrigated wheat to different inputs in different climates by field method is time-consuming, costly, and in some cases impossible, so the introduction of an efficient model that can predict yield and analyze yield sensitivity to various parameters is a great help. It will be to solve this problem. This study aimed to develop and evaluate the capability of three models of the neural network, tree, and multivariate linear regression in predicting wheat yield based on parameters affecting its yield in major wheat production hubs in the country. Materials and Methods: The information used in this study includes the volume of water consumption and yield of irrigated wheat and the committees related to these two indicators in irrigated wheat fields under the management of farmers (241 farms) in the provinces of Khuzestan, Fars, Golestan, Hamadan, Kermanshah, Khorasan Razavi, Ardabil, East Azerbaijan, West Azerbaijan, Semnan, south of Kerman and Qazvin, which were harvested in a field study in the 2016-17 growing season. According to the Ministry of Jihad for Agriculture statistics, these provinces have the highest area under irrigated wheat cultivation in the country and cover about 70% of the area under cultivation and production of this crop in the country. One of the most widely used monitored neural networks is the Perceptron multilayer network with error replication algorithm, which is suitable for a wide range of applications such as pattern recognition, interpolation, prediction, and process modeling. In the present study, in order to develop the neural network, the capabilities of R software with Neuralnet package have been used. After the normalization step, the data were randomized. This step aims to have a set of inputs and outputs in which the input-output categories do not have a special system. After the randomization of the data, the amount of information that should be used in the network training process is determined. This part of the data was considered for training (70%) and another part for network test (30%). Perceptron neural network activator functions in the implementation of network training and testing. The hyperbolic tangent activity function has been used to limit the range of output data from each neuron and the pattern-to-pattern training process. In the present study and the neural network modeling capability, the tree model method has been used to predict wheat yield. Tree modeling is one of the most powerful and common tools for classification and forecasting. The tree model, unlike the neural network model, produces the law. One of the advantages of the decision tree over the neural network is that it is resistant to input data noise. The tree model divides the data into different sections based on binary divisions. Each data partition can be re-subdivided into another binary, and a model fitted to each subdivision. In this research, the capabilities of WEKA software have been used to run a tree model. It is worth noting that after grouping, the prediction model is applied to the grouped data. Results and Discussion: In this study, the efficiency of three models of the artificial neural network, multivariate linear regression, and tree model to predict the performance of irrigated wheat in major production areas in the country was evaluated based on field information recorded in 241 farms. The results showed that the coefficient of explanation of the model in predicting the yield of wheat production in the model of artificial neural network and a multivariate linear regression model was 0.672 and 0.577, respectively, which was applied by grouping the data by tree method. The coefficient of explanation has been increased to 0.762. The output results of the tree model showed that the major wheat production areas in Iran in terms of water consumption could be divided into four independent groups. Finally, it can be concluded that the tree model, considering the purposeful grouping in the input data, can be used as a powerful tool in estimating irrigated wheat yield in major wheat production areas in Iran. Conclusion: In this study, the need to use data mining methods in analyzing field information and organizing large databases and the usefulness of data mining methods, especially the decision tree in estimating wheat crop yield, were investigated and compared with other forecasting methods. The general results of the research show that purposeful separation of input data into forecasting models can increase the output accuracy of forecasting models. However, it is not possible to provide a general approach to selecting or not selecting a forecasting model in different regions. In some studies, neural networks have shown a high ability to predict the performance of different products, but it is important to note that if there is sufficient data and correct understanding of the factors affecting the dependent variable, the accuracy of the models can be applied by data mining methods. It also improved the neural network. In a general approach, considering the accuracy of estimating the predicted models under study, these techniques can be used to estimate other late-finding characteristics of plants and soil.
javad baghani; A. Alizadeh; H. Ansari; M. Azizi
Abstract
Introduction: Production and growth of plants in many parts of the world due to degradation and water scarcity have been limited and particularly, in recent decades, agriculture is faced with stress. In the most parts of Iran, especially in the Khorasan Razavi province, drought is a fact and water is ...
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Introduction: Production and growth of plants in many parts of the world due to degradation and water scarcity have been limited and particularly, in recent decades, agriculture is faced with stress. In the most parts of Iran, especially in the Khorasan Razavi province, drought is a fact and water is very important. Due to melon cultivation in this province, and the conditions of quality and quantity of water resources and water used to produce the melon product in this province, any research done on the use of saline and brackish waters is statistically significant.
Materials and Methods: To study the effects of different water salinity and water management on some of the agronomic traits of late summer melon with drip irrigation, an experiment with 7 treatments and 3 repetitions was conducted in a randomized complete block design, in Torogh station, Mashhad. The irrigation treatments were: 1- fresh water from planting to harvesting, 2- water (3 dS/m) from planting to harvesting, 3- water (6 dS/m) from planting to harvesting, 4- water (6 dS/m) from 20 days after plantation to harvesting, 5-water (6 dS/m) from 40 days after plantation to harvesting, 6-water (3 dS/m) from 20 days after plantation to harvesting, 7-water (6 dS/m) from 40 days after plantation to harvesting.
Row spacing and plant spacing were 3 m and 60 cm, respectively and the pipe type had 6 liters per hour per unit of meters in the drip irrigation system.
Finally, the amount of salinity water, number of male and female flowers, number of seed germination, dry leaves' weight, leaf area, chlorophyll (with SPAD) etc. were measured and all data were analyzed by using MSTAT-C software and all averages of data, were compared by using the Duncan test.
Results and Discussion The results of analysis of data showed the following:
Number of seeds germination: Salinity in water irrigation had no significant effects on the number of seed germination. However, there was the most number of seed germinations in the fresh water treatments. However, with increased water salinity, the time of seed germination reduced. The maximum delay in germination of seeds was in the treatment that was irrigated with fresh water from the beginning of cultivation.
Number of flowers: First, the male flowers appeared and after 5 to 7 days, the appearance of female flowers began. The effect of irrigation treatments on female flower appearance was significant. With increased water salinity, the number of male flowers decreased. There was the lowest male flower in the treatment that was irrigated with saline water from the beginning, but there was no significant difference among the other treatments.
Root, steam and leaves: The effect of saline irrigation water on dried leaves’ weight and dry root weight was significant at 1% and 5% levels, respectively. Fresh treatment and salinity treatment have the least and the most root dries weight, respectively (irrigated from the beginning with fresh or saline water). Two treatments that were irrigated with fresh and brackish water from thebeginning of cultivation have the highest leaf growth. The same trend was true for steams.
In general, in all treatments, after applying different quality water to the end of the growing season, the trend of plant growth was similar to the others.
Chlorophyll: One of the most common measurements made by plant scientists is the determination of Chlorophyll concentration. The SPAD index was used for comparison of chlorophylls. With an increase of the salt in irrigation water, the SPAD index was also increased.
The maximum and minimum SPAD was in the treatments that were irrigated with saline water (treatment A) and fresh water (treatment C) from the beginning of cultivation, respectively.
Yield: With increasing the salinity of water, the total yield decreased. Salinity in irrigation water had a significant effect (at the 5% level) on total yield. The mean yield of brackish and salinity irrigation water treatments were 17.5% and 26% less than the fresh water irrigation treatment, respectively.These differences were significant. However, there was no significant difference between the yield of cases using brackish or salt water.
Conclusion: The results showed the following:
Salinity in irrigation water had no significant effect on the number of seed germinations. However, there was the most number of seed germinations in the fresh water treatments, but by raising the salinity of water, the time of seed germination was reduced.
With increasing the salinity of water, the number of male flowers decreased. There was the lowest male flower in the treatment that were irrigated with salt water from the beginning, but there was no significant difference between the other treatments.
The effect of salinity water on leaf dry weight and dry root was significant at 1% and 5% levels, respectively. Fresh and salinity treatments have the least and the most root dry weight, respectively (irrigated from the beginning with fresh or salt water). Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaf growth.
The same trend was true for steams.
Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaves areas. And they had significant difference with other irrigation treatments.
With an increase in the salt in irrigation water, the SPAD index also increased.
The mean yield of brackish and salinity water irrigation treatments were 17.5% and 26% less than that of fresh water irrigation treatment, respectively.These differences were significant. But there was no significant difference between the yield of brackish and salt water.
mohammad karimi; J. Baghani; M. Joleini
Abstract
Introduction: One of the serious problems in the further development of maize cultivation is increasing irrigation efficiency. Using conventional irrigation causes a shortage of water resources to increase the acreage of the crop. With regard to the development of maize cultivation, agronomic and executable ...
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Introduction: One of the serious problems in the further development of maize cultivation is increasing irrigation efficiency. Using conventional irrigation causes a shortage of water resources to increase the acreage of the crop. With regard to the development of maize cultivation, agronomic and executable methods must be studied to reduce water consumption. Using drip irrigation system is most suitable for row crops. Hamedi et al. (2005) compared drip (tape) and surface irrigation systems on yield of maize in different levels of water requirement and indicated that drip irrigation increases the amount of yield to 2015 kg/ha and water use efficiency to 3 time. Kohi et al. (2005) investigated the effects of deficit irrigation use of drip (tape) irrigation on water use efficiency on maize in planting of one and two rows. The results showed that maximum water use efficiency related to crop density, water requirement and planting pattern 85000, 125% and two rows, respectively with 1.46 kg/m3. Jafari and Ashrafi (2011) studied the effects of irrigation levels, plant density and planting pattern in drip irrigation (tape) on corn. The results showed that the amount of irrigation water and crop density on the level of 1% and their interactions and method of planting were significant at the 5 and 10% on water use efficiency, respectively. The yield was measured under different levels of irrigation, crop density and method of planting and the difference was significant on the level of 1%. Lamm et al. (1995) studied water requirement of maize in field with silt loam texture under sub drip irrigation and reported that water use reduced to 75%; but yield of maize remained at maximum amount of 12.5 t/ha. The objective of this study was to evaluate the drip (tape) irrigation method for corn production practices in the Qazvin province in Iran.
Materials and Methods: In this study, yield and yield components of corn (SC 704) were investigated under different levels of irrigation water in drip tape systems in one and two rows planting patterns with different plant densities. The experiment was conducted on randomized complete blocks as a split plot (Split block) design with 3 replicates in the Qazvin region. Four levels of irrigation including: 80, 100 and 120 percent of water requirement with drip irrigation (tape) and 100% water requirement with furrow irrigation (control treatment) as main plots and method of planting (one and two rows) with three levels of crop density including: 75000, 90000 and 105000 as subplots were considered. After harvesting, grain yield, number of rows per ear, number of kernels per ear row, number of grains per ear and 1000-kernel weigh were measured.
Results and Discussion: The results of simple variance analysis of attributes showed that the method of planting has a significant difference on the level of 5% for grain yield, but on the other the measured attributes did not have any significant effect. The respective effect of planting method and crop density showed a significant difference on the level of 5% for grain yield, number of kernels per ear and the 1000-grain weight, whereas it did not have any significant effect on the other measured attributes. The respective effects of irrigation method, planting method and crop density showed a significant difference on the level of 1% for the attributes of the number of kernels per ear. The planting in one row resulted in significantly higher grain yields than the other planting patterns. In mean comparisons of the interactions between irrigation methods, crop density and planting method, grain yield in drip irrigation at a level of 120% water requirement in the two rows planting pattern and crop density equal to 75000 plants was shown in the lead on the level of 10%. The results showed that the yields of the treatments were only affected by the method of planting and planting of one row lead the planting of two rows. According to means comparison and water use efficiency in each of the treatments and limitation of water resources, one row planting pattern with crop density equal to 90000 under drip irrigation at 80% and 120% (If there is no water restrictions) of water requirement were suitable.
Conclusion: According to the table of variance analysis, it can be seen that the effect of irrigation on corn grain yield was not significant. Research results of Sorensen and Butts (2005) and Azari et al. (2007) have also confirmed this subject. The grain yield in one row planting method was superior compared to two rows planting method. The superiority of one ton per hectare was statistically significant and substantial. Grain yields varied from 5360 to 12873 kg/ha among the treatments: in drip irrigation at a level of 120% water requirement in the two rows planting pattern and crop density equal to 75000 plants per hectare was 12873 kg/ha and the lowest yield was found in drip irrigation at a level of 80% water requirement in the two-row planting pattern and crop density equal to 75000 plants per hectare as 5360 kg/ha. With regard to mean comparisons of grain yield under the effects of interaction, and water use efficiency for each treatments, I1R1D2, I3R1D2, I1R1D1 and I2R2D3 treatments seem better than others.
Sh. Ashrafi; Hossin Sadrghaen; J. Baghani
Abstract
In order to evaluate the effects of different levels of irrigation, crop densities and cropping patterns on corn (KSC700 variety) water use efficiency using subsurface drip irrigation system, three field experiments were carried out in 2005 and 2006 in Karaj. Experimental design was split plot design ...
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In order to evaluate the effects of different levels of irrigation, crop densities and cropping patterns on corn (KSC700 variety) water use efficiency using subsurface drip irrigation system, three field experiments were carried out in 2005 and 2006 in Karaj. Experimental design was split plot design based on randomized complete blocks with three replications. In the first experimental Field, main plots were Three irrigation levels: 50%, 75% and 100% ET and sub plots were three plant densities: 65000, 75000 and 85000 plant per hectare and sub-sub plots were two planting patterns: one and two row plants per bed. Results showed that increasing the levels of irrigation from 50% to 100% of the plant water requirement, has a significant effect on yield and yield components. Results obtained from two years experiment showed that irrigation levels of 50% and 100% ET had the minimum and maximum yield values of 3.65, 12.28 and 3.58, 12.89 ton per hectare in years of 2005 and 2006 respectfully. Calculation on water use efficiency showed that treatments located to 75% and 100% ET groups have maximum water use efficiency compared to 50% ET treatments. This means that corn is a plant which is highly sensitive to deficit irrigation. It is recommended in area where there is no limitation in water resources, application of 100% ET for maintaining crop water requirement is suggested. In area where water resources is limited, it is suggested to maintain only 75% of crop water requirement by using subsurface drip irrigation method for corn production.
S.H. Sadrghaen; J. Baghani; S.A. Haghayeghi Moghaddam; M. Akbari
Abstract
Abstract
This study was conducted to determine the best drip irrigation method for pepper cultivation with the objective of water saving and obtaining maximum yield. The study was done during two years. Experimental design was randomized complete blocks design (RCBD) in split plot with four replications. ...
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Abstract
This study was conducted to determine the best drip irrigation method for pepper cultivation with the objective of water saving and obtaining maximum yield. The study was done during two years. Experimental design was randomized complete blocks design (RCBD) in split plot with four replications. Three different drip irrigation methods; drip irrigation with in-line emitter tubes, drip irrigation (tape), and drip irrigation with porous pipes as main plot and three different amount of water (50, 75 & 100% water requirement) were as sub-plot. The result in the first year showed that the effect of irrigation levels on the characteristics of plant except yield was no significant (α < 0.01), but the effect of irrigation methods on water use efficiency was significant (α < 0.05) .In the second year the effect of irrigation levels and irrigation methods on yield was significant (α < 0.05), but the effects of combination irrigation levels and methods on yield was not significant. The result in two years showed that the pepper is a sensitive plant to water deficit. The drip irrigation (tape) and 100% water requirement treatment had the highest yield and water use efficiency. The result also showed that the porous pipes had no good efficiency. According to the results, the best option for pepper is drip irrigation (tape) with using 100% water requirement.
Keywords: Drip irrigation, Pepper, Porous pipes, Tape irrigation, Water use efficiency
J. Baghani
Abstract
Abstract
In order to study the effects of cultivation method and water quantities in drip irrigation on yield of potato, an experiment was carried out using a split plot based on randomized complete block design with 4 replications in Torogh Agricultural Research Station (Mashhad, Iran) for tow years ...
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Abstract
In order to study the effects of cultivation method and water quantities in drip irrigation on yield of potato, an experiment was carried out using a split plot based on randomized complete block design with 4 replications in Torogh Agricultural Research Station (Mashhad, Iran) for tow years (2001 and 2002). The main-plots were divided into 3 levels of irrigation: I1= 100, I2= 80 and I3= 60 percent of evapotranspiration. Sub-plots were 3 cultivation methods: B1= distance between rows were 75 cm with one drip irrigation lateral, B2= two cultivation rows with distance of 35 cm and a lateral between them and distance between laterals was 135 cm and B3 = two cultivation rows with the distance of 45 cm and a lateral between them and distance between laterals was 150 cm. The results showed that Total yield in maximum irrigation (I1) was higher than I2 and I3. the B2 cultivation pattern had the highest total (19.7 t/h) and economic (18.5 t/h) yield. The B2 cultivation had the highest tubers yield (35-55 mm). Water use efficiency (WUE) of B2 cultivation with 3.54 kg/m3 was more than B1 and B3, but it was not significant. Water stress lead to reduction of total tubers yield, economic yield and WUE. maximum irrigation level (I1), had the most tubers yield (35-55 and bigger than 55 mm) and had significant difference with I2 and I3 irrigation treatment. WUE in maximum irrigation (3.53 kg/m3) was better than lower irrigation level in drip irrigation of potato and had significant difference.
Keywords: Potato, Drip irrigation, Cultivation method, WUE
