Agriculture
Ahmad Jafarzadeh; Abbas Khashei Siuki; Ali Shahidi
Abstract
Ensemble modelling is expanding in several areas of engineering, especially different aspects of water engineering. Accurate estimation of saffron water requirement (SWR), an essential strategic production of the agriculture sector, is a crucial and influencing act in local water planning of this region. ...
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Ensemble modelling is expanding in several areas of engineering, especially different aspects of water engineering. Accurate estimation of saffron water requirement (SWR), an essential strategic production of the agriculture sector, is a crucial and influencing act in local water planning of this region. Hence, this study aimed to check the applicability of ensemble modelling in enhancing SWR at Birjand, Southern Khorasan, Iran. The actual water requirement of saffron was recorded in the field lysimetric laboratory at the University of Birjand. The simulation of water requirement was conducted utilizing Decision Tree Regression (DTR) with input climate features. Additionally, Boosting and Bagging methods were employed to establish and enhance the ensemble process of soil water requirement (SWR) simulations. To track the effectiveness of any method, some comparative tests were designed, such as statistical criteria (RMSE and MAE) detection, Violin plot analysis, over/underestimation, times series comparison, and error improvement test. Results indicated that although the acceptable performance of DTR in simulating SWR, the probable improvement was potentially felt. Derived results confirmed that supervised ensemble modelling (Boosting) could enhance the accuracy of DTR by more than 30 percent (reducing absolute error from 36 mm to 23.65 mm), resulting in declining RMSE from 0.44 mm to 0.07 mm. Further, different experiment outcomes revealed that the Boosting algorithm quality is more appealing than DTR and Bagging outputs.
Other subject about saffron
Seeboyeh Aghamohamadi; abbas khashei; Ali Shahidi; Sayyed Reza Hashemi
Abstract
Climate changes and phenomena such as drought are effective in the yield of agricultural products. Replacing crisis management with risk management is one of the solutions for these phenomena. With risk assessment before crisis, the amount of damages will be reduced to the minimum amount. In this research, ...
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Climate changes and phenomena such as drought are effective in the yield of agricultural products. Replacing crisis management with risk management is one of the solutions for these phenomena. With risk assessment before crisis, the amount of damages will be reduced to the minimum amount. In this research, the risk assessment of drought by Monte Carlo method will be used in order to reduce the damages caused by drought as a natural and uncontrollable phenomenon on saffron product. The monthly Standardized Precipitation Index (SPI) of drought and the monthly average temperature are calculated as independent variables in the yield distribution function. The relationship between independent variables (temperature and SPI) and dependent variable (saffron yield) is established using Artificial Neural Network (ANN). After that, 2000 random data from independent variables are generated using MATLAB and 2000 simulated yields generated by a trained artificial neural network. Then, the cumulative distribution of the simulated yields are determined and these yields are standardized in order to unification of the yield data of each city. The risk factor is calculated by choosing a reference station and using the cumulative distribution. The relative risks of the stations are considered after drawing the diagram of Yield-Risk standard factor. The results of the research show that most of the studied years are in normal range and the drought frequency in the four stations of Khorasan Jonoobi province is twice the stations in Khorasan Razavi. Furthermore, the artificial neural network with a correlation coefficient of 0.85 could predict the yield of the product very well. The similarity of the cumulative distribution diagram of the real yield with the cumulative distribution of the yields simulated by Monte Carlo indicates that the results are correct. At the end The results of this research show that Ghayen has the highest relative risk compared to the reference station (Torbat-e- Heydariyeh) and Nehbandan has the lowest one.
Agriculture
Mahdieh Rashid Sorkhabadi; Ali Shahidi; Abbas Khashei Siuki
Abstract
The city of Torbat Heydarieh located in the central Khorasan is the largest producer of saffron in the world. According to the influence of various environmental factors on the growth and yield of saffron, the process of assessing land ratio for its cultivation requires the use of various detailed spatial ...
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The city of Torbat Heydarieh located in the central Khorasan is the largest producer of saffron in the world. According to the influence of various environmental factors on the growth and yield of saffron, the process of assessing land ratio for its cultivation requires the use of various detailed spatial and descriptive pieces of information. In this study, first the conditions of cultivating saffron have been studied in detail and suitable regions for planting saffron have been identified using maps of elevation, slope, soil characteristics, water and some climatic factors influencing the cultivation of saffron including effective threshold temperature, rainfall and sunshine hours. For this purpose, Fuzzy Analytical Hierarchy Process (FAHP) method was applied and modeling and spatial analysis were carried out using Arc GIS software environment based on the lands of the city of Torbat Heydarieh which were evaluated for their suitability for cultivation of saffron. It is worth noting that the final map showed that 43 percent of the central parts of Torbat Heydarieh have the highest potential for saffron cultivation. To evaluate the results and ensure the accuracy of the final map data, plant functions and crop qualities were compared with obtained data from final maps and the accuracy of the results was confirmed that shows the effectiveness of Fuzzy Analytical Hierarchy Process (FAHP) method in assessing the potential of lands for saffron cultivation.
