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Showing 8 results for Wheat

Dr Hassan Kharajpour, Dr Zahra Hejazizadeh, Dr Bohloul Alijani, Dr Mohammad Hossein Nasserzadeh,
Volume 0, Issue 0 (3-1921)
Abstract

      Considering the undeniable impact of agricultural plants on climatic and regional changes, it seems necessary to conduct regional research to understand the reaction of each agricultural plant in different stages of growth in relation to weather elements. If the temperature of the air along with the warm cloud is lower or higher than a certain threshold, its development will stop. Between the two limits, there is an optimal temperature where the plant grows the fastest. Temperature and clouds are both the most important climatic elements in agriculture. Both climatic parameters together cause stress in wheat and lower the productivity of the product. Considering the strategic nature of wheat, in order to increase the level of production, in the present research, while taking advantage of the experiences and methods and models used in foreign and domestic researches, it was practical in Kermanshah province due to the extent of the land under wheat cultivation and The significant amount of production, which has a special place in this field at the level of the country, the determination of the statistical threshold and the synoptic analysis of warem cloud temperatures on the performance of the wheat crop are investigated. According to the investigations and consultations with agricultural engineers, the maximum temperature along with cloudy days causes the phenomenon of greenhouse and excessive heat, which causes the fall of flowers, rot, sterility of pollen grains, fruit reduction, Premature aging and poverty become seeds, and this phenomenon occurs mostly in the months of May and June.

Mohamad Reza Mobasheri:, Samira Ranjbar,
Volume 17, Issue 44 (3-2017)
Abstract

The goal of this study is to identify farms which are affected by wheat rust disease. For this, the sensor data of Landsat 7 satellites in growing season of 2013 and 2014 along with some laboratorial data containing reflectance spectrum of leaf and leaf health degree in different levels of disease are used. The reflectance values of leaf are collected by an ASD spectroradiometer in the range of red and near infrared spectrum. The spectral are simulated for Landsat sensor bands using their spectral response functions. Then with the index of DVI and data obtained for leaf health, the Wheat Health Index was introduced. The correlation coefficient obtained is 0.82 and the relevant RMSE is 0.089 which is really good result for diagnosing highly advanced disease. The results show that, this index has a good performance in wheat high growing season when the greenness is high. It can diagnose regions that are healthy from those whom are blighted. Because the WHI index is a spectral index and is sensitive to leaf color, if the acquired images are close to the harvesting time, its performance will be weakened. The selected region in this survey is located in Fars, province, Saadatshahr city.


Naseh Qaderi, Bohloul Alijani, Zahra Hejazizadeh, Mohammad Saligheh,
Volume 18, Issue 48 (3-2018)
Abstract

Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data of planting area, amount of production, damages and yield of wheat of 31-year in 10 regions of Kurdistan along with the hourly, daily, decade, monthly, seasonal and yearly levels data of 22 synoptic stations were collected. The correlation between wheat yield and 128 independent variables was calculated. The effect of variables on yield evaluated by multivariate regression. The spatial analysis of variables was performed and the spatial model of wheat yield was introduced for province and regions. The results showed that climatic elements in various regions are different, in a 99% confidence. Most of the independent variables alone have a significant effect on wheat yield, but in the stepwise model, 7 variables such as: the number of rainy days of the year, the sum of the degree hours (of temperature less than -11 ° C) in germination and tilling stage, annual precipitation and the precipitation of November are determinants of the yield. Yield and effective independent variables have significant spatial differences even in a cluster climate type. The highest and lowest coefficient of variation of wheat yield is related to Bijar and Kamyaran areas, respectively. Kamyaran and Sanandaj regions have the highest and lowest yield, respectively. Bijar is the highest risk region of the province for wheat production.


The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.

Leyla Sharifi, Saeed Bazgeer, Hosain Mohmmadi, Alireza Darbaneh Astaneh, Mostafa Karimi Ahmadabad,
Volume 20, Issue 57 (6-2020)
Abstract

In an agricultural system, crop production is related to climatic conditions. Therefore, a deeper understanding of the impact of regional climate change on production ensures global food security. Wheat is one of the most strategic crops and examining different aspects of its production is a necessity of every agricultural community. According to studies, wheat production is affected by various variables including environmental, individual and social, economic and technological. The aim of this study was to estimate the effect of these variables on changes in wheat production in different climates of Fars province. The required data were collected and analyzed through multi-stage random stratified sampling and 522 completed questionnaires through face-to-face interviews with farmers in the province. Farmers' attitudes were measured in the Likert scale and Cobb Douglas, Transcendental and Translog production functions were used to estimate the effect of variables. Results of comparing effective variables in three Cobb-Douglas, Transcendental and Translog functions; demonstrates the superiority of translog. From the perspective of the farmers of the province in the translog function, respectively; Soil moisture at planting time (0.692), effective rainfall during growing season (0.68) and at planting date (0.66), heat wave at harvest time (0.63), damaging rainfall (0.59) , Profit from wheat production (0.51), farmer education (0.49), soil quality (0.49) and cultivation method (0.49) with the coefficient of the mentioned criteria next to them; The most important factors explaining wheat production in Fars province. Independent variables in the translog function explain 92% of the changes in wheat production in Fars province.

Yousof Parsamehr, Hosien Mohammadi, Faramarz Khoshakhlagh, Saied Bazgeer,
Volume 22, Issue 64 (3-2022)
Abstract

In this study, in order to study the base temperature (minimum temperature for plant growth) at the degree of growth day (GDD), which is one of the important parameters in calculating the degree of growth day, first, the data required for the 2009-2017 statistical period of wheat production at the station Sararood was taken from the station. Then, after sorting and separating growth different stages, using four methods of calculating the base temperature (1 - minimum standard deviation SDgdd day, 2 - minimum standard deviation SDAY days, 3 - regression coefficient per day CRday, 4 - CV coefficient of variation) was the most suitable method for calculating the base temperature of growth in different stages of planting to wheat harvesting. The results showed that the most suitable method is the minimum standard deviation in GDD, which The base temperature was obtained from germination to full reach for different growth stages, 5/8, 0/38, 1/8, 2/6, 0/63, 2, 3/7, 9/7, 8/6, 11 degrees Celsius. By comparing different methods of calculating GDD, the most appropriate of method was the general method of calculating the degree of growth day due to the most of similarity to the station data. The degree of growth day in different stages was calculated based on their base temperature and the results showed that the calculation of the base temperature at each stage of the growth of the wheat was very accurate for GDD calculation and a precise estimate of GDD was obtained.
Dr Bromand Salahi, Vahid Safarian Zangir,
Volume 23, Issue 68 (3-2023)
Abstract

Global warming and temperature rise will have many effects on different sectors, including agriculture, the warming of the earth will increase the rate of evaporation, and consequently the increase in the demand for agricultural products will increase. In this study, in order to monitor the effect of global warming on Mughan Plain wheat, using the LARS-WG model as a relatively inexpensive and accurate instrument for producing climate multi-yearly climate change scenarios On a daily basis, In Ardabil province, Germi Station was selected as the representative of the three stations in the study area due to the data in the appropriate statistical period. In the present study, to monitor the effect of global warming on precipitation fluctuations, as well as in the production and cultivation of wheat crop in Moghan plain, the LARS-WG model and the HADCM3 climate model output under A1B scenario as well as climate data (minimum temperature, maximum temperature, precipitation and Daily Sunshine) The Germys station was used over a 14 year period (2004-2007).The results of the research show that by comparing the monthly mean of these parameters, this result was obtained that at confidence level 1 there is not a significant difference between the simulation data from the model and observational data in the base period and the mean The climatic parameters of the data obtained from the model and the actual data are similar and there is a high correlation between them. Finally, by comparing observational monthly meanings and modeling of climatic elements of precipitation, minimum and maximum temperatures and sunshine were shown using statistical parameters RMSE, MAE, NA and R2 The model (LARS-WG5) is used to accurately simulate daily data in the parameters of the Mughan Plain, Ardebil province. The results of this study showed that the average decrease in yield of irrigated wheat and the decrease of its production in the study area could be due to the decrease of precipitation and the increase of the regional temperature which is due to global warming.
Mohammad Ahmadvand, Shahriar Khaledi, Parviz Kardavani,
Volume 23, Issue 69 (6-2023)
Abstract

Climate and the required parameters for agricultural products are the important factors of production. We can determine potential facilities in different areas and consider the maximum tapping through agricultural meteorology. Due to drylands potentials in Hamedan province, we conducted a comprehensive survey based on 20 years (1995-1995) climatic elements of 9 main and supplementary synoptic stations. Thus, according to wheat phenological conditions and matching those with climatic conditions requirements in Hamedan province, we surveyed effective indices in grow crops. Finally, using geographic information systems (GIS) we implemented climatic elements zoning and weighting. Then the appropriate and inappropriate areas of the province for dryland wheat were determined. Results indicated among the climatic elements, annual rainfall and its distribution during the growing season, also the grow degree day (GDD) are important factors in process of dryland wheat. Based on maps extracted from the GIS, about 18 percent of the areas of province which are located in west, south west including Nahavand, Tuiserkan and Asadabad cities, enjoy very potentials and 46percent medium, 34percent good and 2 percent of Ghahavand city of Hamedan city functions lacks the necessary talent. with no potentials.
 
Mohamad Hosein Hoseini Rozbahani, ,
Volume 23, Issue 71 (12-2023)
Abstract

Wheat is the main human food that is consumed directly. Recognition of climatic parameters and study of climatic needs of crop plants is one of the most important factors in the production of rainfed wheat. This study is due to the importance of climatic parameters in rainfed wheat production and also due to the potential of rainfed rainforests in Tajikistan, including Ryan Panjkent and Qa in Wadi Zarafshan. The data used in this study were collected through the Tajik Meteorological Department and the Tajik Ministry of Agriculture and the Pentecostal Agricultural Office in the field and in libraries. In the first step, the data were checked for homogeneity and uniformity. In the next step, using Lars Wg software using HadGEM2-ES series models and three scenarios of RCP26, RCP45, RCP85 in the period 2011-2050, the Lars model's ability to predict the climatic variables of Panjkent station was evaluated and then the data. The prediction was evaluated with observational data and also through Anova correlation and test between climatic parameters and production of rainfed wheat per hectare by Toronto White Climate Method. Connection results between climatic parameters and rainfed wheat production Using the analysis of variance (F) test and comparison with the table of coefficients of F showed; There is a significant relationship between rainfall in May and maximum temperature in June with wheat production and also rainfall in October, maximum temperature in November with rainfed wheat production in Panjkent station, there is no significant relationship per hectare.

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