جستجوی مقالات مرتبط با کلیدواژه « soybean » در نشریات گروه « جغرافیا »

Among the various influencing factors in soybean production, climatic conditions are one of the most important variables that must be controlled. In this research, in order to know the natural capabilities of 7 stations of Parsabad, Ardabil, Khalkhal, Meshginshahr, Bileh Sawar, Sarein and Nair for soybean cultivation from the growth day degree, annual and seasonal rainfall, relative humidity, average, minimum and maximum temperature for the statistical period of 2001 to 2018. was used and with ANP a weight was determined for each criterion and SAW technique was used to calculate land suitability. By combining DEM and IDW maps, zoning maps were obtained in GIS. The results of the research showed that Parsabad and Beile Sawar are suitable for cultivation due to their altitude less than 1300 meters and Ardabil, Khalkhal, Sarein and Nair are highly restricted for cultivation due to their altitude greater than 1300 meters.

The evaluation of environmental conditions in particular climatic conditions of crops such as soybean that have a great economic importance for the country. In this regard, climate regions, with a minimum requirement of soybean cultivation were identified. By choosing a 20-year period from 1989 to 2008 and precipitation map of Iran on the basis of all available stations over 20 years of daily data completed, three regions with annual rainfall of over 500 mm in the North, West and South West were then determined. To increase precision, creating a virtual stations on the basis of daily maximum and minimum temperatures, areas outside of the internal parts were removed and each of the relevant area, was approved to determine the ultimate potential. Using CGMS software, the minimum temperature, maximum vapor pressure, sunshine hours and wind were estimated for rainfall estimation from Completely Regularized Spline (CRS) method, and Spline Regularize (SR) method was used to estimate relative humidity. In the next phase, the mean rate of deficit in soybean yield in dry land conditions was determined using the CROPWAT. Then, three valuable layers of precipitation, relative humidity and maximum temperature were explained by the use of AHP to determine the weight of each layer which was overlapped. The results showed that in the West and South West regions, with the percentage deficit crop yield of over 50%, conditions are low to moderate but the western half of the country's northern region can be considered suitable for soybean cultivation. Calculations showed that the deficit efficiency of the crop in this region, was less than 10 percent and thus has good potential for rain-fed soybean cultivation. It also became clear that to start rain-fed soybean cultivation in all regions, the month of Ordibehesht was more suitable than other months.

IntroductionChemical concentration of plants is indicator of their biologic status. Among the many foliar chemicals in plants, nitrogen (N) is an important indicator of photosynthetic rate and overall nutritional status. Plants usually take up nitrogen in the nitrate form (NO3 -) and one major source of nitrate leaching is fertilizer applied to the crops. Supplying inadequate N may decrease crop yields and increase the N fertilizer (more than the needs of plants). In addition to economic loss, nitrate ions may move into surface and ground water and contribute to eutrophication of lakes and streams and raise health problem (Liaghat and Balasundram 2010). Thus estimation of nitrogen content is important in many agricultural studies. Traditionally leaf nitrogen content is measured in the lab using different chemical methods. Nitrogen analysis either by the Kjeldahl or Dumas method is expensive and requires specialized equipments. An alternative method for N determination is the digestion of potassium persulfate (K2S2O8). Persulfate digestion requires only a modest initial investment and has few environmental risks. The common problems of all above mentioned approaches are the facts that they are time consuming, expensive and destructive approaches. The advent of remote sensing has proved its usefulness as an alternative measure to these traditional approaches. The aim of this study is to estimate canopy nitrogen content in vast area in northern part of Iran, Gorgan, using remote sensing vegetation indices. Later it was used in calibration of different vegetation indices and for estimation of CNC of a vast area in Gorgan, Iran.MethodologyLANDSAT TM imagery simultaneous to the field campaign was acquired. The field campaign was conducted in the latter half of August 2009 in northern part of Iran, Gorgan (36° 54' N, 54° 53' E). Fifty sample plots of 30 m× 30m were randomly chosen. In each sample plot, 4 to 7 subplots were selected and in each subplot 30 leaves form different parts of Soybean crops were cut and transferred to lab. Then using persulfate digestion, nitrogen content of the leaves was determined. In the field, canopy percentage was measured and multiplied by the leaf nitrogen content to calculate the canopy nitrogen content (CNC). The regression line between different vegetation indices (NDVI, GI, SAVI2, GRI) and CNC was calculated and the results validated using cross validation approach.Results and DiscussionOur study showed that the Persulfate digestion is an accurate method for determination of total N in soybean plant when measured in lab. Persulfate digestion does not produce a large quantities of toxic waste associated with Kjeldahl digestion. Additionally, persulfate digestion requires a minimum of specialized equipment: large screw topped culture tubes, an autoclave or a large pressure cooker and test tube racks. The method facilitates the determination of a large number of samples with the use of simple equipments. The relation of measured nitrogen at leaf and canopy level against indices is shown in figure 2. Clearly the relation at canopy level shows a better behavior than at leaf level. Results showed that GI has close relationship with CNC and can be used to retrieve crop vegetation nitrogen. This index uses green band of the electromagnetic spectrum which is appropriate for chlorophyll estimation and has a direct relationship with nitrogen. The most commonly used vegetation index is NDVI. The NDVI has been used for many years to measure and monitor plant growth, biomass production and vegetation cover from multispectral satellite data. Although in our study NDVI was not chosen as the best index, this index is generally considered a good indicator of the amount of vegetation and, hence, is useful in distinguishing vegetation from soil (Svotwa et al. 2012).ConclusionOur study showed that persulfate digestion does not produce the large quantities of toxic waste associated with Kjeldahl digestion and it requires a minimum of specialized equipments. In comparison to the used indices in this study (NDVI, GI, SAVI2, GRI), the GI index demonstrated a better correlation with canopy nitrogen content. This good relationship is not surprising as GI has been developed for chlorophyll estimation which has a direct relationship with nitrogen. Although, the amount of N is only 26% of leaf dry weight but surprisingly it has strong effect on reflected radiation.

Nowadays, global warming and its impact on various fields such as agriculture, economics, energy, and politics are interested to researchers. Therefore, it is interesting to investigate the effect of global warming on agriculture and safeness of food for the residents. Soy bean is one of those products which seem to be important and strategic for various areas, especially Gorgan. In this study data were obtained on a daily, monthly and annual basis considering minimum and maximum degrees for long-term observation since 1961 to 1990 from the Meteorological Department. For this study, to evaluate various effects of climate change over two periods of 2034-2049 and 2065-2079 on the scale of degree-day, the model HasCM3 was used. But the outputs of this model were evaluated by using Lard-WG on daily station scale. Moreover, to investigate the role of scenarios, scenarios of A1, A1B and B2 were used. As for the heat output for various scenarios, the most pessimistic result which is equivalent to the maximum degree is the A2 scenario with the temperature increase of 0.64 ° C for the period 2035-2049 and 0.60 ° C for the period 2065 to 2079. However, on the basis of the degree increase, the trend of degree-day for most scenarios and simulated years increased, although the values for the late summer and early autumn ​​coincided with the summer planting showed a decrease in degree-day trend. But based on long term statistics from 2011 to 2100, the trend of degree-day showed an increase for spring planting and a decrease for summer crop. So it is recommended that in the coming decades due to climate change, early planting of this crop in the summer should be implemented. This is because of the fact soybean can provide its appropriate degree-day value in a brief period.[1].