نشریه بوم شناسی کشاورزی
سال هفتم شماره 3 (پاییز 1394)

Most important factor limiting plants growth in agriculture is deficiency of nitrogen as compare to other nutrients. Plant needs to nitrogen is due to reason that nitrogen after hydrogen is largest elements in plant that absorbed from soil. Nitrogen in soil especially in surface layer is more and in the form of organic composition, therefore nitrogen accumulation in soil has direct relationship with organic matter accumulation. Soil organic matter in the in our country are low due to different reasons including low rain fall, unsuitable cultivation rotation. Urea is one of the nitrogen sources which its uses extended all over the world in agriculture sector. Nitrogen is one of the important nutritious mineral matters for plant growth and is a suitable source for increasing yield especially in improved varieties. At present due to economical problems in cost of chemical fertilizers in one side and environmental effects of high consumption on the other side are the difficulties of sustainable agriculture (Mulvaney et al., 2009). Ngo et al. (2012) showed that mineral fertilizers application had negative effects on soil like soil acidifying, drainage loss and decreasing microbial biomass. Displacement of mineral fertilizer with organic compounds like compost can reduce negative effects. Composts are organic material which has lots of advantages. Results of different studies showed that compost cause better soil fertility (Caravaca et al., 2002). Sunflower (Helianthus annuus L.) is one of five oil plants which is resistant to drought and adaptable in different climate of the country, growth and develop in different soil. Also high oil quality, low growth period after wheat and barley and its cultivation as a second crop cultivation. For reaching these aims we should understand how its effect the high absorption efficiency of nutrient mineral and other factors affecting and ways to achieve them. For the reaction of sunflower to different levels of urea fertilizer and iron sulphate in the presence and non presence of vermicompost, a field experiment conducted in Darreh Gaz district (Khorasan Razavi province) in 2013. This experiment was in the form of factorial on the bases of complete randomized block design with three factors and three replications. In this experiment three level of urea fertilizer including, 50, 150 and 250 kg.ha-1 as main factor and two levels of iron sulphate including zero and 80 kg.ha-1 as second factor and vermicompost in two levels zero and 7 t.ha-1 as third factor. Nitrogen treatment was applied in three stages. First stage was 1/3 of urea application at seeding stage. Second stage was at 8 leaf stage and application second 1/3 of urea and last 1/3 of urea applied at flowering stage. Iron sulphate treatment totally applied at flowering stage. Seeds were sown at depth of 3-5 cm on the furrows; plots had 4 lines for cultivation with the length of 6 meter. Distance between lines was 50 cm and distance between plants was 20 cm. At the end of season growth properties of plant like, plant height, stem diameter, tray diameter, leaf dry weight, leafstalk dry weight, stem dry weight, tray dry weight were measured. Statistical analysis were done with SAS ver. 9.1 and figures were done with excel. Mean comparison at 5% level were done with LSD test. Plant height, interaction effect of nitrogen and vermicompost on sunflower stem height was significant at 1% level. Highest stem observed at 250 kg.ha-1 nitrogen and zero vermicompost application. Conjoint effect of nitrogen and iron sulphate on plant stem height was significant at 1% level. It seems that increase in nitrogen level cause better plant photosynthesis and finally higher plant height. Interaction effect of three factors had significant effect at 5% level on plant stem height. Composition effect of nitrogen and vermicompost on stem diameter was significant at 5% level. Lowest stem diameter achieved at 50 kg.ha-1 nitrogen and zero vermicompost application. Effect of nitrogen and iron sulphate on stem diameter were significant at 5% level. Interaction effect of vermicompost and iron sulphate was significant at 5% level. Interaction effect of nitrogen and vermicompost on tray diameter was significant at 1% level. Also interaction effect of vermicompost and iron sulphate on tray diameter was significant at 1% level. (Rahimizadeh et al., 2010) showed that micro element application to sunflower had significant effect on tray diameter. Three factor interaction on tray diameter were significant at 1% level. Sunflower verities had different reaction to nitrogen application. Interaction between nitrogen and vermicompost had significant effect on yield at 1% level. Highest yield were 7.73 t.ha-1 with interaction of nitrogen (250 kg.ha-1 and vermicompost at 7 t.ha-1). Results showed that combination of vermicompost and iron sulphate along with different levels of urea compared to single effect of them needs more investigation. Vermicompost application as improve soil properties like porosity, available moisture and nutrient elements can improve the plant growth and better fertilizer use efficiency. Therefore it seems that conjunction of chemical fertilizer and vermicompost can improve sunflower growth in Darreh Gaz District.

Carbon sequestration is one of the most important approaches to reduce CO2 concentration in the atmosphere. Increase of CO2 in the atmosphere has prompted renewed interest in increasing the stocks of carbon (C) in the world’s croplands to mitigate climate change and also improve soil quality. To better characterize, predict and manage soil C dynamics, more precise and accurate estimates of C inputs to the soil is required. The C fixed in plants by photosynthesis and added to the soil as above- and below-ground litter, is the primary source of C in ecosystems (Warembourg & Paul, 1977). Predicting the changes in C stocks (notably in soils), therefore, depends on reliable estimates of net primary productivity (NPP) and the proportion of the NPP returned to the soil (Paustian et al., 1997). The annual NPP in agroecosystems, and the distribution of C in plant parts, is usually calculated from agricultural yield, the plant component most often measured. For carbon sequestration estimation, it is necessary to evaluate the effects of management practices on soil organic carbon (SOC) dynamics in a wide range of production systems and climatic zones. Soil organic carbon is essential for maintaining fertility, water retention, and plant production in terrestrial ecosystems. The amount of SOC stored within an ecosystem, depends on the quantity and quality of organic matter returned to the soil matrix, the soils ability to retain organic carbon (a function of texture and cation exchange capacity), and biotic influences of both temperature and precipitation. The abiotic influences on SOC dynamics, such as moisture, temperature, aeration and the composition of plant residues are reasonably well understood. The objective of this study was to evaluate the amount of carbon sequestration by agro-ecosystems and also the amount of CO2 emitted from agro-ecosystems in Iran. The amount of carbon input for seven main crops including cereal (wheat, barley, rice and maize), forage crops (alfalfa), industrial crops (cotton) and legume (chickpea) were calculated in different climate types of Iran and finally, the amount of carbon sequestration and CO2 emission for different crops were estimated. Plant C allometric functions developed for the crops together with The Introductory C Balance Model (ICBM; Andrén and Kätterer, 1997) to describe SOC dynamics for the cropping systems were employed in this study. The model has two compartments, called Young and Old soil C, and five parameters: i, re, h, kY and kO. Annual inputs of soil C to topsoil from crop and manure are summarized in i. The parameter re (decomposer activity factor, see above) is multiplied by kY and kO, respectively, to determine the actual decomposition rates of the young and old pools for a given year. Parameter h, the humification coefficient, determines the fraction of the input that goes through Young and into Old (humus, or refractory component), and is about 0.1 for most agricultural crops and about 0.3 for manure. Then we adapted the ICBM soil climate and decomposer activity parameter (re) to account for the major effects of managing and climatically parameters. The re parameter usually is calculated from subparameters based on climate, soil type, crop type, intensity of cultivation and so on. The average of carbon input during 20 years showed that the warm-dry climate had the highest carbon input and cold climate had the lowest amount. The highest carbon input fluctuation was obtained in cold climate by 29.13% per year and the lowest fluctuation was related to warm-dry climate by 8.82% per year. Trend of carbon input changes among different crops illustrated that the highest carbon input was gained by alfalfa and cotton and the lowest was for chickpea. Alfalfa and cotton had the highest sequestrated carbon to the soil in all years and the lowest was observed in chickpea. The highest and lowest carbon sequestration was related to warm-dry and warm-wet climate, respectively. The highest amount of CO2 emission was observed in warm-wet climate (450 kg.ha-1.year-1) as average of 20 years and the lowest was gained in cold climate (125 kg.ha-1.year-1). The results showed that the average of CO2 emission in 20 years was 580 kg carbon for alfalfa which had the highest amount and chickpea had the lowest CO2 emission (78.8 kgc.ha-1). A significant relation was observed between CO2 emission with carbon input to the soil and also with temperature. In essence, it was shown that by increasing the temperature and decreasing the humidity of regions, the value of carbon input was reduced. Among the study crops, alfalfa and cotton had the highest sequestrated carbon to the soil. The highest and the lowest amount of CO2 emission was related to warm-wet and cold climate, respectively.

Crop productivity is highly constrained by water and nitrogen limitations in many areas of the world. Therefore, there is a need to investigate more on nitrogen and water management to achieve higher production as well as quality. Irrigated sugar beet in the cropping systems of Khorasan province in northeastern of Iran accounts for about 34% of the land area under sugar beet production (~115,000 ha) with an average yield of around 36 t.ha-1. However, there is a huge yield gap (the difference between potential and water and nitrogenlimited yield) mainly due to biotic and abiotic factors causing major reduction in farmers’ yield. Accordingly, yield gap analysis should be carried out to reduce the yield reduction and reach the farmer’s yield to the potential yield. The current study aimed to simulate potential yield as well as yield gap related to water and nitrogen shortage in the major sugar beet-growing areas of Khorasan province of Iran. This study was carried out in 6 locations across Khorasan province, which is located in the northeast of Iran. Long term weather data for 1986 to 2009 were obtained from Iran Meteorological Organization for 6 selected locations. The weather data included daily sunshine hours (h), daily maximum and minimum temperatures (◦C), and daily rainfall (mm). Daily solar radiation was estimated using the Goudriaan (1993) method. The validated SUCROSBEET model (Deihimfard, 2011; Deihimfard et al., 2011) was then used to estimate potential, water and nitrogen-limited yield and yield gap of sugar beet for 6 selected locations across the Khorasan province in the northeast of Iran. This model simulates the impacts of weather, genotype and management factors on crop growth and development, soil water and nitrogen balance on a daily basis and finally it predicts crop yield. The model requires input data, including local weather and soil conditions, cultivar-specific parameters, and crop management information. Soil water module was used to determine soil water balance under water-limited conditions. Some questionnaires were then sent to extension agents to obtain information from the main sugar beet producing fields in each location. The SUCROSBEET model reasonably well predicted root yield across the study locations. The model could be used to simulate sugar beet yield under potential, water and nitrogen-limited situations. Simulation results of SUCROSBEET model showed that the lowest and highest sugar beet potential yield were obtained in Sabzevar (100 t.ha-1) and Neishaboor (137 t.ha-1), respectively. Total yield gap (the difference between potential and farmer’s yield) ranged from 74 to 109 t.ha-1, in Sabzevar and Neishaboor, respectively. Despite the fact that most of the farms had been irrigated up to 20 times over seasons, there were still yield gap of an average 42 t.ha-1 due to water shortage. To reach the potential yield in the study locations, more than 2000 mm water is required in Sabsevar and Torbat-Jam and 1400 to 1500 mm in Ghoochan and Neishaboor, respectively. On average, to fill nitrogen-limited yield gap, 440 to 530 kg.ha-1 of nitrogen for sugar beet uptake are also required. However, the farmers in various locations have been able to apply only 50% of the sugar beet nitrogen demands during the past decade. The results of the current study also suggested that the farmer yields of about 16-48 t.ha-1in the irrigated locations across Khorasan province, were not constrained by low genetic yield potential. It is also needed to irrigate more than two times in some locations for reaching water-limited yield to potential one. Although there is a high potential for production of sugar beet (more than 130 t.ha-1), the ratio of yield production to water consumption (known as water productivity) is not suitable in the study locations and production of sugar beet would not be cost-effective. Another issue which has not been considered in the simulations is qualitative traits of sugar beet (such as sugar content, Alkaloids, molasses sugar, sodium and potassium in storage organ, etc.) particularly under different levels of nitrogen applications. Although increasing nitrogen application would be resulted in higher yield and lower yield gaps, supplied nitrogen more than crop demand could be accumulated in storage organs and reduce white sugar yield. For instance, every 15 kg additional application of nitrogen reduced sugar content by 0.1 percent and reduced extraction coefficient of sugar. It is also worth noting that the current version of SUCROSBEET model is not capable to simulate qualitative traits of sugar beet and a few subroutines are needed to add to the model for future investigations. Conclusion The results indicated that although there is high yield potential for sugar beet in Khorasan province, water productivity would not be reasonable. In addition, yield gap in sugar beet cropping systems which reflects the actual yield gap in irrigated environments is essentially due to non-adoption of improved crop management practices and could be reduced if proper interventions are made.

Considering the nutrient loss, environmental pollution and increase in production costs on account of chemical fertilizer application, supplying mineral nutrients based on organic sources and mycorrhizal inoculation can improve organic matter content in soil (Hallajnia et al., 2007), promote sustainable production of oil crops (Kawthar et al., 2010) and ultimately affect the long term performance of the agricultural ecosystems in arid and semi-arid regions. Safflower (Carthamus tinctorius L.) is an annual oil seed crop belonging to the Asteraceae family and its spring cultivars are mainly grown in semiarid regions, especially in Iran. Hence, the current experiment was aimed to evaluate the effects of manure application and mycorrhizal inoculation on yield and yield components of spring safflower cultivars in Iran. In addition, quality yield in term of oil percentage was studied in response to experimental treatments. A field experiment was conducted at Agricultural Research Station of Ferdowsi University of Mashhad, Iran (latitude: 15° 36´ N, longitude: 28° 59´ E, altitude: 985 m), during growing season of 2009-2010, by using a completely randomized block design based on factorial fraction with three replications and sixteen treatments. The experimental treatments included four spring safflower cultivars (Darab, Isfahan, Arak and IL-111), two manure levels (no applying and applying manure 25 t.ha-1) and two mycorrhiza levels (no inoculation and inoculation with Glomus mosseae). The experimental field was prepared according to the local practices for safflower production. Each plot was 6 m2 (3 m long) and 1 m apart. Between blocks, 2 m alley was kept to eliminate all side effects of treatments. Seed sowing was performed at 14th April in 2010. Final density was 50 plants.m-2. The first irrigation was immediately done after seed sowing with weekly irrigation until physiological maturity stage (10 days before harvesting). At fully blooming stage, plant were harvested in one square meter in each plot and fresh and dry petal yield were recorded. At maturity stage, five plants from each plot were chosen randomly and number of branch per plant, number of seeds per head, seed weight per plant and 1000-seed weight were recorded. Final grain and oil yields were measured by harvesting 1 m2 of the central part of each plot. For statistical analysis, analysis of variance (ANOVA) and Duncan’s multiple range test (DMRT) were performed using SAS ver. 9.1 software. Results indicated that applying manure significantly affected number of branch per plant, number of seed per head, seed weight per head and 1000- seed weight as well as petal, grain, biological and oil yields of safflower cultivars. For instance, the applying manure significantly increased grain and oil yields of safflower cultivars more than two times. As mentioned before, organic fertilizers can improve the organic matter content, aggregates stability and nutrients availability in soil (Khandan & Astaraei, 2005; Halajnia et al., 2007), so application of manure fertilizer and gradual release of mineral nutrients into the soil would increase the growth, production and quality yield of spring safflower cultivars. Based on the results, effects of mycorrhiza inoculation on increasing the number of seed per plant, 1000 seed weight, petal, grain, biological and oil yields of safflower were significant. The highest grain (2546 kg.ha-1) and oil yields (685 kg.ha-1) were obtained from manure + mycorrhiza inoculation treatment. However, manure + mycorrhiza inoculation treatment did not have any effect on oil percentage and harvest index. Effective role of mycorrhizal inoculation in increasing the grain yield of safflower has also been reported by (Mirza Khani et al., 2010). Among safflower cultivars, Darab cultivar indicated the highest grain and oil yields (1327.7 and 346.4 kg.ha1, respectively). Based on our results, Darab and IL-111 cultivars had the most grain and oil yields, in comparison with Isfahan and Arak cultivars. However, no significant difference was observed between the spring safflower cultivars in term of number of seed per head and oil percentage. Consequently, selecting the Darab cultivar and applying manure in combination with mycorrhizal inoculation is strongly recommended to achieve a reasonable and stable yield of safflower. However, the environmental conditions of the cultivated area should be specifically considered to select a spring safflower cultivar.

The practice of growing two or more crops simultaneously in the same field is called intercropping and it is a common feature in traditional farming of small landholders. It provides farmers with a variety of returns from land and labour, often increases the efficiency with which scarce resources are used and reduces the failure risk of a single crop that is susceptible to environmental and economic fluctuation. The most common advantage of intercropping is the production of greater yield on a given piece of land by making more efficient use of the available growth resources using a mixture of crops of different rooting ability, canopy structure, height, and nutrient requirements based on the complementary utilization of growth resources by the component crops. Moreover, intercropping improves soil fertility through biological nitrogen fixation with the use of legumes, increases soil conservation through greater ground cover than sole cropping, and provides better lodging resistance for crops susceptible to lodging than when grown in monoculture. Careful planning is required when selecting the component crops of a mixture, taking into account the environmental conditions of an area and the available crops or varieties. A number of indices such as land equivalent ratio (LER), relative crowding coefficient (RCC), aggressivity (A), competitive ratio (CR), actual yield loss (AYL), and intercropping advantage (IA) have been proposed to describe competition within, economic advantages and equivalent yield of intercropping systems (Agegnehu et al., 2006; Banik et al., 2006; Dhima et al., 2007). The objective of this study was to determine the best treatment of sole or intercropping of wheat and chickpea and evaluation of competition indices in intercropping under nitrogen consumption. In order to investigate the competition indices of intercropping of wheat and chickpea under nitrogen effect, an experiment was arranged as factorial based on Randomized Complete Block Design with three replications during 2009-2010 in Gonbad Kavous University farm. Planting patterns factor included four levels of sole cropping of wheat (W), two rows of wheat with one row of chickpea (W2C1), one row of wheat with two rows of chickpea (W1C2) and sole cropping of chickpea (C) and nitrogen application consisted of four levels of 0, 25, 50, 75 and 100 kgN ha-1. Each plot had 5 rows and the rows distance was kept 25 cm in all the treatments. Sowing date was 19th December 2009 and plants harvested at 25th May 2010. Eventually, seed yield and indices of land equivalent ratio, relative crowding coefficient, aggressivity, competitive ratio, actual yield loss, intercropping advantage and barley equivalent yield were computed. Analysis of variance was performed using SAS Software (Ver. 9.1.3) and treatment mean differences were separated by the least significant difference (LSD) test at the 0.05 probability level. The results showed that the highest grain yield and wheat equivalent yield was obtained from sole cropping of wheat. In the intercropping of two rows of wheat with one row of chickpea and one row of wheat with two rows of chickpea land equivalent ratio was 0.87 and 0.71, respectively, that was less than sole cropping of wheat and chickpea. This means that intercropping requires 13% to 29% more land than the sole crop to produce equal yieldswhich indicating greater land-use efficiency of sole crops than intercrops. relative crowding coefficient of wheat in two rows of wheat with one row of chickpea and one row of wheat with two rows of chickpea was 1.93 and 1.73 and of chickpea was 0.15 and 0.17, respectively. The Aggressivity parameter indicated a tendency for wheat to dominate chickpea in both intercropping. Competitive Ratio in two rows of wheat with one row of chickpea was greater than one row of wheat with two rows of chickpea. Actual yield loss and intercropping advantage in wheat was positive and in chickpea was negative. Intercropping of wheat and chickpea decreased actual yield loss and intercropping advantage. The present study concludes that intercropping of wheat with chickpea in different planting patterns affected seed yield, competition between the two species and economics of the planting patterns as compared to solitary cropping of the same species. Results of this study illustrated that intercropping of wheat and chickpea was not suitable system. Intercropping indices such as Land Equivalent Ratio, Aggressivity, Competitive Ratio and Intercropping Advantage indicated that wheat crop was the dominant species in two intercropping treatments.

Intercropping is one of the effective agroecological systems which presence of two or more crops in this system will increase total yield due to improving some resource use efficiencies such as nutrient and light (Aynehband et al., 2010). In this regard, it has been found that-in corn-mung bean intercropping system the highest forage yield was belonged to 75% corn and 25% mung bean density ratio (Aynehband & Behroz, 2011). Hence, the aim of this study was to evaluate the competitive ability of sesame and mung bean crops in intercropping system and its effects on grain yield of these crops in Ahvaz. In this research, a field experiment was conducted for one year (2012) at the experimental farm of Collage of Agriculture, Shahid Chamran University, Ahvaz, Iran. Experimental design was split-plot based on RCB with three replications. Main plot was included two planting patterns with 50 and 75 cm inter-rows and sub-plots were included five plant density ratios with 100% sesame or mung bean and, 25% - 75%, 50% - 50%, 75% - 25% of each crop. Finally, grain and biological yield of both crop in monocropping and double cropping were calculated and also some competitive indices such as LER: Land equivalent ratio, AYL: Actual yield loss, A: Aggressivity, K: Relative crowding coefficient, RCI: Relative competition intensity, CR: Competitive ratio and ACI: Absolute competition intensity were computed. Our result showed that both 50 and 75 cm inter-rows in 50+50% density ratios had the highest intercrop grain yield, respectively (2.05 and 2 t.ha-1). In the most treatments, sesame had the higher grain yield than Mung bean. Increasing plant density had a positive effect on yield improving of both crops and increasing of inter-row had more positive effect on grain yield than biological yield. The harvest index (HI) was improved by increasing of inter-row due to increase in grain yield and decrease in biological yield. The LER index was higher than one in all intercropping treatments which mirror the priority of intercropping systems compared to mono-cropping systems. In both inter-rows and in 50% and 75% sesame density, LER of sesame was higher than LER of mung bean. The highest LER (1.34) belonged to 50–50% density ratio of each crop and changing in inter-row had not effect on LER. In addition, reduction in sesame density ratio (less than 25%) converts this crop to lower aggressive crop. When density ratio of mung bean was more than 75%, this crop had a suitable aggressive situation in canopy. At the same planting density (e.g. 50%+50%), sesame will be more aggressive crop and also, have higher use of inputs than mung bean. Without change in density ratio, increase in inter-rows, increased the aggressively of sesame (from 0.15 to 0.17), while this situation decreased the aggressively of mung bean (from –0.15 to –0.17). It is found that, ignoring the density ratios, wider inter-row caused increase in sesame aggressively (from 0.15 to 0.17), but, this situation had opposite effect on mung bean. It seems that some of these different reactions between both crops was due to differences in plant height (sesame was taller than mung bean) and the placement of pods in crop stand (sesame pods mostly located on the top of stand, but mung bean pods are in the middle of stand). These anatomic differences caused that just when mung bean density was more than 75%, this crop became more aggressive than sesame. It is concluded that sesame had higher competition ability than mung bean, so this crop was dominant crop in intercropping system. Sesame also had higher relative crowding coefficient. This advantage caused to this fact that sesame had a decisive role to shape the intercropping canopy arrangement, but mung bean had a lower change in actual yield loss than sesame in intercropping system. In addition, 50% - 50% density ratio was the optimum intercropping density due to the highest grain yield and also, 75 cm inter-row was the best cropping pattern due to optimum competition ability. It is also found that the grain yield is not the only appropriate parameter in intercropping system; therefore the other competition indices for this system should also be considered.

In many parts of the world, there is not enough precise information about suitable land for cultivation. On the other hand, variability of weather, soil and topography result in different agro-ecological conditions which may be suitable or unsuitable for some crops (Ghaffari et al., 2012). Land evaluation is one of the applied methods to achieve sustainable agriculture.Agro-ecological zoning is one of the land evaluating method that can be used to find better lands and improve the planning and management of land resources. This research was performed to perform agro-ecological zoning across Qazvin for cultivation of wheat. Providing a comprehensive database of land resources properties for planning and organizing of optimal land use, land suitability evaluation in each of the Agro-ecological zones was aimed as well by using parametric method (square root), calculation of wheat potential yield and land production potential in each of the agro-ecological zones. Finally in order to extract the zoning maps of each soil profile a database in the GIS environment was created. Study area: The present study was conducted across Qazvin which is located in 36° 00' 27" and 36° 11' 6" N latitude and between 50° 16' 58" and 50° 20' 16" E longitude. The study area is 16618 hectares. Isohyet map: In order to prepare the Isohyet map, since there was a few number of meteorological stations in the study area isohyet map was supplied by the Directorate General of Qazvin weather. IDW was used as interpolation. To obtain isothermal map, the regression equation was used between annual mean temperature and height temperature.. Length of growth period map: To obtain length of growth period map, the, potential evapotranspiration during growth period was calculated by Cropwat software across for selected weather stations (Nirugah, Bagh Kousar, Qazvin and Boyin Zahra). After Growth period maps were obtained based on stations, isothermal and isohyet lines. The soil map: For soil mapping, aerial images 1/40000 area and the IRS images as auxiliary data were used in field studies. Morphological properties of 61 soil samples were measured. then soil families were determined and finally the soil map was prepared. Land use map: Landsat 7 ETM+ and IRS satellite images in 2011 were used to prepare a land use map. Agro-ecological zoning map: Agro-ecological zoning map of the study area was obtained by combination of agro-climatic data (Isohyet map, Isothermal map, Length of growing period map), agro-edephic zoning (Soil Map, Slope Map, Land use map) and using the Union function in GIS environment. Land suitability evaluation: In order to evaluate the Land suitability in Agro-ecological zoning, conformity of the land characteristics in each defined zone with wheat growing requirements was done and the final class of land was measured. Potential yield: To estimate the Potential yield in the region, FAO model (Sys et al., 1991), was used. After overlapping desired maps in the GIS, the study area was defined and separated into 43 Agro-ecological zones. Land suitability evaluation Based on square root method, 34.14%, 43.16%, 14.94%, 4.03% and 3.72% of land were located in the classes including highly suitable land (S1), moderately suitable (S2), marginally suitable (S3), unsuitable (N) and unstudied (NS), respectively. Potential yield of wheat was obtained 6666 kg.ha-1 by using the FAO method. The main aim of this study was agro-ecological zoning of Qazvin for agricultural planning. By overlay agroclimatic and agro-edaphic zoning maps, 43 agro-ecological maps were obtained. Land suitability and potential land production evaluation were performed in each zone for wheat based on parametric method (square root). The results showed that climatic properties did not create significant limitations for wheat cultivation. Limitations related to soil properties results showed that the central part of the study area was the most suitable zone. In addition, soil depth and gravel percentage in the northern part beside salinity, alkalinity, lack of organic material and gypsum are the major limiting factors in the southern part of the area. Our results indicated that agro-ecological zoning is an essential tool for agricultural planning. In this approach, key and important components, as a similar set, characterized potential agricultural capacity and its limitations for decision makers and planners.

Land use suitability is the ability of a given type of land to support a defined use. The suitable areas for agricultural use are determined by evaluating the environmental components and understanding of local biophysical restraints. The topographic characteristics, climatic conditions and the soil quality of an area are the most important determinant parameters of land suitability evaluation (Almashkreki et al., 2011). Bhagat et al. (2009) analyzed land suitability for cereal production in Himachal Pradesh (India). In this study different parameters including climatic variables (precipitation and temperature), topographic (elevation), soil type and land cover/land use have been used in order to evaluate land suitability for cereals food-grain crops. The possibility of further expansion of cultivation area under each cereal crop was also determined. Golestan province is one of the most important region for crop production in Iran. In this study, geographical information system (GIS) and multi-criteria evaluation (MCE) were applied to evaluate the feasibility of agricultural lands in Aq-Qalla township for annual alfalfa (Medicago scutellata L. Mill.) cultivation. This research was conducted in northern part of Iran, Aq-Qalla township in Golestan province. The climate of this region is under the influence of Alborz Mountains, Caspian Sea, the southern wildernesses of Turkmenistan and forests. The suitability of current agricultural lands in Aq-Qalla township for annual alfalfa cultivation, were evaluated by matching the environmental requirements of crop and the land characteristics. For this purpose, required data and information of the study area were collected during 2013, and thematic maps were provided. Climatic data were collected from 43 weather stations located in Golestan province. The digital elevation model (DEM) dataset with a 40×40 m resolution and township boundary of the study area were obtained from Natural Resources Organization of Golestan province. The soil nutrient data were collected from 300 sampling sites distributed in Aq-Qala township, including EC, pH, Texture, N, P, K, Ca, Fe, Zn and Organic matter. Kriging and IDW methods were applied for interpolation of environmental variables. The digital environmental layers overlaid and integrated in GIS in respect to Analytical Hierarchy Process (AHP) weights. The weight of factors for feasibility were obtained from local experts, through a pairwise comparison of statistical analysis in Expert Choice software (ver. 2000). Zoning of lands carried out in four classes including: highly suitable (S1), suitable (S2), semi-suitable (S3) and non-suitable (NS). This system was based on matching between land qualities/characteristics and crop requirements. Highly suitable, suitable and semi-suitable lands were expected to have a crop yield of 80-100%, 60-80% and 40-60% of the yield under optimal conditions with practicable and economic inputs, respectively. Non-suitable lands were assumed to have severe limitations which could rarely or never be overcome by economic use of inputs or management practices (Ghaffari et al., 2000). Results of AHP questionnaires analysis showed that among the factors affecting land suitability, climate (0.559) and topography (0.113) criteria had the highest and least weight, respectively. In this AHP model inconsistency ratio is about 0.002. This indicates that the comparisons of criteria were perfectly consistent, and the relative weights were suitable for use in the land suitability analysis in Aq-Qala. The results showed that 23.1% and 47.2% of these areas were high suitable and suitable for alfalfa cropping, respectively. These zones had enough precipitation, suitable topography and high fertility. The semi-suitable and non- suitable regions (about 30% of area) were located in the northwest, east and south of Aq-Qalla township. In these zones, the environmental requirements of annual alfalfa were not fitted to ecological variables of agricultural land. The results showed that the topography and climatic characteristics (temperature and precipitation) of this region were suitable for annual alfalfa growth. In this study, the limiting factors were: high EC (about 30 dS.m-1), deficiency of organic matter, K and Ca. Therefore, analyzing the soil quality is essential for understanding the environmental degradation processes in the region. Proper land management practices, leaching, drainage, land preparation, crop rotation, specific irrigation methods and using resistant crop are helpful methods to increase crop yield in this area.