عبدالمحمد محنت کش

In order to improve the quantity and quality of medicinal plants, the use of natural substances such as amino acids have increased in recent years, which provide little information on their individual effects, as well as interaction with other fertilizer sources.

To investigate effect of different fertilizers and the foliar application of L-phenylalanine on nutritional elements of hyssop [Hyssopus officinalis L. subsp. angustifolius (Bieb.)], an experiment was done in a randomized complete block design with three replications during two consecutive years of 2016 and 2017 in a field experiment at the experimental field, Shahrekord. The investigated factors were fertilizer treatments including chemical fertilizer (NPK), organic fertilizers (animal and vermicompost) and a bio-fertilizer, mycorrhizal fungus (including Glomus genus) in the main plots and L-phenylalanine (at three levels: 0, 500, and 1000 mg/L) in sub plots.

Results indicated that the application of different fertilizers along L-phenylalanine at two studied concentrations (500 and 1000 mg/L) led to significant increase in the concentration of most nutrient elements including nitrogen (N), phosphorus (P), potassium (K) and micro elemts [Iron (Fe), zinc (Zn), manganese (Mn) and copper (Cu)] in the leaf were compared to the control. Among them, the application of fungal and vermicompost fertilizers, L-phenylalanine × fungal fertilization, and phenylalanine × vermicompost had highest effects on the increase of these traits. In conclusion, the results indicated that the application of organic fertilizers along with L-phenylalanine spraying at 1000 mg/L level has a beneficial role in the improvement of nutritional elements and dry matter yield of H. officinalis L. subsp. angustifolius (Bieb.).

Today, a considerable amount of Zagros forests is faced with the phenomenon of oak decline. Environmental stresses have caused the weakness of the trees, imbalance in food and water absorption, and eventually the deterioration of trees. Site factors play an important role in the resistance of trees to biotic and abiotic stresses. This research was conducted to evaluate the reaction of health and non-health Brant`s oak (Quercus brantii Lindl.) trees to nutrients absorption in different aspects and elevations in the Helen forest of Chaharmahal & Bakhtiari province. Three transects were considered in two main aspects (North and South) of the study area. On each transect, three plots (with an area of 1000 m2) were designed in three elevation levels (800-1500, 1800-2000, and above 2000m a.s.l) randomly. Leaves of five health and non-health trees were gathered to measure the nutrient elements. This research was conducted as a factorial experiment in randomized complete block design and the mean values of variables were compared using Duncan test. The results showed that the effect of geographical aspects was significant on N and Ca uptake. Also, the difference in the absorption of essential nutrients in leaves of health and non-health oak trees were significant. The absorption of Fe, Mn, Zn and Cu in the leaves of the trees in the northern aspects was higher than the southern aspects. Health trees also absorbed more of these elements compared to non-health trees.

Understanding the capability of soils and land use limitations is a key factor in allocating the lands to the most appropriate use and also improving the growth conditions of plants in those lands. This research aimed to study the soils and recognize their limitations in cypress forest of Mobarakeh Steel Complex in order to prevent deterioration and decline of the trees. In the first step, plots were selected in the forest and a soil profiles was drilled in each plot. Soil samples were collected from the profiles. Also, soil and leaf samples were collected from the canopy of the healthy and unhealthy trees, separately. The results indicated that the soils have variety of limitations, including high gravel content (more than 50%), lack of organic matter (less than 0.5%) and nutrients, high calcium carbonate and pH coupled with soil compaction. There was a significant difference in the uptake of iron, manganese, zinc, copper, chlorine and sodium from the soil between healthy and unhealthy cypress trees. To improve the soil conditions in order to prevent the decline of cultivated trees, soil fertility and plant nutrition management program should be considered in the study area. Also, the use of organic fertilizers is recommended.

Agriculture is the main source of national income and food for all developing countries, but the main problem facing many managers and farmers is when and where they can cultivate. Horticulture is one of the agricultural activities, the maintenance and development of which requires sustainable economic, social, cultural, ecological and institutional infrastructure. It also requires the participation and comprehensive planning at a local to national scale. The first step in achieving sustainable development, especially in the agricultural activities and the subsequent orchard farming, is to recognize the ecological potential and the land capability in each region. In this regard, the knowledge of land evaluation plays a decisive role in determining the land suitability or evaluating the ecological potential of each region for the intended uses, including the development of gardens. Numerous studies have been conducted to evaluate the land suitability for crop cultivation, including horticultural and agricultural products. Since orchards require more investment and time than crop farming, the importance of basic studies and research for the orchards will be much greater than that the crop; because if an unsuitable land is used for orchard establishment, after it, for several years, more important than wasting the money paid is the loss of time, which is not compensable. But, only one crop season is lost for crop farming.

In Chaharmahal and Bakhtiari province, the development of the orchard is very important for the people as well as the relevant officials. Therefore, the selection of the suitable location for the orchard farming is a very important issue. For this purpose, this research was conducted with the aim of achieving the best and most sustainable use of land in Saman County, which has the first rank in the province with about 13,000 hectares of gardens. Due to the climate of this area, the orchard products for cold regions, such as apricots, almonds, apples, peaches and grapes was selected and the possibility of sustainable development of these orchards was studied using the land suitability evaluation based on the FAO standard method. For this purpose, the land characteristics (LC) related to the intended crops, which mostly included the climatic characteristics and the characteristics of the soil and the land, were first collected and classified. Then, the requirements of the these crops or products were determined and at the end, the characteristics or qualities collected were compared and evaluated with the requirement tables of the selected crops. Each land feature was then given a class or numerical value, which combined two important indicators, including the climate index and the land index. In this study, the process of land suitability assessment was performed with a size approach and numerical (parametric) method and then land fit maps of the desired products were prepared.

Table 1 shows the class and subclass of land suitability for apricots. As can be seen, 42530.7 hectares or 86.87% of the whole land are in the suitable order. The subclasses include climatic (c) and soil physical (s) limitations. The most important soil physical limiting factors are soil depth, lime percentage and gravel percentage. Also, the land with an area of ​​6429.7 hectares or 13.13% of the land is in the not-suitable order, which due to the limitations of the gravel percentage and soil depth is in the permanently unsuitable class or N2s class.The results of land suitability assessment for peaches, apples, grapes, and almonds are shown in tables 2 and 3. The findings showed that according to climatic and soil characteristics, different regions had different degrees of proportionality or ecological potential, so that the study area had S3 and N classes in 86.87% and 13.33% of the area, respectively.For grapes and almonds, the land suitability classes were S2, S3 and N classes, in 21.90%, 65.57% and 90% of the area, respectively (Table 3). The most important limitations were the soil depth, gravel, slope, and climatic constraints. According to such findings, planners and decision makers can plan and choose the best options to take into account both the product profitability and sustainability. Of course, in addition to ecological requirements, it is recommended to study other requirements such as social characteristics, economic conditions, cultural acceptance, and the current situation of orchards to complete the process of sustainable development for horticulture.
Table 1. Land Suitability Classification for Apricots

Introduction:

 In order to land classification for agricultural and natural resources, the most important criterion and factor is the production or yield of the lands. The best way to evaluate a method is to interact between the yield and potential of the product with the land specification involved in the production. One of the new methods in the land evaluation for different uses is the modeling or simulation of the intended use. Artificial neural networks are one of the new tools that are used today to simulate yield and determine the effective factors in the production of agricultural crops. New land evaluation methods include different modeling techniques, which these new methods, including simulations, are used in land valuation methods to test the ability of models for determining the relationship mentioned. An artificial neural network is one of the techniques that can do nonlinear analysis. It is important to recognize the most important input parameters to the predictive models of olive yield, which are also considered to be effective variables in production. Through the process of sensitivity analysis, valuable information about the sensitivity of the model to its input variables can be provided to the designer and model architect. In north of Iran, in the southern areas of Gilan Province, the most important olive gardens of the country are located in the southern part of the country. Different soil and water, topographical and climatic factors affect the yield of olive orchards.

Materials and Methods:

 Climatic data, soil and water characteristics, topographic characteristics and leaf nutrition elements as input variables and olive yield were used as output models. Twenty-eight factors were selected as the most important factors or variables affecting the yield of olive orchards. These input variables included soil properties: EC, (TNV), organic carbon percentage, available phosphorus, available potassium, clay percentage and silt percentage; irrigation water characteristics including: EC and content of irrigation water; topographic characteristics including: altitude and the slope; the concentration of nutrients in leaves included: nitrogen, phosphorus, potassium, iron and zinc; climatic factors including: sunny hours, evaporation rate, average temperature and olive yield were considered as output of artificial neural network model.

Results and Discussion:

 Using the MATLAB software by artificial neural network, the best structure of this network was obtained for the component of the yield of olive. The trained structure had 28 input nodes in 5 groups and one output node. The number of hidden nodes, 38 nodes and the most appropriate number of repetitive learning based on the test and error, 20 were determined for olive product yield. After determining the best structure of the neural network with a R-test of 80%, using Hill's sensitivity analysis, the model's response to each of the input variables was studied and the most important factors influencing the yield of olive oil were obtained. Based on the results of sensitivity analysis, the most important parameters affecting the yield of olive are content of leaf nitrogen, soil phosphorus, winter evaporation, summer evaporation, average autumn temperature, summer sunshine, leaf potassium, salinity, salinity, and slope, respectively. In general, this study showed that the amount of nitrogen and phosphorous is the most important factor for the production of olives, and then variables that are related to the amount of water in the soil, (summer evaporation, average autumn temperature, summer sunshine), were identified as important. The concentration of potassium, iron and zinc in the leaf as a nutrient element and water and soil salinity from stressors for plants and slope are important topographical factors that affected the amount of soil depth and soil water content as the most important factors in olive crop production.

Conclusion:

 In brief, the role of micro and macro nutrients and the factors affecting the maintenance of water in the soil and providing moisture for the plant. In addition to nutrients, gardeners should consider soil and water salinity, which is a stressor for plants, as well as slope, which is important topography factor that effective on soil depth and water available and nutrients for plants as the most important factors in olive production.

Soils play an important role in environmental issues and sustainable management and development programs. Then there is a growing need for the preparation of soil maps with high reliability and accuracy. Taking into account the decreasing the chance of conducting new soil surveys due to the limitation of resources, legacy soil data have been receiving a great deal of attention. These data, which carry important information about the state and properties of soil over time and place, can create a perspective for better management of different resources. Considering these issues and also the dependence of better soil management on this legacy information and the importance of using it in environmental management, serious efforts should be made to maintain and reuse these legacy soil data. Then performing some preprocesses in order to maintain and renew this information is obviously necessary, in which rescue and renewal of soil legacy inventories are the most important ones. These preprocess have to be performed before any reusing of them. In spite of global efforts in this regard, no important effort has been made to renew this valuable information so far. However, it has a good history of soil science and is full of legacy soil information inherited from pioneer soil scientists. Therefore, this study aims at rescue, renewal and evaluate available legacy soil surveys as prerequisite processes for reusing them in the framework of digital mapping.

The 10480 km2 study area is located in the border of Isfahan and Chaharmahal-va-Bakhtiari provinces. Due to the existence of Zayandehrud river in this region, it has been surveyed a lot so far. However, because of the lack of access to all these studies, three legacy soil studies covering the whole study area were selected and examined. After recording of the information of these studies in computer and georeferencing the maps, the boundaries of soil map units were digitized. The quality of the maps was afterward evaluated according to the Cornell adequacy criteria. The spatial accuracy of soil map units was then checked and their probable dislocation was finally corrected using available axillary maps and information. Also, the weighted Tau index and overall accuracy were calculated to quantitatively evaluate the quality of the maps.

The information of selected legacy soil maps and profile was successfully recorded in computer in order to keep them from destruction, and a table filled with the information of their soil profiles. The results indicate that the georeferencing of soil maps was done with relatively good quality. The results of quality and efficiency of soil map units’ assessment showed that the map scale is larger than the scale provided on the maps, however, the map legends provide enough information to the users of the map. The investigation of the boundary displacement of the map units showed that the maps had a high-level of spatial accuracy. The results of statistical evaluation of soil map units’ accuracy showed that in all studies as well as their total, the weighted overall accuracy and Tau index of the map at all levels of classification is more than 70% and 50%, respectively, which indicates a good accuracy of the maps.

Despite the public belief about the quality of legacy soil maps, the results of this study indicate well that the studied legacy soil maps have a good quality in terms of their general characteristics. It is also proved that the legacy information and maps can be used with a good degree of confidence in the digital mapping process. Thus, the cost of new soil studies can be saved using this legacy information.

Abandonment of arable lands is the starting point of vegetation succession. The trajectory and speed of succession can be different according to the time of abandonment. The aim of this study is to assess the effect of abandonment periods on species richness, diversity and functional groups in shrublands and grasslands of Shirmard rangelands in Chaharmahal va Bakhtiri, Iran. A total of 96 abondoned arable lands were selected and grouped according to the abandonment periods (less than 5, 5-15, 15-25 and more than 25 years). 24 patches around abondoned arable lands were chosen as control sites. Cover of all species was estimated in 4 m2 plot (10 plots in each patches). Data were analyzed using one-way ANOVA. The results of this study indicated that the lowest values of Shannon-Wiener and Margalef indices in both vegetation types belonged to area with less than 5 years abondonment. The greatest Shannon-Wiener and Margalef indices in shrubland (1.85 and 3.83 respectively) were found in 15-25 years but in grassland (1.93 and 4.39 respectively) it happened in 5-15 years. In both vegetation types we found that the average canopy covers of functional groups such as annual plants, annual grasses, Poaceae and Cruciferae families significantly decreased as the time of abandonment incraesed. In contrast, a significant increase was found for perennial plants, shrubs, trees and Papilionaceae family. Therefore, this study showed that vegetation indices improved during natural succession of vegetation in abandoned arable lands but the reversibility of vegetation indices varied according to the kind of index and vegetation type.

  Climate has a key role in plant growth Therefore, it is clear that climate change will directly effect on sowing and harvesting of cultivate crops (FAO, 2013). Many scientists used APSIM to simulate the phenology and yield of canola. To understand the impact of climate change it is necessary to project the future climate based on different emission scenarios. These results must be combined with simulation models to predict crop yield and phenological stages. Assessment the impact of climate change on phenology and yield of agricultural crops in different regions show different results. The aim of this study was to investigate the impact of climate change on phenological stages and yield of Canola by APSIM-canola modules. Chaharmahl va bakhtiari in the southwestern of Iran is one of the main agricultural production zones is considered as the highest province of Iran. The soil physical properties were obtained from Agricultural Research center of Farokhshahr. Required meteorological data including precipitation, solar radiation, and daily maximum and minimum temperature were collected from 6 synoptic weather station in the study area. Data was used after quality control process. The meteorological data convert to compatible text format with APSIM.
Biometric data and phenology:Canola has several varieties. Okapi is one of the winter varieties which was recommended for the study area. Agrometeorological data, including phenology and biometry from 2001 to 2010 were gathered and summarized. Includes the canola yield and phenological stages containing planting, germination, emergence, the first true leaf, rosette, stop the growth of winter, budding, stem elongation, flowering, pod, ripening and harvesting. Farm management information such as the amount of fertilizer, irrigation and frost and pest were also recorded. A total of 1700 reported of phenological stages was used over the 10 years of crop evaluation.
Future climate data:Climate change data were downloaded from one of The World Climate Research Programme (WCRP) project so called Coordinated Regional Climate Downscaling Experiment (CORDEX). We used CORDEX MENA data in which the simulations were performed on a rotated grid with the pole at 180°W longitude and 90°N latitude.The domain covers roughly the region from about 27°W to 76°E longitude and 7°S to 45°N latitude. Simulations were carried out using two different resolutions: 0.44° (approx. 50 km) and 0.22° (approx. 25 km).
Model Description:Agricultural Production Systems Simulator (APSIM) known as a highly advanced simulator agricultural systems in the world. There are 43 selectable varieties of spring and winter canola on APSIM v 7.7, but none of them cultivated in the study area. Germination, emergence, end of juvenile phase, flower initiation, flowering, grain filling and maturating are seven simulation of the phenological stages. For simulation of each phonological stage, elapsed time from sowing to the first day of reaching at each stage was counted. Water stress, nutrition, photoperiod, and vernalization have influence on the phenological stages (Zhang et al., 2014).
Highest RMSE was calculated in the simulation of days after sowing to maturity (DTM) stage with 5 days and bias error was -0.7 days. Greatest bias error occurred in simulation of days after sowing to emergence (DTE). The correlation coefficient of the DTG and DTE was not statistically significant and this indicator in the other stages (P-Value = 0.01) is significant. The strongest correlation was obtained between observed and simulation of days after sowing to flower initiation (DTFI) and days after sowing to flowering (DTFL).
Because of the crop management, soil and water conditions, simulation was done in three cases of poor, middle and high management. The RMSE in estimating of yield was 329.8 kg/ha which included 7.2% of canola average yield on study area. The rate of Bias error was18.2 kg and correlation between actual and simulated data were 0.96. We consider every year Farm management, nutrient and irrigation in the simulation and results showed that APSIM has reliability skill in simulation
Based on scenario RCP8.5, considering : DTE, DTFI, DTFL, DTEGF and DTM stages will be reduce between 1 to 13 days the maximum reduction can be seen in the flowering and grain filling phases. However DTEJ will be raise and longer10 days.
The results of data from RCP4.5 showed that DTFL and DTEGF stages, will decrease from 2 to 3 days, the greatest rate of decline was observed in the flowering period. DTEJ, DTFI and DTM stages will rise. DTFI and DTM stages will be increased up to 3 day. And similar to RCP8.5, DTEJ will be raised up to 9 days. It is expected that with RCP8.5 scenario the average of yield on the optimal nutrition and management will be increased around 18%. Whereas in poor management conditions the yield will be increased 18 and 13.6 percent respectively.
RCP 4.5 in optimal nutrition and management will be inceased13.4% and in intermediate and poor management will raise around 14.3 and 13.6 percent. This suggests that without water limit, global warming will have a positive impact on canola yield in this area. The study showed, APSIM could simulate the yield of canola with RMSE 320 kg/ha. Results showed that with RCP8.5, phenological stages including of DTE, DTFL and DTEGF and DTM will be shorten. with RCP4.5 phenological stages including of DTFL and DTEGF will be shorten The higher rate of decline was observed by RCP 8.5 scenario. DTEJ on RCP 8.5 and RCP 4.5 will be respectively longer 10 days and 9 days. It is expected that ,canola yield will be risen with both studied scenarios in optimum nutrition is about18%, in average more than 13 percent and on low nutrient up to 18 percent.
Canola-Okapi yield increasing outlook in rejoin of Iran show a good potential on planting of this variety and this product will be develop on 2030 horizon

Oak decline is a complex phenomenon affecting vast areas of Zagros forests. Dust is the most important factors in the decline of Zagros forest. In order to assess the impacts of dust on oak decline, six dust traps were installed in Helen protected area at the beginning of spring 2016. Dust samples were collected using the traps surface in autumn. The weight of dust samples and the amount of heavy metals were measured in the laboratory. Three transects (replicates) with fixed distances were designed in each of northern and southern directions. In each transect, three circular plots (with an area of 1000 m2) were laid out in three altitudinal ranges (1500-1800, 1800-2000, and more than 2000 meter a.s.l.). In each plot, leaf samples of five trees were collected from healthy and unhealthy trees, and the amounts of heavy elements including lead, cadmium, nickel, arsenic and mercury were measured. The results showed that cadmium and lead in leaves of healthy and unhealthy trees had a significant difference and the amount of these elements in the leaves of healthy tree was more than unhealthy trees. Higher amounts of heavy metals were absorbed by oak trees located in the southern aspect compared with those in the northern one. Moreover, the amounts of intercepted cadmium and lead had significant differences. It seems that the stress caused by the absorption of these heavy elements in the leaves of trees is one of the most important factors for oak trees decline.

There is a concern with assessment of land performance when used for specific purposes. Land evaluation analysis is considered as an interface between land resources and land use planning and management. However, the conventional soil surveys are usually not useful for providing quantitative information about the spatial distribution of soil properties that are used in many environmental studies. Development of the computers and technology lead to digital and quantitative approaches have been developed. These new techniques rely on finding the relationships between soil and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. Different types of the machine learning approaches have been applied for digital soil mapping of soil classes, such as the logistic and multinomial logistic regressions, neural networks and classification trees. To our knowledge, most of the previous studiesapplied land suitability evaluation based on the conventional approach. Therefore, the main objective of this study was to assess the performance of digital mapping approaches for the qualitative land suitability evaluation in the Shahrekord plain of Chaharmahal-Va- Bakhtiari province.
An area in the Shahrekord plain of Chaharmahal-Va-Bakhtiari Province, Iran, across 32º13′ and 32º 23′N, and 50º 47′ and 51º 00′E was chosen. The soils in the study area have been formed on Quaternary shale and foliated clayey limestone deposits. Irrigated crops such as wheat, potato, maize and alfalfa are the main land uses in the area. According to the semi-detailed soil survey, 120 pedons with approximate distance of 750 m were excavated and soil samples were taken from different soil horizons. Soil physicochemical properties were determined. The average of soil properties was determined by considering the depth weighted coefficient up to 100 and 150 centimeters for annual and perennial crops, respectively. Qualitative land suitability evaluation for main crops of the area including wheat, maize, alfalfa and potato was determined by matching the site conditions (climatic, hydrology, vegetation and soil properties) with studied crop requirement tables presented by Givi (5). Land suitability classes were determined using parametric method. Land suitability classes reflect degree of suitability as S1 (suitable), S2 (moderately suitable), S3 (marginally suitable) and N (unsuitable). Different machine learning techniques, namely artificial neural networks (ANNs), boosted regression tree (BRT), random forest (RF) and multinomial logistic regression (MLR) were used to test the predictive power for mapping the land suitability evaluation. Terrain attributes, normalized difference vegetation index (NDVI), clay index, carbonate index, perpendicular vegetation index (PVI), geology map, existing soil map (1:50000 scale) and geomorphology map were used as auxiliary information. Finally, all of the environmental covariates were projected onto the same reference system (WGS 84 UTM 39 N) and resampled to 50 * 50 m since the soil samples were collected with approximate distance of 750 m (1:50,000 scale). According to the suggested resolutions for digital soil maps, the pixel size 50 *50 m fits to a 1:50,000 cartographic scale. Training the models was done with 80% of the data (i.e., 96 pedons) and their validation was tested by the remaining 20% of the dataset (i.e., 24 pedons) that were split randomly. The accuracy of the predicted soil classes was determined using error matrices and overall accuracy.
The results showed that climatic conditions are suitable (S1) for wheat and potato whereas the most important limiting factors for maize and alfalfa were the average of minimum temperature and average temperature, respectively. Results demonstratedthat among the studied models, random forest showed the highest performance to predict the land suitability classes and subclasses. However, different models had the same ability for prediction. In addition, the overall accuracy decreased from class to subclass for all of the crops. The terrain attributes and remote sensing indices (normalized difference vegetation index and perpendicular vegetation index) were the most important auxiliary information to predict the land suitability classes and subclasses.
Results suggest that the DSM approaches have enough accuracy for prediction of the land suitability classes that affecting land use management. Although digital mapping approaches increase our knowledgeabout the variation of soil properties, integrating the management of the sparse lands with different owners should be considered as the first step for optimum soil and land use management.

Introduction One of the objectives of land evaluation method is determining the land suitability degree and class in case of making any changes, including causing elimination or limitation. Thus, as an example, if it could be possible to predict changes in soil salinity for the future, any changes in land suitability class can be investigated based on the predicted variations over time.The most important crops in Neyriz area are wheat and barley. Unfortunately, over the past two decades, improper agricultural management caused reduction and salinization of irrigation water in this region. To this end, the present study was performed to investigate the possibility of changes in the class or degree of land suitability in case of variations in soil electrical conductivity due to irrigation with saline water in Neyriz, for the next 10 years.
Materials and Methods In three soil map units in three regions consisting of Deh-Fazel, Tal-Mahtabi and Nasir Abad, wheat and barley fields were selected and representative pedons were excavated, described and classified. Soil and water samples were obtained and necessary analyses and soil humidity and salinity, hydraulic conductivity and bulk density and water electrical conductivity were determined. Crop yields were evaluated by 1×1 quadrate, soil surface layer hydraulic conductivity was carried out by guelph permeameter and the volume of irrigation water was measured according to pipe discharge in each farm. Soil retention curve was calculated for all soil layers using sand box and pressure plate. van Genuchten equation parameters were gained using RETC software. Afterward, solute transport modeling was done using the software Hydrus and its results were validated using four statistical parameters including Coefficient of determination (R2), Root Mean Square Error (RMSE), Model efficiency (EF) and Coefficient of Residual Mass (CRM) to investigate the possible variation in soil salinity during the next 10 years, the data of the studied period of the crop year between 1392 and 1393 was repeated for 10 years. Qualitative and quantitative land evaluation was performed by standards methods. Finally, the Hydrus results were compared with salinity maps of Neyriz area which were calculated and obtained in the previous research from Landsat images bands for the past 20 years.
Results and Discussion Based on the results, climate suitability class in Neyriz area was suitable (S1) for wheat and relatively suitable (S2) for barley. The limiting factor for barley was the average of maximum temperature in the coldest month for barley. The soil suitability class was suitable (S1) for both crops (wheat and barley) in all farms. Therefore, the land suitability in the studied farmlands was S1 for the wheat and S2 for the barley. Results also revealed that the values for potential production were 10723 and 8677.5 Kg(grain)ha-1 for wheat and barley and for critical production were 1167 and 1297.6 Kg(grain) ha-1 for wheat and barley, respectively in the farms. Amongst the farmlands, only a barley farm which was located in Tal-Mahtabi had the S1 quantitative suitability class and others had S2. The results also showed that if all other conditions like volume and the quality of the irrigation water, precipitation, temperature and evaporation remain constant over the next 10 years, land suitability class will not change but land suitability degree will decrease gradually over time. The validation of the Hydrus model, based on the RMSE values, revealed that the predicted soil salinity and the observed value were very similar and the model had good ability in estimating and modeling soil salinity in the studied area. Comparing the results of modeling and soil salinity maps over the last 20 years have confirmed this trend. Based on the satellite salinity maps, the soil salinity of the studied fields has increased slightly from 2 to 4 dSm-1 between the years 1374 and 1393. Hence it can be concluded that the prediction of Hydrus model about gradual rise in predicted soil salinity and land suitability degree during the next 10 years is acceptable.
Conclusion The present study showed that climate and land suitability class in Neyriz area was suitable and relatively suitable for wheat and barley, respectively. Solute transport modeling showed that land suitability degree will decrease gradually and soil quality will decline over time by assuming constant irrigation and precipitation condition over the next 10 years. Therefore, preventing the expansion of soil salinity and degrading agricultural lands require serious considerations of the authorities in the crisis Managements

Wheat (Triticum aestivum L.) as the most strategic crop for human nutrition is cultivated in many countries under rainfed conditions in semiarid regions. To be vital importance to predict rainfed wheat yield and determine the important factors which affect this crop. Modeling is one of the approaches to predict the response of land to land use. Artificial neural networks (ANN) are considered as one of the modeling approaches to yield prediction and determination of the most important parameters in crop productions. In rainfed wheat hilly land of central Zagros of Iran, there are various parameters that influence this crop production. Therefore, the objective of this study was to identify these important factors.
This study was conducted for two years and at two sites under rainfed conditions in Koohrang and Ardal districts in Chaharmahal and Bakhtiari provinces, central Zagros of Iran. At both sites, the study was made on farmer–operated winter wheat fields. At the Koohrang and Ardal sites, 102 and 100 sampling points were selected, respectively. 202 sampling points were chosen on the landscape covering summit, shoulder, backslope, footslope, and toeslope at two sites with varying climatic conditions. Four parameter groups including terrain attributes, soil physical and chemical properties, precipitation, and weed biomass, including 54 factors were used as the inputs, and wheat grain and biomass yield as the targets for ANN models. A feed-forward back-propagating ANN structure was used to develop yield prediction models. The data set was randomly shuffled; 60%, 20% and 20% of them were used for the learning network, testing and verification, respectively. After determination of the best structure of ANN model, crop yields were predicted by the ANN models. By the Hill sensitivity analysis method (Hill, 1998), response of each factor was studied and determined the most effective parameters on grain and biomass yield. This method calculates relative sensitivity coefficient by dividing the sensitivity coefficient of every variable when the variable is reduced 10% by the maximum sensitivity coefficient, therefore the maximum relative sensitivity coefficient is 1.
The descriptive statistics for various soil characteristics showed that, soil chemical and physical parameters can be classified into three orders. Sand, TN, Kava., Pava., SOM, CCE, and gravel showed high variability (CV>35); clay, silt, and CEC had moderate variability (3515); and SP and pH indicated low variability (CV

The aim of this study was to investigate the climate change impacts on some factors affecting rainfed wheat growth such as effective rainfall, planting date and length of growing season in four stations located in Chaharmahal and Bakhtiari province. Firstly, it is necessary to predict future (2046-2065) climatic conditions. For this purpose, the output of HADCM3 general circulation model was used under three scenarios of A1B, A2 and B1. The data were downscaled by LARS-WG model. After simulating the climatic parameters in mention period, the effective rainfall during the wheat growing season was calculated by Food and Agriculture Organization method. Also, the optimum planting date was defined according to the date of the first rain (at least 10 mm in case of continuing for next days). The wheat's growth stages were determined by Growing Degree Days method. The results indicated a rise in temperature for four stations. On average, it is expected that the annual temperature increase by 1.8°C compared with the baseline period (2010-1990). Total annual precipitation in Shahrekord, Koohrang and Borujen will decrease 2.2, 7.8 and 3.6 per cent respectively. About Lordegan it will increase by 2.7 per cent. Also, the results showed that in three stations of Shahrekord, Koohrang and Borujen, the amount of effective rainfall in November will increase compared to baseline, but in Lordegan it will reduce. So, in the first three stations, in most years, planting date was obtained earlier than baseline, but in Lordegan it was later than baseline. The Length of growing season will reduce in Shahrekord, Borujen and Lordegan stations, 12 days on average and in Koohrang about 13 days.

The accurate information about the spatial distribution of land suitability assessment are important elements for sustainable land management and diversity is a way for measuring soil variation. Beside, soil surveys are important sources of data that can be used to improve land suitability classifications. Unfortunately, comparing the variation of land suitability using diversity indices and different soil mapping approaches is rarely considered. Therefore, the main objective of this study was to investigate the viewpoint of different soil mapping approaches (conventional and digital soil mapping) for description the variation of suitability class and subclass for main irrigated crops (wheat, maize, alfalfa and potato) in Shahrekord plain of Chaharmahal-Va-Bakhtiari province.
The area under investigation has a size of approximately 10000 ha. 120 pedons with approximate distance of 750 m were excavated and described. Soil samples were taken and their physicochemical properties were determined. Soil map was prepared at family level. For the representative pedons, the average of soil properties was determined by considering the depth weighted coefficient up to 100 and 150 centimeters for annual and perennial crops, respectively. Based on FAO framework, suitability class and subclass for main irrigated crops were determined using parametric method. Also, Random Forest model was used to predict suitability class and subclass for all of the crops. Then, for each crop, the map units that have the highest frequency in land suitability conventional map were selected as indicator to calculate functional diversity indices. The selected map units were overlaid on digital maps and diversity indices were calculated. Then, the mean of Shannon’s diversity index for two approaches was statistically evaluated.
For all of the studied crops, significant difference was not observed for diversity between mean values of conventional and digital maps at class level. However, in the subclass level, a significant difference (95% confidence level) was obtained only for potato. For all of the studied crops, regardless the mapping approaches, diversity indices showed higher values in the subclass level than class level of suitability. This difference was significant at 0.001 probability level for alfalfa, maize and potato using two mapping approaches and for wheat in digital maps.
No significant difference was observed between two mapping approaches for all of the studied crops confirm that description the variation of suitability class and subclass less influenced by the land use type and mapping approaches. The results recommended that revision of the FAO criteria to include the spatial distribution of soil properties for sustainable land management.

Given the importance of wheat in human nutrition and its cultivation in large-area under rainfed in Iran, this study was aimed to evaluate the efficiency of artificial neural networks and linear multiple regression models to predict biomass and grain yields of wheat (cv. Sardari), in two-year study. In two stations (Koohrang and Ardal), 202 sampling points were selectedin the various hillslopes includes summit, shoulder, back slope, foot slope and toe slope. Atthe harvesting stage, the soil and plant samples were collected. Primary and secondary terrain attributes were extracted from digital elevation models, and meteorological data were used in two regions. Topography, 54 different soil characteristics, rainfall and management as the inputs as well as biomass and grain yields were considered as the outputs of both models. Artificial neural networks and multiple linear regression models, respectively, accounted for 84% and 15% of variations (R2) in grain yield prediction, and 76% and 6% in prediction of biomass yield. The root mean square error (RMSE) of the models also were equal to 0.033 and 0.092 to predict grain yield, and 0.037 and 0.102 to predict the biomass based on artificial neural network and multiple linear regression models, respectively. The results showed a better ability of artificial neural networks in comparison with multiple linear regression to estimate grain and biomass yields of wheat in the target areas.

Appropriate knowledge of the species ecological requirements will have an important role in the conservation and protection of the reforestation. Mobarakeh steel company created 1,500 hectares of artificial forest by non native tree species. Cupressus arizonica is one of this species. Tree species decline causing serious problems in this area. Plantation areas of this species were identified toinvestigate the causes of cypress dieback. A plot of 2000 m2 was considered in each area that planted by this species. In addition, quality and quantity characters of all trees in each plot such asdiameter, height and crown diameter and trees health were measured. The leaf samples offive healthy and unhealthy trees were collected separately for analytical measurements. The soil sampling and profiling was performed from the areas under healthy and unhealthy tree canopy in each plot. The results of this investigation showed that there are many limiting factors such as poor soil and water salinity as the main factors in reducing the absorption of micro and macro nutrients in unhealthy trees.

Mulberry is used for planting development. This tree is one of the important species that planted in the Mobarakeh Steel Complex. This tree dieback has been a main managerial problem in recent years in the company. Environmental stress is one of the most important factors that influencing on species dieback. Absorption of heavy metals as an environmental pollutants, nutrient absorption, plant pigment and proline can determine the impact of stress on the occurrence of this phenomenon. The 2000 m2 plot was built in each area that planted by this species. Leaves complex sample of 5 trees were collected of healthy and unhealthy trees to compare of elements concentration. The results showed that the uptake of heavy metals including lead, mercury, cadmium and nickel in the leaves of unhealthy trees was higher than healthy trees, but the amounts of these elements were not toxicity in unhealthy trees. Absorption of macro and micro nutrients such as calcium, potassium, nitrogen, manganese, magnesium, iron, copper and zinc in the leaves of healthy trees was more than unhealthy leaves, but the amount of sodium and chlorine in the leaves of unhealthy trees were rather than healthy trees.This condition was indicative of salinity stress in the habitat. Water sources also indicate this phenomenon. Lack of soil fertility also created many problems for power plants. Soil fertility stresses was extended dieback of trees.

Potato (Solanum tuberosum L.) is one of the most important crops that plays a major role in feeding the world. The growing demand for potato, as both a fresh and processed food, along with the increase in world population, mean that yield will have to be improved through some combination of germplasm enhancement, better crop protection and more efficient and productive management of irrigation and fertilization (Haase et al., 2007). Researches have proved potato is sensitive to drought stress at all stages of growth, especially at tuber formation stage due to reduction of leaf area and photosynthesis (Fabeiro et al., 2001; Ayas, 2013; Shock et al., 2013). Abiotic stress factors, such as drought, have severe, adverse effects on potato growth and yield. In particular, a regular water supply is necessary to achieve a high quality yield (Ierna and Mauromicale, 2006). In comparison with other species, potato is very sensitive to water stress because of its shallow root system (Ayas, 2013).
Water shortage during tuber differentiation can delay growth and reduce earliness, whereas during tuber growth and bulking can decrease tuber size and have a drastic effect on yield (Alva et al., 2012; Liu et al.; 2006; Ayas, 2013).
For processing potato, a careful N and water management is required to ensure regular growth, high dry matter content and marketable tubers (Shock et al., 1998; Zhang et al., 2006; Shahnazari et al., 2007).
So this research was done to evaluate effects of different levels of water deficit and nitrogen fertilizer on tuber yield, yield components and water use efficiency of potato crop in Chahar Mahal va Bakhtiari province, in Iran.
In order to study the effects of different levels of water deficit and nitrogen fertilizer on tuber yield and other agronomic traits of potato crop (Boren variety), a split plot experiment based on randomized complete block design, conducted at Chahar Mahal va Bakhtiari Research Center of Agriculture and Natural Resources, in 2013. The levels of water deficit were S1, S2 and S3 (100, 75 and 50% of the water requirement of potato crop after emergence by the end of the growing season, respectively), as the main plots and nitrogen fertilizer treatments were N1, N2, N3 and N4 (100, 66, 33 percent of plant nitrogen requirement and without nitrogen consumption, respectively) as sub plots.
In this experiment water deficit had decreasing effect on tubers dry matter percent but nitrogen changes had no distinct effect on this trait. By applying water deficit and decreased levels of nitrogen, the number of tubers per plant and the average tubers weight also fell. The greatest and the lowest number of tubers per plant were seen at S1 and S3 treatments (8.4 and 7.4 respectively). The maximum weight of tubers observed at full irrigation treatment (118 g) that had no significant difference with S2, but at treatment S3 (50% of the water requirement), tubers were produced lighter with an average weight of 86.6 grams. So it can be concluded, in this irrigation regime, the average weight of tubers is closer to weight of seed tuber class. Many studies have confirmed these findings (Fabeiro et al., 2001; Ayas and Korukcu, 2010; Ayas, 2013).
The results showed that maximum tuber yield gained from S1 treatment (55.9 ton/ha) that had no significant difference with S2, but intensive drought stress (S3) produced minimum tuber yield (31.7 ton/ha). N1 and N2 treatments led to highest tuber yield but the lack of nitrogen (N4) caused the lowest tuber yield (38.7 ton/ha). Generally, in S2 and S3 drought stress levels, N2 produced maximum tuber yield. The reduction of tuber yield in S2 and S3 treatments within increment of nitrogen consumption (N1), caused the significant interaction between drought stress and nitrogen on tuber yield.
Ierna and Mauromicale (2006) reported that water deficit stress as much as 50% of the water requirement, had increased stomatal resistance and caused the reduction of leaves photosynthesis, biomass, tuber growth and tuber yield. Demelash, 2013; Alva et al., 2012 and Ayas, 2013 studies also confirm the results of this Research.
The second level of nitrogen (N2) in S3 treatments led to maximum, but S1N4 led to minimum water use efficiency (9.21 and 5.24 kg/m3 respectively). Liu et al. (2006) reported, by reducing the amount of irrigation volume, tuber yield decreases baut water use efficiency will increase.The stepwise regression analysis showed that the average tuber weight explains most changes of marketable tuber yield per plot.
Based on the results of the present study, since there is no statistical difference in tuber yield, between S1 and S2 irrigation regimes, it is recommended that for proper utilization of water resources and achieve economic yield, potato crop, produce with 6400 m3 water per hectare with irrigation at 7 days period. Results showed, at S2 irrigation regime, N2 Treatment (consumption of 270 kg Urea/ ha) had produced the highest yield, so S2N2 treatments is the best option for potato crop production.

Topography is one of the soil formation factors that has direct and indirect effects on physical and chemical properties, as well as soil formation and development. This study was conducted to investigate the effect of slope position on selected soil characteristics in Chelgerd region of Chaharmahal-va-Bakhtiari, Iran. Three transects were selected on west hill slope and 9 profiles were dug on three slope position, including summit, back slope and foot slope. Soil samples were gathered from each profile for physical and chemical analysis. Soil profiles in the summit and back slope were classified as Inceptisols while soil profiles in the foot slope position were classified as Vertisols. Significant differences between clay, sand and organic matter content in different slope positions were observed. The highest amount of clay and organic matter content were observed in foot slope position and maximum amount of sand was related to back slop position. Mineralogy results showed the presence of different minerals such as smectite, illite and kaolinite in all studied profiles; smectite with more than 70% was the dominant mineral. There was no significant difference between different slope positions in term of mineral composition, but smectite showed a slight increase toward down the slope.

Soil depth is defined as the depth from the surface to more-or-less consolidated material and can be considered as the most crucial soil indicator, affecting desertification and degradation in disturbed ecosystems. Soil depth varies as a function of many different factors, including slope, land use, curvature, parent material, weathering rate, climate, vegetation cover, upslope contributing area, and lithology. Topography, one of the major soil forming factors, controls various soil properties. Thus, quantitative information on the topographic attributes has been applied in the form of digital terrain models (DTMs). The prediction of soil depth by topographic attributes depends mainly on: i) the spatial scale of topographic variation in the area, ii) the nature of the processes that are responsible for spatial variation in soil depth, and iii) the degree to which terrain-soil relationships have been disturbed by human activities. This study was conducted to explore the relationships of soil depth with topographic attributes in a hilly region of western Iran.

The study area is located at Koohrang district between 32°20′ to 32°30′ N latitudes and 50°14′ to 50°24′ E longitudes, in Charmahal and Bakhtiari province, western Iran. The field sites with an area of 30,000 ha are located on the hillslopes at about 20% transversal slope. The soils at the site are classified as Typic Calcixerepts, Typic Xerorthents and Calcic Haploxerepts for the representative excavated profiles in summit, shoulder and backslope, respectively. The soils located at footslope and toeslope were classified as Chromic Calcixererts. Measurements were made in twenty representative hillslopes of the studied area. At the selected site, one hundred points were selected using randomly stratified methodology, considering all geomorphic surfaces including summit, shoulder, backslope, footslope and toeslope during sampling. Overall, 100 profiles were dug and described; and the solum thickness was measured for each profile. DEM data were created by using a 1:2,5000 topographic map. Topographical indices were generated from the DEM using TAS software. Terrain attributes in two categories, primary and secondary (compound) attributes; primary attributes are included elevation, slope, aspect, catchment area, dispersal area, plan curvature, profile curvature, tangential curvature, shaded relief. Secondary or compound attributes such as soil water content or the potential for sheet erosion, stream power index, wetness index, and sediment transport index. Correlation coefficients to define relationships between soil depth and terrain attributes, and analysis of variance by Duncan test were done using the SPSS software. The statistical software SPSS was used for developing multiple linear regression models. Terrain attributes were selected as the independent variables and soil depth was employed as dependent variable in the model. Thirty sampling sites were used to validate the developed soil-landscape model. In testing soil-landscape model, we calculated two indices from the observed and predicted values included mean error (ME) and root mean square error (RMSE).

The soil depth in the studied profiles varied from 30 cm to 150 cm with an average of 108.6 cm. Relatively high variability (CV = 76%) was obtained for soil depth in the study area. The linear correlation analysis of the 12 topographic attributes and one soil property (soil depth), showed that there was a significant correlation among 36 of the 77 attribute pairs. Soil depth showed high positive significant correlations with catchment area, plan curvature, and wetness index, and showed high negative correlation with sediment transport index, sediment power index and slope. Low positive significant correlations of soil depth were identified with tangential curvature, and profile curvature. Moreover, soil depth was negatively correlated with elevation. The rest of the topographic attributes including aspect, shaded relief, and dispersal area were not significantly correlated with soil depth. Many of these relationships are similar to those found in other landscapes. The results of analysis of variance showed that there are significant differences for soil depth among the selected slope positions in the studied area. The highest values of soil depth were observed in the downslope positions including footslope and toeslope. The lowest soil depth was observed in shoulder position with the highest rate of soil erosion.

It seems that the high variability for soil depth depends on topography of the field, and the landscape position, causing differential accumulation of water at different positions on the landscape; and moreover the soil erosion and deposition processes, resulting in high variability in the soil depth. We found relatively high correlation coefficients of soil depth with two groups of topographic attributes (erosional processes and water accumulation). Empirical model (MLR) using selected terrain attributes explains 76% of the variation of soil depth in the studied area. The terrain attributes that best predicted soil depth variability in the selected site were mainly the attributes that had significant relationships with soil depth. The dominant attributes in the MLR model included slope, wetness index, catchment area and sediment transport index.

Wheat is planted in several million ha of hummocky land of Zagros area. Considering high precipitation in this area, it is important to study nitrogen application management with respect to soil, water and environmental protection. This study was conducted in rainfed wheat fields located on different slope positions. Soil properties, crop yield, N uptake and residual soil N were determined in 100 points of rainfed cultivated wheat. The results showed that soil characteristics and crop yield varied in different slope positions. The highest and the lowest crop yields were obtained in toeslope and shoulder, respectively. Maximum and minimum N uptake and residual soil N were also observed in the same slope positions. Soil N in toeslope had a movement toward downhill and was higher than wheat requirement. Thus, residual soil N in this position may be exposed to the soil surface erosion and move on to the waterways and deep percolation to ground water during intermittent years, and thus the excess N in the soil would probably lead to soil and water contamination. Based on the results of this investigation and in order to prevent N losses, it is recommended that N application should be managed to use less N in all slope positions, especially in the toeslope, to split application of N fertilizers in appropriate times, and to use organic.

This study was conducted to investigate the type and origin of clay minerals via several profiles in Lordegan hilly lands. The profiles were located in two kinds of land uses including forest and dry farm at different slope positions as sampling sites. The soil saples were collected from two depths of soil horizons to indicate CEC, soil texture, OC%, calcium carbonate equivalent, X-ray diffraction and micro-morphological study via undistributed soil sampling. The results illustrated that the dominating clay minerals are Illite، Smectite, Chlorite and Chlorite-Smectite as mixed minerals. According to the result, the origin of minerals in both land uses and different slope positions is inheritance from parent material. These minerals are mostly apparent in lower positions of the slope especially rain feed. Thin sections investigation of some horizons in the both land use in different slope positions showed that there was no difference regarding the kind of soil voids and C/F ratio between two sampling sites. (including land use and slope positions). Complex packing voids, Vugh and planar voids were the most dominant voids of these profiles. The observed b-fabric in all horizons was crystallitic and soil structure in back slop was subangular blocky. In all horizons of rain feed land use except for shoulder and back slop, clay films and calcite coatings were observed.

In order to investigate the effect of levels of drought tension and nitrogen on yield and qualitative and physiological traits of potato, this experiment as split plots was carried out based on randomized complete blocks design, with three levels of drought tension S1 (control, providing 100 percentage water requirement), S2 (providing 75 percentage) and S3 (providing 50 percentage of water requirement of potato after emergence to the end of the growing period) as the main factors and four nitrogen fertilizer treatments N1 (providing 100 percentage fertilizer requirement), N2 (66 percentage), N3 (33 percentage) and N4 (without applying nitrogen fertilizer) as the sub factors in Agriculture and Natural Resources Research Center of Chahar Mahal va Bakhtiari province. In this experiment maximum tuber yield gained from without tension treatment (S1) by the amount of 55/9 tons per hectare that had no significant difference at five percent level with S2 treatment but S3 with significant difference than two mentioned treatments, produced the average yield 31/7 ton per hectare. N1 and N2 treatments produced the highest tuber yield without statistically difference at five percentage level, but lack of nitrogen consumption (N4) led to the lowest tuber yield (38/7 ton per hectare). Generally, in S2 and S3 tension levels, N2 treatment caused access to the maximum tuber yield. Due to the reduction of tuber yield in S2 and S3 treatments within the highest nitrogen consumption level (N1), the interaction between drought tension and nitrogen on tuber yield was significant at one percentage level.

Adopting different systems in soil cultivation after ignorant and non-scientific approaches regarding land use change leads to physical and chemical changes in soil properties especially in agricultural lands on steep slops. This research has been done by the aim of study of landscape position and landuse on physicochemical soil properties and microbial respiration of soils on in Lordegan hill-land under two landuses: dryland and forest. In this way sample from a hill with five part of slope (including: summit, shoulder, back slope, foot slope, toe slope) in two kinds of land use, forest and dryland were collected. The results showed that available K and P, clay, total nitrogen, organic carbon content, in both of land use had been increase through the lower part of slope and CEC at forest land use had been increase of the summit to back slope. soil pH in two kinds of land use decreasd from up to the down of the slope. Comparison of mean of microbial respiration index in both kinds of land use showed that more soil microbial respiration in forest land use than other, which in both, the two kinds of land use were increased through the lower part of slope because of accumulation of organic matter. Overall, relief, plant community, slope position and land-use are influence on soil erosion and leaching.