نشریه مدیریت خاک و تولید پایدار
سال نهم شماره 1 (پیاپی 27، بهار 1398)

Urmia Lake drying up and withdrawal of its shores resulted in remaining of vast saline lands around it. The study of soils as the indicator of the environmental condition, in which they have developed, can provide valuable information about the past climate of the area. The aim of this research was to study the evidence of the Urmia Lake fluctuations through the developed soils in its Southeastern shore. a transect perpendicular to Urmia Lake was studied in southeast Urmia Lake, in Bonab Plain. Seven pedons based on the variation of geomorphic surfaces and landscape change, were described and sampled along a transect next to the southeastern shore of Urmia Lake. Soil samples were collected from all diagnostic horizons and analyzed for some of their physicochemical characteristics. From some of the diagnostic horizons, undisturbed samples were gathered for micromorphological analysis. Clay mineralogy was also performed for some of the horizons. Results showed that among studied soil pedons, pedons 1, 2, 3, 4, and 5 had saline soils along with buried horiozons and their developments were mostly affected by Urmia Lake sediments and fluctuations. In all of these 5 soil pedons, buried soils with different degrees of development were detected, which showed that these soils had been exposed during different time periods, before further burial by lacustrine sediments. Buried soils in first 3 pedons had more developed soils than their upper soils, showing that upper soils are in their early stages of development. micromorphological study of buried Bk horizon in the depth of 50-105 cm of P2, revealed that it is a highly pedal and highly separated horizon with calcite coatings and infillings. Based on the results, no evidence of buried soils or lacustrine sediments was observed in pedon 6, which was located in agricultural lands, 1 km from pedon 5. In pedon 6, highly developed calcic horizons were observed, showing that this part of landscape has been stable for a long time, at least longer than other 5 studied pedons. The existence of buried soils and textural discontinuities in some of the studied soil pedons showed that Urmia Lake had several fluctuations due to climatic changes and had also been much more extended than that of 1998 in the past. The study also revealed that its recession has happened during several stages which has also coincided with several expansions and consequent sedimentations, through which, soil evolution and development in its southeastern shore has affected.

The arbuscular mycorrhizal symbiosis enhances plant tolerance to water deficit. Methyl jasmonate (MeJA) is a phytohormone related to multiple developmental and growth processes, which might play an important role in the mycorrhizal interaction. Hormonal regulation and the symbiotic relationship provide benefits for plants to overcome stress conditions. The aim of this study was to evaluate the effects of MeJA application and mycorrhizal symbiosis on some growth and biochemical properties of alfalfa plant under water deficit stress. A combined factorial design was performed with three factors: (1) plants non-inoculated (NM) or inoculated with the mycorrhizal fungus Rhizophagus intraradices (AM) (2) untreated plants and plants treated with 50 μm MeJA, and (3) soil moisture levels including field soil capacity (FC) and 55% FC. Half of the plants received a MeJA treatment through foliar spray 30 days after growth and the other half of the plants were considered as not- MeJA treated. Water deficit treatment was applied one week after hormone applying for four weeks. After harvest, root colonization percentage, dry weight of shoots and roots, total chlorophyll and carotenoids contents, soluble sugars and proline contents, as well as P and N contents, were assessed. MeJA application significantly increased total chlorophyll content of AM and NM plants at FC moisture by 76.6% and 106.6%, respectively. MeJA caused a significant increase only in chlorophyll content of NM plants under water deficit stress by 116.4%. Water deficit stress had no significant effect on carotenoids content. Obtained results indicated synergistic effect of the co-treatment of mycorrhiza and MeJA on carotenoids content at FC moisture. In addition, the content of total chlorophyll and carotenoids significantly were higher under water deficit stress in AM plants than NM plants. Dry weights of shoot and root of AM plants under all soil moisture and MeJA treatments were significantly higher than NM plants. Moreover, the application of MeJA augmented the positive effect of mycorrhizal colonization on shoot and root dry weights under both moisture levels. Shoot and root dry weights under water deficit stress and co-treatment of mycorrhiza and MeJA increased 3.4 and 2.8-folds, respectively, compared to NM plants. Mycorrhizal growth dependency (MGD) was increased by 86.9% under water deficit stress condition compared with the non-stressed condition. However, MGD was decreased significantly by MeJA application in stressed-plants. MeJA application and water deficit stress did not exhibit a significant effect on mycorrhizal colonization rate while they increased proline and soluble sugar production. Co-treatment of mycorrhiza and MeJA had a significant synergistic effect on proline accumulation in shoots and roots of stressed plants by 77.3% and 62.2% respectively compared with stressed NM plants. Furthermore, MeJA application caused a significant increase in N and P contents, and root to shoot ratio of soluble sugars of AM plants by 77.8%, 64.3% and 35.1% respectively at FC moisture level. MeJA application induced a significant change in carbohydrate allocation to roots in mycorrhizal plants and also decreased MGD of stressed plants. MeJA treatment and mycorrhizal symbiosis improved plant response to water deficit stress, and there was an interactive positive effect between MeJA and mycorrhizal fungi which alleviated growth impairment under water deficit conditions by modifying the physiological and biochemical properties of the host plant.

Many soil maps that produced in Iran are in medium scale related to the soil survey projects that have done over the past six decades. In many cases, soil maps have not updated due to the high cost of soil survey activities in conventional methods. A proposed solution to overcome limitations of the conventional soil survey is digital soil mapping (DSM) that extensively used for producing soil maps in many countries recently. The extrapolation method in which soil pattern rules in reference area is used for soil class prediction in other areas as a cost-effective method have been mentioned by some soil surveyors. To achieve the main advantages of extrapolation in DSM, in this research we evaluated the use of random forest model in a reference area (donor area) for producing soil taxonomic classes at subgroup level in a site out of the reference area (recipient area). In this study two neighboring areas in Fars Province in southern Iran were selected: 1) Saadat Shahr plain as donor site and, 2) Seidan plain as recipient area. Two agricultural plain have a moderately similar environmental condition such as elevation, geology, physiography, and climate and agriculture behavior. In donor area, 82 soil profiles were excavated, described and analyzed. Latin hypercube sampling (LHS) was used as a statistical method in donor area. In recipient area, 27 locations were determined on some parallel transects across the plain. All soils were classified according to USDA soil taxonomy System (2014). Random forest (RF) in R statistical software was used to predict soil classes in donor area. Then the constructed model in donor area saved and applied to the recipient area. 25 variables related to soil forming factors consist of 1) primary and secondary train attributes and 2) remote sensing indices obtained from Landsat 8 satellite, OLI sensor imagery were used in this study. All auxiliary environmental covariate layers were resampled to a 30 resolution. Producer's, users and overall accuracy and kappa index calculated according to the agreement of the field surveyed with predicted soil classes. Using RF algorithm from the 25 variables related to soil forming factors, five primary and secondary train attributes consist of slop, multiresolution index of valley bottom flatness (MRVBF), terrain ruggedness index, topographic wetness index and modified catchment area were selected as influential covariates. An overall accuracy of 72%, and a Kappa index of 0.59 in the donor area, illustrating the relatively desirable agreement between observed and predicted soil classes. For extrapolating evaluation, the result of RF model with 70% of soil samples in the donor area was compared with the output of the transported RF model using 27 observations of the validation dataset. The overall accuracy of the external validation was 45%, and the Kappa index was 0.28. Transferring the RF model constructed by all soil samples of the donor area (100%) showed a better result of soil prediction in the recipient area. The overall accuracy and the Kappa index of the external validation was 52% and 0.38, respectively. From the six soil subgroup classes, the best predicted classes were Typic Calcixerepts and Typic Xerorthents. Some classes were too sparse and the model was unable to predict them correctly. The results showed that the model extrapolation in the framework of DSM could be a powerful tool for producing soil map in the area of Iran that soil maps are not available or updating the present soil maps are time and cost consuming. The low-cost and time saving method reported here, encourages soil surveyors to select model extrapolation for their survey activities.

In recent decades, site-specific management (SSM) has been specifically considered to achieve to increased input efficiency, improved economic margins of crop production and reduced environmental risks. Short-scale spatial variability of soil properties caused more necessity of SSM techniques. Natural variability of soil results from complex interactions between geology, topography and climatic factors, as well as land use change and land management strategies. Deforesting and vast land use changes are considered as the important land management strategies that have been extensively used in recent decades. Therefore, determining the effects of land use change on soil properties in conjunction with local environmental conditions and on the spatial variability of soil properties may drastically help the land use planners. Therefore, the present study was done aimed to explore the effects of oak trees deforesting in Shah-Mokhtar region in Yasouj and land use changes to dry farming on the spatial variability of nutritional elements using geostatistical techniques. The present study was conducted in a Shah-Mokhtar, north, and northwest of Yasouj, in Kohgiluyeh Province, southern Iran. Spatial variability of seven soil fertility properties, including N, P, K, Fe, Cu, Zn, and Mn concentration in soil, were examined in three land uses, including dense forest, degraded (semi-dense) forest and rain-fed lands. A total of 100 surface (0-30 cm) soil samples were collected and analyzed for the nutritional elements after preparing in the laboratory. Data were analyzed statistically and their normal distribution pattern was examined using the Kolmogrov-Smirnov test. In the geostatistical analyses step, the spatial structure of studied variables was analyzed by fitting the suitable authorized models on calculated experimental semi-variograms. The concentration of studied elements was interpolated using ordinary kriging (OK) and inverse distance weighting (IDW) estimators and finally, the spatial distribution map of each soil nutrient was prepared using ArcGIS 10.3. The results showed that the highest mean soil concentration of almost all of selected nutrients belonged to the dense forest lands and due to the land use changes to the degraded forest and then dry farming, average values of selected elements significantly decreased. Among the studied properties, soil N concentration with an average of 0.34%, 0.17% and 0.08% in dense forest, degraded forest, and rain-fed soil samples, had the most decrease caused by deforesting. Semi-variogram analyses showed that spherical model had the best performance. For interpolating the soil K and Mn concentration, IDW method and for other studied elements, OK method was efficiently used. The spatial correlation class was strong for N, Cu, and Fe; whereas a moderate class was calculated for soil P and Zn concentration. The spatial distribution maps of selected nutrients revealed that the dense forest and dry farming soils had the highest and lowest contents of soil nutritional elements. According to the findings of the present study, it can be stated that degradation of oak forest may lead to the significant decrease of soil nutritional elements, specifically soil N concentration as one of the main soil fertility quality. Therefore, it seems that not only the significant soil quality decline but also the extensive degradation of whole ecosystem and unfavorable climatic consequences will be the unavoidable results of deforesting in Shah-Mokhtar region.

The conversion of natural vegetation to other vegetation covers and climate change has had a major impact on the decomposition of soil organic carbon and eventually the emission of carbon dioxide (CO2) from the soil into the atmosphere. But so far in Iran, little researches have looked at the effect of the conversion of vegetation and climate change on the amount of soil organic carbon (SOC) stock as a key component in reducing the effects of climate change and global warming. To overcome the limitations of field studies, SOM models provide the best scientific understanding of the dynamics of SOM. RothC Carbon model is one of the most widely used models in soil carbon sequestration studies that has been used in many studies to study the effect of climate change on soil carbon stock. The purpose of present study, investigate the effect of converting native vegetation (rangeland) into four new vegetation (rangelands of cypress under-story, rangelands of almond under-story, cypress trees and almond trees), as well as the simulation of the effect of two climate scenarios (non-occurrence of climate change and the occurrence of climate change) on the dynamics of SOC stock in the five vegetation covers of the Shiraz Bajgah region for 36 years (2014-2050). In this study, 210 soil samples were collected to determine the soil organic carbon and soil texture as well as 420 samples for determining the soil bulk density. After measuring the parameters, SOC stock at 0-20 cm depth was calculated for each vegetation cover treatment. Finally, the effect of vegetation conversion and two climate scenarios on the amount of SOC stock using the RothC model was investigated in the five vegetation covers of Shiraz Bajgah region. The results showed that the increase of SOC stock due to planting of cypress trees after 15 years was higher than the amount increase of SOC stock due to the planting of almond trees after 30 years in Bajgah region. The simulation results of the RothC model also indicated that in comparison with 2014, the SOC stock in the 2050 in the rangeland, rangelands of almond under-story, rangelands of cypress under-story, cypress trees and almond trees treatments will be decreased by 12.19%, 12.14%, 12.11%, 10.37% and 10.49%, respectively due to climate change; and the amount of SOC stock in each of the treatments before and after climate change at 5% level (P <0.05) had significant difference.

Soil salinity is one of the most important soil properties and it's variability investigation is essential to crop management, land degradation and environmental studies. Soil salinity is measured using electrical conductivity (EC) and estimation of soil salinity contents using experimental methods is expensive and time consuming. Therefore, the collection of information on the spatial distribution of soil salinity in n vast areas requires new inexpensive techniques. Recently, new techniques such as electromagnetic induction, visible - near infrared spectroscopy and remote sensing were applied to measure soil salinity. The purpose of this study is the estimation of soil salinity using visible- near infrared spectroscopy, electromagnetic induction, and remote sensing methods. The study area is located 20 km northeast of Ghorveh city in Kurdistan Province and covers a surface of 26000 hectares. 100 soil samples (0–30 cm depth) were collected and. soil electrical conductivity was measured in a saturated extract. Applied auxiliary data in this study were spectral information of visible - near infrared spectroscopy method, reading of electromagnetic induction method, and ETM+ data of Landsat 8. In the 100 sampling sits, horizontal and vertical readings were read using EM38 and salinity index (SI) and normalized difference vegetative index (NDVI), bright index, and Bands 1, 2, 3, 4, 5, 6 , and 7were computed and extracted using Landsat 8 ETM+ data and Arc GIS software. Moreover, the 100 samples were scanned using spectrometer (model of FieldSpec®3, ASD, FR, USA) with a spectral range of 350 to 2500 nm. To make a relationship between soil salinity and auxiliary data of the three methods, artificial neural network (ANN) model were applied. Finally, soil salinity were estimated using ANN and were validated using cross validation method. Soil salinity contents were low to high (0.23 to 14.47 dSm-1). The highest contents of soil salinity were observed in central regions (low and bare land) and the lowest contents of soil salinity were located in high and range land. Based on sensitive analysis of artificial neural network model, in remote sensing methods salinity index, NDVI index, band 7, and band 3 were the most variables to predict soil salinity. In general, the results showed the most important auxiliary variables to predict soil salinity were spectral information of visible - near infrared range, vertical reading, and remote sensing data, respectively. Soil visible - near infrared spectroscopy method to predict soil salinity had 0.94, 0.27 and 0.64, respectively for determination of coefficient (R2), mean error (ME), and root mean square root (RMSE) and was better compared to the electromagnetic induction, remote sensing although combination of three methods together had the best results to estimate soil salinity. The most important auxiliary data to predict soil salinity in the study area was spectral information of visible - near infrared range. Electromagnetic induction method also is suitable auxiliary data to predict soil salinity and it can recommend as speed, accurate and cheap method to predict soil salinity. Combination of three methods together (electromagnetic induction, visible - near infrared spectroscopy and remote sensing) had the best results to estimate soil salinity. Therefore, it is suggested to predict soil salinity, ANN model and auxiliary data such as spectral information of visible - near infrared spectroscopy method and electromagnetic induction will be applied in the future studies.

Abstract Excessive accumulation of heavy metals in agricultural soils, not only leads to environmental pollution but also increases the absorption of heavy metals by plants. Food consumption had been identified as the major path way of human exposure. The purpose of this study was to determine the concentration of some heavy metals in common vegetables and plants in the region in a part of the agricultural land of Varamin in Tehran province and assess the environmental risk of heavy metals using human health indices. The composite sampling of basil, garden cress, radish, chives, mint, parsley, chard, and savory, as well as corn and rice in a region of 50 hectares with three replications was done randomly. Samples were prepared by dry digestion method and cadmium, lead, zinc, copper, chromium, cobalt and nickel concentrations were determined using atomic absorption spectrometry. Following the results of the experiment, the bioaccumulation factor (BCF), Translocation Factor (TF), average daily intake index (EDI), and Health index (THQ, TDHQ and HI) were calculated. The highest average concentration of zinc, copper, lead, cadmium, cobalt, chromium and nickel was found in garden cress (12.54), mint (3.3), mint (1), radish (0.22) basil (0.48), chives (0.70) and corn (1.24 mg/kg dry matter) were observed. The translocation factor (TF) of lead in garden cress, cadmium in parsley, zinc in chard, cobalt, chromium, and lead in radish and chromium in savory were more than 1. In contrast, transfer factor (TF) values for rice, corn and oats were less than 1 for all the heavy elements. The bioaccumulation factor (BCF) of cobalt in peppermint, and cadmium for chard, and savory were more than one, and for other plants, the amount of this factor for the metal studied was less than one. Cadmium, cobalt, copper, nickel, zinc and lead in rice plant in adults (0.062, 0.029, 0.110, 0.225, 0.052, 0.193) and in children (0.061, 0.008, 0.096, 0.020, 0.050 and 0.149 have the highest risk of non-cancerous diseases (HQ) for residents of the region. The Target hazard quotient (THQ) in both age groups was reduced as follows: (Corn Sugar, Mint, Basil, Rice, Parsley, Radish and Rice) and in a healthy range. The value of Target diet Hazard Quotient (TDHQ) was less than one, indicating the absence of risk of non-cancerous diseases for consumers due to the consumption of 10 examined products in accordance with Iran's national consumption patterns. Lead in the children's age group showed the highest TDHQ (0.300), indicating a higher risk of lead risk in the total consumption of products than other elements. Overall, the results showed the total health index (HI) of heavy elements for each of the studied age groups was less than 1, indicating that the residents in the study area are in a safe condition

Assessing soil quality and balancing between crop production and quality of natural resources are essential issues in sustainable soil management for agricultural and natural resource protection. In agricultural fields for optimum management and maximum economic productivity, knowledge of the factors affecting the soil quality is necessary. Also, determining the appropriate method for soil quality evaluation is important for sustainable soil management and soil degradation prediction. This study was carried out with the aim of assessing soil quality of paddy fields, determining the minimum data set for soil quality evaluation and investigating the effect of soil quality index using different methods on rice yield in Pirbazar region of Guilan province. Based on the mean annual rice yield, the selected paddy fields were divided into low (4.6 t ha-1) productivity. Sixty soil samples were collected from 0 to 30 cm depth. The rice products were harvested at a 1 m2 plot at each site. In this research, using the principal component analysis (PCA) method, among 20 physical, chemical and biological soil indicators as total data set (TDS), 6 indicators were selected for the minimum data set (MDS). Then, the soil quality of high and low productivity paddy fields was evaluated by simple additive integrated quality index (IQISA) and weighted additive integrated quality index (IQIWA) in two collections of soil properties include MDS and TDS. To evaluate soil quality of paddy fields, an MDS was established with organic carbon, total nitrogen, available potassium, clay percentage and urease activity and these explained about 67% of the soil quality variability. The significant differences were found between the soil quality index of low and high productivity paddy fields when IQIWA and IQISA were developed based on MDS. So that, the mean IQISA-MDS and IQIWA-MDS of the high productivity paddy fields (0.84 and 0.89, respectively) were higher than low productivity paddy fields (respectively 0.78 and 0.80, respectively). Additionally, data indicated that IQISA-MDS and IQIWA-MDS were most strongly correlated with crop yield, the correlation coefficient ranged between 0.44–0.54. Significant differences between the soil quality indices based on MDS for low and high productivity paddy fields indicated that the MDS more efficiently shows the difference of soil quality between paddy fields with different productivity. The significant correlation between IQISA-MDS and IQIWA-MDS indices with rice yield indicated that an MDS with a limited number of indicators was carefully selected and effectively evaluated the status of soils as a rice production medium. Therefore, using an MDS can save time and money and assess the reliable soil quality indices of paddy fields in the study area.

Due to the undesirable effects of using long-term chemical fertilizers and the defection of organic matter in Iranian soils, it is necessary to use of organic fertilizers. Many of the plant remains, including sugar cane, can be transformed into biochars and used as organic fertilizers in the soil. Also, the filter cake is a component of the purification products of sugar that can be used as organic material. Therefore, the present study was conducted with the aim of investigate the effect of organic- and bio-fertilizers on some soil characteristics and wheat yield and to investigate the best combination of organic fertilizers and stimulating bacteria on wheat growth. This research was done in greenhouse in a completely randomized design with factorial arrangement. Factors including organic fertilizer (control, filter cake as 20 (F20) and 40 ton ha-1 (F40), and biochar as 36 (B36) and 72 ton ha-1(B72)) and bacteria (control, Enterobacter Cloacae and Paenibacillus Lactis). Five kg pots were prepared and 10 grains of Chamran variety were cultivated. Harvest was carried out after grain filling and some soil properties such as basal and substrate-induced respirations (BR and SIR respectively), soil organic carbon (SOC), microbial biomass carbon (MBC), permanganate oxidable carbon (POC), cold and hot water soluble carbon (CWC and HWC), Olsen phosphorus and also the dry biomass of the plant grains and the amount of P of them were measured. The results showed that bacterial inoculation reduced the amount of electrical conductivity and pH in compared to non-inoculated treatments. The highest amount of BR (75.0 mg kg-1day-1), Olsen phosphorus (35.7 mg kg-1), and SOC (1.13%) were observed in the treatment of F40 inoculated with Bacillus and the highest amount of MBC (78.1 mg kg-1) was observed in soil treated with F40 inoculated with Enterobacter. Also, the highest amount of CWC (2706 mg kg-1), HWC (3596 mg kg-1) and POC (173 mg kg-1) were related to the treatment of B72 inoculated with Entrobacter. The highest amount of dry weight (5.23 g pot-1) and seed phosphorous amount (1.04 %) were related to F40 inoculated with Bacillus. However biochar was applied to soil in higher weight; but, regarding with plant dry weight, soil olsen phosphorus and SOC, filter cake was more efficient and more proper to improve soil quality indices. Also, the results show that Bacillus had better effects than Enterobacter and it is recommendable to use the F40 as organic fertilizer and inoculation the soil with Bacillus for better growth of wheat.

Land use change and long-term sugarcane cultivation can affect soil properties and soil quality. Study of soil properties changes in long-term cultivation soils can help to improvement the agriculture management. The objective of this research was to evaluate chemical properties of the soils under long-term sugarcane cultivation and adjoining virgin soil in order to monitor changes caused by long-term cropping. This research was undertaken in fields of the Karun Agro-industry at Diamche area of Shushtar in the Khuzestan province. This study was carried out as a factorial experiment based on a randomized complete design with two factors including fields in seven levels and depth in three levels (0-30, 30-60 and 60-90 cm) and three replications. Soil samples were collected from seven depths in six fields with the long-term sugarcane cultivation and the adjoining uncultivated land. The studied soils were influenced by continuous sugarcane cultivation for over four decades. Then, some chemical properties were measured by standard Soil pH and EC of saturated paste, soluble sodium (Na), soil organic matter content by wet oxidation method, calcium carbonate equivalent (CCE) by titration with hydrochloric, soil gypsum by methods of acetone and soil available K and P was measured. Also, the soil sodium bicarbonate extractable phosphorus (P) by Olsen method and available K using 1 N NH4OAc were measured. Results indicated that land use change and long-term sugarcane cultivation result in change soil chemical properties. There were not observed significant different between soil pH in sugarcane cultivation soils and adjoining virgin soil. Land use change and long-term sugarcane cultivation led to a significant decrease in electrical conductivity, soluble sodium, calcium carbonate equivalent, soil gypsum at different depths of soils. Long-term sugarcane cultivation cause to a significant decrease in the available K (63.2 – 77.9%) at 0-30 cm soil depth. The mean of soil available P and organic matter percentage was higher in soils of sugarcane cultivation lands compared to the adjoining uncultivated land. In general, Results of this study indicated changes of soil chemical properties in surface soil (0-30 cm depth) was higher than other depths (30-60 and 60-90 cm). results of this research showed the soil chemical properties of different sugarcane fields significantly changed responses to land use change long-term sugarcane cultivation. Exchangeable K was known to be the sensitive indicators following long-term continuous sugarcane cropping. It seems that monitoring the chemical properties of the soil must be considered in order to land management and to maintain the quality of the studied soils.