نشریه آب و خاک
سال سی و پنجم شماره 4 (پیاپی 78، مهر و آبان 1400)

North of Khuzestan province is one of the major areas for autumn sugar beet planting. Conventional tillage (CT) is widely practiced by sugar beet growers in this region. CT in sugar beet consists of burning wheat residue, using deep plowing with a moldboard plow or ripper plowing followed by several passes of disking, leveling, and furrowing. These aggressive tillage practices have many negative consequences for soils. Losses of soil organic carbon decreases soil permeability and consequently increases soil erosion and surface runoff. Therefore, applying conservation agriculture principles in sugar beet planting, conservation of residues and elimination or reduction of tillage, can help to optimize water use management and improve soil health on a farm scale. The objectives of this study were (i) to determine the possibility of direct planting of autumn sugar beet in wheat residues, (ii) to estimate sugar beet yield and crop water productivity (WP) under CT, chisel (CH), minimum tillage (MT) and no-tillage (NT) systems, (iii) to evaluate the response of sugar beet cultivars (Sharif and Palma) to different soil tillage systems, and (iv) to determine the effect of soil tillage systems on some soil physical properties.

A field experiment was conducted for two years (2016—2017) at the Safiabad Dezful Agricultural Research Center (32° 14.44´-32°15.93´ and 48° 25.41´-48°47). The soil of the study site was deep, well-drained with a silty clay loam texture. The mean annual precipitation and evaporation are 317 and 2400 mm, respectively, with an elevation of 108 m above mean sea level. Irrigation water was supplied from the Dez irrigation network without any salinity restrictions. The experimental was conducted in a split-plot arrangement based on a randomized complete block design with three replicates. The main-plot treatment was tillage method and the subplot treatment was two sugar beet cultivars (Palma and Sharif). Tillage treatments included conventional tillage (CT) (moldboard ploughing + MT steps), chisel (CH) (chisel ploughing + MT steps), minimum tillage (MT) (two perpendicular disks, fertilizing centrifugal machine, disking, furrowing, planting with pneumatic row planter), and no-tillage (NT) (spraying, planting with NT pneumatic row planter). The length and width of each plot were 100 and 6 m, respectively, and row spacing was 75 cm.Soil penetration resistance or cone index (CI) readings were recorded in 2 cm increments to a depth of 50 cm using SP1000 digital penetration tester to reflect the soil compaction. Soil bulk density was determined in 0-10 and 10-20 cm layers. In the first and second year, sugar beet samplings were done 216 and 220 days after planting, by harvesting a row of 75 cm with length of 10 m (7.5 m2). WP was calculated by dividing the root and sugar yield to irrigation water and effective rainfall (effective rainfall was calculated every year with SCS method). Composite data analysis and mean comparison were performed with MSTATC statistical software.

Results of CI showed no significant difference between four tillage methods at 0-10 cm depth. With increasing depth up to 30 cm, slight differences in soil compaction were observed for different tillage treatments, especially in the second year. Overall, compaction in the 0-50 cm profile in the CT and CH method were about 45% and 33%, respectively, lower than NT method, whereas in MT method it was about 37% higher than NT method. Results of root branch number analysis showed that the NT and CT treatments had the lowest branching (2.67 and 2.83, respectively) and the two CH and MT treatments had the highest branching (4.2 and 5.3, respectively). Therefore, NT had no negative effect on root growth of sugar beet. The results of bulk density measurements in the 0-10 cm layer were consistent with the results of the CI, but at depth of 10-20 cm, NT method with the highest bulk density (1.71 g cm-3) had significant difference with the other three tillage methods. Tillage method had no significant effect on root and sugar yield and root and sugar WP. However, in CT treatment, root yield increased by 6-8.5% and sugar yield by 6-12%, while root and sugar WP in NT treatment was about 8% higher than in the other three tillage treatments. On the other hand, changing climate conditions, especially rainfall during two years of the experiment, resulted in significant interaction between year and cultivar for yield and WP at 1% probability level. In the first year, the yield of Sharif cultivar (86.7 t ha-1) was higher than Palma (80.2 t ha-1), but in the second year, despite the decreasing yield of both cultivars, higher resistance of Palma cultivar to Cercospora disease resulted in a significant increase in sugar yield and WP over last year.

The two-year results of this study showed that the direct planting of autumn sugar beet in wheat residues (NT) is possible. Sugar beet yield and WP were not significantly different in tillage methods, but NT reduced tillage traffic from 7 times to 2 times and reduced energy consumption. The response of the two sugar beet cultivars to different tillage methods was the same and among them the Palma cultivar had the highest yield because of its higher resistance to Cercospora disease.

Sediment transportation and accurate estimation of its rate is a significant issue for river engineers and researchers. So far, various and complex relationships have been proposed to predict the amount of suspended sediment transport rate, such as velocity and critical shear stress based equations. However, the complex nature of sediment transport and lack of validated models make it difficult to model the suspended sediment concentration and suspended sediment discharge carried by rivers. Although the developed models led to promising results in sediment transport prediction, due to the importance of sediment transport and its impact on hydraulic structures it is necessary to use other methods with higher efficiency. On the other hand, in recent years, the Meta model approaches have been applied in investigating the hydraulic and hydrologic complex phenomena. Hybrid models involving signal decomposition have also been shown to be effective in improving the prediction accuracy of time series prediction methods, as indicated in. Complementary Ensemble Empirical Mode Decomposition analysis is one of the widely used signal decomposition methods for hydrological time series prediction. Decomposition of time series reduces the difficulty of forecasting, thereby improving forecasting accuracy.In this study, due to the complexity of the sediment and erosion phenomenon and the effect of different parameters in estimating,  time series pre-processing methods along with support vector machine (SVM) and Gaussian process regression (GPR) kernel based approaches were used to estimate suspended sediment load of a natural river at two consecutive hydrometric stations. For this purpose, different models were defined based on hydraulic and sediment particles characteristics. Moreover, the capability of integrated pre-processing and post-processing methods in two states of inter-station and between-stations was investigated. First, the Wavelet Transform (WT) method was used for data pre-processing then, the high-frequency sub-series were selected and re-decomposed using the Empirical Mode Decomposition (EMD). Finally, the most effective sub-series were imposed as inputs for kernel-based models. In addition, to assess the reliability of the superior model, Monte Carlo uncertainty analysis was used.The results showed that the GPR model had a desirable degree of uncertainty in modeling.

In this study, data of two stations of Housatonic River was used. The distance between stations was approximately 50 km. The first station is located near Great Brighton, Massachusetts, and the second station is in Connecticut. The basin area for the stations is 282 and 634 square miles, respectively. The flow path is from the first station to the second station. SVM and GPR models are based on the assumption that adjacent observations should convey information about each other. Gaussian processes are a way of specifying a prior directly over function space. This is a natural generalization of the Gaussian distribution whose mean and covariance are a vector and matrix, respectively. Due to prior knowledge about the data and functional dependencies, no validation process is required for generalization, and GP regression models are able to understand the predictive distribution corresponding to the test input. Wavelet Transform (WT) uses a flexible window function (mother wavelet) in signal processing. The flexible window function can be changed over time according to the signal shape and compactness. After using WT, the signal will decompose into two approximations (large-scale or low-frequency component) and detailed (small-scale component) components. EEMD was proposed to solve the mode mixing issue of empirical mode decomposition (EMD) which specifies the true IMF as the mean of an ensemble of trials. Each trial consists of the decomposition results of the signal plus a white noise of finite amplitude. EMD can be used to decompose any complex signal into finite intrinsic mode functions and a residue, resulting in subtasks with simpler frequency components and stronger correlations that are easier to analyze and forecast. Another important feature of empirical model of decomposition is that it can be used for noise reduction of noisy time series, which can be effective in improving the accuracy of model predictions. In the uncertainty analysis method, two elements are used to test the robustness and to analyze the models uncertainty. The first one is the percentage of the studied outputs which are in the range of 95PPU and the next one is the average distance between the upper (XU) and lower (XL) uncertainty bands. In this regard, the considered model should be run many times (1000 times in this study), and the empirical cumulative distribution probability of the models be calculated. The upper and lower bands are considered 2.5% and 97.5% probabilities of the cumulative distribution, respectively.

In order to evaluate and review the performance of the tested models and determine the accuracy of the selected models, three performance criteria named Correlation Coefficient (CC), Determination Coefficient (DC), and Root Mean Square Errors (RSME) were used. The obtained results indicated that the accuracy of the applied integrated models was higher than the single SVM and GPR models. The use of integrated methods decreased the error criteria between 20 to 25 %. The obtained results for the uncertainty analysis showed that in suspended sediment load modeling the observed and predicted values were within the 95 PPU band in most of the cases. Moreover, it was found that the amount of d-Factors for train and test datasets were smaller than the standard deviation of the observed data. Therefore, based on the results, it could be induced that the suspended sediment modeling via integrated WT-EEMD-GPR model led to an allowable degree of uncertainty.

Comparison of the developed models’ accuracy revealed that integrated GPR and SVM models had higher performance compared with single GPR and SVM models in predicting the suspended sediment discharge. The use of these two methods approximately decreased the error criteria between 20 to 25 %. According to the results, for the models that were developed based on the station data, the model with the input parameters of Dwt, Dwt-1, and Dst-1 and in the case of investigating the relationship between the stations, the model with the input parameters of Dst-2, Dwt-1, and Dst-1 were superior models. Also, based on the uncertainty analysis, the integrated GPR model had an allowable degree of uncertainty in suspended sediment modeling. However, it should be noted that the used methods are data sensitive models. Therefore, further studies using data ranges out of this study and field data should be carried out to determine the merits of the models to estimate suspended sediment load in the real conditions of flow.

In hydrological studies, time series are observed as continuous or discrete. Groundwater level and rainfall can be considered as discrete time series. The most common way to measure the dependence between two variables in a discrete time series is to calculate the Pearson correlation coefficient (r). Pearson correlation test is a parametric test that quantitatively measures the linear relationship between variables. This coefficient is essentially a dimensionless index that describes the relationship between two variables numerically. The groundwater level is more or less influenced by rainfall, and this influence may be delayed for a variety of reasons. The process of comparing two time series in different time steps is called cross-correlation. In the cross-correlation analysis, the time-dependent relationship between the dependent and the independent variables is analyzed by computing the coefficients of cross-correlation for various time lags. Results are plotted on a graph called a cross-correlogram.Mashhad-Chenaran aquifer with an area of about 2527 km2 is the most important aquifer in Khorasan Razavi province. Unfortunately, so far in the Mashhad-Chenaran aquifer, the recharge lag time has not been calculated due to the very complex geological and hydrogeological conditions of the aquifer. In this study, an attempt has been made to calculate the groundwater recharge lag time.

In this study, 15 years (Sep. 2001 to Sep. 2016) data of monthly depth to water-table and rainfall have been used . There is 74 active observation well in Mashhad-Chenaran aquifer. Out of 74 wells, 31 well were selected based on geological and hydrogeological conditions. To calculate the rainfall at the observation wells, the daily rainfall data from rain gauge and evaporation stations (25 rain gauge stations and 9 evaporator stations) have been used. First, the cumulative daily rainfall at each station for one month (from 15 months to 15 months later) was calculated. Then, a monthly rainfall raster was prepared using ArcGIS.Finally, the rainfall at the observation well was extracted from the raster file.

The correlation coefficient between the groundwater level and rainfall was calculated for the 31 wells at two confidence levels (α = 0.05 and α = 0.1). The lag time was calculated based on the highest correlation coefficient for the two confidence levels. Results showed that the cross-correlation coefficient varied from at least 0.129 in the Tanglshour-Morgh Pardak observation well (very weak) to 0.495 in the Kalateh Sheikhha observation well (moderate). The coefficients of cross-correlation for various time lags were plotted on the cross-correlogram. In cross-correlogram, the month zero was equivalent to October and the month 11 was equivalent to September of the next year. It was observed that the trend of correlation coefficient followed the two specific patterns. In the first group, the water table usually reacts to rainfall after the second month. Then, the correlation coefficient gradually increased. The correlation coefficient reached its maximum in the fourth and fifth months and then decreased with a gentle slope. From the seventh month to the eleventh month the correlation coefficient has become negative. Although there was a significant relationship during these months, there was no cause-and-effect relationship between changes in the water table and rainfall. In the second group, the relationship between the groundwater level and rainfall was not significant at the 95% confidence level. This group includes Doghai observation wells, Qarachah, Shurcheh, Mochenan, Yekehlengeh, Chamgard, Ghahghahe, Tangleshour - Morgh Pardak, and Shorcheh. Changes in the correlation coefficient of these wells were very irregular and the relationship between rainfall and water table changes was probably influenced by other factors. The map of lag time showed that the spatial variations of the lag time completely followed the pattern of the Iso-depth map. In general, the lag time was a function of the depth to the water-table in the Mashhad-Chenaran aquifer. With increasing water depth, the lag time also increased. A closer look at the map showed that in the northern and southern margins of the first hydrogeological unit, the lag time was more than its center. In the northern and southern hydrogeological units, the lag time showed the greatest compliance with the groundwater depth. The amount of lag time from the northern margin of the aquifer to the south gradually increased and finally reached its maximum value in the Akhlamad, Torqabeh-Shandiz.

As discussed previously, the groundwater level was influenced by rainfall, and this influence may be delayed for a variety of reasons. In this study, the groundwater response to rainfall has been estimated from 31 observation wells by cross-correlation method in a period of 15 years (Sep. 2001 to Sep. 2016). The correlation test results showed that after about 2 to 3 months, the effect of rainfall was gradually observed on the groundwater level and the correlation coefficient at the confidence level α = 0.05 and α = 0.1 for 77 % and 97% of wells became meaningful, respectively. The minimum lag time was 2 months and the maximum was 7 months. In general, the estimated lag time was well matched to the groundwater depth and fully followed the Iso-depth map pattern. The amount of groundwater recharge throughout the Mashhad-Chenaran aquifer was mainly controlled by the unsaturated area properties such as thickness, material, etc. Changes in groundwater depth were the major factor affecting the lag time. It seems that with the start of rainfall in late October, groundwater recharge in most wells begin in mid-autumn and continues until late spring. Most of the groundwater recharge takes place in late winter. In summer, rainfall has a very small role in groundwater recharge. In this period, the uncontrolled extraction of water from the aquifer and consequently a sharp and continuous drop in groundwater level plays a major role in water table fluctuations.

The deficiency of phosphorus has attracted a lot of attention as one of the most important nutrients for agricultural plants especially in calcareous soils. However, in some soils, organic phosphorous containing 80 percent of total phosphorus in some soils but in most cases, that form of phosphorus is not available for plant uptake. The availability of phosphorus from both organic and inorganic sources by phosphate-solubilizing microorganisms (PSMs) as bio-inoculants are promising substitutes for chemical fertilizer and other agrochemicals amendments. Both arbuscular mycorrhizal fungi (AMF) and phosphate solubilizing bacteria (PSB) play a key role in providing phosphorus for agricultural plants. Among several phosphate-solubilizing fungal isolates, Aspergillus sp. is able to solubilize calcium phosphates by secreting various organic acids, e.g., oxalic and formic acids, and producing phytase enzyme. The present study aimed to evaluate the ability of different strains of Aspergillus for phytase production. The second aim of this study was the purification and application of purified phytase and its efficiency in the phosphorus availability from hexaphosphorylated inositols. Two separate experiments were carried out in two different stages. In the first one phytase was isolated from three strains of Aspergillus (Aspergillus niger provided by the department of plant protection, Agricultural college, Ferdowsi University of Mashhad), Aspergillus flavus, and Aspergillus fumigatus strains were collected from the Iranian biological resources center, Tehran). All Isolates were recultured on PDA (potato dextrose Agar) medium for 5 days at 30 oC in an incubator. Quality evaluation of phytase production by three strains of Aspergillus tested using hydrolysis of phytate sodium on PSM (phytase screen medium) medium.  Solubility index was calculated for all three strains (Solubility index = (Colony diameter + Hallow diameter)/ Colony diameter). Phytase production was carried out on fermentation media (Shieh and Ware 1968) but starch was substituted by dextrin. Fermentation media inoculated by fungal strains for 14 days at 30 oC.  Fermentation media was centrifuged (10,000 g) for 30 minutes and supernatant was collected. Purification of phytases was done against Tris-HCl 25mM, pH=7.2 for 12 hours. Phytase activities were evaluated in a completely randomized design with three replications. Then purified phytase from three Aspergillus strains was applied in a pot experiment using a completely randomized design with the factorial arrangement and three replications. The experimental factors included two levels of hexaphosphorylated inositols (and 50 mg/kg) and four types of phytase (Control, phytase isolated from Aspergillus niger, Aspergillus flavus, and Aspergillus fumigatus. In the greenhouse experiment, the effects of different phytase types on phosphorus availability from sodium phytate (hexaphosphorylated inositols) and phosphorus uptake by maize plant was evaluated. Corn plants (Zea maize 704 single cross) were grown in 5 kg pots at 70 % of water holding capacity for 60 days. Plant height, root dry weight, shoot dry weight, phosphorus concentration in shoot and root were evaluated.    The results showed that Aspergillus niger and Aspergillus flavus had the highest (4.96) and the lowest (1.23) solubility index among the tested strains, respectively. The results from the laboratory experiment showed that phytase isolated from Aspergillus niger had the maximum amount of phytase activity (16.48 µmol/ min.ml) and phytase isolated from Aspergillus flavus had the minimum phytase activity (4.67 µmol/ min.ml). Aspergillus niger phytase was more effective compared to Aspergillus flavus and Aspergillus fumigatus phytases. The results of the greenhouse experiment represented that the highest amount of phosphorous in the shoot (0.125 percent), root (0.0102 percent), and shoot dry weight (46.08 g/pot) belonged to the maize plants treated by phytase isolated from Aspergillus niger in the presence of 50 mg/kg of sodium phytate. Generally, the results showed that Aspergillus niger strain was more effective than the other two strains in both laboratory and greenhouse experiments. Phytase enzymes isolated from strains had positive effects on phosphorous concentration in a different parts of maize plant and growth characteristics of maize. Phosphatase and phytase generally improve the availability of phosphorus from different phosphorus sources. It should be kept in mind that phytase also increases the bioavailability of other essential minerals such as Ca2+, Mg2+, P, Zn2+, Fe3+, which are bound to phytic acid. Since the phytase production by fungi has been attained by different cultivation methods (solid-state, semisolid, and submerged fermentation) it seems that different cultivation methods can affect the phytase efficiency. Therefore, we suggested that phytates from different cultivation methods can be tested for phosphorus bioavailability from different sources.

The use of sewage sludge, which is mixed locally with poultry waste and is available at a relatively low cost, improves the circulation of nutrients and organic matter in the soil, reduces the concentration of CO2 in the atmosphere, and increases the level of soil organic carbon. Fertilization with this method is of particular importance in soils of arid and semi-arid regions that face erosion and organic matter reduction. However, there are concerns about the presence of essential and unnecessary heavy metals such as Cd, Cr, Cu, Ni, Pb, and Zn that enter the environment from domestic, light industrial, commercial and municipal wastewater sources and can lead to soil contamination and eventually enters the food chain through absorption, transport, and accumulation in agricultural and non-agricultural products and has threatened human and animal health. Phytoremediation is the cleaning up of polluted terrestrial areas and aquatic sites from heavy metal and organic contaminants by green plants. An appropriate plant for phytoremediation should ideally have a high ability to translocate contaminants into the plant shoot. However, the toxicity of the remains of these plants has become a severe problem for human health. Iran is an arid and semi-arid country and many soils face the problem of using animal manure sources with sewage sludge and the possibility of contamination with heavy metals. Farmers cultivate the barley plant (Hordeum vulgare L.) in these areas widely, and it has a significant role in the food chain of livestock and humans. Therefore, in this study, we evaluated the barley plant in terms of lead and chromium accumulation by increasing drought levels in the field.

It was a two-year field experiment with three irrigation levels (irrigation per 100 (control), 75 and 50% of field capacity). The amount of chromium and lead in soil and plant samples was measured using atomic spectroscopy with flame mode after extraction by digestion in acid. We used bio-concentration coefficients including root bioaccumulation factor ( ), shoot bioaccumulation factor ( ) and translocation factor ( ) to measure the plants bio-accumulation capacity. A plant with a root bioaccumulation factor bigger than one and a bio-translocation factor of less than one is suitable for plant stabilization of elements. In contrast, a plant with a shoot bioaccumulation factor and bio-translocation factor of more than one and root bioaccumulation factor of less than one is suitable for plant extraction of elements from the soil.

After barley harvest, the average concentration of lead and chromium in soil decreased by 23% and 17% compared to before harvest. The results of the analysis of variance showed that the effect of experimental years was significant on the concentration of chromium in the soil and the aerial part of barley and shoot bioaccumulation and root bioaccumulation factor of the same elements in the barley (p<0.05). The effect of drought was significant on the shoot and root dry weight, chromium concentration in both shoots and roots, lead concentration in shoots, lead and chromium shoot bioaccumulation factor, chromium root bioaccumulation factor, and lead bio-translocation factor (p<0.01) and chromium bio-translocation factor (p<0.05) but the interaction effect of year and drought was not significant on any of these traits. In all cases, the concentration of elements in the roots was higher than the aerial part, and with increasing drought stress, the concentration of lead in the roots remained constant but increased in the aerial parts while the concentration of chromium decreased. As the amount of drought increased, the shoot bioaccumulation factor increased for the lead but decreased for the chromium. The root bioaccumulation factor of chromium also decreased while the translocation factor increased for both elements, but the increase was more pronounced for the lead. Lead shoot bioaccumulation factor decreased linearly with an increasing dry weight of aerial parts (β = -0.86), but chromium shoot bioaccumulation factor increased (β = 0.62). Root dry weight predicted chromium root bioaccumulation factor (β = 0.85). The total plant dry weight regression model could predict the lead translocation factor (β = -0.89) and chromium transfer factor (β = -0.67).

In this experiment, the studied bioconcentration coefficients were all less than one. So, barley is an avoidant plant when encountered with lead and chromium in the soil, and in increasing drought conditions in the field, it does not translocate these toxic metals to the food chain.

The consumption of inorganic fertilizers in agricultural ecosystems led to the destruction of soil physical, chemical, and biological characteristics and severely affected the quality of the products. Therefore, the application of compost fertilizers in agricultural lands has been widely considered, and it has been mentioned as the best environmental measure. Rootstock plays a crucial role in the growth of citrus trees. Among all the nutrients needed by citrus, nitrogen has a vital role, and a large amount of this macronutrient is supplied in the soil every year. The release of nutrients from organic matter, especially nitrogen, is slower than the nitrogen release from chemical fertilizers. Rootstock affects the photosynthetic capacity of the transplanted cultivar, which is related to the annual carbohydrate redistribution and is a determining factor for vegetative growth and reproductive development. The growth, yield and fruit quality of cultivars are, therefore, strongly regulated by rootstock. In the recent study, the effects of compost and nitrogen fertilizers on common rootstocks in Mazandaran province, including citrange, citrumelo, and sour orange, were investigated. An experiment was conducted as a completely randomized design at Qaemshahr Horticultural Research Station. The treatments included sulfur granular compost (0, 2.5, 5, and 7.5%), produced by Mazandaran Wood and Paper Industries Company, and pure nitrogen (0, 20, 40, and 80 mg kg-1) in the form of ammonium sulfate. Vegetative growth, including plant height, crown diameter, and the number of leaves, were measured. Also, to study the changes in leaf nutrient concentration, leaf samples were collected, in July and the concentration of nutrients in leaf tissue was measured. A randomized complete block design was conducted at Qaemshahr Horticultural Research Station in 2017. The treatments included sulfur granular compost (0, 2.5, 5, and 7.5%), produced by Mazandaran Wood and Paper Industries Company, and pure nitrogen (0, 20, 40, and 80 mg kg-1) in the form of ammonium sulfate. One-year-old seedlings of the same size from citrange, citrumelo, and sour orange were planted in 7- kg pots containing arable soil and the treatments. The applied soil was analyzed, and its physical and chemical properties were determined. Irrigation of all pots until reaching the field capacity (weight method) was performed uniformly for all treatments. At the end of the growth period, vegetative growth parameters, including plant height, crown diameter, and the number of leaves, were measured. Also, to study the changes in leaf nutrient concentration, fully developed leaves samples were collected, in July and the concentration of nutrients was analyzed. Nitrogen was determined by the Kjeldahl method with a sulfuric acid-hydrogen peroxide mixture. Phosphorus by calorimetric, potassium using a flame photometer, and calcium, magnesium, iron, manganese, zinc, and copper were measured using the flame atomic absorption method. Results showed that the highest nitrogen concentrations in citrange and citrumelo seedlings were 2.92 and 2.97% due to 40 and 80 mg kg-1 N and 2.5% compost, respectively. In citrumelo rootstock, plant height increased with enhancing nitrogen application levels at different compost levels. Compost levels did not show a significant increase in citrange height, but the highest height growth was observed at 40 and 80 mg kg-1 nitrogen. In the sour orange rootstock, consumption of high levels of compost and nitrogen significantly reduced plant height. In all three rootstocks, the highest concentrations of potassium were observed in high levels of compost and no nitrogen application. The concentration of iron and zinc in citrumelo leaves increased with increasing compost levels. The trend was different in citrumelo so that consumption of 2.5% compost and 40 mg nitrogen fertilizer showed the highest concentration of leaf iron (151 μg g-1), while the application of 5% compost without nitrogen reduced the concentration of iron to 62.2 μg g-1. Changes in citrange zinc concentration were similar to citrumelo. In sour orange, iron concentration changed limitedly and ranged from 83.8 μg g-1 in 2.5% compost and 20 mg kg-1 nitrogen fertilizer to 61 μg g-1 in control. In this rootstock, the highest concentration of zinc was obtained from no compost application and 40 mg kg-1 nitrogen (28.14 μg g-1), whereas the lowest concentration of iron was observed in control. Citrange seedlings performed better in nutrient uptake than citrumelo and sour orange seedlings. Consumption of 5 and 7.5% levels of compost in sour orange rootstock reduced plant height and crown diameter and caused rosette, led to an increase in the number of leaves. The most effective level of nitrogen in sour oranges was 80 mg kg-1 nitrogen. Application of 80 mg kg-1 nitrogen and 2.5% compost, and 80 mg kg-1 nitrogen and 5% compost led to the highest number of leaves in citrumelo and citrange rootstocks, respectively. According to vegetative growth and concentration of nutrients data, especially from the nitrogen concentration point of view, maximum vegetative growth was obtained in citrumelo rootstock from 2.5% compost and 40 mg kg-1 nitrogen treatment and in citrange and sour orange rootstocks from 2.5% compost and 80 mg kg-1 nitrogen treatment.

One of the most important causes of land degradation and reduced fertility is soil erosion, a severe threat to human welfare and food security. With the intensification of erosion and sediment transport in the watershed, water quality is reduced, and sediment production and flood risks are increased. The consequences of soil impoverishment cause irreparable damage, including the abandonment of farms, increased migration, economic, social, and political problems. In this regard, paying attention to soil and water resources conservation is one of the most necessary measures to control erosion. So that the performance of natural ecosystems increases through conserving the soil and preventing the occurrence and intensification of erosion. Therefore, it is essential to know different stages of erosion and evaluation of the factors governing it in properly managing soil and water resources in a watershed. So far, various biological methods and structures are used to control soil and runoff loss in watersheds. Since biological methods are based on ecosystems' conditions, it is essential to control soil erosion in the early stages. In recent years, extensive methods for the conservation of soil and water resources have been introduced and used in practice. Therefore, one of the most important methods of protecting soil and water resources is the use of biological methods in terms of low use of tillage operations, limited intervention, and manipulation in nature, cost-effectiveness, and also better efficiency than structural measures. However, the biological management of soil erosion has not yet been welcomed by executive experts due to the lack of a proper implementation model.

The present study was conducted to investigate biological erosion management in the Gavoshan Watershed, Iran, due to distributed and manageable erosion and the available information. The Gavoshan Watershed, with an area of 7736 ha, the mean annual precipitation of 339 mm, the minimum and maximum elevations of 1635, and 2455 meters above sea level, is located in Kermanshah Province. After determining the erosion status, climatic characteristics, and plant growth conditions, the executive procedure of biological management of the region was proposed.

The results showed that surface erosion is predominant in the area, and therefore the suitability of the conditions for bio-management measures was confirmed. While reporting the prevalence of sheet erosion, the results emphasized the erosion status in the low and moderate classes and the ability to perform biological approaches in the watershed based on the climatic-agricultural map. The results further showed that according to the climatic-agricultural map, the whole study watershed was divided into five categories. In this regard, the second category with an area of 3421 ha had the highest, and the fifth category with 82 ha had the lowest areas. Finally, after determining the area of different land-uses and according to the maps of soil erosion and climatic-agricultural conditions as well as ombrothermic and hetherograph diagrams, suitable rangeland species were selected and suggested for each climatic-agricultural category based on the expected characteristics of elevation, precipitation, temperature, phenology and adequate role in soil conservation. Finally, the executive plan of biological management of soil erosion in the Gavoshan Watershed was presented based on phytosociology and relevant ecological expectations. Since bio-management measures are applicable in rangelands with moderate and poor vegetation conditions, the good rangelands were not prioritized for the planning. Accordingly, moderate and weak rangelands with an area of about 4219 ha, i.e.> 54%, of the watershed were considered for biological activities. It is expected that by taking biological measures, erosion control will be done in the early stages, and by increasing the vegetation level in 54.63% of the watershed, in addition to controlling soil erosion or at least stopping it in the early stages, carbon sequestration conditions, nitrogen fixation, and increase soil fertility. The use of endemic species in this watershed would facilitate ecological balance and at the same time protect the basic resources of water, soil, and vegetation by increasing the level of ground cover.

Biological management is a new approach in soil and water resource sustainable management that inhibits soil loss in the early stages of erosion and prevents the destruction of ecosystems. The results of the present study are anticipated to meet the expected needs in the protection of soil and water resources in similar watersheds in the west of the country. The results of the present study can be used in soil and water resources management in the western regions of the country with similar ecological conditions. Although the proposed approach can be used in most parts of the country rangelands, appropriate field studies and continuous monitoring of the proposed function will be necessary to provide comprehensive and integrated conclusions for soil and water resources management.

Understanding the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Over the past two decades, the use of data mining approaches in spatial modeling of soil organic carbon using machine learning techniques to investigate the amount of carbon to soil using remote sensing data has been widely considered. Accordingly, the aim of this study was to investigate the feasibility of estimating soil organic matter using satellite imagery and to assess the ability of spectral and terrestrial data to model the amount of soil organic matter.

The study area is located in Lorestan province, and Sarab Changai area. This area has hot and dry summers and cold and wet winters and the wet season starts in November and ends in May. A total of 156 samples of surface soil (0-30 cm) were collected using random sampling pattern. Data were categorized into two categories: 80% (117 points) for training and 20% (29 points) for validation. Three machine learning algorithms including Random Forest (RF), Cubist, and Partial least squares regression (PLSR) were used to prepare the organic soil carbon map. In the present study, auxiliary variables for predicting SOC included bands related to Lands 8 OLI measurement images, and in order to reduce the volume of data, the principle component analysis method (PCA) was used to select the features that have the greatest impact on quality.

The results of descriptive statistics showed that soil organic carbon from 0.02 to 2.34% with an average of 0.56 and a coefficient of variation of 69.64% according to the Wilding standard was located in a high variability class (0.35). According to the average amount of soil organic carbon, it can be said that the amount of soil organic carbon in the region is low. At the same time, the high value of organic carbon change coefficient confirms its high spatial variability in the study area. These drastic changes can be attributed to land use change, land management, and other environmental elements in the study area. In other words, the low level of soil organic carbon can be attributed to the collection of plant debris and their non-return to the soil. Another factor in reducing the amount of organic carbon is land use change, which mainly has a negative impact on soil quality and yield. In general, land use, tillage operations, intensity and frequency of cultivation, plowing, fertilizing, type of crop, are effective in reducing and increasing the amount of soil organic carbon. Based on the analysis of effective auxiliary variables in predicting soil organic carbon, based on the principle component analysis for remote sensing data, it led to the selection of 4 auxiliary variables TSAVI, RVI, Band10, and Band11 as the most effective environmental factors. Comparison of different estimation approaches showed that the random forest model with the values of coefficient of determination (R2), root mean square error (RMSE) and mean square error (MSE) of 0.74, 0.17, and 0.02, respectively, was the best performance ratio another study used to estimate the organic carbon content of surface soil in the study area.

In this study, considering the importance of soil organic carbon, the efficiency of three different digital mapping models to prepare soil organic carbon map in Khorramabad plain soils was evaluated. The results showed that auxiliary variables such as TSAVI, RVI, Band 10, and Band11 are the most important variables in estimating soil organic carbon in this area. The wide range of soil organic carbon changes can be affected by land use and farmers' managerial behaviors. Also, the results indicated that different models had different accuracy in estimating soil organic carbon and the random forest model was superior to the other models. On the other hand, it can be said that the use of remote sensing and satellite imagery can overcome the limitations of traditional methods and be used as a suitable alternative to study carbon to soil changes with the possibility of displaying results at different time and space scales. Due to the determination of soil organic carbon content and their spatial distribution throughout the region, the present results can be a scientific basis as well as a suitable database and data for the implementation of any field operations, management of agricultural inputs, and any study in sustainable agriculture with soil properties in this area. In general, the results of this study indicated the ability of remote sensing techniques and random forest learning model in simultaneous estimation of soil organic carbon location. Therefore, this method can be used as an alternative to conventional laboratory methods in determining some soil characteristics, including organic carbon.

In recent years, the production of healthy foods through environmentally friendly methods has received much attention. Spinach is a vegetable plant rich in minerals and vitamins which is used in green and cooked forms. Thus, healthy production of this plant with the greatest quantitative and qualitative yield is of particular importance. Weeds as unwanted plants in spinach fields can damage this plant significantly. Nevertheless, spinach is severely sensitive to different herbicides. The goal of this study was to investigate the effect of plant growth promoting rhizobacteria (PGPR), filter cake and metribuzin herbicide on growth and mineral nutrition of spinach plant. In this study, the growth and nutritional parameters of spinach interact with PGPR, filter cake and metribuzin herbicide was also aimed. The spinach seeds (Spinacia oleracea L. Varamin cultivar) were sown in pots containing 40% field soil and 60% sand (10 seeds in each pots). To investigate the impact of PGPR isolates and filter cake on concentration of macronutrients (K, Ca, Mg, and P), micronutrients (Cu, Zn, and Fe) and leaves dry weight, Pseudomonas protogenes CHA0 (CHA0) as a reference strain, P. alloputida RUM14 (RUM14) which was collected from Iranian field soil and 3% by weight of fresh filter cake (F3%) were used. Spinach seedlings were inoculated for 14 days with 50 mL of bacteria strains suspension with optical density one (OD600=1). 3% by weight of filter cake were mixed to soil of pots before sowing the seeds. Metribuzin herbicide at three levels (0 (H0), 50 (H1) and 100 (H2) grams per hectare) were used. The effects of PGPR, filter cake and metribuzin herbicides and their interactions were also studied (CHA0 + F0 + H1, RUM14 + F0+ H1, CHA0 + F0 + H2, RUM14 + F0 + H2, B0 + F3% + H0, B0 + F3% + H1, B0 + F3% + H2, CHA0 + F3% + H1, RUM14 + F3% + H1, CHA0 + F3% + H2, RUM14 + F3% + H2). The experiment had a randomized complete block design with three replications. The treatments (3 metribuzin herbicide × 2 filter cake × 3 PGPR) were arranged in factorial combination. The statistical analysis was performed using Duncan’s multiple range test at 5% probability level. Statistical analysis revealed that the application of PGPR (CHA0 and RUB14), filter cake, and their interaction increased tissue plant concentration of macronutrients, micronutrient and leaf dry weight of spinach plant. Statistically, the highest concentration of P, K, Ca, and Mg macronutrients (5583.30, 83000.00, 10886.70, 10766.60 mg kg-1 dry matter, respectively), Cu, Zn, and Fe micronutrients (22.73, 73.00, and 221.36 mg kg-1 dry matter, respectively) and dry weight of leaves (8.76 g) was observed in treatment of combination of PGPR and filter cake. The application of Metribuzin herbicide led to decline the concentration of macronutrients, micronutrient, and leaf dry weight of spinach plant. The decline increased with increasing herbicide concentration. The lowest concentration of P, K, Ca, and Mg macronutrients (3233.30, 48867.00, 6403.30, and 6283.30 mg kg-1 leaf dry weight, respectively), Cu, Zn, and Fe micronutrient (4.40, 19.50, and 132.66 mg kg-1, respectively), and leaf dry weight (2.83 g) was observed in B0+F0+H2 treatment (using just herbicide 100 g ha-1). However, the detrimental effect of herbicide on leaf dry weight and mineral nutrition of spinach plant were alleviated using the PGPR (CHA0 and RUB14) and filter cake (F3%) either alone or together (RUM14+F3%, CHA0+F3%). Statistically, the greatest alleviation of the detrimental effect of herbicide was observed in the treatment of RUM14+F3%. The results of this research showed that inoculation of spinach with Pseudomonas PGPR (P. protogenes CHA0, P. alloputida RUM14) with and without filter cake not only improved the growth and mineral nutrition of spinach plant, but also alleviated the detrimental effect of herbicide in the plant. In general, the proper function of PGPR and filter cake in spinach plant growth is due to 1- Supplying more nutrients to the spinach plant due to filter cake rich in nutrients 2- The ability of Pseudomonas bacteria to induce resistance of the plants to stress and supply of some nutrients such as iron due to its ability to produce siderophore 3- Supply of food by filter cake for further growth of PGPR and the possibility of increasing the population of these bacteria. 4- Filter cake rich in organic matter can improve the physical and biological properties of the soil and can provide the better conditions for plant growth and nutrition. The results of this research showed that P. alloputida RUM14 and filter cake can be used as biological and organic fertilizers.

It is possible to guide the agricultural experts to achieve a suitable genotype and adapt to climatic conditions in proportion to the length of the modified growing season by identifying the impact of climate change in recent years on the cumulative rate of degree-days of plant growth. This will prevent the waste of capital and agricultural inputs and ultimately prevent the reduction of the final crop due to the mismatch of genotype-crop with the current climate. In the present study, an attempt has been made to study and compare the trend in the start and end of the growing season, the growing season length (GSL), and growing degree-days(GDD) during 1959-2018 in the elevated and coastal areas of Iran.

For this study, the daily temperature of 27 synoptic stations were used including 19 stations in elevated areas and 8 stations in coastal areas during 1959-2018. The first day with a minimum daily temperature equal to or greater than 0, 5, and 10 °C was considered as the start of the growing season (SGS). Moreover, the first day after the start of the growing season which has a minimum daily temperature of less than 0, 5, and 10 °C was considered as the end of the growing season (EGS). Trend analysis was performed in time series of GSL and GDD based on thresholds of 0, 5, and 10 °C using the Mann-Kendall test. To compare the results, the statistical period of 60 years was divided into two periods of 30 years (1959-1988 and 1989-2018). In both periods, the statistical characteristics of the GSL and GDD based on the three thresholds mentioned in coastal and elevated areas were surveyed and compared. In this study, deviation from the mean was used to complete the study of changes in the GSL. This index shows the scatter of data around the mean.

The GSL extension came from both the advance in SGS and the delay in EGS. Comparison results of the two 30-year periods (1959-1988 and 1989-2018) showed that during 1989-2018, in most stations the GSL has increased. During this period, based on 0 °C, the earliest and latest SGS were on February 24 and April 30 in Yazd and Shahrekord, respectively. Accordingly, the earliest and latest EGS were on October 15 and December 11 in Shahrekord and Gorgan, respectively. Based on 5 °C, the earliest and latest SGS were on February 10 and June 2 in Abadan and Gorgan, respectively. Accordingly, the earliest and latest EGS on September 17 and December 6 were at Shahrekord, Bam, and Abadan, respectively. Based on 10 °C, the earliest and latest SGS was on February 11 and June 20 at stations, respectively. Accordingly, the earliest and latest EGS were on August 27 and December 8 in Shahrekord and Bushehr, respectively. The shortest and longest GSLs based on all three thresholds of 0, 5, and 10 °C were Shahrekord and Bandar Abbas, respectively. The highest and lowest coefficient of variation of GSL were 20.8% in Zanjan and 4.9% in Bandar Abbas, respectively. Based on 0, 5, and 10 °C, the lowest GDDs in GSL are 3233, 1767, and 880 °C.d, respectively, and all of them were obtained at Shahrekord. On the other hand, the highest GDD0, GDD5, and GDD10 in GSL were 6783, 7372, and 5761 °C.d, respectively, in Yazd, Abadan, and Bandar Abbas. The most significant trend in GSL was in Zanjan, Zahedan, and Khorramabad.

Examination of changes in the GSL indicates the existence of a significant trend in a limited number of stations. Also, with increasing the threshold from 0 to 5 and from 5 to 10 °C, there is a significant decreasing trend in more stations. At the threshold of 10 °C a significant and decreasing trend of GSL was observed in Urmia, Sanandaj, Khorramabad, Birjand, and Bandar Abbas stations, In following, a significant increasing trend was observed in Tabriz, Tehran, Kermanshah, Isfahan, Yazd, and Bushehr stations. The results of the studies showed fewer changes in the time series of the GSL based on thresholds of 0 and 5 °C in the statistical period of 1989-2018. On the other hand, the results showed that the GSL trend is significant in more stations in the recent period based on the threshold of 10 °C. Deviation from the average GSL in coastal areas was greater than the elevated areas so that the GSL based on 10 °C in both areas increased with greater slope and continuity. This increasing trend of deviation from the average in the coastal areas from the early '70s and the elevated areas from the early '90s and continues until now. In this regard, Bandar Abbas station and then Bushehr station had the longest GSL, and Shahrekord station had the shortest GSL among other stations which has been studied. Comparison of GDDs of the GSL during 1989-2018 showed the decrease of GDDs from south to north and from west to east of the country. Accordingly, in the southern stations of the country, the conditions for tropical plants (threshold of 10 °C) have become more suitable than the cold stations of the west and northwest, Time series analysis of the average annual GDDs based on the three thresholds during 1989-2018 showed a significant increasing (positive) trend in 93% of the stations. During the second 30-years period, Shahrekord and Shiraz stations did not show a significant trend in all three mentioned thresholds. However, the analysis of the annual average of GDDs during 1959-1988 showed the trend in 41% of the stations. According to the results of this study, it can be concluded that in cold regions, due to the increase in GDDs, the supply of cooling units for plants with certain cooling needs is more difficult. In the south of the country, as the total required GDD is achieved earlier, the GSL gets shorter, and therefore less dry biomass will accumulate in the product. This likely leads to a reduction in crop yields in this part of the country.