نشریه مدیریت خاک و تولید پایدار
سال سیزدهم شماره 1 (پیاپی 43، بهار 1402)

The most obvious problem of calcareous soils is lack of plant available iron. Nano fertilizers are a suitable option to meet the needs of the plant with the high efficiency. The aim of this study was the green synthesis of nanocarbon dot iron fertilizers in two forms, uncoated and coated with polylactic acid polymer, and the incubation study of these fertilizers in a period of one month in a calcareous soil.

The green synthesis of iron nano carbon dot sample was done using lemon juice (as the carbon base of fertilizer) and Ferrous sulfate heptahydrate by hydrothermal method and the iron nano carbon dot sample was synthesized by polylactic acid polymer coating and test samples after synthesis to confirm the loading of iron on the carbon dot sample and also to confirm the successful coating of the synthesized iron nano carbon dot fertilizer by means of UV, XRD, Fluorescent Spectrophotometric, TEM, FESEM, EDAX, FTIR, DLS and Zeta Potential were characterized. In order to investigate the effect of synthesized iron nanocarbon dot on the availability of iron in a calcareous soil, an incubation experiment was conducted in a completely random design in 3 replications. The treatments include control (without nano carbon dot application), iron sulfate, sequestrin (commercial) and synthesized iron nano carbon dot loaded with iron (as two separate treatments without coating and coated with polylactic acid polymer) at levels 5, 10 and 20 mg Fe kg-1 soil (total of 9 treatments with 3 replications). At the end of the incubation period (720 hours), the extractable iron content of the soil was determined with DTPA. Also, in order to investigate the changes in the extractable iron of soil with DTPA with time, the amount of iron extracted in soil with DTPA in three times of 3, 360 and 720 hours in control treatments without fertilizer, treatment of 5 mg kg-1 soil iron soil from different sources of iron were compared with each other.

The successful loading of iron on the surface of nano-carbon iron dots without coating and coated with polylactic acid polymer was confirmed by XRD, UV-VIS, FTIR and scanning and transmission electron microscopes. The amount of total iron in the uncoated sample was equal to 4.98% and in the sample coated with polylactic acid it was equal to 1%. The results of the incubation showed that extractable iron in the soil with DTPA increased significantly.The highest concentration of iron in the soil at the end of 720 hours is related to the sample coated with iron nano carbon dot with polylactic acid polymer with an iron concentration of 20 mg kg-1 equal to 9.58 mg kg-1. Also, by examining the changes in iron release in treatments with a concentration of 5 mg kg-1 in three time periods of 3, 360 and 720 hours, it was observed that the coated treatment caused a significant increase in iron compared to the iron sequestrin treatment. Iron sequestrin treatment after 720 hours compared to the first 3 hours increased by about 60% (from 5.19 to 8.28 mg kg-1), while the amount of iron extracted with DTPA in the nano carbon dot iron coated treatment In this period of time, it increased by about 400% (from 1.36 to 6.63 mg kg-1).

According to the results of the research, it can be said that among the experimental treatments regarding the slow release of iron, the sample coated with natural and biodegradable polylactic polymer with an iron concentration of 20 mg kg-1has the highest iron release compared to had other treatments,

Background and Due to the importance of soil quality in life and environment, various evaluation methods have been proposed to describe the effect of pollutants such as heavy metals on soil quality. In this study, we evaluated the quality of the soil around Zanjan lead and zinc complex located in Zanjan city by using the mathematical model of the improved weighted index and compared it with the results of Nemerow indices and pollution load index. In this study, the results of 71 soil sampling stations around Zanjan lead and zinc complex, located in the northwest of Iran, by inductively coupled plasma emission spectrometry device for reading the concentration of heavy metals Lead, Zinc, Arsenic, Cadmium, Thallium, Barium, Antimony, Vanadium, Cobalt, Molybdenum, Nickel and Copper were used. Soil acidity was also analyzed. In this approach, during the calculation of the improved weighted index, weights were assigned to different heavy metals using statistical tools, including hierarchical cluster analysis and principal component analysis. The result of the index quantitatively determines the amount of pollution. Based on the improved weight index, 19.9% of the samples were in moderate pollution and 4.2% of the samples were in severe pollution, and the other samples were without pollution or with little pollution. According to the pollution load index, 5.8% of the samples are in moderate pollution and 2.8% are in severe pollution, and according to the pollution index, 19.9% of the samples are in moderate pollution and 42.2% are in severe pollution. Comparing the correlation of the results obtained from the model with the weighted improved index with the pollution load index, the correlation value is 0.907, and with the Nimro index, the correlation value is 0.701, which indicates that it is closer to the pollution load index. The results of the improved weight index showed that the heavy metals Zinc, Lead, Cadmium and Arsenic are of anthropogenic origin and as a result of the industrial activities of Zanjan lead and zinc complex. While heavy metals Barium, Vanadium, Thallium, Molybdenum, Cobalt, Copper, Nickel and Antimony are of earth origin. The results showed that the improved weighted index has a good match with the previous indices and can be used in wide ranges. It also overcomes the shortcomings of the previous indicators and can be used as a new model to evaluate soil pollution and soil ecological risk. This index can be used to identify and determine possible sources of pollution.

Water infiltration to soil play an important role in irrigation management, storage moisture in soil especially in dry and semi-dry area and increasing agronomy yield. Understanding water infiltration to soil is of important in designing and applying water conservation methods, flood and runoff control and soil erosion management. Additionally, accurately measuring water infiltration to soil in different times is more important for predicting water storage in root zone, irrigation designing and planning and agronomy management. In other hand, water infiltration to soil is a base for precision agriculture, therefore, producing accurate maps for water infiltration to soil play an important role in land management and applying precision agriculture. Modeling soil water infiltration at the field scale with ruler of calcareous, saline and sodic conditions is important for a better understanding of infiltration processes in these soils and future of infiltration modeling. The present study aimed for estimating water infiltration to soil at different times using soil spatial prediction functions and spatial estimators.

in present study, 72 soil samples were collected using a random sampling method in Marvdasht plain, Fars Province. In selected points, soil bulk density, sand silt, clay, pH, electrical conductivity, calcium carbonate, solution sodium, solution calcium and magnesium and organic carbon contents. For measuring water infiltration to soil, the double ring method were used. Multiple linear regression (MLR), artificial neural network (ANN) and spatial estimators were used for deriving soil spatial prediction functions models between water infiltration to soil in different times including 5, 10, 20, 45, 90, 150, 210 and 270 min. In this study, the readily available soil properties and auxiliary variables such as remote sensing and topography data were used in soil spatial prediction functions.

The results of evaluating regression and artificial neural networks models based on the mean error (ME), coefficient of determination (R2) and root mean square error (RMSE) criteria in testing phase were showed that the developed artificial neural network models in present study performed better than multiple linear regression models in water infiltration to soil prediction at different times. Moreover, the results showed that the combined estimators (artificial neural network - Kriging) performed better than ordinary kriging model for estimating water infiltration to soil.

In totally, the results of this study showed that the applying soil spatial prediction functions (using auxiliary variables such as remote sensing data and topography data with the readily available soil properties) had a great potential to predict spatial estimation of water infiltration to soil at most considered times.

The soil characteristics of each region are affected by the topography factor. This factor has direct and indirect effects on the physicochemical properties of soil and even nutrient concentrations. Potassium is one of the most important elements in plant nutrition and is the second major nutrient absorbed by plants. Potassium exists in the soil in four forms, including soluble, exchangeable, non-exchangeable and structural. Many studies conducted on different potassium forms in relation with mineralogy, soil characteristics and classification, climate, and especially topography, but investigating the effect of different physiographic units and different levels of classification had been neglected. Therefore, this study was aimed to investigate the effect of different levels of classification and topography (physiographic units) on the potassium status of Sepidan soils in Fars province.

In order to investigate the effect of topography on the potassium status of Sepidan soils in Fars province, toposequence was applied in Sepidan region of Fars province. After digging and describing the selected profiles in each identified physiographic unit, samples were taken and physical and chemical properties of soils were measured by conventional methods. The different forms of potassium were measured by summary method; and using SPSS16 statistical software and LSD statistical test, the significance of differences in the amount of different forms of potassium were determined at different classification levels and different physiographic units.

Investigation of studied pedons showed that soils were classified as Entisols, Inceptisols and Alfisols based on 2014 taxonomy classification system. Three suborders, four great groups and subgroups were identified. In the study area, soluble, exchangeable, non-exchangeable, structural and total potassium had a mean of 0.96, 279, 510, 3792 and 4583 mg kg-1, respectively. The mean of soluble, exchangeable, non-exchangeable, structural forms and total potassium related to different physiographic units were reported 0.73, 421, 1360, 1405, 15833 mg kg-1 in the colluvial-alluvial fan, 1.21 , 236, 565, 2803 and 3603 in piedmont plain, 0.76, 352, 436, 2071, 2860 mg kg-1 in flood plain, 0.73, 270, 372, 2249, 2893 mg kg-1 in river terrace, 0.91, 321, 656, 2541, 3520 mg kg-1 in alluvial plain and 1.17, 172, 88, 2292, 2554 mg kg-1, respectively. Total potassium and also different forms of potassium except soluble potassium in different physiographic units were significantly different from each other (P<0.05). In relation to the effect of different classification levels, there were significant differences (P<0.05) between exchange and non-exchange forms in all the studied levels.

The present study showed that topography in the form of different physiographic units by controlling the amount of humidity, received sunlight and also the speed of weathering lead to differences in physicochemical properties and classification of soil. The set of these factors led to observe significant differences in the amount of different forms of potassium in different physiographic units. Due to the lack of application of very significant differences in different classification levels up to the subgroup level, it is suggested that for having better monitoring of the potassium element to obtain sustainable agriculture, at least the classification of soils at the family level should be performed so that the differences are better be understood. Also, it is worth mentioning that the type of parent material, climate, topography and other environmental conditions can affect the accuracy of the study in different areas, which should not be neglected when choosing the accuracy of the study.

Zagros forests play an essential role in providing groundwater resources, air conditioning, soil protection and preventing erosion, and providing wildlife habitat. Today, the ecosystem of these forests has become completely fragile due to improper exploitation and destruction. This study was conducted in areas of Zagros forest in Kermanshah province that were included in the implementation of the protection plan, including Sorkhak and Tappeh Goleh in Islamabad and Qeshlaq in Ravansar. The main purpose of this study was to evaluate the implementation of the forest conservation plan on soil properties.

For this purpose, composite soil samples were collected by random-systematic method from the mentioned area and their respective control area, and their physical, chemical, and biological properties were measured. Soil characteristics in Tappeh Goleh, Sorkhak and control sites were analyzed by one-way analysis of variance and Qeshlaq soil characteristics were analyzed by T-test. The soil samples collected from the forest were air-dried in the laboratory environment and sieved (2 mm). Then their physical and chemical properties (pH, EC, bulk density, and soil organic carbon content) were measured. Soil samples were collected with sterile equipment and sieved through a 4 mm sieve. Fresh and moist soil was kept at a temperature of 4 °C for soil biological tests (basal soil respiration, metabolic quotient, and microbial biomass carbon).

The results showed that no statistically significant changes in soil EC and pH were observed in all study areas. The amount of organic carbon in Sorkhak was significantly higher. Among the measured biological properties of soil, no significant change was observed in organic carbon mineralization in all study areas. However, microbial biomass carbon and soil metabolic quotient in Sorkhak were significantly higher than those in control and Tappeh Goleh areas.

The results of this study showed that the forest protection plan if properly implemented in the field (Sorkhak area) will be able to revive some soil quality indicators. The provisions of forest protection management and the process of soil regeneration in these forest lands should be investigated. Among the studied indicators, soil organic carbon and microbial biomass carbon were among the indicators that responded well to the correct and complete implementation of the forest protection plan, and we have witnessed the improvement of these parameters in managed lands. This suggests that biological soil quality indicators are more sensitive to responding to land management and respond more quickly to these changes.

The use of potassium solublizing bacteria (KSB) in soils containing an accumulation of insoluble and non-absorbable potassium by plants can help further solubility of these potassium mineral sources in the soil and thus the uptake of this element by the plant. Also, the application of KSB on the yield and yield components of wheat can prevent the overuse of potassium chemical fertilizers and instead predispose soil conditions for the development of plant nutrition. Therefore, the aim of this study was to determine the effect of application of KSB in comparison with the application of common potassium chemical fertilizers in the country's farms on quantitative and qualitative traits of wheat grain. To study the effect of application of KSB on the yield of wheat cultivars in southern Kerman, Iran, this experiments were performed over two years in the form of split plots in a randomized complete block with three replications in the research farm of Islamic Azad University of Jiroft in loamy sand soil. Various wheat cultivars including Chamran 2, Barat and Khalil were located in the main plot and sources and amounts of calcium were at four levels: 1. Control (without fertilizers) 2. Application of chemical sulfate potassium (at the rate of 200 kg / ha based on soil test results 3. Half of the recommended chemical fertilizer at the rate of 100 kg/ha + consumption of KSB from the source of Potabarvar biofertilizer at the rate of 100 g/ha 4. KSB (at the rate of 100 g/ha as the seed treatment), were placed in sub-plots. The results showed that wheat cultivars showed different reactions to different levels and sources of fertilizer during the two years of the study. The highest grain yield in Chamran 2 cultivar was obtained by applying KSB at the rate of 8 t/ha. Application of KSB alone in Khalil cultivar and application of potassium solfate along with KSB in Barat cultivar produced 7.49 and 7.6 tons of grain per hectare, respectively, Whithout significant different by 8 tons per hectare. Application of KSB could significantly improve grain yield, spike length, number of grains per spike, grain nitrogen percentage and grain protein percentage. The results showed that the applied KSB improved the quantitative and qualitative traits in wheat grain. Although the application of potassium sulfate based on soil test results also had an effective role to increase wheat traits, but it is suggested that in agriculture based on sustainability in agriculture, potassium biofertilizer should be used with half of the recommanded potassium sulfate fertilizer. In addition to reducing the consumption of chemical fertilizers, this can be effective in reducing wheat production costs and farm health.