نشریه پژوهشهای خاک (علوم خاک و آب)
سال سی و هفتم شماره 4 (زمستان 1402)

The soil units in the irrigated plains across the country were identified based on previous soil studies, satellite images, land use maps, and agricultural-climatic zones. The purpose was to determine the land potential for irrigated cultivation of industrial crops such as sugar beet, cotton, safflower, and sugarcane. Then, the FAO framework and the square root parametric method were used to evaluate the land suitability for irrigated cultivation of these crops. The survey results revealed the land suitability classes for four crops under irrigated cultivation: sugar beet, cotton, safflower, and sugarcane. For sugar beet, out of 4 million hectares (Mha) of surveyed land, 1.23 Mha were in class S1 (highly suitable), 1.5 Mha in S2 (moderately suitable), 740 thousand hectares (Tha) in S3 (marginally suitable), 390 Tha in N1 (currently suitable), and 420 Tha in class N2 (permanently suitable). For cotton, out of 2.4 Mha of surveyed land, 75 Tha were in class S1, 671 Tha in S2, 895 Tha in S3, 420 Tha in N1, and 340 Tha in N2. For safflower, out of 2.2 Mha of surveyed land, 38 Tha were in class S1, 56 Tha in S2, 1.3 Mha in S3, 363 Tha in N1, and 398 Tha in N2. For sugarcane, out of 615 Tha of surveyed land, 6 Tha were in class S1, 18 Tha in class S2, 193 Tha in class S3, 98 Tha in class N1, and 300 Tha in class N2. The data was statisticaly analysed and the results indicated that the the land suitability classes were classified with resonable accuracy. The following factors were the main limiting characteristics that limited cultivation of the four crops under irrigation: For sugar beet: soil pH, salinity, alkalinity, and drainage; for cotton: climate, slope, salinity, alkalinity, lime and gypsum; for safflower: pH, drainage, salinity, alkalinity and climate; and for sugarcane: salinity, alkalinity, drainage and slope. Due attention to the prepared land suitability maps of the aforementioned crops would facilitate cultivation management for farmers and planners.

The quantity and quality of sugar beet root impurities, especially sodium, is one of the factors affecting root quality and extraction coefficient of sugar (ECS) from sugar beet. Various factors such as soil conditions, application time, and quantity of different fertilizers have effects on the amount of sugar that can be extracted in the factory. Data and results obtained from researches conducted during 1997-2021, which were published in 30 final reports in Sugar Beet Seed Institute (SBSI), were analyzed in order to investigate the factors that affected sugar beet impurities and its quantitative and qualitative traits. The data of these reports were created in a database containing 480 rows and 26 columns. The data corresponding to the investigated treatments included manure, bacterial products and amino acids, and time and amount of nitrogen application were extracted from the database. Then, the reaction ratio (the ratio of trait changes in each treatment to the control in the same experiment), average of the reaction ratio, standard deviation, and the significant effects of the contribution of each factor to sugar beet root traits were determined. The results of the meta-analysis studies showed that consumption of 60 t/ha of manure, 150-200 kg/ha nitrogen, and the split application of 25% of N-fertilizer before planting, 50% during thinning, and 25% during the second thinning, increased root, sugar, and white sugar yields significantly, while sodium content in sugar beet roots did not change significantly. Excessive use of nitrogen (i.e. 250-300 kg/ha) and use of all nitrogen fertilizer after planting increased root sodium content by, respectively, 18% and 7.5%, while reducing yield. The bacterial product and amino acid only increased the sugar content by about one percent.

Pyrolysis is important as an economical and environmentally friendly technology to facilitate recycling and reduce the environmental risk of sewage sludge. The aim of this research was to study changes in the structure, specific surface area, and pores of biochar, and to evaluate the risk of heavy metals contamination due to pyrolysis of sewage sludge. Sewage sludge biochar was prepared under limited oxygen conditions at temperatures of 300, 400, 500, 600 and 700 0C. Specific surface area and pore analysis were determined using the N2 adsorption isotherm, BET equation, and scanning electron microscopy (SEM) images. The risk of lead and zinc contamination was assessed using the BCR fractionation method and contamination factors. The results showed that the specific surface of biochar under the influence of temperatures of 400, 500, 600 and 700 0C was 2.65, 3.65, 8.38, and 5.57 times that of sludge, respectively. By comparing the total volume and the average pore diameter, biochar had more porosity than sewage sludge. The main pores in the biochar were meso (8.34-19.98 nm). The morphological structure of the sewage sludge was smooth and irregular, and, in contrast to the biochars, they had more porous and uneven surface. The presence of honeycomb-shaped structures was detectable at high temperatures, especially at 600 ° C. The toxic response factor (Er) for sewage sludge and biochar was low. By converting the sewage sludge to biochar, the contamination factor (Cf) of Zn and Pb was reduced by more than 50%. The conversion of sewage sludge to biochar increased the specific surface, increased porosity, and stabilized carbon in the form of aromatic compounds. Due to the reduction of metal contamination factor and the possibility of environmental risk in biochar, these materials can be used as adsorbents or modifiers in different environments.

Measuring the moisture content of surface soil, as one of the most important components of the water cycle, plays a significant role in the optimal management of water and soil resources. The aim of this research was to evaluate the accuracy of spectral indices and Sentinel-2 satellite images for estimating soil moisture during the period of 2020-2022 in the Telo region, Tehran Province, Iran. The data used included the daily Sentinel-2 images, 30-Meters Digital Height Model and field measurements using the TDR. The spectral indices used in this study included NDWI, MNDWI, NDVI, NDMI, and SAVI. Analysis of the amount of surface soil moisture recorded showed that the average soil moisture in the area was 14.07%. In terms of time, the maximum amount of soil moisture with a value of 40% was recorded on December 18, 2020, and the minimum value was recorded with a value of 1.3% in early June, 2021. Analysis of the trend of soil moisture values showed that the minimum soil moisture values were recorded in the warm season due to the increase in temperature and evaporation and the decrease in precipitation, while the maximum soil moisture was recorded in the cold season with the beginning of the rainy season in the region and the decrease in temperature. Investigating the relationship between soil moisture values recorded using TDR and spectral indices calculated on Sentinel-2 images showed that there was no clear and significant relationship between NDVI and SAVI indices with TDR soil moisture values; and the maximum correlation was obtained for NDWI indexes with a correlation value of 0.23, NDMI with a value of 0.35 and MNDWI index with a correlation value of 0.59.

Forests have important role for ecosystem maintenance, and deforestation is one of the factors in degradation of soil quality.  In this study, using multivariate analysis, soil quality index was evaluated in three land uses including forest, grassland, and cropland at two depths of 0-10 and 10-20 cm in Sidasht of Guilan Province, Iran. The weighted additive soil quality was calculated using two methods (1) Minimum data set (MDS1) and (2) Revised minimum data set (MDS2). Also, each feature’s variance and communality and two scoring methods, namely, linear and non-linear, were compared and evaluated. In MDS2, the effects of land use on soil quality index (SQI) indicated that the mean values calculated by the non-linear scoring method was significantly more precise than the linear one. Soil quality indices in forest and grassland had the maximum values when compared to cropland. SQIW2-MDS2-NLS had the highest sensitivity index (SI= 3.14). In MDS2, the soil properties including silt, Mean Weight Diameter, pH, CaCO3 and available phosphorus were selected. Efficiency ratio of MDS2 was 80% and in soil quality assessment, MDS2 had higher efficiency than MDS1. Soil condition and change of soil management practices were reflected in MDS2 more clearly than in MDS1. Accordingly, SQIW2-MDS2-NLS method was the best means for evaluating the effects of deforestation on soil quality in the studied area.

Petroleum hydrocarbons are one of the most common groups of organic pollutants in the environment. Bioremediation of soils contaminated with petroleum compounds is an effective process for cleaning petroleum pollutants in the environment. In the present research, to reduce  light naphtha (1%) pollutant in in a sandy loam soil, different bioremediation methods including biostimulation, bioaugmentation, and integrated treatment (including both bioaugmentation and biostimulation) were used. This experiment was done as a split-plot design with three factors (pollution, bioremediation, and time) with 3 repetitions in 3 kg pots. After running the experiment at time intervals of 0, 5, 10, 15, 20, 30, 45, 60, 90 and 120 days, samples were taken from the test pots and parameters including basal respiration (BR) and substrarte-induced respiration (SIR) were measured. The results showed that application of bioremediation treatments had reduced light naphta pollution. Also, petroleum pollution had affected the activity of soil microorganisms, such that the maximum amount of BR and SIR was obtained in the early days; but with the passing of time, BR had a sharper drop compared to SIR. Seemingly, the microbial community responded to added glucose as a simple and available carbon source, and SIR was less reduced, but, probably, basal respiration encountered lack of carbon sources and decreased more. The results showed that, among the bioremediation treatments, integrated treatment had a greater effect on the reduction of petroleum hydrocarbons than other bioremediation treatments at the probability level of (P<0.01). The use of integrated treatment, in addition to increasing the active microbial population involved in the decomposition of petroleum compounds and providing optimal conditions for their activity, stimulates the indigenous soil microbial population and is a suitable method for removing petroleum compounds.