Journal of Soil Management and Sustainable Production
Year:2020 | Volume:10 | Issue:1|Papers Count:8

Background and Objectives: The importance of agriculture has been revealed for all human societies more than ever before as the population grows. Iron (Fe) element is one of the vital elements for plant growth and its presence is essential for plant metabolism and physiological processes of the plant. In the present study, we tried to study the stability of plasma membrane against the entry of the elements into it and the resistance of the plant to the stresses on the inner membrane of the plant, which is the amount of applied Fe levels in addition to studying the concentration of microelements in the root and shoot of the plant. The purpose of this study is to compare Fe resources intake and its interaction with the concentration and type of applied fertilizer on the concentration of microelements and the stability of the plasma membrane of the sorghum plant. Materials and Methods: A greenhouse experiment was conducted as a factorial design in a completely randomized design with three replications in the educational greenhouse of Zabol University in order to studying the use of Iron sources on the characteristics of Sorghum plant (Sorghum Bicolor (L. ) Moench. Var. Speed feed). The treatments consisted of two Iron levels (soil application: 0. 270, 0. 405 mg per kg of soil and spraying: 0. 25 and 0. 5 g of Fe per liter, along with control) from five type of fertilizer (Iron chelate, ferrous sulphate, Green nano Fe (include 9% Fe), Polymeric Iron chelate, Polymeric ferrous sulphate). Results: The results of analysis of variance of data showed that the triple interaction of all traits (except for the Cu of shoot that had no significant difference) and the dual interaction effects of Cu in the root of the plant have been statistically significant at the 5% probability level. The percentage of PMSI of the root (5. 06 times) in the soil application of 0. 270 mg. kg-1 Iron chelate and the concentration of Zn of the root (6. 99 times) at the level of 0. 405 mg. kg-1 in Green nano Fe (include 9% Fe) treatment were significantly higher than control. The total chlorophyll content (75. 95%), the percentage of leaf PMSI (6. 33 times) and Fe concentration in the shoot (1. 99 times) had significant increase in the Polymeric Iron chelate, Green nano Fe and Polymeric ferrous sulphate respectively and the concentration of Zn in the shoots showed significant decrease (75. 05%) in Iron chelate treatment in the spraying of iron sources at a level of 0. 25 g. L-1. The concentration of Mn was significantly decreased in the shoot (30. 67%) and in the root (37. 46%) in Polymeric Iron chelate and Iron chelate respectively and the concentration of Fe in the root (47. 86%) showed significant increase in polymeric ferrous sulfate treatment compared to control at the level of 0. 5 g. L-1. According to the results, the highest concentrations of Cu in the root were observed in the green nano spray application.Conclusion: In general, according to the results, the effects of Fe sources on the physiological characteristics of sorghum and plant PMSI were evaluated positive and confirms the positive effect of the spraying of all Fe sources on the traits of PMSI root and leaf, total chlorophyll and Fe concentration in the shoot and root.

Background and Objectives: Soil C dynamics will be influenced differently following incorporation of various plant residues with different qualitative characteristics. One of the most important ways to improve soil organic matter is to manage the correct use of plant residues in agricultural products, so that by bringing these residues back to the soil, the average annual carbon input to soil is increased and part of the carbon output from decomposition microbial is compensated. Hence, the purpose of this study was to investigate the effect of various plant residues on the mineralization kinetics of carbon and organic carbon content in different soils around the Lake of Urmia. Materials and Methods: This study was conducted as a laboratory incubation experiment in a completely randomized factorial design, including three soil types (calcareous, saline-sodic and sodic) and five plant residues (corn stalks, sunflower stalks, wheat straw, clover and vetch residues) with control treatment (soil without plant residues) in three replications. Plant residues (20 g kg-1) were added to the soils and incubated for 10 weeks (70 days) at 25± 1 ° C. CO2 emissions were measured once a week for 10 weeks, and then the parameters of the kinetic equation of mineralization of carbon were calculated. Finally, the organic carbon content of soils was measured immediately after the completion of the experiment on all treatments. Results: The results of analysis of variance showed that the soil type and plant residue significantly (P<0. 01) affected C mineralization. In all treatments, the highest CO2 emissions occurred during the first week of incubation and then there was a decreasing trend until the end of the incubation time. The highest amount of cumulative C mineralized obtained from calcareous soils treated with vetch and clover residues. There was a positive and significant correlation between plant N concentration and C mineralized, while there was a negative and significant correlation between ratios of C/N, Lignin/N, Cellulose/N, Hemicellulose/N, Cellulose+Lignin/N, N/P ratio and C mineralized. Carbon mineralization in all three studied soils is better estimated with C0K than C0. Also, with the return of plant residues to the soils, the amount of organic carbon increased in all three studied soils. The order of increasing organic carbon in different treatments of plant residues in all three studied soils was wheat> corn> sunflower> vetch> clover. Conclusion: In general, the highest cumulative mineral carbon in calcareous soils among the three studied soils, indicates the further decomposition of residues in these soils. Therefore, it should be compensated annually for the return of more residues to these soils, part of the carbonoutput resulting from microbial decomposition. Considering that the main purpose of using organic matter in soils was to increase soil organic matter, the results of this study showed that the greatest effect was on organic carbon increase in all three soils (calcareous, sodic and saline-sodic) of wheat residues and then corn with high C/N ratios and the smallest role obtained from clover and vetch with the lowest C/N. This suggests that increasing the amount of soil organic carbon content by adding plant residues depends on the quality of plant remains (C/N, Lignin/N, Cellulose/N, Hemicellulose/N, Cellulose+Lignin/N and N/P). Therefore, the use of plant residues with high C/N ratio is recommended for carbon sequestration in these soils.

Background and Objectives: Spatial and temporal variations of soil characteristics occur in large and small scales. Study of these variations is very time-consuming and costly especially in large scales. In order to the fast and reliable determination of soil properties, various interpolation techniques have been developed and applied. The most widely used interpolation techniques in various sciences is the Kriging types. The copula function is one of the new interpolation techniques that are widely used in sciences such as hydrology. Thus, the aim of this study was to evaluate the spatial variations of some soil physical properties using copula function and to compare with geostatistics techniques. Materials and Methods: Sampling by regular networking was done in an area of 484 ha located in 10 km from the west of Baft city, Kerman province and finally, 121 surface soil samples were collected. After air drying, the apparent bulk density was determined using the Hunk, then the soil samples were passed through a 2 mm sieve to determine the percentage of sand. To interpolate, four functions of the Archimedean copula including the Clayton, Frank, Gumbel and Joe functions, and geostatistics techniques including simple, ordinary, universal and disjunctive Kriging and the Inverse Distance Weighting (IDW) method were used. The results were analyzed using Root Mean Square Error (RMSE), determination coefficient (R2), Mean Absolute Error (MAE) and Mean Bias Error (MBE). Results: Based on the descriptive statistics, soil bulk density and soil sand followed a normal and skewed distribution, respectively. In order to fit the copula function, the distribution functions of the studied variables were firstly determined. The results showed that the sand and bulk density followed the Frechet (3P) and Wakeby distribution functions, respectively. Also, based on the Pearson correlation coefficient, the correlation between pairs of points was determined in distances less than 2000 m and distances more than 2000 m were known as an independent distance. The estimation efficiency based on the determination coefficient (R2) showed that value of determination coefficient for copula function for the sand variable, 6% and for bulk density 8%, more than conventional geostatistics techniques were obtained. Also, the estimation error of copula function was minimum that indicate good performance of copula function to estimate the spatial variation of soil physical properties. Conclusion: The results of study showed that copula function, especially the median copula, have the better performance for estimation the studied soil properties. One of the most important reasons for this superiority is the ability to fit the marginal distribution function on the data in copula, while it is not possible in geostatistics techniques. Other reasons include the ability to express the correlation between the data at different intervals and the lack of sensitivity to outlier data in copula relative to conventional geostatistics techniques. Due to the skewness nature of soil data, as well as the need for more accurate analysis and interpretation of actual soil data, copula functions can be widely used to estimate of soil properties.

Background and Objectives: In recent years, due to the lack of surface coating and low soil resistance to wind erosion, the large area of Khuzestan province is sensitive to dust production. Among the soil characteristics, the organic matter by collecting soil particles, has important role in soil resistance to wind erosion and dust production. Since these areas are so wide, the use of traditional methods of soil analysis is really costly and time consuming. The spectroscopy approach, due to the advantage of speed and easy movement, can reduce the cost and time of measurement. The aim of this study is to investigate the spectral behavior of soil organic carbon in central and southern regions of Khuzestan province by using tow multivariate regression, Support Vector Regression (SVR) and neural network (PLS-ANN) and key wavelength determination of soil organic matter in these areas. Materials and Methods: In this research, the study area was divided into 2 km square grids and systematic and random sampling Methods were performed. The soil organic matter in samples was measured in the laboratory. The Reflectance spectra of soil samples were determined using FildSpect setup in dark room. And spectral measurements were carried out with three types of detectors in range of visible to near infrared (3500-2500 nm). To eliminate the noise in normal reflectance spectra, the main spectra were preprocessed by four methods, including the first derivative with the Savitzky-Golay filter (FD-SG), the second derivative with the Savitzky-Golay filter (SD-SG), the standard normal variant method (SNV) and the continuum removed method (CR). Next, the performance of SVR and PLS-ANN models in main spectra preprocessed method were compared. Results: The results showed that the PLS-ANN model had better accuracy compared to SVR model in estimating organic carbon. In SVR models, the continuum removal method (CR) had the best performance (R2 CAL=0. 84, RMSECAL=0. 06 and RPDCAL=1. 82) and the main Spectra had the worst performance (R2 CAL=0. 74, RMSECAL=0. 14 and RPDCAL=1. 66). In PLS-ANN models, the best performance belonged to the second derivative (SD-SG), (R2 CAL=0. 92, RMSECAL=0. 05 and RPDCAL=2. 34) and the worst performance was related to the first derivative (FD-SG), (R2 CAL=0. 80, RMSECAL=0. 1 and RPDCAL=1. 86). Conclusion: In this study, the preprocessing methods improved the overall accuracy of SVR and PLS-ANN models compared to the main spectrum. According to the second derivative method, in PLS-ANN witch had the best accuracy in estimating soil organic carbon, the Wavelength ranges around 800, 1800 and 2000 nm were identified as the key wavelength of the organic carbon in sensitive centers to dust production.

Background and Objectives: Biochar is a carbon-rich product which is produced using pyrolysis of carbon-containing organic residues under anaerobic or oxygen-limited conditions. Due to unique properties such as high organic carbon, specific surface area and cation exchange capacity, application of biochar leads to increase in adsorption and holding capacity of water and nutrients. This, in turn, results in improved soil fertility. The aim of this study was to investigate the effect of iron impregnated biochr on iron uptake and growth of soybean grown in calcareous soil. Materials and Methods: An iron deficient calcareous soil (0-30 cm) was collected from east of Golestan province and after air drying, it was passed through a 2 mm sieve. Two types of biochar were produced from wheat straw and particleboard (at 300 ○ C) and impregnated with iron sulfate (Fe2SO4. 7H2O). A pot experiment was conducted as a factorial arrangement in a completely randomized design with four replications. Factors were biochars (wheat straw biochar (WB) and particleboard biochars (PB) with 2. 5% w/w), iron impregnated biochars (Fe impregnated wheat straw biochar 2. 5% w/w (Fe-IWB1) and 5% w/w (Fe-IWB2), 2. 5% w/w (Fe-IPB1) and 5% w/w (Fe-IPB2) Fe impregnated particleboards, Fe-Sequestrene (S) and control (C) and two Soybean cultivars (Williams and Saman). The sown pots were maintained in field capacity by weighing method for 12 weeks. Then, height, fresh and dry weights, total iron concentration and uptake of shoot and soil available iron contents were determined after the harvest. Results: The application of Fe impregnated biochar increased iron availability in the soil. Also, SEM images showed that iron was adsorbed or accumulated on biochars surfaces. Height, fresh and dry weights of both soybean cultivars in Fe impregnated biochars were significantly higher than those of bichars and control treatments (P≤ 0. 01), but there were no significant differences among them with treatment Fe-Sequestrene. Furthermore, with the application of Fe impregnated biochars, the iron concentration and uptake number of shoots in both soybean cultivars increased significantly compared to control and non-impregnated biochars treatments (P<0. 01). Cultivars responses to Fe impregnated biochars showed that shoot dry weight and iron uptake of the Saman variety were significantly higher than those of Williams variety in both levels of Fe impregnated biochars. Conclusion: The application of Fe impregnated biochar in calcareous soils with iron chlorosis increased iron availability. Therefore, in addition to improving the physical, chemical and biological properties of soil, Fe impregnated biochars like Fe-Sequestrene can effectively remove the iron deficiency of the plant.

Background and Objectives: Soil quality is one of the most important soil properties which investigation of its changes is essential to soil management and degradation. Quantifying soil quality using soil quality index to improve understanding of soil ecosystems is have been wieldy used. The soil quality index is calculated by measuring some soil characteristics which measuring these properties is expensive and time consuming. Therefore, one of the solutions is the use of digital soil mapping technique that can digitally predict soil properties using auxiliary data and data mining models. The purpose of this research is using a random forest model and auxiliary data for mapping the soil quality index. Materials and Methods: Based on the geomorphology map, 17 soil profiles and 105 auger samples were taken from a depth of 0-20 cm in the Ghorveh area of Kurdistan Province (covers 6500 ha) and soil texture, organic carbon, cation exchange capacity, electrical conductivity, pH, carbonate calcium equivalent, total nitrogen, available phosphorus, microbial respiration rate, sodium adsorption ratio (SAR), bulk density and gravel percentage were measured and calculated then the soil additive weighted index was calculated. Environmental variables in this research were map geomorphology, terrain attributes and data of ETM+ image. Geomorphology map was prepared based on hierarchy method. Terrain attributes (including 10 parameters), soil adjust vegetative index (SAVI), normalized difference vegetative index (NDVI) and brightness index (BI) were computed and extracted using SAGA and Arc GIS software, respectively. To make a relationship between soil quality index and auxiliary data, random forest (RF) model were applied and using cross validation method and statistic criteria including coefficient of determination (R2), mean error (ME) and root mean square error (RMSE) was validated. Results: According to the communality (share of each soil indicator), bulk density, sand, cation exchange capacity and clay had the highest weight (≥ 0. 1) and gravel and SAR had the lowest weight (≤ 0. 05) among the soil quality properties. To predict soil quality index, auxiliary variables including slope, SAVI index, wetness index, MrVBF index, LS factor, elevation, NDVI index and geomorphology map were the most important. The results of this study showed that the random forest model with 0. 65, 0. 042 and 0. 062 for determination of coefficient (R2), mean error (ME) and root mean square root (RMSE) had a fairly suitable accuracy for prediction of soil quality index. The soil quality index was ranged between 0. 3-0. 65 and its mean values in geomorphologic units with low gradient and low soil depth (Mo131, Mo141 and Hi231) were the lowest and in geomorphologic units with low slope and high soil depth (Pi111, Pi311, Pi322, Pi211 and Pi312) were the highest which these differences were statistically significant. Conclusion: In this research, a randomized forest model was used to study the spatial variation of soil quality index in Ghorveh area of Kurdistan province. The geomorphologic conditions of the study area have affected many soil characteristics and subsequently the soil quality index in the region. The soil quality index content was the lowest in highlands of north, northwest and northeast with high slope and low soil depth. The slope was the most important auxiliary variables to predict soil quality index in the region. Based on the results of statistical indices, random forest model also had relatively accurate estimation of the soil quality index. Therefore, it is suggested to map soil properties podometric techniques (such as randomized forest) and auxiliary data such as geomorphologic map, terrain attributes, and satellite images were applied.

Background and Objectives: The grapes are one of the most important garden products in the world as well as in Iran. One of the most important limiting factors of the growth of plants, especially fruit trees, in arid and semi-arid regions, is the lack of water resources. Water shortage reduces the water content of plant tissues and limits their growth. Also, the availability of different nutrients in the soil is significantly changed under water stress conditions. Accordingly, the management of plant nutrition under water stress conditions is one of the important issues in the production of the plant. The use of organic and chemical fertilizers as amendments of the physical, chemical and biological properties of soil can be one of the strategies to reduce the adverse effects of drought stress. Materials and Methods: In order to evaluate the effect of potassium sulfate, compost and biochar on some soil properties and grapes nutritional status under water stress conditions, this experiment was conducted in the research greenhouse during 2017-2018. The experiment was carried out as a factorial experiment based on a block of randomized completely design with two factors and four replications. The first factor, water stress had two levels (40, 80 % FC) and fertilizers’ treatments included potassium sulfate (10 g pot-1), compost (5 % w/w) and biochar (10% w/w). The macro-and micro-elements’ contents of grapes leaf and soil properties included the macro and micro-elements, pH, EC, OC. were also measured. Results: The results showed that the interaction effect of water stress and fertilizers’ treatments was significant for nitrogen (N), magnesium (Mg), ferrous (Fe), zinc (Zn) and copper (Cu) concentrations of grapes leaves (P<0. 01). The analysis of variance (ANOVA) indicated that the simple effects of water stress and fertilizers’ application had a significant effect (P<0. 01) on macro-and micro-elements’ concentrations of grapes leaves. The results also showed that under water stress conditions, the highest N concentration was observed for compost and potassium sulfate applications. Without water stress conditions, there was no significant difference between treatments. Under the water stress conditions, the highest concentration of Mg of grapes leaves was achieved with biochar application. While without water stress conditions, the lowest concentration of Mg was observed for biochar treatment. With and without water stress conditions, the concentration of Fe and Cu was higher for organic treatments compared to potassium sulfate application. With and without water stress conditions, the highest concentration of Zn was achieved for potassium sulfate application. The ANOVA results showed that the interaction effect of water stress and fertilizers’ treatments was not significant for soil properties except soil calcium. The water stress caused a significant decrease in soil phosphorus (P) and Mg (P<0. 05) as well as calcium (Ca) (P<0. 001). The effect of fertilizers’ treatments was significant on electrical conductivity, organic carbon, N, P, potassium (K), and sodium (Na) (P<0. 01), Ca and Mg (P<0. 001) concentrations of soil. The application of potassium sulfate and compost increased the sodium concentration of soil 8. 53 and 60. 52 percent, respectively. However, the Na concentration of soil decreased 3. 73 percent with the biochar application. Conclusions: According to the results of this study, it can be concluded that under water stress conditions, the application of compost and biochar in comparison with potassium sulfate enhanced the nutritional status of grapes because of the improvement of soil fertility status. The highest K concentration and uptake of grapes leaves and soil were observed with biochar application. Under water stress conditions, in comparison with no fertilizer application, K uptake increased 69. 85, 36. 21 and 178. 97 percent by potassium sulfate, compost and biochar applications, respectively. Since K is a critical element to regulate the water content of plant tissue and reduces the hazards of water stress, the application of compost and biochar is recommended for the improvement of plant resistance under water stress conditions. However, between compost and biochar, biochar is suggested due to having properties such as highly porous structure, high specific surface area, higher water holding capacity of the soil, the longterm stability in the soil and the reduction of Na hazards in soil.

Background and Objectives: Soil is the thin layer of materials covering the Earth’ s surface and forms from the interaction of the atmosphere, lithosphere, biosphere and hydrosphere. Soil formation, development and functions influence the sustainability of ecosystem. The unique characteristics of soil have made it one of the key subjects of the Earth Science. Minerals are important components of the soil environment. They influence on the water-holding capacity of soils and affect their cation exchange capacity. Mineral weathering is an important process in soils, during which available forms of important nutrient elements are released from minerals structure into the soil system for root uptake. Micaceous minerals are common components of soils, sediments and minerals. Several studies have examined the characteristics of compost enriched with mineral compounds. While the mineralogical changes during the process of compost production have not yet been investigated. Therefore, the objective of this research was to evaluate the rate of biological weathering of phlogopite with time in phlogopite-enriched compost. Materials and methods: An experiment was run in petri dishes under laboratory conditions using 2 levels of phlogopite mineral (0 and 20% by weight) and four time periods (45, 90, 135 and 180 days) in 3 replications. Each petri dish contained 20 g of a mixture of cow manure and phlogopite mineral. In each period, 6 petri dishes were separated and their contents were oven dried at 30 ° C, powdered and passed through a 2 mm sieve. After preparing the contents of petri dishes, organic carbon content of the samples was measured by wet oxidation method and their total nitrogen by Kjeldahl method. The mineralogical changes were evaluated using X-ray diffraction analysis. Results: XRD patterns showed that during the composting process, phlogopite was partially weathered to vermiculite and smectite. The rate of weathering was higher at the early stages. The weathering of phlogopite was influenced considerably by the activity of microbial communities during organic matter decomposition process. At the end of the composting process, the weathering rate decreased and continued at a stable rate. Mineralogical changes occurred in phologopite during the composting were in line with the reduction of C/N ratio with time. The C/N ratio rapidly changes at the early stages of the composting process and gradually becomes constant. Conclusions: In general, the results indicate that the increase of availability of elements such as potassium in mica-enriched compost is in fact due to the weathering of micaceous minerals added. The weathering rate was influenced by the activities of microbial communities.