جستجوی مقالات مرتبط با کلیدواژه « شاخص کیفیت خاک » در نشریات گروه « آب و خاک »

Evaluating and determining the minimum data set to evaluate soil quality is very important, valuable in terms of cost, and time save. The aims of this study were to assess the quality index of soils under successive, and long-term cultivation of wheat by a valid model (Integrated quality index= IQI), determine the minimum data set to evaluate the quality of soils in this region, and evaluate the relationship between soil quality index and wheat yield components. For these purposes, 18 physical, chemical, and fertility properties of the surface soil belonging to 40 soil profiles were determined in the croplands from Piranshahr region of West Azerbaijan province. The soils were classified in the three order of Mollisols, Inceptisols, and Vertisols. Total variables affecting soil quality (TDS) were determined, and minimum effective data (MDS) were estimated using principal component analysis (PCA). The soil quality index was divided into five classes according to the growth of the plant using the interpolation technique. Based on the results of PCA, five properties of organic carbon, clay, sodium adsorption ratio, calcium carbonate equivalent and silt had a specific value greater than one and were selected as MDS indicators. The highest values of IQITDS, and IQIMDS were observed in the Inceptisols, followed by Mollisols and Vertisols, respectively. A significant relationship (p <0.05) was found between wheat yield components (grain yield, and biological yield of wheat) with IQITDS and IQIMDS models, which showed a positive, and significant effect of soil quality index on wheat yield components. Moreover, the IQITDS model was more accurate than the IQIMDS model in predicting the performance of wheat components due to its higher R2. However, due to the positive, and significant correlation between IQITDS and IQIMDS (R2 =0.9(, the IQIMDS model is an economic and better model for evaluating the quality of soils in the region.

 The type of management operations and land use systems are the key parameters affecting the soil quality and sustainable land use. The exploitation systems by efficient use of soil and water recourse can decrease productions costs and increase the yield as well as conserve the natural resources. However, farmers and stakeholders need to be aware that through their management practices, they affect soil quality and, with the short-term goal of production and greater profitability, lead to soil degradation. They can both use the land economically and improve and maintain soil quality by balancing production inputs and refining their management approaches. There are different management systems of productivity in agricultural lands in Neyshabour plain in northeastern Iran. In addition to the water and soil limitations in the study area, the prevalence of the smallholder system and the unwillingness of farmers to integrate smallholder, has further increased the destruction of soils in the study area. The objective of this study was to assess the changes in soil quality index in surface soil and profile (0-100 cm) and calculate the correlation between soil quality index and alfalfa and rapeseed yield in rangeland and agricultural areas managed by smallholders, total owners, and Binalood Company in the study area.

 A total of 21 soil profiles were described in the total owner, smallholder and Binalood company management system and sampled from the alfalfa and rapeseed lands. Questionnaires were prepared with the help of farmers and experts in the study area based on Analytic Hierarchical analysis (AHP) method. The physical and chemical characteristics of the soil samples were determined. The important soil characteristics affecting plant growth were determined by interviewing farmers and experts study area. Soil quality index in the minimum data set (MDS) was calculated by two methods of principal component analysis (PCA) and expert opinion (EO), by additive and weighted methods in surface soil and profile. To achieve a single value for each soil properties in the soil profile, two methods of weighted mean and weighted factor were used. To evaluate the accuracy of the assessment, the correlation between soil quality index and alfalfa and rapeseed yield was investigated of the various management system.

The results showed that the highest additive and weighted soil quality index at both surface and soil profile in both PCA and EO methods were in rangeland. It was due to lack of cultivation and maintaining organic matter comparing to agricultural land. The total owner management system due to its economic power and the use of appropriate and scientific methods comparing to smallholder management system, showed the highest additive and weighted soil quality index. In all management system, the EO-calculated weight index by weighted factor method had the highest value due to assigning the suitable weight for soil characteristics. The correlation analyses soil quality indices with canola and alfalfa indicated that the EO soil quality calculated by weighted factor for the soil profile were more correlated than surface soil in total owner system and the Binalood company. Weight coefficient method due to the application of different weights to each layer based on their importance, showed a higher soil quality index in both EO and PCA sets than the weighted average method. The reason for better EO performance probably is that the PCA is a reducing the dimensions, meanwhile, the minimum data selection in the EO method is based on regional experts which are familiar with cause-and-effect relationship of the soil properties. Due to the relatively good correlation of the yield of the studied products, with the soil quality index, an appropriate management needs to maintain and improve soil quality, especially in the smallholder system, as well as meeting the nutritional needs of these products.

 Soil quality assessment in this study indicated that calculation of the soil quality index only considering the surface soil properties may not provide complete information for the farmers and land managers. Then inclusion of both surface and profile soil properties with farmers' knowledge and study area experts are essential for sustainable soil management. On the other hand, the differences in the management system also affected the soil quality index. Although the smallholder management system due to low input, especially chemical fertilizers, water and agricultural implements, had a high potential concerning environmental issues, but in terms of production, total owner and Binalood company management systems because of their high economic strength had the higher soil quality index. The farmers and stakeholders of the total owner management systems should be considered despite the proper management, however due to high inputs of fertilizer and water, especially in the Binalood company, the production may not be sustainable. Therefore, for further studies, calculating the water consumption in the desired management systems is recommended.

Knowledge on the spatial distribution of soil quality is one of the most ‎important issues in recognition, planning, management and optimal ‎exploitation of soil resources. In this study, physical, chemical and biological properties of topsoil ‎‎(0-30 cm) were measured in 50 fields (1650 m × 1650 m) in Savojbolagh region, Alborz ‎province. All of the factors influencing soil quality were selected using ‎the principal component analysis (PCA). The Weighted Additive Soil Quality Index (SQIw), the Additive Soil Quality Index (SQIa) and the Nemero Soil Quality Index (NQI) were quantified using either the total data set (TDS) or the minimum data set (MDS). Spatial variability of these soil quality indices were analyzed using geostatistical technique. In addition, spatial distribution of them were determined using the Ordinary Kriging method‎. The results showed that for the NQI index, the best fitted model was the Gaussian (R2= 0.93) when MDS was used, whereas, the exponential (R2= 0.79-0.99) model was strongly fitted to the other indices obtained from MDS and TDS. Furthermore, the effective range of spatial variability for SQIa, SQIw and NQI indices was 6-6.2, 2.7-3.65 and 4.5-7.2 kilometers, respectively. The NQI obtained from the TDS appeared to have the higher accuracy in the area (R2= 0.85, normalized root mean squares error (NRMSE) = 0.01). A large part of the area has high quality (class II) as well as to some extent areas have medium quality (class III) and very high (class I). Soil quality indices in the region were in moderate spatial dependence (0.31-0.7). So, the soil quality in the region is affected by both natural and external factors. Therefore, regarding the low organic matter as well as the weak structural stability of soil in the study area, one may expect that by implementing appropriate management methods such as adding organic matter, the soil quality will be increased.

Soil quality can be considered as a comprehensive index for sustainable land management assessment. Studying the most important soil physical properties and combining them as an index of soil physical quality (SPQI) could be used as an appropriate criteria for evaluating and monitoring soil physical changes. In this regard, this study was conducted to determine the most important soil physical properties and calculate the SPQI of medium to coarse-textured soils of Khorasan-Razavi province.
Torogh Agricultural and Natural Resources Research and Education Station of Khorasan-Razavi province is located in south-east of Mashhad city (59° 37' 33"-59° 39' 10" E, 36° 12' 31"-36° 13' 56" N). Soil texture variability in this research station is one of its outstanding features. The soil textures are classified into loam, silt loam, silty clay loam, clay loam, and sandy loam. More than 90% of agricultural soils in Khorasan-Razavi province are classified in these five texture classes. Using the available data, 30 points with different soil textures and OC contents were selected. The soil samples were collected from 0-30 cm soil depth at each point. Intact soil cores (5 cm diameter by 5.3 cm length) were used for sandbox measurements, and disturbed soil samples were used to determine other properties. Required laboratory analysis and field measurements were conducted using standard methods. In this research, 35 soil physical properties as total data set (TDS) including: soil moisture release curve (SMRC) parameters, particle size distribution and five size classes of sand particles, soil bulk and particle density, dry aggregates mean weight diameter (MWD) and stability index (SI), S-index, soil porosity and air capacity, location and shape parameters of soil pore size distribution (SPSD) curves, relative field capacity (RFC), plant available water measured in matric pressure heads of 100 and 330 hPa for the field capacity (PAW100 and PAW330), least limiting water range measured in matric pressure heads of 100 and 330 hPa for the field capacity (LLWR100 and LLWR330), integral water capacity (IWC) and integral energy (EI) of different soil water ranges were measured and calculated for 30 soil samples. The most important soil physical properties were selected using principal component analysis (PCA) method by JMP (9.02) software. Selected physical properties as minimum data set (MDS) were weighted and scored using PCA results and scoring functions, respectively. In this study, three types of linear scoring functions were used. The soil physical quality index (SPQI) was calculated by two scoring and two weighting methods for each soil sample and the differences between these four SPQIs were tested by sensitivity index.
Principal component analysis results showed that among 35 soil physical properties (TDS) which were studied at this research, six properties of mean pore diameter (dmean), PAW100, total porosity (PORT), EI LLWR330, SI and PAW330 accounted for about 90% of the variance between soil samples. Weight of the selected properties (MDS) was calculated by the ratio of variation in the data set explained by the PC that contributed the selected property to the total percentage of variation explained by all PCs with eigenvalue ˃ 1. In this research, the parameters of PAW100, total porosity (PORT), SI and PAW330 were scored using scoring function of more is better, EI LLWR330 was scored using scoring function of less is better and dmean was scored using scoring function of optimum by two scoring methods with score ranges of 0.1-1 and 0-1. Considering unweighted and weighted MDS and two ranges of scores, four SPQIs were calculated for each soil sample. The results showed that SPQIs which were calculated by the MDS derived from PCA method and scoring weighted MDS at the range of 0-1, had the highest sensitivity index and could represent the differences between the studied soil samples better than other SPQIs. By this method, maximum and minimum SPQI values for the studied soils were 0.82 and 0.12, respectively. SPQI is a relative comparison criterion to quantify the soil physical quality which could be applied only for the studied soils with specific characteristics.
The results of this research showed that minimum data set (MDS) explained about 90% of the variance between soil samples. Combining MDS into a numerical value called soil physical quality index (SPQI) could be used as a physical comparison criterion for the studied soils. From the SPQI based on the MDS indicator method, soil quality was evaluated quantitatively. Soil samples with grade I, II, III, and IV accounted for 10%, 36.7%, 30%, and 23.3% of the soil samples, respectively.

The excessive use of pesticides in recent years and their continuation in the future may have harmful effects on the microbial population of the soil, as an indicator of soil health and one of the main components of the environment. The purpose of this study was to investigate the effect of three mostly used insecticides (Diazinon, Chlorpyrifos and Imidacloprid) on ec-ophysiological and chemical indices of soil. The experiment was conducted as a factorial in a completely randomized design which included the pesticide factor at four levels (three insecticides plus control soil) and time factor at three levels (before, three months and six months after pesticide application). Concentrations of insecticides (0.1, 1 and 0.67) mg per kilogram of soil were used for imidacloprid, diazinon, and chlorpyrifos, respectively. Some biological and ec-ophysiological indices of the soil were measured at the beginning of the experiment, three and six months after the beginning of the experiment. The results showed that, the application effect of insecticides after three months affected the biological indices including dehydrogenase enzyme activity, metabolic quotient, basal respiration, substrate-induced respiration and also organic carbon decreased compared to the control -92.2%, -46.7%, -24.7%, 15.8% and -7.61%, respectively and urease enzymes activity, microbial biomass carbon, microbial biomass nitrogen, carbon to nitrogen ratio and soil microbial quotient increased compared to control 6.67%, 32.1%, 15.6%, 16.5% and 58.9. Also, the results showed that among the insecticides Chlorpyrifos and Diazinon had the highest and the least negative effect on the indices, respectively. The application of insecticides Diazinon, Chlorpyrifos and Imidacloprid at least in the short term, had a negative effect on soil ecophysiological indices and the most sensitive indices for determining the negative impact of insecticides on the soil microbial community were the dehydrogenase enzyme activity, metabolic quotient, substrate-induced respiration and basal respiration.

Rapid growth of population, followed by increasing food demand, necessitates knowledge of the relationship between yield and soil conditions. The soil quality index (SQI) is one of the indicators showing the soil conditions and the related properties very well.This study was performed to determine the effect of soil quality on rice yield in north of Iran (Gilan province). 64 soil samples from rice fields were prepared to measure the physical and chemical properties affecting soil quality and also the yield of rice in the mentioned fields were determined using plot. Then the total yields were divided into three classes with yields of less than 4000 kg/ha (first class), 4000-4500 kg/ha (second class) and more than 4500 kg/ha (third class). Among the studied properties, 16 properties as selected indicators of total data method (TDS) and five properties using principal component analysis as selected indicators of minimum data set method (MDS) were selected to determine the soil quality index. Fuzzy logic was used for scoring and the concept of communality index was used to weight the indicators and finally they were combined using weighted additive method. The results of quality index showed a positive and high correlation between TDS and MDS methods (R2 = 0.87). The results of correlation coefficient between yield and SQI by TDS method (R2 = 0.52) were higher than the SQI by MDS method (R2 = 0.28).  In the MDS method, simmilar to TDS method, there was an increasing trend in the SQI value of higher yield classes, but there is no significant difference between the second and third classes. The difference between soil quality and lower yields with MDS method is significant, but this difference is not significant at higher yield levels, because as the number of indicators decreases, the accuracy and sensitivity of soil quality assessment decreases.

Agricultural activities, especially rainfed wheat, is one of the main reason of the destruction of natural rangeland in the west of Iran. This study aimed to investigate the effect of changing natural rangeland to rainfed wheat for 40 years on some soil properties at the Saral Agricultural Research Station in Kurdistan province. Soil samples were collected from 0–25 cm depth randomly. Some soil properties such as soil texture, bulk density, mean weight diameter, cation exchange capacity, electrical conductivity, pH, calcium carbonate equivalent, total nitrogen, total organic carbon and available amount of Mg, Ca, K, P, NO3 and NH4 were measured. The results showed that land use change from rangeland to rainfed wheat significantly reduces soil quality with regard to all investigated properties except bulk density, calcium carbonate equivalent, P, K, NO3 and NH4. Determination of soil quality index (SQI) using Principal Component Analysis (PCA) showed that total organic carbon, total nitrogen, clay and silt almost justify more than 90% of the variance, which were selected as the minimum data set in the SQI calculation. The results of SQI showed that the index was significantly higher in rangeland (1.58) than in cropland (0.72), indicating degradation of soil quality by cultivating operations.

This study aimed to investigate the effect of five herbicides (Tribenuron-methyl, Metribuzin, Trifluoralin, Haloxyfop-methyl, and 2, 4-D (on the soil dehydrogenase and urease activities.

The experiment was conducted as a completely randomized design with five herbicides and a control with three replicates for six months and the enzyme activities were measured at beginning of the experiment, and after three and six months. The concentration of herbicides was 0.27, 0.67, 0.67, 0.67, and 0.1 mg/kg soil for Haloxyfop-methyl, Metribuzin, Trifluoralin, 2, 4-D, and Tribenuron-methyl, respectively.

The results showed that the effect of herbicides on the enzyme activities was significantly different (p0.01). After 3 months, the herbicides decreased the urease activity in comparison to the control (34.9 µgN.g-1). The most reduction was related to Trifluoralin (24.8 µgN.g-1) which was 28.9% lower than the control. Urease activity increased after six months compared to three months, and this increase was 41.5% for Trifluoralin herbicides (35.1 µgN.g-1). Urease activity in control treatment in six months was not significant compared to the three months. All of the herbicides significantly reduced the dehydrogenase activity after three months compared to the control (0.6 µgTPF.g-1), so that the dehydrogenase activity was observed in Haloxyfop treatment with 0.01 µgTPF.g-1, which was 98% lower than the control. In all treatments, dehydrogenase activity after six months was significantly higher than that in the three months, so that the highest dehydrogenase activity was observed in 2,4-D treatment (1.44 µgTPF.g-1), which was significantly higher than the control.

The results show that the herbicides significantly decreased the activity of the enzymes compared to the control during the three months. After six months the enzyme activities recovered to the level before herbicides application. Probably this was due to a short lifetime of herbicide in the soil which was less than six months.

In the present study, mid-term variations in soil quality were studied on the farm scale. The studied area was a research-educational farm of the Agricultural and Natural Resources Campus of University of Tehran covers 260 hectares, with thermic soil temperature and aridic soil moisture regimes, respectively. In this study, the process of improving or destruction of the integrated soil quality index at two depths (0-20 and 20-40 cm) in years of 1379 and 1396 was compared. The minimum data set was determined using the method of two-phases PCA. Definition of standard scoring functions and non-linear fuzzy membership functions were performed through programming in the MATLAB software environment. Covariance-correlation method was used for weighing the selected variables in determining Soil Quality Integrated (SQI) index. The results of this study showed that in most of the adaptive areas of the soil, the incremental and decreasing pattern of the soil quality index in the first and second depths of the previous and present studies were consistent and in some places, this pattern was almost constant. In profiles No. 1, 5, 11 of the previous research which include 27.3% of the samples, and in profiles No. 1, 5, 7, 9 and 18 of the present study which include 20.83% of the samples, the soil quality index at the first depth was less than the one in the second depth. Classification of the soil quality classes for all samples in both years revealed a reduction in soil quality index. So that the soil quality reduced from grade III (45%) and IV (54%) to grade IV (73-75%).

A comprehensive assessment of agricultural soils quality is essential for making wise decision that leads to sustainable production and environmental preservation. Many studies have shown that soil quality index, based on a combination of soil characteristics, can describe soil conditions better than individual soil characteristics. In this study, to evaluate the soil quality, first, a minimum data set was made by using the principal component analysis. Then, quantitative characteristics of the soil were quantified through scoring. Finally, by weighting each attribute (through the principal component analysis), soil quality index (SQI) was obtained and converted to map by GIS software. The results showed that most of the soils (97% of soil samples) had electrical conductivity less than 2 dS/m and they were in the group of natural soils without limitation. Most of the studied paddy soils had a good pH and no special limitation. The average of available phosphorus concentration was more than the critical level (12 mg/kg) because of the presence of a number of high concentration samples, while there was a poor phosphorous situation in more than 50% of the region. Nearly 76 percent of the studied regions had total nitrogen higher than 0.2 percent, which indicated the relative adequacy of this nutrient element in most of the land. The concentration of available potassium in most of the studied areas was less than the critical level. Mapping of the soil quality index showed that some paddy fields had poor fertility quality because of the limitation of soil intrinsic and static properties such as clay, organic carbon, and cation exchange capacity. However, most of the studied lands had moderate fertility quality and the most important limiting factor was the shortage of available phosphorus and potassium, while the use of phosphorus and potassium fertilizers was low in this area.

Assessing the soil quality of agricultural land is essential for the economic success and sustainability of the environment in developing countries. Recently, there are many types of methods for assessing soil quality, each of them uses different criteria. Considering that Qazvin plain is one of the most important regions of agricultural products in Iran as well as Middle East, so the assessment of the soil status using quantitative models of soil quality can be used as an indicator of the status of soils in relation to sustainable agriculture, optimal utilization of resources Natural and better land management. Among the quantitative models of soil quality index, cumulative model integrated quality index (IQI) and Nomero (NQI) index can be mentioned. Therefore, this study intends to evaluate the best quantitative and quality index model by examining and comparing two methods of selecting the appropriate criteria, Total data set (TDS) and Minimum (MDS) and the second order soil quality index, integrated quality index(IQI) and Nomero (NQI) index in Qazvin plain lands.
Material and The study area with 25220 hectares is located in east of Qazvin Province. The average annual precipitation is 275 mm and the soil moisture and temperature regimes are Thermic, Dry xeric and Weak Aridic, respectively. A total of 76 samples from the depth of 0-20 cm of the soil surface were studied and based on uniformity, soil type and land use. In this study, four types of criteria that affect the quality of soil in terms of their performance, including: upper limit, lower limit, optimal limit and descriptive function were selected. To qualify (normalize), the upper limit, lower limit and peak limit were selected. In the following, the Total Data Set (TDS) and the Minimum Data Set (MDS) set of data were used. In the TDS method, all of the measured characteristics (a total of 19 physicals, chemical and biological properties of the soil) were considered. Then, the degree of soil quality indices was determined based on the combination of TDS and MDS criteria and the final NQI and IQI quality indices.
Result and Dissection: Comparison of soil types in the region showed that the Aridisols had good, moderate and poor quality (19.35% of soil with good quality, 67.76% with moderate quality and 12.94% with poor quality), Entisols have good and medium quality (53.21% of the soil with good quality and 46.79% with moderate quality) and Inceptisols have very good, good, moderate and poor quality (96.9% Soils with very good quality, 66.73% with good quality, 15.85% with moderate quality and 13.44% with poor quality).
According to the TDS standard and the NQI model, the soils with qualities I, II and III were 30.67%, 66.86%, 47.2% of the total soils of the area (lands with poor quality soil quality were not observed in TDSNQI method). Therefore, according to this method, Aridisols has a very good, good and medium quality (13.26% of the soil with a very good quality rating, 73.88% with a good quality and 12.84% with a moderate quality grade), Entisols with The good quality (100% of the soil with good quality degree) and Inceptisols have a very good and good quality (28.11% of the soil with a very good quality grade, 71.88% with a good quality grade). The results of quantitative soil quality by using the MDS standard method and IQI model were showed, soils with very good, good, moderate and poor degree are 2.45, 16.45, 48.93 and 46.3 percent of total land area respectively.
The results of the combination of the MDS and the NQI model also showed that the soils with a very good, good and average grade are 30.67%, 66.86% and 47.2% of the total land, respectively. Also, the results of the combination of the MDS and NQI model showed that the soils with very good, good and average quality are 30.67%, 66.86% and 47.2% of the total land area respectively. The results of the evaluation based on 4 indicators showed that good quality (II) was prevalent in the studied soils and accounted for about 47% of the total area studied in Qazvin plain lands. The map of distribution of soil quality degrees, the distribution of soil degrees is relatively similar to all of four combination methods, the choice of criteria and model. By examining the linear relationship between the indices obtained from TDS and MDS criteria and the IQI and NQI indexes, it is observed that the correlation coefficient is more and more reliable than the NQI model when used in the IQI model (R2 = 0.77). So the highest correlation coefficient we observed two methods for selecting the TDS and MDS criteria when using the IQI model. In general, the results of this study indicate a better performance of the MDS criteria than TDS.
Therefore, the main results of this study suggest using the IQI model with the MDS selection method as the starting point in the global standard path for future studies. Special attention should be paid to the criteria chosen by the MDS. In addition, conducting a series of research into the future in order to modify the MDSIQI model can make it more relevant to international standards.

World population growth, human need of food, his interference in natural ecosystems and changing soil intrinsic properties by degradation, increases the need of evaluating land use changes impacts, on soil quality. This study was carried out to evaluate the effects of land use change on some of soil quality indicators in land use changed forest of Northern Zagros.
in this study about 96 soil samples were taken from North Zagros forests as well as adjacent areas with land use changed. Some soil properties including basal respiration (BR), substrate induced respiration (SIR), microbial biomass carbon (MBC), pH, electrical conductivity, total nitrogen, available phosphorus, dissolved and exchangeable potassium, cation exchange capacity (CEC), soil organic matter (SOM), sodium adsorbtion ratio (SAR) and exchangeble sodium percent (ESP) were measured. Soil quality index (SQI) was determined using principal component analysis (PCA).
The results showed that changing forest to other land uses significantly reduced microbial biomass carbon, basal respiration, substrate induced respiration, the amount of dissolved calcium and potassium, exchangeable calcium, magnesium and sodium, organic matter, CEC, SAR and potassium. Soil organic matter amount in pasture, garden and agriculture decreased 16, 47 and 57.5 percent compared to forest, respectively. As a result of changing forest to pasture, gardens and agriculture MBC amount decreased 28.34, 48.66 and 58.28, respectively. The amount of total nitrogen, potassium and CEC in forest were 2.5, 1.39 and 1.4 times more than agriculture, respectively. Also, in different land uses, depth effect on all measured parameters was significant. As the results showed, the highest amount of potassium, nitrogen, cation exchange capacity, basal respiration, microbial biomass carbon and substrate induced respiration was seen in forest surface soils. Principal component analysis showed that between 16 properties assessed soil quality as total data set (TDS), organic matter, carbon availability, microbial carbon proportion to organic carbon, available phosphorus, pH and SAR, as the most important or the least effective properties on soil quality (minimum data set or MDS), had the greatest impact on the quality of studied soils. According to the cumulative soil quality index (SQI), soil quality for forest (0.756) and pasture (0.73) was II (lowly restricted) and for agriculture (0.646) and garden (0.626) was III (with limitation for plant growth).
Therefore, any management and land use change that increases soil disturbance, will reduce soil quality and increase land susceptibility to soil erosion. So, in order to maintain soil quality, appropriate management practices should be done.

Land use has considerable effect on soil properties and awareness of these properties is necessary to preserve ecosystem stability and increase the soil productivity. In this study, the effects of agronomic (alfalfa and wheat), orchard (apple) and forest (chestnut) land uses (over 30 years) on soil chemical properties in West Azerbaijan province were evaluated. About 75 soil samples were randomly collected from surface soil of each land use for the depth of 0-20 cm and some of their chemical properties as well as the soil quality index (SQI) of the soil of each land use were determined. Results showed that the soil organic carbon (2.8%) and total nitrogen (0.20%) in forest land use were significantly higher than those in the other land uses. Available phosphorous in the soil of the apple orchards (16.2 mg kg-1) was higher than those in the soils of the agronomic (12.6 mg kg-1) and forest (10.6 mg kg-1) land which can be attributed to the high phosphorous fertilizer application in the orchards. The amounts of pH, EC and CaCO3 in soil of the forest land use were less than those in soils of the other land uses. Assessment of soil quality index (SQI) showed that organic carbon, pH and available phosphorous as minimum data set (MDS) had the highest effect on quality of studied soils. Soil quality index in the forest land use (1.4) was significantly higher than those in the orchard (1.3) and agronomic (1.2) land uses. It is concluded that the land use effects on the soil qualitative propertise can be intensified with the organic matter input rates and tillage activities.

Topography is one of soil forming factors through the degree and aspect of slope affect on soil physical properties. The aspect of slope influences soil moisture, temperature and activity of micro organisms cause change soil organic matter in different soil aspects and therefore create different soil qualities. Different solpe degrees through transport of organic and clay particles down parts of the slope and changing bulk density affect the soil quality (15). In order to maximize utilization of agricultural lands and minimal environmental degradation and to prevent soil erosion, study soil quality is essential. The aim of this study was to evaluate soil quality in different degrees of both northern and southern slopes in catchment of Torogh dam, located south eastern of Mashhad.
To asses the soil quality, 40 soil samples were taken from 0-30 cm soil depth in both northern and southern slopes consist of less than 10%, 10-20%, 20-30% and more than 30% slope degrees in catchment of Torogh dam, located south eastern of Mashhad. 5 soil samples were collected from each slope degree and and properties such as soil organic matter content, bulk density, CaCO3, sodium adsorption ratio (SAR), mean weight diameter of aggregates, water dispersible clay and silt, sand, silt and clay percent, pH and soil structural stability index (SI ) were measured. The score of each property based on scoring functions and their weights were calculated by dividing the communality value of each property to total communality of all properties in JMP4 software. Then Soil quality index was calculated by multiplying the score and weight of the studied properties and sum of them.
According to the results of this research, The significant correlation between the percentage of organic matter, CaCO3, water dispersible clay and silt, silt and clay with soil quality index was positive and, that of soil quality index with mean weight diameter of aggregates and percentage of sand was negative (P In this research, the effect of slope aspect on soil quality was more than degree, and different slope degrees had no significant effect on soil quality.

For assessing of soil quality, the sensitive indicators can be used in land use managements. Monitoring all soil characteristics is costly and laborious therefore, limited soil characteristics for this mean are recommended. The purposes of this study were comparing several soil attributes of different land use types and determination of minimum effective soil characteristics on soil quality in Chughakhor Basin, Chaharmahal va Bakhtiari Province, Iran. To fulfill the objectives slope, land use and soil maps and Latin Hypercube strategy were used and locations of 125 composite and surficial soil samples were determined. After pretreatment of soil samples, 29 soil physical and chemical characteristics were measured using appropriate methods. The mean comparison of different land uses showed that mean weighted aggregate diameter, available water content, air content, Dexter index, organic carbon, particle organic carbon in macro aggregate, the proportion of particle organic carbon in macro to in micro aggregates, P, Fe and Cu contents values of land use types were in the order Orchards>cultivated areas>Good rangelands>Dry land areas>Weak rangelands. For determination of effective indicators in soil quality assessing, the principle component analysis and stepwise discriminant analysis are used. The soil characters like water stable aggregates, soil texture elements, proportion of particle organic carbon in macro to in micro aggregates and soil Cu and Zn concentrations as minimum data set for soil quality assessment.

Management of organic and inorganic treatments may have positive or negative effects on soil quality, plant growth and human nutrition. The objectives of this study were to determine the effects of organic and inorganic zinc fertilizer application on soil quality indicators and wheat yield. This research was conducted at Agricultural Research Station Roudasht, Isfahan, Iran. Sewage sludge and cow manure (5 and 10 t/ha), ash rubber (1 t/ha), powder rubber (200 kg/ha), ZnSO4 (40 kg/ha) were applied and wheat was cultivated. Soil samples were collected at tilling and harvest stages. After taking samples and measurements of the soil parameters, we determined the critical limits for each category and class rating for the each soil parameters, and the soil quality index was calculated. The results showed sewage sludge and rubber ash were significantly effective in increasing soil bioavailable Zn compared to other treatments. Application of sewage sludge and cow manure at 10 ton/ha improved soil quality. The expanded soil quality index can help better understand the effect of fertilizers on soil. A positive and significant relationship between soil quality indicators and Zn uptake and wheat yields was also observed. Our results indicate that addition of 10 t/ha sewage sludge as fertilizer can significantly improve soil quality, supplying the necessary amount of Zn for wheat growth.

Continuous soil quality evaluation in is necessary agricultural regions to sustainable soil management and profitable agricultural production. The objectives of this study were comprised of an evaluation of soil quality utilizing Integrated Quality Index (IQI) along with its spatial distribution in Qazvin province. IQI was calculated and its spatial changes analyzed using different interpolation methods via GIS software. Precision criteria MAE and RMSE, bias criteria MBE and correlation between measured vs. predicted values (r) were employed to determine a suitable interpolation method. The results indicated an IQI index of strong spatial correlation (Nugget/Sill = 0.38) with an effective range of 19.18 kilometers. The IQI spatial distribution is well fitted by the exponential model. Completely Regularized Spline was selected as a suitable interpolation method using evaluation criteria as well as existing trend in area. IQI model revealed the soil areas with moderate quality (grade III) as dominant.

The effect of land use type on soil functioning within an ecosystem can be assessed and monitored using soil quality attributes. Such studies, which are carried out to create a balance between the biological production and the maintenance and improvement of land resource quality, provide a framework for land degradation control and also for identification of sustainable management. In this research investigated the effect of different land uses on soil physical quality indices. Three land uses including a natural pasture, dryland farming and irrigated farming were selected. From natural pasture 54 samples, dryland farming 40 samples and irrigated farming 17 samples were collected in the surface soil (0-15cm). Saturated hydraulic conductivity, infiltration rate, bulk density, soil distribution size, soil erodibility index, organic carbon and water aggregate stability (three classes) were determined for each land use. The results showed that mean, minimum and maximum of saturated hydraulic conductivity in irrigated farming land use is more than others land uses. Water aggregate stability index the macroaggregates (>2 mm) in irrigated farming land use is lower than others land uses. In the among studies variables, saturated hydraulic conductivity, clay percentage, soil erodibility index and water aggregate stability in macroaggregates in different land uses are significant differences in 5% level. Soil erodibility index and water aggregate stability for macroaggregates seems to be the most reliable soil quality indices for the area.