جستجوی مقالات مرتبط با کلیدواژه « بافت خاک » در نشریات گروه « زراعت »

The use of cultivated plants in the consecutive of cropping systems is one of the most important alternative and sustainable methods to eliminate or reduce the use of herbicides. To investigate the effect of crop residues on weed control and corn yield of NS640 cultivar, an experiment was conducted in 2015-2016 and 2016-2017 cropping years. This experiment was performed in two years and two places in a randomized complete block design with four replications. Two farms with clay- loamy and sandy-loam soil as a place and cultivation of four pre-corn crops including bean-branch (Vicia faba L.), wheat-Chamran (Triticum aestivum L.), rapeseed-Hayula 401 (Brassica napus L.), cabbage - Steady hybrids (Brassica oleraceae L.) and fallow were the treatments. Combined analysis of the results showed that the comparison of weed density and dry weight in different treatments of pre-cultivated plants with fallow (without pre-cultivated plants) showed the potential of pre-cultivated plant residues in reducing and controlling weeds. The reduction in the number of weeds in clay-loam field in the residues of bean, wheat, rapeseed and cabbage pre-cultivation plants compared to fallow were 22, 9, 10 and 29%, respectively, and in sandy-loam field 40, 48, 42 and 46%, respectively. Weed dry weight was significantly affected by crop residues. Bean, wheat, canola and cabbage residues reduced weed dry weight by 54, 55, 43 and 65% compared to fallow, respectively. The use of bean residues as a growing crop in clay-loamy and sandy-loam soils increased corn seed yield by 40 and 55%, respectively. The use of crop residues by higher decomposition of crop residues in the second year and creating a state of soil damage and a negative effect on weed dynamics indices can play an effective role in improving corn growth and increasing the productivity of the cultivation system.

Saffron (Crocus sativus L.) is one of the most expensive crop which is grown in restricted areas of the world. Due to its economic values, some farmers, based on similarities of climatic conditions have cultivated it in some regions of country regardless of land capability and suitability, which sometimes the result was not satisfactory. Saffron yield prediction based on soil properties enables us to assess the land suitably for cultivation of this valuable plant. For this purpose, 100 soil samples were collected from Vamenan Saffron fields in Golestan province and the soil chemical and physical properties including the percentage of constituents of the mineral part of soil texture (Sand, Silt, Clay), Phosphorus, potassium, Nitrogen, pH, Electrical Conductivity (EC), Organic matter and Calcium Carbonate Equivalent were measured. In addition, the weight of Saffron wet flower (kg.Ha-1) was measured. In the present study, various combinations of soil properties as input were applied and nine models were developed using artificial neural networks and multiple linear regression models for predicting the saffron yield. Performance of the models was validated using Root Mean Square Error (RMSE), Correlation Coefficient (R) and Geometric Mean of Error Ratio (GMER) methods. The results of the correlation analyses showed phosphorus and organic matter are most effective factors in the production of Saffron. Results showed that performance of the models is much different where R2 value varies from 0.45 to 0.89. Comparing the performance of Saffron yield estimation models indicated the optimal model was obtained from the combination of phosphorous, organic matter, potassium and calcium carbonate equivalent as input and values of R2 and RMSE equal to 0.874 and 0.996 kg.ha-1, respectively.Evaluation of model results indicated that the coefficient varied was obtained from 0.45 to 0.89. The best model in saffron yield estimation was obtained when phosphorous, organic matter, potassium and electrical conductivity were as the input, so that values of R2 and root mean square error (RMSE) were obtained 0.891 and 0.89 kg.ha-1, respectively.

One of the most important requirements in planning production and processing of medicinal plants in order to obtain high yield and high-quality is the initial assessment of the soil physical and chemical properties, which can reduce the production cost by avoiding the use of unnecessary soil analysis. Summer Savory(Satureja hortensis L.)is one the most widely used medicinal plants that quality index of plant is related to the quantity and the constituent of its essential oil content.Understanding the relations between the quantity and quality of medicinal plants with the several physical and chemical properties of soil is very complex and the estimation of parameters changes of medicinal plants affect by soil quality characteristics is more difficult. Today, with the introduction of multivariable regression models and artificial network models in the research, many complex relationships found in nature is understandable.Hence the need for estimation of the essential oil yield of savory using fast, cheap and acceptable accuracy methods is necessary. The present study was performed as pot experiment based on completely randomized design with 3 replications. Fifty three soil samples were collected from different parts of Nishabur, and easily available soil properties including sand, silt and clay percentage, organic matter, pH, salinity, phosphorus, potassium, nitrogen and carbon contents of the soil samples were measured at laboratory and the primary results were obtained. Approximately 90 days after seed planting in mentioned soil samples, the sampling of plants was done based on the treatments. Samples were placed for 24 hours in an oven at 40 °C, for drying. Finally, the relationship between the essential oil yield and easily available soil parameters was determined using artificial neural network by Matlab7.9 software. To obtain the most sensitive parameters, sensitivity analysis was calculated by using sensitivity coefficient without dimension method. So that, if the parameter value is more than 0.1, then that parameter is considered as the sensitive parameter of the model. An artificial neural network is simulated from a human neural network model, which, after training, estimates the output parameters by applying the input parameters. In this research, the perceptron neural network structure was used with Marcoat Levenberg training algorithm to estimate the essential oil yield from easily available soil parameters such as soil texture, organic matter, and macro elements. The high R2 values and the low RMSE values indicate that predictive data are close to the measurement data and high accuracy of the model in the estimation of summer savory essential oil yield. Based on this, soil texture parameters (sand, silt and clay percentages) and organic carbon, organic matter, salinity, potassium and soil acidity were selected as the most sensitive parameters, respectively. High values of R2 and low levels of RMSE mentioned the proximity of the forecast data with measurement data and high accuracy of the model in summer Savory essential oil yield estimation. Accordingly, the parameters of organic carbon, nitrogen, phosphorus, organic matter, potassium, pH, salinity, clay, silt and sand respectively were selected as the most sensitive parameters. The results showed that the created neural models were not able to estimate the essential oil yield of summer savory with a maximum accuracy (R2=0.50).Among the 8 fitted models, a model based on independent variables EC+texture+carbon+organic matter + potassium + pH was better than the other, but the high number of input factors of this model is considered to be a limitation. Since the present study is an initial assessment of the essential oil yield of medicinal plants, it is recommended to continue the research in this regard as well as to predict the performance of other medicinal herbs.

Many factors including climate, type of rootstock, soil properties, geological factors, plant nutrition and irrigation affect the quantity and quality of orange fruit. In this study, the relations between citrus orchards conditions, their soil properties and leaf elements concentration and fruit quality were evaluated. The experiment was conducted as a randomized complete block design and soil, fruit and leaf samples were collected from six different regions of Darab, Fars, Iran. After fruit sampling, land properties such as physiographic features, slope, gravel, altitude and soil physical and chemical properties such as percent of sand, silt, clay, organic matter, calcium carbonate, pH and electrical conductivity and also N, P, K, Fe and Zn availability were determined. Several morphological and qualitative characteristics of fruit including, rind and flesh weight, rind thickness, length, diameter, fruit granulation, flavor, sugar and fruit juice acidity were determined. The contents of N, P, K, Fe and Zn in the collected leaves were determined. Three random samples were taken for each orchard and each replicate consisted of one tree. Results showed that fruit weight was correlated with the land slope, soil pH, electrical conductivity, soil organic matter content, soil N, P and K and leaf K content. Rind thickness showed a significant positive correlation with parameters such as land slope, electrical conductivity, organic matter, silt, clay and soil N, P and Zn and leaf N and K content. However, there was a significant negative correlation between rind thickness and soil gravel and sand contents. The relations between fruit granulation and soils calcium carbonate, gravel, organic matter content and soil K concentration were significant. TSS to TA ratio in fruit juices had significant negative correlation with land altitude, soils silt, calcium carbonate contents and leaf K content. Generally, many soil properties had significant effects on fruit quality but it seems that soil texture, organic matter, pH, P and K were more effective on fruit quality.

A field study was carried out to investigate the effects of four planting depths and three soil types with different physical characteristics on green bean (Phaseolus vulgaris Var. sunray) and maize (Zea mays L. Var. Amyla) seed germination and seedling emergence.The aim of the experiments was to investigate the physical effects of the soil on seed ecology and emergence dynamics. The result revealed that germination inhibition was directly proportional to clay content and inversely proportional to sand content due to burial depth. Depth of fifty percent emergence inhibition (Di50%) were equal to 5.3 cm in clay soil for both green bean and maize, if this was for silty soil, respectively 5.4 and 2.7 cm. A significant linear regression between clay particle content and Di50% revealed that those soil components had opposite effects in terms of favoring or inhibiting depth mediated inhibition. Therefore, increasing soil clay contents increased inhibition of seedlings. The data also showed that the oxygen content in the surrounding soil of seeds can not be an important factor for seed germination differences, and its effect was insignificant. Increasing geometric mean decreased particle diameter soil inhibition. In conclusion, these experiments showed soil physical properties had a strong effect on buried-seed ecology and consequently on seed germination and seedling emergence.

The rapidly growing world population places considerable pressure on increasingly scarce natural resources, spurring the need to develop more efficient and sustainable agricultural production systems to feed these growing populations. this study to evaluate the agricultural lands in Golestan province for soybeans, using Geographic Information System (GIS) and weighted linear method (WLC) was performed. For this purpose, the needs of the crop and environmental variable factors were determined and graded and according to current elements prepared required map. Studied Physiographic variables were consisted of slope, aspect, elevation and the soil texture. Data were standardized by fuzzy method, and Analytic Hierarchy Process (AHP) was used for weighting the criteria. Finally, soybean cultivation potential map were prepared with using weighted linear combination (WLC) in the software IDRISI The results showed the highest amount weighty criteria by the Analytic Hierarchy Process in the soybean soil texture (0.5228) and elevation whit (0.0765) had the lowest coefficient in the rankings. Then zoning of lands carried out in 4 classes (high suitable, suitable, less suitable and non-suitable Generally results of the weighted linear combination of Physiographic showed that 11.08 and 37.60 percent of the lands for soybean production areas were located in high suitable and suitable zones. In addition, limiting factor of the soybean cultivation in the Golestan province can be cited soil texture.

Since the soil is considered as the most important source of nutrients, understanding the spatial variation and geographical distribution patterns of nutrients is crucial for the proper management and the right application of fertilizers. Nowadays, soil management based on spatial variability of soil properties in crop growth is necessary (Morales et al, 2011; Bijanzadeh et al, 2014). However, accurate estimates of soil properties in all areas are not time and cost effective. Therefore, interpolation is a suitable solution to estimate not sampled areas. There are different techniques for predicting the soil characteristics in not sampled areas such as geostatistics (Mohammadi, 2007). Therefore, this study aimed to evaluate the physical and chemical properties of some soil paddy fields in Foumanat, Guilan province using the geostatistics technique. The present study was performed in Foumanat plain during two cropping seasons of 2013 and 2014. Soil samples were taken from 45 fields and geographic coordinates were recorded. Soil properties including electrical conductivity, cation exchange capacity, organic matter, pH, clay, silt, sand were measured. Interpolating of variables were investigated with kriging (KG) and inverse distance weighting (IDW) methods with power one to five. The best interpolation method was selected using evaluating statistics such as Mean Absolute Error (MAE), Mean Bias Error (MBE) and Root Mean Square Error (RMSE). Results indicated that electrical conductivity, cation exchange capacity, pH and silt fitted by an exponential model while two parameters of organic matter and sand along with clay were fitted by the spherical and Gaussian models, respectively. High determination coefficients for sand, clay and electrical conductivity were 0.95, 0.83 and 0.80, respectively. According to the calculated variograms, electrical conductivity and sand exhibited a medium spatially structured variability whereas highly structured variability was observed for soil CEC, organic matter, pH, clay and silt. Least nugget effect among the studied variables was allocated to CEC, organic matter and sand. The results showed that the IDW method provided more accurate and less error for CEC, organic matter, pH and silt in the study area as compared to the kriging method. Moreover, there were not differences between the two methods of IDW and kriging in terms of electrical conductivity, clay and sand parameters. Overall, the fertility of paddy fields was statistically different. The most coefficient of variation (CV) from 15 to 24 percent, the average variation were found in electrical conductivity, sand and clay while the amount of CV in the cation exchange capacity, organic matter, pH and silt were recorded lower than 15% (low diversity). In the studied characteristics, two types of medium and strong structures were observed. In general, the results of this study can be used to estimate the fertility and physical and chemical characteristics of rice farms. Therefore, these results could help to adopt crop improvement methods including crop choice and site-specific fertilizer recommendations to optimum management of inputs and sustainable production.

In order to determine optimum culture condition to produce high quality storage roots in sweet potato, an experiment was conducted as split-split plot in randomized complete block design with three replications. Main plots were allocated to soil texture (loamy and sandy), sub plots to irrigation method (furrow and drip) and sub-sub plots to sweet potato cultivars (White and Red). Cutting establishment percent, bush vegetative growth, qualitative and quantitative characteristics of storage root as well as crop per drip (CPD) were measured. Results showed that soil texture affects foliage fresh weight, shoot/root ratio, storage root number, weight and diameter, stem and leaf number, bush length, reducing and total sugar as well as CPD. Irrigation method influenced all the traits except root number. The greatest CPD was observed in loamy soil using drip irrigation respectively 5.492 and 4.569 kg/m3 for White and Red cultivar. According to path analysis results, storage root yield directly influenced by foliage fresh weight (0.726**), leaf number (0.722**), stem number (0.710**), storage root weight (0.668**), storage root diameter (0.449**), foliage length (0.352**) and storage root length (0.314**). Based on the obtained results, cultivation of Red cultivar on loamy soil using furrow irrigation at cutting establishment stage, drip irrigation during growth period and final furrow irrigation at storage root filling is more successful as a tool to produce high quality sweet potato storage root in Minab.

Nineteen irrigated farms of canola from six cities of Khorasan selected to assess the seedling emergence one month after sowing in 2009. Soil texture of each farm determined using the Hydrometer method. The results showed that weather conditions of sowing areas had no significant effect on emergence of oilseed rape. With increasing the temperature (within the range of 19. 5 to 21. 5 ˚C) emergence percentage was not increased significantly. Rainfall also caused no significant effect on seedling emergence. The percentage of emergence in machine-sowing and hand-sowing were 38. 4% and 28%، respectively. Soils with loam silt، silt clay loam and loam texture had emergence of 27. 2%، 31. 2% and 47% respectively. It seems soil texture plays a great roll on the emergence of oilseed rape with epigeal seedlings.

The objective of this study was to determine the allowed and desired limits for heavy soils of texture (clay loom)، as it has operational capability (friability)، These limits were 6. 34 mm for planting and 10. 62 mm for harvesting in each raining or irrigation episode. We determined some factors that affect soil wetness and water content as follow: the amount and severity of rain، the condition of soil’s drainage، the percent of air moisture، evapotranspiration، the amount of runoff، the amount and severity of sunlight، the ambient temperature، the condition of vegetation and، the soil texture. The time needed for dryness and removal of soil moisture as evapotranspiration in each over- desired and allowed capacity rains are 5-7 days. Also، because of higher evaporation in planting time (late April and early May) than in harvesting time (November)، and also higher surface temperature in spring، both result in moving the vapor from deeper layers of soil to surface. Therefore، as our result showed، the time needed for readiness of soil for machinery operation at time of planting are 5 days for planting (late April and early May) and 7 days for harvesting time (November). According to our calculation، 19. 5% of rains at planting time and 7. 5% at harvest time changed to run- off; and with taking this amount of run- off in account at allowed- limit calculation، and also because of texture of the studied soil، the maximum allowed rain in which the soil remains in proper condition for machinery planting and harvesting activities exceeded 7. 6 and 11. 41 mm in each rainy day. As a result، according to limiting factor of well doing of operations and also factors affecting these restricting factors، the number of working days for mechanized planting operation was found to be about 19. 69 days and also 21. 98 days for harvesting operations in farms with heavy soil with 98% of probability.

In order to study the effect of different resources of farmyard manure, compost and biofertilizers on grain yield and quality of canola (Talaieh cultivar), an experiment was conducted at Kurdistan region in 2008 and 2009 growing season. Experimental units were arranged in split-split plots design based on randomized complete blocks with three replications. Main plots consisted of two locations with difference in soil texture (L1): Agricultural Research Center of Sanandaj and (L2): Islamic Azad University of Sanandaj, as location levels. Also, five strategies for obtaining the base fertilizer requirement including (N1): farmyard manure; (N2): compost; (N3): chemical fertilizers; (N4): farm yard manure + compost and (N5): farm yard manure + compost + chemical fertilizers were considered in split plots. Four levels of biofertilizers were (B1): Bacillus lentus and Pseudomonas putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus and Pseudomonas putida & Trichoderma harzianum; and (B4): control. Results showed that location, different resources of fertilizer and interactions of them have a significant effect on grain yield. The highest grain yield (4660 kg/ha) was obtained from treatment, that farmyard manure, compost and biofertilizers were co application in clay loam soil (Gerizeh station). Location, basal fertilizers and biofertilizers have a significant effect on N, S and N/S of canola seed. Co application of compost and farmyard manure produced highest percent of olieic acid (61.5 %) and linoleic acid (22.9%). Co application of compost and farmyard manure has a significant increase in oleic acid and linoleic acid. Finally, L1N5B3 treatment, that compost, farmyard manure and biofertilizers were co application in Gerizeh station in compare to other treatments, selected as a best treatment of experiment.