Volume 38 - Issue 1
Soil Biology, Biochemistry and Biotechnology
Majid Baghernejad
Abstract
Abstract Introduction Drought stress is one of the important environmental factors that limit distribution and productivity of major crops. Drought stress caused by reducing the availability of external water, which makes reduces the ability of the plant’s roots to take up nutrients and induced ...
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Abstract Introduction Drought stress is one of the important environmental factors that limit distribution and productivity of major crops. Drought stress caused by reducing the availability of external water, which makes reduces the ability of the plant’s roots to take up nutrients and induced cellular and photo-oxidative damages, through the increased accumulations of reactive oxygen species. Plant growth promoting rhizobacteria and arbuscular mycorrhizal fungi by using different mechanisms such as production of siderophores, organic acids, proton, growth regulators, and other chelating agents, and creative of reductive conditions, increase dissolution of minerals and mobility of non-soluble nutrients and thus improve nutrients uptake and yield of plants. They can influence plant root morphology and change the quantity and quality of root exudates. Mycorrhizal symbiosis involves a complex interaction among plant, soil and mycorrhizal fungi. Arbuscular mycorrhizal associations' relationship are rather important in crops because they are believed to increase nutrients uptake, improve plant fitness, and plant water relations and thus increase the drought resistance of host plants. Plant growth promoting rhizobacteria improve water relations of plants in part due to increases of plant growth, nutrient uptake and antioxidant activities. Maize is an effective host of arbuscular mycorrhiza in infertile and drought conditions and its root system consists of different root types. Therefore, the objectives of this study was to evaluate the effects of Glomus intraradices, Pseudomonas fluorescens (as a PGPR bacterium) and drought stress on growth characteristics and micro-nutrients uptake of maize in a calcareous soil under maize cultivation. Materials and Methods A greenhouse experiment in a factorial completely randomized design was conducted to evaluate the effects of arbuscular mycorrhizal (AM) fungus (Glomus intraradices), Pseudomonas fluorescence, and drought stress on root colonization and absorption of micro-nutrients (Fe, Mn, Zn, Cu) by maize (Zea mays). The factors were consisted of arbuscular mycorrhizal fungus at two levels: G0 (not inoculated with fungus) and G1 ( inoculated with Glomus intraradices), bacteria at two levels: B0 (not inoculated with bacterium) and B1 (inoculated with Pseudomonas fluorescence) and drought stress at four levels: S0 (without stress), S1 (75% FC), S2 (50% FC) and S3 (25% FC). Mycorrhizal inoculum was prepared through the trap culture of forage sorghum (Sorghum biocolor L.) with spore of Glomus intraradices. The potential of inoculum (spore numbers of 12 g-1 substrates and root colonization of 80%) was measured for spore extraction and counting, and evaluation of root colonization. The bacterium used in the present experiment was Pseudomonas fluorescens and provided by soil biology and biotechnology laboratory of College University of Agriculture and Natural Resources of Tehran University, Karaj, Iran. The bacterium had a high ability to dissolve poorly soluble organic and inorganic phosphate compounds, to produce siderophores, indole acetic acid (IAA), and 1-aminocyclopropane-1-carboxylate (ACC)-deaminase enzyme. A non-sterile composite soil sample was collected from depth of 0-30 cm soil surface of Agriculture Research Station of Shiraz University, Shiraz, Iran (fine, mixed, mesic, Calcixerollic Xerochrept). The samples were air-dried and passed through a 2mm sieve. Some physical and chemical properties of studied soil are measured. The seeds were inoculated with 1mL fresh and active suspension of bacterium (population of 1×108 colony-forming units (CFU) per milliliter). After a growth period of 4 months, plant materials harvested and data were subjected to analysis of variance and means were compared by least significant difference. Results and Discussion In non microbial treatments, wet and dry weights of shoot significantly decreased whereas other measured parameters had not significant changes under drought stress of 25% FC. At each level of drought stress, root colonization significantly higher in mycorrhizal treatments than non mycorrhizal treatments. The highest root colonization percent was observed in treatments of co-inoculation of plant with both inoculants. Co-inoculation of plant with both inoculants significantly increased morphological properties and shoot nutrients uptake except Fe uptake in comparison with non microbial treatments up to drought stress of 50% FC. Conclusion All measured parameters ( leaf area, wet and dry weights of root, root colonization, shoot micronutrient uptake) except wet and dry weights of shoot significantly decreased with increasing of drought stress up to 25% of FC. Single and co-application of bacterium and fungus decreased the negative effects of drought stress under low levels of water stress. Root colonization significantly increased with single application of fungus and co-inoculation of plant with fungus and bacterium. Co-application of fungus and bactrieum increased shoot nutrients uptake except Fe uptake up to 50% FC in comparison with non inoculated treatments.
Research Paper
M Alizadeh; M Chorom; N Enayatizamir
Abstract
Introduction: After salinity, drought is of the most common environmental stress for plants in the world and a significant proportion of natural ecosystems and agricultural world is located under salt stress. In general, preventing plant growth of salinity may be due to improper plant photosynthesis, ...
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Introduction: After salinity, drought is of the most common environmental stress for plants in the world and a significant proportion of natural ecosystems and agricultural world is located under salt stress. In general, preventing plant growth of salinity may be due to improper plant photosynthesis, and stomata closure due to the limitation of carbon dioxide is absorbed. Previous studies have shown an increase in the electrical conductivity of the soil with microbial biomass, microbial respiration, and plant residue decomposition rate is negative. The results of studies have showed that the organic matter in soils with high salinity levels even with low vegetation can cause grow the microbial populations resistant to salinity, rapidly. Therefore, the increase residual plants enhance the activity of soil microbes which are beneficial to decompose and release carbon dioxide, nitrate and other ingredients. In arid and semi-arid lands soil organic matter in the soils is generally poor, because of the high temperature maintain and preserve organic matter in these soils is very difficult. Although the use of mineral fertilizers is apparently the faster way is to maintain soil fertility, but the high cost of fertilizer, and cause soil pollution and environmental degradation, is unfavorable act. The aim of this study was to evaluate the effect of plant residues on soil microbial characteristics such as carbon, nitrogen and phosphorus biomass influence on barley plant growth at different levels of soil salinity. Materials and Methods: To make salty soil 40 liters of salinity effluent collected with EC about 33.4 dS /m and after the initial analysis, was diluted and three levels of salinity (2, 4, 8 dS m) were created. After preparing the soil with 3 levels of salinity (2, 4, 8 dS/m), 2 types of debris from wheat straw and alfa alfa (2 levels, zero and 100 g per pot) with 3 replications (total of 36 pots) were prepared. After cultivation of barley seeds, the pots were irrigated. The experiment was conducted in a completely randomized design in a greenhouse. Wet pots were kept at 60 percent of field capacity and irrigation was done by weight. To evaluate the plant's response to the effects of crop residue added at the end of the experiment, after 60 days, shoot and root samples were collected. All samples of barley leaves and stems of the plants were collected two months after planting. The amount of chlorophyll by chlorophyll meter was measured manually by Spad units. Plant height was determined by ruler from the surface to the end of the cluster. For the measurement of pH and EC plant debris from shattered remnants extract ratio (1: 8) was used. Carbon and nitrogen biomass by fumigation extraction method was measured. Results and Discussion: Effect of salinity and crop residue application on barley plant height was significant at 1% level. But, there was no significant interaction between salinity and treated straw. The effect of wheat residue treatment was significant on plant height, but showed a decreasing trend with increasing salinity. Comparison of means of salinity levels showed the greatest reduction in leaf area in 3 salinity levels of the treated straw and the lowest was of the hay treatment. The comparison of means of salinity levels showed that the treated straw had the lowest chlorophyll compared to other treatments. The effect of the addition of plant residues in different levels of salinity on microbial biomass carbon was significant at 1% level. Adding mineralization of organic waste leads to increased precursor enzymes and microbial growth increases. The results showed that moderate amounts of carbon, nitrogen and phosphorus microbial biomass was affected by increasing salinity in reverse. The amount of phosphorus added to the soil was deeply influenced by phosphorus ratio of carbon to biomass and biomass is phosphorus. P ratio of carbon to biomass increased by reducing the availability of phosphorus. Changes in the ratio of carbon to microbial biomass P refers to changes in microbial communities in soil. Reduced microbial biomass carbon in soils containing straw because of organic compounds toxic like phenols produced the soil micro-organisms. Increased alfalfa and crop residue as organic fertilizer to the soil salinization significantly affects the microbial biomass nitrogen. Comparison of the results showed that microbial biomass phosphorus in 3 salinity levels was, at 1%, significantly different from control and treatment straw and in between treatments; alfalfa treatment significantly increased microbial biomass phosphorus. Conclusion: The results indicated that salinity reduced height, leaf area and plant chlorophyll content of barley. Added plant residues at different levels of salinity, while increasing soil organic matter and soil microbial, somewhat affected the barley crop yields. This effect was different depending on the type and quality of plant residues. Hay debris due to available nutrients, especially nitrogen and phosphorus, reduced soil salinity, and crop yield was somewhat increased, but the impact of wheat residues was not observed on the plant atmosphere. The results also showed that with increasing salinity of soil, microbial indexes such as microbial biomass carbon and nitrogen was decreased.
Research Paper
Maryam Jamshidsafa; Bijan Khalili Moghadam; Siroos Jafari; Shoja Ghorbani
Abstract
Introduction: Wind erosion is not only a basic geomorphic process of eroding and altering landforms but also one of the main causes of sandy desertification in arid and semiarid areas (Chepil 1945; Nordstrom and Hotta 2004). Single-grained, fine sand dunes are usually composed of none-strength materials ...
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Introduction: Wind erosion is not only a basic geomorphic process of eroding and altering landforms but also one of the main causes of sandy desertification in arid and semiarid areas (Chepil 1945; Nordstrom and Hotta 2004). Single-grained, fine sand dunes are usually composed of none-strength materials with a low water retention that make them susceptible to wind erosion. They lack organic matter and are inherently of low fertility (Ahmadi, 2002). Therefore, sand dunes and drift areas require non-oil artificial covers for their stabilization and that of the vegetation cover (Rezaie, 2009). The covering material types include oil (Rezaie, 2009), flat crop residues (Chepil, 1944; Bilbro and Fryrear, 1994), standing residues (Siddoway et al., 1965; Bilbro and Fryrear, 1994), pebble (Li et al., 2001), cotton gin trash, clay, gravel, picket fence, brush, straw, and hay (Fryrear, 1985). Soil properties including compressive strength, plasticity, compactibility, strength characteristics, elastic modulus, crushing strength, unconfined compressive strength, erodibility, shear strength, and permeability have been investigated for evaluating mulch effectiveness. Improvements have been achieved in sand dune stabilization by decreasing permeability and enhancing strength properties. The effect of soil properties on wind erosion has been studied through shear strength of soil surface which includes a frictional term (due to inter-particle frictional strength) and a cohesive term (due to intrinsic bonds among particles) (Koolen and Kuipers, 1983; Alizade, 2009). As regards the factors influencing soil shear strength, soil particle diameter, bulk density, cohesion, aggregate index, water content, crust, and organic matter have all been found to influence wind erosion (Raji et al., 2004; Homauoni and Yasrobi, 2011). Based on these observations, it may be hypothesized that soil cohesion caused by mulching operations could be effective in reducing wind erosion. Filter Cake is residue produced in huge amounts by the agro-industry that is composed of cellulosic substances, CaCO3, N, P, K, organic matter, and clay. The objective of this research is feasibility of Filter Cake using as a Khuzestan sugarcane residues for adopted-environmental mulch production. Materials and Methods For this purpose, Factorial experiments in completely random design form were conducted that factors included mulch kind(5 organic mulch and oil mulch), thickness(1 or 2 layers) and precipitation. In this study, Filter cake and clay soil samples (Albaji-Ahvaz) were used to make sugarcane mulches. A sand dune sample was selected as bed for applying the mulch. To select the right ingredient and treatments, Filter cake, clay samples were mixed with water in try and error, and producted suspension sprayed on sand dune bed. Surface surface soil shear strength, penetration resistance, soil adhesion and mulch’s internal frictional angle and erodibility were measured by shear vane, penetrometer, Zhang’s shear device, wind tunnel respectively. Results and Discussion The results determined that there is significant effect (p<0.01) on surface shear strength and penetration resistance in different much and thickness. But there is no significant effect on soil adhesion and mulch’s internal frictional angle because Zhang’s shear device hasn’t essential sensitive to differentiate them. Based on this research, Mulch 1(50g clay+150 g Filter Cake) is selected as superior mulch in Ahvaz sand dune stabilization because of higher surface shear strength and penetration resistance rate. It is defined as the resistance soil materials can offer against shear stress. This property is directly related to the cohesive and friction forces between soil particles (Koolen and Kuipers, 1983; Knapen et al., 2007; Khalilmoghadam et al., 2009) and, thereby, related to soil intrinsic properties such as clay content, salinity, and organic matter content (Horn et al., 1994). Sugarcane residues due to their effects on cohesive forces affect soil strength via the physical and chemical properties of Filter Cake. In this study, increases in SAR were found to be inversely proportional to SSS and PR. With identical values of SAR, treatments with higher EC values exhibited greater saturated SSS and PR. This shows the adjusting effect of EC on SAR effects. It is, therefore, concluded that the combined Filter Cake and clay soil could strongly affect soil resistance to erosive shearing stresses and wind erosion under environmental conditions. Conclusion Sugarcane mulches were shown to be effective in stabilizing sand dunes as compared to oil mulches. It is, therefore, concluded that the combined Filter Cake strongly influence to erode under environmental conditions.
Research Paper
H Zaki Dizaji; S Minaei; T Tavakoli Hashtjin; M Mokhtari Dizaji
Abstract
Introduction: It is known for a long time that ultrasound offers unique features in food industry and also agricultural industry for characterizing products in their intact state, with no sample preparation and no sample destruction. However, it is used still mostly in research environment and there ...
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Introduction: It is known for a long time that ultrasound offers unique features in food industry and also agricultural industry for characterizing products in their intact state, with no sample preparation and no sample destruction. However, it is used still mostly in research environment and there is little available research about fruit quality assessment by ultrasonic technique in IRAN. Knowing the quality of agricultural products not only from the perspective of export and domestic consumers is important interests, but it also helps to control and reduce its postharvest losses. Determination of the quality of agricultural products such as fruits and vegetables is important in commercially competitive modern agriculture. Physiological degradation of pomegranate results in reduced quality exhibited as peel softening and loss of freshness. Native land of the pomegranate (Punica granantum L) is IRAN and it is an important tree of the tropical and subtropical regions of the world which is valued for its delicious edible fruit. Among the native fruits grown for export, pomegranate has a special significance. According to the FAO statistical report, Iran is the first producer and exporter of pomegranate in the world. Despite its importance, its basic tissue attributes and whole fruit maturity has not been studied. On the other hand, pomegranate fruits are not maturity indicators obviously such as tomato. For this reason pomegranate was selected for the current research. In this study, ultrasonic technique is utilized as a suitable method for quality determination of pomegranate fruit. Materials and Methods: Ultrasonic technique is one of the earliest nondestructive testing (NDT) methods, which is still under development for quality determination of agricultural products. In this research, pomegranate quality was evaluated using Ultrasonic technique and punch test (Magness-Taylor). In line with previous research work, a novel ultrasonic system dubbed “Ultrasonic Qualimeter System” (UQS) and its control programs, “Ultrasonic Qualimeter System software“(UQSS) with central frequency 40 kHz were utilized to evaluate ultrasonic indices of pomegranate fruit in four quality classes of unripe(hard), ripe(medium), overripe(soft) and decayed(so soft). This ultrasonic system works based on processing the signal passing through the materials. The ordinary indices of the through-transmission ultrasonic test are wave velocity and attenuation coefficient. The other ultrasonic index is root mean square that is calculated in time zone of the digital signals. Firmness as a mechanical property, and ultrasonic wave velocity as an ultrasonic parameter, was selected to assess pomegranate quality. Evaluation of pomegranate quality was carried out through testing of its tissue and peel. The firmness index of pomegranate peels was metered by the punch test using universal material test machine (Hounsfield, H50 K-S, England). Results and Discussion: UQS were successful in transmitting ultrasound wave through pomegranate tissue (1-2 cm thickness) and peel, but results of excited and received signal processing showed that due to its non-homogenous tissue pomegranate vigorously diminished the intensity of transmitted waves. By comparison, the attenuation coefficient of pomegranate peel and its tissue is higher than that of the other agricultural products such as potato and avocado. Statistical analysis demonstrated that the quality of pomegranate fruit can be assessed using ultrasonic technique, so that decreasing freshness of pomegranate peel samples leads to decrease of wave velocity from 290 (unripe fruit) to 63 m/s (decayed fruit). In other words, depending on samples quality levels, transmitted wave velocity is varied about 230 m/s for pomegranate peel samples. One of the mechanical properties that are most useful to demonstrate fruit quality conditions is stiffness. Initially, analyses showed that Chart trend of stiffness in four quality levels is similar to wave velocity. So non-linear regression models were developed with good correlation (R2=0.83) between the firmness and ultrasonic velocity. Results of regression analysis demonstrated that ultrasonic indices of pomegranate peels can be used for inspection of pomegranate quality conditions. Conclusion: The first step in nondestructive assessment of any medium is introducing fitness index or indexes in which it can show the medium conditions. In this research, statistical analysis demonstrated that the quality of pomegranate fruit can be assessed by ultrasonic technique. However, it is necessary to carry out more research to improve this technique for widespread applications. To use this method, the ultrasonic system should be modified so that the transmitted and received transducers test the whole pomegranate by its peels.
Research Paper
R Taghizadeh-Mehrjardi1; F Sarmadian; A. A Zolfaghari; A. Jafari
Abstract
Introduction: Cation exchange capacity (CEC) has long been input parameter of many environmental models (Manrique et al., 1991). Added to this, CEC data can give more clear and complete interpretation of soil, plant nutrition process and consequently fertilizer and soil amendment requirements. Laboratory ...
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Introduction: Cation exchange capacity (CEC) has long been input parameter of many environmental models (Manrique et al., 1991). Added to this, CEC data can give more clear and complete interpretation of soil, plant nutrition process and consequently fertilizer and soil amendment requirements. Laboratory analysis is the most accurate method for direct measurement of CEC. However, direct measurement of CEC is difficult, particularly in the soils of arid and semi-arid regions of Iran, due to large amounts of calcium carbonate that makes measuring expensive, laborious, and time-consuming (Amini et al., 2005). It can be an appropriate approach to predict CEC from readily available properties via developing nonparametric or parametric methods (Minasny et al., 1999). Therefore, the objectives of this study were to compare and apply different data mining approches including multi-linear regression (MLR), multi-nonlinear regression (MNR), cascade neural network (CNN), two radial base functions (RBF), multi-layer perceptron neural network (MLP), and adaptive neuro-fuzzy inference system (ANFIS) to estimate cation exchange capacity in different soils of Iran. Materials and Methods: For this purpose, 1770 soil samples were selected from different sites in Iran from which 356 samples were used as the testing data, and the remaining 1414 soils were employed as the training. The soil samples were dried, crushed and passed through a 2 mm sieve to prepare for physical and chemical analyses. The percentages of sand (50 -2000 mμ), silt (2-50 mμ) and clay (<2μm) were determined using the hydrometer method according to USDA soil textural classification system. The soil organic carbon was determined using Walkly-Black method and the CEC was measured by the standard method. Then the data mining techniques (i.e. MLR, MNR, CNN, RBF, MLP, ANFIS) were applied to predict CEC from readily available data (i.e. soil organic carbon and clay percentages). Finally, to compare efficiencies of these techniques, different error criteria including root mean square error (RMSE), mean error (ME), coefficient of determination (R2) and relative improvement (RI) were applied. In the present research, an effort was made to calculate the uncertainty of pedotransfer functions using Monte Carlo technique. Results and Discussion: Statistical analyses indicated the soil organic matter and soil texture have the highest variation. For example, variation of SOM has ranged from 0.01 to 2.94. Investigation of correlation coefficients shows that CEC is more related to the parameters, clay and soil organic matter content. Thus, the parameters, clay, silt, sand and organic carbon content were the input independent variables (readily available properties), and the CEC was an output dependent variable in this study. Root mean square error (RMSE) of linear and nonlinear regression was 4.74 and 4.71 meq 100g-1, respectively. This indicates that both methods are able to properly and equally predict CEC. Nonlinear recession equation increased the accuracy of prediction by 0.6 %. Results show that nonparametric artificial neural networks do not increase the accuracy of prediction CEC, significantly. The best result of neural networks was obtained using MLP. Nonparametric regression tree accuracy was slightly better than artificial neural network methods (4.53 and 4.61 meq 100g-1, respectively). The best method for prediction of CEC was ANFIS (RMSE=4.02 meq 100g-1). The accuracy of prediction using this method was 15 % more than linear regression. Moreover, the ANFIS model on the partitioned data by fuzzy k-means cloud enhances the prediction accuracy up to 26%. Monte Carlo results indicate the highest and lowest uncertainty belongs to MLR and ANFIS models, respectively. Conclusion: In the present research, different data mining techniques were applied to predict CEC in various ranges of soils. The data base related to 1770 soil samples was gathered from all over Iran. Results of the comparison indicate the highest prediction accuracy belongs to ANFIS model. Moreover, partitioning the data base to four groups enhances the accuracy of models. This result confirms that pedotransfer functions are more reliable only on the range of existing data. Overall, our efforts resulted only in R2 of 0.58. This means that soil organic matter and clay percentage could only model the 58% CEC variation. This suggests we should incorporate more input data including kind of clay mineral, percentage of calcium carbonate, gypsum, and etc.
Research Paper
L Naderloo; R alimardani; M Omid; F Sarmadian; H Javadikia; M. Y Torabi
Abstract
Introduction: Social, technical and economic factors in addition to environmental, soil and climate factors affect crop yield and cultivation. This study was implemented to know the impact of age, experience and literacy level of farmers as social factors and access to water supply, roads, silo, labor, ...
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Introduction: Social, technical and economic factors in addition to environmental, soil and climate factors affect crop yield and cultivation. This study was implemented to know the impact of age, experience and literacy level of farmers as social factors and access to water supply, roads, silo, labor, tractors and machinery and conservation tillage as technical-mechanization factors on crop yield. Fuzzy rule-based inference system converts the complex decision-making problems to the smaller criteria and makes easier the multi-criteria evaluation process. So we decided to use fuzzy approach to modeling the social and technical-mechanization indices. The main disadvantage of fuzzy systems is their inability to learn. So, the optimization of fuzzy systems is the most important step in its implementation. Genetic algorithm (GA) approach is used as a complementation of fuzzy model to optimize fuzzy rules. One method to optimize the fuzzy rules is Pittsburgh method in GA. In this method, one gene is used for every rule and the gene value finds out the rule.The kind of membership function will have a great impact on the result. The kinds of membership function for fuzzy sets involve triangular, trapezoidal, generalized bell, Gaussian, Gaussian combination, Sigmoidal, product of two sigmoidal, difference between two sigmoidal, Π, Z and S shapes. The objectives of this study are: 1- providing two fuzzy models for the social and technical-mechanization indices for wheat production 2- optimizing the fuzzy rules and the type of membership function for the fuzzy set. Materials and Methods: Fuzzy toolbox of MATLAB software ver. 7.8.0 (R2009a) was used to design fuzzy model. Fuzzy inference system (FIS) used in this study was Mamdani type that is based on if-then rules. The age, experience and literacy level of farmers were selected as input data for fuzzy social model. Access to water supply, roads, silage, labor, tractors and machinery and conservation tillage equipment were selected as input data for fuzzy technical-mechanization model. Mamdani fuzzy inference system was used to design models. Fuzzy rules were written by a mechanization expert knowledge. To correct written rules, the method of Pittsburgh in GA was used to optimize the fuzzy rules for all FISs. Then, a program was written in MATLAB software to get the best combination of membership functions to achieve the best result. The program tested 24 kinds of combined membership functions for medial and side fuzzy sets of input variables. The result was the best when the relationship between obtained index and crop yield had the highest value of the correlation coefficient (R2), minimum value of mean square error (MSE) and mean absolute error (MAE). So the fuzzy-GA model will produce the social and technical-mechanization indices while the fuzzy rules of model have been optimized and the best combination of membership functions has been selected. Results and Discussion: The coefficients of determination were obtained 0.11 for fuzzy social model and 0.51 for technical-mechanization model before optimization of fuzzy rules. The error of fitness function decreased with rising generation numbers of GA until the best answer was obtained. After optimization of fuzzy rules by genetic algorithm, these values increased to 0.50 and 0.71 for the fuzzy social and technical-mechanization models, respectively. This result showed that optimizing the fuzzy rules had a significant impact on results of models. After implementation of the written program, to select the best type of membership functions for fuzzy input variables, coefficient of determination varied from 0.14 to 0.51 and 0.1 to 0.73 for the fuzzy social and technical- mechanization models, respectively. This result showed that the effect of social factors on wheat yield was less than technical-mechanization factors and yield can be predicted by technical-mechanization factors with more accuracy than social factors. In the social model for input of experience, the lowest MSE and the highest R2 belong to a FIS with three fuzzy sets and S, Π and Z-shaped membership functions for the right, medial and left fuzzy sets, respectively. In the technical model for input of road availability, the lowest MSE and the highest R2 belong to a FIS with three fuzzy sets and s, trapezoid and z- shaped membership functions for the right, medial and left fuzzy sets, respectively. These results showed that the type of membership functions for fuzzy sets had considerable importance for the accuracy of the model. Conclusion: It can be concluded that the accuracy of the fuzzy model with optimized rules by GA and the best type of membership function for fuzzy sets are considerable. Effect of technical-mechanization factors on wheat yield was more than social factors. This result also showed the strength of fuzzy–GA method in modeling of such issues.
Research Paper
M Aalipour Shehni; A Farrokhian Firouzi; A Koraie; H Motamedi
Abstract
Introduction: Preferential flow is one of the major processes influencing the rapid movement of pollutants to ground water. Macropores created by plant roots provide pathways for rapid transport of pollutants in a soil profile. The growth of plant roots into soil causes creation of big pores that ...
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Introduction: Preferential flow is one of the major processes influencing the rapid movement of pollutants to ground water. Macropores created by plant roots provide pathways for rapid transport of pollutants in a soil profile. The growth of plant roots into soil causes creation of big pores that improve water movement and solute transport through soil profile. Field soils or undisturbed soils have many different types of macropores. These macropores may contribute to preferential flow. Therefore, to better evaluate the macropores that are created by plant root in preferential flow, it is essential to isolate the macropore and examine that macropore individually. The main objective of this study was quantitative investigation of the effect of plant root on chloride transport through soil profile under a saturated condition. Materials and methods: In order to investigate the influence of corn root system on soil hydraulic properties and chloride transport in soil an experiment was conducted in completely randomized design. The treatments were prepared as bare soil (control), soil with corn (Zea mays L.) root and soil with corn root 3 months after harvesting in 9 soil columns packed uniformly with loamy sand-textured soil (Bulk density=1.48 g/cm3). The particle size distribution and organic carbon of soil were determined. Saturated hydraulic conductivity was measured for each soil column using constant head method. The breakthrough curves of chloride were measured under saturated condition (constant head method). Before starting the displacement experiment, the soil columns were subjected to capillary saturation from the bottom with 0.01 M CaCl2 for two consecutive days. In order to establish steady state flow conditions, the soil columns were irrigated with a 0.01 M CaCl2 solution at a constant rate and less than 0.5 cm of water was ponded above the soil surface. The chloride concentration in the outflow samples was measured using an electrical conductivity sensor. For measuring the chloride breakthrough curves (BTCs), the 0.01 M CaCl2 solution was replaced by a 0.05 M CaCl2 solution. The chloride transport in the soil columns was simulated using CXTFIT Convection-Dispersion Equation (CDE) and Mobile-Immobile Model (MIM). A nonlinear least-squares program was used to fit the convection-dispersion equation (CDE) and the physical nonequilibrium model (MIM) to the experimental data. Results and Discussion: The research result showed that macropores created by growing and remaining of plant root (Zea mayz L.) have a significant effect on soil hydraulic properties and solute transport.The results indicated that there is significant difference between soil hydraulic properties (saturated hydraulic conductivity and Darcy's flux density) in different treatments (p<0.05). Darcy's flux density indices in soil columns were 1.23 and 1.31 times more than control treatment in plant root and plant root 3 months after harvesting treatments, respectively. The two models (CDE and MIM) fit the BTCs curve data well. Models fits were excellent with R2 values from 0.85 to 0.97. The CDE parameters (D and ν) in treatments had significant difference (p<0.05). Dispersion coefficient (D) values were 2.65 and 3.71 times more than control treatment in plant root and plant root after 3 months harvest treatments, respectively. Pore water velocity (ν) values were 1.36 and 1.52 times more than control treatment in the mentioned treatments.The breakthrough curves of soil with corn (Zea mays L.) root and soil with corn root after 3 months harvest treatments were asymmetrical in shape (asymmetrical with respect to the C/C0=0.5 point on the BTCs). The relative concentration C/C0 in the effluent is obtained before one pore volume of chloride is passed through the soil column. Conclusion: High flow velocity, saturated hydraulic conductivity (Ks) and dispersion coefficient (D) of the soil columns treated with plant root or with plant root after 3 months harvest indicated the presence of macropores in the soil that is created by deep corn root system. The early breakthrough of chloride BTCs reveals the existence of preferential flow, suggesting that a portion of chloride moves through soil macropores. The occurrences of preferential flow were attributed to well-connected macropores created by plant roots and decayed corn root 3 months after harvesting. Furthermore, the results of this research indicated that when considering solute transport in agricultural soil the effect of plant root needs to be considered.
Research Paper
N Kazemi; M Almasi; H Bahrami; M. J Shaykhdavoodi; M Mesgarbashi
Abstract
Introduction: Identifying and evaluating of variables that impact tractor performance needs correct size of the variables and their effects on parameters during the tractor operations. So it is necessary to measure accurately performance parameters for improving draft performance of tractor. Generally, ...
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Introduction: Identifying and evaluating of variables that impact tractor performance needs correct size of the variables and their effects on parameters during the tractor operations. So it is necessary to measure accurately performance parameters for improving draft performance of tractor. Generally, there must be a proper assessment and identification from operational parameters such as forward speed, slippage, drawbar pull, etc. In this regard, a lot of research has been conducted using various methods to measure and calculate these parameters under various soil condition and different implementations for achieving the maximum overall energy efficiency, analyzing various treatments and predicting experimental models. But to change soil physical properties and different reactions of machinery on the one hand and to do operations related to on the other hand, precision agriculture intervals between the measurement of performance parameters and making decision for applying operational changes in real condition of work should be as short as possible. These conditions are required to be an accurate system with high confidence ratio for executing, measuring and recording simultaneously in farm. Therefore it is necessary to develop data acquisition for calculating field performance parameters in new methods of farm management. Materials and Methods: In this study, nine different sensors were installed on a MF399 tractor for recording engine and wheel speeds, drawbar power, and fuel consumption. A processing unit was designed and the performance parameters values of tractors-implement were fed into a software to a maximum of 1000 data per second real time, and also remotely from 1.5 km distance in Excel Sheet .Early stage testing of different combinations of the nine sensors included pre-installation on the tractor with four wheels on the jack (In workshop, on tractor) and on the farm and asphalt. Results and Discussion: The results showed that for engine and wheels and the fifth wheel speed sensors (actual forward speed) are accurate the slip was calculated real time using ultrasonic flow meters with 150 cc.min-1 flow rate The lowest fuel consumption was related to the no load and stationery is also possible. About draft, load cell measures 10 Nm real time. Generally, to identifying and survey the effect of various variables on performance parameters of tractor-implements, also designing automatic control system, SSCM and spatial variability in accurate agriculture depend on accurate and precise performance data measurement and correct measurement of variables and changes of parameters during operation execution at the same time. So the installed system is designed in such way that it can measure real-time wirelessly 9 main variables to a distance of 1500 meters with max 1000 data per second including forward speed, speed of all wheels, engine speed, net fuel consumption, drawbar pull and performance parameters such as OEE% (overall energy efficiency), SFC (lit/kw-hr),SE (specific energy in Mj/ha), AFC(Ha/hr), average slip of rear and front wheel(%) , drawbar power (kw), draft(kn/m), FCha(lit/ha)… which are calculated based on the nine variables and display data in tables and graph on pc and finally save separately and totally measurement results and all raw data (pulses) in 10 worksheets into an excel file for any sensor.. It is obvious that number and type of parameters, measurement unit and table display are editable in averaged form and totally this system is installable on common tractors with trivial changes in Iran. However, RTPM (remote tractor performance monitoring) was tested in real conditions of work and of library and its performance was found to be satisfactory. With a tractor equipped with an accurate measurement tool and data acquisition unit, this study tries to make actual interval between receiving, processing and displacing data while it provides the right analysis of recorded changes for controlling automatically and applying instructions with types of operators installed on tractor or mounted instruments on it. Finally, it displays measurement results in such a way that they are understandable not only for researchers and designers of agricultural machineries but also for a regular operator. The system can be installed with minimal changes on all conventional tractors in Iran.
