Agricultural Engineering

Research Paper Plant Nutrition, Soil Fertility and Fertilizers

Effect of combined application of struvite recovered from sewage sludge and triple superphosphate on phosphorus bioavailability in soil and its uptake by wheat

Taleb Nazari; Mojtaba Barani Motlagh; Seyed Omid Rastegar; Mohammad Hosien Sedri

Volume 47, Issue 3 , October 2024, Pages 299-322

https://doi.org/10.22055/agen.2024.45841.1711

Abstract

Introduction: The recovery of phosphorus as struvite from treatment plants has attracted researchers' attention due to its potential as a phosphorus fertilizer. Struvite is a white crystalline substance consisting of magnesium, ammonium and phosphorus in equal molar concentrations (MgNH4P04.6H2O). The ... Read More Introduction: The recovery of phosphorus as struvite from treatment plants has attracted researchers' attention due to its potential as a phosphorus fertilizer. Struvite is a white crystalline substance consisting of magnesium, ammonium and phosphorus in equal molar concentrations (MgNH4P04.6H2O). The low water solubility of struvite is thought to limit its agronomic utility as a phosphorus (P) fertilizer compared with highly soluble P fertilizers (triple superphosphate). Because limited studies have been done regarding the effect of struvite on the availability of phosphorus in calcareous soils. Therefore, this study examines the effect of struvite replacement with triple superphosphate fertilizer on phosphorus availability in wheat plants in calcareous soils deficient in phosphorus.Methods and Materials: Soil with phosphorus deficiency was collected from 0-30 cm depth under arable lands of Hajjiabad-e Seyyedeh located in Ghorveh township, Kurdistan Province, Iran. The soil was air-dried and ground to pass through a 2-mm sieve, followed by laboratory analysis to determine its physico-chemical properties. Struvite used in the research was obtained by optimizing the three main factors of sulfuric acid concentration, solid-to-liquid ratio, and time for the leaching process, and the three key factors of Mg/P ratio, N/P ratio and pH for the precipitation process by Response Surface Methodology. To achieve the aim of this study The factorial experiment was carried out in the form of a completely randomized design in 3 replications. The factors include the application of different proportions of struvite replaced with triple superphosphate in 6 levels (S0:P0, S0:P100, S25:P75, S50:P50, S75:P25 and S100:P0) and 3 levels of phosphorus (50, 100 and 150 kg/ha) and a total of 54 pots. The application rate for struvite was calculated based on total phosphorus (P2O5) of triple superphosphate. Then 10 wheat seeds were planted in each pot at 2-cm depth which after plant emerging and greening declined to 4 plants in each pot. The pots were randomly moved twice a week during the growth period to eliminate environmental effects. Irrigation and weeding operations were done by hand. Plants (shoots and roots) were harvested 60 days after planting (beginning of flowering), washed with distilled water and dry with tissue paper. The samples were air-dried and then oven dried at 70˚C to a constant weight in a forced air-driven oven. Phosphorus concentrations in plant extracts by the molybdenum vanadate or yellow method and Nitrogen concentration in plant was measured by the Kjeldahl method. After harvesting the plants, the soil was immediately air-dried and passed through a 2mm sieve. Then, the amount of phosphorus was determined by Olsen method. The statistical results of the data were analyzed using SAS software and LSD test (at 5% level) was used for comparing the mean values.Results and Discussion: Based on the obtained results, all of the investigated treatments and their interactions were significant at the probability level of one percent (P < 0.01). The comparison of the average effects of different struvite treatments showed that by replacing struvite instead of triple super phosphate fertilizer in all three levels of fertilizer, the highest shoot fresh weight (with an average of 7.79 gr/pot), shoot dry weight (with an average of 1.13 gr/pot) shoot Nitrogen concentration (with an average of 4.82%) and its uptake (with an average of 5.44 gr/pot) was obtained from the application of S75:P25 150 kg/h superphosphate fertilizer. Also, the results showed that the highest amount of phosphorus concentration and uptake, respectively, with an average of 0.174% and 0.197 gr/pot, was obtained from the application of the S75:P25 treatment with 150 kg TSP/ha, which is compared to the application of the S75:P25 treatment of 50 and 100 kg TSP/ha had an increase equivalent to 26.43, 59.89, 11.49 and 43.14% respectively. The results also showed that the highest amount of soil phosphorus after harvesting the plant with an average of 18.95 mg/kg was obtained from the S100:P0 treatment with 150 kg TSP/ha, which compared to the S100:P0 treatment with 100 and 50 kg TSP/ha with an average of 13.29 and 12.56 mg/kg had an increase equivalent to 29.86 and 33.72%, respectively. Conclusions: In spite of its low solubility, struvite is as effective as highly soluble phosphorus fertilizers for plants. There is still a lack of clarity regarding the mechanisms of struvite dissolution as well as the reasons behind this apparent dichotomy. Therefore, more accurate measurements of pH and EC in substrates, analysis of soil properties and fractionation of phosphorus in soil will enhance our understanding of the use of struvite. Therefore, it is recommended to optimize the timing and application rate of struvite in relation to the demand for different agricultural and garden crops

Research Paper Plant Nutrition, Soil Fertility and Fertilizers

The Effect of Humic Acid and Biochar on the Quantitative, Qualitative, Biochemical and Nutritional Characteristics of Anthurium Plants under Hydroponic Cultivation System

Esmaeil Khaleghi; Mehrangiz Chehrazi; Hojjat Shirazi

Volume 47, Issue 3 , October 2024, Pages 323-336

https://doi.org/10.22055/agen.2024.46319.1714

Abstract

IntroductionAnthurium (Anthurium scherzerianum schott) is one of the most important ornamental plants with beautiful leaves and flowers. The quantitative and qualitative characteristics of this flower can be affected by many factors, including the cultivation and feeding system. Biochar is a carbon-rich ... Read More IntroductionAnthurium (Anthurium scherzerianum schott) is one of the most important ornamental plants with beautiful leaves and flowers. The quantitative and qualitative characteristics of this flower can be affected by many factors, including the cultivation and feeding system. Biochar is a carbon-rich solid material that is produced during the process of pyrolysis (decomposition of organic materials by heat in the absence of oxygen or a small amount of oxygen). It includes elements such as (Si, P, S, N, H, O, K, alkali cations and heavy metals) with different proportions. In addition, humic acid is used as a biological polymer in the agricultural field to increase the efficiency of cultivation of various plant products, improve the efficiency of fertilizer consumption, the possibility of using it in soilless and greenhouse cultivation environments and increasing the efficiency of water consumption.Materials and MethodsThis study was conducted to investigate the effect of biochar and humic acid on the quantitative, qualitative and nutritional characteristics of anthurium flowers as a factorial experiment based on randomized complete block design in three replications in the greenhouse of the Faculty of Agriculture of Shahid Chamran University of Ahvaz during 2017-2018. In order to perform this experiment, first, Anthurium seedlings were prepared from the Anthurium flower production greenhouse located in Pakdasht Varamin and transferred to the greenhouse of Shahid Chamran University of Ahvaz. Then they were cultivated in 15 liter pots containing cocopeat and perlite in a ratio of 1:1. The treatments included biochar at 3 levels (0%, 5%, and 10% by weight), which was provided to the substrate at the same time as cultivation, and humic acid at 3 concentrations of 0, 500, and 1000 mg/liter. The end of experiment, indicators such as fresh and dry weight of roots, root surface, chlorophyll a and chlorophyll b and carotenoids, total soluble carbohydrates, nitrogen and potassium were measured.Results and DiscussionThe results showed that the use of biochar and humic acid significantly increased the morphological characteristics such as fresh and dry weight of roots, number of leaves, root surface and leaf surface. The highest fresh weight (50.62 grams) and dry weight (5.12 grams) of the root was obtained by using 10% biochar along with 1000 mg/liter of humic acid. There was a significant difference between plants treated with 1000 mg/liter of humic acid and 500 mg/liter of humic acid in all different levels of biochar on leaf number. The highest number of leaves (82.66) in the highest concentration of humic acid and biochar were obtained. The highest number of flowers was obtained at the highest level of humic acid and biochar. Also, biochemical properties such as chlorophyll and carotenoid and nutritional properties such as nitrogen and potassium increased significantly under the influence of treatments. The increase in growth parameters can be due to the effect of these two compounds in increasing the photosynthetic pigments, improving the absorption of water and nutrients, including nitrogen and potassium. Biochar, as a compound resulting from the anaerobic pyrolysis of different biomasses, changes the physical and chemical characteristics of the cultivation environment and increases the capacity to hold water and nutrients, increase total porosity and ventilation porosity, living and non-living biological compounds. On the other hand, humic acid, as a biopolymer, has a high ability to stimulate chemical reactions in the plant environment, especially in the rhizosphere of the plant. It is worth mentioning that the behavior of humic acid as a biopolymer in the plant environment can also affect the secondary metabolites of the plant, which has been reported in various studies for plants.ConclusionIn general, Mechanisms such as increasing root activity due to increasing cationic capacity, increasing water retention capacity in the culture medium, increasing biological activities in the culture medium during the application of biochar are important and key factors that they can affect the absorption of different nutrients and the biochemical reactions of the rhizosphere environment of the plant. Therefore, the results showed that the consumption of biochar and humic acid significantly increased in vegetative characteristics, reproductive characteristics, photosynthetic pigments and nutritional elements such as nitrogen and potassium. The use of 10% biochar and 1000 mg/liter of humic acid was the most effective treatment in improving the mentioned factors.

Research Paper Remote Sensing and GIS

Monitoring and classification of crops with satellite remote sensing technology

Nikrooz Bagheri; Alireza Sabzevari; Ali Rajabipour

Volume 47, Issue 3 , October 2024, Pages 337-356

https://doi.org/10.22055/agen.2024.46785.1723

Abstract

Introduction The use of remote sensing, due to the provision of timely data and the high capability of image analysis, as well as the possibility of studying in a wide range with acceptable accuracy, is of great help to the planners and implementers of the agricultural sector. Remote sensing is one of ... Read More Introduction The use of remote sensing, due to the provision of timely data and the high capability of image analysis, as well as the possibility of studying in a wide range with acceptable accuracy, is of great help to the planners and implementers of the agricultural sector. Remote sensing is one of the effective tools for monitoring, studying and determining the level of cultivation of agricultural and horticultural products, especially in large areas. Therefore, Annual Landsat images are valuable resources that enable crop monitoring in issues related to diagnosis, crop yield prediction, and crop-cultivation pattern studies.Materials and Methods Landsat 8 and OLI satellite images related to 2018 were used to estimate the overall level of crops in the area and to separate the agricultural area from other areas. These images were downloaded from the site http://earthexplorer.usgs.gov, which is related to row 37 and path 166. In order to collect additional information used in this research, Google Earth images and ground control points taken with a GPS device, Garmin model 64s, were used. Finally, the area under cultivation of the products was calculated. The statistics of the Ministry of Agricultural Jihad in the crop year 2016-2017 were used to evaluate the results. The classification steps are done to classify different classes.Results and Discussion For this purpose, in this research, to estimate the monitoring of main crops in the area and to classification agricultural crops, satellite images of Landsat 8 sensors with OLI sensor and NDVI index related to the time series of one-year images were used. The area of wheat and barley cultivated land in the region was estimated to be 10639 hectares, which shows an error of about 6.8% compared to the results of Jihad Keshavarzi statistics, which is 9956.56 hectares. After classifying the satellite images, using teaching samples that were not involved in the classification process, the accuracy of the classified image was evaluated. In this research, after calculating the cultivated area in GIS, the results were validated by comparing with the available statistics of Jihad-Agriculture and regional service centers and time control points by GPS, kappa coefficient and general accuracy coefficient. Supervised classification method with support vector machine algorithm and artificial neural network was used to separate farms. The crop classification maps were divided into 5 categories, wheat and barley, summer crops, rice crops, irrigated crops and non-agricultural lands. The lowest amount of commission error in both classification methods, 8.1 %, is related to summer cultivation, and the emission error in non-agricultural lands was 0.5 % in support vector machine method and 2.5% in artificial neural network method. Sentinel-2 images with a spatial resolution of 10 meters were used to prepare the classification map.Conclusion After classification, the maps produced by satellite images were compared with reference data and ground facts, as well as with the help of satellite images available in Google Earth software. Then the error matrix was formed. Kappa coefficient and overall accuracy were obtained in the vector machine method as 0.74 and 68%, respectively, and in the neural network method as 0.70 and 76% respectively. Results and Discussion For this purpose, in this research, to estimate the monitoring of main crops in the area and to classification agricultural crops, satellite images of Landsat 8 sensors with OLI sensor and NDVI index related to the time series of one-year images were used. The area of wheat and barley cultivated land in the region was estimated to be 10639 hectares, which shows an error of about 6.8% compared to the results of Jihad Keshavarzi statistics, which is 9956.56 hectares. After classifying the satellite images, using teaching samples that were not involved in the classification process, the accuracy of the classified image was evaluated. In this research, after calculating the cultivated area in GIS, the results were validated by comparing with the available statistics of Jihad-Agriculture and regional service centers and time control points by GPS, kappa coefficient and general accuracy coefficient. Supervised classification method with support vector machine algorithm and artificial neural network was used to separate farms. The crop classification maps were divided into 5 categories, wheat and barley, summer crops, rice crops, irrigated crops and non-agricultural lands. The lowest amount of commission error in both classification methods, 8.1 %, is related to summer cultivation, and the emission error in non-agricultural lands was 0.5 % in support vector machine method and 2.5% in artificial neural network method. Sentinel-2 images with a spatial resolution of 10 meters were used to prepare the classification map.Conclusion After classification, the maps produced by satellite images were compared with reference data and ground facts, as well as with the help of satellite images available in Google Earth software. Then the error matrix was formed. Kappa coefficient and overall accuracy were obtained in the vector machine method as 0.74 and 68%, respectively, and in the neural network method as 0.70 and 76% respectively.

Research Paper Post-harvest technology

Detecting the adulteration of Arabica coffee from Robusta using electronic nose and artificial intelligence

Saleh Azari; Esmaeil Mirzaee- Ghaleh; Hekmat Rabbani; Hamed Karami

Volume 47, Issue 3 , October 2024, Pages 357-373

https://doi.org/10.22055/agen.2024.47040.1730

Abstract

Introduction: Coffee is a common drink which is obtained from the roasted and ground beans of the coffee plant. Coffee beverages are widely consumed as a stimulant, a property largely attributed to the presence of caffeine, which is the most active pharmaceutical ingredient consumed worldwide. When the ... Read More Introduction: Coffee is a common drink which is obtained from the roasted and ground beans of the coffee plant. Coffee beverages are widely consumed as a stimulant, a property largely attributed to the presence of caffeine, which is the most active pharmaceutical ingredient consumed worldwide. When the fruit of the coffee plant ripens, the coffee beans are harvested, processed, and finally dried. Dried coffee beans are roasted to different degrees and graded depending on the desired aroma and taste. It is very important to detect natural and unnatural impurities and adulteration in coffee.Materials and Methods: An odor machine system based on eight MOS sensors was used to investigate the effect of bread storage time based on odor characteristics. The designed system includes a data acquisition system, sensors, sensor shield, sample container, power supply, connections, electric valves, air pump, and air filter. The sensor array consisted of 8 MOS sensors, including MQ136, TGS822, MQ9, MQ3, TGS813, TG2620, TG2602, and MQ135, each reacting to specific volatile compounds. These sensors are widely used in olfactory machines because of their high chemical stability, high durability, low response to moisture, and affordable prices. They are the most commonly used sensors in electronic nose systems. Sensors are the main components of an electronic nose system; therefore, it is necessary to select sensors able to detect differences among samples. In this research, the use of electronic nose technology and artificial intelligence was evaluated to detect common adulteration in Arabica coffee (Medium Dark). Robusta coffee samples with weight percentages of 10, 40, 30, 20, and 50% were used for experiments and adulteration. An electronic nose equipped with eight metal oxide sensors was used to carry out experiments related to odor. The data received from 8 sensors was first recorded and stored as raw data. In this research, the fractional method was used to normalize the data. Preprocessed data were used as the input matrix for multivariate analytical methods. The unsupervised multivariate principal component analysis (PCA) method was used to analyze the data. The LDA method was used to reduce classification differences and expand the differences between different groups. The artificial neural networks (ANN) method was used for classification. All calculations and analyses were done using Excel 2016, Unscrambler x10.4, and MATLAB software. Model evaluation criteria are used to evaluate algorithm performance in supervised learning. To analyze the system's performance, common criteria including Specificity, Recall, Precision, Accuracy, Area Under the Curve (AUC), and F-score were used.Results and Discussion: The results of PCA showed that 87% of the total variance of the data was explained by PC1, and 8% by PC2, and the two main components constituted 95% of the total variance of the normalized data. Based on the results, pure Robusta coffee (B) was located on the right side of the PCA diagram and completely separate from other levels of adulteration. Also, pure Arabica coffee (A) was placed in the vicinity of counterfeit samples, and all counterfeit samples showed the same behavior as Arabica coffee, which is very difficult to distinguish. The loading diagram was examined to determine the role of sensors in separating the groups. Based on the loading diagram for coffee adulteration detection, the sensors that had the highest value on the principal component were MQ9, TGS822, and MQ136. Other sensors also showed a high correlation with the smell of the samples. In other words, other sensors could be neglected. The models of artificial neural networks analysis were evaluated by the correct classification rate (CCR), root mean square error (RMSE), and coefficient of determination (R2). According to the results obtained for 7 different coffee groups, the 7-8-8 structure had the best results. This structure has 8 neurons in the input layer (number of sensors), a hidden layer with 8 neurons, and 7 neurons in the output layer (7 groups). The average values of the class obtained from the ANN model for the parameters of accuracy, precision, recall, specificity, area under the curve (AUC), and F-score were equal to 0.984, 0.952, 0.943, 0.990, 0.971, and 0.942, respectively. Also, the ANN method showed higher accuracy than the LDA method.Conclusion: The electronic nose showed that it is a fast and effective tool for detecting adulteration substances in coffee.

Research Paper Design and Evaluation of Agricultural Machines

Design, Construction and Performance Evaluation of a Novel Combinatorial Compressed Air Driven Water Pump

sara saki; Mohamad Esmail Khorasani Ferdavani; Seied Mohamad safieddin Ardebili; Amir Soltani Mohammadi

Volume 47, Issue 3 , October 2024, Pages 375-389

https://doi.org/10.22055/agen.2024.47124.1732

Abstract

Introduction: Compressed air is a versatile energy source used in various applications. However, pumping water with compressed air requires specific designs. Various designs have been proposed for pumping water using compressed air. Some of these designs include Air jet pumps, air-lift pumps, diaphragm ... Read More Introduction: Compressed air is a versatile energy source used in various applications. However, pumping water with compressed air requires specific designs. Various designs have been proposed for pumping water using compressed air. Some of these designs include Air jet pumps, air-lift pumps, diaphragm pumps, and hydro-pneumatic pumps (discrete flow). The hydro-pneumatic pump is composed of a chamber with two unidirectional valves for intake and discharge, separated by a well. Additionally, it includes an internal tube connected from the top to the outlet unidirectional valve. As compressed air enters the chamber, it applies pressure on the water surface within the chamber, resulting in the closure of the intake valve and the opening of the outlet valve, facilitating the upward pumping of water through the internal tube. Studies have been carried out in the field of jet pumps and air-lift pumps. However, the notion of enhancing flow rate and efficiency by integrating the pumping mechanisms of these pumps gave rise to the original idea of developing a hybrid water pump with a compressed air driver. The primary goal was to approach the efficiency of a hydro-pneumatic pump and simplify the design, allowing water pumping without the need for sensors or control systems. Materials and Methods: To assess the compressed air water pump and compare its performance with a hydro-pneumatic pump, a prototype with similar dimensions was constructed. By turning on or off and combining three compressed air nozzles within the pump structure, it was possible to operate the Combinatorial compressed air pump in four different modes. During field experiments, the performance, which included measuring input air pressure, flow rate, and water pumping height, was measured. Additionally, the efficiency of the Combinatorial compressed air pump was calculated under experimental conditions. Field experiments was conducted using a factorial design in randomized blocks. Treated variables included immersion depth (4 levels), inlet air pressure (6 levels), pump types and their working modes (5 levels). Discharge flow rates and water pumping height were measured across four replicates. at post processing, pumping efficiency calculated. Analysis of variance and post-hoc tests were conducted to analyze the significant effects of treatment variables and their interactions. to identify the best level for each treatment across different levels of other treatments, interaction slicing was employed. result was presented in charts and tables.Results: The variance analysis revealed a significant difference at the 1% confidence level among pump types, Immersion depth, input air pressure, and their interactions on water pump flow rate. Increasing submergence depth led to higher flow rates in the hydro-pneumatic pump, Combinatorial pneumatic pump, Bubble pump, Bubble & Airlift combined pump, and air-lift pump. Additionally, raising input air flow resulted in increased water pumping rates for all types of pumps.The hydro-pneumatic pump exhibited higher flow rates compared to other pumps, attributed to its positive displacement structure. The flow rate in all pumps increased with higher input air pressure due to the increase in air flow.The variance analysis on pump efficiency showed significant differences at the 1% confidence level in input air pressure levels, Immersion depth, pump type, and their interactions. With increased Immersion depth, pump efficiency rose in the following order: Combinatorial pneumatic pump, hydro-pneumatic pump, Bubble pump, Bubble & Airlift combined pump and air-lift pump, and air-lift pump. The Combinatorial pneumatic pump showed the most positive impact of Immersion depth on efficiency.Immersion depth, inlet air pressure, and pump type significantly impacted discharge rate and pump efficiency. With increased immersion depth and air pressure, discharge and efficiency rose for all pump models and operating modes. The hydro-Pneumatic pump achieved higher efficiency and discharge due to its different structure. At 2m immersion depth, the best performance among all pump models and modes was observed: Airlift pump (10.3% efficiency), Bubble pump (20.8%), Bubble & Airlift Combined pump (19.3%), Pneumatic Combined Pump (27.1%), and Hydro-Pneumatic pump (25.2%). Discussion: While the hydro-Pneumatic pump offered superior performance, the compressed air pump's simpler structure and lack of electronic control circuitry present advantages. Future research could explore optimizing the compressed air pump design for improved efficiency while maintaining its structural simplicity. Due to structural differences, the hydro-pneumatic pump exhibits significantly higher efficiency (approximately 54%). It was expected that this efficiency would be maintained with increasing pressure, but due to the limited immersion depth in the experiments and dimensional mismatch of the pump with high input air pressure, we observed a decrease in efficiency at higher pressures. This indicates that for each submergence depth and pump head, there is an optimal pressure that the pump dimensions should be designed to suit.

Research Paper Post Harvesting Technology

Optimization of preparation conditions and characterization of micropowder of sour tea extract containing anthocyanin by spray drying method

Parham Afshari; Narges Shahgholian; Hassan Zaki Dizaji

Volume 47, Issue 3 , October 2024, Pages 391-409

https://doi.org/10.22055/agen.2024.47240.1734

Abstract

Introduction Drying is one of the most economical ways to preserve food and is used to increase its shelf- life. Microencapsulation protects sensitive foods from adverse environmental conditions (such as the effect of moisture and oxygen) and reduces food quality fluctuations. The principle of microencapsulation ... Read More Introduction Drying is one of the most economical ways to preserve food and is used to increase its shelf- life. Microencapsulation protects sensitive foods from adverse environmental conditions (such as the effect of moisture and oxygen) and reduces food quality fluctuations. The principle of microencapsulation via spray drying is to prepare an emulsion or suspension and spray it in the hot air of the drying chamber. Plant pigments, such as anthocyanins, have been considered, but they are unstable under processing conditions. Hibiscus sabdariffa (sour tea) is a resistant herbaceous shrub and annual or perennial plant that contains anthocyanins. More than 300 types of sour tea are found in tropical and subtropical regions worldwide. Gum Arabic and maltodextrin are used as carrier materials to maintain the stability and functional characteristics of the powder prepared by spraying. Owing to its high solubility, low viscosity, and suitable emulsifying properties, gum Arabic is a carrier of interest in the spray drying process. Maltodextrin is a partial hydrolysis product of starch and oligosaccharides and has become one of the most important and widely used carrier compounds in spray drying because of its high solubility and low viscosity. Because anthocyanins are soluble in water, they are compatible with formulations containing maltodextrin, gum arabic, and starch. The main goal of this research was to investigate the microencapsulation of sour tea extract using a spray drying method for the development of stable anthocyanin formulations because this method is scalable.Materials and Methods Sour tea was prepared from the gardens of Khuzestan province, Karun city, in 2023. To prepare the sour tea plant, the sepals were first washed with distilled water and dried in an oven for 15 h at a temperature of 40º C. The sepals were then powdered using a hand mill. After passing through a sieve with a mesh size of 150 micrometers, the prepared powder was extracted using 50% ethanol. The extract was passed through a paper filter and centrifuged in a refrigerated centrifuge (10 minutes, 3780 g). Extraction was performed from sour tea, and after the concentration stage, it was combined with gum arabic and maltodextrin as carriers. The carrier material including the binary solution of gum arabic and maltodextrin in a specific ratio dissolved in 1000 ml of warm distilled water (at a temperature of about 70 º C) and stirred overnight on a magnetic stirrer at 4º C were kept. The ratio of the extract to the wall material was varied (1, 2, and 3% by weight). In this study, the inlet air temperature, inlet air flow, and inlet feed temperature to the dryer were considered constant, and the inlet air was sent to the dryer at a constant temperature of 160º C. The feed and air flow rate were 70% (respectively equivalent to 3 L/min and 25 m3 /h), and the nozzle opening and closing time intervals were 3 and 1 s, respectively. In order to optimize the preparation of the powder, the response surface methodology (RMS) with a central composite design (CCD) was used to obtain a mathematical model to predict the process behavior. The effects of independent variables, including the amount of wall material (4, 7 and 10%) and sour tea extract (1, 2 and 3%), on dependent variables, such as total anthocyanin (TAC), surface anthocyanin (SAC), and encapsulation efficiency (EE), were investigated. Moisture content, solubility index, bulk density, tapped and particle density, flowability, porosity, and morphology were also investigated in the powder samples.Conclusion The obtained data were modeled using the Design Expert software11. The data analysis showed that the best model for estimating the surface anthocyanin and anthocyanin encapsulation rate was the third-order model with coefficients of explanation of 0.8853 and 9205. After final optimization, the SAC value was 0.49, TAC was 4.371 mg/liter, EE was 42.27%, moisture content was 3.92, solubility index was 45.47%, bulk density was 0.98, tapped density was 1.03, and particle density was 2.28 g/cm3. Hausner and carr index confirmed the excellent flowability of the powders. The optimal wall and core materials were 66.6% and 1.63%, respectively. Scanning electron microscopy images showed that the powder particles were micrometer in size and almost spherical. Powders containing a high percentage of gum Arabic showed relatively greater shrinkage and indentation than powders containing high maltodextrin content.

Research Paper Soil Genesis and Classification

Incorporation of spatial autocorrelation in soil salinity distribution modeling in Qazvin area

Azam Jafari; Fereydoon Sarmadian; Ahmad Heidari; Zahra Rasaei

Volume 47, Issue 3 , October 2024, Pages 411-427

https://doi.org/10.22055/agen.2024.47331.1735

Abstract

Introduction: Machine learning algorithms usually do not consider spatial autocorrelation in soil data, unless it is perspicuity specified. Machine learning algorithms that compute autocorrelated observations have been recently formulated, such as geographic random forest (Georganos et al., 2019), or ... Read More Introduction: Machine learning algorithms usually do not consider spatial autocorrelation in soil data, unless it is perspicuity specified. Machine learning algorithms that compute autocorrelated observations have been recently formulated, such as geographic random forest (Georganos et al., 2019), or spatial ensemble techniques (Jiang et al., 2017). In theory, if we include all relevant environmental variables to model a soil property or class, there should be no spatial autocorrelation in the residuals of the fitted models. If this happens, some important predictors are likely to be missed. Despite the availability of the data set and the care taken during modeling, residual autocorrelation is still likely to occur. Several researchers have suggested the use of spatial alternative covariates as an indicator of spatial location in the SCORPAN model. The most common alternative is to use geographic coordinates (east and north) as covariates in the model, which leads to synthetic maps, especially when used in combination with tree-based algorithms. On the other hand, distance maps from observation locations are proposed by Hengl et al. (2018). Distance maps to observation locations usually do not have a clear meaning in terms of soil processes in an area (e.g., distance from a river). In the field of digital soil mapping, the current use of distance maps is not satisfactory for several reasons. The presence of pseudo-covariates with a set of covariates related to pedology is not very useful because it prevents the analysis of residuals and the creation of new hypotheses from these residuals. It also hinders the interpretation of the most important key predictors. Finally, pseudo-distance covariates may be well integrated into multiple pedology-related covariates, making them better predictors or masking the effect of pedology-related covariates. In spatial ecology, spatial eigen-vector maps, spatial filters or trend level regression replace distance maps in reducing or eliminating spatial autocorrelation (Kuhn et al., 2009). The purpose of this study is first to detect and calculate the spatial autocorrelation in the soil data. In the second step, it is going to develop a non-spatial model without considering the spatial autocorrelation, then to extract the spatial eigenvectors as an index of the spatial autocorrelation, and finally to use them as independent variables in spatial modeling.Methods and Materials: In this study, the soil salinity data utilized of 297 soil samples from a section of the Qazvin plain. The first and second derivatives of a digital elevation model as topography factors, remote sensing indices, parent material map, geoform map, and annual average temperature and rainfall maps were used to select the most important auxiliary variables. Finally, in order to select the best and most relevant environmental variables for modeling, the correlation between these variables and the dependent variable i.e. soil salinity in 297 study points was used using FSelector package of R software. Moran's I and Jerry's C indices were used to evaluate the spatial autocorrelation of soil data. First, the non-spatial ordinary least square (OLS) model was fitted to predict the spatial distribution of soil salinity. At this stage, spatial autocorrelation was not considered. Then spatial regression was fitted by calculating spatial filters through spatial eigenvectors as independent variables. Finally, the comparison of the outputs of the non-spatial OLS model and the spatial regression model was done with criteria such as R2, Akaike information criteria (AIC), autocorrelation of residuals and root mean of square error (RMSE).Results and Discussion: Statistical analysis indicated the high variability of soil salinity in the study area (coefficient of variation or CV more than 35%). Also, soil salinity shows high skewness and kurtosis, indicating its abnormal distribution. The high variability of this soil characteristic emphasizes the interaction of complex and numerous factors, including soil forming processes and different management strategies. The most important variables selected based on the correlation analysis include elevation, Multi-resolution Valley Bottom Flatness (MrVBF), wetness index, drainage basin, greenness index, normalized differential vegetation index (NDVI) and the corrected and transformed vegetation index (CTVI). A total of 7 variables were selected, which include four topography variables and three remote sensing variables. Among the topographical variables, the MrVBF had the most importance (correlation: 0.70). The spatial distribution map of soil salinity shows that the soil salinity is low in the northern, northeastern and northwestern parts towards the center of the studied area. The highest amount of salinity is found in the southern and southeastern regions. Moran's I and Jerry's C indices were 0.57 and 0.4, respectively. Based on both indices, soil salinity in the study area exhibits spatial autocorrelation. In the spatial regression model, by considering spatial autocorrelation, compared to the non-spatial model, the results are improved. By considering the spatial autocorrelation, the value of R2 increased, while the values of AIC, spatial autocorrelation of the residuals and RMSE decreased. The distribution maps of residuals from the non-spatial OLS model and the spatial regression model differ in terms of the spatial sign of the residuals and the spatial autocorrelation distribution that can be recognized in the form of clusters. Clusters (red or blue) indicate the presence of spatial autocorrelation in the residuals. In the distribution map of the residuals of the non-spatial model, more and larger clusters (marked with green ovals) are identified, indicating the existence of spatial autocorrelation in the residuals of the model. The presence of spatial autocorrelation in the residuals of a model shows that the model is not able to remove the spatial dependence, which may be due to not considering an important auxiliary variable in the modeling.Conclusion: This study was conducted in order to investigate the effect of spatial autocorrelation on the results of soil salinity modeling. Soil salinity prediction was done by non-spatial OLS model (without considering spatial autocorrelation) and spatial regression model (with spatial autocorrelation considered). The results indicated the improvement of the performance of the spatial regression model compared to the non-spatial ordinary least squares model. In the spatial model, considering the spatial autocorrelation as a covariate, the value of R2 increased, while the values of AIC, spatial autocorrelation of the residuals, and RMSE decreased.

Research Paper Soil Physics, Erosion and Conservation

Improving the accuracy of soil heavy metal concentration estimation based on spectral reflectance by minimizing the effect of moisture with the external parameter orthogonalization algorithm

Soheila Alioghli; Mahmoud Shabanpour; Hosein Ali Bahrami

Volume 47, Issue 3 , October 2024, Pages 429-444

https://doi.org/10.22055/agen.2024.47640.1738

Abstract

Introduction: Rapid global industrial development has led to a significant increase in the risk of environmental contamination with heavy metals. Soil contamination with heavy metals is a challenge due to the risks associated with human health and the environment, as well as soil-related food security. ... Read More Introduction: Rapid global industrial development has led to a significant increase in the risk of environmental contamination with heavy metals. Soil contamination with heavy metals is a challenge due to the risks associated with human health and the environment, as well as soil-related food security. It is considered universal. Soil moisture, as one of the influencing parameters on soil spectral reflectance and its high spatio-temporal variability, is considered the most important confounding factor in using Visible and Near Infrared Reflectance Spectroscopy (VNIRS) techniques to estimate soil heavy metals. . In this study, the ability of the external parameter orthogonal (EPO) algorithm to reduce the effect of moisture on soil spectral reflectance was evaluated to improve the performance of machine learning methods for heavy metal estimation.Materials and Methods: In the present study, a modeling approach based on spectral information obtained from VNIRS technique is used to investigate the effect of soil moisture on the estimation of heavy metal concentration (nickel and lead). Soil samples were obtained from areas suspected of heavy metal contamination. For this purpose, 129 soil samples were collected from fields contaminated with heavy metals in Tehran, Gilan and East Azerbaijan provinces. Nickel and lead concentrations in air-dried and sieved soil samples were measured in the laboratory using the ISO 11466 method. Then the soil samples were coded and transferred to the dark room for spectroscopy. Spectral reflectance of soil samples at 7 moisture levels (air-dried, 6, 12, 18, 24, 30 and 36%) using a FieldSpec-3 spectrometer and a contact probe in the spectral range of 350-2500 nm in a room Darkness was measured. After applying the necessary pre-processing, the soft and de-noised spectra related to the soil samples were randomly separated into two sets of data sets for modeling and validation. EPO using a set of calibration samples was developed. To estimate heavy metals, machine learning algorithms including PLSR and SVR were used.Results and Discussion: The results indicate that with the increase in soil moisture, the spectral reflectance in the entire range of 2450-400 nm decreases non-linearly. This means that the amount of reduction in different wavelengths is not the same. The greatest reduction occurs in the range of absorption peaks located in the range of wavelengths of 1600-1400 nm and 1850-2000 nm. VNIR spectroscopy has a high ability to estimate nickel and lead heavy metals in dry soil. The presence of moisture in the soil, even at the level of 6%, leads to a significant decrease in the ability of this technology to accurately estimate heavy metals in the soil. At humidity greater than 24%, both machine learning models evaluated for both heavy metals are in the medium class.Conclusion: In a general conclusion, it can be stated that the use of EPO algorithm significantly improves the ability of machine learning methods in the estimation of heavy metals in soil in the presence of moisture in soil samples. In general, SVR algorithm has the best performance compared to PLSR methods for modeling soil heavy metals. On the other hand, VNIR reflectance spectrum information provides more capability in estimating nickel than lead.In this study, the ability of the EPO method was evaluated in order to minimize the effect of soil moisture disturbing parameters on the ability of VNIR spectroscopy to improve the accuracy of soil heavy metal concentration modeling including nickel and lead based on PLSR and SVR machine learning methods. The results indicate that with the increase in soil moisture, the spectral reflectance in the entire range of 2450-400 nm decreases non-linearly. This means that the amount of reduction in different wavelengths is not the same. The greatest decrease occurs in the range of absorption peaks located in the wavelength range of 1600-1400 nm and 1850-2000 nm. VNIR spectroscopy has a high ability to estimate nickel and lead heavy metals in dry soil. The presence of moisture in the soil, even at the level of 6%, leads to a significant decrease in the ability of this technology to accurately estimate heavy metals in the soil. At humidity greater than 24%, both machine learning models are evaluated for both heavy metals in the medium class. Using the EPO algorithm significantly improves the ability of machine learning methods to estimate heavy metals in soil in the presence of moisture in soil samples. In general, SVR algorithm has the best performance compared to PLSR methods for modeling soil heavy metals. On the other hand, the information of VNIR reflectance spectrum offers more capability in estimating nickel than lead.

Effect of Tillage and Planting Methods in Hill Slopes on Soil Erosion and Wheat Grain Yield under Rain Fed Conditions in Kermanshah Province

Volume 35, Issue 2 , March 2012, , Pages 1-12

Abstract

The erosion in dryland causes decrease in yield and soil quality, especially in slope lands with conventional tillage. To investigate the effects of tillage and planting methods in slope lands on erosion and yield of rain fed wheat, an experiment was conducted in 2007-2008 at Kermanshah Province. The ... Read More

Ergonomic Evaluation of the Posture of Dates Packinghouse Workers by REBA Method

Volume 37, Issue 1 , September 2014, , Pages 13-22

Abstract

This study was conducted among dates’ packinghouse workers with the objectives of a) determining of MSDs prevalence and b) evaluating level of exposure to MSDs risk factors. The results of this study can be used to develop MSDs preventive strategies in the workplace and improve workers’ health. ... Read More

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Application of gypsum and manure on improving the amount of nitrogen, phosphorus and potassium in leaves and seeds of wheat under salinity stress

Volume 36, Issue 1 , September 2013, , Pages 1-11

Abstract

Salinity limited plant growth and will decrease the yield with decrease in solution osmotic pressure, nutrient imbalance and toxicity of some specific elements. Application of amendment materials such as gypsum and cattle manure can adjust the undesirable effects and increase the nutrient elements in ... Read More

The Effects of Different Sizes of Particles of a Superabsorbent Polymer on Water Holding Capacity of Two Different Soil Textures

Volume 36, Issue 1 , September 2013, , Pages 65-75

Abstract

Superabsorbent polymers are water containers that absorb and retain large quantities of water when applied to the soil. These materials release the absorbed water, allowing the plants to consume adequate amounts of water at all growth stages. One of the best options for increasing the irrigation efficiency ... Read More

Estimating Soil Erosion and Sedimentation Using Cesium-137 Method: A Case Study (Raymaleh Watershed, Lorestan)

Volume 35, Issue 2 , March 2012, , Pages 37-54

Abstract

The rate of soil erosion and sediment yield estimation in the catchment areas is considered as an important factor for soil and water conservation practices. Due to difficulties and restrictions in common soil erosion methods, applying a high accuracy method with lowest cost and time consuming would ... Read More

Research Paper

Estimation yield and water use efficiency of tomato using spectroscopy under deficit irrigation regimes and Silica nanoparticle in greenhouse conditions

Anahita Hadighanavat; Abdolrahim hooshmand; Parvaneh Tishehzan; Kazem Rangzan; Naser Alemzadeh ansari,

Articles in Press, Accepted Manuscript, Available Online from 17 October 2024

https://doi.org/10.22055/agen.2024.47342.1736

Abstract

Introduction Nowadays, the management of water resources has become one of the major challenges in the world due to recent droughts and water shortages. Therefore, timely and non-destructive monitoring of Water use efficiency (WUE) and yield of plants to screen cultivars with high water use performance ... Read More Introduction Nowadays, the management of water resources has become one of the major challenges in the world due to recent droughts and water shortages. Therefore, timely and non-destructive monitoring of Water use efficiency (WUE) and yield of plants to screen cultivars with high water use performance and efficiency and rational allocation of water has become one of the important goals in agriculture. Compared with traditional crop Yield and WUE monitoring and diagnostic tools, hyperspectral remote sensing technology has made it possible to obtain water use efficiency and Yield by taking advantage of large amounts of continuous data on a large scale. Therefore, this study aimed to create a model capable of estimating the WUE and Yield of tomato plants based on hyperspectral remote sensing data by establishing a relationship between common spectral indices and WUE and Yield in greenhouse conditions.Materials and Methods The research was carried out during the growing season of 2021 from January to June at the research greenhouse of the Department of Water and Environmental Engineering, Shahid Chamran University, Ahvaz, Khuzestan Province, The main factor was irrigation treatments in three levels including full irrigation, 20%, and 40% deficit irrigation, and the sub-main factor was silica nanoparticles with concentrations of 0 and 100 mg/lit. The pot experiment plot was laid out in a split plot in a randomized complete design (RCD) with four replications (120 pots in total). Then Tomato yield and WUE under the various treatments, were calculated. Canopy hyperspectral reflectance was measured using a portable spectrometer (ASD FieldSpec 3) operated in the spectral range of 350-2500 nm. The spectral data acquisition was conducted in four stages of plant growth during the growing season and the data were used to calculate spectral indices NWI5, WI3, WI4, NDVI, NDVI, and OSAVI. Then the ability of spectral indices to evaluate the water use efficiency and yield of tomato plants in different irrigation regimes and nanoparticles was investigated. Analysis of variance (ANOVA) was performed on spectral indices and WUE and yield of tomato plants using a split plot design. The PROC GLM method of SAS software (version 9.4, SAS Institute, Inc., Cary, NC, USA) was used for this analysis. Then, in order to compare the averages and whether they have a significant difference with each other at the 0.01 and 0.05 levels, the least significant difference (LSD) test was used.Results and Discussion The results showed that the Water use efficiency (WUE) under deficit irrigation treatments is increased with increasing water stress but the yield of tomato decreases with increase of water stress. In addition, the WUE and yield of tomato increases with increasing the concentration of silica nanoparticles (from 0 to 100 mg/liter). The value of NDVI and OSAVI indices decreased with the increase of water stress, while the value of RDVI, WI3, WI4 and NWI5 indices increased. The amount of NDVI and OSAVI spectral indices in the treatment containing 100 mg/liter nanoparticles was higher than the treatment without nanoparticles. Also, the amount of spectral indices RDVI, WI3, WI4 and NWI5 in nanoparticles with a concentration of 100 mg/liter was lower than the control treatment (zero concentration). The results also showed that the coefficient of determination between the different spectral indices and the WUE and Yield index was 0.55**Furthermore, among the six spectral indices, three spectral indices (NWI5, WI3, and WI4) jointly met most of the criteria used to determine the accuracy of the models for predicting yield and WUEConclusion Maintaining existing water resources through improving irrigation management and increasing water use efficiency and Yield of plants is the main goal for the sustainable development of water agriculture. As a result, rapid and non-destructive monitoring of water use efficiency and Yield is of great importance in improving irrigation management of crops and saving water consumption. significant relationship with yield and WUE index of tomato plants in greenhouse conditions. In conclusion, Spectral indices studied in this research could be useful and non-destructive assessments of the water use efficiency and yield of tomato in greenhouse conditions.Keywords: Deficit Irrigation, Spectral indices, spectroscopy, Tomato Plant, Water use efficiency

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Research Paper

Effect of co-application of zinc enriched biochar and foliar application of zinc on some physiological traits and the zinc uptake in wheat (Triticum aestivum L.)

Narges sousaraeS; Mojtaba Barani Motlagh; Seyed Alireza Movahedi Naeini

Articles in Press, Accepted Manuscript, Available Online from 27 May 2024

https://doi.org/10.22055/agen.2024.46559.1719

Abstract

Introduction: When the supply of micronutrients needed by the plant is insufficient, not only the yield of the product but also the quality of plant products are affected. Application of organic amendments is one of the ways to increase the nutrients such as zinc uptake by plants for. Biochar can be ... Read More Introduction: When the supply of micronutrients needed by the plant is insufficient, not only the yield of the product but also the quality of plant products are affected. Application of organic amendments is one of the ways to increase the nutrients such as zinc uptake by plants for. Biochar can be used as a raw material for the preparation and synthesis of mineral or metal composites due to its high specific surface area, porous structure and oxygen bonding groups on its surface. In these composites, biochar is used as a good porous structure to support and host metals. Biochar can have a significant impact on soil properties, the availability of nutrients, and the dynamics of the nutrients in arid and semi-arid soils, Depending on the feedstock and pyrolysis conditions However, very limited studies have examined biochar use as a nutrient carrier in the synthesis of organic-mineral compounds. Therefore, the present study was done to investigate the efficiency of zinc-enriched biochar pellets using two pre-pyrolysis and post- pyrolysis methods, and their effect on some physiological traits (chlorophyll a, b and total) and bioavailability of zinc in soil and plant.Methods and Materials A zinc deficiency Soil was collected from 0-30 cm depth under arable lands of Seyed Abad located in Azadshahr township, Golestan Province, Iran. To achieve the objectives of this study, a factorial experiment in a completely randomized design with three replications and 18 treatments (54 pots in total) was performed in the greenhouse of Gorgan University of Agricultural Sciences and Natural Resources. Factors included three types of zinc fertilizers (zinc sulphate, zinc-rich biochar prepared using pre-pyrolysis and post-pyrolysis methods) in three levels (0, 10 and 20 mg kg-1 zinc) and foliar spraying (distilled water and 3:1000 zinc). Zinc foliar spraying was done during the 6-10 leaf stage in the early hours of the morning before sunrise. Irrigation and weeding operations were performed manually. At the end of the growing period (vegetative and reproductive), some physiological traits (chlorophyll a, b, total and carotenoid), concentration and zinc uptake in shoots in the two stages of flag leaf emergence and seed maturity, and available concentration of zinc in the soil after wheat plant harvest were measured. The statistical results of the data were analyzed using SAS software and LSD test (at 5% level) was used for comparing the mean values.Results and Discussion: Based on the results, the interaction of type and levels of treatments was significant on all the studied traits at P<0.01, except for carotenoid. The means comparison showed that both zinc-enriched biochar pellets and zinc sulfate increased physiological traits in wheat plants. The highest amount of chlorophyll a, b, and total was obtained with an average of 4.99, 3.36, and 8.35 mg g-1 of fresh weight of the plant from the treatment of a pre-pyrolysis pellet with a concentration of 20 mg kg-1 with zinc sulfate foliar spraying, respectively. The highest zinc uptake in both the flag leaf emergence and seed maturity stages was obtained with an average of 120.33 and 86.62 mg kg-1 of dry weight of the plant from the pre and post-pyrolysis pellet treatment with a concentration of 20 mg/kkg with zinc sulfate foliar spraying, which had an increase of 20 mg kg-1 of zinc sulfate foliar spraying, respectively, equivalent to 27.69 and 30%. The pre-pyrolysis pellet treatment with 20 mg kg-1 zinc and zinc sulfate foliar spraying gave the most zinc extracted with DTPA, at an average of 3.41 mg kg-1. This was compared to the 10 mg kg-1 and 0 mg kg-1 pre-pyrolysis biochar pellet treatments, which gave an average of 2.39 mg kg-1 and 0.92 mg kg-1, respectively, which is an increase of 29.91 and 73.02 percent. The amount of DTPA extractable Zn with the amount of chlorophyll a (r = 0.87**), chlorophyll b (r = 0.81**), total chlorophyll (r = 0.87**), and carotenoids (r = 0.89**) had a positive and significant correlation. The results showed that between DTPA extractable Zn with zinc concentration (r = 0.91**) and zinc uptake (r = 0.90**) in the stage of flag emergence and zinc concentration (r = 0.87**) and zinc uptake (r = 0.86**) in the stage of seed maturity in the wheat plant, there was a positive and significant correlation.Conclusions: In general, the results showed that the positive role of biochar-zinc pellets in increasing the concentration and zinc uptake in wheat plants. Nevertheless, supplemental zinc foliar application with biochar pellets rich in zinc in the amount of 20 mg kg-1 in the form of post-pyrolysis had the greatest effect on the physiological characteristics and Zn bioavailability for wheat plants.

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Analytical and Applicable Papers

Seasonal changes in nutrients of three date (Phoenix dactylifera L.) varieties in Ahvaz weather conditions

Fatemeh Foroozesh fard; Shohreh Zivdar; Esmaeil Khaleghi; Edris Shabani

Articles in Press, Accepted Manuscript, Available Online from 20 October 2024

https://doi.org/10.22055/agen.2024.47849.1741

Abstract

Background and Objective: One of the important aspects of nutrition physiology in fruit trees is the study of seasonal changes in leaf elements, because the seasonal pattern of absorption and distribution of nutrient elements is very important in estimating the fertilizer requirement of fruit orchards. ... Read More Background and Objective: One of the important aspects of nutrition physiology in fruit trees is the study of seasonal changes in leaf elements, because the seasonal pattern of absorption and distribution of nutrient elements is very important in estimating the fertilizer requirement of fruit orchards. The movement of nutrients in fruit crops has been reported a lot, and the plants' need for a specific element is influenced by a specific growth stage in the plant. Research has shown that nutrient accumulation occurs as a continuous process throughout the growing season. In plants, the change process of elements is different in the seasons. By examining the dynamics of elements during different seasons and having the necessary information about these changes, it is possible to examine the relationship between the demand for nutrients during the periods of vegetative and reproductive growth.In Iran, many research has been done on the nutritional requirements of different commercial fruit cultivars, and many studies have reported the dynamics of nutrients in fruit trees during the growing season, but in the case of dates, despite the relative diversity Regarding the cultivars of this plant and Iran's presence in the international competitive markets, there was no report on measuring the dynamics of nutrient elements during the seasons. In the upcoming research, the seasonal evaluation of the concentration of some macronutrients and micronutrients in the leaves of three date varieties has been done.This study was carried out in order to evaluate the seasonal changes in nutrients in the leaves of three date varieties. Materials and Methods: This experiment was conducted in the date palm research garden in the northern part of Shahid Chamran University of Ahvaz, in a randomized complete block design with four replications, during 2022 on the leaves of ten years old date palm cultivars (Berhi, Estamaran, and Zahedi). In this experiment, the trend of seasonal changes in macro nutrients (nitrogen, phosphorus, potassium and calcium) and micro nutrients (iron, copper, boron, zinc and manganese) concentration, were investigated throughout the four seasons.After collecting the data, the data was statistically analyzed using SAS 9.1 statistical software, and Duncan's test was used to compare the average data at the level of one and five percent. Results: The results showed that the seasons have a significant effect on the concentration of the elements except nitrogen and manganese. Also, the interaction of season and cultivar had a significant effect on the concentration of all nutrients. In terms of macronutrients, Berhi had a better condition, especially during the growing season (spring and summer). The highest difference in terms of element concentration was observed between the winter and growth seasons for date cultivars. The minimum concentration of nitrogen (0.94%) was for Zahedi in spring and winter and the maximum concentration was 2.01% for Barhi (winter). Phosphorus concentration was recorded from the lowest (0.13%) in winter and spring to the highest (0.36%) in summer for Barhi. The range of potassium changes ranged from 1.01% (Estamaran, autumn) to 1.18% (Zahedi, winter). The seasonal changes in calcium concentration was recorded between 0.76 and 0.92%. Also, the range of changes in iron concentration during the year was from 65 to 130 mg/kg and during the growing season to mid-summer from 87 to 117 mg/kg. Bades on the results, leaf iron concentration was estimated to be less than optimal in all seasons. Also the concentration of nitrogen, potassium and copper in leaves decreased during the growth season, especially in summer, and can be due to the consumption of these elements for reproductive growth. Conclusion: The concentration of minerals in plants depends on the interaction of several factors including soil, plant species, climate, growth stages, plant production and management and the interaction of elements during absorption. The successful growth of plants and trees requires suitable soil and the presence of sufficient amounts of usable elements and the relationship between them, among which nitrogen, phosphorus and potassium elements are among the main essential elements required by the plant. The results showed that there is a significant seasonal variation in macronutrients and micronutrients in three date varieties. Also, different seasonal changes patterns were observed among cultivars regarding elements. In such a way, potassium and calcium are more stable than nitrogen and phosphorus during different seasons of the year. Macronutrients (phosphorus and calcium) and micronutrients (zinc, boron and manganese) were at the optimal level. But, the amount of nitrogen, potassium, iron and copper was evaluated as less than the optimal level, which suggests the use of fertilizers containing the mentioned elements at the end of winter..

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Improving the nutritional management and yield of Ricinus communis L. using Arbuscular mycorrhizal fungus and organic fertilizers

Hadi Ahmadian; Shiva Khalesro; Gholamreza Heidari

Articles in Press, Accepted Manuscript, Available Online from 05 November 2024

https://doi.org/10.22055/agen.2024.46395.1716

Abstract

Introduction: A decline in soil organic matter is a key facet of soil degradation, leading to the loss of soil fertility and the capacity to produce crops. The intensive use of synthetic inorganic inputs, such as chemical fertilizers, has resulted in soil organic matter depletion, groundwater contamination, ... Read More Introduction: A decline in soil organic matter is a key facet of soil degradation, leading to the loss of soil fertility and the capacity to produce crops. The intensive use of synthetic inorganic inputs, such as chemical fertilizers, has resulted in soil organic matter depletion, groundwater contamination, air pollution, and reduced production quality in arid and semi-arid regions. Therefore, sustainable techniques, such as organic fertilizers and natural inputs, are becoming increasingly important to enhance soil organic matter and plant yield in sustainable agricultural systems. The use of organic fertilizers and soil amendment like biochar and wood vinegar can significantly improve soil organic matter. Much of the world's interest in biochar stems from the worsening condition of agricultural soils and the depletion of water resources. Additionally, biochar has attracted researchers’ interest mainly due to its long-term soil carbon sequestration potential, role in greenhouse gas mitigation, phytoremediation, and ability to improve soil fertility. Biochar and wood vinegar can be made from various biomass materials/residues such as wood waste, crop and refinery residues, animal manures, and municipal wastes. Biofertilizers also play a vital role in sustainable agriculture systems. Mycorrhiza is one of the most important biofertilizers. Mycorrhizal associations help plants obtain water and nutrients in dry and nutrient-poor conditions by increasing the root surface area for water and nutrient uptake. Castor bean (Ricinus commonis L.) is a valuable annual herb belonging to the Euphorbiaceae family. It is an important oilseed crop widely used in industry and medicine today. Numerous studies have underlined the beneficial effects of organic fertilizers on soil fertility and crop yield. However, no study has evaluated the impact of organic fertilizer, biochar, wood vinegar, and mycorrhiza on Ricinus commonis L. This research aims to discover the main effects and interactions of these treatments on the quantitative and qualitative traits of Ricinus commonis L. Materials and Methods: The field experiment was conducted at the Research Field at the University of Kurdistan (35° 19' N, 47° 18' E) during 2022 growing season. The research was designed as a factorial experiment using a randomized complete block design with three replications. Treatment included five fertilizer types: control, organic fertilizer (800 kg ha-1), biochar (3000 kg ha-1), wood vinegar (90 kg ha-1) and chemical fertilizer (urea 200 kg ha-1, and TSP 100 kg ha-1). Additionally, two mycorrhiza levels (Rhizophagus irregularis) were tested: no-inoculation and inoculation. Each experimental plot consisted of six rows, each 6 meters long and spaced 75 cm apart. The seeds were sown on 10 May 2020. Agronomic traits such as plant height, number of capsules per plant, and 1000-seed weight were randomly measured from five plants at full maturity in each plot. In the center rows of each plot, 2.25 m2 of area was harvested at the end of each growing season to evaluate biological and seed yield. Other studied traits included harvest index, seed oil content, seed oil yield, and the nitrogen, phosphorous, and potassium concentration of the seeds. Results and Discussion: The results showed that the effect of mycorrhiza inoculation on the plant height, capsules number per plant, seed number per plant, and 1000-seed weight was significant. Furthermore, the fertilizer impact on the mentioned traits except of 1000-seed weight was significant. Organic fertilizer, biochar, wood vinegar, and chemical fertilizer significantly increased the capsules number per plant. The highest number of capsules per plant and seed number per plant belonged to the organic fertilizer. Mycorrhiza inoculation enhanced the seed number per plant and 1000-seed weight by 16% and 23% compared to control, respectively. the interaction effects of different fertilizers and mycorrhiza inoculation improved the quantitative and qualitative traits of castor bean. The highest biological yield (3650.2 g/m2), seed oil content (50.5 %), and oil yield (588.3 g/m2) were observed in the integrated treatment of organic fertilizer and mycorrhiza inoculation. This treatment increased seed and biological yield by 36.5% and 24% compared to control, respectively. Mycorrhiza can enhance plant growth and yield by increasing the supply of phosphorus to the host plant. Mycorrhizal plants can absorb and accumulate several times more phosphate from the soil or solution than non-mycorrhizal plants. Organic fertilizer and biochar positively affected the morphological characteristics. Biochar reduces water consumption and improves soil properties under drought conditions. Compared to other amendment materials, biochar has the benefit of a large surface area and pore spaces, allowing it to absorb and retain water. The highest seed nitrogen and potassium content was observed in the organic fertilizer treatment. Organic fertilizers may promote root development by retaining more water and nutrients in the soil, secreting more plant hormones, and increasing the amount of inorganic material such as nitrogen, phosphorus, and potassium that plants can absorb. Conclusion: Therefore, it can be said that the integrated application of organic and biofertilizers not only improve the quantitative and qualitative traits of Ricinus commonis L. but also could be a key strategy in sustainable agricultural systems by reducing the consumption of chemical fertilizers.

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Design, Manufacture, and Evaluation of Blades for a Rotary- Trencher Machine

Arash Khoshabari; Seyed reza Mousavi Seyedi; Sajad Kiani

Articles in Press, Accepted Manuscript, Available Online from 14 November 2024

https://doi.org/10.22055/agen.2024.47767.1739

Abstract

Introduction Two-wheeled tractors are used to disturb the topsoil in greenhouses and small gardens. These machines consist of a rotating shaft connected to a gearbox, on which a set of flanges is mounted. Blades are attached to each flange in a specific arrangement. When the flanges rotate, they come ... Read More Introduction Two-wheeled tractors are used to disturb the topsoil in greenhouses and small gardens. These machines consist of a rotating shaft connected to a gearbox, on which a set of flanges is mounted. Blades are attached to each flange in a specific arrangement. When the flanges rotate, they come into contact with the soil, lifting and throwing it backward, thus breaking up the soil and creating a suitable seedbed for planting agricultural products. A transmission system transfers the necessary and generated force from an engine to the blades for soil cutting. Notable features of these machines include reasonable prices, high operational speed, easy mobility due to lightness, and simple maintenance and repair. Rotary cultivators or rotary soil mixers are also used to prepare the soil bed and control weeds in fruit orchards. In this research, the most suitable blade for producing a double-purpose rotary-trencher machine equipped with a V-shaped gearbox was designed and produced.Materials and Methods Catia software (V5-6R2018) was used for the design and Abaqus software (6.14-4) was used for mechanical analysis of the designed blades. First, the blades were designed with three different surfaces 42.75, 38.53, and 35.39 cm2. The goal was to achieve a blade design that not only creates a suitable tilled soil surface but also maximizes soil displacement to ensure the device performs acceptably during furrow creation. The blade stress analysis was performed based on the Von Mises criterion and finite element analysis (FEA). After the design of the blades, to ensure their strength against the forces exerted from the soil surface, FEA and examination of the mechanical strength of the selected alloy (ST52) were performed in Abaqus software. Then, the blade spread design was cut using a CNC machine, forged using a blacksmithing mold, and bent with a 38-millimeter radius. After this stage, the surface of the blades was hardened. The evaluation of the device in the disturbing of the topsoil with three blade models at three blade shaft speeds (200, 300, and 400 rpm) was performed in three repetitions in the form of a factorial experiment in a completely randomized design using SPSS software. The disturbing of the topsoil and the depth of the created trench were considered as criteria for evaluating the rotation speed and dimensions of the blades.Results and Discussion The maximum force applied to blades showed that the maximum stress obtained with surfaces of 42.75 cm2, 38.53 cm2, and 35.39 cm2, based on the Von Mises criterion, was 0.74, 0.7, and 0.188 MPa, respectively. Also, the maximum principal stress in these three blade models was 0.27, 0.24, and 0.122 MPa, respectively. The results illustrated that the maximum stresses obtained are much lower than the yield stress or ultimate strength of the alloy used in the blade. To do the topsoil tillage operation 6 flanges of blades (18 blades) and to do trenching two flanges of blades (6 blades) were installed on the axis of the gearbox. The results from comparing Mean Weight Diameter (MWD) values of the disturbed topsoil showed that by increasing rotation of the blade shaft, the soil disturbing significantly increases. On the other hand, results showed that the increase in the surface of the blade was not significant in disturbing the topsoil particles. Also, the blades were evaluated by creating a trench. Two flanges of the blades (6 blades, Fig 1. b) are performed when the machine moves backward (Fig 9-a and Fig 11). The machine's reverse speed was kept constant at 2 km/h. The results clearly showed that the surface of the blades has had a significant effect on the performance of creating a trench, and with the increase of the blade's surface, the amount of soil transferred out of the trench has increased. However, increasing the blade surface increased the trench depth, but increasing the blade's axis rotation was not as significant as the blade surface because the backward speed of the machine is constant and slow.Conclusion In this research, a new type of blade for a dual-purpose rotary-trencher machine was designed, analyzed, produced, and evaluated. The results of the statistical analysis showed that the blade's surface has no effect on the tillage quality, but the rotation speed of the blades was significantly effective. On the other hand, in the operation of creating a trench, the surface of the blade was significantly effective, and with the increase of the surface, the depth of the created trench increased due to the movement of more soil particles. Finally, a blade with a surface of 42.75 cm2, made of ST52 alloy steel, with a forged and hardened edge, and a bending radius of 38 mm was proposed for this type of dual-purpose soil rotary-trencher machine. Therefore, this machine equipped with the designed blade model is suitable for both topsoil disturbing and trencher.

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Investigating factors affecting the density, strength and durability of pellets made from olive processing plant waste

Reza Tabatabaeekoloor; shaban ghavami jolandan

Articles in Press, Accepted Manuscript, Available Online from 16 November 2024

https://doi.org/10.22055/agen.2024.48055.1744

Abstract

Introduction Fuel pellets are one of the uses of biomass, which are made from agricultural waste, plant residue, and animal excrement. They produce more energy per unit volume. Various factors are effective in the pelleting process. Having information about them helps to optimize the pelleting process ... Read More Introduction Fuel pellets are one of the uses of biomass, which are made from agricultural waste, plant residue, and animal excrement. They produce more energy per unit volume. Various factors are effective in the pelleting process. Having information about them helps to optimize the pelleting process and to understand the compression mechanism and the design of compacting equipment. Materials and Methods Olive pomace raw material for making pellets was obtained from an olive processing factory in Rudbar city in Gilan province. The prepared materials were transferred to the laboratory in the necessary amount in nylon bags and dried in the oven at 105 degrees Celsius for 24 hours. The dried samples were powdered by a laboratory grinder and then passed through sieves in the range of 0.6-1.5 mm and used to make pellets. Before making pellets, the initial moisture content of the samples was obtained using the drying method. First, pre-tests were conducted to make pellets and the moldability and strength of the samples were checked. A palletization mechanism was used to compress the pellet. This system was designed and built in biosystem mechanics of Sari University of Agricultural Sciences and Natural Resources. The material was placed inside a steel mold with a cylinder inner diameter of 8.05 mm and a height of 150 mm with a blocked end. A piston with a diameter of 8 mm connected to the driving arm of the tension-compression test machine was used to compress the material. Loading by a piston with a quasi-static speed of 6 mm per minute is compressed. In this research, the effect of particle size treatments (600-900, 900-1200 and 1200-1500 μm), compaction pressure (75, 150 and 225 MPa) and temperature (50, 70 and 90 ͦC) on the density, strength and durability of the pellet were investigated.Results and Discussion The results indicated that the main effects of all three mentioned treatments on the strength, density and durability of the pellet are significant. Also, the mutual effects of some treatments are also significant on these characteristics. The interaction effect of particle size and compaction pressure on pellet compressive strength is significant at 5% level. With the increase in particle size, the pellet strength increased first, and then with the further increase in particle size, the pellet strength decreased slightly. On the other hand, with the increase in compression pressure, the pellet resistance increased. Pellet density is an important factor for storage and transportation as well as combustion efficiency. The mutual effect of compression pressure and particle size on pellet density is significant. Changes in pellet density were obtained in the range of 1.015 to 1.350 grams per cubic centimeter. The usual and recommended density for pellets made from agricultural and forest residues should be more than 0.8 grams per cubic centimeter. The interaction effect of compaction pressure and temperature on pellet durability is significant. The range of durability changes for pellets is between 81 and 95 percent. Increasing compaction pressure significantly improved the stability of the pellets, which indicates the role of compaction in bonding between particles and creating bridges for greater particle strength. The highest pellet strength was obtained in the combination of particle size of 900-1200 micrometers, temperature of 90 degrees Celsius and compaction pressure of 225 MPa. The highest density was obtained at a particle size of 600-900 and a compression pressure of 225 MPa and the best stability at a compression pressure of 150 MPa and a temperature of 90 degrees Celsius. In general, the physical and mechanical properties of the pellet were affected by all three factors: particle size, temperature and compaction pressure.Conclusion The results of this research showed that all three factors of particle size, compaction pressure and temperature have a significant effect on the physical and mechanical properties of pellets such as density, strength and durability. Choosing the right particle size plays an important role in making the pellet stronger. The temperature of the die during pelleting is also very important in the bonding of the pellet particles because at the right temperature, the bonding between the bridges strengthens the connection of the particles and as a result increases the strength and durability of the pellet. In general, the results of the research showed that to make pellets from olive processing factory waste, a suitable combination of particle size parameters, compaction pressure and die temperature is needed to make pellets with high strength and durability.

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Presenting a schedule model for annual Massey Ferguson 399 tractors maintenance using GERT method, A case study: Dehkhoda Sugarcane Agro-industry Company

Mehdi Anafche; nasim monjezi

Articles in Press, Accepted Manuscript, Available Online from 26 November 2024

https://doi.org/10.22055/agen.2024.47154.1733

Abstract

Introduction Considering the high use of agricultural machines in sugarcane Agro-industry company; management of maintenance and repairs is necessary. The application of agricultural mechanization and the management of machines in agriculture is responsible for improving the way of working and correct ... Read More Introduction Considering the high use of agricultural machines in sugarcane Agro-industry company; management of maintenance and repairs is necessary. The application of agricultural mechanization and the management of machines in agriculture is responsible for improving the way of working and correct use of machines. Today, with the mechanization of agricultural systems, the timely performance of activities requires correct machine planning. For proper planning, one must know the reliability of the machines. Increasing efficiency and reliability of machines is an economic necessity. Any scheduled program to increase the reliability of machines can be effective in reducing time loss due to repairs and cause repairs to be completed on time. Therefore, in this research, according to the nature of the project of annual repairs of MF 399 tractors, in which the activities and the time of their completion are possible, the graphic evaluation and review technique (GRET) method was used. GERT's method is one of the possible network programming methods. In GERT's method, the occurrence of activities is considered possible and a percentage of probability is assigned for the occurrence of each activity. Materials and Methods This research was conducted in the Dehkhoda Sugarcane Agro-industry Company in the crop year of 2023-2024. Dehkhoda Sugarcane Agro-industry Company has 42 Messi Ferguson 399 double differential tractors. In this research, in order to schedule annual repairs, statistics and data related to the repairs of 22 MF 399 tractors were collected and the data of other machines were used to compare the actual repair time with the calculated schedule. The 13 repair items of MF 399 tractors used in the company include: engine, clutch, gearbox, differential and rear axle, brake, rear hub, body, front axle, hydraulics, electricity and battery, wheels, service and greasing. The work breakdown structure diagram and network model of annual MF 399 tractor repairs were drawn. To extract the time distribution density function of each activity, first the available information was collected for each activity, then the time distribution density function was determined for each activity. The time to perform the activities is fuzzy and they are expressed by triangular fuzzy numbers. In this research, after scheduling, the results obtained from GERT's method were compared with the actual time spent to perform annual MF 399 tractor repairs and the appropriateness of the estimates was determined. For this purpose, in order to determine the actual time of annual MF 399 tractor repairs, among the tractors available in the mechanical equipment department of Dehkhoda Sugarcane Agro-industry Company, in the crop year 2023-2024, a sample was randomly selected and the actual duration of repairs was determined. Then the actual time to complete the operation was compared with the expected time. Results and Discussion The time to complete the annual repairs of MF 399 tractors was estimated to be 225.93 hours using the classic GERT method. But in GERT's Fuzzy method, the time calculated for annual MF 399 tractor repairs was (295.30, 232.07, 168.73) hours. The actual duration of annual repairs for 20 tractors (out of a total of 42 tractors) in Dehkhoda Sugarcane Agro-industry Company, which were repaired during the 2023-2024 crop year, according to the information available in the technical office of the company's mechanical equipment, was determined. 29.12% of the real times for completing MF 399 tractor repairs were estimated outside the fuzzy time. Therefore, the manager of the repair unit can reduce the cost of time loss and manage the time to complete the operation in the optimal time frame by using correct planning and reducing the reasons for the delay in the operation. Conclusion Therefore, GERT F Fuzzy's method provides the possibility to the manager of the repair unit to set the completion time in the estimated range appropriately, taking into account other effective factors involved in the operation, so that there is no disruption in the implementation of activities and on the other hand, the costs to minimize when the work is not done. It also provides the possibility to create cuts at different times and control the operation process and modify it if needed. In the real world, due to existing uncertainties, there is not enough confidence in the duration of the annual maintenance of tractors, but nevertheless, the results obtained from GERT's method in this research are close to the actual time of completion of operations and make the estimates more appropriate.

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Modelling and Digitally Mapping of Surface Soil Organic Carbon in Semirom County Employing Several Machine Learning Algorithms

Fatemeh Rahmati; ُSaeid Hojati; Kazem Rngzan; Ahmad Landi

Articles in Press, Accepted Manuscript, Available Online from 16 December 2024

https://doi.org/10.22055/agen.2024.47815.1740

Abstract

Introduction: Knowledge about the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance ... Read More Introduction: Knowledge about the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. Accurate mapping of SOC’s spatial distribution is a key assumption for soil resource management and land use planning. During the last two decades, the utilization of data mining approaches in spatial modeling of SOC using machine learning algorithms have been widely taken into consideration. The digital environment needs to have soil continuous maps at local and regional scales. However, such information is always not available at the required scale. Therefore, DSM approach is a key solution for quantifying and assessing the variation of soil properties such as SOC using remotely sensed indices and digital elevation model (DEM) as the most commonly useful ancillary data for soil organic carbon prediction. In this way, the data mining techniques is the pathway to create digital soil maps. Therefore, this study was carried out to compare the two common machine learning algorithms including random forest and multiple linear regressions in digital mapping of surface SOC in the Semirom County, Isfahan province. The digital maps of SOC using the two above-mentioned algorithms were also created and the most important variables affecting the distribution of SOC in the study area reported. Materials and Methods: A total number of 200 surface soil samples (0-10 cm) were collected from the Semirom area (51º 17' - 52º 3' E; 30º 42' - 31º 51' N), Isfahan, Iran. Based on the synoptic meteorological station reports, the annual average temperature was in the range of 7.5-12.5 ▫C, the annual precipitation ranged between 350-450 mm. Soil moisture and temperature regimes are Xeric and Mesic, respectively. Then, using the Global Positioning System (GPS), sampling was done from the soil surface layer (0-10 cm). The preparation of soil samples includes air drying, pounding and softening of the collected samples performed, and then the samples were passed through a 2 mm sieve. Then, the amount of organic carbon in the samples was determined utilizing the Walkley-Black method. Also, in order to evaluate the effect of other soil properties on the organic contents of the soils, laboratory analyzes including saturated soil moisture content, soil texture, soil pH in saturated pastes, electrical conductivity of the soil saturation extracts and the calcium carbonate equivalent of the soils were measured utilizing standard laboratory protocols. In this research, auxiliary variables including terrain parameters and vegetation indices were derived from digital elevation model (DEM) and the Landsat 8 OLI satellite images employing ArcMap version 10.4.10 and SAGAGIS version 6.0.4. Then, all auxiliary layers were converted to raster format using the “raster” package and merged with each other using the “Covstack” function. Afterwards, the values of the all environmental covariates at each sampling point were extracted in a single file using the “extract” function of the “sp” package in the RStudio environment. Then, using SPSS software v.19 and the principal component analysis (PCA) method, among the 29 auxiliary variables used in this research, the most important auxiliary covariates were used in the modeling process. The dataset were then split into two groups referred to as calibration (80%) and validation (20%) subsets. Finally, SOC contents of the soils were predicted and mapped using multiple linear regression (MLR) and random forest (RF) algorithms in RStudio environment. MLR and RF algorithms were run employing “lm” and “randomForest” packages, respectively. Five different statistics was used for evaluating the performance of each model including the coefficient of determination (R2), bias, root mean square error (RMSE), nRMSE, and mean bias error (MBE). Results and Discussion Based on the descriptive analysis of the soil samples, soils of the study area were characterized as non-saline, alkaline, and calcareous soils. The SOC contents of the soils ranged from 0.3 % to 2.2% with the mean value of 0.89 %. The coefficient of variation for the SOC contents was 21.7%, based on which soils of the study area are classified as soils with the moderate variability considering the values proposed by Wilding (1985). The results of PCA showed that the most important auxiliary variables could be used for the modeling process are slope aspect, channels network base level, catchment slope, total curvature, height, longitudinal curvature, mass balance index, modified catchment area, slope degree, slope length, topographic position index, vertical distance to channel network, soil adjusted vegetation index, transformed vegetation index, difference vegetation index, ratio vegetation index, and general curvature.These variables explained 80% of the total variance over the study area. The comparison of the two different SOC prediction models, demonstrated that the RF model (ntree =1000 and mtry =10) with the R2, RMSE, nRMSE, and bias values of 0.79, 0.12, 0.13, and 0.002 respectively, had a better performance rather than MLR model in this study. The first five very important variables detected by RF algorithm to predict SOC contents over the study area were transformed vegetation index, ration vegetation index, soil adjusted vegetation index, and slope degree. The final map of the surface SOC distribution over the study area shows that although the estimates made by the RF algorithm have provided better estimates compared with the MLR model, but caused overestimation and/or underestimation in predicting the minimum and maximum values of the surface SOC contents, respectively. Conclusion The results of this study showed the better performance of the RF regression algorithm due to its ability to take into account the nonlinear and complex relationships between SOC contents and the environmental covariates compared to the MLR method.

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Evaluation of the nutrient content of soil and wheat grain due to the integrated application of chemical and organic fertilizers

Ali Reza Jafarnejadi; Farhad Moshiri; Fatemeh Meskini-Vishkaee

Articles in Press, Accepted Manuscript, Available Online from 21 December 2024

https://doi.org/10.22055/agen.2024.48100.1746

Abstract

Introduction Arid and semi-arid areas such as Khuzestan province has highly fragile ecosystems that are characterized by low soil fertility, and high organic matter decomposition rates. Moreover, according to the FAO, around 12% of world soils and 65% of Iran's soils are calcareous and more than ... Read More Introduction Arid and semi-arid areas such as Khuzestan province has highly fragile ecosystems that are characterized by low soil fertility, and high organic matter decomposition rates. Moreover, according to the FAO, around 12% of world soils and 65% of Iran's soils are calcareous and more than 20 % of the irrigated farms in the world is affected by salinity. Since soil carbon saturation is low in saline-calcareous soils, the use of organic manure can be effective in increasing soil organic carbon and supplying essential nutrients in crop production. Applying organic manure in agriculture has been considered during the last two decades due to its high-quality products, high price, and low market availability of synthetic fertilizers, chiefly in developing countries. The manure application, both alone or in combination with inorganic fertilizers, is effective in increasing soil organic carbon (SOC) content and improve in soil fertility, microbial activity, and soil water retention capacity. Now the integrated application of organic and chemical fertilizers is inevitable for sustainable production and soil conservation. Hence, comprehension of the response of the soil and crop to applying organic and inorganic fertilizer may help to determine proper manure management strategies to enhance SOC and improve soil health and its ecosystem services. Thus, the aim of the study was to investigate the effects of different fertilizer managements on nutrient content of soil and wheat in saline-calcareous soils of Khuzestan province. Materials and Methods To evaluate the effect of the integrated and long-term application of chemical and organic fertilizers on the nutrient content of soil and wheat grain in fixed plots, this research was carried out in Khuzestan province (Ahvaz city) in a calcareous- saline soil with silty clay texture under wheat cultivation (Barat cultivar) as a randomized complete block design in six treatments with three replications for four years (2017-2021). The treatments included T1: unfertilized control, T2: application of nitrogenous, phosphorus and potassium chemical fertilizers based on soil test, T3: application of 20 tons of cattle manure every two years + 75% of recommended nitrogen + 50% of the recommended phosphorus and potassium, T4: application 20 tons of bagasse every two years + 75% of the recommended nitrogen + 50% of the recommended phosphorus and potassium, T5: annual application of 20 tons of cattle manure + 75% of the recommended nitrogen, T6: annual application of 20 tons of bagasse + 75% of the recommended nitrogen. In treatment T2 recommended dose of P2O5, K2O, and 30 % of recommended N were applied at the time of second irrigation; the remaining N dose was applied in two splits at tillering (40 % of recommended N) and booting stages (30 % of recommended N). The organic manures were incorporated in the soil (depth 0-15 cm) a week before sowing. At the end of the growing season, wheat yield components were measured. At the end of the growth season, some soil properties involved pH, salinity and SOC, and the concentration of nitrogen, phosphorous and potassium in soil and grain wheat were determined. SAS v.9.1 statistical software and LSD test were used to compare the means of the studied treatments. Results and Discussion The mean values of SOC varied in range of 0.60 to 0.73 %. As a result of applying treatment T2 (inorganic fertilizers application as alone), no significant difference was observed in SOC compared to the control treatment (p< 0.05). Compared to unfertilized control treatment, the SOC content were increased significantly by the use of cattle manure at T3 treatment (0.13 %), which could be attributed to the larger proportion of tenacious organic compounds in organic fertilizers than in chemical fertilizer. The highest concentration of soil available phosphorus (19.8 mg kg-1) was obtained in the integrated application of chemical fertilizer and cattle manure (T3), which is 60 and 169 % higher than those in the exclusive chemical fertilizer application (12.35 mg kg-1) and control (7.35 mg kg-1) treatments, respectively. The highest average soil available potassium concentration (253.3 mg kg-1) was also observed in T3. The results showed that the application of different fertilizer treatments was significant only on the nitrogen concentration of wheat grain (p< 0.01). The increase in wheat grain nitrogen concentration due to the application of integrated fertilizer treatments (28-38% increase compared to the control treatment) was significantly higher than the chemical fertilizers treatment (19% increase compared to the control treatment). Conclusion Based on the results of this research, it was found that the integrated application of organic and inorganic fertilizers has a more positive effect on improving soil fertility in the long term than using them alone. Moreover, the results indicated that the use of cattle manure was more effective than bagasse manure which may be due to its lower carbon to nitrogen ratio (21.3). The integrated use of organic and inorganic fertilizers not only improve soil fertility, but also increases the efficiency of chemical fertilizer use, which reduces the basic chemical fertilizers consumption. Therefore, it is recommended to application of 20 tons of cattle manure every two years + 75% of recommended nitrogen + 50% of the recommended phosphorus and potassium (T3) in the saline-calcareous soils under wheat cultivation in arid and semi-arid climates such as southern of Khuzestan province.

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