Research Article
Mohammad Reza Alashti; Mojtaba Khoshravesh; Fardin Sadegh-Zadeh; Hazi Mohammad Azamathulla
Abstract
Introduction
The rapid growth and development of urban communities, coupled with the increased industrial and economic activities in recent years, have led to the production and release of various pollutants into the environment. These pollutants have adverse effects on human health, living organisms, ...
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Introduction
The rapid growth and development of urban communities, coupled with the increased industrial and economic activities in recent years, have led to the production and release of various pollutants into the environment. These pollutants have adverse effects on human health, living organisms, and the overall environment. With limitations in water resources, insufficient rainfall, the looming risk of water crises in many countries, and the escalating pollution of surface and underground water, there is a pressing need for environmental solutions to mitigate these issues. It is important to acknowledge that wastewater often contains pollutants that may render it unsuitable for certain applications. The utilization of biochar derived from cost-effective materials and innovative technologies such as ultrasonics is one avenue that warrants exploration for enhancing water quality. In this approach, a nitrate solution is exposed to both an adsorbent and ultrasonic waves. This dual treatment induces changes in the physical and chemical properties of water, thereby offering potential improvements in water quality.
Materials and Methods
This study aimed to explore the impact of utilizing biochar derived from rice straw, which was coated with iron (III) and zinc cations, and subjected to ultrasonication, on the nitrate adsorption process from aqueous solutions. In order to produce biochar, cheap materials of rice straw were used. The chopped straw was placed in the electric furnace and heated for one hour to reach the desired temperature. Then it was kept at that temperature for 2 hours. After that, the obtained biochar was washed three times with distilled water at a ratio of 1:20 and dried in an oven at 70°C for 24 hours. In this research, two different temperatures of 350°C and 650°C were used for the production of biochar, which according to the results obtained in the pre-tests of the research that nitrate removal efficiency is higher in biochars made at 650°C. These biochars were used for the continuation of the experiments. In this research, after conducting pre-tests to optimize the adsorbent dose in the proportions of 0.1, 0.3, 0.5, 0.8 and 1 gram of the adsorbent and 40 ml of nitrate solution, concentrations of 20, 45, 80, 100, 150 and 200 ppm of nitrate solution was investigated. The research involved conducting experiments to determine the optimal parameters for each treatment, with three repetitions conducted in the water quality laboratory of Sari agricultural sciences and natural resources university during the years 2021 and 2022. The treatments comprised biochar (B), biochar and ultrasonic (BU), biochar with iron (III) coating (BF), biochar with iron (III) coating and ultrasonic (BFU), biochar with zinc coating (BZ), and biochar with zinc coating and ultrasonic (BZU). In this investigation, Langmuir and Freundlich adsorption isotherms were examined.
Results and Discussion
The results indicated that the BF and BFU treatments exhibited a higher maximum adsorption capacity. The Freundlich isotherm demonstrated higher correlation coefficients for BF, BFU, BZ, and B, suggesting a superior fit of the Freundlich model in these treatments. The better fit of the Freundlich adsorption isotherm indicates the heterogeneity of biochar surface adsorption sites, which means that the adsorption process is not confined to a single constituent layer. Nitrate adsorption on biochar surface is probably influenced by electrostatic adsorption and ion exchange. Conversely, the BZU and BU treatments showed a better fit with the Langmuir model. In the analysis of the Freundlich isotherm, nf values revealed that BF, BFU, and BZ treatments exhibited a favorable adsorption state with a desirable curve shape. The B treatment displayed a normal adsorption state with a linear curve shape, while BU and BZU treatments showed a weak adsorption state with an unfavorable curve shape. The elevated values of adsorption capacity (KF) obtained for BF, BFU, and BZ, namely 1909.414, 1484.22, and 386.63 ((mg/g)(L/mg)1/n), respectively, underscore the high nitrate adsorption capacity of these treatments. Also, biochars coated with iron (III) and with iron solution concentration of 10000 mg/L had a very good performance in removing nitrate from aqueous solutions. The new ultrasonic technology was able to improve the performance of the tested adsorbents in a period of 5 minutes without the need to stir the mixture of biochar and nitrate solution in the obtained equilibrium times, which were between 60 and 120 minutes. The use of this technology can be effective and useful in increasing the economic benefits of using limited water resources and increasing the efficiency of water consumption.
Conclusions
The utilization of cost-effective biochars derived from rice straw, along with the application of ultrasonic technology, can substantially decrease nitrate levels in aqueous solutions. In the case of biochar with iron (III) coating, biochar with iron (III) coating combined with ultrasonic treatment, and biochar combined with ultrasonic treatment, there is a notable affinity for nitrate to be adsorbed onto the surface of the adsorbent.
Research Article
خدیجه Javan; Alireza Movaghari
Abstract
Introduction
The most important effect of global warming is the increase in extreme weather events. According to AR5 reports, between 1951 and 2010, the number of warm days and nights increased and the number of cold days and nights has declined globally. In addition, the duration and frequency of hot ...
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Introduction
The most important effect of global warming is the increase in extreme weather events. According to AR5 reports, between 1951 and 2010, the number of warm days and nights increased and the number of cold days and nights has declined globally. In addition, the duration and frequency of hot periods, including thermal waves, has increased since the middle of the twentieth century. The trend analysis of temperature extreme indices is important in estimating the trend of global warming. Temperature Changes are affected by many complex factors. A significant part of these changes is due to the elements of the general circulation of the atmosphere and the sea surface temperature. Given that extreme weather events are one of the most devastating natural hazards and have harmful effects on different parts of society, therefore, many researchers have studied the changes in the past and future of extreme events and the mechanisms that trigger these changes. This research attempts to study the trend of changes in extreme temperature indices in North-West of Iran, and also their relation with general circulation of atmosphere.
Data and methods
At first, diurnal data of minimum and maximum temperature of 20 synoptic stations of the Northwest of Iran, which have long-term and reliable statistics, extracted for the period of 1986-2010 and quality control and data homogeneity of them were investigated. afterwards, 16 Extreme temperature indices introduced by ETCCDMI were applied. In general, these indices are categorized into five categories of absolute indices, based on percentiles, based on thresholds, periodic, and amplitudes that measure the frequency, severity and duration of the temperature. These indices are estimated by RClimDex software and the trend rate of the changes in indices was shown as maps. To measure the changes in the general circulation of atmosphere the annual mean circulation composites extracted for the periods of 1961-1985 and 1986 -2016 based on the reanalysis data of the NCEP / NCAR. Then the difference maps plotted using grads software.
Results
The regional trend of extreme indices and the percentage of stations with a positive and negative trend were identified and the spatial distribution of the gradient of each of the indices was mapped. The results show that all absolute temperature indices have an increasing trend. On average, the maximum temperature (TXx and TXn) has increased by about 0.04 degrees over the decade. The Increase rate of TNx is about 0.03 degrees, while the TNn increased about 0.1 degrees Celsius per decade during the study period. Therefore, in the north-west of Iran, temperature increase has mainly occurred at night. The values of cold days (TX10) and cold nights (TN10) decreased with a gradient of -0.46 and -0.42 days in the decade. The warm days (TX90) and warm nights (TN90) have an increasing trend in 95% of the stations in the area. Frost days (FD) and icing days (IDs) have a decreasing trend, whereas, summer days (SU25) and tropical nights (TR20) have an increasing trend. The number of frost days with a gradient of -0.95 and the number of icing days with a gradient of -0.63 days in decade are decreasing. While, the number of summer days with a gradient of 0.81 and the number of tropical nights with gradient of 0.31 days in decade are increasing. In the northwest of Iran, all stations have been experiencing the increasing trend in Warm spell duration index (WSDI), but the cold spell duration index (CSDI) in 70% of the stations in the region has decreased. Growing season length, as an effective index especially in agriculture, is increasing by an average of 1.1 days per decade. Based on the results of research carried out globally and at the Iran, the trend of Daily temperature range (DTR) is negative, while this index has a positive and increasing trend in 65% of North-West stations in Iran. Except TNx and TNn indices that have positive trend in most stations in the region, Comparison of warm and cold extreme indices indicates that warm indices have a positive and incremental trend, while cold indicators show a decreasing trend. The positive gradient of these indices also corresponds to the decreasing trend of cold day and night indices, which indicates an increase in temperature and a decrease in cold days and nights. The study of large-scale changes in atmospheric circulation shows that the study area has been warmer in the spring and summer and colder in autumn and winter.
Conclusion
In this study, the trend of temperature extreme indices in North-West of Iran and its relation with the large-scale general circulation of the atmosphere have been investigated. The results show that all absolute temperature indices (TXx, TXn, TNx and TNn) are incremental. The indices of cold days (TX10) and nights (TN10) decreased with a gradient of -0.46 and -0.42 days in the decade and the indices of warm days (TX90) and warm nights (TN90) are increasing in 95% of the stations in the area. Frost days and icing days (IDs) show declining trend and summer days (SU25) and tropical nights (TR20) have an increasing trend. In the north-west of Iran, all stations have experienced an increasing trend in Warm spell duration index (WSDI), but the cold spell duration index (CSDI) has been decreasing in 70% of the stations in the area. Growing season length (GSL) is increasing by an average of 1.1 days in every decade. Daily temperature range (DTR) has a positive and increasing trend in 65% of stations in north-west Iran. Comparison of warm and cold extreme indices indicates that warming indices have a positive and incremental trend, while cold indices show a decreasing trend. Study of the general circulation of atmosphere of the region by drawing and analyzing difference maps indicates that the study area has been warmer in spring and summer and colder in autumn and winter.
Keywords: Climate Change, Temperature Indices, Atmosphere Circulation, Northwest of Iran.
Research Article
Ali Sarabchi; Hossein Rezaei; farzin shahbazi
Abstract
Introduction
High-resolution satellite imagery data is widely utilized for Land Use/Land Cover (LULC) mapping. Analyzing the patterns of LULC and the data derived from changes in land use caters to the increasing societal demands, improving convenience, and fostering a deeper comprehension of the interaction ...
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Introduction
High-resolution satellite imagery data is widely utilized for Land Use/Land Cover (LULC) mapping. Analyzing the patterns of LULC and the data derived from changes in land use caters to the increasing societal demands, improving convenience, and fostering a deeper comprehension of the interaction between human activities and environmental factors. Although numerous studies have focused on remote sensing for LULC mapping, there is a pressing need to improve the quality of LULC maps to achieve sustainable land management, especially in light of recent advancements made. This study was carried out in an area covering approximately 8000 hectares, characterized by diverse conditions in LULC, geomorphology and pedology. The objective was to investigate the potential for achieving maximum differentiation and accurate mapping of land features related to LULC. Additionally, the study assessed the impact of various spectral indices on enhancing the results from the classification of Landsat 8 imagery, while also evaluating the efficacy of support vector machine (SVM) and maximum likelihood algorithms in producing maps with satisfactory accuracy and precision.
Materials and Methods
As an initial step, LULC features were identified through fieldwork, and their geographic coordinates were recorded using GPS. These features included various types of LULC, soil surface characteristics, and landform types. Following the fieldwork, 12 types of LULC units were identified. Subsequently, the LULC pattern in the study area was classified using the RGB+NIR+SWIR1 bands of Landsat 8, employing both SVM and maximum likelihood classifiers. To assess the impact of various spectral indices on improving the accuracy of the LULC maps, a set of vegetation indices (NDVI, SAVI, LAI, EVI, and EVI2), bare soil indices (BSI, BSI3, MNDSI, NBLI, DBSI, and MBI), and integrated indices (TLIVI, ATLIVI, and LST), and digital elevation model of study area were successively incorporated into the classification algorithms. Finally, the outcomes from the two classification algorithms were compared, taking into account the influence of the applied indexes. The classification process continued with the selected classifier and indices until reaching the maximum overall accuracy and kappa coefficient.
Results and Discussion
Field observations revealed that the study area could be categorized into 12 primary LULC units, including irrigated farms, flow farming, dry farming, traditional gardens (with no evident order observed among planted trees), modern gardens (featuring regular rows where soil reflectance is visible between tree rows), grasslands, degraded grasslands, highland pastures (covered by Astragalus spp., dominantly), lowland pastures (covered by halophyte plants), salt domes (with no or very poor vegetation), outwash areas (River channel with many waterways), and resistant areas. The results of image classification indicated that the performance of the SVM algorithm across different band combinations is superior to that of the maximum likelihood method. Using SVM resulted in an increase in overall accuracy and Kappa coefficient by 3-8% and 0.03-0.08, respectively. For the map generated using RGB+NIR+SWIR1 bands and employing SVM, overall accuracy and Kappa coefficient were determined to be 76.6% and 0.72, respectively. Among the vegetation indices used in the SVM algorithm, LAI had the most significant impact, increasing the classification accuracy by 2.64%. Among the soil indices, BSI and MBI indices demonstrated the best performance; with BSI increasing the classification accuracy by 1.95% and MBI by 1.64%. Among the integrated indices, LST and ALTIVI enhanced the classification accuracy by 2.75% and 2.35%, respectively. It should be noted that the inclusion of the digital elevation model did not significantly improve the classification accuracy when using the support vector machine algorithm; in fact, it led to a decrease in accuracy when applied to the maximum likelihood classification. The probable reason for this issue is the different nature of DEM data compared to the other input data, as well as the limitations of parametric statistical approaches to effectively integrating data from diverse sources. Finally, the classification process was executed using the three visible bands, NIR, and SWIR1, in conjunction with selected indices (LAI, BSI, MBI, LST, and ALTIVI). Results indicated that using these spectral indices significantly improved classification accuracy, particularly for the DF, DGL, MG, O, and IF land cover/use classes. The calculated accuracies for these classes increased by 11.62%, 18.57%, 20.06%, 29.39%, and 33.19% respectively. Consequently, the accuracy of the classification and the Kappa coefficient (using support vector machine algorithm) increased to 85.24% and 0.82, respectively.
Conclusion
In this research, we aimed to accurately map various land use/land covers by utilizing Landsat 8 imagery and incorporating three group of spectral indexes. Despite spectral interferences and overlaps among various phenomena related to LULC, the utilization of different spectral indices resulted in significant differentiation among LULC classes. Finally, considering the limitations of modelling in ENVI software, it is recommended to investigate the effectiveness of other models for classification in more specialized software, such as R.
Research Article
Abdolreza Zahiri; Khalil Ghorbani; Hamed Feiz Abady; Hossein Sharifan
Abstract
Introduction: The reservoirs are considered as vital sources of water supply for human societies, hence the correct and planned management of their reserves is an essential issue. Dams are used for purposes such as urban water supply, irrigation of agricultural lands, floods control and hydroelectric ...
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Introduction: The reservoirs are considered as vital sources of water supply for human societies, hence the correct and planned management of their reserves is an essential issue. Dams are used for purposes such as urban water supply, irrigation of agricultural lands, floods control and hydroelectric power generation. In order to properly manage and monitor the consumption of these important reserves, it is inevitable to know their capacities. Using water stage and the reservoir's initial volume-area-elevation curve, which is prepared with the hydrographic operations, is a common method for estimating the storage capacity of reservoirs at different water levels. Over time and the occurrence of numerous sedimentations that can occur due to factors such as floods, the initial volume-area-elevation curve of the reservoir changes, hence it needs to be modified.The hydrographic operation of reservoirs using tools like Eco-sounders is a conventional method for correction of this curve, which is not only expensive but also time-consuming. In recent years, various studies based on remote sensing with the aim of estimating the volume of water stored in reservoirs have calculated water levels to establish the surface area-elevation curve. The basis of these studies are the separation of water-lands masks with the help of spectral indices, the calculation of water levels, and the developing of reservoir surface area-elevation curves using linear or polynomials relationships. The main limitation of these methods is the inaccuracy of linear or polynomial relationships in fitting the surface area-elevation curves of the reservoir for the beginning and end points of the water stage change interval, which corresponds to the empty or fullness of the reservoir. and these happen due to the occurrence of factors such as drought or floods.In this research, with the help of to eliminating the limitation of linear and polynomial relationships for accurately predicting the points of the reservoir surface area-elevation curves where the observational data are not available due to non-occurrence, by drawing the hypsometric curve using the Modified Strahler method has been used. By using the hypsometric curve, it is possible to calculate the storage capacity of the reservoir between successive water levels and obtain the final volume of water stored in it. In this study, by comparing the volumes of water stored at the present and initial reservoir capacities, the sedimentation rate and the useful life of the reservoir of Negarestan dam have been estimated.
Material and Methods: Negarestan Dam (Kabudval) is located on the Qara Su (Zarin Gol) river, and 45 km east of the city of Gorgan in the Golestan province. This dam is used for purposes such as supplying urban water to Aliabad city and supplying water needed for the agricultural irrigation network of Qarasu. In this srudy, landsat8 satellite images were used to estimate the useful life of the Negarestan reservoir. The required images of the ROI were downloaded through the USGS database and pre-processed in Envi5.3 software. Using visible and infrared spectral bands, water indices NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet were calculated to separate land-water masks. After evaluating the accuracy of the obtained water level results by comparing it with the initial volume-area-elevation curve of Negarestan reservoir, the MNDWI index was used as the most accurate index to calculate water levels.In this study, the modified Strahler method was used to obtain the hypsometric curve of the surface area-elevation of the reservoir, which has high accuracy in extrapolating the beginning and end points of the curve. By using the hypsometric curve, water level levels were extracted for arbitrary water levels and with the help of the prismoidal method relation of the volume between consecutive water levels, the sum of these volumes is equal to the current storage capacity of the reservoir. To estimate the sedimentation rate of the Negarestan dam reservoir, the current storage capacity of the reservoir was compared with the initial storage capacity in 2015, and based on this, the useful life of the reservoir was accurately predicted.
Results and Discussion: Validation results for calculating water surface areas using NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet water indices showed that the MNDWI index with an average water surface areas calculation error equal to 5% is more accurate than other indices. Therefore, MNDWI index was used in this study. Also, the comparison of the volume of water stored in the Negarestan reservoir with its initial storage capacity at the time of operation showed that in a period of 9 years, the storage capacity of the reservoir (at the water level equal to about 189.5 meters), which is equivalent to the approximate level of the overflow crest. It has decreased from about 24 to 20 million cubic meters, based on which the average annual sedimentation rate of the reservoir was estimated to be about 1.6%. The results showed that in a period of 9 years, the average level of the bathymetry of Negarestan reservoir has increased by 10 meters due to the accumulation of sediments, and the minimum level of the batymetry has reached from 160 to about 170 meters.According to the statistics of the International Commission on Large Reservoirs (ICOLD), the average annual sedimentation rate of the world's reservoirs is reported to be about 0.95%, and the results show that this amount in the Nagaristan Dam reservoir is almost 2 times the average rate. It is universal. According to the results obtained from this research and assuming constant climatic conditions, the useful life of the Nagarestan dam reservoir was estimated to be about 53 years from the beginning of 2024.
Conclusion: Considering the increasing importance of water resources management, including dam reservoirs, in this study, a fast and inexpensive method based on remote sensing is used to calculate the volume of water stored in dam reservoirs and estimate the useful life. They were presented. In addition to the appropriate accuracy, this method was able to overcome the limitations of the previous methods in estimating the volume of accumulated sediment in the deep parts of the reservoir and can be used for the correct management of water resources.
Research Article
mohamad malehmir chegini; AHMAD GOLCHIN
Abstract
Introduction:
Soil contamination with heavy metals poses a significant threat to both environmental and human health. Anthropogenic activities, including the use of chemical fertilizers and pesticides, industrial processes, wastewater disposal, and mining, contribute to the accumulation of heavy metals ...
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Introduction:
Soil contamination with heavy metals poses a significant threat to both environmental and human health. Anthropogenic activities, including the use of chemical fertilizers and pesticides, industrial processes, wastewater disposal, and mining, contribute to the accumulation of heavy metals in soil. These contaminants can then be taken up by plants and enter the food chain, causing various health problems. Soil amendments such as biochar and activated carbon offer a promising strategy for reducing the mobility and bioavailability of heavy metals in soil. This study investigated the effectiveness of biochar and activated carbon derived from organic waste materials (wheat straw, walnut shells, and almond shells) in immobilizing lead (Pb), zinc (Zn), and cadmium (Cd) and promoting corn (Zea mays L.) growth in a greenhouse setting using contaminated soil.
Materials and Methods:
Three types of organic waste – wheat straw, walnut shells, and almond shells – were pyrolyzed at two temperatures (300 °C and 500 °C) under oxygen-free conditions for two hours to produce six types of biochar. The resulting biochars were then activated with phosphoric acid at their respective production temperatures, yielding six types of activated carbon. These organic waste materials, biochars, and activated carbons were added to a soil contaminated with lead, zinc, and cadmium at four application rates (0, 2.5, 5, and 10% by weight) in triplicate, 4.5 kg pots. The pots were incubated for one month under controlled temperature and humidity to achieve a relative equilibrium. Following incubation, the concentration of available heavy metals in the treated and control soils was measured. Corn was then planted in the pots, and at the end of the growth period, plant growth parameters (dry weight of shoots and roots) and heavy metal concentrations in plant tissues were determined. The data were analyzed using a completely randomized factorial design, and treatment means were compared to each other and to the control.
Results:
Increasing pyrolysis temperature resulted in increased biochar pH, electrical conductivity (EC), and ash content, while the percentage of organic carbon, C/N ratio, and cation exchange capacity (CEC) decreased. Activation with phosphoric acid lowered the pH, ash content, EC, and organic carbon content of the biochars, while increasing their CEC. Amending the soil with biochar significantly increased soil pH and EC, whereas activated carbon amendments decreased these parameters. All amendments (organic waste, biochar, and activated carbon) significantly reduced the concentration of available heavy metals in the soil. Activated carbon had the greatest effect on immobilization, while organic waste had the least. The highest dry weight of corn shoots and roots was observed in treatments containing activated carbon produced at 500 °C and applied at a rate of 5%. Conversely, the lowest concentration of heavy metals in corn tissues was observed in treatments with activated carbon produced at 500 °C and applied at a rate of 10%.
Conclusion:
This study demonstrates that activated carbon derived from organic waste materials can be an effective and sustainable method for remediating soil contaminated with heavy metals and promoting plant growth. However, the presence of detectable heavy metals in corn tissues following activated carbon application suggests that this approach may be best suited for soils with low to moderate contamination levels.
Heavy metals are persistent soil pollutants that pose significant risks to environmental and human health. The application of soil amendments such as biochar and activated carbon has been proposed as an effective strategy for reducing the mobility of heavy metals in soil. This study examines the impact of various organic wastes (wheat straw, walnut shells, and almond shells), along with the biochar and activated carbon derived from these wastes, on immobilizing heavy metals (lead, zinc, and cadmium) and promoting corn plant growth in contaminated soil under greenhouse conditions. Biochars were produced at two pyrolysis temperatures, 300°C and 500°C, and subsequently activated with phosphoric acid and the experimental treatments were added to a contaminated soil at four levels (0, 2.5, 5 and 10% by weight) and in three replicates The results showed that organic wastes, biochars, and activated carbons significantly reduced the concentration of available heavy metals in the soil at a probability level of 5%. Activated carbons had the most effect and organic waste had the least effect. The lowest concentrations of lead, cadmium, and zinc extractable with DTPA were observed with the 500°C activated carbon derived from wheat straw at a 10% application rate, with values of 1.6, 4.5, and 464 mg/kg soil, respectively, representing reductions of 99.46%, 83.67%, and 63.96% compared to the control treatment. This treatment also resulted in the lowest heavy metal concentrations in both the aerial parts and roots of the corn plants. Specifically, the lowest concentrations of lead, zinc, and cadmium in the aerial parts were 71.67, 490.67 and 1.67 mg/kg dry weight, respectively, and in the roots, they were 206, 1095 and 20 mg/kg dry weight, respectively. The highest dry weights of the aerial parts and roots were also observed with this treatment and a 5% application rate, with values of 5.76 and 1.84 grams per pot, respectively. The findings of this study suggest that activated carbon is an effective and sustainable method for remediating soils contaminated with heavy metals and enhancing plant growth.
Research Article
Nadia Bahremand; Hossein Aroiee; Ahmad Aien
Abstract
Introduction: the watermelon (Citrullus lanatus) is a known product with high demand and nutritional value and the capability to export all over the world, and considering that the ultimate goal of all agricultural production systems is to achieve the maximum yield of the plant, and providing the water ...
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Introduction: the watermelon (Citrullus lanatus) is a known product with high demand and nutritional value and the capability to export all over the world, and considering that the ultimate goal of all agricultural production systems is to achieve the maximum yield of the plant, and providing the water required for the plant is most effective factor on yield, as a result, investigating of t water limitation effec seems to be an undeniable necessity. On the other hand, dificit irrigation has been introduced as a tool to increase water productivity, thus it is necessary to take into account the effects of this method of saving water consumption on plant production, which doubles the need for research and shows it more clearly, and in addition, Deficit irrigation is applied by providing a part of the plant's water needs, while regulated deficient irrigation is a type of deficient irrigation that can be implemented in several ways, including irrigation based on growth stages or, in other words, allocating of the water to stages that are more sensitive to drought. we should know that the response of plants to lack of the irrigation depends on several factors, including climatic conditions, type of plant, intensity and method of application of deficit irrigation, soil condition and management.
Materials and methods: In order to determine the effect of deficit irrigation and regulated deficit irrigation on yield and water productivity of the watermelon, an experiment in the form of randomized complete blocks with 8 treatments including three irrigation levels of 100, 70 and 50 % of the plant's water requirement (evapotranspiration estimated by the FAO-Penman-Monteith method) and 5 regulated deficit irrigation levels including 50% of the water requirement in the stages of seedling, vine, flowering, fruit expansion and fruit maturity was carried out with three repetitions under black plastic mulch, during 2020-2022, in the Research and Education Center of Agriculture and Natural Resources in the south of Kerman province. Irrigation as the main plot at three levels of 100, 70 and 50% of water requirement and mulching at three levels of crushed date palm leaf, black plastic and no mulch, as the sub-plot, were considered. Crimson B 34 watermelon seeds produced by Seminis company, were planted on January 2021, in plots with the size of 13.5 × 7 m, on furrows and ridges planting system (the width of furrows and ridges were 0.5 and 4 meters, respectively). After planting, bow-shaped wires were put on the planting rows and a transparent plastic was placed as a tunnel on them. In the first year, the total depth of the irrigation in aforesaid treatments was respectively 444, 321, 237, 413, 389, 435, 345 and 425, and in the second year 427, 303, 223, 395, 373, 416, 331 and 405 mm.
Results and Discussion: The results showed that the highest and lowest yield were observed in full irrigation and irrigation 50 % (60.1 and 16.3 t ha-1 respectively). Among the regulated deficit irrigation treatments, irrigation 50% at the seedling stage was the closest to full irrigation, and the irrigation 50 % at the fruit expansion stage had the lowest yield. the highest water productivity belonged to the irrigation 50 % in the seedling and vine stages (15.9 and 1.15 kg m-3 respectively). Irrigation 50% in fruit maturity stage despite irrigation 50% improved Qualitative characteristics such as soluble solids, vitamin C, dry matter, lycopene and fruit taste.
Conclusion: By applying of deficit irrigation with intensities used in this study, compared to full irrigation (control), a significant decrease in watermelon yield was observed. water productivity remained almost constant, there was no significant increase in the quality of the edible part, but treatments of regulated deficit irrigation including seedling stage in terms of yield without significant difference with full irrigation and irrigation 50 % of vine stage in terms of water productivity and irrigation 50% of fruit maturity stage were superior in terms of quality compared to the control. generally regulated deficit irrigation had better results than deficit irrigation due to less yield reduction, increased water productivity and fruit quality in the watermelon, which it can be noticeable in the conditions of water restriction. Finally, it is recommended that milder intensities of deficit irrigation that seem to have more favorable results in this plant should be investigated in the next studies.
Acknowledgement:
Research Article
Helaleh Fahimi; Abd0llah Faraji; bohlul alijani
Abstract
Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity ...
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Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea.
Research Article
Narges Lotfi; shahram kiani; Hamid Reza Motaghian
Abstract
Introduction
Selenium (Se) is one of the beneficial elements for plants, which is usually not supplied in the nutrient solutions used in soilless cultures. It is an essential element for both humans and animals. Application of Se at low concentrations has a positive effect on the growth and quality ...
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Introduction
Selenium (Se) is one of the beneficial elements for plants, which is usually not supplied in the nutrient solutions used in soilless cultures. It is an essential element for both humans and animals. Application of Se at low concentrations has a positive effect on the growth and quality indices of plants. Nitrate accumulation in leafy vegetables poses threaten to human health. Leafy vegetables such as Lettuce (Lactuca sativa L.) contain high levels of nitrate. According to the results of some researches, application of Se in the nutrient solutions can decrease nitrate accumulation in vegetables. However, the optimum concentration of Se in the nutrient solution for lettuce production in hydroponic culture is still not clear. This experiment was conducted to elucidate the effect of different levels of Se in the nutrient solution on the growth indices, yield, and nitrate accumulation of red French lettuce (cv. Lolla Rossa) in soilless culture.
Materials and Methods
A perlite culture experiment, using completely randomized design, was carried out with seven levels of Se in the nutrient solution (0, 0.1, 0.5, 1, 5, 10 and 20 µmol L-1) with four replications in the research greenhouse of Shahrekord University. Lettuce seedlings were grown in 1.7 L plastic pots (one plant per pot) containing perlite with size of 0.5-5 mm and were manually fertigated with the nutrient solutions on a daily basis. Different concentrations of selenium were applied as sodium selenate (Na2SoO4) in the nutrient solution (Domingues et al., pH= 5.4±0.1, EC=1.36-1.41dS m–1). After four weeks, lettuce plants were harvested and the fresh weights of shoots and roots were measured. Plant growth indices consisting of leaf number, leaf length, leaf width, plant height, plant diameter, leaf chlorophyll index, and leaf total soluble solids were determined. In one bush in each treatment, the leaves were separated as 1st to 10th outer leaves and other inner leaves. The leaves were dried in an oven at 70 °C and were ground. Nitrate concentrations in outer and inner leaves were measured calorimetrically using a spectrophotometer at a wavelength of 410 nm. Shoots Se concentration was determined with ICP-MS after wet digestion of samples with HNO3 and H2O2. Analysis of variance was done using SAS software and means comparison was conducted using the least significant difference test at 0.05 probability level.
Results and Discussion
The results indicated that application of Se in the nutrient solution had not significant effect on the lettuce growth indices including of leaf length, leaf width and leaf number. Application of 10 µmol L-1 of Se in the nutrient solution led to significant decrease of plant height in comparison with control, but plant diameter increased with application of Se in the nutrient solution. The highest plant diameter was observed in 10 μmol L–1 of Se treatment. The highest and the lowest shoot fresh weight were obtained under 0 and 1 μmol L–1 Se in the nutrient solution, respectively. Application of 1 μmol L–1 Se increased shoots fresh weight by 22% comparing to the control. Shoot Se concentration was increased with application of Se in the nutrient solution. The highest concentration of Se in shoots (15 mg kg-1 dry matter) was observed at the rate of 20 μmol L–1 Se in the nutrient solution. The amount of Se accumulated in the plant tissue is important in biofortification programs. The results showed that application of Se in the nutrient solution (with the exception of 1 µmol L-1 Se) led to significant decrease in the nitrate concentration of roots, outer leaves, inner leaves and all leaves of lettuce. The lowest nitrate concentration in all leaves of lettuce (2095 mg kg-1 fresh weight) was obtained in plants nourished with 0.5 μmol L–1 Se in the nutrient solution. Compared with control (0 μmol L–1 Se), nitrate concentration in all leaves for 0.5 μmol L–1 Se treatment was decreased 28%. Selenium has a positive function on decreasing nitrate accumulation in plants via regulating the transport of nitrate and enhancing activities of nitrogen metabolism enzymes.
Conclusions
According to our results, application of Se decreased nitrate concentration in lettuce plants. Therefore, application of Se in the nutrient solution at the rate of 0.5 μmol L–1 is suggested for red French lettuce production in hydroponic culture under the conditions of the present study.
Research Article
Somayyeh Mirshekari; Fatemeh Yaghoubi; Seyed Abolfazl Hashemi
Abstract
Introduction
The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the ...
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Introduction
The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the countries in the Middle East with a different climate in each region of the country, has suffered significant adverse effects of climate change. Considering the importance of the climate change, it is important to investigate the changes in climate variables to know the future conditions and make management decisions. In the field of climate research, global climate models are useful tools that are often used to investigate the global climate system, including historical and projected periods. Since the use of the CMIP6 dataset provides improved clarity and accuracy for predicting future climate forecasts, the main objective of the present study is to predict the temperature and precipitation changes in the near, mid, and far future in Sistan-va-Baluchestan province.
Materials and Methods
The minimum temperature, maximum temperature, and precipitation data of 10 general circulation models (GCMs) of the 6th IPCC report for the baseline (1990-2014) were downloaded from the Global Climate Research Program database (https://esgf-node.llnl.gov). Then GCMs were including ACCESS-CM2, CMCC-ESM2, CNRM-CM6-1-HR, CNRM-ESM2-1, EC-Earth3-CC, EC-Earth3-Veg-LR, INM-CM4-8, INM-CM5-0, MIROC6, and NorESM2-MM. Four statistical indicators including correlation coefficient (R2), RMSE, Nash-Sutcliffe efficiency (NSE), and mean absolute error (MAE) were used to evaluate the performance of 10 GCMs. Based on the results obtained from the these indicators, the models that had higher performance in predicting the temperature and precipitation data were selected as the best models for forecasting in the future. The ensemble of these models under two SSP2-4.5 and SSP5-8.5 scenarios for the near, middle, and far future (2026-2050, 2051-2075, and 2076-2100) were extracted from the World Climate Research Program database.
CMhyd (Climate Model data for hydrologic modeling) tool was used to bias correction climate data of the selected models. In order to choose the best bias correction method, the R2, RMSE, NSE, and MAE were estimated.
After bias correction, the climate data of selected models were ensembled and then the changes in precipitation and maximum and minimum temperature in three future periods compared to the baseline was estimated.
Results and Discussion
The results showed that out of 10 GCMs, seven models had good performance (R2 > 0.40, 4.23 < RMSE < 12.02°C, 0.12 < NSE < 0.74, and 3.36 < MAE < 9.59°C) in simulating daily minimum and maximum temperature. However, the performance of all models in simulated daily precipitation was poor (R2 > 0.19, 1.24 < RMSE < 3.70 mm, -7.41 < NSE < -0.57, and 0.23 < MAE < 0.85 mm).
Among the different bias correction methods of temperature and precipitation available in CMhyd, the distribution mapping method had the best performance.
In all three regions, compared to the baseline, the average annual minimum and maximum temperature under two scenarios will increase in the future periods and precipitation will decrease in most periods and scenarios. These changes will be mainly in the SSP5-8.5 scenario compared to SSP2-4.5 and also in the far future period compared to the middle and near future. Averaged across all locations, annual maximum temperature showed increases in near, middle, and far projected periods of 1.3, 2.1, and 2.8°C under SSP2-4.5 and 1.6, 3.1, and 5.1°C under SSP5-8.5, respectively (Fig. 2), while for minimum temperature, the increases will be of 1.6, 2.6, and 3.4°C for SSP2-4.5 and 1.9, 3.9, and 6.3°C for SSP5-8.5.The range of annual precipitation among all sites was from –58.22 to 49.33% under SSP5-8.5 in the near and far future periods in Zabol and Iranshahr, respectively.
The annual increase in the average maximum and minimum temperature will be mainly due to the increase in air temperature in the months of January, February, August, September, October, November and December. The annual decrease in precipitation will mainly result from the decrease in precipitation in January, February, March, November, and December, and the annual increase in precipitation will result from the significant increase in precipitation in May and October compared to the baseline.
Conclusions
The results showed that under different scenarios of climate change, the maximum and minimum temperatures in the near, middle, and far future periods will face an increase compared to the baseline. However, the precipitation changes in the future time periods are not the same as compared to the baseline, and in some periods the precipitation will decrease and in others it will increase. But in general, the decrease in precipitation will be more than its increase. Therefore, it is very important to formulate and implement appropriate management programs for the needs of each region, in order to properly manage water resources and adapt to extreme temperatures and their consequences.
Research Article
Peyman Tahmasebi; Fatima Dalvand; Seyyed Abulfazl Hosseini; B. Karimi; Hirsch Ghadershenas
Abstract
Abstract
Agriculture plays a dual role in the energy sector meaning that it acts both as a source of raw material for bioenergy production and as a major consumer of energy, particularly in the processes of planting, cultivation and harvesting, transportation, processing, and storage of agricultural ...
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Abstract
Agriculture plays a dual role in the energy sector meaning that it acts both as a source of raw material for bioenergy production and as a major consumer of energy, particularly in the processes of planting, cultivation and harvesting, transportation, processing, and storage of agricultural products. Among the numerous challenges facing the agricultural sector, optimizing energy or input consumption is of paramount importance. These key inputs play a crucial role in ensuring food security and economic stability for the country. One of the most important agricultural development programs in the country should be to increase efficiency of energy consumption in the agricultural sector. In Iran, approximately 9.2 million hectares have been equipped with modern irrigation systems (pressure system) which has increased the water productivity index from 0.87 kg/m3 in 2014 to 0.32 kg/m3 in 2014. Accordingly, it is predicted to reach 0.60 kg/m3 hectares until 2025. The Dehgolan Plain, located in the east of Sanandaj city, has an area of 84,982 square kilometers. Groundwater is the only source of water for agriculture in the region. Due to the annual decrease in the groundwater level, energy consumption for water extraction has increased. Common irrigation systems in the region's farms include fixed-mobile sprinkler classic rain irrigation systems, center pivot, and lateral roll. Thus, it seems necessary to evaluate the energy productivity and efficiency indexes in the mentioned plain. The main objective of this study is to evaluate the energy consumption indexes of wheat in farms under fixed-mobile sprinkler classic and Willet rain irrigation systems.
Materials and Methods
This study was conducted in the farms of Dehgelan plains where the energy consumption trend of input factors in two irrigation systems was investigated. All information related to input factors and working hours of machinery, agricultural equipment, and manpower was recorded at the end of the cropping season 1400-1401 through filling out questionnaires. The studied farms in this research were all under dry wheat cultivation and equipped with two rain irrigation systems, system 1 (fixed-mobile sprinkler classic) and system 2 (WillMove irrigation). The required input factors for wheat production in each hectare were determined. The amount of different input factors for conversion to energy standard was calculated using energy coefficients and equivalents. As a result, energy productivity, energy use efficiency, specific energy, and net energy indexes were used to investigate the energy consumption trend of wheat in the two mentioned irrigation systems.
Results and Discussion
As a result, the total input energy for wheat production in systems (1) and (2) was 85943.97 and 69189.04 MJ/ha, respectively and Energy consumption in the Willet rain irrigation system was higher than in the fixed-mobile sprinkler classic rain irrigation system due to the high consumption of electricity and irrigation water. The electricity consumption in both systems accounted for the highest energy consumption. Moreover, the energy productivity and efficiency of the two systems were almost equal as well as the net energy of irrigation system (1) and irrigation system (2) was 41510.96 and 64156.03 MJ/ha, respectively.
Conclusion
In conclusion, the main topic of this study is to evaluate the energy trend in rain irrigation systems in dry wheat farms in Dehgelan plains, Kurdistan province, Iran. In this study, the energy indexes of wheat in smallholder farmers' farms in Dehgelan plain, Kurdistan province, were evaluated. The studied farms were categorized into two groups, system (1) (fixed-mobile sprinkler classic rain irrigation system) and irrigation system (2) (Willet rain irrigation system), the energy source of which was electricity for both systems. At the end of the cropping season, the total amount of input and output factors were collected by filling out questionnaires in person, and to validate the amount of electricity consumption, the amount was obtained from the Dehgelan Electricity Company. The results of the research showed that the energy consumption per unit of wheat production in the Willet irrigation system was higher than in the fixed-mobile sprinkler classic irrigation system. This difference was due to the higher consumption of electricity and irrigation water in the Willet irrigation system and the energy productivity and efficiency indexes were almost equal in both systems. Eventually, the net energy of the fixed-mobile sprinkler classic irrigation system was higher than that of the Willet irrigation system.
Research Article
Soheila Hosseinzadeh; ٍٍٍEsfandiar Fateh; amir aynehband; masoumeh farzaneh; JAFAR HABIBI ASL
Abstract
2. Introduction
Tillage is an important component of soil management that affects the production of crops. Maintaining and improving the quality of the soil is a basic requirement to ensure the sustainability of the ecosystem. This experiment was conducted in order to investigate the effect of different ...
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2. Introduction
Tillage is an important component of soil management that affects the production of crops. Maintaining and improving the quality of the soil is a basic requirement to ensure the sustainability of the ecosystem. This experiment was conducted in order to investigate the effect of different tillage methods and the use of plant residues on the yield, protein and nitrogen percentage of triticale plant and physical and chemical indicators of the soil.
3. Materials and Methods
The experiment was carried out in split plots based on a randomized complete block design with three replications at Shahid Chamran University of Ahvaz during 2022-2023. The main factor includes different methods of tillage in three levels (conventional tillage, reduced tillage and no tillage) and the sub factor also includes 5 levels of plant residue application (without residues (control), wheat residues, mung bean, sesame and half of wheat residues + half of residues Mung bean) was considered. The amount of residues used for each plot was approximately 30% of the biological yield of the product, which was considered to be 3, 1.5 and 1 ton.ha-1 for wheat, sesame and mung bean, respectively. At the end of the experiment yield and yield components, seed nitrogen and protein of triticale plant and physical characteristics (bulk density, percentage of porosity) and chemical (PH, EC, organic carbon content, nitrogen) soil properties were calculated, all statistical calculations were made using SAS 9.3 statistical software and for The LSD test was used to compare the means at a probability level of 5%.
4. Results and Discussion
The interaction of tillage treatments and the use of plant residues showed that the highest grain yield was equal to 8.6 ton.ha-1 from the treatment of reduced tillage and the use of Mung bean residues, and the lowest value obtained was related to the effect of the treatment conventional tillage and NO residues (Control) with 3.5 ton.ha-1. The grain yield in the reduced tillage method was 12.5% and 7.6% more than the conventional tillage and no tillage methods. . Also, the reduced tillage method showed a 32.2% increase in seed protein and a 32% increase in seed nitrogen compared to conventional tillage, the results showed that the interaction effect of tillage treatments and the use of residues on yield grain (p<0.01). Also, the interaction effect of tillage and application of residues on the bulk density (p<0.01). Based on this, the lowest bulk density of (1.3 g.cm-3) was related to the conventional tillage treatment and the use of wheat and Mung bean residues and the combination, which were placed in the same group. The highest bulk density (1.75 g.cm-3) was obtained from the no-tillage treatment and the use of NO residues (Control) . Based on the obtained results, the interaction effect of tillage treatments and the use of residues on soil organic matter, soil organic carbon and nitrogen soil (p<0.05). The interaction between the effects of tillage and the use of residues showed that the highest soil organic matter (1.53%) was from the treatment of reduced and the use of wheat residues.
5. Conclusion
The results showed that tillage methods and the use of plant residues, in addition to affecting the percentage of nitrogen and protein of triticale seeds, also affected the physical and chemical indicators of the soil. The changes related to the physical and chemical indicators of the soil in the method No tillage are more than the two methods of reduced tillage and conventional tillage, and the improvement of these characteristics has been limited even at this time. Overall, from the point of view of soil protection, the results of this experiment clearly show the superiority of conservation tillage methods compared to conventional tillage methods. Considering that the purposes of sustainable agriculture are to produce optimal yields while maintaining the structure of the environment and minimizing the negative consequences of agricultural activities, and the lack of organic matter and its consequences is one of the main problems in sustainable agriculture, the implementation of conservation tillage and management of plant residues that It is one of the main elements of production in agriculture. By improving the quality of the soil, it will increase productivity in production.
6. Acknowledgement
We would like to thank the Research and Technology Vice-Chancellor of Shahid Chamran University of Ahvaz for funding this research, which is part of the research contract SCU.AA1400.309.
Research Article
Adel Neisi; mostafa chorom; heidar ghafari; jafar alekasir
Abstract
Introduction
Sugarcane (Saccharum officinarum L.) is a perennial plant belonging to the cereal family. It is a significant agricultural crop that is widely cultivated in various tropical and subtropical regions around the world. Phenological growth cycles of sugarcane cause changes in the plant's ...
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Introduction
Sugarcane (Saccharum officinarum L.) is a perennial plant belonging to the cereal family. It is a significant agricultural crop that is widely cultivated in various tropical and subtropical regions around the world. Phenological growth cycles of sugarcane cause changes in the plant's nutritional requirements, so recognizing this requires a complete knowledge of the plant's growth stages and the decomposition of soil and leaves of plants in the growth stages. The availability of nutrients required by the plant during the growth stages of the plant is one of the key points of normal plant growth, therefore, plant nutrition management plays a significant role in achieving optimal performance. Considering these changes, the leaf analysis and diagnosis method can prevent the limitations caused by plant nutritional disorders and the optimal use of fertilizers required in sugarcane cultivation. The multiple nutrient detection (CND) method is one of the appropriate methods in interpreting the results of plant nutrient analysis, nutrient requirements and nutritional balance status in plants. Performing leaf sample analysis is an effective approach to monitor and assess the nutritional status of sugarcane. Given that sugarcane may have a multi-year cycle, this method provides a reliable indicator for assessing the nutritional needs of the crop during its cultivation period. One of the effective methods for assessing nutritional limitations in sugarcane is through the combined nutrient detection (CND) method. This method offers the advantage of quickly providing up-to-date standards and allows the identification of specific nutrients responsible for nutritional imbalances that may lead to reduced productivity. In addition, it allows the detection of limitations due to deficiencies and excesses, which are indicated by negative and positive indices, respectively. The aim of this study is to determine the order of limitation of nitrogen, phosphorus, potassium, calcium, magnesium, copper, iron, manganese and zinc by the multiple nutrient detection method CND in sugarcane plant commercial variety CP69-1062 of Ratoon farms. In the northern Khuzestan farms that can produce better sugarcane, they limit themselves in terms of nutrition.
Materials and methods
The present study was conducted in Ratoon sugarcane fields in the Shuaibih area of Imam Khomeini sugarcane cultivation and industry. The objective was to investigate the effect of fertilization management and evaluate the balance of nutrients in the sugarcane plant of the commercial variety CP69-1062 of Ratoon Farms. To this end, 25 farms were selected in the 1402-1403 crop year. The concentrations of nitrogen, phosphorus, potassium, calcium, magnesium, iron, manganese, zinc and copper were determined in the leaves of the sugarcane plants. Once the harvest season had concluded, the yield of each field was calculated. The intermediate yield, obtained using the Khayari method, allowed the farms to be divided into two groups based on whether the yield was favorable or unfavorable. Subsequently, CND reference numbers, CND nutrient index and nutrient balance index (r²) were calculated. The nutrient balance index (r²) was calculated using the Keith-Nielson method, based on the Chi-square statistical distribution function (K²) in Excel software.
Results and Discussion
The results of the cumulative distribution function of the variance of nutrients, with an intermediate yield of 99 tons per hectare, indicate that 52% of the studied ratoon sugarcane farms were in the high yield group and 48% were in the low yield group. After solving the equations of the cumulative function of the third order of the studied nutrients, the nutrient balance index values was found to fall within the range of (2.62 to 20.58) in the optimal performance group, with an average value of 109.28 tons per hectare. The highest value of this index (r2 = 199.95) was observed in the Raton sugarcane field, with a yield of 73.08 tons per hectare. The CND reference numbers of the evaluated nutrients and remaining compounds are as follows: V*N= 2.87, V*P= 1.04, V*K= 2.64, V *Ca =1.95, V*Mg =1.29, V*Fe = -1.75, V*Mn = -3.35, V*Zn = -4.72, V*Cu = -3. 92, and V*Rd = 4.13. The index of CND nutrients showed that copper and iron had the highest negative index among micronutrients in the group of low-yielding ratoon sugarcane fields. The presence of calcareous conditions in the soil of the studied fields can be one of the reasons for this observation.
Conclusion
The CND nutrient balance index (r2) was positive, especially in low-yielding ratoon sugarcane fields, and much higher than its value in high-yielding fields, which indicates nutritional imbalance in these fields. Proper management and balanced use of fertilizers should be considered. It can improve yield and growth cycle of sugarcane.
Research Article
shokrollah asghari; Kimia Heidari; Mahsa Hasanpour Kashani; Hossain Shahab Arkhazloo
Abstract
Introduction
The study of soil mean weight diameter (MWD) of wet aggregates, important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to ...
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Introduction
The study of soil mean weight diameter (MWD) of wet aggregates, important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to generate helpful information required for the soil health assessment to save time and cost involved in soil analysis. Therefore, it is useful to use of different models such as multiple linear regression (MLR) and intelligent models including artificial neural network (ANN) and gene expression programming (GEP) to estimate MWD of wet aggregates through easily accessible and low-cost soil properties. The objectives of this study were (1) to creating MLR, ANN and GEP models for predicting MWD from the easily measurable soil variables in forest, range and cultivated lands of the Fandoghloo region of Ardabil province (2) to compare the precision of the mentioned models in the prediction of MWD of wet aggregates using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria.
Materials and methods Disturbed and undisturbed soil samples (n= 80) were nearly systematically taken from 0-10 cm depth with nearly 50 m distance in forest (n= 20), range (n= 23) and cultivated (n= 37) lands of the Fandoghloo region of Ardabil province, Iran (lat 38° 24' 10" to 38° 24' 25" N, long 48° 32' 45" to 48° 33' 5" E) at summer 2023. The contents of sand, silt, clay, CaCO3, pH, EC, bulk (BD) and particle (PD) density, organic carbon (OC), geometric mean diameter (GMD) of dry aggregates were determined in the laboratory using standard methods. Total porosity (n) was calculated using BD and PD data (n= 1-BD/PD). The mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles were computed by sand, silt and clay percentages. The mean weight diameter (MWD) of wet aggregates was measured in the aggregates smaller than 4.75 mm by wet sieving equipment using sieves with 2, 1, 0.5, 0.25 and 0.106 mm pore diameter. All data were randomly divided into two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with the stepwise method, MATLAB and Gene Xpro Tools 4.0 software were used to derive multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) models, respectively. A feed forward three-layer (9, 8, 6 and 6 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the ANN modeling. A set of optimal parameters were chosen before developing a best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The precision of MLR, ANN and GEP models in predicting MWD of wet aggregates were evaluated by the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics.
Results and discussion The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (3 to 42.18 %), OC (1.01 to 7.17 %), PD (2.00 to 2.67 g cm-3), n (0.39 to 0.87 cm3 cm-3), GMD of dry aggregates (0.8 to 1.33 mm) and MWD of wet aggregates (0.35 to 2.65 mm) showed good variations in the soils of the studied region. The studied soils had clay loam (n= 11), sandy clay loam (n= 6), sandy loam (n= 12), loam (n= 13), silty clay loam (n= 14), silty clay (n= 1) and silt loam (n= 23) textural classes. There were found significant correlations between MWD with OC (r= 0.67**), sand (r= 0.70**), GMD (r= 0.30**) and PD (r=- 0.46**). Also, it was found significant and positive correlation between OC and sand (r= 0.59**). Due to the multicollinearity of sand with dg (r= 0.87**), we did not use the dg as an input variable to estimate MWD of wet aggregates. Generally, four MLR, ANN and GEP models were constructed to predict MWD of wet aggregates from measured readily available soil variables. The results of MLR, ANN and GEP models indicated that the most suitable variables to estimate MWD of wet aggregates were sand, OC and GMD of dry aggregates. The values of R2, RMSE, ME and NS criteria were obtained equal 0.52, 0.48 mm, 0.13 mm and 0.48, and 0.85, 0.30 mm, 0.03 mm and 0.78, 0.79, 0.35 mm, - 0.10 mm, 0.95 for the best MLR, ANN and GEP models in the testing data set, respectively. Many researchers also reported that there is a positive and significant correlation between MWD of wet aggregates and OC.
Conclusion The results showed that sand, OC and GMD of dry aggregates were the most important and readily available soil variables to predict the mean weight diameter (MWD) of wet aggregates in the Fandoghloo region of Ardabil province. According to the lowest values of RMSE and the highest values of R2 and NS, the precision of ANN models to predict MWD of wet aggregates was more than MLR and GEP models in this study. Because ANN is more flexible and effectively captures non-linear relationships, it performed better than the other models in predicting MWD.
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