Soil science
A. Ansori Savari; , M. Nabipour; M. Farzaneh
Abstract
IntroductionThe high water demand of sugarcane in arid and semi-arid regions, combined with declining rainfall, has led to increased use of drainage water as a strategy for sustainable production management. It has been estimated that 20% of all cultivated land and 33% of irrigated agricultural land ...
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IntroductionThe high water demand of sugarcane in arid and semi-arid regions, combined with declining rainfall, has led to increased use of drainage water as a strategy for sustainable production management. It has been estimated that 20% of all cultivated land and 33% of irrigated agricultural land are affected by high salinity. Salinity stress poses two main threats to plants: ionic toxicity and osmotic stress. Ionic toxicity occurs when there is a significant accumulation of Na⁺ in plant leaves under saline conditions. This disrupts the balance of water and ions, damages organelle structures, inhibits growth, and can ultimately lead to plant death. Some studies have shown that ion toxicity caused by Na+ can inflict more irreversible damage on plants than osmotic stress. Silicon application (Si) showed improved photosynthetic efficiency, growth, and yield compared to plants under salt stress. Previous studies have also shown that silicon treatments can increase salinity tolerance in various plants, including wheat, corn, rice, and canola. However, the extent of silicon-mediated benefits under salinity can vary greatly between species and is largely dependent on the plant's capacity for element uptake dictated by its genetic makeup. There is limited information regarding the use of drainage water in sugarcane irrigation management in arid and semi-arid regions, as well as the potential for improving salinity stress through silicon application. Therefore, this study was conducted to evaluate the effects of Si on two sugarcane varieties irrigated with salt water. Materials and MethodsThe pot experiment was conducted in a greenhouse under natural light at the agricultural site of Sugarcane Dehkhoda Company in Khuzestan Province, Iran, in 2021-2022. The temperature and humidity percentages are indicated in Figure 1. This study was carried out as split-split plot design based on randomized Block design (RBD). The main plot factors included three levels of salinity: control of 1.4±0.2 dS.m-1 (S0) from the river water source, salinity stress of 4.1±0.2 dS.m-1 (S1), and salinity stress of 8.2±0.2 dS.m-1 (S2) from the drain water source, with a sub-factor of variety treatment (CP73-21 and CP69-1062). The silicon application timing was also considered as a sub-factor, with four levels: Si0, non-silicon application (Control); Si1, one month before salinity stress; Si2, during salinity stress; and Si3, after 30 days of salt stress, silicon was applied. The sugarcane sprouts are grown in polyethylene pots 100 cm in height and 45 cm in width. Each pot contained 100 kg of soil. A total of 216 experimental units were used during the experiment. The experimental pots were filled with a mixture of field soil and sugarcane filter cake in a 3:1 ratio. The results of the chemical analysis of field soil and filter cake are presented in Table 2. The salt stress was applied 113 days after growing cuttings and continued until harvest. Results and DiscussionThe results of the first year showed that salt stress significantly reduced the height of the sugarcane stalk. Also, at the salinity stress levels of 4.1 and 8.2 dS/m, the SPAD index decreased by 22.3% and 27%, respectively. Additionally, leaf sheath moisture dropped by 6.4% and 11.8%, electrolyte leakage increased by 11% and 22.7%, and the photosynthesis rate decreased by 28% and 42% compared to the control treatment. The optimal time to apply silicone fertilizer was one month prior to the onset of stress, which resulted in a significant improvement in all studied traits at salinity stress levels of 1.4 dS/m (control) and 4.1 dS/m. Furthermore, the qualitative analysis of sugarcane syrup in the second year revealed a decrease in sucrose percentage (14.1% and 33.5%, respectively) and white sugar content (12.6% and 40.9%, respectively) at salinity stress levels of 4.1 and 8.2 dS/m. The photosynthesis rate of sugarcane leaves decreased by 28.3 to 41.8 percent under salt stress levels of 4.1 and 8.2 dS, respectively. The CP69-1062 variety exhibited a better response compared to the CP73-21 variety, showing relative superiority in all growth and physiological traits studied. Conclusion The results also indicated that the optimal time to apply silicon fertilizer to sugarcane plants was one month before the onset of stress, resulting in a significant improvement in all studied traits. The application of silicon fertilizer led to a 1 percent increase in sucrose, 3.7 percent increase in syrup purity, and 3 percent increase in white sugar yield compared to no application. Acknowledgments We would like to express our special thanks to the Faculty of Agriculture, Shahid Chamran University of Ahvaz for the financial support (Grant number SCU.AA98.336).
E. Karamian; M. Navabian; M.H. Biglouei; M. Rabiee
Abstract
IntroductionMany agricultural lands in Guilan province of Iran, especially paddy fields, remain uncultivated in the second half of the year due to various reasons including heavy rainfall, low soil permeability (stickiness of soil particles) and inefficiency of the existing drains. Mole drainage as a ...
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IntroductionMany agricultural lands in Guilan province of Iran, especially paddy fields, remain uncultivated in the second half of the year due to various reasons including heavy rainfall, low soil permeability (stickiness of soil particles) and inefficiency of the existing drains. Mole drainage as a low-cost drainage method, proportion for rice cultivation conditions and easier to implement than pipe drainage, can be a suitable solution in the development of second cropping. Due to the oil content of 40% of the seed, the rapeseed plant is one of the valuable oil plants and has the ability to be cultivated as a second crop in paddy fields. Nitrogen plays a key role in the performance of plants and its deficiency causes limitations in plant production. Equipping paddy fields with mole drains along with the application of appropriate level of nitrogen fertilizer can increase the quantitative and qualitative yield of rapeseed as a second crop and contribute to the food security of the country. Therefore, the development of the cultivated area of rapeseed in paddy fields after rice harvesting in Rasht region, the study of the combined effect of mole drainage and different levels of nitrogen fertilizer on yield and yield components were the aims of this project. Materials and MethodsIn order to investigate the effects of mole drainage and nitrogen fertilizer on the yield and yield components of rapeseed as a second crop in Rasht rice fields, a factorial layout based on a randomized complete block design with three replications at the research field of the Faculty of Agricultural Sciences of Guilan University was implemented in the crop year of 2022-2023. The factors included mole drainage at three levels (without drainage, without gravel and with gravel) as D0, D1 and D2 respectively, and nitrogen fertilizer as urea source at two levels (180 and 240 kg ha-1) as N1 and N2 respectively. Rapeseed plant (Brassica napus) of Delgan cultivar was selected as the second crop after rice harvest. To carry out the experiment, at first the desired land was blocked and divided into plots, then the underground drains of mole were created without gravel and with gravel with a special blade in the desired plots. To drain the drainage from the mole drains, the polyca pipe was installed at the end of each mole tunnel, then the other side of polyca pipe was connected to the sub-pipe collection and finally led to the main surface drain. This experiment was conducted in 18 plots and each one was 9 × 6 meters. The distance between plots was 1.5 m, between replications was two meters, and the distance between plants was 15 and between rows was 25 cm. To avoid the effectiveness of drainage treatments from undrained treatments, undrained plots were considered at the end of the field. Before cultivation, basic chemical fertilizers, 200 kgha-1 of potassium from potassium sulfate source and 200 kgha-1 of phosphorus from ammonium phosphate source were applied. Nitrogen fertilizer from urea source was applied at the level of 180 and 240 kgha-1 in equal amount at three stages. Just before the harvest stage, to determine the traits of the number of seed in the pods of sub-branches, the number of seed per pod, the weight of seed in sub-branches, the weight of seed in the main branch and the weight of seed per plant, ten plants were randomly selected and harvested manually from the crown area. Also, to determine the seed yield, one square meter was randomly selected from each plot, taking into account the borders, and the bushes were manually harvested from the crown area. After the moisture content of the seeds reached the desired level, the seeds were separated from the pods and weighed using a laboratory scale with an accuracy of one thousandth of a gram, and the seed yield was calculated in kgha-1. SOXTEC SYSTEM HT 1043 Extraction Unit set was used to determine oil percentage and Kjeldahl set was used to determine seed protein. Statistical analysis of the data was done using SAS software (version 9.4) and comparison of means was done using the minimum significant difference test at 5% probability level. Excel software was used to draw the graphs. Results and DiscussionThe results of variance analysis of the data showed that the interaction effects of mole drainage and nitrogen fertilizer on the traits of seed weight in the main branches, seed weight in the plant and seed yield was significant at 5% probability level, so that the highest seed weight in the main branch with 0.733 seeds in the mole drainage with gravel with a nitrogen fertilizer level of 180 kgha-1 (D2×N1) treatment was obtained and the highest seed weight in the plant with 1.443 g in the mole drainage without gravel with a nitrogen fertilizer level of 240 kgha-1 (D1×N2) treatment was obtained. Also, the highest seed yield was obtained under 3579.48 kgha-1 in the treatment of mole drainage without gravel using 240 kgha-1 of fertilizer (D1×N2) which is compared to the treatment of without drainage and drainage with gravel with the same level of fertilizer 13.63 and 2.31 percentage was higher, respectively. In addition, rapeseed plant is more important in terms of oil percentage, no significant difference was observed between drainage and nitrogen fertilizer treatments in terms of average oil percentage. Therefore, the mole drainage treatment without gravel with a fertilizer level of 240 kgha-1 (D1×N2) is the most suitable option for rapeseed cultivation as the second crop after rice harvesting. ConclusionThe results of this study showed that mole drainage without gravel by improving soil ventilation conditions and preventing waterlogging of paddy fields along with the level of nitrogen fertilizer of 240 kgha-1 increased the yield of rapeseed compared to the condition of without drainage at the same level of nitrogen fertilizer. Therefore, rapeseed cultivation in vast paddy fields after rice harvesting can be recommended as a basic solution in order to increase the production of oilseeds and provide part of the country's oil consumption.
M. Abiyat; M. Abiyat; M. Abiyat
Abstract
Introduction Agriculture is the essential sector for promoting food security. Crop area estimation (CAE) can meet the requirements of the crop monitoring plan. The organizing basis of the cultivation pattern is recognizing the types of crops and examining the condition of their crop area. Shush ...
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Introduction Agriculture is the essential sector for promoting food security. Crop area estimation (CAE) can meet the requirements of the crop monitoring plan. The organizing basis of the cultivation pattern is recognizing the types of crops and examining the condition of their crop area. Shush county in Khuzestan Province has 300,000 hectares of the crop area. It is one of the agricultural hubs of Iran because it has a record annual production of more than two million tons of strategic crops such as wheat, sugar beet, and corn. CAE affects the amount of net production and shortage or surplus of produce for market steadiness. Traditional approaches for CAE are time-consuming and costly and are not widely enforceable. Remote sensing (RS) data provide good information for decision-makers by determining the crop type and the crop area. RS data has made it possible to avoid continuous reference to agricultural lands with less time and cost than another usual method and accurate CAE. Also, the use of multi-time images during the growing season of agricultural products allows the use of spectral curves when related to the crop calendar of each crop. This spectral curve is almost separate for each product and increases the ability to distinguish between products. Therefore, multi-temporal images support segregation based on multispectral images of products. The current study follows a speedy method with appropriate accuracy established on satellite image classification algorithms and spectral indices to identify and separate crops with RS data in Shush County.Materials and Methods Landsat-8 data with path/row coordinates 166/38 extracted from the USGS website were used to identify and separate the cultivated lands of the region. The reason for choosing Landsat images is the relatively suitable temporal and spatial resolution, availability, and the appropriate time distribution with the product growth period. The Landsat 8 carries 2-sensors, OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor). The OLI sensor with a spatial resolution of 30 meters has 8-bands in the visible spectrum, near-infrared (NIR), short-wavelength infrared (SWIR), and a panchromatic band with a spatial resolution of 15 meters. The TIRS sensor can record thermal infrared radiation with a spatial resolution of 100 meters with the help of 2-bands in atmospheric windows of 10.6 to 11.2 micrometers for band 10 and 11.5 to 12.5 micrometers for band 11. This research used bands 1-7 of the Landsat-8 OLI sensor with a spatial resolution of 30 meters after the initial corrections of satellite images. The spectral similarity between the region's dominant crops has made it impossible to select a single image to differentiate and extract the cultivation pattern. Wheat and barley have a high spectral similarity. The peak of the greenness of these products is in the first four months of the year, which has high NDVI values at this time. Therefore, choosing a good time to separate the crops was feasible by referring to the Khuzestan Organization Agriculture-Jihad (KOAJ) and receiving the regional crops calendar in 2018-19. Then, the low-level cloud cover images on April 24, June 27, and August 30, 2019, were selected for classification based on the crop calendar. Planting, harvesting, maximum greenness, and ripening information of the dominant crops in the area were pivotal in obtaining image dates. In dates selected related to the images were considered planting, harvesting, maximum greenery, and ripening information of the region's dominant crops.Results and Discussion According to the results, from total crop area in Shush county (163313.7 hectares) is allocated about 103513.2 hectares (63.4% of the county's crop area) to the ANN, about 102875.1 hectares (63.0% of the county's crop area) to the SVM, and about 102,277.3 hectares (62.6% of the county's crop area) to the NDVI, which in comparison with the KOAJ statistics, has an error of 0.11, 6.2 and 1.8%, respectively.This difference is the similarity of the reflective spectrum in some places, which affects the separability and recognition of phenomena and increases the error in estimating the area under cultivation of different crops. The highest and lowest errors in estimating the area under cultivation in the artificial neural network method were in barley and rice crops, respectively, in the support vector machine method were in wheat and rice crops, respectively, and in NDVI index were in wheat and barley crops, respectively. The difference between the cropped area obtained from classification methods and NDVI index with cropped area statistics of Agricultural-Jihad Organization may be due to the following: First, the cultivation history of different has caused problems such as reflections of diverse agricultural lands in one image. Second, the agricultural lands in this area are small. Most of them are under one hectare. Also, the crops in this area are diverse. Third, the smallest region that the image used in the present study can distinguish is about 900 square meters, which is a large number for the agricultural lands of the study area and causes errors.Conclusion The study results showed that the support vector machine method had the lowest error in CAE than the artificial neural network method, which indicates the higher accuracy of the support vector method in identifying and separating crops in the region. Comparing the area obtained from the NDVI index with the statistics of the Agricultural-Jihad Organization of Khuzestan province and evaluating the accuracy of this method indicated the higher efficiency of spectral indices in CAE for the region compared to classification methods. The NDVI index minimizes the error values of the results due to having a threshold and better identification of vegetation density. Therefore, based on the accuracy assessment results and comparing the cropped area with the KOAJ statistics, the utilization of the NDVI index provides the best CAE in the region.
