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Donya Parmah; Hamid Reza Chaghazardi; Farzad Mondani; Ali Beheshti Al Agha; Daniel Kehrizi
Abstract
IntroductionOptimum yield production in rainfed cultivation directly depends on the amount of rainfall and moisture storage in the soil. The tillage system directly affects the moisture storage and the physical and chemical properties of the soil, and choosing the right tillage system affects the yield ...
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IntroductionOptimum yield production in rainfed cultivation directly depends on the amount of rainfall and moisture storage in the soil. The tillage system directly affects the moisture storage and the physical and chemical properties of the soil, and choosing the right tillage system affects the yield of the product. Oilseeds are particularly important among crops, forming the second-largest food reserves in the world after grains. These products are rich in fatty acids. Today, the oil extraction and production industry is one of the most strategic industries in most countries. Iran has vast arable lands and favorable fields for cultivating oilseeds. Still, according to the available statistics, more than 80% of the country's required oil is supplied from abroad. Considering that our country needs more and better quality oil products on the one hand, and the other hand, is involved in climate issues and problems such as consecutive droughts, it seems that the cultivation and development of plants with fewer water requirements and high resistance and providing management methods and appropriate fertilizer in line with conservation agriculture is a suitable solution to increase crop yields and maintain and increase soil quality in the long term. For this purpose and considering the value of oilseed cultivation, an experiment was conducted to investigate the effect of tillage and fertilization on the yield and components of safflower yield in rainy conditions.Materials and Methods The experiment was carried out as split plots in a basic design of random complete blocks, with three replications in rainfed conditions. The treatments included tillage systems (conventional tillage, reduced tillage, and no-tillage) as the main factor and NPK fertilizer (a mixture of urea, triple superphosphate, and potassium sulfate) at four levels of zero, 33, 66, and 100% as a secondary factor. Potassium and phosphorus fertilization and 50% of nitrogen fertilizer were used at the same time as planting, and the remaining 50% of nitrogen fertilizer was used four months after planting. Each block had three main plots; the distance between each block was 3 meters, and between the main plots was 2 meters. In each main plot, four sub-plots were created, and the distance between the sub-plots was 1 meter. The area of the main plots was 21 × 15 meters, and the area of each sub-plot was 4.5 ×15 meters. The amount of seed used for safflower was 25 kg per hectare. The safflower seeds were sown in 5 rows and planted at a distance of 50 cm and a distance between plants of 10 cm. In all the stages of planting, holding, and harvesting, all agricultural management was carried out based on the traditional management of the studied area and in the farmer's way. The final sampling or harvesting was done manually in the physiological treatment stage. Before analyzing the variance of the data, the normality test of the data was performed. In this research, the LSD test was used to compare the mean at the 5% probability level, Excel software was used to draw graphs, and SAS 9.4 software was used to analyze the data.Results and Discussion The research showed that the traits examined, including leaf area index, dry matter content, thousand seed weight, seed yield, and biological yield, were affected by the tillage system, fertilizer, and their interaction effect. The highest safflower seed yield of 195.6 g/m2 was obtained from the fertilizer ratio of 33% and conventional tillage, and the lowest seed yield of 116.2 g/m2 was obtained from no-tillage and no fertilizer use. The results showed that the conventional tillage system had better results than low-tillage and no-tillage. The results showed that in reduced tillage and no-tillage, the changing trend of safflower plant leaf area index was not much different, and only in safflower, the 100% fertilizer ratio in reduced tillage had a more significant effect than no tillage. Also in the condition of no fertilizer use in no-tillage, the leaf area index was lower. The use of fertilizer increased the biological yield of the plant, but the effect of this use in conventional tillage was higher than in reduced tillage and no-tillage. Consumption of 33% of the fertilizer required by the plant under conventional tillage conditions caused the highest biological yield in the safflower plant. So, the biological performance of safflower increased by 94% compared to the control.Conclusions In most of the examined traits, the application of 33 and 66% of the fertilizer requirement caused the best results, and the 100% fertilizer ratio left adverse effects, which indicates the lower fertilizer requirement of this cultivar in the studied conditions compared to cultivars in other regions. Since the research was conducted in rainy years, conventional tillage was better than low tillage. It is suggested that this plant's production amount be evaluated under different irrigation conditions and moisture limitations so that tillage systems and management methods can be examined and selected more carefully.
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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.
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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.
